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Why we need a revolution in clinical research.

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Masud Husain, Why we need a revolution in clinical research, Brain , Volume 147, Issue 9, September 2024, Pages 2897–2898, https://doi.org/10.1093/brain/awae265

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We are at a pivotal moment for clinical research. In the UK, the system is fundamentally broken as recent reports have alluded to. 1 , 2 In other parts of the world too there are similar issues that are, at the very least, slowing down innovation and research. There are many factors that have been identified as contributing to this sad state of affairs in the UK. One important issue that has not attracted so much attention recently—though it was the subject of a report 3 in 2020—is the relationship between higher educational institutions (mostly universities) and healthcare providers (largely the National Health Service, NHS).

The vast majority of research activity in the UK occurs within the higher education sector, while most patient-related research such as clinical trials relies on NHS infrastructure. And this is where there is a massive disconnect. Each of these systems are huge, cumbersome behemoths, with their own local lumbering administrations focused on aims that are not aligned to the mission of producing rapid results in clinical research. In the university sector, the priorities of leaders are to keep the system financially afloat and minimize potential legal risks. Many institutions in the UK are on the cusp of fiscal ruin and so require grant and other research income to subsidize their existence. In the NHS on the other hand the aim is to cut waiting lists which, post pandemic and doctors’ industrial action, are now very lengthy, and to provide adequate service delivery. Making healthcare research effective and efficient is the last thing on the minds of the leadership of either sector.

But who can blame them? Surely, it’s difficult enough to run either a university or an NHS hospital? Indeed, this seems sufficient explanation—an adequate excuse—for some leaders of both these types of institution for the huge delays in getting any useful research done. Many teams are now waiting over a year to get their grant-funded research off the ground. Remarkably, some trials are failing because they never start, several years after the funding has been awarded. Material or data transfer agreements between universities; slothful legal reviews of contracts and agreements with third parties; calculating overheads to be charged; multiple reviews of research protocols by R&D departments; dragging of feet over costings independently for the university and hospital; sluggish reviews by research services; signing off contracts with the NHS; obtaining honorary contracts for non-clinical personnel; and many other procedures may take months, if not years, to complete. The system is both Byzantine and exasperating to navigate. No wonder that pharmaceutical companies are balking at initiating trials in the UK, their gaze turning instead to countries where they are more serious about getting things done sooner, not later. 1

So how do we get out of this mess? Given the narrow goals that the leaderships of universities and NHS hospitals have, we cannot expect a great deal more from them on this front— unless they are compelled to make changes. In the UK, when the National Institute for Health and Care Research (NIHR) was formed in 2006, many of us were under the impression that its mission really was to ‘create a health research system in which the NHS supports outstanding individuals, working in world-class facilities, conducting leading-edge research focused on the needs of patients and the public’. 4 Clearly though this just hasn’t happened. Otherwise, why the need for recent reports? 1 , 2

One of the key reasons for this failure (we cannot refer it to it as anything else) is the simple fact that universities and NHS infrastructure are not joined up. Many pretend to be, but it is obvious to anyone who works at even the best centres in the UK that this is a sham. At Oxford, one of the hospital networks calls itself the Oxford University Health NHS Foundation Trust, but there really is very little to suggest why ‘University’ should be in its title. The levels of duplication of work and contracting between the university and the hospital make a mockery of the concept of seamless integration between these institutions. It is the same elsewhere too. The result is a growing duopoly of administrations that negotiate with each other, waste time and slow the pace of progress. Even when a research proposal has been approved by a ‘joint’ R&D unit, there needs to be a costings agreement between university and NHS trust.

From a national perspective this makes little sense, either economically or for governance. We are in the bizarre situation where two sets of institution—universities and hospitals—both largely funded by taxpayers are independently setting their (growing) administrative staffs to scrutinize research protocols or haggle over costings on projects that are mostly funded by government or charities. It is even worse for multicentre studies when many different universities and NHS trusts each want a share of the pie. This has a hidden cost in numbers of people employed, researchers’ time dealing with paperwork, and an opportunity cost in terms of time taken to get studies off the ground. Furthermore, there is no incentive to do things better or faster. There is simply a parochial incentive to make money locally and mitigate risks locally . Until the day that universities and hospitals associated with them are compelled to work as one integrated unit, there is very little hope for change. We will be left in the current quagmire of structural indolence. And that is why we need a revolution. Writing more reports on the matter will not help.

