research gap of time management

College Students’ Time Management: a Self-Regulated Learning Perspective

• Review Article
• Published: 27 October 2020
• Volume 33 , pages 1319–1351, ( 2021 )

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• Christopher A. Wolters   ORCID: orcid.org/0000-0002-8406-038X 1 &
• Anna C. Brady 1  

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Despite its recognized importance for academic success, much of the research investigating time management has proceeded without regard to a comprehensive theoretical model for understanding its connections to students’ engagement, learning, or achievement. Our central argument is that self-regulated learning provides the rich conceptual framework necessary for understanding college students’ time management and for guiding research examining its relationship to their academic success. We advance this larger purpose through four major sections. We begin by describing work supporting the significance of time management within post-secondary contexts. Next, we review the limited empirical findings linking time management and the motivational and strategic processes viewed as central to self-regulated learning. We then evaluate conceptual ties between time management and processes critical to the forethought, performance, and post-performance phases of self-regulated learning. Finally, we discuss commonalities in the antecedents and contextual determinants of self-regulated learning and time management. Throughout these sections, we identify avenues of research that would contribute to a greater understanding of time management and its fit within the framework of self-regulated learning. Together, these efforts demonstrate that time management is a significant self-regulatory process through which students actively manage when and for how long they engage in the activities deemed necessary for reaching their academic goals.

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Wolters, C.A., Brady, A.C. College Students’ Time Management: a Self-Regulated Learning Perspective. Educ Psychol Rev 33 , 1319–1351 (2021). https://doi.org/10.1007/s10648-020-09519-z

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ORIGINAL RESEARCH article

Positive time use: a missing link between time perspective, time management, and well-being.

• 1 LINP2, University of Paris Nanterre, Nanterre, France
• 2 International Laboratory of Positive Psychology of Personality and Motivation, HSE University, Moscow, Russia
• 3 School of Psychology, University of East London, London, United Kingdom
• 4 Positran, Épone, France

Introduction: The notion of satisfaction with the use of one’s time has not been operationalized previously. Based on qualitative interviews, we propose a concept of positive time use comprised by four components: self-congruence of daily activities, balance between activities, efficient use of time, and a sense of mastery over one’s time.

Methods: Using data from two UK adult samples ( N  = 173 and N  = 357), we developed a new measure, Positive Time Use Inventory (PTUI), and investigated its structural and convergent validity.

Results and discussion: The associations of positive time use with balanced time perspective, affect balance, satisfaction with life, sense of coherence, and self-reported satisfaction with time use indicate convergent and discriminant validity of the new measure. Positive time use partially explained the associations of balanced time perspective with subjective well-being and fully mediated the effects of future time perspective and time management on subjective well-being. We propose positive time use as a new model of temporal well-being, which brings together the notions of work-life balance, time efficiency, and time mastery in a single comprehensive framework, helping to inform the time management coaching interventions.

Introduction

The twenty-first century has been marked by a renewed interest in human well-being and the development of positive psychology, a scientific study of the things that make life worth living. However, within this rapidly growing field, there has been very little work focused on the positive aspects of our relationship with time, one of the fundamental conditions of human existence.

In this paper, we propose a positive psychological model of time use informed by existing theory and by qualitative studies of time use satisfaction. The model describes four phenomenological criteria of positive use of time that entails a combination of efficiency and fulfillment in one’s daily life: self-congruence and balance of activities, as well as efficiency and a sense of mastery with respect to time. We also present two empirical studies aimed to develop and refine a self-report measure of positive time use that could benefit researchers and practitioners interested in exploring the humans’ relationship with time.

The problem of time pressure

Time is a basic dimension of our lives: we live in a world of time, where the present evolves from the past and becomes the future ( Boss, 1963 ). Whether we are aware of it or not, time keeps passing; after all, life is only the amount of time each of us has at our disposal. Even though the very passage of time is outside our control, we normally have a choice concerning the activities, people, and things that we devote our time to. Time appears as a limited resource that we continuously consciously or unconsciously distribute between the numerous activities that comprise our life and compete for our attention. Like money, time has a zero-sum character ( Robinson, 2002 ): by spending it on one thing we inevitably spend less time on another, and we continuously face the experience of not having enough time ( Mogilner et al., 2018 ).

Concepts such as “time famine” ( Banks, 1983 ; Perlow, 1999 ), “time crunch” ( Robinson and Godbey, 1997 ), “time poverty” ( DeGraaf, 2003 ), and “time pressure” ( Goodin et al., 2005 ) have become all too familiar. Chronic time pressure has been recognized as an “unavoidable experience of daily life in highly industrialized societies” ( Szollos, 2009 , 345) and conceptualized as a combination of an objective time shortage and a subjective experience of being rushed. Despite the advances in technology that enable us to do things faster and to multitask, thus using our time more “efficiently” in terms of how much we manage to accomplish in an average day, people’s subjective experience of time pressure does not seem to improve ( Newport, 2015 ). Although the objective amount of work hours has declined over the past century, paradoxically, people nowadays feel they have less time to spare ( Robinson and Godbey, 1997 ; Pentland et al., 1999 ; Sullivan and Gershuny, 2001 ). This may be explained by the time use choices people make and the extent to which they feel in control of their time ( Goodin et al., 2005 , 2008 ).

Time management programs aimed at optimizing one’s time use have gained popularity in recent decades. The limited existing research evidence suggests that although these programs may increase participants’ subjective feelings of control over their time and relieve time pressure and stress, the evidence concerning their impact on participants’ actual performance and well-being is mixed, at best ( Claessens et al., 2007 ; Aeon and Aguinis, 2017 ). Indeed, while intensive time management may free up some time by squeezing an extra hour or two out of each day, it may also result in “time deepening,” cramming a larger number of activities into a shorter amount of time, leading to negative experiences of time fragmentation, time strain, and being rushed ( Robinson and Godbey, 1997 ).

And having more time to spare does not always make people happier either. Despite an objective trend reflecting an increase in leisure time between 1965 and 2005, the proportion of time Americans spent doing pleasant vs. unpleasant activities has remained nearly the same ( Krueger et al., 2009 ). Even though weekly workload and the amount of free time do predict time pressure and feeling stressed, their associations with satisfaction with the use of time are quite weak ( Roberts, 2007 ; Zuzanek, 2017 ), suggesting that people may be satisfied with their use of time even when they have very little time to spare. Though recent findings show that people who spend money to buy more time do indeed experience greater satisfaction ( Whillans et al., 2017 ), the reason is probably related to why people value time and what they use it for ( Whillans and Dunn, 2019 ).

It seems that the time crunch problem cannot be solved by simply increasing the amount of time available to individuals or by giving them tools to manage it more efficiently. It is not having more time, but having more satisfying time that people seem to need. But what is positive time use and what it is that helps people to experience time as spent well?

Having a “good” time vs. using one’s time well

One way to answer the question of a “good” time is to equate it with pleasant time. Within this paradigm, “good” time use can be defined as spending time in activities that bring positive momentary emotional experiences or receive a retrospective positive evaluation. This approach can be labeled hedonic and it has laid the ground for a number of well-known time use studies relying on subjective indicators, such as the U-Index ( Kahneman and Krueger, 2006 ; Krueger et al., 2009 ). However, eudaimonic well-being research shows that experiences bringing momentary pleasure may not necessarily be satisfying in the long term ( Vittersø, 2013 , 2016 ; Waterman, 2013 ).

From the time management point of view, “good” time use can be defined as efficient time use, that is, objectively, absence of procrastination and time-wasting, and, subjectively, a sense of control over one’s time and absence of time poverty and time stress, having “enough” time. Research shows that the experience of time scarcity or time poverty is associated with engaging in inefficient time management behaviors ( Kaufman-Scarborough and Lindquist, 2003 ) and also with lower subjective well-being ( Kasser and Sheldon, 2009 ). However, the subjective notion of having “enough” time can hardly be defined without specifying what it is that the time is needed for and why .

Both of these approaches to defining positive time use (as either “satisfying” or “efficient”) seem incomplete. People who typically spend time on enjoyable activities may fail to achieve important life goals and face disappointment in the long term. On the other hand, people who are highly efficient in their use of time may eventually face burnout and depression in case their daily activities fail to bring them lasting fulfillment ( Längle, 2003 ). Curiously, time management literature, with few exceptions ( Black and Bailey, 2006 ), has remained silent about the necessity to like (at least, to some extent) the activities that a person aims to fit into their day. We believe that the definition of positive time use needs to combine and transcend these two, rather simplistic, perspectives, by addressing the question of when and why do activities bring lasting satisfaction.

The answer is provided by the theory of basic psychological needs, a part of Self-Determination Theory (SDT) postulating that satisfaction of the needs for autonomy, competence, and relatedness is essential for positive human functioning ( Ryan and Deci, 2017 ). Within the time use field, Kasser (2009) has introduced the concept of time affluence, an opposite of time poverty, defined as having enough time for activities and experiences that sustain psychological well-being by satisfying the basic psychological needs described in SDT. Christiansen and Matuska proposed a theory of a balanced lifestyle, viewing it as one that helps to meet psychological needs (including, but not limited to the needs for autonomy, competence, and relatedness described in SDT, as well as needs for self-esteem, security, purpose, and health) and is satisfying, healthful, meaningful, and sustainable ( Christiansen and Matuska, 2006 ; Matuska and Christiansen, 2008 ). Matuska (2010 , 2012a , b) operationalized life balance as congruence between desired and actual time spent in activities and equivalence of the degree of discrepancy between the two across various life domains.

Sheldon et al. (2010) provide an extensive critique of this model and propose a two-pronged definition of optimal life balance, viewing it as a distribution of time across activities in various life domains that is objectively equitable (close to uniform) and is also subjectively congruent with one’s ideal time-use profile. In a series of empirical studies using cross-sectional, longitudinal, and experimental designs in two cultures, they found that although the indices operationalizing the subjective and objective balance were only weakly correlated, both predicted well-being and this effect was mediated by the satisfaction of SDT’s basic psychological needs.

Recently, based on a combined body of empirical findings, Sheldon and colleagues have proposed the Eudaimonic Activity Model (EAM) ( Sheldon, 2013 ; Martela and Sheldon, 2019 ; Sheldon and Lyubomirsky, 2021 ). According to the EAM, basic psychological need satisfaction (“feeling well”) is an outcome of eudaimonic activities (“doing well”) directed at goals that fit the person and are experienced as personally meaningful, valuable, and concordant with the self. Based on these ideas, positive time use can be defined as using time efficiently and distributing it in a balanced way across activities directed at personally meaningful goals that satisfy basic psychological needs and bring a lasting sense of fulfillment.

The model of positive time use: a conceptual framework

A first attempt to define “good” time use was made by the second author ( Boniwell, 2005 , 2006 ) in her qualitative interview study of time use satisfaction and well-being. She interviewed 22 participants, half of whom were largely satisfied and another half largely dissatisfied with their use of time. Using Interpretative Phenomenological Analysis, she identified 148 emergent themes grouped into 10 general clusters describing a satisfying use of time (ordered in terms of decreasing frequency): balance and variety of activities, discipline and adaptability, achievement vs. wasting time, taking responsibility and feeling in control, prioritization and acceptance of limits, time anxiety and perspectives on time, liking what one does, life goals and worthwhile activities, time management mechanics, and, finally, reflection and evaluation.

These clusters formed four super-ordinate themes, or facets of perceived time use: Motivation (liking what one does in life and perceiving it as worthwhile), Organization (prioritization resulting in a balance of activities and in having time for oneself), Execution (discipline and responsibility, achieving instead of wasting time), and Evaluation (absence of anxiety and lack of control with respect to time). Based on these phenomenological findings, the second author developed a pool of 69 items tapping into satisfaction with time use and conducted an exploratory factor analysis to investigate its structure, discovering four distinct factors corresponding to the proposed facets ( Boniwell, 2005 , 2006 ). However, the study was limited with respect to both sample and analytic methods.

Building on these early results and on later theorizing, we propose to define positive time use as a multifaceted construct reflected in four phenomenological experiential indicators:

1. Self-congruence of daily activities: an alignment of the things one typically does in everyday life with one’s values, goals, and priorities which results in one’s daily activities being experienced as personally meaningful, important, satisfying, and fulfilling (even if not always pleasant). According to Self-Determination Theory, this experience is an outcome of pursuing goals that satisfy one’s basic psychological needs ( Ryan and Deci, 2017 , 253).

2. Balance between daily activities directed at different goals and life domains. This notion is more general than work-life or work-family balance and refers to a general feeling of satisfaction with the way one distributes one’s time and resources (attention, effort) between the various activities comprising one’s life.

3. Efficiency in the use of time: absence of procrastination and of time experienced as wasted in one’s daily life; efficient organization, initiation, and execution of one’s activities.

4. Control over one’s time or time mastery: absence of time anxiety and time pressure a daily basis, a sense of being “in control” of one’s time, rather than being overwhelmed and guilty.

In short, we define positive time use as both satisfying (due to having a healthy balance between life areas and choosing self-congruent activities on a daily basis) and efficient (both objectively, spending time efficiently, and subjectively, experiencing a sense of mastery over one’s time). Empirically, we expect that these four components or indicators of positive time use are supposed to form a single second-order dimension (Hypothesis 1).

The construct of positive time use overlaps with earlier constructs, such as time affluence ( Kasser, 2009 ), lifestyle balance ( Matuska, 2010 ), and purpose ( Martela and Steger, 2016 ), but it also brings in the notion of efficient time use developed within time management literature ( Bond and Feather, 1988 ). We believe that it may help to fill the gaps and explain the links between some well-studied individual-difference constructs, such as time perspective and time management, on the one hand, and general subjective well-being, on the other hand. In the following sections, we will discuss the antecedents of positive time use.

Antecedents of positive time use: balanced time perspective

Time perspective is an individual’s cognitive way of relating to his/her psychological past, present, and future which affects decision-making and subsequent actions ( Zimbardo and Boyd, 1999 ). Empirical studies have shown that time perspective has a powerful influence on almost all domains of human life and is associated with diverse outcomes, such as educational attainment, somatic and mental health, delinquency and substance abuse, sleep and dreaming patterns, choice of romantic partner, economic behavior, sustainable lifestyle, to name only a few ( Stolarski et al., 2015a ).

A widely adopted empirical model of time perspective was proposed by Zimbardo and is operationalized in the Zimbardo Time Perspective Inventory (ZTPI) ( Zimbardo and Boyd, 1999 ), which measures five distinct dimensions of one’s subjective representation of time: Past-Negative (a focus on past experiences that were aversive, noxious, traumatic, or filled with regret), Past-Positive (a pleasurable, usually sentimental and nostalgic views of one’s past), Present-Hedonistic (living in the present moment, enjoying high-intensity activities, sensation-seeking), Present-Fatalistic (helpless and hopeless attitude toward the future in the face of uncontrollable present), and Future (orientation toward setting and attaining future goals at the expense of present enjoyment, delaying gratification, considering the consequences of one’s actions and decisions). The validity of the ZTPI as a research tool has been confirmed in numerous studies using various behavioral outcomes, such as substance use, risky driving, health risk taking, etc. ( Zimbardo and Boyd, 1999 ; Boniwell and Zimbardo, 2004 , 2015 ). The ZTPI has been translated into more than 25 languages and validated in at least 33 countries ( Sircova et al., 2014 , 2015 ).

Which time perspective is most conducive to well-being? Studies using the ZTPI consistently reveal that individual dimensions of the ZTPI only show weak associations with trait well-being indicators ( Boniwell et al., 2010 ). To address this issue, Zimbardo has proposed the concept of balanced time perspective (BTP), in which “the past, present and future components blend and flexibly engage, depending on a situation’s demands and our needs and values” ( Zimbardo, 2002 , 62). This notion is based on the idea that an excessive orientation toward any single temporal locus (the past, the present or the future) may be detrimental to well-being.

BTP was defined as a combination of high scores on Past-Positive, Present-Hedonistic, and Future dimensions with low scores on Past-Negative and Present-Fatalistic. Studies using various operationalizations of BTP based on the ZTPI have consistently found that BTP is a better predictor of well-being (life satisfaction, affect balance) and positive functioning (optimism, purpose in life), compared to each of the individual time orientations that comprise it ( Drake et al., 2008 ; Boniwell et al., 2010 ; Zhang et al., 2013 ; Stolarski et al., 2015b ).

However, despite the well-confirmed associations of balanced time perspective with well-being, the mechanisms underlying these associations are not quite clear. Are people with a balanced time perspective happier because they perceive past and present in a generally more positive way, or are they happier because they have adopted more flexible and optimal strategies of managing their time and manage to achieve a more optimal time use?

Based on the Positive Time Use model, we propose that individuals with a balanced time perspective are happier because they are likely to choose more satisfying activities and to use their time more efficiently. In short, we expect the associations between balanced time perspective and well-being to be mediated by positive time use (Hypothesis 2).

Antecedents of positive time use: time management behaviors

The issues of time management have enjoyed limited research attention in psychology. Despite the popular appeal of this concept reflected in thousands of self-help books, a 2007 review ( Claessens et al., 2007 ) has only found 35 previous scientific studies, most of which have used one of the three most popular instruments, the Time Management Behavior Scale (TMBS) ( Macan et al., 1990 ), Time Structure Questionnaire (TSQ) ( Bond and Feather, 1988 ), or the Time Management Questionnaire (TMQ) ( Britton and Tesser, 1991 ). Studies using these measures have shown that individuals with higher self-reported time management skills and behaviors tend to estimate the expected time durations more accurately, spend more time on high priority tasks, and are more successful in the academic domain. Time management is positively associated with perceived control of time, job satisfaction, and has a negative relation with job-induced strain and distress; however, its links with job performance were modest, at best ( Claessens et al., 2007 , 2009 ; Eerde, 2015 ).

Despite having a range of empirical instruments, the time management field still lacks theory that would describe how and explain why and whether time management works ( Claessens et al., 2007 ). Macan (1994) suggested that the relationship of time management skills (setting goals and priorities, mechanics of time management, and preference for organization) with their respective outcomes is mediated by perceived control of time. More recent work has pointed out other variables that may play a role, such as team-level effects ( Mohammed and Harrison, 2013 ; Gevers et al., 2016 ). However, there are still important gaps in the literature concerning the personality and motivational antecedents of time management behaviors and its connection to more general well-being outcomes, outside the professional or academic domains ( Claessens et al., 2009 ).

We attempt to contribute to filling these gaps by studying the associations of self-reported time management behaviors, on the one hand, with time perspective, which may explain the individual differences in adoption of time management behaviors and, on the other hand, with positive time use, which may be facilitated by time management practices and explain their effects on well-being.

The Positive Time Use model allows to explore why and how time management works: we expect that time management is only conducive to well-being when it enables people not only to use their time more efficiently, but also to maintain a better balance in life by devoting more time to activities perceived as important and satisfying. In other words, we expect that the associations between time management behaviors and well-being are mediated by positive time use (Hypothesis 3a). At the same time, time management behaviors may be a mechanism underlying the effects of time perspective on positive time use. We expect that time management behaviors mediate the associations of time perspective with positive time use (Hypothesis 3b).

A summary of the theoretical model is shown in Figure 1 . Below we present two studies aiming to validate a measure of positive time use as a single multifaceted construct. The second study also aims to test the hypotheses 2 and 3 by investigating the associations of positive time use and time management behaviors with their hypothesized predictors and outcomes and testing the corresponding mediation models.

Figure 1 . A theoretical model of the associations of positive time use with other constructs.

Study 1: development of the positive time use inventory

The aim of Study 1 was to explore the structure of the Positive Time Use Inventory and to obtain preliminary evidence of its convergent and discriminant validity against other well-being measures.

Participants and procedure

The sample ( N = 173) was comprised by part-time university students from the UK, 114 female and 59 male, aged 23 to 85 ( M = 42.37, SD = 12.37), 76.3% of whom were employed or self-employed. The study was approved by the university student research project panel. There were 28 missing responses in the dataset, EM imputation was used to recover the missing data.

Instruments

Positive Time Use Inventory

The initial pool of 69 items was based on the qualitative interview study of satisfaction with time use undertaken by the second author ( Boniwell, 2005 , 2006 ). The items reflected the themes identified using Interpretative Phenomenological Analysis from the interviews of 22 respondents. Based on exploratory factor analyses, 26 items with low communalities ( h  < 0.30) were selected out by the second author ( Boniwell, 2005 , 2006 ). The present study used the remaining set of 43 items that the participants evaluated on a 5-point Likert-type response scale from 1 (Strongly disagree) to 5 (Strongly agree).

Sense of Coherence Scale (SOC)

The 13-item short version of SOC ( Antonovsky, 1987 ) includes five Comprehensibility items, four Manageability items, and four Meaningfulness items. Each item is evaluated using a 7-point response scale. Sample item: “Do you have the feeling that you do not really care about what goes on around you? 1 = Very seldom or never … 7 = Very often.”

Satisfaction with Life Scale (SWLS)

The SWLS ( Diener et al., 1985 ) is a 5-item measure tapping into overall satisfaction with one’s life (sample item: “In most ways my life is close to my ideal”). The SWLS uses a 7-point Likert response scale from 1 (Strongly disagree) to 7 (Strongly agree).

Positive and Negative Affect Schedule (PANAS)

The PANAS ( Watson et al., 1988 ) is a list of 20 emotional adjectives (sample items: “interested,” “ashamed”) grouped into two scales, Positive Affect (PA) and Negative Affect (NA). For each adjective, the participants were asked to indicate the extent to which they have felt this way during the past few weeks on a 5-point Likert response scale from 1 (Very slightly or not at all) to 5 (Extremely).

