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Patient activation in adults with visual impairment: a study of related factors

This study aims to analyze variables related to patient activation in 78 individuals with visual impairment. The Patient Activation Measure (PAM) scores of participants showed no differences between males and ...

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The impact of social cohesion and risk communication on excess mortality due to COVID-19 in 213 countries: a retrospective analysis

Tools for assessing a country’s capacity in the face of public health emergencies must be reviewed, as they were not predictive of the COVID-19 pandemic. Social cohesion and risk communication, which are relat...

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Overdose-related suicide attempts represent a significant portion of self-harm presentations in the psychiatric emergency department (ED). Identifying specific patient characteristics associated with these att...

Co-occurrence of obesogenic behaviors and their implications for mental health during the COVID-19 pandemic: a study with university students

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YouTube/ Bilibili/ TikTok videos as sources of medical information on laryngeal carcinoma: cross-sectional content analysis study

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Uncovering multi-level mental healthcare barriers for migrants: a qualitative analysis across China, Germany, Netherlands, Romania, and South Africa

Forced displacement is a significant issue globally, and it affected 112 million people in 2022. Many of these people have found refuge in low- and middle-income countries. Migrants and refugees face complex a...

Work environment adversity and non-communicable Disease risk among drivers working for application-based-cab-aggregators in an Indian metropolis

Bengaluru, a metropolis in Southern India, is one of the largest markets for cab aggregator companies. Drivers working for these companies play a vital role in urban transportation but unlike other drivers, th...

Unravelling the Belgian cascade of hypertension care and its determinants: insights from a cross-sectional analysis

Hypertension is a major risk factor for cardiovascular disease and all-cause mortality worldwide. Despite the widespread availability of effective antihypertensives, blood pressure (BP) control rates remain su...

Secular trend of Kawasaki disease and its correlation with viral activity in Taiwan: a nationwide population-based study

Kawasaki disease (KD) is the most important acquired heart disease in children. This study investigated annual incidence, seasonality, secular trend and the correlation of KD incidence with viral activity in T...

Comparison of food intake pattern of diabetic patients and healthy individuals in a sample of Saudi population: a case-control study

There has been a significant rise in the number of individuals diagnosed with type 2 diabetes mellitus (T2DM), with the condition reaching epidemic proportions globally. This study examined the dietary pattern...

Impact of the pandemic on leisure physical activity and alcohol consumption

The COVID-19 pandemic precipitated heightened morbidity and elevated mortality attributed to the SARS-CoV-2 infection. The pandemic also influenced health behaviors such as physical activity (PA) and alcohol c...

Characterizing the utilization of doula support services among birthing people of color in the United States: a scoping review

Birthing people of color experience disproportionately higher rates of infant and maternal mortality during pregnancy and birth compared to their white counterparts. The utilization of doula support services m...

Instagram for audience engagement: an evaluation of CERC framework in the GCC nations for digital public health during the Covid-19 pandemic

In this study, we investigate the utilization of Instagram by public health ministries across the Gulf Cooperation Council (GCC) nations to disseminate health-related information during the COVID-19 pandemic. ...

Systemic inflammatory biomarkers are novel predictors of all-cause and cardiovascular mortality in individuals with osteoarthritis: a prospective cohort study using data from the NHANES

Chronic inflammation may contribute to increased mortality risk in individuals with osteoarthritis (OA), but research on the prognostic value of inflammatory biomarkers is limited. We aimed to evaluate the ass...

Notable dysthymia: evolving trends of major depressive disorders and dysthymia in China from 1990 to 2019, and projections until 2030

Depressive disorders have been identified as a significant contributor to non-fatal health loss in China. Among the various subtypes of depressive disorders, dysthymia is gaining attention due to its similarit...

The association between the child’s age and mothers’ physical activity: results from the population-based German National Cohort study

Since physical activity is an important determinant of physical and mental health, lower levels of physical activity among mothers reported in previous research are concerning. The aim of this study was to exa...

Infant feeding experiences among Indigenous communities in Canada, the United States, Australia, and Aotearoa: a scoping review of the qualitative literature

Although exclusive breastfeeding is recommended for the first six months of life, research suggests that breastfeeding initiation rates and duration among Indigenous communities differ from this recommendation...

Exploring the perspectives of older adults who are pre-frail and frail to identify interventions to reduce sedentary behaviour and improve mobility: a thematic content analysis

Older adults who are frail are one of the most sedentary and the least physically active age groups. Prolonged sedentary time is associated with increased risk of negative health outcomes. To help design effec...

Air pollutants, seasonal influenza, and acute otitis media in children: a population-based analysis using 22-year hospitalization data

Acute otitis media (AOM) is a prevalent childhood acute illness, with 13.6 million pediatric office visits annually, often stemming from upper respiratory tract infections (URI) and affected by environmental f...

Assessment of non-communicable disease risk factors, functional performance, and health-related quality of life in adults: a comparative analysis in low-resourced urban and rural areas of South Africa

Globally, disparities between non-communicable disease (NCD) risk factors, functional performance, and health-related quality of life (HRQoL) exist in people living in rural and low-resourced urban settings. E...

Prevalence and trends of Chlamydia trachomatis infection in female sex workers and men who have sex with men in China: a systematic review and meta-analysis

Chlamydia trachomatis infection can cause a significant disease burden in high-risk populations. This study aimed to assess the overall prevalence of C. trachomatis infection, and determine the long-term trends a...

Clostridium and Cryptosporidium outbreak linked to a splash pad

. Splash pads for recreational purposes are widespread. Using these pads can pose a health risk if they lack installation regulation and water quality supervision. Our aim was to describe a waterborne disease ...

Disparities in cause-specific mortality by health insurance type and premium: evidence from Korean NHIS-HEALS cohort study, 2002–2019

Although one’s socioeconomic status affects health outcomes, limited research explored how South Korea’s National Health Insurance (NHI) system affects mortality rates. This study investigated whether health i...

Understanding the associations between information sources, sociodemographics, and views on public health measures: evidence from the COVID-19 pandemic in Austria

Throughout the COVID-19 pandemic, it was a key priority for governments globally to ensure agreement with, and subsequently adherence to, imposed public health measures, specifically non-pharmaceutical interve...

Hepatitis B discrimination: global responses requiring global data

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“It’s another gay disease”: an intersectional qualitative approach contextualizing the lived experiences of young gay, bisexual, and other sexual minoritized men in the United States during the mpox outbreak

The U.S. mpox outbreak in 2022 introduced new and exacerbated existing challenges that disproportionately stigmatize gay, bisexual, and other sexual minoritized men (GBSMM). This study contextualizes the perce...

Utilization of machine learning for dengue case screening

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine l...

Estimating the causal effects of income on health: how researchers’ definitions of “income” matter

There is a well-established cross-sectional association between income and health, but estimates of the causal effects of income vary substantially. Different definitions of income may lead to substantially di...

Can #chatsafe support parents and carers beyond Australia? A qualitative study

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Community interpreting in Germany: results of a nationwide cross-sectional study among interpreters

Community interpreters (CIPs) play a crucial role in various community services, including healthcare, when service providers and users do not share a common language. However, there is a lack of evidence-base...

Risk of breakthrough infection and hospitalisation after COVID-19 primary vaccination by HIV status in four Italian regions during 2021

As of 2024, vaccination remains the main mitigation measure against COVID-19, but there are contradictory results on whether people living with HIV (PLWH) are less protected by vaccines than people living with...

Effectiveness of cognitive rehearsal programs for the prevention of workplace bullying among hospital nurses: a systematic review and meta-analysis

To solve the problem of workplace bullying among nurses, it is necessary to review the effects of interventions and generalize the findings. We conducted a systematic literature review and meta-analysis to eva...

Collaboration in the return-to-work process after sick leave due to common mental disorders: a qualitative study of stakeholders’ views on goals and roles

This study explores how the goals of collaboration in the return-to-work (RTW) process for people with common mental disorders are described by the stakeholders involved, and how they experience stakeholders’ ...

The role of gender in health insurance enrollment among geriatric caregivers: results from the 2022 informal caregiving, health, and healthcare survey in Ghana

Female informal caregivers of older adults experience a higher burden of physical and mental health problems compared to their male counterparts due to the greater intensity of care they provide. This is likel...