It is interesting to reflect on the fact that it was also radical change that was necessary to bring medicine into the modern era—to make it based on observation, clinical examination and the scientific method—in the first place. From the confusing and sometimes bizarre practices that characterized medicine in the 18th century, there emerged a new way of doing things which came about within one generation and in perhaps one of the least advanced places in Europe for clinical science at that time: Paris. From being a backwater, the ‘Paris School of Medicine’ instigated such dramatic change that within 50 years it became the leading international centre for clinical practice, attracting physicians from around the world to learn about the ‘new medicine’. 5

The rise of scientific medicine in Paris depended on systematic correlation of physical examination findings on hundreds of patients with pathological findings at post-mortem; flexibility to revise diagnoses on the basis of these assessments; deployment of statistics, including data on mortality; and most of all on conducting this work and teaching it to medical students in hospitals. 5 What made this possible was reform. Before the French Revolution, control of medical care rested largely with the Church. With the reform of medical education that came after the Revolution, hospitals were centralized and their administration was overseen by the state. Fundamental changes in the way in which faculties of medicine were organized in France led the way for dramatic new ways of learning from patients and disseminating knowledge to clinicians. Medical education was transformed but it needed the convulsive change of a Revolution to make this happen. 6 It required top-down edicts to bring about change because there was no incentive for the old institutions to make those changes themselves.

We are now confronted with a similar problem. The old institutions—universities and hospitals—are used to doing things their way. There is no incentive for them to change unless the state or its organs of power intervene. In the UK, NIHR funds now support Biomedical Research Centres (BRCs) which supposedly cross universities and NHS hospital trusts, but in truth the fiscal support helps to prop up university research personnel with very little going to the NHS. Most importantly, the NIHR has not insisted on BRCs having joined up (i.e. single) integrated, university-NHS systems in place, or for seamless national transfer of approvals across sites without the need for new sets of contractual agreements. Nothing fundamental will change unless it or the new government compels this change. The pursuit of national interests requires national leadership to intervene; we can't rely on local, devolved institutions to make the obvious decisions that are required. This is why we need a revolution in healthcare research.

O’Shaughnessy J . Commercial clinical trials in the UK: The Lord O’Shaughnessy review - final report. Accessed 13 August 2024. https://www.gov.uk/government/publications/commercial-clinical-trials-in-the-uk-the-lord-oshaughnessy-review/commercial-clinical-trials-in-the-uk-the-lord-oshaughnessy-review-final-report

The Academy of Medical Sciences . Future-proofing UK health research: A people-centred, coordinated approach. https://acmedsci.ac.uk/file-download/23875189

The Academy of Medical Sciences . Transforming health through innovation: integrating the NHS and academia. https://acmedsci.ac.uk/file-download/23932583

Department of Health and Social Care . Best research for best health: a new national health research strategy. https://www.gov.uk/government/publications/best-research-for-best-health-a-new-national-health-research-strategy

La Berge A , Hannaway C . Paris medicine: Perspectives past and present . Clio Med . 1998 ; 50 : 1 – 69 .

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Ackerknecht EH . Medicine at the Paris hospital, 1794–1848 . Johns Hopkins University Press ; 1967 .

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Unlike scholarly journals, magazines are written for a mainstream audience and are not peer-reviewed. A handful of academic journals (like Science and Nature ) blur the line between these two categories; they publish peer-reviewed articles, but combine them with news, opinions, and full-color photos in a magazine-style presentation.

Trade journals are targeted toward a specific profession or industry. Despite the name, they are usually not peer-reviewed. However, they sometimes represent a gray area between popular magazines and scholarly journals. When in doubt, ask your professor or TA whether a specific source is acceptable.

Newspapers as Primary Sources

Though usually written by journalists who were not direct witnesses to events, newspapers and news broadcasts may include quotes or interviews from people who were. In the absence of first-person accounts, contemporary news reports may be the closest thing to a primary source available.