Satisfaction with time use

A single item with high face validity (“Overall, I am satisfied with the way I use my time”) rated on a 5-point Likert scale from 1 (Strongly disagree) to 5 (Strongly agree) was used to check the convergent validity of the measure.

The descriptive statistics and reliability coefficients for all the instruments used in this study are presented in Table 1 .

Table 1 . Pearson correlations of PTUI with well-being measures ( N  = 173).

Results and discussion

Structure of the positive time use inventory.

We started by conducting exploratory and confirmatory factor analyses with 43 items (Mplus 8.8, MLR/MLM estimator, Geomin rotation). In interpreting the fit indices we relied on Hu and Bentler’s (1999) guidelines, using CFI values close to 0.95 or greater, RMSEA values close to 0.06 or below, and SRMR values close to 0.08 or below as evidence of reasonably good model fit. The fit indices for all the structural models are presented in Table 2 .

Table 2 . Fit indices for the structural models, Study 1.

In exploratory factor analyses, both parallel analysis and scree plot indicated four latent dimensions. The four dimensions were theoretically interpretable, reflecting self-congruent time use, balance of activities, sense of control over one’s time, and efficient time use. However, the fit of an initial EFA model with 43 items was poor. For each factor, we chose a subset of items with the most theoretically clear formulations and high factor loadings ( λ  > 0.50). The resulting set of 22 items exhibited an interpretable structure and a good fit to the data.

To find out the fit of the theoretically implied model without cross-loadings, we tested a conventional CFA measurement model which fit the data acceptably. We investigated the modification indices and found two strong outliers suggesting correlated uniquenesses for two pairs of items within the same scales. In one case, both items (Δ χ 2  = 35.87, items 7 and 19) referred to “time for myself,” in the other case, both items (Δ χ 2  = 14.09, items 9 and 17, placed adjacent in the original questionnaire) referred to the experienced meaninglessness of one’s daily activities. The resulting model with 2 additional covariances fit the data well. All the items had significant and substantial loadings on their respective factors ( λ  > 0.4).

To find out whether the 4 factors could be viewed as indicators of a single second-order dimension, we tested the fit of a higher-order model with a single second-order factor. Although the difference in the fit was significant, based on the scaled chi-square test (Δ χ 2  = 19.97, df  = 2, p  < 0.001), the difference in the practical fit indices was quite small (ΔCFI = 0.016, ΔRMSEA = 0.006) and the practical fit indices were all within ranges indicating good model fit and supporting the possibility of viewing positive time use as a single second-order dimension. The parameters of the final CFA model are presented in Figure 2 .

Figure 2 . Parameters of the hierarchical CFA model, Study 1. Item labels correspond to Appendix ; all the parameters shown are significant at p  < 0.01.

The descriptive statistics and reliability coefficients for the Positive Time Use Inventory scales are presented in Table 1 . The findings indicate a good structural validity of the PTUI as a multifaceted measure with four subscales: Self-Congruence of Activities, Balance of Activities, Sense of Control over Time, and Efficiency of Time Use. However, the reliability of the Efficiency of Time Use subscale was modest, due to a small number of items, and only acceptable for research purposes. Also, one of the covariances we found could reflect an item order effect.

Positive time use and well-being

The correlations of the PTUI scales with well-being indicators are presented in Table 1 . The PTUI scales were weakly to moderately correlated with each other. The findings indicate that the respondents who report positive time use tend to experience higher levels of subjective well-being and sense of coherence. At the same time, the correlations between these scales do not exceed 0.70, suggesting that the variance captured by the four dimensions of positive time use does not strongly overlap with that of well-being measures.

To investigate the variance shared by the individual dimensions of positive time use with well-being scales and to obtain preliminary evidence of the discriminant validity of the PTUI scales, we performed a multiple regression analysis. The 4 PTUI scales were entered simultaneously as predictors of each well-being measure. The results are presented in Table 3 .

Table 3 . Results of multiple regression analyses.

Satisfaction with life was mainly associated with self-congruent time use, with a minor contribution of balance and control. Positive affect was only predicted by self-congruent time use. However, lack of sense of control over one’s time turned out to be the strongest predictor of negative affect. Sense of coherence was predicted by self-congruence, sense of control, and efficiency of time use. Finally, three out of four scales were significant predictors of the satisfaction with time use item, with the remaining self-congruence scale a marginally significant predictor ( p  = 0.062).

We found that self-congruence of activities, balance of activities, sense of control over one’s time, and perceived efficiency of time use show weak to moderate intercorrelations, suggesting discriminant validity. At the same time, all four subscales are significantly associated with subjective well-being and sense of coherence, indicating their convergent validity as well-being indicators. In multiple regression, we found three out of four PTUI scales to be significant predictors of self-reported satisfaction with time use (with the remaining scale being marginally significant), which indicates their validity as indicators of a multifaceted construct of time use satisfaction.

Limitations

The findings of Study 1 are in line with the expectations based on the theoretical model. However, the limitations of the study include modest sample size, which reduces the precision of parameter estimates ( Kyriazos, 2018 ) and precludes from testing a more rigorous bifactor model ( Bader et al., 2022 ), absence of a cross-validation sample for post-hoc model modifications, and, finally, the use of a student sample. Given these limitations, Study 1 can only be considered as a pilot study. In order to obtain more rigorous evidence in favor of the structure, as well as to test substantive hypotheses about the nomological network of positive time use, we conducted a second study presented below.

Study 2: exploring the links between time perspective, time management, and time use

Study 2 had multiple aims: (1) to improve the psychometric properties of PTUI by supplementing the number of items in the Efficiency subscale, (2) to cross-validate the structure of the measure in a larger and more representative sample, (3) to test the proposed theoretical model and to explore the nomological network of positive time use by investigating its associations with time perspective and time management.

The sample ( N = 357) included 219 (61.3%) female and 138 (38.7%) male individuals, aged 17 to 71 ( M = 40.19, SD = 11.07). The participants were employed or self-employed professionals who described their role in the company as top managers (33.2%), mid-level managers (37.1%) or team members (29.8%). In terms of education, most participants had completed a postgraduate degree (42.6%), an undergraduate degree (30.2%), or a professional diploma (12.6%), a minority had GCSE/A-levels (7.6%) or doctoral degrees (6.7%). The participants completed an anonymous online questionnaire on time use and well-being and received brief feedback on their scores. The questionnaire was designed to exclude missing responses.

To improve the reliability of the Efficiency of Time Use scale, we supplemented it with three additional items (4, 12, and 20) derived from existing measures and tapping into inefficient use of time: “I find that during the day I am often not sure what to do next,” “I take a long time to ‘get going’,” and “I tend to change rather aimlessly from one activity to another during the day.” To reduce the possible response bias, we also slightly modified the instructions, asking participants to rate the extent to which each item is true about them using a 5-point Likert response scale from 1 (Very untrue) to 5 (Very true). The resulting version of the questionnaire is given in the Appendix .

Zimbardo Time Perspective Inventory (ZTPI)

The ZTPI ( Zimbardo and Boyd, 1999 ) is a 56-item measure tapping into five dimensions of individual time perspective: Future (sample item: “I complete projects on time by making steady progress”), Present-Hedonistic (“I take risks to put excitement in my life”), Present-Fatalistic (“Since whatever will be will be, it does not really matter what I do”), Past-Positive (“I get nostalgic about my childhood”), and Past-Negative (“I think about the bad things that have happened to me in the past”). The items are rated on a 5-point Likert scale from 1 (Very untrue) to 5 (Very true).

In line with the theoretical arguments and empirical evidence showing that a balanced time perspective profile is a more important predictor of well-being than score on any single ZTPI dimension ( Boniwell and Zimbardo, 2004 ; Boniwell et al., 2010 ), we also calculated the Deviation from Balanced Time Perspective (DBTP) index ( Zhang et al., 2013 ; Stolarski et al., 2015b ). This index reflects a Euclidean distance of an individual profile from a theoretically defined “optimal” one, characterized by a combination of high scores on the Future, Present-Hedonistic, and Past-Positive scales with low Present-Fatalistic and Past-Negative scores. There are numerous studies supporting its validity ( Stolarski et al., 2020 ).

Time management behaviors

To further investigate the nomological network of positive time use, we chose four indicators of time management behaviors. We used three subscales from the Time Management Behavior Scale (TMBS) ( Macan et al., 1990 ): Setting Goals and Priorities (sample item: “I review my goals to determine if they need revising”), Mechanics – Scheduling, Planning (“I write notes to remind myself of what I need to do”), and Preference for Organization (“At the end of the workday I leave a clear, well-organized workspace”). We also included a subscale from the Time Structure Questionnaire (TSQ) ( Bond and Feather, 1988 ), Structured Routine (sample item: “My main activities during the day fit together in a structured way”). These items were rated using the same 5-point response scale going from 1 (Very untrue) to 5 (Very true).

We did not include the other TMBS and TSQ subscales, which tend to reflect either outcomes of time management behaviors and thus overlap in terms of item content with the positive time use construct (e.g., Perceived Control of Time from the TMBS, Sense of Purpose, Effective Organization from the TSQ, Present Orientation) or reflect the motivational processes underlying time management behaviors and thus overlap with the dimensions of the ZTPI (e.g., Present Orientation and Persistence from the TSQ).

Finally, to measure subjective well-being, we used the same versions of Satisfaction with Life Scale ( Diener et al., 1985 ) and Positive and Negative Affect Schedule ( Watson et al., 1988 ) as in Study 1.

The descriptive statistics and reliability coefficients for all the instruments used in this study are given in Table 4 .

Table 4 . Fit indices for the structural models, Study 2.

To cross-validate the structure in the new sample and to investigate it more rigorously, taking advantage of the larger sample size, we performed a series of analyses in Mplus 8.8 using the new 25-item set with three additional items.

We tested three types models: a correlated-factor model with four factors, a more restricted higher-order model with a single second-order factor, and, finally, a bifactor model with a general positive time use factor and four specific factors reflecting the variance specific to items belonging to each subscale ( Rodriguez et al., 2016 ). These models have different assumptions and advantages, notably, the higher-order model is the most parsimonious (as it assumes that the relationships of the general second-order factor with the indicators are fully mediated by the first-order factor) and can be seen as nested within the bifactor model, which provides a more detailed representation of the relationships between the variables, but can easily be overfit to the data, even if the model is misspecified ( Markon, 2019 ).

Furthermore, each of these three models was tested, firstly, in its theoretically expected version, secondly, in a version with one additional covariance (replicated from Study 1), and, thirdly, following the Editor’s suggestion, as an ESEM model ( Van Zyl and Ten Klooster, 2022 ) allowing all possible cross-loadings. The ESEM models allow to overcome the limitation of imperfect indicators, but, at the same time, are less constrained and easy to overfit, so that the choice between them and the more parsimonious models should not be based on the fit indices alone ( Morin et al., 2020 ). The fit indices for all models are given in Table 4 .

Using conventional criteria applicable to ICM-CFA models ( Hu and Bentler, 1999 ) and based on the combination of fit indices ( Brown, 2015 ), the theoretical ICM-CFA model (1) with four correlated factors showed an acceptable fit to the data. The standardized factor loadings ranged from 0.47 to 0.83 across the items (mean λ was 0.64 and ranged from 0.61 to 0.69 across the four scales), and the factor correlations ranged from 0.27 to 0.69.

Based on modification indices, we identified one correlated uniqueness of items 7 and 19 (Δ χ 2  = 68.67). Both of these items refer to “time for myself” and belong to the Balance scale. The second correlated uniqueness found in Study 1 was not significant. All the remaining modification indices were comparatively weak with χ 2 values of 12 or smaller, corresponding to expected STDYX parameter values of 0.28 or smaller for cross-loadings and error covariances. The resulting correlated-factor ICM-CFA model (4) with one error covariance fit the data quite well, based on all four practical fit indices (CFI and TLI close to 0.95, RMSEA and SRMR below 0.06). The standardized factor loadings ranged from 0.41 to 0.83 across the items (mean λ was again 0.64 and ranged from 0.61 to 0.69 across the four scales), the factor correlations ranged from 0.29 to 0.68.

The parameters of both correlated-factor models (1) and (4) are given in Supplementary Table S1 . The parameters differed only marginally and the pattern of latent factor correlations (all going in one direction, statistically significant, and all but one comparable in magnitude) was consistent with the single higher-order dimension hypothesis. We followed by testing the more constrained model with a single second-order factor. Predictably, the model (2) only fit the data marginally, but the fit indices of the model (5) with an additional covariance were within ranges indicating good fit. Although the introduction of the single second-order dimension resulted in a significant decrease in model fit according to the scaled chi-square test (Δ χ 2  = 75.84, df  = 2, p  < 0.001), the difference in practical fit indices was relatively small (ΔCFI = 0.019, ΔRMSEA = 0.007). The parameters of the resulting hierarchical model are shown in Figure 3 . The loadings of all four scales on the second-order positive time use factor were all significant and pronounced ( λ  > 0.69), in line with a single construct hypothesis.

Figure 3 . Parameters of the hierarchical CFA model, Study 2. Item labels correspond to Appendix ; all the parameters shown are significant at p  < 0.001.

The four scales had good measurement reliability: the McDonald’s ω based on the hierarchical model ranged from 0.83 to 0.93 (see Figure 3 ) and Cronbach’s α for the observed sum scores ranged from 0.80 to 0.83 (see Table 5 ) for the subscales. The reliability of the total score was also high, with both α and ω = 0.91.

Table 5 . Pearson correlations between Study 2 variables ( N  = 357).

To further investigate the structure of the scale, we also tested the bifactor model and calculated the corresponding set of indices ( Rodriguez et al., 2016 ). Predictably, the bifactor models (3) and (6) also fit the data well, although all the practical fit indices and the information criteria tended to favor the more parsimonious correlated-factor versions. As in the case with correlated-factor models, the parameter estimates and the values of bifactor model indices only differed very slightly between the models with and without the additional covariance; for brevity we only present the parameters of the “classical” bifactor model (3) in Table 6 .

Table 6 . Factor loadings and reliability coefficients based on the bifactor ESEM model (9) and the bifactor ICM-CFA model (3), Study 2.

In this model (3), all the factor loadings of items on the general factor and on their respective specific factors were statistically significant. The Explained Common Variance (ECV) index was 0.54, indicating that only about half of the non-error variance of items is common to all the subscales, and suggesting that treating the positive time use construct as multidimensional might reveal some effects peculiar to its individual dimensions. The omega coefficient was 0.93 for the general factor and ranged from 0.79 to 0.85 for the four subscales, indicating good reliability based on joint contribution of the general factor and the subscale-specific variance. The hierarchical omega coefficients for the subscales ranged from 0.28 to 0.49, indicating a substantial proportion of reliable subscale-specific variance remaining after partitioning out the contribution of the general factor. This proportion was the highest for the Efficiency subscale. These analyses based on the bifactor model provide evidence in favor of discriminant validity of the subscales.

Finally, we tested the ESEM versions of the three models. Even though the correlated-factor ESEM model (7) had extremely good fit indices, the structure obtained after target rotation did not approximate simple structure (see Supplementary Table S1 ): there were many substantial cross-loadings and the correlations between factors had different signs. Predictably, the hierarchical ESEM model (8) tested using the procedure proposed by Morin and Asparouhov (2018) , despite showing good fit indices, failed to converge on a proper solution indicating that this correlation structure could not be represented by a single higher-order dimension. Nevertheless, the bifactor ESEM model (9) has shown good convergence and superior values of practical fit indices, despite the higher Bayesian Information Criterion (BIC) scores, compared to the ICM-CFA models (3) and (6).

A substantive comparison of the parameters of models (3) and (9) (see Table 6 ) shows that their differences are quite small: there are only a few cross-loadings unaccounted for by the bifactor model. Apart from the covariance of items 7 and 19 being assigned to the Mastery factor, the other cross-loadings were weak. The loadings of items on the general and group factors, as well as the values of indices based on the bifactor model were comparable to those obtained using the more parsimonious model (3). The only minor differences concerned the estimates of subscale-specific variance for the Self-Congruence and Efficiency factors. Thus, the results of bifactor ESEM have corroborated the results of ICM-CFA modeling, and supported the expected structure.

Does positive time use explain the effects of time perspective on well-being?

First, we explored the correlational links between positive time use, time perspective, and well-being measures (see Table 5 ). Past-Negative and Present-Fatalistic perspectives were negatively associated to all four PTUI dimensions. Their associations with self-congruent time use were particularly strong, suggesting that these perspectives are associated with inability to choose satisfying activities. Future time perspective was positively related to the efficiency of time use, self-congruence of activities, and a sense of mastery over one’s time. The associations of Present-Hedonistic and Past-Positive perspectives with positive time use were only marginal. The pattern of associations between PTUI and SWB indicators was similar to that found in Study 1.

For more detail, the correlations of the factor scores derived from the bifactor models separating the general effects of positive time use and the specific effects of residualized subscale factors are given in Supplementary Table S3 . Below we will focus only on the combined variance of the positive time use dimensions, aiming to validate the theoretical model.

To test the substantive hypothesis 2 that positive time use mediates the associations of time perspective and well-being, we tested a path model in Mplus, where the ZTPI scores predicted subjective well-being and their effects were partially mediated by positive time use. To simplify the model, we used an aggregate subjective well-being score and the total PTUI score. To evaluate the model, we used Maximum Likelihood estimator with 1,000 bootstrap samples to compute the 95% confidence intervals for the indirect effects. To assess the effect size of the mediation, we used the relative indirect effect index P M , which reflects the ratio of the indirect effect magnitude to that of the total effect ( Preacher and Kelley, 2011 ).

The resulting model is presented in Figure 4 . Positive time use emerged as a full mediator of the effects of the Future ( β ind  = 0.13 [0.08; 0.18], p  < 0.001, P M  = 0.77) and Present-Fatalistic ( β ind  = −0.06 [−0.11; −0.02], p  < 0.01, P M  = 0.74) time perspectives. The absence of significant direct effects suggests that the individual differences in well-being associated with future orientation and fatalistic orientation toward the present fatalistic are fully explained by the variance in positive time use. We only found partial mediation for the effects of past-negative ( β ind  = −0.22 [−0.27; −0.15], p  < 0.001; P M  = 0.36) and present-hedonistic ( β ind  = 0.10 [0.06; 0.14], p  < 0.001; P M  = 0.43). Finally, past-positive had only a positive direct effect on SWB.

Figure 4 . Positive time use as a mediator of the associations between time perspective and subjective well-being. Saturated model; parameters significant at p  < 0.05 are shown. PN, Past-Negative; PF, Present-Fatalistic; FU, Future; PH, Present-Hedonistic; PP, Past-Positive; PTUI, Positive Time Use; SWB, Subjective Well-Being.

When the DBTP index was used as a predictor instead of the individual ZTPI scales, we found a partial mediation with indirect effect ( β ind  = −0.28 [−0.33; −0.22], p  < 0.001; P M  = 0.56) being somewhat stronger than the direct effect ( β  = −0.22 [−0.31; −0.14], p  < 0.001), suggesting that the shared variance of balanced time perspective and well-being is largely, but not completely, explained by the variance in positive time use.

Does time management explain the effects of time perspective on positive time use?

Based on the above findings, we sought to test the hypothesis 3 stating that time management explains the effects of time perspective on positive time use and that the latter explains the effects of time management on well-being. First, we tested whether the four scales tapping into time management behaviors could be treated as a single dimension. A confirmatory factor analytic model with a single factor fit the data perfectly ( χ 2 (2) = 2.07, p  = 0.25, CFI > 0.999, RMSEA = 0.010 [0.000; 0.106], SRMR = 0.010), with standardized factor loadings of 0.60 (Preference for Organization), 0.71 (Structured Routine), 0.76 (Mechanics – Scheduling, Planning), and 0.83 (Setting Goals and Priorities).

Next, we tested a model where the 5 ZTPI scales were entered as predictors of the latent factor of time management behaviors. The model fit the data acceptably ( χ 2 (17) = 55.92, p  < 0.001, CFI = 0.946, RMSEA = 0.080 [0.057; 0.104], SRMR = 0.057). The 5 time perspective dimensions explained together 68% of the variance in time management. However, Future time perspective emerged as the only important predictor ( β  = 0.81, p  < 0.001) explaining 66% of the variance in time management behaviors. The only other significant predictor was Present-Hedonistic ( β  = 0.13, p  = 0.008), but its contribution to variance explained was extremely small, and we opted to model only the effects of the Future time perspective.

Finally, to test the third substantive hypothesis, we tested a path model with serial mediation, where the Future time perspective predicted time management, which fully mediated its effects on positive time use, which, in turn, fully mediated the effects of time management on subjective well-being. To simplify the model, the four time management variables were standardized and combined into a single index; the same approach was used for subjective well-being based on satisfaction with life, positive affect, and negative affect scales.

The parameters of the full mediation model tested are shown in Figure 5 . The model fit the data perfectly, according to the chi-square test of exact fit. The indirect effect of future time perspective on positive time use mediated by time management was significant ( β ind  = 0.36 [0.29; 0.43], p  < 0.001). The indirect effect of future time perspective on subjective well-being mediated by time management behaviors and positive time use was also significant ( β ind  = 0.25 [0.20; 0.31], p  < 0.001). The findings suggest that the higher levels of well-being found in individuals with future time perspective can be explained by their time management behaviors and better satisfaction with their use of time.

Figure 5 . Time management and positive time use as mediators of the effects of future time perspective on well-being. Model fit: χ 2 (3) = 3.32, p  = 0.35, CFI = 0.999, RMSEA = 0.001 [0.010; 0.093], SRMR = 0.024. FU, Future time perspective scale (ZTPI); TM, Time management index; PTUI, Positive Time Use Inventory total score; SWB, Subjective well-being index.