The impact of retirement on blood pressure: evidence from a nationwide survey in China

The health impact of retirement is controversial. Most previous studies have been based on self-reported health indicators or the endpoints of some chronic diseases (e.g., morbidity or mortality), but objectiv...

The challenges associated with the prevention of smuggling and counterfeiting health goods in Iran

Smuggling health goods given the importance and critical nature of health services should be undeniably addressed and controlled by all countries. This issue is especially more widespread in developing countri...

Using the International Alcohol Control (IAC) policy index to assess effects of legislative change in Aotearoa New Zealand

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Unraveling agricultural water pollution despite an ecological policy in the Ayeyarwady Basin

The Ayeyarwady Basin in Myanmar, a critical economic zone, faces severe ecological degradation due to unsustainable agricultural practices. These practices pose significant threats to human health and marine b...

The role of the environment: how mask wearing varies across different activities

People’s decisions to engage in protective health behaviors, such as mask wearing during the COVID-19 pandemic, are influenced by environmental and social contexts. Previous research on mask wearing used a sin...

Network development in workplace health promotion – empirically based insights from a cross-company network promoting physical activity in Germany

In the field of health promotion, interorganisational networks are of growing relevance. However, systematic and target-oriented network management is of utmost importance for network development. The aim of t...

Do sociodemographic risk profiles for adolescents engaging in weekly e-cigarette, cigarette, and dual product use differ?

E-cigarette use represents a contemporary mode of nicotine product use that may be changing the risk profile of participating adolescents. Understanding differences in sociodemographic characteristics of adole...

Using structural equation modeling to examine correlations between health-related physical fitness and cell health among Chinese college students

College students’ physical fitness is likely to be directly related to their cells’ health. However, there is a lack of literature on whether the relationship between cell health and college students’ physical...

The perception of genetic diseases and premarital screening tests in the central region of Saudi Arabia

The prevalence of consanguineous marriages (CMs) varies worldwide from one country to another. However, the Middle East stands out as a region with a notably high rate of CMs. CM is particularly widespread in ...

Association between short-term exposure to ambient air pollutants and the risk of hospital visits for acute upper respiratory tract infections among adults: a time-series study in Ningbo, China

Acute upper respiratory tract infections (AURTIs) are prevalent in the general population. However, studies on the association of short-term exposure to air pollution with the risk of hospital visits for AURTI...

Correction to: BMC Public Health 21:408 & 21:2336

The original article was published in BMC Public Health 2022 21 :2336

The original article was published in BMC Public Health 2021 21 :408

Movement behaviour typologies and their associations with adiposity indicators in children and adolescents: a latent profile analysis of 24-h compositional data

Growing evidence supports the important role of 24-hour movement behaviours (MB) in preventing childhood obesity. However, research to understand the heterogeneity and variability of MB among individuals and w...

Care-seeking strategies of migrants during the transition from a specific primary healthcare facility for uncovered individuals to common ambulatory general practice: A French qualitative study

Migrants have complex health needs but face multiple barriers to accessing health care. In France, permanent healthcare access offices (PASSs), as specific primary health care facilities (SPHCs), provide care ...

Nutrient deficiency patterns and all-cause and cardiovascular mortality in older adults with hypertension: a latent class analysis

Previous researches examining the impact of dietary nutrition on mortality risk have mainly focused on individual nutrients, however the interaction of these nutrients has not been considered. The purpose of t...

Whether weekend warriors (WWs) achieve equivalent benefits in lipid accumulation products (LAP) reduction as other leisure-time physical activity patterns? -Results from a population-based analysis of NHANES 2007–2018

Obesity is characterized by excessive fat accumulation in the body. Physical activity (PA) is an effective intervention to combat obesity, but the effectiveness of different PA patterns on controlling obesity ...

The association between HIV infection, disability and lifestyle activity among middle-aged and older adults: an analytical cross-sectional study in Ivory Coast (the VIRAGE study)

People living with HIV (PLWH) live longer and face new health challenges resulting from the confluence of chronic HIV infection and the natural effect of aging and comorbidities. However, there is a dearth of ...

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Research Article

Assessing the impact of healthcare research: A systematic review of methodological frameworks

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

Affiliation Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Roles Data curation, Formal analysis, Methodology, Validation, Writing – review & editing

Roles Formal analysis, Methodology, Supervision, Validation, Writing – review & editing

• Samantha Cruz Rivera, 
• Derek G. Kyte, 
• Olalekan Lee Aiyegbusi, 
• Thomas J. Keeley, 
• Melanie J. Calvert

• Published: August 9, 2017
• https://doi.org/10.1371/journal.pmed.1002370
• Reader Comments

Increasingly, researchers need to demonstrate the impact of their research to their sponsors, funders, and fellow academics. However, the most appropriate way of measuring the impact of healthcare research is subject to debate. We aimed to identify the existing methodological frameworks used to measure healthcare research impact and to summarise the common themes and metrics in an impact matrix.

Methods and findings

Two independent investigators systematically searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), the Excerpta Medica Database (EMBASE), the Cumulative Index to Nursing and Allied Health Literature (CINAHL+), the Health Management Information Consortium, and the Journal of Research Evaluation from inception until May 2017 for publications that presented a methodological framework for research impact. We then summarised the common concepts and themes across methodological frameworks and identified the metrics used to evaluate differing forms of impact. Twenty-four unique methodological frameworks were identified, addressing 5 broad categories of impact: (1) ‘primary research-related impact’, (2) ‘influence on policy making’, (3) ‘health and health systems impact’, (4) ‘health-related and societal impact’, and (5) ‘broader economic impact’. These categories were subdivided into 16 common impact subgroups. Authors of the included publications proposed 80 different metrics aimed at measuring impact in these areas. The main limitation of the study was the potential exclusion of relevant articles, as a consequence of the poor indexing of the databases searched.

Conclusions

The measurement of research impact is an essential exercise to help direct the allocation of limited research resources, to maximise research benefit, and to help minimise research waste. This review provides a collective summary of existing methodological frameworks for research impact, which funders may use to inform the measurement of research impact and researchers may use to inform study design decisions aimed at maximising the short-, medium-, and long-term impact of their research.

Author summary

Why was this study done.

• There is a growing interest in demonstrating the impact of research in order to minimise research waste, allocate resources efficiently, and maximise the benefit of research. However, there is no consensus on which is the most appropriate tool to measure the impact of research.
• To our knowledge, this review is the first to synthesise existing methodological frameworks for healthcare research impact, and the associated impact metrics by which various authors have proposed impact should be measured, into a unified matrix.

What did the researchers do and find?

• We conducted a systematic review identifying 24 existing methodological research impact frameworks.
• We scrutinised the sample, identifying and summarising 5 proposed impact categories, 16 impact subcategories, and over 80 metrics into an impact matrix and methodological framework.

What do these findings mean?

• This simplified consolidated methodological framework will help researchers to understand how a research study may give rise to differing forms of impact, as well as in what ways and at which time points these potential impacts might be measured.
• Incorporating these insights into the design of a study could enhance impact, optimizing the use of research resources.

Citation: Cruz Rivera S, Kyte DG, Aiyegbusi OL, Keeley TJ, Calvert MJ (2017) Assessing the impact of healthcare research: A systematic review of methodological frameworks. PLoS Med 14(8): e1002370. https://doi.org/10.1371/journal.pmed.1002370

Academic Editor: Mike Clarke, Queens University Belfast, UNITED KINGDOM

Received: February 28, 2017; Accepted: July 7, 2017; Published: August 9, 2017

Copyright: © 2017 Cruz Rivera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and supporting files.

Funding: Funding was received from Consejo Nacional de Ciencia y Tecnología (CONACYT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript ( http://www.conacyt.mx/ ).

Competing interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: MJC has received consultancy fees from Astellas and Ferring pharma and travel fees from the European Society of Cardiology outside the submitted work. TJK is in full-time paid employment for PAREXEL International.