Of all the content types listed here, newspapers are the fastest to publish. Use newspaper articles to find information about recent events and contemporary reports of/reactions to historic events.

• News by UCLA Library Last Updated Aug 30, 2024 9588 views this year

Reviews are a type of article that can appear in any of the categories above. The type of publication will usually determine the type of review. Newspapers and magazines review movies, plays, general interest books, and consumer products. Academic journals review scholarly books.

Note that a review is not the same as scholarly analysis and criticism! Book reviews, even in scholarly journals, are usually not peer-reviewed.

Conference papers aren't always published and can be tricky to find . Recent conference papers are often online, along with the PowerPoint files or other materials used in the actual presentation. However, access may be limited to conference participants and/or members of the academic organization which sponsored the conference.

In paper formats, all of the papers from a certain conference may be re-printed in the conference proceedings . Search for Proceedings of the [name of conference] to find what's available, or ask for help from a librarian. But be aware that published proceedings may only include abstracts or even just the name of the presenter and the title of the presentation. This is especially true of poster presentations , which really are large graphic posters (which don't translate well to either printed books or computer monitors).

As the name implies, most technical reports are about research in the physical sciences or engineering. However, there are also technical reports produced in the life and social sciences,

Like conference papers , some technical reports are eventually transformed into academic journal articles , but they may also be released after a journal article to provide supplementary data that didn't fit within the article. Also like conference papers, technical reports can be hard to find , especially older reports which may only be available in microfiche . Ask for help from a librarian!

Anthologies are a cross-over example. They're books that contain articles (chapters). Anthologies may be collections of articles by a single author, or collections of articles on a theme from different authors chosen by an editor. Many anthologies reprint articles already published elsewhere, but some contain original works.

Anthologies are rarely peer-reviewed, but they still may be considered scholarly works, depending on the reputation of the authors and editors. Use the same criteria listed for scholarly books .

Of course, reprints of articles originally published in peer-reviewed journals retain their "scholarly" status. (Note that most style manuals have special rules for citing reprinted works.)

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Letting funding for the All of Us research program lapse will cost the U.S. far more than it saves

Investing in preventive medicine and drug target discovery now will save lives and billions of dollars.

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By Pradeep Natarajan

Sept. 3, 2024

Natarajan is the director of preventive cardiology at Massachusetts General Hospital.

I was in high school when I first encountered the ruthlessness of the number one killer in the U.S. A close friend of mine, then only 16 years old, witnessed his father having a heart attack while checking the mail. Despite desperate attempts at CPR on the driveway, he wasn’t able to save his dad, a seemingly healthy man in his early 40s. That event put me on a path to become a cardiologist. Twenty-five years later, as a physician at Massachusetts General Hospital in Boston, I’m still seeing young patients having heart attacks, though they often have nothing in their health profiles to indicate increased risks.

As a preventive cardiologist, I wish I had a better way to identify patients who have a heightened risk for heart disease earlier so that they can take action before it’s too late. Prevention is the best medicine — it saves lives and health care dollars — but in our current paradigm, we’re focused on treating conditions after they occur.

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Fortunately, there is a new, effective way to better find those at highest risk very early in life, well before they develop risk factors like diabetes or high blood pressure. My research group at Massachusetts General Hospital and the Broad Institute of MIT and Harvard, and many other labs, have been developing genetic tests that can predict disease risk well before disease becomes apparent, called polygenic risk scores.

These types of predictive tests and genetics-informed treatments hold enormous promise for the fight against heart disease, diabetes, cancer, and so much more. Polygenic risk scores have been developed for heart attack and other forms of heart disease, but they aren’t currently accurate for many segments of the U.S. population.

The only way to make these tools actually work for the diverse U.S. population is to study the health profiles of hundreds of thousands of Americans. Generating these profiles is precisely a key goal of All of Us, a federal precision-medicine research effort that’s now facing a potentially fatal funding cliff.

This world-leading initiative, launched in 2018, is recruiting 1 million volunteers from across the U.S. The project is collecting their health, medical, and genetic information, and making that large and invaluable dataset available to scientists like me so that we can find new drug targets and develop preventive tests from genetics for a wide range of diseases.