General discussion

The model of positive time use is based on phenomenological data obtained from semi-structured interviews by the second author who sought to describe and understand the phenomenon of satisfaction with the use of time. The findings of the two quantitative studies described above demonstrate the structural, convergent, and discriminant validity of the new measure, Positive Time Use Inventory, which operationalizes the theoretical model based on qualitative findings. In structural and convergent validity analyses the four dimensions of positive time use emerge as interrelated, yet distinct: even though they all describe different aspects of satisfying time use, they have substantial proportions of non-shared variance and show different patterns of association with well-being outcomes.

In structural analyses, we relied on hierarchical and bifactor models. We saw good fit both of hierarchical models that provide a more parsimonious representation of the structure and bifactor models, which allow for a more detailed partitioning of the variance, are based on an assumption of a single underlying construct, but also require larger sample sizes ( Markon, 2019 ; Bader et al., 2022 ). The results of bifactor ICM-CFA and bifactor ESEM showed very good convergence, supporting the potential discriminant validity of the subscales.

Theoretically, the construct of positive time use fills the gap between time perspective, on one hand, and well-being, on the other hand, by elucidating some of the processes and mechanisms behind their associations. Although positive time use only partially mediates the effects of balanced time perspective with well-being, it fully explains the effects of the Future and Present-Fatalistic dimensions of time perspective and largely explains the effects of the Present-Hedonistic dimension. These findings suggest that satisfaction with time use and subjective well-being can be facilitated by adopting a conscious, mindful, and responsible approach to the time we have at our disposal. Future studies could explore whether the coaching and therapy interventions aiming to achieve a balanced time perspective have causal effects on positive time use.

The concept of positive time use has also allowed us to explore and explain the links of time management with time perspective, on the one hand, and with well-being, on the other hand. We found that time management behaviors are chiefly predicted by future time perspective, in line with previous studies ( Bajec, 2019 ). The findings supported our theoretical model suggesting that time management behaviors fully mediate the effects of future perspective on positive time use, which, in turn, explains their associations with well-being. Unfortunately, cross-sectional design precludes us from making any causal inferences at this stage. However, the working model proposed above paves the way for more rigorous longitudinal studies that could find out whether these links are indeed causal and establish their direction.

The results from the student sample (Study 1) and the working adult sample (Study 2) indicate that satisfying time use and efficient time use do indeed come in combination. Nevertheless, some individual differences in the relative importance of the facets of positive time use can be expected. Individuals focused on achievement might use their time efficiently in pursuit of important goals at the expense of balance between life spheres: past findings indicate that work-life balance is more important for the well-being of working adults than for those who are not employed ( Dittrich and Mey, 2015 ). The results of additional exploratory analyses using person-oriented approach (see Supplementary Table S4 ) suggest that individuals with a strong future orientation and those with a more balanced time perspective emphasizing Present-Hedonistic have different profiles, yet comparable levels of positive time use, as well as comparable levels of general well-being. However, this might only be true for the achievement-oriented business employees comprising our Study 2 sample. Does sacrificing one’s life balance for the sake of one’s future goals come at a price and, if yes, does this price become evident with time? Longitudinal studies using larger and more diverse samples are needed to further explore the individual differences in positive time use patterns.

The findings also suggest that time management behaviors are mainly supported by future time perspective and might mainly be beneficial for positive time use and overall well-being in future-oriented individuals. This is in line with existing evidence showing that the effects of time management interventions are generally modest and may differ vastly depending on the individual and group contexts ( Aeon and Aguinis, 2017 ). More research is needed to find out whether the efficient time use associated with a predominance of future orientation and active time management strategies does indeed translate into higher achievement and whether it is sustainable in a long term.

Naturally, the present studies are limited by modest sample sizes and cross-sectional designs. Given the known cultural differences with respect to the subjective notions of time ( Meyer, 2016 ), the pace of life ( Levine and Norenzayan, 1999 ), and time perspective ( Sircova et al., 2015 ), it is quite possible that some of the effects that we discovered may be peculiar to the British culture and/or to professionally active adults. After all, the very concept of positive time use is operationalized based on the phenomenological data from only one country, Great Britain. Future qualitative studies could tap into the subjective notions of time spent well across different cultural contexts.

Nevertheless, the findings provide sound evidence concerning the structural, convergent, and discriminant validity of the Positive Time Use Inventory in two different UK samples, as well as some information about the nomological network of the new construct. The PTUI emerges as a promising new tool that can be used as part of time perspective coaching process with individuals and organizations ( Boniwell et al., 2014 ; Boniwell and Osin, 2015 ) in order to diagnose the individual problems and to evaluate the effects of time coaching and time management interventions.

The results concerning the effects of time perspective and time management on positive time use suggest that efficient time use can be facilitated by strengthening one’s future time perspective and adopting time management strategies. However, achieving a satisfying time use might rather require a productive relationship with the present – the capacity to enjoy the present moment, to seize the emerging opportunities, and to overcome a passive, fatalistic attitude to life. Thus, the balance facet of positive time use can be facilitated by adopting a more balanced time perspective. Intervention studies could test whether these different approaches to positive time use can complement each other in the coaching process and whether ‘smart’ time management coaching interventions taking into account the individual differences in time perspective and positive time use could be more effective than the ‘one-size-fits-all’ time management recipes.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the Open University Human Participants and Materials Ethical Committee. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written or online informed consent to participate in this study.

Author contributions

EO and IB contributed to the conception and design of the study and performed the data collection. EO performed the statistical analyses and wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

The article was prepared within the framework of a research grant funded by the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2022-325).

Acknowledgments

The authors are grateful to Alan Bec and Tony Murphy for their help with the data collection.

Conflict of interest

IB was employed by company Positran, Épone, France.

The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1087932/full#supplementary-material

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Please read each item and, as honestly as you can, answer the question: “How characteristic or true is this of you?” Please give your answer by choosing a number:

Key (* indicates reverse-scored items, keyed 5 4 3 2 1): Self-Congruence: items 1, 5, 9*, 13, 17*, 21, 25; Balance: items 3, 7*, 11, 15, 19, 23; Efficiency: items 4*, 8, 12*, 16*, 20*, 24*; Mastery: items 2*, 6*, 10*, 14*, 18, 22*; Positive time use index: items 1–25 (after inverting all the reverse-scored items).

Keywords: balanced time perspective, Zimbardo Time Perspective Inventory, subjective well-being, temporal well-being, time management

Citation: Osin E and Boniwell I (2024) Positive time use: a missing link between time perspective, time management, and well-being. Front. Psychol . 15:1087932. doi: 10.3389/fpsyg.2024.1087932

Received: 02 November 2022; Accepted: 25 January 2024; Published: 26 February 2024.

Reviewed by:

Copyright © 2024 Osin and Boniwell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Evgeny Osin, [email protected] ; Ilona Boniwell, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Time management strategies for research productivity

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• PMID: 22868990
• DOI: 10.1177/0193945912451163

Researchers function in a complex environment and carry multiple role responsibilities. This environment is prone to various distractions that can derail productivity and decrease efficiency. Effective time management allows researchers to maintain focus on their work, contributing to research productivity. Thus, improving time management skills is essential to developing and sustaining a successful program of research. This article presents time management strategies addressing behaviors surrounding time assessment, planning, and monitoring. Herein, the Western Journal of Nursing Research editorial board recommends strategies to enhance time management, including setting realistic goals, prioritizing, and optimizing planning. Involving a team, problem-solving barriers, and early management of potential distractions can facilitate maintaining focus on a research program. Continually evaluating the effectiveness of time management strategies allows researchers to identify areas of improvement and recognize progress.

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The importance of effective time management in research: Strategies for improving productivity

Research is a crucial aspect of academic and professional life, but it can be challenging to balance research responsibilities with other commitments. Effective time management is essential for researchers to be productive and achieve their goals without sacrificing their personal lives. In this article, we will explore the importance of time management in research and provide strategies for improving productivity.

Importance of Time Management in Research:

Effective time management is critical in research for several reasons. First, research requires a significant amount of time, and effective time management ensures that this time is used efficiently. Poor time management can result in missed deadlines, incomplete projects, and wasted resources. Second, time management can help researchers achieve a healthy work-life balance, which is essential for maintaining well-being and avoiding burnout. Third, time management can improve research outcomes by allowing researchers to focus on their work without distractions.

Strategies for Improving Productivity:

Here are some strategies for improving productivity through effective time management:

Plan Ahead: Effective time management begins with planning. Researchers should create a research plan that includes their goals, deadlines, and milestones. Planning helps researchers stay organized and avoid last-minute rushes.

Prioritize Tasks: Not all tasks in research are equally important. Researchers should prioritize tasks based on their importance and urgency. Tasks that are urgent and important should be given priority over tasks that are less critical.

Use Time-Blocking: Time-blocking is a technique that involves scheduling specific blocks of time for different tasks. Researchers can allocate time for specific activities, such as writing, data analysis, or meetings. Time-blocking can help researchers stay focused and avoid distractions.

Take Breaks: Taking breaks is essential for maintaining productivity. Researchers should take regular breaks to rest their minds and recharge their energy. Short breaks can help researchers stay refreshed and focused.

Avoid Multitasking: Multitasking can reduce productivity and increase stress. Researchers should focus on one task at a time and avoid distractions. Switching between tasks can reduce efficiency and increase the risk of errors.

Use Productivity Tools: There are several productivity tools available that can help researchers manage their time more effectively. Tools such as calendar apps, to-do lists, and project management software can help researchers stay organized and on track.

Delegate Tasks: Delegating tasks can help researchers save time and reduce their workload. Researchers can delegate tasks to research assistants or collaborators to free up their time for more critical activities.

Effective time management is critical for researchers to achieve their goals and maintain a healthy work-life balance. By planning ahead, prioritizing tasks, using time-blocking, taking breaks, avoiding multitasking, using productivity tools, and delegating tasks, researchers can improve their productivity and achieve their research objectives. Adopting these strategies can help researchers achieve their full potential and succeed in their research endeavors.

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Assessment of time management practice and associated factors among primary hospitals employees in north Gondar, northwest Ethiopia

Muluken Genetu Chanie

1 School of Public Health, Department of Epidemiology and Biostatistics, College of Medical and Health Sciences, Wollo University, Dessie, Ethiopia

Erkihun Tadesse Amsalu

2 Department of Epidemiology and Biostatistics, School of Public Health, College of Medical and Health Sciences, Wollo University, Dessie, Ethiopia

Gojjam Eshete Ewunetie

3 Dembia General Hospital, Outpatient Department, Gondar, Ethiopia

Associated Data

All relevant data are within the manuscript and its Supporting Information files.

Time management practice can facilitate productivity and success, contributing to work effectiveness, maintaining balance and job satisfaction. Thus, this study aimed to assess time management practices and associated factors among employees of primary hospitals in north Gondar.

An Institutional based cross-sectional study among primary hospital employees in north Gondar was conducted from March to April 2018. A structured and pre-tested questionnaire was used to collect the data. Simple random sampling technique was utilized to select 422 employees. Bivariate and multivariate logistic regression model were done to identify factors associated with time management practice. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was ascertained to show the strength and direction of association.

In this study, the prevalence of time management practice was 56.4% (95%CI: 49.3, 61.7). Being satisfied with organizational policies (AOR = 2.16; 95%CI: 1.02–4.68), performance appraisals (AOR: 2.11; 95%CI: 1.32–4.66), compensation and benefits (AOR: 4.18; 95%CI: 2.18–7.99), and planning (AOR: 2.86; 95% CI: 1.42–5.75) were statistically significant factors associated with time management practice.

Conclusion and recommendation

The overall time management practice among the primary hospital employees was low. Planning, organizational policy, compensation and benefit, performance appraisal, and residence were factors significantly associated with hospital employee’s time management practice. Thus managers and employees need to carry out interventions on significant factors to improve the employees’ time management practice.

Introduction

Time is described as a measure of the duration and order of events in the past, the present and the future [ 1 ]. Time is a priceless resource and continues to pass by without coming back. Time itself cannot be managed because it is an inaccessible factor rather task in line with time[ 2 ]. The concept of time management started with industrial revolution and became the modern notion of doing things effectively and efficiently [ 3 , 4 ]. Hence its importance has been increasing from day to day [ 5 ]. Effects of time management are a panacea to organizational effectiveness. It is difficult to measure time management practice but largely depends on the outcomes of employees performance [ 6 ].

Time management practice is the act of influencing one’s key behavioral dimensions to complete as many tasks as possible within a given time period. Such behavioral dimensions include organization of work and continuous application of time management techniques as a habit [ 7 ].

According to Donaldson, “the aim of good time management is to achieve the lifestyle balance you want”. Good time at work means doing high quality work, not high quantity [ 8 ]. Good time management such as setting goals and priorities as well as scheduling and delegation of tasks can facilitate productivity and success, contributing to work effectiveness, maintaining balance and job satisfaction [ 9 ]. In contrast, poor time management has been associated with poor work quality, low productivity, negative influence on career path, and high stress levels [ 10 , 11 , 12 ].

A study has pointed out that time management practices in different countries of the world vary. A study conducted on factors affecting time management and nurses’ performance in Hebron hospital, Palestine, reported time management practice was high with rate 69.5% [ 13 ]. A study conducted in Pakistan on time management and organizational performance in 2011 revealed that among 1200 participants overall time management practice was 30% [ 14 ]. A study done in UAE(United Arab Emirates) revealed that time management practice was 49% and the study showed that 56% of employees lack planning, prioritizing and scheduling time for their work [ 15 ].

A study done in Egypt on time management program showed that time management practice was 45% among the studied head nurses at their work site with impacts on their job performances and performance appraisals [ 16 ].

Another study done in Nigeria on time management in Nigerian hospitals showed that time management practice among employees was found 51% [ 17 ].

A study done in Ethiopia on the effect of time management practice among Dire-Dawa university students showed that time management practice was found 34% [ 18 ].

There is prevalent lack of time management culture in many societies especially in developing countries including Africa which may be detrimental to both the organization as well as the employees [ 17 ]. Most people feel like they have too much to do and not enough time and they blame lack of time for their unachieved goals, poor performance and low productivity [ 14 ].

There were several factors known to contribute to poor time management practices. Among these factors effective time management method related factors, personal factors (punctuality, time wasters), administrative and organizational obstacles of time management (organizational policy, Lack of incentives, performance appraisal), and employees performance in an organization are the most important factors which have important role in determining employees’ time management practices [ 13 , 19 , 20 ]. Other variables such as education, age, marital status, and sex also has been determined as factors that contribute to it [ 19 , 21 ].

There was an implementation of time management practices in every organization but still there is a gap in reaching productivity and improved performance of employees.

There were limited previous studies regarding time management practice, but there were no published data about time management practice among primary hospital employees in Ethiopia including the study setting.

Therefore, this study aimed to assess time management practices and associated factors among employees of primary hospitals in North Gondar Zone.

Method and materials

Study setting.

The study was conducted at primary hospitals found in North Gondar Zone, which is one of the 11 zones found in the Amhara National Regional State. This zone is located in Northwest part of Ethiopia and divided into 24 woredas (Districts). There are 9 primary hospitals, 126 health centers and 573 health posts in this zone. In all 9 hospitals there are about 1,071 employees of which 543 were health professionals and 526 were supportive workers according to North Gondar health department’s plan office data.

Study design and period

Institutional based cross-sectional study was conducted from March to April 28, 2018.

Population and sample

Debark hospital, Metema hospital; Delgi hospital, Gohala hospital, Aykel hospital, Mekane-brhan hospital, Amba-giorgis hospital, Koladiba hospital, and Abraha–Jira hospital were selected hospitals from Gondar zone for this study. There were a total of 1,071 employees working in the selected primary hospitals of north Gondar zone. All employees working in primary hospitals of north Gondar zone for at least 6 months period were included into the study. Those employees who had worked for less than six months in the hospital and respondents with incomplete data were excluded from the study. A total of 391 employees which fulfilled the inclusion criteria were participated in the study.

Sample size determination and sampling procedure

Sample size for the prevalence part of the study was determined by using single population proportion (as there were no previous study conducted in the area) formula considering the following assumptions: taking 50% prevalence of time management practices and expected margin of error (d) 0.05 and with 95% confidence level (Z a/2 ) n = ( z α / 2 ) 2 p ( 1 − p ) d 2 = ( 1.96 ) 2 0.5 ( 0.5 ) ( 0.05 ) 2 = 384

By adding 10% for non-respondents the total sample size was 422.

For associated factors of time management practice the sample size was determined by using double population proportion formula using selected three key predictors [ 22 , 23 ] according to the following assumptions and computed by Epi-info version 7 software ( Table 1 ).

Thus the minimum adequate sample size for this study was 422 taken from single population proportion formula.

Proportional allocation of 422 samples was done for each primary hospital based on the number of employees working in the respective hospitals. Then study participants were selected by simple random sampling method in each Hospital. A total of 84 respondents from Debark hospital, 87 from Metema hospital, 36 from Delgi hospital, 28 from Gohala hospital, 44 from Aykel hospital, 29 from Mekanbrhan hospital, 41 from ambagiorgis hospital, 45 from Koladba hospital, and 28 from abraha-jira hospital were selected.

Study variables and data collection procedure

Time management practice was used as a dependent variable. Socio-demographic factors (sex, age, residence, marital status, educational status, type of profession, and work experience), personal factors (time wasters, procrastination, and punctuality), administrative and organizational factors (organizational policy and strategy, work environment, compensation and benefit, performance appraisal, recognition, and promotion), and employees performance (planning, implementation, and responsibility) were independent variables of the study.

Time management practice was defined as scheduled use of time by employees at work site. It is measured by 5 items each scored a 5 point Likert-scale with 1 denoting strongly disagrees and 5 denoting strongly agree. After dichotomous category, responses above and equal to 65% was categorized as good time management practices [ 13 ].

Organization policy and strategy was described as the respondent’s feeling on the application of organizational policies and strategies. It was measured by using 3 items each scored 5-point Likert scale. It was categorized as satisfied if the responses were ≥ the mean score value and unsatisfied if the responses were below the mean score value.

Responsibility was described as the respondent’s duty to fulfill a responsibility as personal and as member of team work. It is measured by using 3 items each scored 5-point Likert scale. It was categorized as high if the responses were ≥ the mean score value and low if the responses were below the mean score value.

Work Environment was described as the quality of the working environment both its physical attributes and the degree to which it provided meaningful work condition. It was measured by using 5 items each scored 5-point Likert scale. It was categorized as good if the responses were ≥ the mean score value and bad if the responses were below the mean score value.

Compensation and benefit was described as employees feeling of fairness and adequate payment for work done and financial rewards for better performance. It was measured by using 3 items each scored 5-point Likert scale. It was categorized as satisfied if the responses were ≥ the mean score value and unsatisfied if the responses were below the mean score value.

Recognition and Promotion was described as employees feeling of recognition and promotion systems of the hospital. It was measured by using 4 items each scored 5-point Likert scale. It was grouped as satisfied if the responses were ≥ the mean score value and unsatisfied if the responses were below the mean score value.

Performance appraisal was described as the participants feeling on measurement of their actual performance. It was measured by using 3 items each scored 5-point Likert scale. It was categorized as satisfied if the responses were ≥ the mean score value and unsatisfied if the responses were below the mean score value.

Procrastination was described as the employees postponing of scheduled tasks. It was measured by using 4 items each scored 5-point Likert scale. It was categorized as high if the responses were ≥ the mean score value and low if the responses were below the mean score value.

Time wasters were described as the engagement to an activity that spends employees’ productive time at work site. It was measured by using 5 items each scored 5-point Likert scale. It was categorized as high if the responses were ≥ the mean score value and low if the responses were below the mean score value.

For this study the data was collected by using self-administered structured questionnaires adopted from advanced corporate training and legal management consultants [ 24 , 25 ]. Three data collectors (diploma nurses) and two supervisors (BSc Nurses) were recruited. One day training was given by the principal investigator for data collectors about the objectives and processes of data collection. Pre-test was conducted on 10% of total sample size (42 employees) at Addis zemen primary hospital. All filled questionnaires were checked by the principal investigator for its completeness and consistency.

Data management and analysis

Prior to the actual data collection, frequent supervision was done, interviewers were trained, and interviews were performed using the local language Amharic. Reliability test (Cronbach’s alpha) was performed to check reliability of the questionnaire items. Data were checked for completeness, organized and entered into Epi-info version 7, and then exported to STATA version 14 software for analysis.

Tables were used to present the results. Descriptive statistical analysis such as frequencies and percentages were used to describe the characteristics of the study population. As the response variable i.e. time management practice was dichotomous (poor, good), logistic regression was used to identify factors that affect time management practice. Variables with ≤ 0.05 p-values in the bi-variable analysis were fitted in the multivariable model. Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) and p-value < 0.05 in the multivariable model were used to declare significant association with time management practice. Goodness of fit was checked using Hosmer Lemeshow test (p = 0.187).

Ethical consideration

Ethical clearance was obtained from the University of Gondar Ethical Review Board (IRB). Before communicating study participants’ official permission letter of cooperation was obtained from Amara National Regional Health Bureau (ANRHB). The purposes and the importance of the study were explained and informed consent was secured from each participant. Respondents were clearly told about the study and the variety of information needed for them. They were given the chance to raise any question about the study and free to refuse or terminate the interview at any moment. Name of participants and any personal identifiers were not included in the study, and the confidentiality of the data was kept at all level of the study.

Socio -demographic characteristics of respondents

From a total of 422 primary hospital employees, 391 of them went into the analysis. The remaining 31 were excluded from the study due to incomplete information. More than half, 232 (59.3%) were males and 234(59.8), highlanders. Regarding educational status, 254 (65%) of the respondents had diploma and below. The median age of respondents were 28.5 years (IQR: 25.82–31.25). Regarding salary, 194(49.6%) of employees earned less than 3137 Ethiopian Birr (ETB) i.e. below 109 USD monthly ( Table 2 ).