Abbreviations: AIHS, Alberta Innovates—Health Solutions; CAHS, Canadian Academy of Health Sciences; CIHR, Canadian Institutes of Health Research; CINAHL+, Cumulative Index to Nursing and Allied Health Literature; EMBASE, Excerpta Medica Database; ERA, Excellence in Research for Australia; HEFCE, Higher Education Funding Council for England; HMIC, Health Management Information Consortium; HTA, Health Technology Assessment; IOM, Impact Oriented Monitoring; MDG, Millennium Development Goal; NHS, National Health Service; MEDLINE, Medical Literature Analysis and Retrieval System Online; PHC RIS, Primary Health Care Research & Information Service; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; PROM, patient-reported outcome measures; QALY, quality-adjusted life year; R&D, research and development; RAE, Research Assessment Exercise; REF, Research Excellence Framework; RIF, Research Impact Framework; RQF, Research Quality Framework; SDG, Sustainable Development Goal; SIAMPI, Social Impact Assessment Methods for research and funding instruments through the study of Productive Interactions between science and society

Introduction

In 2010, approximately US$240 billion was invested in healthcare research worldwide [ 1 ]. Such research is utilised by policy makers, healthcare providers, and clinicians to make important evidence-based decisions aimed at maximising patient benefit, whilst ensuring that limited healthcare resources are used as efficiently as possible to facilitate effective and sustainable service delivery. It is therefore essential that this research is of high quality and that it is impactful—i.e., it delivers demonstrable benefits to society and the wider economy whilst minimising research waste [ 1 , 2 ]. Research impact can be defined as ‘any identifiable ‘benefit to, or positive influence on the economy, society, public policy or services, health, the environment, quality of life or academia’ (p. 26) [ 3 ].

There are many purported benefits associated with the measurement of research impact, including the ability to (1) assess the quality of the research and its subsequent benefits to society; (2) inform and influence optimal policy and funding allocation; (3) demonstrate accountability, the value of research in terms of efficiency and effectiveness to the government, stakeholders, and society; and (4) maximise impact through better understanding the concept and pathways to impact [ 4 – 7 ].

Measuring and monitoring the impact of healthcare research has become increasingly common in the United Kingdom [ 5 ], Australia [ 5 ], and Canada [ 8 ], as governments, organisations, and higher education institutions seek a framework to allocate funds to projects that are more likely to bring the most benefit to society and the economy [ 5 ]. For example, in the UK, the 2014 Research Excellence Framework (REF) has recently been used to assess the quality and impact of research in higher education institutions, through the assessment of impact cases studies and selected qualitative impact metrics [ 9 ]. This is the first initiative to allocate research funding based on the economic, societal, and cultural impact of research, although it should be noted that research impact only drives a proportion of this allocation (approximately 20%) [ 9 ].

In the UK REF, the measurement of research impact is seen as increasingly important. However, the impact element of the REF has been criticised in some quarters [ 10 , 11 ]. Critics deride the fact that REF impact is determined in a relatively simplistic way, utilising researcher-generated case studies, which commonly attempt to link a particular research outcome to an associated policy or health improvement despite the fact that the wider literature highlights great diversity in the way research impact may be demonstrated [ 12 , 13 ]. This led to the current debate about the optimal method of measuring impact in the future REF [ 10 , 14 ]. The Stern review suggested that research impact should not only focus on socioeconomic impact but should also include impact on government policy, public engagement, academic impacts outside the field, and teaching to showcase interdisciplinary collaborative impact [ 10 , 11 ]. The Higher Education Funding Council for England (HEFCE) has recently set out the proposals for the REF 2021 exercise, confirming that the measurement of such impact will continue to form an important part of the process [ 15 ].

With increasing pressure for healthcare research to lead to demonstrable health, economic, and societal impact, there is a need for researchers to understand existing methodological impact frameworks and the means by which impact may be quantified (i.e., impact metrics; see Box 1 , 'Definitions’) to better inform research activities and funding decisions. From a researcher’s perspective, understanding the optimal pathways to impact can help inform study design aimed at maximising the impact of the project. At the same time, funders need to understand which aspects of impact they should focus on when allocating awards so they can make the most of their investment and bring the greatest benefit to patients and society [ 2 , 4 , 5 , 16 , 17 ].

Box 1. Definitions

• Research impact: ‘any identifiable benefit to, or positive influence on, the economy, society, public policy or services, health, the environment, quality of life, or academia’ (p. 26) [ 3 ].
• Methodological framework: ‘a body of methods, rules and postulates employed by a particular procedure or set of procedures (i.e., framework characteristics and development)’ [ 18 ].
• Pathway: ‘a way of achieving a specified result; a course of action’ [ 19 ].
• Quantitative metrics: ‘a system or standard of [quantitative] measurement’ [ 20 ].
• Narrative metrics: ‘a spoken or written account of connected events; a story’ [ 21 ].

Whilst previous researchers have summarised existing methodological frameworks and impact case studies [ 4 , 22 – 27 ], they have not summarised the metrics for use by researchers, funders, and policy makers. The aim of this review was therefore to (1) identify the methodological frameworks used to measure healthcare research impact using systematic methods, (2) summarise common impact themes and metrics in an impact matrix, and (3) provide a simplified consolidated resource for use by funders, researchers, and policy makers.

Search strategy and selection criteria

Initially, a search strategy was developed to identify the available literature regarding the different methods to measure research impact. The following keywords: ‘Impact’, ‘Framework’, and ‘Research’, and their synonyms, were used during the search of the Medical Literature Analysis and Retrieval System Online (MEDLINE; Ovid) database, the Excerpta Medica Database (EMBASE), the Health Management Information Consortium (HMIC) database, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL+) database (inception to May 2017; see S1 Appendix for the full search strategy). Additionally, the nonindexed Journal of Research Evaluation was hand searched during the same timeframe using the keyword ‘Impact’. Other relevant articles were identified through 3 Internet search engines (Google, Google Scholar, and Google Images) using the keywords ‘Impact’, ‘Framework’, and ‘Research’, with the first 50 results screened. Google Images was searched because different methodological frameworks are summarised in a single image and can easily be identified through this search engine. Finally, additional publications were sought through communication with experts.

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (see S1 PRISMA Checklist ), 2 independent investigators systematically screened for publications describing, evaluating, or utilising a methodological research impact framework within the context of healthcare research [ 28 ]. Papers were eligible if they included full or partial methodological frameworks or pathways to research impact; both primary research and systematic reviews fitting these criteria were included. We included any methodological framework identified (original or modified versions) at the point of first occurrence. In addition, methodological frameworks were included if they were applicable to the healthcare discipline with no need of modification within their structure. We defined ‘methodological framework’ as ‘a body of methods, rules and postulates employed by a particular procedure or set of procedures (i.e., framework characteristics and development)’ [ 18 ], whereas we defined ‘pathway’ as ‘a way of achieving a specified result; a course of action’ [ 19 ]. Studies were excluded if they presented an existing (unmodified) methodological framework previously available elsewhere, did not explicitly describe a methodological framework but rather focused on a single metric (e.g., bibliometric analysis), focused on the impact or effectiveness of interventions rather than that of the research, or presented case study data only. There were no language restrictions.

Data screening

Records were downloaded into Endnote (version X7.3.1), and duplicates were removed. Two independent investigators (SCR and OLA) conducted all screening following a pilot aimed at refining the process. The records were screened by title and abstract before full-text articles of potentially eligible publications were retrieved for evaluation. A full-text screening identified the publications included for data extraction. Discrepancies were resolved through discussion, with the involvement of a third reviewer (MJC, DGK, and TJK) when necessary.

Data extraction and analysis

Data extraction occurred after the final selection of included articles. SCR and OLA independently extracted details of impact methodological frameworks, the country of origin, and the year of publication, as well as the source, the framework description, and the methodology used to develop the framework. Information regarding the methodology used to develop each methodological framework was also extracted from framework webpages where available. Investigators also extracted details regarding each framework’s impact categories and subgroups, along with their proposed time to impact (‘short-term’, ‘mid-term’, or ‘long-term’) and the details of any metrics that had been proposed to measure impact, which are depicted in an impact matrix. The structure of the matrix was informed by the work of M. Buxton and S. Hanney [ 2 ], P. Buykx et al. [ 5 ], S. Kuruvila et al. [ 29 ], and A. Weiss [ 30 ], with the intention of mapping metrics presented in previous methodological frameworks in a concise way. A consensus meeting with MJC, DGK, and TJK was held to solve disagreements and finalise the data extraction process.