The data that All of Us has collected so far represents people from all across America, including those from rural and urban communities and from all walks of life. These people are helping us develop better polygenic risk scores and novel therapeutic strategies that will improve the health of all Americans for generations to come. But without full support from Congress, All of Us will only be able to generate roughly half of the genetic data it has promised. Less data from fewer communities means less accurate genetic tests and fewer new drugs that can keep people out of the emergency room.

All of Us faces a whopping 71% decrease in funding for the coming fiscal year, which starts Oct. 1, compared with its funding level just two years ago. That’s because a major source of its first round of funding, in the 2016 21st Century Cures Act, was designed with fluctuating budget levels over 10 years. This cut is but the start. With just two years left, the clock is nearly up entirely. While I am hopeful about recent efforts from two members of the House on a Cures 2.0 bill and from the Senate Appropriations Committee to restore All of Us funding to the FY 2023 level, it’ll be up to both chambers of Congress this fall to ensure this important program has stable funding to keep going.

All of Us is only half complete, and a loss of stable funding threatens its timeliness and impact. It is unclear how many more Americans will be able to sign up to contribute to this work; I worry that without the necessary support, recruitment levels will fall sharply and data generation will slow dramatically. 

This funding loss will be a blow for preventive medicine in another way, too, by starving the drug development pipeline of much needed new drug targets that are rooted in human genetics. Many in the drug discovery world are familiar with the story of PCSK9 inhibitors, which lower LDL cholesterol levels to help prevent heart disease. These treatments were first approved by the Food and Drug Administration in 2015, just 10 years after genetic studies — similar to the ones that All of Us data can empower — suggested that the PCSK9 gene would be a promising target for cholesterol drugs. The big difference with the full set of All of Us data is that it would include many more people from underrepresented populations, which likely harbor disease-associated gene targets that are yet to be discovered. Without this entire diverse dataset, the genetics community will miss out on opportunities to generate more drug discovery success stories like the PCSK9 one.

This program has another advantage: maintaining and extending this country’s global edge in the life sciences. Other countries with nationalized health systems, like the United Kingdom and Finland, are making progress toward their own large genetic and medical datasets, or biobanks, that reflect the health status of their populations. While this information is useful for researchers all over the world, it is insufficient for developing the genetic insights, diagnostics, and treatments that are most relevant for Americans, because it doesn’t account for the population diversity and unique experiences and environments of the American people the way that All of Us data would.

All of Us is a big bet on a better future. Genomics-based tools will be critical for preventing and treating disease. Better prevention and treatment would save lives, livelihoods, and money: for heart disease alone, the American Heart Association projects annual inflation-adjusted health care costs will triple in the next two decades, from $400 billion to $1.34 trillion.

By restoring funding to All of Us, Congress can help deliver on the promise of a better health care system, and better health for all Americans.

Pradeep Natarajan, M.D., is the director of preventive cardiology and the Paul and Phyllis Fireman endowed chair in vascular medicine at Massachusetts General Hospital (MGH), associate professor of medicine at Harvard Medical School, and associate member of the Broad Institute of MIT and Harvard. MGH and Broad are both institutional recipients of All of Us funding to advance research. Dr. Natarajan does not receive direct funding from All of Us.

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About the reporting

STAT’s investigation is based on interviews with nearly 100 people around the country, including incarcerated patients and grieving families, prison officials, and legal and medical experts. Reporter Nicholas Florko also filed more than 225 public records requests and combed through thousands of pages of legal filings to tell these stories. His analysis of deaths in custody is based on a special data use agreement between STAT and the Department of Justice.

You can read more about the reporting for this project and the methodology behind our calculations.

The series is the culmination of a reporting fellowship sponsored by the Association of Health Care Journalists and supported by The Commonwealth Fund.