Organizational related factors of respondents

In this study majority of employees about 243(62.1%) were unsatisfied with organizational policy. similarly about 239(61.1%) of respondents were unsatisfied with performance appraisal. Regarding compensation and benefit about 348 (89.0%) were unsatisfied. About the working environment, 119 (30.4%) of employees had good Work environment. The finding also showed that about 296 (75.5%) of respondents were unsatisfied with recognition and reward ( Table 3 ).

Employee performance related factors

This study showed that majority of primary hospital employees, 316 (80.8%) had planning for their work. More than half, about 222 (56.8%) of employees showed high responsibility for their work. Regarding implementation about 307(78.5%) had high implementation for their work ( Table 3 ).

Personal related factors of respondents

Regarding punctuality the majority of respondents about, 337(86.2%) was punctual for their work. Similarly majority of employees about, 317(81.1%) had high procrastination. This study also showed that majority of respondents about, 335 (85.7%) were high time waster ( Table 3 ).

The overall prevalence of time management practice among primary hospital employees was 56.4% (95%CI: 49.3%, 61.7%).

Factors associated with time management practice

In the bi-variable analysis punctuality, organizational policy, performance appraisal, work environment, recognition and reward, planning, implementation, compensation and benefit, residence, procrastination, and time waste level were factors found to besignificantly associated with time management practice at p- value≤0.05.

However, in the multivariable mixed effect logistic regression analysis, organizational policies, planning, performance appraisal, compensation and benefit, and residence were factors significantly associated with time management practice among primary hospital employees.

Hospital employees who were satisfied with organizational policies and strategies were nearly two times (AOR = 2.16, 95% CI: 1.021, 4.69) more likely to have good time management practice compared with unsatisfied employees.

Employees who were satisfied with performance appraisals were two times (AOR = 2.11, 95% CI: 1.32, 4.67) more likely to have good time management practice compared with unsatisfied counterparts.

Similarly employees satisfied with compensation and benefit were nearly four times (AOR = 4.18, 95% CI: 2.19, 7.99) more likely to have good time management practice compared with unsatisfied employees.

On the other hand employees who were good in planning were nearly three times (AOR = 2.86, 95% CI: 1.42, 5.75) more likely to have good time management practice compared with those poor in planning.

Employees working in the highland areas were nearly two times (AOR = 2.08, 95% CI: 1.08, 4.01) more likely to have good time management practice compared with those working in lowland ( Table 4 ) .

COR: Crude odds ratio, CI: Confidence interval, AOR: adjusted odds ratio, 1: Reference category

*: significant at p< 0.05

**: Significant at p< 0.001

In this study, the prevalence of time management practice among employees was low. This finding was higher as compared to studies conducted in Nigeria on time management practice 51% [ 17 ], and a study done on time management program on job satisfaction in Egypt 45% [ 16 ]. Similarly, this finding was much higher than studies conducted in United Arab Emirates which was 49% [ 15 ] and Pakistan which was reported as 30% [ 14 ]. The finding was also higher than a study done in Dire-Dawa University Ethiopia which reported the prevalence of time management practice was 34% [ 18 ].

However, it is lower than studies conducted in Palestine on health professionals performance in Hebron Hospital, in which the prevalence of time management practice was reported 69.5% [ 13 ] and in Australia on health professionals the prevalence was reported 64%[ 26 ]. This discrepancy could be resulted from differences in infrastructure in the health institutions, study setting differences, and differences in the respondents which could affect the status of time management practice. In this study the study subjects were primary hospital employees working in public hospitals only, where as in Palestine and Australia the study subjects were health professionals working both in selected public and private hospitals [ 13 , 26 ].

This study identified hospital employee’s time management practices were influenced more by organizational policy and strategy. Hospital employees who were satisfied with organizational policies and strategies had good time management practice. This finding is consistent with studies conducted in Pakistan and Palestine [13, 14[. The possible explanation could be if employees perceived that the policies and strategies of the organization are not fair, they become disappointed and dissatisfied which could affect employee’s time management practice negatively. Whereas satisfied respondents would be motivated and can manage their time effectively in the organization because there is fairness in, and benefits from their organizations [ 14 , 27 , 28 ].

Time management practice was high among the respondents who were satisfied with performance appraisal got from the hospital when compared with unsatisfied employees. This finding is supported by studies done on time management [ 20 ]. This might be due to unfair relationships between some workers and with the department head and/or the hospital manager who may treat some staffs better than others based on some form of personal relationships [ 20 , 29 ].

Another strong significant predictor of time management practice from hospital employees was compensation and benefit. Primary hospital employees who were satisfied with compensation and benefit had good time management practice when compared with unsatisfied. The result of this finding is in line with studies conducted in Egypt about the effect of time management program on job satisfaction [ 16 ]. This could be explained by poor working environment, dissatisfaction with the organization, less professional opportunity because it does not give them a chance to grow and develop their own abilities, which in turn lead to poor time management practices of employees[ 29 , 30 ].

Primary hospital employees who were good in planning were good in time management practice. This finding is in line with a study done on time management and academic performance in United Arab Emirates [ 15 ]. The possible explanation could be good experience in planning decreases employees dependence on others what to do and task leading activities timely [ 27 , 31 , 32 ].

With respect to socio-demographic characteristics, residence was significantly associated with hospital employee’s time management practice. Employees working in the highland areas were more likely to manage their time when compared with employees working in lowland. This finding is consistent with studies done on a cross-cultural investigation of time management practices and job outcomes [ 33 ]. This finding could be explained by the fact that differences in working settings and weather conditions respondents were working [ 32 , 33 ].

The literature is not consistent in terms of the relationship between some associated factors and employees’ time management practice. In this particular study time management practice factors like punctuality, work environment, procrastination, time waster, recognition and reward, implementation, marital status and work experience were not found to be statistically significant associations with employees’ time management practice. This might be due to differences in the content and nature of work in the hospitals and difference in research settings might cause discrepancy results.

The variables used in the study might not be exhaustive and some other variables might be missed that need to be tested for association with time management practice. Use of self-reporting measures may have some potential for reporting biases, which may have occurred because of the respondents’ interpretation of the questions; they may over or under report a phenomenon. Finally, the study lacked the component of follow-up, in which the researcher could compare participants’ time practice versus their actual practice.

The study could have valuable implication to formulate appropriate strategies by different stakeholders involved in hospital administration and management programs, and other related public health interventions. It is also important to enhance and upgrade participants’ understanding about time management; and to equip them with major techniques of time management. This study could also provide information to subsequent researchers on time management practices and factors associated with it.

The overall time management practice among the primary hospital employees was low. Planning, organizational policy and strategy, compensation and benefit, performance appraisal, and residence were predictors significantly and positively associated with hospital employee’s time management practice.

Thus it is recommended that hospital employees must give special emphasis about planning to improve their time management practice. Hospital Managers need to assess and improve organizational policies and strategies and performance appraisal systems practicing in the respective hospitals to treat employees fairly and equally. It is also recommended to conduct further research on the issue by extending the study setting and the study population.

Supporting information

Acknowledgments.

First we would like to thank all study participants for their cooperation in providing the necessary information. We would also thank data collectors and supervisors for the devotion and quality work during data collection for the accomplishment of this work.

Abbreviations

Funding Statement

The authors received no specific funding for this work.

Data Availability

• PLoS One. 2020; 15(1): e0227989.

Decision Letter 0

25 Sep 2019

PONE-D-19-24146

Assessment of time management practices and associated factors among employees of primary hospitals in north Gondar, northwest Ethiopia

Dear Dr Amsalu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I acclaim the authors for taking their time to study this very sensitive topic especially in Ethiopia set up.

Abstract: briefly articulated and has clearly shown the overall study.

Introduction:

This section has tried to explain time and time management practice at a different perspective. It looks good and explanatory. It would be very good if you quote studies in Africa that could deliver better information about time management. Perhaps, that would give a good picture, avoid bias and pointless conclusion. Similarly, a study conducted on Africans resided in Iran, as mentioned in this study, which might have different social fabrics when compared to studies done in other African countries, could be susceptible to bias. Hence, I recommend using studies that have been done in Africa or at least in a similar setting to offer conceivable information.

As a whole, the literature reviews looks very scanty and insufficient to demonstrate time management and practice especially in Ethiopia settings. Perhaps, it would be very useful to incorporate studies that could at least be related to the study setting to make the study more useful and relevant.

Methodology:

In general the methodology appears so murky and narrow to provide enough information. This section needs outright revision or overhaul. it has short of scientific explanation, doesn’t appropriately depict methods and has overlooked key research tools. i found the following point unclear and need to be addressed.

How did you determine the sample size? How did you allocate study participants? How did you select the study participant? Where did you get or how did you develop data collection tools or questionnaire in this study? How did you measure the validity and reliability of the study tools or questionnaire implemented to collect data in this study?  It is not also clear how the cutoff point made for the Likert scale.  How the questionnaire contents organized and formulate to address the objective?  

What is the dependent variable in this study? It looks like level of time management practice appears to be the dependent variable. However, you have operationally defined time management practice on the next paragraph. You should be clear otherwise it would be very confusing.  It looks like there is misconception between time management practice and level of time management practice in this study. Hence, you need to differentiate or clarify both first, then clearly address dependent variable and provide the proper operational definition. Or else, this would affect the full analysis and study. Similarly, would be good to define those factors indicated in this study as well.

The socio-demography well stated. Maybe, it would be useful if you depict the response rate in percent than numbers for simplicity.

However, the remaining part of the result seems disorganized and superficial. It lacks coherence. It is so difficult to assert the authenticity of the analysis. It looks like there is a kind of mingling between the sub-topics “time management practices, organizational policies, employees’ performance and personal factors” and “factors associated with time management practice”. Either you need to modify the first sub topic or merge with the second topic. This section as a whole needs stringent revision.

Discussion:

In general, this section has tried to compare studies that has been conducted in different places and has made arguments, which is very commendable. However, the arguments are weak, frail and lack of scientific reasoning. It is not clear also, for instance, on the first paragraph you indicated that “ the proportion of time management practice among employees was 56.4%”  what does the word proportion designate in this sentences? There is similar inconsistency throughout the document that has to be fixed.

In addition to this, you need to use studies that are closely related to your study setting at various measuring scale to make plausible comparison. Otherwise, citing studies which never have related to your study setting will affect the analysis and the entire result one or another way.

What is the limitation of your study?

Conclusion:  looks good but what are your recommendations? You have inscribed your suggestion and recommendation at the abstract section, but not in this section.

Make sure you stick with reference regulation of the publisher.

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Additional Editor Comments (if provided):

How did you determine the sample size? How did you allocate study participants? How did you select the study participant? Where did you get or how did you develop data collection tools or questionnaire in this study? How did you measure the validity and reliability of the study tools or questionnaire implemented to collect data in this study? It is not also clear how the cutoff point made for the Likert scale. How the questionnaire contents organized and formulate to address the objective?

What is the dependent variable in this study? It looks like level of time management practice appears to be the dependent variable. However, you have operationally defined time management practice on the next paragraph. You should be clear otherwise it would be very confusing. It looks like there is misconception between time management practice and level of time management practice in this study. Hence, you need to differentiate or clarify both first, then clearly address dependent variable and provide the proper operational definition. Or else, this would affect the full analysis and study. Similarly, would be good to define those factors indicated in this study as well.

In general, this section has tried to compare studies that has been conducted in different places and has made arguments, which is very commendable. However, the arguments are weak, frail and lack of scientific reasoning. It is not clear also, for instance, on the first paragraph you indicated that “the proportion of time management practice among employees was 56.4%” what does the word proportion designate in this sentences? There is similar inconsistency throughout the document that has to be fixed.

Conclusion: looks good but what are your recommendations? You have inscribed your suggestion and recommendation at the abstract section, but not in this section.

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Reviewers' comments:

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Reviewer #1: Yes

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Reviewer #1: No

5. Review Comments to the Author

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Reviewer #1: Dear PLOS One thank you for the chance given to review a research article titled “Assessment of time management practices and associated factors among employees of primary hospitals in north Gondar, northwest Ethiopia”. Effective time management particular for those who are directly involved in the process of care of human being. Hence, this research will discover the colossal time management problem in the health sector. The following are my comments:

General Comments

Is there an African / Ethiopia perspective of time?

What are the dimensions of time?

Specific Comments

On the abstract Section

The objective is missed.

Avoid use of ‘predictors’ in cross sectional studies.

In key words include Gondar.

On the Introduction Section

Is this definition of time the contemporary definition?

What is special about time management for health care workers?

What are the adverse consequences of ineffective time management practice?

The flow lacks coherence. Global, regional and national data on the matter of interest were missed.

On the Methods Section

Start with study setting and tell us your reference.

You didn’t mentioned study design.

Why you used systematic sampling?

Is there no difference between male and female health care professionals? Between diploma and degree holders? Between nurses and medical doctors?

On the Result section

Why don’t you classify residence as urban and rural rather than presenting it as highlanders and lowlanders?

When do we say an individual is satisfied with performance appraisal?

What is your case to variable ratio?

Present some of your findings e.g Proportion of Procrastination

On the Discussion Section

Avoid presenting frequencies.

Reference for your justification is needed. For example “This might be due to unfair relationships between some workers and with the department..” what does that mean? Do you have data on it?

What does organizational policy? Is that norm or some other guiding document? Is that endorsed from ministry of health or?

What are the types of compensations and benefits ? do you have evidence? Needs reference?

On the Conclusion Section

You collected data of 65% from diploma holders and you are concluding for all types of health care workers?

The word ‘poor’ is not ethical.

Implications were missed

Lacks recommendation

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Reviewer #1: Yes: Yes

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Author response to Decision Letter 0

We would like to thanks for these constructive, building and improvable comments on this manuscript that would improve substance and content of the manuscript. We considered each comments and clarification questions of editors and reviewers on the manuscript thoroughly. Our point-by-point responses for each comment and questions are described in detailed on the following pages. Further, the details of changes were shown by track changes in the supplementary document attached.

Editor questions/comments Response

Thanks editor for your constructive comments. Even though there were inadequate literatures related with the problem particularly in Ethiopia we have searched effort fully and included them in the main document.

Methodology

How did you determine the sample size? Dear editor thanks for your constructive comments. The sample size was determined using single population proportion formula, taking 50% prevalence of time management practices (as there was no previous study) with the following assumption: 95% CI and 5% margin of error.

For associated factors of time management practice the sample size was determined by using double population proportion formula and computed by Epi-info version7 software. Thus the minimum adequate sample size for this study was 422 taken from single population proportion formula.

Details about sample size determination were put in the main document.

How did you allocate study participants?

Thanks again for your constructive comments. Proportional allocation of study participants (422 employees) was done for each primary hospital based on the number of employees working in the respective hospitals. Details were described in the main document.

How did you select the study participant? Thanks editor for valuable comment. Study participants were selected by simple random sampling method in each Hospital. Details were presented in the main document.

Where did you get or how did you develop data collection tools or questionnaire in this study? Thanks editor for the comment. The questionnaire was adopted from Advanced corporate training (Time Management Questionnaire) and legal management consultants 2010 and put the citation in the main document.

How did you measure the validity and reliability of the study tools or questionnaire implemented to collect data in this study?

Thanks editor for the comment. To measure the validity of the study tools or questionnaires implemented to collect data in this study we have conducted pretest among 42 participants out of the study area (i.e. Addis-zemen hospital) and training was given for data collectors. Reliability test (Cronbach’s alpha) was performed to check reliability of the questionnaire items.

It is not also clear how the cutoff point made for the Likert scale

Thanks for the comment. Cutoff points for independent variables were made based on their mean values as high (i.e. ≥ the mean score value) and low (i.e. below the mean value). But for the outcome variable i.e. time management practice was high/good if ≥ 65% and low if below 65% which was taken from journal of education and practice (Qteat M, 2014).

How the questionnaire contents organized and formulate to address the objective?

Thanks editor for the comment. In this study Questionnaire contents were organized by themes or main concepts from simple to complex for ease of respondents.

What is the dependent variable in this study? It looks like level of time management practice appears to be the dependent variable. Similarly, would be good to define those factors indicated in this study as well.

Thank you editor for this constructive comment. The dependent variable of the study is time management practice not the level of time management practice and it was corrected and operationalized in the main document accordingly.

We have also defined factors in the main document.

Maybe, it would be useful if you depict the response rate in percent than numbers for simplicity. Thanks for the comment. We have depicted the response rate as 92.65% in the main document.

It looks like there is a kind of mingling between the sub-topics “time management practices, organizational policies, employees’ performance and personal factors” and “factors associated with time management practice”. Either you need to modify the first sub topic or merge with the second topic.

Thank you editor for the comment. We have modified the first subtopic in the main document and expressed it correctly as organizational policies, employees performance and personal factors of respondents.

It is not clear, for instance, on the first paragraph you indicated that “the proportion of time management practice among employees was 56.4%” what does the word proportion designate in this sentences? There is similar inconsistency throughout the document that has to be fixed. Thank you editor for the comment. We have changed proportion to prevalence and corrected as “the overall prevalence of time management practice among employees was 56.4%”. We have also made similar change throughout the document.

In addition to this, you need to use studies that are closely related to your study setting at various measuring scale to make plausible comparison. Otherwise, citing studies which never have related to your study setting will affect the analysis and the entire result one or another way. Thank for the comment. Even though there were inadequate literatures we have included almost related studies to our setting in the main document.

Thank you editor for the comment. We have included the limitation of the study in main document.

You have inscribed your suggestion and recommendation at the abstract section, but not in this section Thanks again for the comment. We have included recommendations in the main document according to your query.

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Reviewer #1

General comment

Is there an African / Ethiopia perspective of time? Thanks reviewer for your comment.

Thus the African understands time as consisting of a long past and a present with virtually no future. This contrasts with the Western concept of time which is linear, consisting of an indefinite past, the present and infinite future. For the African, the future is absent since it has not been realized. African time or Africa time is the perceived cultural tendency, in parts of Africa and the Caribbean toward a more relaxed attitude to time.

An African "emotional time consciousness" has been suggested which contrasts with Western "mechanical time consciousness". African cultures are often described as "polychronic", which means people tend to manage more than one thing at a time rather than in a strict sequence. Personal interactions and relationships are also managed in this way, such that it is not uncommon to have more than one simultaneous conversation.

The timezone in Ethiopia is EastAfricaTime (EAT) (UTC+03:00). Almost all Ethiopians use a 12-hour clock system. The daytime cycle begins at dawn 12:00 (6:00:00 AM EAT) and ends at dusk 11:59:59 (5:59:59 PM EAT). The night time cycle begins at dusk 12:00 (6:00:00 PM EAT) and ends at dawn 11:59:59 (5:59:59 AM EAT). The convention is that the day begins at 1:00 o'clock in the morning 12 hour cycle (7:00 AM EAT) rather than midnight (12:00 AM EAT). Therefore, the local population almost effectively observes UTC-03:00.

What are the dimensions of time? Thanks reviewer for your comments. Time is the dimension that allows things to do it, which is why we can measure the duration that they last or how fast they move. Space is where these things are and happen. Time and space are inextricably connected into what’s called the space-time continuum. The normal three dimensions including up-down, left-right, forward-back, and space-time. Two-dimensions of time would make time travel possible. Instead of being linear, at some point time loops back on itself. In this way, you could travel back or forward in time.

abstract Section

The objective is missed Thanks reviewer for your comments. We have included the objective in the main document.

Avoid use of ‘predictors’ in cross sectional studies. Thank you reviewer for the comment and we have replaced predictors with factors associated with in the main document.

In key words include Gondar Thanks again for the comment. We add Gondar in the key word in the abstract section of main document.

Is this definition of time the contemporary definition? Thanks reviewer for the comment. The definition of time was adopted from Mariam Webster dictionary and it is the contemporary definition used in this study.

What is special about time management for health care workers? Thanks again for the comment.

Time management is about how one manages self. One cannot manage the time; one can only manage how he/she can use it. Organizing and prioritizing the patient care activities is of prime importance for providing quality care and to maintain the personal and professional balance. If healthcare workers spent their time out of serving their patient even within seconds they may lose lives and that is why time management for health care professionals is highly important priority issue.

Thanks again for the comment. Some of the adverse consequences of ineffective time management practice are habitual lateness, overextension, inability to achieve goals, lack of success, and lack of confidence, stress, and ineffectiveness in one’s job as mentioned in many management books.

The flow lacks coherence. Global, regional and national data on the matter of interest were missed. Thanks again for the comment. We have corrected the flow of ideas and incorporated global, national and regional data on time management practices in the main document.

Start with study setting and tell us your reference. Thanks reviewer for the comment. We have started with study setting and put the reference i.e. from North Gondar health department’s plan office data and corrected accordingly in the main document.

You didn’t mentioned study design. Thanks reviewer for the comment. We have mentioned the study design i.e. institutional based cross-sectional study design was used for this study in the main document.

Why you used systematic sampling? Thank you reviewer for this fruitful comment. Systematic sampling was inappropriate technique for this study and we have used appropriate sampling technique i.e. Simple random sampling and corrected accordingly in the main document.

Is there no difference between male and female health care professionals? Between diploma and degree holders? Between nurses and medical doctors Thanks again for the comment. In this study the difference is their profession but regarding to our outcome variable every healthcare worker are expected to have almost the same time management practice for their own task because every task performance according to their time in the health care setting has a great place in the accomplishment of organizations goal.