Included studies

Our original search strategy identified 359 citations from MEDLINE (Ovid), EMBASE, CINAHL+, HMIC, and the Journal of Research Evaluation, and 101 citations were returned using other sources (Google, Google Images, Google Scholar, and expert communication) (see Fig 1 ) [ 28 ]. In total, we retrieved 54 full-text articles for review. At this stage, 39 articles were excluded, as they did not propose new or modified methodological frameworks. An additional 15 articles were included following the backward and forward citation method. A total of 31 relevant articles were included in the final analysis, of which 24 were articles presenting unique frameworks and the remaining 7 were systematic reviews [ 4 , 22 – 27 ]. The search strategy was rerun on 15 May 2017. A further 19 publications were screened, and 2 were taken forward to full-text screening but were ineligible for inclusion.

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https://doi.org/10.1371/journal.pmed.1002370.g001

Methodological framework characteristics

The characteristics of the 24 included methodological frameworks are summarised in Table 1 , 'Methodological framework characteristics’. Fourteen publications proposed academic-orientated frameworks, which focused on measuring academic, societal, economic, and cultural impact using narrative and quantitative metrics [ 2 , 3 , 5 , 8 , 29 , 31 – 39 ]. Five publications focused on assessing the impact of research by focusing on the interaction process between stakeholders and researchers (‘productive interactions’), which is a requirement to achieve research impact. This approach tries to address the issue of attributing research impact to metrics [ 7 , 40 – 43 ]. Two frameworks focused on the importance of partnerships between researchers and policy makers, as a core element to accomplish research impact [ 44 , 45 ]. An additional 2 frameworks focused on evaluating the pathways to impact, i.e., linking processes between research and impact [ 30 , 46 ]. One framework assessed the ability of health technology to influence efficiency of healthcare systems [ 47 ]. Eight frameworks were developed in the UK [ 2 , 3 , 29 , 37 , 39 , 42 , 43 , 45 ], 6 in Canada [ 8 , 33 , 34 , 44 , 46 , 47 ], 4 in Australia [ 5 , 31 , 35 , 38 ], 3 in the Netherlands [ 7 , 40 , 41 ], and 2 in the United States [ 30 , 36 ], with 1 model developed with input from various countries [ 32 ].

https://doi.org/10.1371/journal.pmed.1002370.t001

Methodological framework development

The included methodological frameworks varied in their development process, but there were some common approaches employed. Most included a literature review [ 2 , 5 , 7 , 8 , 31 , 33 , 36 , 37 , 40 – 46 ], although none of them used a recognised systematic method. Most also consulted with various stakeholders [ 3 , 8 , 29 , 31 , 33 , 35 – 38 , 43 , 44 , 46 , 47 ] but used differing methods to incorporate their views, including quantitative surveys [ 32 , 35 , 43 , 46 ], face-to-face interviews [ 7 , 29 , 33 , 35 , 37 , 42 , 43 ], telephone interviews [ 31 , 46 ], consultation [ 3 , 7 , 36 ], and focus groups [ 39 , 43 ]. A range of stakeholder groups were approached across the sample, including principal investigators [ 7 , 29 , 43 ], research end users [ 7 , 42 , 43 ], academics [ 3 , 8 , 39 , 40 , 43 , 46 ], award holders [ 43 ], experts [ 33 , 38 , 39 ], sponsors [ 33 , 39 ], project coordinators [ 32 , 42 ], and chief investigators [ 31 , 35 ]. However, some authors failed to identify the stakeholders involved in the development of their frameworks [ 2 , 5 , 34 , 41 , 45 ], making it difficult to assess their appropriateness. In addition, only 4 of the included papers reported using formal analytic methods to interpret stakeholder responses. These included the Canadian Academy of Health Sciences framework, which used conceptual cluster analysis [ 33 ]. The Research Contribution [ 42 ], Research Impact [ 29 ], and Primary Health Care & Information Service [ 31 ] used a thematic analysis approach. Finally, some authors went on to pilot their framework, which shaped refinements on the methodological frameworks until approval. Methods used to pilot the frameworks included a case study approach [ 2 , 3 , 30 , 32 , 33 , 36 , 40 , 42 , 44 , 45 ], contrasting results against available literature [ 29 ], the use of stakeholders’ feedback [ 7 ], and assessment tools [ 35 , 46 ].

Major impact categories

1. primary research-related impact..

A number of methodological frameworks advocated the evaluation of ‘research-related impact’. This encompassed content related to the generation of new knowledge, knowledge dissemination, capacity building, training, leadership, and the development of research networks. These outcomes were considered the direct or primary impacts of a research project, as these are often the first evidenced returns [ 30 , 62 ].

A number of subgroups were identified within this category, with frameworks supporting the collection of impact data across the following constructs: ‘research and innovation outcomes’; ‘dissemination and knowledge transfer’; ‘capacity building, training, and leadership’; and ‘academic collaborations, research networks, and data sharing’.

1 . 1 . Research and innovation outcomes . Twenty of the 24 frameworks advocated the evaluation of ‘research and innovation outcomes’ [ 2 , 3 , 5 , 7 , 8 , 29 – 39 , 41 , 43 , 44 , 46 ]. This subgroup included the following metrics: number of publications; number of peer-reviewed articles (including journal impact factor); citation rates; requests for reprints, number of reviews, and meta-analysis; and new or changes in existing products (interventions or technology), patents, and research. Additionally, some frameworks also sought to gather information regarding ‘methods/methodological contributions’. These advocated the collection of systematic reviews and appraisals in order to identify gaps in knowledge and determine whether the knowledge generated had been assessed before being put into practice [ 29 ].

1 . 2 . Dissemination and knowledge transfer . Nineteen of the 24 frameworks advocated the assessment of ‘dissemination and knowledge transfer’ [ 2 , 3 , 5 , 7 , 29 – 32 , 34 – 43 , 46 ]. This comprised collection of the following information: number of conferences, seminars, workshops, and presentations; teaching output (i.e., number of lectures given to disseminate the research findings); number of reads for published articles; article download rate and number of journal webpage visits; and citations rates in nonjournal media such as newspapers and mass and social media (i.e., Twitter and blogs). Furthermore, this impact subgroup considered the measurement of research uptake and translatability and the adoption of research findings in technological and clinical applications and by different fields. These can be measured through patents, clinical trials, and partnerships between industry and business, government and nongovernmental organisations, and university research units and researchers [ 29 ].

1 . 3 . Capacity building , training , and leadership . Fourteen of 24 frameworks suggested the evaluation of ‘capacity building, training, and leadership’ [ 2 , 3 , 5 , 8 , 29 , 31 – 35 , 39 – 41 , 43 ]. This involved collecting information regarding the number of doctoral and postdoctoral studentships (including those generated as a result of the research findings and those appointed to conduct the research), as well as the number of researchers and research-related staff involved in the research projects. In addition, authors advocated the collection of ‘leadership’ metrics, including the number of research projects managed and coordinated and the membership of boards and funding bodies, journal editorial boards, and advisory committees [ 29 ]. Additional metrics in this category included public recognition (number of fellowships and awards for significant research achievements), academic career advancement, and subsequent grants received. Lastly, the impact metric ‘research system management’ comprised the collection of information that can lead to preserving the health of the population, such as modifying research priorities, resource allocation strategies, and linking health research to other disciplines to maximise benefits [ 29 ].

1 . 4 . Academic collaborations , research networks , and data sharing . Lastly, 10 of the 24 frameworks advocated the collection of impact data regarding ‘academic collaborations (internal and external collaborations to complete a research project), research networks, and data sharing’ [ 2 , 3 , 5 , 7 , 29 , 34 , 37 , 39 , 41 , 43 ].