Pradeep Natarajan

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
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Research bias

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Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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• What Is a Research Design | Types, Guide & Examples
• Data Collection | Definition, Methods & Examples

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• Between-Subjects Design | Examples, Pros, & Cons
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• Control Variables | What Are They & Why Do They Matter?
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• Correlational Research | When & How to Use
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• How to Do Thematic Analysis | Step-by-Step Guide & Examples
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• Population vs. Sample | Definitions, Differences & Examples
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• Transcribing an Interview | 5 Steps & Transcription Software
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• Types of Variables in Research & Statistics | Examples
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• What Is Non-Probability Sampling? | Types & Examples
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• What Is Peer Review? | Types & Examples
• What Is Predictive Validity? | Examples & Definition
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• What Is Qualitative Observation? | Definition & Examples
• What Is Qualitative Research? | Methods & Examples
• What Is Quantitative Observation? | Definition & Examples
• What Is Quantitative Research? | Definition, Uses & Methods

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JD Vance got ‘single cat women’ all wrong. Our research shows they wouldn’t vote for him anyway

Professor of Sociology and Founding Director of The Future of Work Lab, Podcast at MissPerceived, The University of Melbourne

Associate Professor of Political Science, Oregon State University

Associate Professor of Sociology, Oregon State University

Disclosure statement

Leah Ruppanner receives funding from the Australian Research Council. She is also the host of MissPerceived podcast, where she discusses gender research.

Christopher Stout and Kelsy Kretschmer do not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

University of Melbourne provides funding as a founding partner of The Conversation AU.

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The Trump/Vance ticket seems to have a problem attracting the support of women voters . In fact, recent polling shows women in the battleground states report 17 points less support for the Trump/Vance ticket than men .

When the data are split generationally, this gender divide becomes even more stark. Among those aged 18–29, there is a 51-point gender gap . Women in this age bracket support Trump at just 13 points, while women support Harris by 38 points.

There are likely numerous reasons for this growing gender gap, including the historic nature of Harris’ campaign and Trump’s numerous well-documented conflicts with women . However, one source of these polling deficits may be tied to Trump’s vice presidential nominee’s attack on single women and women without children.

As JD Vance emerged as the vice presidential pick for the Trump ticket, a 2021 Fox News Interview resurfaced in which he said the country was being run by a

bunch of childless cat ladies who are miserable at their own lives and the choices that they’ve made and so they want to make the rest of the country miserable, too.

In another interview around the same time, he questioned whether the president of the American Federation of Teachers should be working on school policy , because she did not have children.

The challenge for the Trump/Vance ticket is that, as our research shows , single women are much more likely to see their futures as connected to other women. As a result, they are more likely to support the Democrats. Shaming them for their single status only reinforces their connection to other women, and a vote for Harris.

We are connected: the role of gender linked fate

Our research team has been investigating the concept of “gender-linked fate”, or agreement with the idea that what happens to women in general will affect women’s own lives. This work follows previous research in the US that found Black voters tend to report higher levels of racial-linked fate , or seeing their futures and fates as intrinsically tied to those of other Black people. This link helps explain why Black voters in the US consistently vote Democratic, despite coming from diverse educational and income backgrounds.

We used the 2012 American Election Survey to see if women’s levels of gender-linked fate predicted their political affiliation. And, we found that one group was a standout in their exceptionally high rates of gender-linked fate: single White and Latina women. More than three-quarters of White and Latina single women reported that their futures were tied to what happened to women in general. One in three reported that influence was significant.

So, single women felt particularly connected to other women. Black women’s universally higher levels of gender-linked fate meant that their marital status had little impact on their levels of connection to other women.

We then looked to see if levels of gender linked fate helped explain political ideologies, or levels of conservatism and progressivism, and political party support. We found single women’s higher levels of gender linked fate helped explain why they held more progressive attitudes and were less likely to identify as Republicans than their married counterparts.

Women see the hardships other women ensure

So, JD Vance is right – single women are less likely to be conservative and vote for his ticket. But, it has nothing to do with them being miserable. Rather, they have a unique view of the experiences of woman in a society they feel is stacked against them. We aren’t the only ones to show this. Previous research shows single women are more likely to experience poverty and, despite being more likely to work than married women, earn less .

As a result, single women are more likely to support policies that advance opportunities for all women, especially as they have to rely more heavily on their own incomes. They are also more likely to see gender discrimination at work and gender pay gaps that aren’t tied to individual successes or failures.

They are more likely to be pro-choice , in part because they see their futures and fates as more connected to other women. And women who see themselves as connected to other women are more likely to vote for women .