Why don’t you classify residence as urban and rural rather than presenting it as highlanders and lowlanders? Thanks reviewer for the comment. In this study residence is classified as highlanders and lowlanders but not as urban and rural because all primary hospitals are located in the surrounding rural districts of North Gondar zone. Rather primary hospitals are found in the highlands and lowlands that is why we classified residence as highlanders and lowlanders. Those employees who are working in hospitals found in the highland were classified as highlanders and those working in hospitals found in lowland were classified as lowlanders.

Thanks again for the comment. In this study when individuals are satisfied with performance appraisal if their response to the five items of five point likert scale questionnaires is above or equal to the mean score value of performance appraisals.

Thank again for the comment. In this study case to variable ratio is 0.565 (i.e. 221: 391 or 221/391).

Present some of your findings e.g. Proportion of Procrastination Thanks for the comment. We have presented the findings clearly in the main document e.g. proportion of procrastination was 81.1% (i.e. 317 out of 391), planning was 80.8% (i.e. 316 out of 391) and also for others.

Avoid presenting frequencies. Thanks reviewer for the comment. We avoid frequencies from the main document and corrected it according to your inquiry.

Reference for your justification is needed. For example “This might be due to unfair relationships between some workers and with the department..” what does that mean? Do you have data on it? Thanks reviewer for this golden comment. We have put reference for justifications in the main document.

Thanks again for the comment. It is from the guiding document from ministry of health of Ethiopia that fosters positive working environment in the primary hospitals and the tools were prepared to assess the implementation of the policy and the working cultures of the hospitals as a factor for their time management practice.

What are the types of compensations and benefits? Do you have evidence? Needs reference? Thanks for the comment. Types of compensations and benefits like financial, material, training, educational etc… are expected to be fulfilled for health care workers as to their educational level and performance. The evidence was from the human resource management for health guidelines of Ethiopian primary hospitals (EHRIG, 2014).

Thanks reviewer for the comment. In Ethiopian context most of the primary hospitals are equipped with diploma holders staffs, hence degree and above degree holder staffs are low in number as compared to diploma holders, as our study showed from nine primary hospitals 65% of employees were diploma holders. This is according to the Ethiopian primary hospital standard guideline profession mix.

The word ‘poor’ is not ethical

Thanks reviewer for the comment. We have used good or poor time management practice according to literature’s but now we have changed into high or low time management practice and corrected accordingly in the main document.

Implications were missed Thanks again for the comment and we have included the implications of the study in the main document. The study could have valuable implication to formulate appropriate strategies by different stakeholders involved in hospital administration and management programs, and other related public health interventions. It has helped to enhance and upgrade participants’ understanding about time management; and to equip them with major techniques of time management. This study could also provide information to subsequent researchers on time management practices and factors associated with it.

Thanks again for the comment. We have added recommendation in the main document. Thus it is recommended that hospital employees must give special emphasis about planning to improve their time management practice. Hospital Managers need to assess and improve organizational policies and strategies and performance appraisal systems practicing in the respective hospitals to treat employees fairly and equally. It is recommended that Amara National Regional Health Bureau strengthen regular supportive supervision to the hospitals and time management training programs must be provided to hospital staffs in varies level at different health setting. It is recommended to conduct further research on the issue by extending the study setting and the study population.

Submitted filename: Response to reviewer.docx

Decision Letter 1

15 Nov 2019

PONE-D-19-24146R1

Dear Erkihun Tadesse,

I do appreciated that you tend to incorporate the comments and feed backs given on the first submission. The second submission seems to be more organized and includes opinions relevant information to improve this manuscript. Being said that I have notice  few gaps that need to be address and bridge the gap and move forward to the  next phase of your manuscript.

• The introduction in the abstract section need to be shorten and depict time management and purpose of the study in a clear fashion. In general, this section must show the entire study with limited words if possible with in one page.
• The introduction looks more organized and includes relevant literature that could be useful to make good argument.
• Methods:- I haven't seen a single statement that show the operational definition of your study variable. It would be also very useful to include the dependent and independent variable and its operational definition to provide a clear picture of this study.
• The result section appears to be improved at a different perspective, however, I recommend you to separate the subtopic organization policy, employment performance and personal factors. Perhaps, that would help you to show the detail analysis of this study. 
• The discussion well written and improved significantly. However, still you need to keep the flow of the write up based on the analysis on the result section, which will help you maintain  the coherence of statement in alignment with the result section. 

We would appreciate receiving your revised manuscript by Dec 30 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

I do appreciated that you tend to incorporate the comments and feed backs given on the first submission. The second submission more organized and include opinions relevant to improve this manuscript. Being said that I have notice few gaps that need to be address to move the next phase of your manuscript.

- The introduction in the abstract section need to be shorten and show time management and purpose of the study. Overall, this section should briefly depict the entire study as least in one page.

-The introduction looks more organized and includes relevant literature that could be useful to make good argument.

-Methods:- I haven't seen a single statement that show the operational definition of the study variable in this study. Would be also very useful to include the dependent and independent variable and its operational definition to provide a clear picture of this study.

-The result section appears to be improved at a different perspective, however, I recommend you to separate the subtopic organization policy, employment performance and personal factors. Perhaps, that would help you to show the detail analysis of this study.

-The discussion well written and improved significantly. However, still you need to keep the flow of the write up based on the analysis on the result section, which will help you maintain the coherence of statement in alignment with the result section.

Author response to Decision Letter 1

29 Nov 2019

The introduction in the abstract section need to be shorten and depict time management and purpose of the study in a clear fashion. In general, this section must show the entire study with limited words if possible with in one page.

Thanks editor for your constructive comment. We have corrected this section by depicting time management practice and purpose of the stud in the main document according to your query.

I haven't seen a single statement that shows the operational definition of your study variable. It would be also very useful to include the dependent and independent variable and its operational definition to provide a clear picture of this study. Dear editor thanks for your constructive comments. We have included the dependent and independent variable, and its operational definition in the main document as shown in the truck number from 146 – 192.

The Result section appears to be improved at a different perspective, however, I recommend you to separate the subtopic organization policy, employment performance and personal factors.

Thank you editor for the comment. We have separated the organization related factors of respondents, Employees performance related factors and personal related factors of respondents separately in the main document.

The discussion well written and improved significantly. However, still you need to keep the flow of the write up based on the analysis on the result section, which will help you maintain the coherence of statement in alignment with the result section.

Thank you editor for the comment. We have arranged the discussion section according to the result section in the main document.

Submitted filename: Response to reviewer final.docx

Decision Letter 2

27 Dec 2019

PONE-D-19-24146R2

Assessment of time management practice and associated factors among primary hospitals employees of in north Gondar, northwest Ethiopia

We would appreciate receiving your revised manuscript by Feb 10 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

I would like again to commend authors for the prompt work to improve the manuscript. The manuscripts appears to be further improved from the original submission.

Briefly illustrate the overall of the study and provides precise information.

I have noted the significant change made on the background section. I advise you to remove the last statement after the purpose of the study that appears to be a recommendation and the quote to refer previous study, you don’t have a tangible assertion whether the same topic conducted or not in Ethiopia setting. Please remove the following paragraph “which was not studied previously. Thus the findings from the study would provide valid information for policy makers, managers and stakeholders for taking appropriate action to improve time management practice.”

This section seems well written and have significant improvement. It composed of necessary tools to undertake the study.

It seems to have included the comments provided by the reviewers. The statistical analysis sound and genuine.

The big gap I have noticed in this section is most of the arguments have never been supported by study or evidence. Your arguments need to have reasonable evidence. Your assumption to elucidate the discrepancy originally inferred based on what you thought about it, which is not scientifically sound even if your arguments are correct. There is plenty of research out there that would support your assumption, hence I recommend you to rewrite this section using references that bolster your assertion.

Conclusion:

Make sure your conclusion and recommendation based on merely on the finding of this study. Don’t try to additional points out this study context.

Author response to Decision Letter 2

31 Dec 2019

Rebuttal letter Date: January/01/2020

Erkihun Tadesse

I advise you to remove the last statement after the purpose of the study that appears to be a recommendation and the quote to refer previous study, you don’t have a tangible assertion whether the same topic conducted or not in Ethiopia setting.

Please remove the following paragraph “which was not studied previously. Thus the findings from the study would provide valid information for policy makers, managers and stakeholders for taking appropriate action to improve time management practice.” Thanks editor for your constructive comment. We have removed the paragraph “which was not studied previously. Thus the findings from the study would provide valid information for policy makers, managers and stakeholders for taking appropriate action to improve time management practice.” Expressed as Therefore, this study aimed to assess time management practices and associated factors among employees of primary hospitals in North Gondar Zone.

Your arguments need to have reasonable evidence. Your assumption to elucidate the discrepancy originally inferred based on what you thought about it, which is not scientifically sound even if your arguments are correct. There is plenty of research out there that would support your assumption, hence I recommend you to rewrite this section using references that bolster your assertion. Thank you editor for the comment. We have supported the arguments/assumptions using references and corrected according to your inquiry in the main documents.

Thank you editor for constructive comments. We have presented the conclusion and recommendation based on the finding of this study and corrected according to your inquiry.

Submitted filename: Response to reviewer [email protected]

Decision Letter 3

PONE-D-19-24146R3

Dear Dr. Erkihun Tadesse,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Additional Editor Comments (optional):

Acceptance letter

10 Jan 2020

Dear Dr. Amsalu:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Educational resources and simple solutions for your research journey

Time Management in Research: 10 Strategies to Boost Your Productivity

As researchers, at least once in our lives we have missed an important deadline, and while feeling stressed, wondered how we could have planned our tasks better and managed our time well, isn’t it? Hence, as we do our research, time management becomes one of the most essential skills to possess.

Efficient time management for researchers isn’t as easy as you’d think and the importance of time management in research is almost always undervalued. A researcher’s day is usually packed with tasks including, but not limited to, working on manuscripts, preparing presentations, conducting studies, teaching, and mentoring students to name a few. While researchers juggle these research-related tasks, they also manage logistics and admin tasks. Therefore time management in research often becomes a sinking ship. Moreover, unexpected factors lead to delays and researchers are left with decreased productivity and much less time than they imagine.

Therefore, time management for researchers is important to have a smoother and happier research journey. It would not be an exaggeration to say that for you, the researcher, time management is the key to success.

We would like to share with you some tried and tested time management strategies for research productivity that many of your peers have applied to their lives successfully.

1. It’s okay to say “no”: One of the least discussed tips on time management for researchers is that as a researcher, you’ll often have to prioritize your tasks, and at times turn down tasks or requests if they won’t help you achieve your goals. When you have too much on your plate, ask yourself if you can postpone any of the tasks and concentrate on high impact activities. For example, you may have to choose between attending a conference on a related field and using that time to work on your manuscript.

2. Embrace digital tools for researchers: Wouldn’t you agree that making plans is often the easier part and staying on track is challenging? With the increased availability of digital tools for researchers, planning and organizing has become much easier. You can use online project management and planning tools (such as  Asana ,  Trello , and  ProofHub ) to manage your tasks in a structured way. Rest assured, these tools will bring you closer to your goal of time management in research.

But that is not all! As a researcher, staying abreast of goings-on in your subject area is crucial for you. AI-powered digital tools for researchers like R Discovery can help you save 50% of reading time  by providing recommended articles in the most personalized way based on topics and subject area that you prefer. You can access the papers most relevant to you from over 90 million papers available on R Discovery. So digital tools for researchers like R Discovery can be great assistants in helping you manage your time more effectively.

3. Multitask to quicken the work pace: One of the popular time management strategies for research productivity is to work on multiple tasks without spreading yourself too thin. Multitasking, when planned well, can help you save time and make consistent progress. For instance, you can start writing your Methods section right as you are conducting your experiment. This will help improve time management for researchers in two ways: you won’t have to wait to complete your study to write your paper, and you’ll be able to complete the task faster as you’ll clearly remember all the details.

4. Set realistic deadlines:  If your goal is to eat an entire cake by yourself, it would be pretty tough to do so in one bite, isn’t it? It’s advisable to create smaller milestones when trying to accomplish a bigger goal or overcome a challenge. One of the most important tips for time management in research would be to split the goal into multiple tasks, consider factors that may pose challenges, and set attainable timelines accordingly.

Keeping a tight schedule may seem a good idea at the outset but eventually can lead to counter-productivity, loss of motivation, and early burnout. So one way to optimize time management for researchers to ensure you complete tasks within timelines is by keeping aside some buffer time for each task. You may benefit from this  blog  by Dr. Raul Pacheco-Vega, an Assistant Professor at a university in Mexico, where he shares how changing his perspective of goal setting helped him create feasible goals for himself.

5. Maintain a to-do list: Another of our important tips for time management in research is to make it a habit to plan your day by jotting down priority tasks. You could do this first thing in the morning or at the end of your day (if you want to plan your next day). Having a clear picture of what your priorities for the day are can help you plan your day better and complete your tasks more efficiently. And you’re less likely to miss any deadline. Also, striking off tasks on your to-do list each day is satisfying and motivating. Use one of the digital tools for researchers mentioned above and try it yourself!

6. Complete high-priority tasks first: Often called the “eat a frog” technique of time management for researchers and non-academics, this can be extremely effective is done properly. Many researchers find it useful to block time at the beginning of their day for tasks that need more time, energy, and concentration. When a major chunk of your daily tasks is ticked off at the start of your day, it gives you a sense of accomplishment and keep you motivated for the entire day.

“When you begin your day by reading messages, you are prioritizing other people’s requests before taking action towards your long-term goals… To make consistent progress, begin your day by doing the highest priority task,” says Dora Farkas, PhD from MIT and founder of the Finish Your Thesis Academy in her  blogpost  on time management for researchers.

7. Eliminate disturbances: Block some time of your day to focus on your work and get things done. Here are a few time management strategies for research productivity that will help you stay focused.

• Turn off push notifications on your phone.
• Turn on the ‘do not disturb’ mode on your phone.
• Avoid the temptation to read and respond to any emails.

8. Avoid delaying tasks: One of the most important time management tips for and researchers  –  Don’t slow down your journey towards your publication goal by procrastinating. Most of us avoid tasks that we don’t like or find challenging. However, delaying even one task can wreak havoc on your deadlines. An  amazing trick by Agata, a PhD student in the University of Nottingham to avoid procrastination is to have plans after work. It helps improve time management for researchers by pushing you to finish your work on time, which increases your productivity significantly.

9. Don’t precrastinate: That’s not a typo! We’ve all been guilty of precrastination – the act of picking lesser important tasks to avoid doing an important task that we find challenging or are uninterested in. So, when talking about time management for researchers, it’s important to resist going down that path; look at the bigger picture – your publication goal. Stay motivated and remember why you started. For example, responding to emails that are not urgent instead of working on your literature review report using literature review tools is an act of precrastination.

10. Take guilt-free breaks: Value the importance of time management in research – but that does not mean you need to overburden yourself. That 10-minute break to brew yourself a cup of coffee is not a waste of time! It is a fact that taking breaks after focused sessions of one or two hours can boost your productivity and is a great way to improve time management for researchers. Use these breaks for activities that you like and will help you relax. From taking a half an hour walk, meditating for a couple of minutes, or enjoying a cup of coffee in your balcony, it will help you rejuvenate for another focused session. Larger breaks are equally important, and many often leave this out when listing time management tips for researchers. When you spend time with friends, family, and with oneself, it brings out the best in you at work, so make sure to include breaks in your schedule.

To sum up our list of tips on time management for researchers, while it is important to have a plan, it is best not to set it in stone. Time management for scientists and researchers starts with maintaining a balance between the daily activities. It is okay to relax or have a less productive day once in a while. To get the most out of your day, take a hard look at your goals, plan according to what works best for you (use digital tools for researchers to simplify this), and revise your plan as and when required. Stay focused on your goals but keep some room to mold your plan as required. Hopefully, as you use these time management strategies for research, productivity and efficiency are only going to get better.

Let’s close by reiterating why time management for researchers is an important skill to have

• Prevents last-minute stress
• Increases your productivity exponentially
• Avoids delays in submissions
• Improves your work efficiency
• Keeps tasks organized
• Reduces chances of missing important information or tasks

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

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The Importance of Time Management

The definition of the concept of time has been associated with ambiguities and even contradictions. For instance, time has been described as “time nothing more than the occurrence of events in sequence, on after another” (Olpin and Hessen, 2012, p.167), and “a resource that, when lost or misplaced, is gone forever” (Kerzner, 2009, p.286).

The definition of time management has been offered as “the process of skilfully applying time to finish and perfect a specific activity within time constraint” (Harris, 2008, p.22). However, there is no single definition of time that fully captures all aspects of the concept.

Becker and Mustric (2008) divide time into two categories: quantitative and qualitative. It can be specified that “quantitative time is seen to represent time as quantities, that is, time can be measured and counted into seconds, minutes, days, weeks, months, and years” (Wu, 2009, p.5). Qualitative time, on the other hand, is associated with a meaning of an activity the time is spent on.

Similar to the concept of time, there are varying opinions amongst secondary data authors regarding the definition and role of time management. For instance, it has been noted that “time management is about taking charge, carefully, consciously, purposefully – not shrinking from difficulties, but engaging them” (Kristan, 2010, p.4).  Moreover, some secondary data authors also note that “time management is not an end itself. It is the means to an end. When linked with setting and meeting goals it provided a way of getting really high achievement out of individuals and others with whom they come into contact” (Pearson and Thomas, 2010, p.49).

Marquis and Huston (2009), on the other hand, disagree with the term of time management, and argue that time cannot be managed in any ways, but rather individuals can manage events in their lives in relation to time.

At the same time, it has been warned by some secondary data authors that “time management must not be seen as only concerned with packing more activity on the available time, though this may be part of it; it must be in ensuring that objectives are met” (Forsyth, 2010, p.13). Moreover, it has also been stated that  “time management is not about creating more time but rather about making the best use of the time we have” (Hansen, 2011, p.3).

The majority of publications devoted to the issues of time management discuss the advantages of effective management of time and offer techniques that can be used in order to achieve this objective.

For instance it has been stated that “when we manage our time more effectively and efficiently, we reduce stress and frustration, we become more confident, and we feel better” (Mancini, 2007, p.viii). Moreover, some secondary data authors convincingly argue that “with proper planning and some self-discipline, many urgent matters disappear altogether or, when they do surface, your planning and discipline makes them less urgent and easier to deal with” (Rivera, 2007, p.51).

Moreover, authors state that “the benefits of time management are many. Rather than running around in a state of frenzy, you feel a sense of empowerment from getting things done and having the time to enjoy life’s simple pleasures” (Seaward, 2011, p.134).

Furthermore, the additional advantages of time management have been highlighted by secondary data authors as being more productive (Green and Skinner, 2005, Alexander and Dobson, 2008), having more energy to accomplish tasks (Limoncelli, 2006, Becker and Mustric, 2008, Christie, 2009), feeling less stressed (Bhugra and Howes, 2007, Brott, 2008, Christie, 2009), possibility to pursue personal interests (Felton and Sims, 2009), getting more things done (Green and Skinner, 2005, Mustric, 2008), relating to others in more positive manner (Bhugra and Howes, 2007), and feeling better about self (Brott, 2008).

Secondary data authors stress that time management principles can be and have to be mastered by everyone regardless the nature of the their employment, age, religion or any other demographic or other variables. Namely, it has been said that “given the right intention, and motivation, it is possible for anyone to improve their time utilisation and to do so markedly of you have not thought about it recently” (Forsyth, 2010, p.8).

Major Concepts and Ideas Associated with Time Management

First of all, it is important to note that “in spite of all popular attention to managing time, relatively little research has been conducted on the process involved in using one’s time effectively (e.g. by using “prime time” to carry out important tasks) and completing work within deadlines” (Claessens et al, 2007, p.256)

According to Fleming (2011) an effective time management is closely associated with an understanding the difference between efficiency and effectiveness. Fleming (2011) clarifies that while efficiency involves completing specified tasks in a right manner, effectiveness relates to identifying the right tasks to be accomplished in the first place.

A similar viewpoint is expressed by Fleming (2011) as well, who argues that the practice of identification of strategic tasks in an appropriate manner, and the selection of appropriate tools and techniques for the completion of those tasks can be considered the most basic conditions of effective time management.

Singh (2008) points to two fundamental aspects associated with the concept of time:

a)    The sequence, and more precisely, the order of the changes;

b)    The duration of the changes or of the period between them.

Felton and Sims (2009), on the other hand, closely associate the concept of time management with one’s self management. The authors assert that “the focus of time management is priorities and stems from self-management. Self-management is the powerhouse of time management” (Felton and Sims, 2009, p.21).

Zeller (2008) expands this idea and stresses the importance of having an effective personal system of time management along with a comprehensive Specifically, the author reasons that “effective time management requires more than good intent and self-knowledge” (Zeller, 2008, p.14), and a good system consisting of specific processes need to be put in place in order to engaged in time management in an efficient manner. The specific processes involved in time management are specified by Downs (2008) as setting priorities, analysing, filtering, scheduling and executing.

The importance of environmental factors in effective management of time has been mentioned by Singh (2008), Forsyth (2010), and Silvis (2011). All of these authors give credit to Schematic Model of Factors Affecting Time Use proposed by Robinson (1977) in terms of classification and presentation of environmental factors affecting use of time in an effective manner. Moreover, Singh (2008) argues that despite the fact that more than three decades have passed from the introduction of Schematic Model of Factors Affecting Time Use the importance of the model has not been compromised.