2. Influence on policy making.

Methodological frameworks addressing this major impact category focused on measurable improvements within a given knowledge base and on interactions between academics and policy makers, which may influence policy-making development and implementation. The returns generated in this impact category are generally considered as intermediate or midterm (1 to 3 years). These represent an important interim stage in the process towards the final expected impacts, such as quantifiable health improvements and economic benefits, without which policy change may not occur [ 30 , 62 ]. The following impact subgroups were identified within this category: ‘type and nature of policy impact’, ‘level of policy making’, and ‘policy networks’.

2 . 1 . Type and nature of policy impact . The most common impact subgroup, mentioned in 18 of the 24 frameworks, was ‘type and nature of policy impact’ [ 2 , 7 , 29 – 38 , 41 – 43 , 45 – 47 ]. Methodological frameworks addressing this subgroup stressed the importance of collecting information regarding the influence of research on policy (i.e., changes in practice or terminology). For instance, a project looking at trafficked adolescents and women (2003) influenced the WHO guidelines (2003) on ethics regarding this particular group [ 17 , 21 , 63 ].

2 . 2 . Level of policy impact . Thirteen of 24 frameworks addressed aspects surrounding the need to record the ‘level of policy impact’ (international, national, or local) and the organisations within a level that were influenced (local policy makers, clinical commissioning groups, and health and wellbeing trusts) [ 2 , 5 , 8 , 29 , 31 , 34 , 38 , 41 , 43 – 47 ]. Authors considered it important to measure the ‘level of policy impact’ to provide evidence of collaboration, coordination, and efficiency within health organisations and between researchers and health organisations [ 29 , 31 ].

2 . 3 . Policy networks . Five methodological frameworks highlighted the need to collect information regarding collaborative research with industry and staff movement between academia and industry [ 5 , 7 , 29 , 41 , 43 ]. A policy network emphasises the relationship between policy communities, researchers, and policy makers. This relationship can influence and lead to incremental changes in policy processes [ 62 ].

3. Health and health systems impact.

A number of methodological frameworks advocated the measurement of impacts on health and healthcare systems across the following impact subgroups: ‘quality of care and service delivering’, ‘evidence-based practice’, ‘improved information and health information management’, ‘cost containment and effectiveness’, ‘resource allocation’, and ‘health workforce’.

3 . 1 . Quality of care and service delivery . Twelve of the 24 frameworks highlighted the importance of evaluating ‘quality of care and service delivery’ [ 2 , 5 , 8 , 29 – 31 , 33 – 36 , 41 , 47 ]. There were a number of suggested metrics that could be potentially used for this purpose, including health outcomes such as quality-adjusted life years (QALYs), patient-reported outcome measures (PROMs), patient satisfaction and experience surveys, and qualitative data on waiting times and service accessibility.

3 . 2 . Evidence-based practice . ‘Evidence-based practice’, mentioned in 5 of the 24 frameworks, refers to making changes in clinical diagnosis, clinical practice, treatment decisions, or decision making based on research evidence [ 5 , 8 , 29 , 31 , 33 ]. The suggested metrics to demonstrate evidence-based practice were adoption of health technologies and research outcomes to improve the healthcare systems and inform policies and guidelines [ 29 ].

3 . 3 . Improved information and health information management . This impact subcategory, mentioned in 5 of the 24 frameworks, refers to the influence of research on the provision of health services and management of the health system to prevent additional costs [ 5 , 29 , 33 , 34 , 38 ]. Methodological frameworks advocated the collection of health system financial, nonfinancial (i.e., transport and sociopolitical implications), and insurance information in order to determine constraints within a health system.

3 . 4 . Cost containment and cost-effectiveness . Six of the 24 frameworks advocated the subcategory ‘cost containment and cost-effectiveness’ [ 2 , 5 , 8 , 17 , 33 , 36 ]. ‘Cost containment’ comprised the collection of information regarding how research has influenced the provision and management of health services and its implication in healthcare resource allocation and use [ 29 ]. ‘Cost-effectiveness’ refers to information concerning economic evaluations to assess improvements in effectiveness and health outcomes—for instance, the cost-effectiveness (cost and health outcome benefits) assessment of introducing a new health technology to replace an older one [ 29 , 31 , 64 ].

3 . 5 . Resource allocation . ‘Resource allocation’, mentioned in 6frameworks, can be measured through 2 impact metrics: new funding attributed to the intervention in question and equity while allocating resources, such as improved allocation of resources at an area level; better targeting, accessibility, and utilisation; and coverage of health services [ 2 , 5 , 29 , 31 , 45 , 47 ]. The allocation of resources and targeting can be measured through health services research reports, with the utilisation of health services measured by the probability of providing an intervention when needed, the probability of requiring it again in the future, and the probability of receiving an intervention based on previous experience [ 29 , 31 ].

3 . 6 . Health workforce . Lastly, ‘health workforce’, present in 3 methodological frameworks, refers to the reduction in the days of work lost because of a particular illness [ 2 , 5 , 31 ].

4. Health-related and societal impact.

Three subgroups were included in this category: ‘health literacy’; ‘health knowledge, attitudes, and behaviours’; and ‘improved social equity, inclusion, or cohesion’.

4 . 1 . Health knowledge , attitudes , and behaviours . Eight of the 24 frameworks suggested the assessment of ‘health knowledge, attitudes, behaviours, and outcomes’, which could be measured through the evaluation of levels of public engagement with science and research (e.g., National Health Service (NHS) Choices end-user visit rate) or by using focus groups to analyse changes in knowledge, attitudes, and behaviour among society [ 2 , 5 , 29 , 33 – 35 , 38 , 43 ].

4 . 2 . Improved equity , inclusion , or cohesion and human rights . Other methodological frameworks, 4 of the 24, suggested capturing improvements in equity, inclusion, or cohesion and human rights. Authors suggested these could be using a resource like the United Nations Millennium Development Goals (MDGs) (superseded by Sustainable Development Goals [SDGs] in 2015) and human rights [ 29 , 33 , 34 , 38 ]. For instance, a cluster-randomised controlled trial in Nepal, which had female participants, has demonstrated the reduction of neonatal mortality through the introduction of maternity health care, distribution of delivery kits, and home visits. This illustrates how research can target vulnerable and disadvantaged groups. Additionally, this research has been introduced by the World Health Organisation to achieve the MDG ‘improve maternal health’ [ 16 , 29 , 65 ].

4 . 3 . Health literacy . Some methodological frameworks, 3 of the 24, focused on tracking changes in the ability of patients to make informed healthcare decisions, reduce health risks, and improve quality of life, which were demonstrably linked to a particular programme of research [ 5 , 29 , 43 ]. For example, a systematic review showed that when HIV health literacy/knowledge is spread among people living with the condition, antiretroviral adherence and quality of life improve [ 66 ].

5. Broader economic impacts.

Some methodological frameworks, 9 of 24, included aspects related to the broader economic impacts of health research—for example, the economic benefits emerging from the commercialisation of research outputs [ 2 , 5 , 29 , 31 , 33 , 35 , 36 , 38 , 67 ]. Suggested metrics included the amount of funding for research and development (R&D) that was competitively awarded by the NHS, medical charities, and overseas companies. Additional metrics were income from intellectual property, spillover effects (any secondary benefit gained as a repercussion of investing directly in a primary activity, i.e., the social and economic returns of investing on R&D) [ 33 ], patents granted, licences awarded and brought to the market, the development and sales of spinout companies, research contracts, and income from industry.

The benefits contained within the categories ‘health and health systems impact’, ‘health-related and societal impact’, and ‘broader economic impacts’ are considered the expected and final returns of the resources allocated in healthcare research [ 30 , 62 ]. These benefits commonly arise in the long term, beyond 5 years according to some authors, but there was a recognition that this could differ depending on the project and its associated research area [ 4 ].

Data synthesis

Five major impact categories were identified across the 24 included methodological frameworks: (1) ‘primary research-related impact’, (2) ‘influence on policy making’, (3) ‘health and health systems impact’, (4) ‘health-related and societal impact’, and (5) ‘broader economic impact’. These major impact categories were further subdivided into 16 impact subgroups. The included publications proposed 80 different metrics to measure research impact. This impact typology synthesis is depicted in ‘the impact matrix’ ( Fig 2 and Fig 3 ).