Group-based attacks are not a winning strategy

Attacking women for their life choices is likely to increase levels of group consciousness among women. When women feel marginalised, they tend to display higher levels of gender-linked fate . Vance trivialising the value of the work of women without children is likely to highlight the marginalisation they feel in society. This greater recognition of the shared bonds that are forged from shaming likely heightens their sense of connection to others who share their gender and circumstance.

This sense of gender-linked fate, which is likely furthered by these comments, will amplify support for the Democratic ticket. Not only should higher levels of gender link fate lead women to feel a greater disconnect between their preferences and the Republican Party’s positions around reproductive rights and gender equity, but it may also increase support for the Harris campaign’s attempt to break the glass the ceiling.

To learn more about research on women in politics, tune into this week’s episode of MissPerceived podcast .

• 2024 US election

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Energy Innovation Hub teams will emphasize multi-disciplinary fundamental research to address long-standing and emerging challenges for rechargeable batteries

WASHINGTON, D.C . - Today, the U.S. Department of Energy (DOE) announced $125 million in funding for two Energy Innovation Hub teams to provide the scientific foundation needed to seed and accelerate next generation technologies beyond today’s generation of lithium (Li)-ion batteries. These multi-institution research teams, led by Argonne National Laboratory and Stanford University, will develop scientific concepts and understanding to impact decarbonization of transportation and incorporation of clean energy into the electricity grid.

Rechargeable batteries, such as Li-ion and lead-acid batteries, have had a tremendous impact on the nation’s economy. Emerging applications will require even greater energy storage capabilities, safer operation, lower costs, and diversity of materials to manufacture batteries. Meeting these challenges requires a better understanding of foundational battery and materials sciences to enable scalable battery designs with versatile and reversible energy storage capabilities beyond what is currently possible. Additional benefits may include mitigation of supply chain risks associated with the current generation of batteries.

"Providing the scientific foundation to accelerate this important research is key to our economy and making sure the U.S. plays a lead role in transforming the way we store and use electricity,” said Harriet Kung, DOE’s Acting Director for the Office of Science. “Today's awards provide our Energy Innovation Hub teams with the tools and resources to solve some of the most challenging science problems that are limiting our ability to decarbonize transportation and incorporate clean energy into the electricity grid."

The two Energy Innovation Hub teams are the Energy Storage Research Alliance (ESRA) led by Argonne National Laboratory and the Aqueous Battery Consortium (ABC) led by Stanford University. ESRA will provide the scientific underpinning to develop new compact batteries for heavy-duty transportation and energy storage solutions for the grid with a focus on achieving unprecedented molecular-level control of chemical reactivity, ion selectivity, and directional transport in complex electrochemical cells. ABC will focus on establishing the scientific foundation for large-scale development and deployment of aqueous batteries for long-duration grid storage technologies.  Both of these teams will prioritize study and use of Earth-abundant materials to mitigate supply chain risks.

Both Energy Innovation Hubs teams are comprised of multiple institutions, including Historically Black Colleges and Universities (HBCUs) and other Minority Serving Institutions (MSIs). The projects provide an outstanding opportunity for workforce development in energy storage research and inclusive research involving diverse individuals from diverse institutions. 

The teams were selected by competitive peer review under the DOE Funding Opportunity Announcement for the Energy Innovation Hub Program: Research to Enable Next-Generation Batteries and Energy Storage. While focused on basic science, the Funding Opportunity Announcement was developed in coordination through the DOE Joint Strategy Team for Batteries.

Total funding is $125 million for awards lasting up to five years in duration. More information can be found on the Basic Energy Sciences program  homepage and  Energy Innovation Hubs page.

Selection for award negotiations is not a commitment by DOE to issue an award or provide funding. Before funding is issued, DOE and the applicants will undergo a negotiation process, and DOE may cancel negotiations and rescind the selection for any reason during that time. 

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This is a summary of: Charalambous, C. et al . A holistic platform for accelerating sorbent-based carbon capture. Nature 632 , 89–94 (2024) .

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doi: https://doi.org/10.1038/d41586-024-02819-2

‘Expert opinion’ and the figure are published under a CC BY 4.0 licence.

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