Adair, J & Allen, M. (1999) “Time Management and Personal Development” Hawksmere Alexander, R & Dobson, M.S. (2008) “Real-world time management” AMACOM Barling, J., Kelloway, E. K. & Cheung, D. (1996). “Time management and achievement striving interact to predict car sale performance”  Journal of Applied Psychology ,  81 , 821-826. Becker, H & Mustric, F. (2008) “Can I Have 5 Minutes of Your Time?” Morgan James Publishing Beevers, R. (2006) “Customer Service Excellence in the Public Sector”, Northern Housing Consortium Bhugra, D. & Howes, O. (2007) “Handbook of Psychiatric Trainees” RCPsych Publications Blaxter, L, Hughes,C & Tight, M. (2006) “How To Research” 3 rd  edition, McGraw-Hill Bond, M. & Feather, N. (1988) “Some correlates of structure and purpose in the use of time”  Journal of Personality and Social Psychology Boone, LE & Kurtz, DL (2010) “Contemporary Business” John Wiley & Sons Brink, H, Walt, C.V & Rensburg, G.V. (2005) “Fundamentals of Research Methodology for Helath-Care Professionals” Juta Online Brott, R. (2008) “Successful Time Management: Be the Productive Person You Want to Be” ANC Book Publishing Buchbinder, S.B & Thompson, J.M. (2010) “Career opportunities in health care management” Jones and Bartlett Learning Butler, G & Hope, T. (2007) “Managing Your Mind: The Mental Fitness Guide” Oxford Christie, S. (2009) “Effective time management for doctors” Developmedica Claessens, J.C., Eerde, W. & Rutte, C.G. (2007) “A Review of the time management literature”  Personnel Review , Vol. 36, pp. 255 – 276 Covey, S. (1990) “ The Seven Habits of Highly Effective People”  Fireside Denscombe, M. (2010) “The Good Research Guide for Small-Scale Social Research Projects” fourth edition. Denhardt, R.B. (2010) “Theories of Public Organisation” Cengage Learning Decrop, A. (2006) “Vacation decision making” CABI Dodd, P & Sundheim, D. (2011) “The 25 Best Time Management Tools and Techniques: How to Get More Done Without Driving Yourself Crazy” John Wiley & Sons Downs, L.J. (2008) “Time Management Training2 ASTD Engel, R.J. & Schutt, R.K. (2009) “Fundamentals of Social Work Research” SAGE Publications Evans, C. (2008) “Time Management for Dummies” John Wiley & Sons Felton, S & Sims, M. (2009) “Organising Your Day: Time Management Techniques That Will Work for You” Revell Fleming, I. (2011) “The Time Management Pocketbook” 6 th  edition, Management Pocketbooks Flynn, N. (2007) “Public Sector Management” 5 th  edition, SAGE Publications Forsyth, P. (2010) “Successful Time Management” Kogan Page Green, P & Skinner, D. (2005) “Does time management training work? An evaluation”  International Journal of Training and Development  Volume 9, Issue 2, pp. 124 – 139

Harris, J. (2008) “Time Management 100 Success Secrets: The 100 Most Asked Questions on Skills, Tips, Training, Tools and Techniques for Effective Time Management” Lulu Publications

Hillestad, S.G & Berkowitz, E.N. (2004) “Health care market strategy: from planning to action” Jones and Bartlett Learning Kassel, D.S. (2010) “Managing Public Sector Projects: A Strategic Framework for Success in an Era of Downsized Government” Taylor & Francis

Kerzner, H. (2009) “Project Management: A Systems Approach to Planning, Scheduling, and Controlling” John Wiley & Sons

Kristan, P. (2010) “Awakening in Time: Practical Time Management for Those on a Spiritual Path” Dog Ear Publishing

Lakein, A. (1973) “How to Get Control of Your Time and Your Life” P.H. Wyden New York Limoncelli, T. (2006) “Time management for system administrators” O’Reilly Macan, T. H. (1996 “Time management training: Effects on time behaviours, attitudes, and job performance”  Journal of Psychology ,  130 , 229-236 Managing Interruptions. (2011) Available at:  http://www.time-management-success.com/managing-interruptions.html   Accessed November 13, 2011

Marquis, B.L. & Huston, C.J. (2009) “Leadership roles and management functions in nursing: theory and application” Wolters Kluwer Health

Matsuo, M. (2005) “The role of internal competition in knowledge creation: an empirical study of Japanese firms” Peter Lang Mancini, M. (2007) “Time Management: 24 Techniques to Make Each Minute Work” McGrow-Hill Mudrack, P. E. (1997) “The structure of perceptions of time”  Educational and Psychological Measurement ,  57 , 222-240

Olpin, M. & Hesson, M. (2012) “Stress Management for Life: A Research – Based Experiential Approach” Cengage Learning Randel, J.(2010) “The Skinny on Time Management: How to Maximise Your 24-Hour Gift” RAND Media Co Rivera, C. (2007) “Time Management” Global Media Seaward, B.L. (2011) “Essentials of Managing Stress” Jones and Bartlett Learning Seaward, B.L & Seaward, B. (2011) “Managing Stress: Principles and Strategies for Health and Well-Being” Jones and Bartlett Learning Secunda, A. (1999) “ The 15 second principle : short, simple steps to achieving long-term goals ” Berkley Books Silvis, C. (2011) “Time Management and Organisation for Writers” in 2012 Writer’s Market Simmons, S. (2011) “9 Ways to Handle Interruptions Like a Pro” Available at:  http://www.lifehack.org/articles/lifehack/9-ways-to-handle-interruptions-like-a-pro.html   Accessed December, 2, 2011. Singh, U.B. (2008) “Time Management: A Study of HRD Managers” Kalpaz Publications Starling, G. (2010) “Managing the Public Sector” Wadsworth Tobis, M & Tobis, I. (2002) “Managing multiple projects” McGraw-Hill Professional Tracy, B. (2007) “Eat That Frog! 21 Great Ways to Stop Procrastinating and Get More Done in Less Time” Berrett-Koehler Store Walsh, R. (2008) “Time Management: Proven Techniques for Making Every Minute Count”  Adams Media Waterworth, S. (2003) “Time management strategies in nursing practice” Journal of Advanced Nursing, Volume 43, Issue 5, pp. 432 – 440 Wirick, D.W. (2009) “Public-Sector Project Management: Meeting the Challenges and Achieving the Results” John Wiles & Sons

Wu, D. (2009) “Temporal Structures in Individual Time Management: Practices to Enhance Calendar Tool Design” IGI

Wysocki, D.K. (2007) “Readings in Social Research Methods” Cengage Learning Yager, J. (2008) “Work Less, Do More: The 14-Day Productivity Makeover, Barnes & Noble Zapico-Goni, E & Wholey, J. (2007) “Monitoring Performance in the Public Sector,” Transaction Books Zeller, D. (2008) “Successful Time Management for Dummies” For Dummies

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Home » Research Gap – Types, Examples and How to Identify

Research Gap – Types, Examples and How to Identify

Table of Contents

Research Gap

Definition:

Research gap refers to an area or topic within a field of study that has not yet been extensively researched or is yet to be explored. It is a question, problem or issue that has not been addressed or resolved by previous research.

How to Identify Research Gap

Identifying a research gap is an essential step in conducting research that adds value and contributes to the existing body of knowledge. Research gap requires critical thinking, creativity, and a thorough understanding of the existing literature . It is an iterative process that may require revisiting and refining your research questions and ideas multiple times.

Here are some steps that can help you identify a research gap:

• Review existing literature: Conduct a thorough review of the existing literature in your research area. This will help you identify what has already been studied and what gaps still exist.
• Identify a research problem: Identify a specific research problem or question that you want to address.
• Analyze existing research: Analyze the existing research related to your research problem. This will help you identify areas that have not been studied, inconsistencies in the findings, or limitations of the previous research.
• Brainstorm potential research ideas : Based on your analysis, brainstorm potential research ideas that address the identified gaps.
• Consult with experts: Consult with experts in your research area to get their opinions on potential research ideas and to identify any additional gaps that you may have missed.
• Refine research questions: Refine your research questions and hypotheses based on the identified gaps and potential research ideas.
• Develop a research proposal: Develop a research proposal that outlines your research questions, objectives, and methods to address the identified research gap.

Types of Research Gap

There are different types of research gaps that can be identified, and each type is associated with a specific situation or problem. Here are the main types of research gaps and their explanations:

Theoretical Gap

This type of research gap refers to a lack of theoretical understanding or knowledge in a particular area. It can occur when there is a discrepancy between existing theories and empirical evidence or when there is no theory that can explain a particular phenomenon. Identifying theoretical gaps can lead to the development of new theories or the refinement of existing ones.

Empirical Gap

An empirical gap occurs when there is a lack of empirical evidence or data in a particular area. It can happen when there is a lack of research on a specific topic or when existing research is inadequate or inconclusive. Identifying empirical gaps can lead to the development of new research studies to collect data or the refinement of existing research methods to improve the quality of data collected.

Methodological Gap

This type of research gap refers to a lack of appropriate research methods or techniques to answer a research question. It can occur when existing methods are inadequate, outdated, or inappropriate for the research question. Identifying methodological gaps can lead to the development of new research methods or the modification of existing ones to better address the research question.

Practical Gap

A practical gap occurs when there is a lack of practical applications or implementation of research findings. It can occur when research findings are not implemented due to financial, political, or social constraints. Identifying practical gaps can lead to the development of strategies for the effective implementation of research findings in practice.

Knowledge Gap

This type of research gap occurs when there is a lack of knowledge or information on a particular topic. It can happen when a new area of research is emerging, or when research is conducted in a different context or population. Identifying knowledge gaps can lead to the development of new research studies or the extension of existing research to fill the gap.

Examples of Research Gap

Here are some examples of research gaps that researchers might identify:

• Theoretical Gap Example : In the field of psychology, there might be a theoretical gap related to the lack of understanding of the relationship between social media use and mental health. Although there is existing research on the topic, there might be a lack of consensus on the mechanisms that link social media use to mental health outcomes.
• Empirical Gap Example : In the field of environmental science, there might be an empirical gap related to the lack of data on the long-term effects of climate change on biodiversity in specific regions. Although there might be some studies on the topic, there might be a lack of data on the long-term effects of climate change on specific species or ecosystems.
• Methodological Gap Example : In the field of education, there might be a methodological gap related to the lack of appropriate research methods to assess the impact of online learning on student outcomes. Although there might be some studies on the topic, existing research methods might not be appropriate to assess the complex relationships between online learning and student outcomes.
• Practical Gap Example: In the field of healthcare, there might be a practical gap related to the lack of effective strategies to implement evidence-based practices in clinical settings. Although there might be existing research on the effectiveness of certain practices, they might not be implemented in practice due to various barriers, such as financial constraints or lack of resources.
• Knowledge Gap Example: In the field of anthropology, there might be a knowledge gap related to the lack of understanding of the cultural practices of indigenous communities in certain regions. Although there might be some research on the topic, there might be a lack of knowledge about specific cultural practices or beliefs that are unique to those communities.

Examples of Research Gap In Literature Review, Thesis, and Research Paper might be:

• Literature review : A literature review on the topic of machine learning and healthcare might identify a research gap in the lack of studies that investigate the use of machine learning for early detection of rare diseases.
• Thesis : A thesis on the topic of cybersecurity might identify a research gap in the lack of studies that investigate the effectiveness of artificial intelligence in detecting and preventing cyber attacks.
• Research paper : A research paper on the topic of natural language processing might identify a research gap in the lack of studies that investigate the use of natural language processing techniques for sentiment analysis in non-English languages.

How to Write Research Gap

By following these steps, you can effectively write about research gaps in your paper and clearly articulate the contribution that your study will make to the existing body of knowledge.

Here are some steps to follow when writing about research gaps in your paper:

• Identify the research question : Before writing about research gaps, you need to identify your research question or problem. This will help you to understand the scope of your research and identify areas where additional research is needed.
• Review the literature: Conduct a thorough review of the literature related to your research question. This will help you to identify the current state of knowledge in the field and the gaps that exist.
• Identify the research gap: Based on your review of the literature, identify the specific research gap that your study will address. This could be a theoretical, empirical, methodological, practical, or knowledge gap.
• Provide evidence: Provide evidence to support your claim that the research gap exists. This could include a summary of the existing literature, a discussion of the limitations of previous studies, or an analysis of the current state of knowledge in the field.
• Explain the importance: Explain why it is important to fill the research gap. This could include a discussion of the potential implications of filling the gap, the significance of the research for the field, or the potential benefits to society.
• State your research objectives: State your research objectives, which should be aligned with the research gap you have identified. This will help you to clearly articulate the purpose of your study and how it will address the research gap.

Importance of Research Gap

The importance of research gaps can be summarized as follows:

• Advancing knowledge: Identifying research gaps is crucial for advancing knowledge in a particular field. By identifying areas where additional research is needed, researchers can fill gaps in the existing body of knowledge and contribute to the development of new theories and practices.
• Guiding research: Research gaps can guide researchers in designing studies that fill those gaps. By identifying research gaps, researchers can develop research questions and objectives that are aligned with the needs of the field and contribute to the development of new knowledge.
• Enhancing research quality: By identifying research gaps, researchers can avoid duplicating previous research and instead focus on developing innovative research that fills gaps in the existing body of knowledge. This can lead to more impactful research and higher-quality research outputs.
• Informing policy and practice: Research gaps can inform policy and practice by highlighting areas where additional research is needed to inform decision-making. By filling research gaps, researchers can provide evidence-based recommendations that have the potential to improve policy and practice in a particular field.

Applications of Research Gap

Here are some potential applications of research gap:

• Informing research priorities: Research gaps can help guide research funding agencies and researchers to prioritize research areas that require more attention and resources.
• Identifying practical implications: Identifying gaps in knowledge can help identify practical applications of research that are still unexplored or underdeveloped.
• Stimulating innovation: Research gaps can encourage innovation and the development of new approaches or methodologies to address unexplored areas.
• Improving policy-making: Research gaps can inform policy-making decisions by highlighting areas where more research is needed to make informed policy decisions.
• Enhancing academic discourse: Research gaps can lead to new and constructive debates and discussions within academic communities, leading to more robust and comprehensive research.

Advantages of Research Gap

Here are some of the advantages of research gap:

• Identifies new research opportunities: Identifying research gaps can help researchers identify areas that require further exploration, which can lead to new research opportunities.
• Improves the quality of research: By identifying gaps in current research, researchers can focus their efforts on addressing unanswered questions, which can improve the overall quality of research.
• Enhances the relevance of research: Research that addresses existing gaps can have significant implications for the development of theories, policies, and practices, and can therefore increase the relevance and impact of research.
• Helps avoid duplication of effort: Identifying existing research can help researchers avoid duplicating efforts, saving time and resources.
• Helps to refine research questions: Research gaps can help researchers refine their research questions, making them more focused and relevant to the needs of the field.
• Promotes collaboration: By identifying areas of research that require further investigation, researchers can collaborate with others to conduct research that addresses these gaps, which can lead to more comprehensive and impactful research outcomes.

Disadvantages of Research Gap

While research gaps can be advantageous, there are also some potential disadvantages that should be considered:

• Difficulty in identifying gaps: Identifying gaps in existing research can be challenging, particularly in fields where there is a large volume of research or where research findings are scattered across different disciplines.
• Lack of funding: Addressing research gaps may require significant resources, and researchers may struggle to secure funding for their work if it is perceived as too risky or uncertain.
• Time-consuming: Conducting research to address gaps can be time-consuming, particularly if the research involves collecting new data or developing new methods.
• Risk of oversimplification: Addressing research gaps may require researchers to simplify complex problems, which can lead to oversimplification and a failure to capture the complexity of the issues.
• Bias : Identifying research gaps can be influenced by researchers’ personal biases or perspectives, which can lead to a skewed understanding of the field.
• Potential for disagreement: Identifying research gaps can be subjective, and different researchers may have different views on what constitutes a gap in the field, leading to disagreements and debate.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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The Research Gap (Literature Gap)

Everything you need to know to find a quality research gap

By: Ethar Al-Saraf (PhD) | Expert Reviewed By: Eunice Rautenbach (DTech) | November 2022

If you’re just starting out in research, chances are you’ve heard about the elusive research gap (also called a literature gap). In this post, we’ll explore the tricky topic of research gaps. We’ll explain what a research gap is, look at the four most common types of research gaps, and unpack how you can go about finding a suitable research gap for your dissertation, thesis or research project.

Overview: Research Gap 101

• What is a research gap
• Four common types of research gaps
• Practical examples
• How to find research gaps
• Recap & key takeaways

What (exactly) is a research gap?

Well, at the simplest level, a research gap is essentially an unanswered question or unresolved problem in a field, which reflects a lack of existing research in that space. Alternatively, a research gap can also exist when there’s already a fair deal of existing research, but where the findings of the studies pull in different directions , making it difficult to draw firm conclusions.

For example, let’s say your research aims to identify the cause (or causes) of a particular disease. Upon reviewing the literature, you may find that there’s a body of research that points toward cigarette smoking as a key factor – but at the same time, a large body of research that finds no link between smoking and the disease. In that case, you may have something of a research gap that warrants further investigation.

Now that we’ve defined what a research gap is – an unanswered question or unresolved problem – let’s look at a few different types of research gaps.

Types of research gaps

While there are many different types of research gaps, the four most common ones we encounter when helping students at Grad Coach are as follows:

• The classic literature gap
• The disagreement gap
• The contextual gap, and
• The methodological gap

Need a helping hand?

1. The Classic Literature Gap

First up is the classic literature gap. This type of research gap emerges when there’s a new concept or phenomenon that hasn’t been studied much, or at all. For example, when a social media platform is launched, there’s an opportunity to explore its impacts on users, how it could be leveraged for marketing, its impact on society, and so on. The same applies for new technologies, new modes of communication, transportation, etc.

Classic literature gaps can present exciting research opportunities , but a drawback you need to be aware of is that with this type of research gap, you’ll be exploring completely new territory . This means you’ll have to draw on adjacent literature (that is, research in adjacent fields) to build your literature review, as there naturally won’t be very many existing studies that directly relate to the topic. While this is manageable, it can be challenging for first-time researchers, so be careful not to bite off more than you can chew.

2. The Disagreement Gap

As the name suggests, the disagreement gap emerges when there are contrasting or contradictory findings in the existing research regarding a specific research question (or set of questions). The hypothetical example we looked at earlier regarding the causes of a disease reflects a disagreement gap.

Importantly, for this type of research gap, there needs to be a relatively balanced set of opposing findings . In other words, a situation where 95% of studies find one result and 5% find the opposite result wouldn’t quite constitute a disagreement in the literature. Of course, it’s hard to quantify exactly how much weight to give to each study, but you’ll need to at least show that the opposing findings aren’t simply a corner-case anomaly .

3. The Contextual Gap

The third type of research gap is the contextual gap. Simply put, a contextual gap exists when there’s already a decent body of existing research on a particular topic, but an absence of research in specific contexts .

For example, there could be a lack of research on:

• A specific population – perhaps a certain age group, gender or ethnicity
• A geographic area – for example, a city, country or region
• A certain time period – perhaps the bulk of the studies took place many years or even decades ago and the landscape has changed.

The contextual gap is a popular option for dissertations and theses, especially for first-time researchers, as it allows you to develop your research on a solid foundation of existing literature and potentially even use existing survey measures.

Importantly, if you’re gonna go this route, you need to ensure that there’s a plausible reason why you’d expect potential differences in the specific context you choose. If there’s no reason to expect different results between existing and new contexts, the research gap wouldn’t be well justified. So, make sure that you can clearly articulate why your chosen context is “different” from existing studies and why that might reasonably result in different findings.

4. The Methodological Gap

Last but not least, we have the methodological gap. As the name suggests, this type of research gap emerges as a result of the research methodology or design of existing studies. With this approach, you’d argue that the methodology of existing studies is lacking in some way , or that they’re missing a certain perspective.

For example, you might argue that the bulk of the existing research has taken a quantitative approach, and therefore there is a lack of rich insight and texture that a qualitative study could provide. Similarly, you might argue that existing studies have primarily taken a cross-sectional approach , and as a result, have only provided a snapshot view of the situation – whereas a longitudinal approach could help uncover how constructs or variables have evolved over time.

Practical Examples

Let’s take a look at some practical examples so that you can see how research gaps are typically expressed in written form. Keep in mind that these are just examples – not actual current gaps (we’ll show you how to find these a little later!).

Context: Healthcare

Despite extensive research on diabetes management, there’s a research gap in terms of understanding the effectiveness of digital health interventions in rural populations (compared to urban ones) within Eastern Europe.

Context: Environmental Science

While a wealth of research exists regarding plastic pollution in oceans, there is significantly less understanding of microplastic accumulation in freshwater ecosystems like rivers and lakes, particularly within Southern Africa.

Context: Education

While empirical research surrounding online learning has grown over the past five years, there remains a lack of comprehensive studies regarding the effectiveness of online learning for students with special educational needs.

As you can see in each of these examples, the author begins by clearly acknowledging the existing research and then proceeds to explain where the current area of lack (i.e., the research gap) exists.

How To Find A Research Gap

Now that you’ve got a clearer picture of the different types of research gaps, the next question is of course, “how do you find these research gaps?” .

Well, we cover the process of how to find original, high-value research gaps in a separate post . But, for now, I’ll share a basic two-step strategy here to help you find potential research gaps.

As a starting point, you should find as many literature reviews, systematic reviews and meta-analyses as you can, covering your area of interest. Additionally, you should dig into the most recent journal articles to wrap your head around the current state of knowledge. It’s also a good idea to look at recent dissertations and theses (especially doctoral-level ones). Dissertation databases such as ProQuest, EBSCO and Open Access are a goldmine for this sort of thing. Importantly, make sure that you’re looking at recent resources (ideally those published in the last year or two), or the gaps you find might have already been plugged by other researchers.

Once you’ve gathered a meaty collection of resources, the section that you really want to focus on is the one titled “ further research opportunities ” or “further research is needed”. In this section, the researchers will explicitly state where more studies are required – in other words, where potential research gaps may exist. You can also look at the “ limitations ” section of the studies, as this will often spur ideas for methodology-based research gaps.