CIHR, Canadian Institutes of Health Research; HTA, Health Technology Assessment; PHC RIS, Primary Health Care Research & Information Service; RAE, Research Assessment Exercise; RQF, Research Quality Framework.

https://doi.org/10.1371/journal.pmed.1002370.g002

AIHS, Alberta Innovates—Health Solutions; CAHS, Canadian Institutes of Health Research; IOM, Impact Oriented Monitoring; REF, Research Excellence Framework; SIAMPI, Social Impact Assessment Methods for research and funding instruments through the study of Productive Interactions between science and society.

https://doi.org/10.1371/journal.pmed.1002370.g003

Commonality and differences across frameworks

The ‘Research Impact Framework’ and the ‘Health Services Research Impact Framework’ were the models that encompassed the largest number of the metrics extracted. The most dominant methodological framework was the Payback Framework; 7 other methodological framework models used the Payback Framework as a starting point for development [ 8 , 29 , 31 – 35 ]. Additional methodological frameworks that were commonly incorporated into other tools included the CIHR framework, the CAHS model, the AIHS framework, and the Exchange model [ 8 , 33 , 34 , 44 ]. The capture of ‘research-related impact’ was the most widely advocated concept across methodological frameworks, illustrating the importance with which primary short-term impact outcomes were viewed by the included papers. Thus, measurement of impact via number of publications, citations, and peer-reviewed articles was the most common. ‘Influence on policy making’ was the predominant midterm impact category, specifically the subgroup ‘type and nature of policy impact’, in which frameworks advocated the measurement of (i) changes to legislation, regulations, and government policy; (ii) influence and involvement in decision-making processes; and (iii) changes to clinical or healthcare training, practice, or guidelines. Within more long-term impact measurement, the evaluations of changes in the ‘quality of care and service delivery’ were commonly advocated.

In light of the commonalities and differences among the methodological frameworks, the ‘pathways to research impact’ diagram ( Fig 4 ) was developed to provide researchers, funders, and policy makers a more comprehensive and exhaustive way to measure healthcare research impact. The diagram has the advantage of assorting all the impact metrics proposed by previous frameworks and grouping them into different impact subgroups and categories. Prospectively, this global picture will help researchers, funders, and policy makers plan strategies to achieve multiple pathways to impact before carrying the research out. The analysis of the data extraction and construction of the impact matrix led to the development of the ‘pathways to research impact’ diagram ( Fig 4 ). The diagram aims to provide an exhaustive and comprehensive way of tracing research impact by combining all the impact metrics presented by the different 24 frameworks, grouping those metrics into different impact subgroups, and grouping these into broader impact categories.

NHS, National Health Service; PROM, patient-reported outcome measure; QALY, quality-adjusted life year; R&D, research and development.

https://doi.org/10.1371/journal.pmed.1002370.g004

This review has summarised existing methodological impact frameworks together for the first time using systematic methods ( Fig 4 ). It allows researchers and funders to consider pathways to impact at the design stage of a study and to understand the elements and metrics that need to be considered to facilitate prospective assessment of impact. Users do not necessarily need to cover all the aspects of the methodological framework, as every research project can impact on different categories and subgroups. This review provides information that can assist researchers to better demonstrate impact, potentially increasing the likelihood of conducting impactful research and reducing research waste. Existing reviews have not presented a methodological framework that includes different pathways to impact, health impact categories, subgroups, and metrics in a single methodological framework.

Academic-orientated frameworks included in this review advocated the measurement of impact predominantly using so-called ‘quantitative’ metrics—for example, the number of peer-reviewed articles, journal impact factor, and citation rates. This may be because they are well-established measures, relatively easy to capture and objective, and are supported by research funding systems. However, these metrics primarily measure the dissemination of research finding rather than its impact [ 30 , 68 ]. Whilst it is true that wider dissemination, especially when delivered via world-leading international journals, may well lead eventually to changes in healthcare, this is by no means certain. For instance, case studies evaluated by Flinders University of Australia demonstrated that some research projects with non-peer-reviewed publications led to significant changes in health policy, whilst the studies with peer-reviewed publications did not result in any type of impact [ 68 ]. As a result, contemporary literature has tended to advocate the collection of information regarding a variety of different potential forms of impact alongside publication/citations metrics [ 2 , 3 , 5 , 7 , 8 , 29 – 47 ], as outlined in this review.

The 2014 REF exercise adjusted UK university research funding allocation based on evidence of the wider impact of research (through case narrative studies and quantitative metrics), rather than simply according to the quality of research [ 12 ]. The intention was to ensure funds were directed to high-quality research that could demonstrate actual realised benefit. The inclusion of a mixed-method approach to the measurement of impact in the REF (narrative and quantitative metrics) reflects a widespread belief—expressed by the majority of authors of the included methodological frameworks in the review—that individual quantitative impact metrics (e.g., number of citations and publications) do not necessary capture the complexity of the relationships involved in a research project and may exclude measurement of specific aspects of the research pathway [ 10 , 12 ].

Many of the frameworks included in this review advocated the collection of a range of academic, societal, economic, and cultural impact metrics; this is consistent with recent recommendations from the Stern review [ 10 ]. However, a number of these metrics encounter research ‘lag’: i.e., the time between the point at which the research is conducted and when the actual benefits arise [ 69 ]. For instance, some cardiovascular research has taken up to 25 years to generate impact [ 70 ]. Likewise, the impact may not arise exclusively from a single piece of research. Different processes (such as networking interactions and knowledge and research translation) and multiple individuals and organisations are often involved [ 4 , 71 ]. Therefore, attributing the contribution made by each of the different actors involved in the process can be a challenge [ 4 ]. An additional problem associated to attribution is the lack of evidence to link research and impact. The outcomes of research may emerge slowly and be absorbed gradually. Consequently, it is difficult to determine the influence of research in the development of a new policy, practice, or guidelines [ 4 , 23 ].

A further problem is that impact evaluation is conducted ‘ex post’, after the research has concluded. Collecting information retrospectively can be an issue, as the data required might not be available. ‘ex ante’ assessment is vital for funding allocation, as it is necessary to determine the potential forthcoming impact before research is carried out [ 69 ]. Additionally, ex ante evaluation of potential benefit can overcome the issues regarding identifying and capturing evidence, which can be used in the future [ 4 ]. In order to conduct ex ante evaluation of potential benefit, some authors suggest the early involvement of policy makers in a research project coupled with a well-designed strategy of dissemination [ 40 , 69 ].

Providing an alternate view, the authors of methodological frameworks such as the SIAMPI, Contribution Mapping, Research Contribution, and the Exchange model suggest that the problems of attribution are a consequence of assigning the impact of research to a particular impact metric [ 7 , 40 , 42 , 44 ]. To address these issues, these authors propose focusing on the contribution of research through assessing the processes and interactions between stakeholders and researchers, which arguably take into consideration all the processes and actors involved in a research project [ 7 , 40 , 42 , 43 ]. Additionally, contributions highlight the importance of the interactions between stakeholders and researchers from an early stage in the research process, leading to a successful ex ante and ex post evaluation by setting expected impacts and determining how the research outcomes have been utilised, respectively [ 7 , 40 , 42 , 43 ]. However, contribution metrics are generally harder to measure in comparison to academic-orientated indicators [ 72 ].

Currently, there is a debate surrounding the optimal methodological impact framework, and no tool has proven superior to another. The most appropriate methodological framework for a given study will likely depend on stakeholder needs, as each employs different methodologies to assess research impact [ 4 , 37 , 41 ]. This review allows researchers to select individual existing methodological framework components to create a bespoke tool with which to facilitate optimal study design and maximise the potential for impact depending on the characteristic of their study ( Fig 2 and Fig 3 ). For instance, if researchers are interested in assessing how influential their research is on policy making, perhaps considering a suite of the appropriate metrics drawn from multiple methodological frameworks may provide a more comprehensive method than adopting a single methodological framework. In addition, research teams may wish to use a multidimensional approach to methodological framework development, adopting existing narratives and quantitative metrics, as well as elements from contribution frameworks. This approach would arguably present a more comprehensive method of impact assessment; however, further research is warranted to determine its effectiveness [ 4 , 69 , 72 , 73 ].