By following this process, you’ll orient yourself with the current state of research , which will lay the foundation for you to identify potential research gaps. You can then start drawing up a shortlist of ideas and evaluating them as candidate topics . But remember, make sure you’re looking at recent articles – there’s no use going down a rabbit hole only to find that someone’s already filled the gap 🙂

Let’s Recap

We’ve covered a lot of ground in this post. Here are the key takeaways:

• A research gap is an unanswered question or unresolved problem in a field, which reflects a lack of existing research in that space.
• The four most common types of research gaps are the classic literature gap, the disagreement gap, the contextual gap and the methodological gap. 
• To find potential research gaps, start by reviewing recent journal articles in your area of interest, paying particular attention to the FRIN section .

If you’re keen to learn more about research gaps and research topic ideation in general, be sure to check out the rest of the Grad Coach Blog . Alternatively, if you’re looking for 1-on-1 support with your dissertation, thesis or research project, be sure to check out our private coaching service .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

41 Comments

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Very helpful specialy, for those who are new for writing a research! So thank you very much!!

I found it very helpful article. Thank you.

it very good but what need to be clear with the concept is when di we use research gap before we conduct aresearch or after we finished it ,or are we propose it to be solved or studied or to show that we are unable to cover so that we let it to be studied by other researchers ?

Just at the time when I needed it, really helpful.

Very helpful and well-explained. Thank you

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hello brother could you explain to me this question explain the gaps that researchers are coming up with ?

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Kindly explain to me how to generate good research objectives.

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How to tabulate research gap

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How do I Cite this document please?

Research gap about career choice given me Example bro?

I found this information so relevant as I am embarking on a Masters Degree. Thank you for this eye opener. It make me feel I can work diligently and smart on my research proposal.

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Insightful…

I have found this quite helpful. I will continue using gradcoach for research assistance

Doing research in PhD accounting, my research topic is: Business Environment and Small Business Performance: The Moderating Effect of Financial Literacy in Eastern Uganda. I am failing to focus the idea in the accounting areas. my supervisor tells me my research is more of in the business field. the literature i have surveyed has used financial literacy as an independent variable and not as a moderator. Kindly give me some guidance here. the core problem is that despite the various studies, small businesses continue to collapse in the region. my vision is that financial literacy is still one of the major challenges hence the need for this topic.

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What is the research gap for time management?  

Insight from top 4 papers, source papers (4).

Related Questions

Effective time management strategies have been found to have a significant impact on study habits and academic performance . However, there is a research gap in understanding the specific effects of time management strategies on study habits. While some studies have focused on the relationship between time management and academic performance, there is limited research on the effects of time management on study habits specifically . Additionally, the socio-cultural and pedagogical factors involved in the development of effective time management skills have been largely overlooked in the existing literature . Therefore, further research is needed to explore the effectiveness of time management strategies on study habits, taking into account the socio-cultural and pedagogical aspects that influence students' organization of time. This research would contribute to a better understanding of how time management strategies can be effectively utilized to improve study habits and ultimately enhance academic performance.

Time management limitations include the lack of standardized definitions and operationalizations of time management, limited attention given to the nursing and health field, and the need for more accurate research on the obstacles of time management in nursing and health professions . Additionally, time management is crucial in workflow-based process management, but there are challenges in planning workflow execution, estimating execution duration, avoiding deadline violations, and satisfying external time constraints . Time management is also a limitation in applying workflow technologies to complex enterprises, and effective time modeling is key to enhancing flexibility and competitiveness . In the context of intervention programs, time management is essential for planning, implementing, and evaluating the program's actions, and any disparity between scheduled and real time can have serious consequences . In workflow management systems, time management involves calculating execution time, identifying critical paths, and avoiding time constraint violations .

Effective time management has a significant impact on productivity . Good time management practices, such as setting goals, prioritizing tasks, and delegating responsibilities, can enhance productivity and job satisfaction . On the other hand, poor time management can lead to low productivity, poor quality of work, and increased stress levels . Studies have shown that organizations that effectively manage their time resources experience higher levels of productivity . Time management is considered a valuable commodity that, when managed effectively, can contribute to achieving individual and organizational goals . It is recommended that organizations provide necessary time management tools and create a favorable working environment to improve self-commitment to time management and enhance productivity . Further research is needed to explore the importance of time management and its impact on productivity in different contexts .

Research gaps are areas where the current knowledge and research data are insufficient to fully answer a particular research question . These gaps arise due to limitations in study design, inadequate research tools, or external factors that may or may not be under the researcher's control . Identifying research gaps is crucial as it helps to determine the areas where new research can contribute to expanding the field of study . For example, in the field of vehicle control strategies for improved fuel economy, research gaps include the need to incorporate perception and planning subsystems, study the effects of mispredictions, and provide physical demonstrations of the planning subsystem . Research gaps can also exist in the implementation of evidence-based teaching practices in teacher education, where knowledge, beliefs, and attitudes play a role in accelerating the adoption of evidence-based practices . Taking a comprehensive and integrated approach is important in addressing research gaps and achieving research goals .

The foreign literature on the research topic of lack of time management reveals several key findings. One study by Cladellas found that employees who have limited opportunities for individual time management experience lower satisfaction, worse general and mental health, and higher levels of stress . Another paper by Belayneh Zerihun and Krishna highlights the lack of agreement on the definition of time management and the absence of a theoretical model for understanding it . Macan's research suggests that engaging in certain time management behaviors may lead to reduced job tensions and increased job satisfaction, but not necessarily improved job performance . Additionally, Hellsten argues that there is a lack of literature summarizing time management across disciplines and a need for a psychometric review of instruments used to assess generic time management .

Trending Questions

Local studies on math anxiety in Davao del Norte reveal significant insights into its impact on students' academic performance and coping strategies. Carabeo and Tado's research highlights that self-control is a crucial predictor of academic achievement in mathematics among Grade 10 students, suggesting that enhancing self-control could mitigate math anxiety and improve performance. Similarly, a study by Villegas and González emphasizes that students face difficulties in understanding mathematical concepts, which can exacerbate anxiety, and they employ various coping strategies such as perseverance and expert consultation. Moreover, the findings from Pinugu et al. indicate that math anxiety significantly affects mathematics performance among college students, underscoring the need for supportive educational environments to foster self-efficacy and engagement. These studies collectively suggest that addressing math anxiety through targeted interventions, such as enhancing self-control and providing supportive teacher-student rapport, is essential for improving students' mathematical outcomes in Davao del Norte.

Cross-dressing can significantly influence social interactions within academic settings by fostering a greater understanding and acceptance of diversity. Research indicates that cross-dressing artists promote pluralism and respect for differences, which can enhance social relations and reduce intolerance among peers . This aligns with findings that suggest attire, including cross-dressing, can impact students' evaluations of academics, potentially affecting their perceptions and interactions . Furthermore, negative interpersonal interactions, such as bullying, are prevalent in academic environments, and the visibility of diverse expressions like cross-dressing may challenge traditional norms, thereby influencing the dynamics of these interactions . However, the portrayal of cross-dressing in cultural contexts, such as in the "Prymskvida," highlights the complexities of gender roles and societal expectations, suggesting that while cross-dressing can promote inclusivity, it may also provoke mixed reactions based on cultural interpretations . Overall, cross-dressing in academic settings can serve as a catalyst for dialogue and understanding, albeit with potential challenges.

Community colleges can support Black and Latinx students on academic probation through targeted programs and interventions that address their unique challenges. Research indicates that these students often face difficulties such as balancing employment, family obligations, and academic integration, which contribute to their probationary status. Implementing mandatory support programs can be effective, as they ensure that students who may not seek help on their own receive necessary assistance. Additionally, peer tutoring programs that honor the cultural backgrounds of Latinx students can enhance their navigational and social capital, fostering a sense of belonging and community within the institution. These programs not only provide academic support but also promote emotional resilience and behavioral changes, framing academic probation as an opportunity for growth. By combining these strategies, community colleges can create a more inclusive environment that supports the success of Black and Latinx students on academic probation.

Gestalt therapy can significantly enhance character analysis in literature by emphasizing the dynamic and evolving nature of characters, as well as their interactions within narratives. Morozova and Pozharytska highlight how fanfiction can reshape character perceptions through the lens of Gestalt theory, suggesting that authors' personal sympathies can alter character profiles while maintaining a recognizable backdrop of the original text. This aligns with Burley and Freier's assertion that Gestalt therapy focuses on how behaviors manifest, allowing for a nuanced understanding of character development as a process rather than a static state. Furthermore, Jayakumar et al. advocate for viewing character relationships as evolving entities, which resonates with Gestalt principles of interconnectedness and change. By integrating these perspectives, literary analysis can benefit from a more holistic view of characters, recognizing their complexities and the influences of both internal and external factors on their development.

Lifeways refer to the patterns and practices through which individuals and communities live their lives, encompassing cultural, social, economic, and environmental dimensions. This concept is explored across various contexts, highlighting its multifaceted nature. In the context of small-scale gold mining, lifeways are described as the lived experiences and relational phenomena associated with mining activities. These lifeways are not only about the economic sustenance provided by mining but also involve the social and environmental dynamics that shape miners' perspectives on sustainability. The study emphasizes that these lifeways are deeply embedded in societal contexts and are influenced by factors such as government policies and community discourses, which collectively impact the sustainability transformations within mining communities . The notion of lifeways is also linked to broader lifestyle changes necessary for sustainable living. Research on sustainable lifestyle scenarios, such as the SLIM scenarios, illustrates how lifeways can be transformed to mitigate climate change. These scenarios consider the role of structural support and individual behaviors in reducing emissions, highlighting the importance of lifestyle changes in achieving sustainability goals. The study underscores that lifeways, when aligned with supportive policies and technologies, can significantly contribute to reducing environmental impacts . Furthermore, lifeways are connected to socio-economic and cultural dimensions, as seen in the study of competitive sportsmen. Here, lifeways are described as being influenced by societal production modes and class situations, reflecting the interplay between individual lifestyles and broader socio-economic structures. This perspective emphasizes the role of spiritual and cultural desires in shaping lifeways, which are continuously evolving with societal changes . Overall, lifeways encompass the diverse ways in which people navigate their lives, influenced by a complex interplay of personal, societal, and environmental factors. These patterns are crucial for understanding how individuals and communities can adapt to and drive sustainability transformations across different contexts.

This paper is in the following e-collection/theme issue:

Published on 5.8.2024 in Vol 13 (2024)

Evaluating the Population-Based Usage and Benefit of Digitally Collected Patient-Reported Outcomes and Experiences in Patients With Chronic Diseases: The PROMchronic Study Protocol

Authors of this article:

• Janis Nikkhah 1 , MSc   ; 
• Viktoria Steinbeck 1 , MSc   ; 
• Thomas G Grobe 2 , MD, MPH   ; 
• Thorben Breitkreuz 2   ; 
• Christoph Pross 1 , PhD   ; 
• Reinhard Busse 1 , MD, MPH  

1 Department of Healthcare Management, School of Economics and Management, Technical University Berlin, Berlin, Germany

2 aQua Institute, Göttingen, Germany

Corresponding Author:

Janis Nikkhah, MSc

Department of Healthcare Management

School of Economics and Management

Technical University Berlin

Straße des 17. Juni 135, H80

Berlin, 10623

Phone: 49 151 689 414 32

Email: [email protected]

Background: Chronic diseases are associated with a high disease burden. Under- and overprovision of care as well as quality variation between health care providers persists, while current quality indicators rarely capture the patients’ perspective. Capturing patient-reported outcome measures (PROMs) as well as patient-reported experience measures (PREMs) is becoming more and more important to identify gaps in care provision, prioritize services most valuable to patients, and aid patients' self-management.

Objective: This study aims to measure the potential benefits and effectiveness of using electronic patient-reported outcome measures (ePROMs) and electronic patient-reported experience measures in a structured and population-based manner to enhance health care for chronic disease patients in Germany.

Methods: This prospective cohort study aims to evaluate the potential benefits of PROM usage in patients with chronic diseases. We evaluate whether (1) digitally collected PROMs and PREMs can be used for health system performance assessment by generating a representative response of chronically diseased individuals with asthma, chronic obstructive pulmonary disease, diabetes, and coronary artery disease across Germany, and (2) based on the PROMs and PREMs, low-value care can be identified. As patient-reported outcomes (PROs) are rarely presented back to patients, (3) this study also examines patients’ reactions to their PROM scores in the form of digital PRO feedback. For these purposes, randomly selected patients from a nationwide German insurer are digitally surveyed with generic and disease-specific PROMs and PREMs, as well as additional questions on their health-related behavior, 4 times over 1 year. Individual PRO feedback is presented back to patients longitudinally and compared to a peer group after each survey period. Patient-reported data is linked with health insurance data. Response rates, changes in health and experience outcomes over time, self-reported changes in health behavior, and health care system usage will be analyzed.

Results: The PROMchronic study explores the usage of PROMs in patients with chronic diseases. Data collection began in October 2023, after the initial invitation letter. All the 200,000 potential patients have been invited to participate in the study. Data have not yet been analyzed. Publication of the interim results is planned for the autumn of 2024, and the results are planned to be published in 2025.

Conclusions: We aim to fill the research gap on the population-based usage of PROMs and PREMs in patients with chronic diseases and add to the current understanding of PROM data-sharing with patients. The study’s results can thereby inform whether a health care system-wide approach to collecting PROMs and PREMs can be used to identify low-value care, assess quality variation within and across chronic conditions, and determine whether PRO feedback is helpful and associated with any changes in patients’ health behaviors.

Trial Registration: German Clinical Trials Register DRKS00031656; https://drks.de/search/en/trial/DRKS00031656

International Registered Report Identifier (IRRID): DERR1-10.2196/56487

Introduction

Background and rationale.

Globally, 1 in 3 persons and up to 60% in industrialized countries are living with at least 1 chronic disease [ 1 - 3 ]. Furthermore, this share is continuously increasing across the globe due to demographic change and consumption patterns [ 3 , 4 ]. Chronic diseases, including conditions such as diabetes, cardiovascular diseases, and chronic obstructive pulmonary disease (COPD), are long-lasting conditions that can significantly impact a patient's quality of life and are a key driver of escalating health costs in both developed and developing economies [ 5 ]. Diagnosing and treating chronic conditions comes with substantial uncertainties for patients, families, and caregivers [ 6 ]. The high complexity of chronic care, for instance, raises uncertainty regarding whether patients with chronic diseases will respond to a selected treatment in the way a priori expected and, in the event they do, whether it is the most efficient one [ 7 ].

Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) have been used for over 20 years, but have become increasingly widespread and accepted only in recent years [ 8 ], as reflected by their increasing usage in oncology [ 9 - 11 ] and orthopedics [ 12 - 14 ]. The use of PROMs in monitoring interventions has, for instance, shown benefits in terms of increased survival rates, lower hospitalizations, improved health-related quality of life in oncology and reduced fatigue, and improved health-related quality of life in orthopedics [ 15 , 16 ]. PROMs are questionnaires that allow valuable insights into the patient’s perspective of living with a (chronic) disease as they reflect the patient’s own perception of their health status [ 17 , 18 ]. PREMs are questionnaires used to gather information from patients about their personal experiences and perceptions of the care and services they have received [ 19 ]. With electronic PROMs (ePROMs) and electronic PREMs (ePREMs) being reported and used more frequently in the last few years [ 20 , 21 ], usage for population health purposes appears more in reach but has rarely been examined [ 22 ].

PROMs and PREMs might have care improvement potential in the field of chronic diseases due to their information value for patient empowerment, including self-management and shared decision-making, which could influence treatment adherence and lifestyle choices [ 23 ]. However, PROMs and PREMs have rarely been used in routine chronic care due to the unspecified timeline and the complexity of implementation [ 24 ]. Due to the high relevance of this topic, the OECD (Organisation for Economic Co-operation and Development) PaRIS (Patient-Reported Indicator Surveys) initiative focuses on collecting and analyzing PROMs in patients with chronic diseases across 18 countries, starting their trial phase in 2023. The initiative does not cover Germany [ 25 ]. The present study, “PROMchronic,” aims to fill the research gap by evaluating the usage of ePROMs and ePREMs in the German chronic disease population for 4 selected chronic disease profiles.

Furthermore, providing patients with information on their health status based on PROMs in reference to a comparable peer group is rarely done [ 26 , 27 ]. Yet, specific information about patients’ health status is crucial because it can help patients better understand their health conditions and enable decision-making and overall patient empowerment. When patients are well-informed about their health, they are more likely to adhere to treatment plans and achieve better health outcomes [ 28 ]. Patients can use this information together with their health care providers to set realistic goals for their treatment, monitor their progress, and identify areas where additional support is needed.

Our study aims to evaluate the potential benefits of the structured and population-based use of ePROMs and ePREMs to improve care for chronically ill patients in Germany. First, we evaluated whether and how representative the response to the digitally collected questionnaires is and thereby investigate PROMs as a tool for health system performance assessment (HSPA). Second, we assessed if low-value care elements can be identified in today’s care for chronically ill patients across Germany. Third, we analyzed patients’ understanding of and reactions to individualized patient-reported outcome (PRO) feedback. To achieve these objectives, this study aims to answer 3 overarching research questions and their subquestions ( Textbox 1 ).

Can electronic patient-reported outcome measures (ePROMs) and electronic patient-reported experience measures (ePREMs) be used in patients with chronic diseases for quality measurement at the health system level (eg, for health system performance assessment [HSPA])?

• How representative are response rates in patients with chronic diseases via digital surveys in terms of gender, age, and diagnoses?
• How do response rates and willingness to respond multiple times vary over time by age, gender, indication, city or state, health system use (frequent versus infrequent users), web- or app-based surveys, and Disease Management Program (DMP) participation?

To what extent can value-of-care variation be identified from ePROMs and ePREMs surveys?

• What is the share of suspected low-value care and suspected high-value care in Germany, per indication and in subgroups?
• How do ePROM and ePREM results and health indicators of health insurance data differ according to age, gender, indication, city or state, health care system usage (changes in frequency of outpatient practitioner attendance, prescriptions, hospitalizations, etc), and DMP participation?
• Can ePROMs and ePREMs function as an early warning signal for deteriorating chronic conditions or adverse events such as hospital admission?

What are the benefits or drawbacks of patient-reported outcome (PRO) feedback (outcome reports) sent to patients?

• Are the PRO outcome reports understandable to patients?
• Can PRO feedback function as a positive nudge (be associated with positive behavioral changes, eg, healthier or more active lifestyle, more active participation in medical treatment, actively approaching treating physicians in the office setting)?
• Are there any negative emotional reactions when receiving PRO feedback that shows values worse than those of a comparable group?

Trial Design

This is an observational prospective cohort study covering the 4 chronic diseases: asthma, COPD, diabetes types 1 and 2, and coronary artery disease (CAD). As shown in Figure 1 , the first point of contact will be a letter from the insurer to insured patients selected for their chronic disease. A patient can then sign up digitally for the study via a QR code or web-based link. For each of the different diseases, a distinct patient pathway is automatically assigned, with a registration process followed by some background questions and the respective generic and disease-specific PROMs and PREMs. The study covers a timeframe of 1 year, split into 4 time intervals with further information and reoccurring questionnaires. The time intervals are split into smaller tasks to facilitate the answering process for participants. The first interval includes self-registration and a baseline assessment of health behavior. A few weeks after responding to the first set of questions ( Figures 1 A and 1B), patients will receive a report with their individual PROM scores compared to a peer group and will be surveyed on the comprehensibility of the PRO report ( Figure 1 C). From the second interval onwards, patients will also receive their individual PRO results longitudinally. Lastly, following the individual PRO feedback report, participants will be surveyed regarding their health behavior ( Figure 1 D). After 1 year, the primary data collection process is finished, and patient-reported data will be merged with health insurance data. Further explanations of subgroup definitions can be found in the Statistical Analysis Plan ( Multimedia Appendix 1 ).

Study Setting

This study will recruit patients all over Germany who are insured by one of the largest statutory health insurers in Germany (BARMER). The BARMER represents more than 10% of the German population. After the identification of individuals based on their chronic disease profile, validated PROM sets are used digitally to regularly survey patients with asthma, COPD, diabetes, or CAD on their health outcomes as well as their experience with the health care system.

Eligibility Criteria

Patients are eligible for participation in the study if they are above the age of 18 years and have at least 2 outpatient consultations in 2021 documenting a confirmed chronic disease diagnosis of 1 of the 4 focus diseases. Additionally, for type 1 diabetes patients, at least 1 insulin prescription must be documented in 2021. To contact patients and enable the linkage of health insurance data, patients must be insured by BARMER health insurance all year in 2021. Patients enrolled in a Disease Management Program (DMP) as well as patients not enrolled in any DMP are eligible. However, enrolment in more than 2 DMPs is not permitted to avoid multiple invitation letters and cross-over groups.

Participant Timeline

Eligible participants will be participating in the study for a maximum of 4 quarters, starting with the first access to the digital questionnaires, followed by quarterly digital surveys split into several tasks (compare Figure 1 ). To start the survey, participants register with their study pseudonyms received in their enrollment letter and then share basic demographics. Each survey period contains 4 tasks to be completed by participants, defined as sets of questions that each will take 5-10 minutes to complete. The participants will receive individual reports on their patient-specific and peer group outcomes (PRO feedback) and will be asked about the comprehensibility of the report. Following the report, the participants receive a set of questions regarding their health-related behavior.