Finally, it became clear during this review that the included methodological frameworks had been constructed using varied methodological processes. At present, there are no guidelines or consensus around the optimal pathway that should be followed to develop a robust methodological framework. The authors believe this is an area that should be addressed by the research community, to ensure future frameworks are developed using best-practice methodology.

For instance, the Payback Framework drew upon a literature review and was refined through a case study approach. Arguably, this approach could be considered inferior to other methods that involved extensive stakeholder involvement, such as the CIHR framework [ 8 ]. Nonetheless, 7 methodological frameworks were developed based upon the Payback Framework [ 8 , 29 , 31 – 35 ].

Limitations

The present review is the first to summarise systematically existing impact methodological frameworks and metrics. The main limitation is that 50% of the included publications were found through methods other than bibliographic databases searching, indicating poor indexing. Therefore, some relevant articles may not have been included in this review if they failed to indicate the inclusion of a methodological impact framework in their title/abstract. We did, however, make every effort to try to find these potentially hard-to-reach publications, e.g., through forwards/backwards citation searching, hand searching reference lists, and expert communication. Additionally, this review only extracted information regarding the methodology followed to develop each framework from the main publication source or framework webpage. Therefore, further evaluations may not have been included, as they are beyond the scope of the current paper. A further limitation was that although our search strategy did not include language restrictions, we did not specifically search non-English language databases. Thus, we may have failed to identify potentially relevant methodological frameworks that were developed in a non-English language setting.

In conclusion, the measurement of research impact is an essential exercise to help direct the allocation of limited research resources, to maximise benefit, and to help minimise research waste. This review provides a collective summary of existing methodological impact frameworks and metrics, which funders may use to inform the measurement of research impact and researchers may use to inform study design decisions aimed at maximising the short-, medium-, and long-term impact of their research.

Supporting information

S1 appendix. search strategy..

https://doi.org/10.1371/journal.pmed.1002370.s001

S1 PRISMA Checklist. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist.

https://doi.org/10.1371/journal.pmed.1002370.s002

Acknowledgments

We would also like to thank Mrs Susan Bayliss, Information Specialist, University of Birmingham, and Mrs Karen Biddle, Research Secretary, University of Birmingham.

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Health Psychology

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Journal scope statement

Mission: Health Psychology ® is the official scientific journal of the Society for Health Psychology (Division 38 of the American Psychological Association) and the premier scientific journal addressing the complex and multidimensional influences on the human experience in physical health research. Adhering to the highest standards of peer-review, the journal’s mission is to advance basic to translational science, policy, and practice to significantly impact population health. The journal actively encourages submissions that address psychological, behavioral, biobehavioral and sociocultural dimensions of the diversity of human experience, and which reflect a strong commitment to inclusive excellence to facilitate the goal of optimal health for all. 

Scope: The journal seeks submissions that address the interface of psychology and health and wellness. Topics include but are not limited to state-of-the-science research on biobehavioral pathways and mechanisms; social determinants of health; psychosocial and sociocultural influences; intervention development, dissemination and implementation science including sustainability, policy, and impact on clinical practices; and theoretical and methodological advances. 

Manuscripts representing relevant science across the lifespan are encouraged. 

The journal publishes a wide range of original research reports, systematic reviews and meta-analyses, intervention and translational science reports, guidelines and policy discussions, and catalyst pieces that address contemporary debates, identify priorities, communicate phenomena, and facilitate engagement and multidisciplinary collaborations that advance the journal’s mission.

Equity, diversity, and inclusion

Health Psychology supports equity, diversity, and inclusion (EDI) in its practices. More information on these initiatives is available under EDI Efforts .

Calls for papers

• Reverse translation: Bridging the practice-to-research gap

Open science

The APA Journals Program is committed to publishing transparent, rigorous research; improving reproducibility in science; and aiding research discovery. Open science practices vary per editor discretion. View the initiatives implemented by this journal .

Editor's Choice

One paper in each issue of Health Psychology will be identified an “ Editor’s Choice ” paper. Our editors use this designation to honor papers that are likely to have a relatively large impact on the field or that highlight an important future direction for science.

Author and editor spotlights

Explore journal highlights : free article summaries, editor interviews and editorials, journal awards, mentorship opportunities, and more.

Please follow the submission guidelines detailed below. Manuscripts that do not conform to our Instructions to Authors may be returned without review.

Manuscript submission

Prepare manuscripts according to the Publication Manual of the American Psychological Association using the 7 th edition. Manuscripts may be copyedited for bias-free language (see Chapter 5 of the Publication Manual ). APA Style and Grammar Guidelines for the 7 th edition are available.

Submit Manuscript

Contact our Peer Review Coordinator Katt Fambrough , if you have questions about submitting a manuscript or if you do not receive confirmation of your submission within three business days.

Some institutional spam filters may block emails from our editorial office or from APA Journals. If this happens, add “apa.org” to your safe address list and ask your IT service to add it to their white list.

Submission Process

Our Editorial Manager system will ask you for the following items during the submission process.

Article Type: Indicate whether the manuscript is a regular article , a brief report , or a submission for a special issue or series . Some special issues and special series submissions require permission or are by invitation only; please obtain permission if needed before choosing one of the special article types.

Files: You will be asked to upload the following files:

• Cover letter. The letter should briefly describe the paper; explain how it fits within the journal’s scope; and confirm that it has not been published, is not under review elsewhere, and does not contain data that are under review or that have been published elsewhere. It should also confirm that all authors have reviewed the final version of the paper that is being submitted.
• Manuscript. See the Manuscript section (below) for instructions.
• Tables and Figures: Place tables and figures at the end of the manuscript, after the references, with one table or figure per page. Include page numbers on the table and figure pages.
• Supplemental Materials: You may place a variety of materials in an online-only supplement, such as 1) methodological details, tables, and figures that are not essential for inclusion in the manuscript itself but that enhance the report; 2) computer code needed to reproduce the major analyses; 3) nonproprietary questionnaires, survey forms, other data collection instruments, scripts, or experimental stimuli; and 4) qualitative response material. There is no specific limit on the length of the supplemental document, and it does not count against the manuscript’s page limit. Refer readers to the supplement at appropriate points in the text of the manuscript. See Supplementing Your Article with Online Material for more information.
• Reporting Checklist: If you have completed a reporting checklist (e.g., CONSORT, PRISMA, or STROBE), submit it as a Reporting Checklist file.

Use Microsoft Word (.doc) or LaTeX (.tex) to create documents for submission. If using LaTeX, submit a zip file that includes a .pdf version of each .tex file.

Manuscripts should adhere to the guidelines provided in the 7 th edition of the Publication Manual of the American Psychological Association . APA Style guidance is available online.

Classifications: Use this checklist to classify the manuscript’s area(s) of interest or specialization.

Suggested Reviewers: Enter the name, institution, email address, and qualifications of at least three potential reviewers.

Questionnaire: The questionnaire asks about 1) serving as a reviewer; 2) funding agencies that supported the submitted work; 3) the larger study or project, if any, on which the current study is based; and 4) potential conflicts of interest.

If your report is based on data from a larger study or project (e.g., an analysis based on a large epidemiological dataset or a secondary analysis of clinical trial data), use the questionnaire to explain the relationship between the current paper and the larger study or project, and briefly explain the current study’s novel or value-added scientific contribution relative to other papers from the same dataset. List any papers that were based on the larger study or dataset and that have been published, are under review, or are in press, about which the editors and reviewers of the current paper should be aware. Cite them in the manuscript as well if readers should be aware of them.

Manuscripts

Length: Regular articles are limited to 30 pages, meta-analyses to 35 pages, and brief reports to 12 pages. The page limit includes all parts of the manuscript, including the title page, abstract, text, references, tables, and figures. Use a sans serif font such as 11-point Calibri or 11-point Arial, or a serif font such as 12-point Times New Roman, and double-space the text. Authors may request permission to exceed the page limit, but the journal operates under a contractual page budget, so overages are allowed only when necessary. Please write succinctly and place nonessential materials in a supplement, not in the manuscript.