Sample Size

The initial enrollment letter is sent to 200,000 insured patients, 50,000 for each of the selected chronic conditions. Diabetes type 1 and type 2 are considered jointly, as there is no differentiation in the selected PROMs. Patients with all chronic diseases are allocated to groups based on their participation in DMP (DMP or non-DMP group). Prior experiences suggest that around 30% of patients react to invitations to participate in research by their insurer [ 29 - 31 ]. Two-thirds of initial participants are expected to allow follow-up contacts and processing of their health insurance data, and around 40% of these patients will continue participating in all the follow-up surveys after receiving reminders for each task. Therefore, after accounting for nonparticipants and participants with no complete survey data, we expect a complete data set for 16,000 participants. However, the first research question will investigate response rates, as there is no evidence on this population yet.

BARMER Health Insurance will send out enrollment letters based on a random selection of BARMER-insured patients following the defined eligibility criteria. Matching of DMP- and non-DMP participants will be done according to the steps provided in Textbox 2 .

The output is a data set containing matched pairs per indication. The first 25,000 matching pairs for each chronic condition will be selected. Diabetes type 1 and type 2 are considered jointly, with patients having diabetes type 1 selected first (approximately 6600 matched pairs are expected), followed by supplementing the remaining required matched pairs with patients having diabetes type 2.

Stratification by:

• Gender (male or female).
• 10-year age groups (first group: 18 to younger than 30 years and last group: 90 years and older).
• Number of outpatient cases with indication diagnoses within the year 2021 (outpatient cases in less than 4 quarters, outpatient cases in all 4 quarters but less than or equal to 6 cases, outpatient cases in all 4 quarters with more than 6 cases).
• Matching DMP and non-DMP patients by strata and a generated random numbering within the strata (1:1 matching).
• Consecutive selection of randomly sorted matched pairs if both matched individuals are insured all year long.

Recruitment

An initial enrollment letter including the study explanation, a QR code, and a link as an invitation to participate in the study will be sent to insured patients in October 2023 ( Multimedia Appendix 2 ). The enrollment survey and, thereby, the recruitment period will be open for 2 months.

Ethical Considerations

The study will be conducted in accordance with the Declaration of Helsinki and was approved by the Charité’s Ethic Committee, Berlin (EA2/035/23). All potentially eligible participants will be approached to offer their informed consent to participate in the study as well as to allow linkage of their insurance data for further analysis. This protocol is version 1, dated January 10, 2024. Any changes in the study design will be communicated to all project partners.

Informed consent must be provided digitally before patients can participate in the study. By signing the informed consent, patients allow contact for follow-up surveys via email and to process their survey data for academic research purposes. Additionally, patients are asked to sign a second consent form for processing and linking their insurance data to their survey data. The second consent form is optional and is not a prerequisite to participating in the study. Patients will be free to withdraw from either one of the consents without stating a reason until the anonymization of the data. Through the anonymization of the primary and secondary data before the provision of data sets to research institutions in the project, patient identification will not be possible. If the patients withdraw their consent for participation, all their data will be deleted. Consent forms can be found in Multimedia Appendix 3 . Participants are not reimbursed for their participation.

Intervention

Explanation for the choice of comparators.

This prospective observation cohort study does not involve any specific therapeutic treatment. To analyze and report insights on sub-cohorts of the study population, splits for age, gender, indication, PRO feedback, and usage of the health care system (eg, DMP) are formed.

Intervention Description

In addition to filling out the survey questions (considered here as intervention 1), all participants will receive PRO feedback (considered here as intervention 2—see Multimedia Appendix 4 ). The PRO feedback will be a pdf report sent via email, which graphically (line charts) shows the patients’ individual generic and disease-specific health status in comparison to a patient-specific peer group. In addition to the visual feedback, the results will shortly be explained on the same page. The description will cover whether patient-individual PRO scores are better or worse compared to the peer group, and if worse, the patients' health status might be still good and can be discussed with the patients' physician. Additional details on the scores and sub-scores are shared with the patients on the subsequent pages of the report. Peer groups are classified according to their disease, gender, and age group (18-45 years, 45-65 years, 65-75 years, and 75 years and above). The report refers to a patient’s routine care physician as the main contact to discuss the results or if there are questions.

Criteria for Discontinuing or Modifying Allocated Interventions

Participants may withdraw from the study at any time. Following discontinuation, all participants’ individual study data will be deleted, and surveys and reminders will not be sent anymore.

Strategies to Improve Adherence to Interventions

To enhance adherence, the sign-up process for the digital solution was minimized. In addition, email reminders will be sent to patients. Moreover, the PRO feedback includes multiple elements (graphics, bolded text, and descriptions), as this was shown to improve patient understanding [ 27 , 32 ].

The primary end point (research question 1) of the study is sufficient study participation to determine the representativeness of the results. As expected, study participation will vary depending on gender, age, and diagnosis, but this can be compensated for by weighting the study participants according to structural information on the target population.

Within our study, data on health care usage is available for both participants and the whole target population. Weighted measures of health care usage from participants will be compared with measures of health care usage of the complete target population and will be assumed to be formally representative if the weighted measures from participants fall within the 95% CI of the same measures based on data from the complete target population.

Secondary end points are the end points to answer research questions 2 and 3 ( Textbox 3 ; Figure 2 ).

Figure 2 represents how PROMs and PREMs can be combined into one value of care indicator, for example, if PREMs and PROMs are both average or above (up to 1 SD), care is suspected to be high-value, whereas if PROMs and PREMs are below 1 SD of the average, care is suspected to be low-value. Since for each disease group, a disease-specific PROM will be used next to a generic PROM, the assessment of low- and high-value care across diseases will be conducted by using the generic PROMs. Moreover, the disease-specific PROMs will be used to create low- and high-value care categorizations on a detailed level within a disease group. Adding cost data as a third dimension to the value of care framework (as described in the Statistical Analysis Plan, Multimedia Appendix 1 ) then enables a clear distinction between patients considered to have received low-value care and patients who received high-value care. A more detailed description of the outcomes can be found in the Statistical Analysis Plan ( Multimedia Appendix 1 ).

Research question 2:

• Share of low-value care using the VBHC framework introduced in Figure 2 and specified in further detail in the Statistical Analysis Plan ( Multimedia Appendix 1 )
• Share of high-value care, specified in Figure 2
• Outcome and patient experience variation across subgroups
• Adverse events such as hospital admission due to a chronic disease profile

Research question 3:

• Comprehensibility and usability of patient-reported outcome (PRO) feedback
• Impact of PRO feedback on health care behavior

Assignment of Interventions: Allocation

Sequence generation.

The sequence generation data are provided in Textbox 4 .

• The BARMER health gender (male and female)
• Number of outpatient cases with indication diagnoses within the year 2021 (outpatient cases in less than 4 quarters, outpatient cases in all 4 quarters but less than or equal to 6 cases, outpatient cases in all 4 quarters with more than 6 cases)
• Matching Disease Management Program (DMP) and non-DMP patients by strata and a generated random numbering within the strata (1:1 matching).
• Consecutive selection of randomly sorted matched pairs if both matched individuals are insured all year long

Implementation

The random selection of patients will be performed by BARMER Health Insurance according to the selection process description provided by the independent evaluating aQua institute.

Data Collection and Management: Plans for Assessment and Collection of Outcomes

There are 2 main data sources used in this study. First, primary data will be collected from the participants’ surveys. Second, secondary data from the cooperating health insurer, BARMER, will be used. The primary data collection is conducted via digital surveys, which include different questionnaire categories, namely PROMs, PREMs, comprehensibility of the PRO feedback, and questions on patients’ health behavior. Additionally, an anchor question using the Global Rating of Change scale [ 33 ] with 5 answer options is included to assess changes in health status.

An overview of all selected survey items, including the selected validated PROMs, can be found in Figure 3 and is described in more detail in the following paragraphs.

Various PROMs exist that can be classified into generic, treatment-specific, and disease-specific instruments. Generic PROMs assess health outcomes broadly and enable comparison across diseases, whereas treatment- or disease-specific PROMs are tailored to a specific treatment or disease and are more suitable for comparisons inside patient groups receiving the same treatment or a population with similar diseases [ 17 ]. The selection of the PROMs is in line with the selection criteria reported in the literature [ 34 - 37 ] as well as project-specific criteria. The criteria that were used for the selection of PROs are listed in Textbox 5 .

• The questionnaire must be brief to not burden participants and increase response rates [ 38 ]. The overall item count across one survey period was restricted to 60 items and a maximum of 15 minutes to complete.
• The patient-reported outcome measures (PROMs) must be available in German.
• The sets must be validated, at least in the German language, and ideally also for digital applications.

Licensing fees

• Licensing fee for surveys for academic use does not exceed US $5000 per set.
• Scoring information must be available to enable PRO feedback based on overall scores.

Health dimensions

• The combined set of PROMs must cover all overarching health dimensions of physical, mental, and social health and reflect a mix of generic and disease-specific PROMs to enable informative intra- and inter-group comparisons.

OECD comparison

If possible, given the above-mentioned selection criteria, similar PROMs as the OECD (Organisation for Economic Co-operation and Development) PaRIS (Patient-Reported Indicator Surveys) initiative were selected to facilitate the comparability of results.

As a result, all participants will receive the PROMIS (patient-reported outcomes measurement information system) Preference Score (PROPr) [ 39 ] as well as disease-specific PROMs based on their chronic disease ( Textbox 6 ).

• Asthma: Asthma Impairment and Risk Questionnaire (AIRQ) [ 40 ]
• COPD: Clinical COPD Questionnaire (CCQ) [ 41 ]
• Diabetes: Problem Areas in Diabetes (PAID-5) [ 42 ]
• CAD: Seattle Angina Questionnaire-7 (SAQ-7) [ 43 ], and Rose Dyspnea Scale (RDS) [ 44 ]

PREMs are used to collect information about the experiences of patients with health care services. PREMs ask patients about aspects of care such as communication, coordination, and access to care [ 19 , 45 ]. The responses can provide valuable insights into how health care services are perceived by patients and how they can be improved. There are a variety of different PREMs survey available, each with its own strengths and weaknesses and focus areas. Similar to the selection of the PROMs, the selection of PREMs followed criteria of time required to complete, validity, language, licensing fees, and HSPA relevance. Consequently, participants will receive the 11-item “responsiveness” component of the IPHA questionnaire with modified observation periods, as it is validated in chronic disease patients in Germany, is available in the German language, and is relatively short (11 items) [ 46 ].

Questions on PRO Feedback

The study examines a patient's perception and reaction to individual PRO feedback. First, patients will be asked if they have opened the pdf report. In addition, the comprehensibility and usefulness of the report will be investigated by asking 1 question each. A final question is asked about a possible change in mood after seeing the results in the pdf report. The set of questions can also be found in Textbox 7 .

Review of report

• Have you looked at your health report?

Comprehensibility

• Is the information in the health report understandable to you?
• Is the information in the health report helpful for you?

Change in mood

• How do you feel based on the information in your health report?

Health Behavior

Health behavior is significantly associated with health outcomes like mortality or the occurrence of chronic diseases [ 47 ]. Regarding chronic diseases, there are 5 essential health behaviors related to health outcomes, which include physical activity, diet, smoking, alcohol consumption, and sleep [ 48 ]. Participants’ perceptions of health behavior are assessed by 1 question on each of these 5 health behavior dimensions. Thereafter, their intention to change health behavior in the coming months and triggers for change are assessed. Additionally, participants receive a question regarding whether the results were discussed with their treating physicians.

Health Insurance Data

For those participants who have given consent, health insurance claims data will be linked to the participants’ primary data after the completion of the final survey period. Claims data will contain health care resource consumption (residence, comorbidities, inpatient hospital stays, outpatient consultations, complications, rehabilitation, drugs, physiotherapy, medical remedies and aids, and care services) and additional data points further specified in the Statistical Analysis Plan ( Multimedia Appendix 1 ).

Plans to Promote Participant Retention and Complete Follow-Up

Complete survey data is important to calculate PROM scores [ 49 ]. Participants can access digital dashboards showing open tasks (questionnaires) and the remaining time to complete them. To increase data completeness, the participants will be reminded by email to fill in their follow-up questionnaires 1, 3, and 10 days after the initial dispatch of surveys.

Data Management

The collection, storage, and processing of personal data in this project are carried out in accordance with the General Data Protection Regulation in Germany, the specific data protection provisions of the Social Code, and all other national data protection regulations. During the study, all electronically recorded primary data, as well as participation and consent forms, will be stored on the server of Oncare GmbH and deleted after the end of the evaluation period. The Oncare team will manage patient information through the myoncare app and study website, always respecting data security and confidentiality. All reading and processing processes are logged in the database. All data will be collected and transferred completely pseudonymized.

Pseudonyms are created by the health insurer BARMER following the universally unique ID standard and are only re-identifiable by BARMER health insurance. Consequently, the pseudonym is added to the health insurance data to match primary patient data to insurance claims data. All identification information will be erased prior to data transfer to the research institutes Technical University Berlin and aQua Institute. Pseudonymized data will be kept for the period of data analysis of 2 years by the Technical University Berlin and aQua Institute and stored for an additional 10 years at study centers to ensure further evaluation of the study's outcome. This follows the recommendations for good practice in secondary data analysis [ 50 ].

Confidentiality

A unique study pseudonym is assigned to each participant by the health insurer. The pseudonym list with patient names will only be accessible to the health insurer, and they will not receive any primary data. During the primary data collection, no data that would allow re-identification will be collected. Minimum contact data is collected to ensure follow-up surveys can be completed and reminders can be sent to the participants. Linkage of health insurance data will be conducted via study pseudonyms. The project adheres to all data protection laws.

Statistical Methods

Statistical methods for primary and secondary outcomes.

The statistical analyses are reported in the separate Statistical Analysis Plan ( Multimedia Appendix 1 ) but generally include descriptive statistics, parametric and nonparametric methods, as well as time series analyses for the primary and secondary end points.

Methods for Additional Analyses (eg, Subgroup Analyses)

Participants with the respective chronic diseases are grouped into specific subgroups based on the research questions. For all participant groups, additional control data from overall insured patients will be accessible on an aggregated level. Therefore, the study population is segmented into different subgroups ( Figure 4 and Textbox 8 ).

• All patients: a full BARMER-insured population with at least one of the chronic diseases included in the study, with data available only at an aggregated level
• Invited patients (from “All patients”): Patients who receive the initial invitation letter
• First responders (from “Invited patients”): Patients who complete the first survey period, including consent to use their health insurance data
• Regular responders (from “First responders”): Patients who complete at least 3 out of 4 survey periods
• Full responders (from “Regular responders”): Patients who complete all 4 quarterly survey periods

Methods in Analysis to Handle Protocol Nonadherence and Any Statistical Methods to Handle Missing Data

The study is set up as a prospective observational cohort study, inviting patients to complete different surveys over a 1-year time frame. Nonadherence, defined as nonparticipation or dropout in this study, is one of the main research questions and will not be handled specifically for research question 1. Complete PROM data are important to calculate scores. In cases of missing data, we will adhere to PROM-specific guidelines to handle missing data (eg, imputation or calculating scores based on remaining values).

Composition of the Coordinating Center and Trial Steering Committee

The study is monitored by the German research center “Deutsches Zentrum für Luft- und Raumfahrt” (German Aerospace Center). Quarterly status reports are provided by the project team. Status reports include an overview of the achievement levels of the milestones defined prior to the start of the study.

Composition of the Data Monitoring Committee, Its Role, and Reporting Structure

The management of the study is overseen by a project team from Technical University Berlin. The project team is composed of researchers responsible for the study's design, representatives from the participating BARMER health insurance, the technical service provider Oncare, and the evaluating aQua Institute. Regular updates on the study's status are provided to the sponsor.

Adverse Event Reporting and Harms

Adverse events are not expected as the medical treatment of patients with chronic care is not affected. The effects of the PRO feedback intervention are one of the primary end points, and the results will be monitored and published.

Plans for Communicating Important Protocol Amendments to Relevant Parties (eg, Trial Participants and Ethical Committees)

Any substantial amendments to the protocol will be submitted to the ethics committee (see below) and all relevant regulatory institutions. Additionally, any amendments to the study design, timeline, or budget need to be communicated to the study sponsor, and approval by the coordination center must be obtained.

Dissemination Plans

The results of this study will be disseminated via publications in peer-reviewed journals and presentations at relevant conferences. Moreover, the funding institution (Innovation Fund of the Federal Joint Committee) will receive an evaluation report that includes the findings of the study as well as interim reports on the study’s milestones. All results will be aggregated, with no opportunity to reconnect on an individual patient level.

Principal Findings

The study aims to fill the gap in the literature on large-scale usage of ePROMs and ePREMs in patients with chronic diseases. First, the study protocol details how the representativity of the responses to ePROMs and ePREMs will be assessed over time in different subgroups. This foundational groundwork will help with future targeted efforts and the mitigation of representativity issues. Second, the study protocol identifies how PROMs and PREMs will be used to uncover potential low-value care for patients with chronic diseases. The results can thus inform future investigations on activities for low-value care reduction. Third, it introduces how individual PRO feedback can be shared with patients with chronic diseases and provides insights into the usability and usefulness of PRO feedback. The results of the evaluation can thereby aid the understanding of this specific PRO feedback mechanism.

ePROM collection will increasingly be the standard for capturing patients’ perspectives on treatment outcomes as well as their own health status. It was previously shown that the administrative burden for patients and health care providers can be significantly reduced through the collection of ePROMs compared with phone- or paper-based collection, while response rates and the completeness of data collection remain high [ 51 ]. The results of this study will fill the research gap in terms of the representativity of the patient population through ePROM and ePREM collection, for which no previous evidence exists. While this study uses ePROM to measure care quality variation, most of that research was focused on oncological studies [ 52 ]. This study aims to fill the research gap on measuring care quality through ePROM and ePREM usage in patients with chronic diseases. Other studies have shown, that working with PROMs can improve care by significantly reducing low-value behavior [ 53 , 54 ]. Additionally, the use of ePROMs and ePREMs can enable (almost) real-time, individual PRO feedback [ 55 - 57 ]. Providing PRO feedback is one way to enhance the use of PROMs in clinical practice and shared decision-making [ 58 ]. Previous studies indicate that patients who reviewed shared information on their PRO outcomes are more engaged and actively participate in their health care, but they have not investigated direct-to-patient feedback in patients with chronic diseases [ 59 , 60 ].

There are some limitations to the study that need to be considered. One limitation is the potential for nonresponse bias, as patients who choose to participate in the study may differ from those who do not. However, given the access route via large-scale, randomized health insurance paper-based outreach, we hope some participants who would not take part in studies in a clinical study will be accessed. Moreover, it is one of the study’s aims to detect the representativeness of the responders. Given that the letter and questionnaire will be in German, we anticipate that non-German speakers will be excluded from the study, which unfortunately could not be addressed via the digital solution, the adjustment to letters, and the low availability of validated PROMs in other languages often spoken besides German in Germany (eg, Russian or Turkish). Moreover, respondents to the study might do systematically better in terms of their PROMs and PREMs results, which cannot be assessed if there are no other systematic differences between the responder and nonresponder population [ 61 ]. This could also be the case if the monitoring itself improves health outcomes, as suggested in the current literature [ 62 , 63 ].

The broader implications of this study are insights generated for (1) ePROM and ePREM usage among patients with chronic diseases globally and specifically in Germany, as well as (2) cross-country learnings. (1) The expected benefits of PREM and PREM usage among patients with chronic diseases were previously stated by experts, while a lack of evidence in the treatment of chronic diseases exists [ 22 ]. This study will examine if and to what extent digitally collected PROMs and PREMs as well as automatically generated PRO feedback could strengthen patient empowerment, informed shared decision-making, and behavior changes in patients with chronic diseases. (2) Given that the OECD PaRIS study will assess PROMs and PREMs across many countries besides Germany, the results of this study can enable Germany to be part of this research community and to benchmark its health care system against those of other OECD countries. Long-term benchmarking results across countries and within Germany can have implications for health care spending based on patients’ needs and care reorganization while raising awareness of care value.

Trial Status

This protocol is version 1, dated October 5, 2023. Patient recruitment will begin with BARMER's letter dispatch around October 11, 2023. The collection of survey data will be finished by September 30, 2024. The study is expected to run until June 30, 2025.

Acknowledgments

The study is funded by the Innovation Fund of the German Federal Joint Committee (G-BA) in the stream “Cross-sector and outpatient usage of PROMs/PREMs.” The funding period is set for July 1, 2022, to June 30, 2025 (funding reference number 01VSF21037). JN and VS jointly prepared the manuscript for this paper. VS, CP, and RB prepared the research proposal. JN is responsible for the implementation of the trial and leading the project administration. TGG and TB provided input for the statistical analysis plan and reviewed the manuscript. CP and RB reviewed and provided valuable feedback on the manuscript. RB supervises the study. All authors reviewed and approved the final version of the protocol for submission. The authors attest that there was no use of generative artificial intelligence (AI) technology in the generation of text, figures, or other informational content in this manuscript.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Conflicts of Interest

For transparency purposes, CP is contracted full-time with Stryker Corporation, a medical technology company that also produces knee and hip implants. JN is partially employed at Boston Consulting Group GmbH, a global consulting company. All others declare that they have no relevant competing interests.

Statistical Analysis Plan.

Invitation letter for participation in the study.

Study Information and Consent Form.

Patient-reported outcome feedback.

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Abbreviations

Edited by S Ma; submitted 17.01.24; peer-reviewed by M Rose, Marie-Pierre Gagnon; comments to author 14.03.24; revised version received 28.03.24; accepted 24.04.24; published 05.08.24.

©Janis Nikkhah, Viktoria Steinbeck, Thomas G Grobe, Thorben Breitkreuz, Christoph Pross, Reinhard Busse. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 05.08.2024.

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