Title Page: The title page should adhere to APA Style and include an APA-style Author Note. The manuscript’s title should be no more than 12 words long, and it should not state an assertion or conclusion. The title should include “a randomized controlled trial,” “a meta-analysis,” “a systematic review,” or “systematic review and meta-analysis,” if appropriate.

APA-Style Author Notes include the following information:

• Paragraph 1 : Authors’ ORCID iDs if available. Authors will be asked to identify the contributions of all authors at submission using the Contributor Roles Taxonomy (CRediT) . All authors should have reviewed and agreed to their individual contribution(s) before submission. Authors may claim credit for more than one role, and the same role can be attributed to more than one author.
• Paragraph 2: Changes, if any, in author affiliations that occurred after the study ended.
• Paragraph 3: Disclosures and acknowledgements, if any, including: a) Study preregistration information including registry name and record number, e.g., “Trial registration: ClinicalTrials.gov Identifier NCT999999.” b) links to data, materials, and code. c) Financial support including funding agencies and grant numbers. d) Disclosure of any real or potentially perceived conflicts of interest including financial interests or affiliations that might be seen as influencing the research. If there are no conflicts of interest, this should be clearly stated. e) Acknowledgements of nonfinancial assistance such as staff or student contributions to the research.
• Paragraph 4: Corresponding author’s contact information, including an email address.

Abstract: Empirical reports must include a structured abstract with < 250 words and these headings:

• Objective: Brief statement of the purpose or aims of the study.
• Methods: Essential information about the study design, procedures, and measures.
• Results: Primary findings; include sample size and primary statistical results, if possible.
• Conclusions: Main conclusions based on the primary findings.

Papers such as narrative reviews or invited commentaries for which a structured abstract would be inappropriate should include an unstructured manuscript with a maximum of 250 words.

The journal will provide a Spanish translation of abstracts for all papers accepted as of March 1, 2023. This abstract will be added in post-production after acceptance and will be included in the online (html) version and the end of the article in the PDF version

Keywords: List up to five keywords below the abstract. Use National Library of Medicine medical subject heading ( MeSH ) vocabulary or APA psychological index terms .

Body of the Manuscript: Empirical reports should include:

• a clear statement of the research question, hypothesis, specific aims, or purpose of the study;
• essential information about the methods even if a separate methods or protocol paper is cited;
• descriptive statistics to characterize the sample, the sample size, and the measures;
• a CONSORT-style participant flow diagram, if appropriate;
• disclosure of the study’s limitations; and
• conclusions that are consistent with the findings.

The methods section of reports of research involving human participants must provide information about institutional review board or ethics board approval, including the name(s) of the institution(s) that approved the study, or an explanation of why the study was exempt from approval and oversight. Informed consent and assent procedures should also be briefly described.

Reports should explain the significance or novel contribution of original research without overstating the study’s translational, clinical, or public health significance.

If the purpose of the work is to attempt to replicate or extend previous studies, this should be disclosed, and minor innovations or superficially novel features should not be overstated. The statistical methods should adhere to the APA Task Force on Statistical Inference guidelines. Statistical results, tables, and figures should adhere to APA Style guidelines.

Areas of interest

Translational research.

Health Psychology publishes work across the entire spectrum of translational research in health psychology and behavioral medicine, including observational, experimental, and interventional studies. Programmatic research is especially welcome. If the study is integral to an ongoing, well-focused program of research, its relationship to previous and planned work should be described.

When applicable, authors are encouraged to position their study within an established framework or model for translational research, intervention development or optimization, or implementation science, such as the ORBIT Model (Czajkowski et al., Health Psychology 2015;34(10):971-982).

Observational and experimental research

Health Psychology publishes many kinds of observational, epidemiological, and experimental studies. However, studies with the following characteristics are seldom accepted:

• studies with little or no direct relevance to physical health or medical illness
• studies with limited ecological validity or generalizability
• mediation analyses based on cross-sectional data
• small qualitative studies

Early-phase intervention research

Health psychology is an applied science that draws upon many areas of basic research. Translational and intervention optimization models such as ORBIT, the NIH Stage Model, or the Multiphase Optimization Strategy (MOST) encourage us to ground our health-related behavioral intervention research in basic social and behavioral science research, the science of behavior change, and in other areas of psychosocial, clinical, and public health research. These models also promote a programmatic approach to intervention development, optimization, testing, and implementation.

The journal welcomes basic research that is conducted to inform health-related behavioral intervention development or other clinical or public health applications of health psychology. We also welcome early-phase research on health-related behavioral interventions, such as intervention development, optimization, and dose-finding studies; proof-of-concept evaluations; and feasibility studies. However, these reports must meet certain criteria to be considered for publication.

• The study should be embedded in a translational or intervention optimization model and in programmatic line of research whose long-term goal concerns maintaining physical health, preventing medical illness, or improving significant medical or public health outcomes.
• The report should not claim that the study is definitive or that it has significant practice or policy implications; it should instead point to specific next steps in the line of research.
• It should not include severely underpowered statistical tests of efficacy hypotheses; see Freedland KE. Health Psychology 2020;39(10):851-862 for further information.

Small, early-phase studies must compete against larger and more definitive studies in the journal’s priority ranking system. This is especially challenging for small or preliminary studies that are conducted primarily to guide the investigator’s own work and that may be of limited interest to other researchers. Thus, early-phase research reports should highlight aspects of the study that would be informative for other investigators.

Randomized controlled trials (RCTs)

The journal welcomes reports based on randomized controlled trials of health-related behavioral interventions. However, secondary or exploratory analyses of RCT outcome data should not be submitted until the primary findings of the trial have been published. Manuscripts that do not include outcome data, such as analyses that are limited to baseline data, may be submitted before the primary findings have been published.

Meta-analyses and Meta-regression analyses

Meta-analyses and meta-regression analyses of research in health psychology and behavioral medicine are welcome. They must provide significant added value if other meta-analyses of the same area of research have already been published.

Psychometric studies

Research on questionnaires or other assessment instruments should be based on modern psychometric methods. A convincing case should be made for a new, modified, or translated measure, and it should be relevant to a large segment of the journal’s readership.

Methodological issues and advances

Health Psychology welcomes reviews and tutorials on the following methodological topics:

• Advanced statistical procedures that are applicable to multiple areas of health psychology or behavioral medicine research but that are underutilized.
• Standard statistical methods that are widely misunderstood, misused, or neglected in health psychology and behavioral medicine research.
• Nonstatistical methodological issues that affect the quality or impact of health psychology and behavioral medicine research.

Authors should 1) present advanced methods in a clear and accessible manner for readers who are not statistical experts; 2) provide guidance about the assumptions and utilization of statistical procedures, examples, and computer code; and 3) provide links to sample datasets if applicable.

• Letters to the editor

Selected letters to the editor are published online, on the journal’s website. Submit letters to the editor by email to Katt Fambrough with a cover letter disclosing any potential conflicts of interest. If the letter is accepted, the target article’s authors may be invited to respond.

Transparency and Openness Promotion

Work submitted to Health Psychology should adhere to the Transparency and Openness Promotion (TOP) Guidelines . For empirical reports, include a brief "Transparency and Openness" subsection at the beginning of the methods section. This subsection should detail the efforts the authors have made to comply with the TOP guidelines; the purpose is to gather all required disclosures and links in one location to make it easier for readers, reviewers, and editors to find this information. This is an example of a brief transparency and openness statement for an RCT:

In this article, we report how we determined our sample size, all data exclusions, all manipulations, and all measures that were included in the study, and we follow the CONSORT guideline for reporting parallel group randomized trials. All data, analysis code, and research materials are available at [ stable link to permanent repository ]. Data were analyzed using R version 4.0.0 (R Core Team, 2020). The trial was pre-registered on clinicaltrials.gov (NCT99999999).

Empirical reports submitted to Health Psychology are required to meet certain TOP standards. Adherence to other TOP standards is optional but the manuscript must disclose the level of adherence. The list below summarizes these requirements; see the TOP guidelines for details.

• Citation Standards: Level 2, Required—All data, program code and other methods must be cited in the text and listed in the References section.
• Data Transparency: Level 1, Disclose—The article must disclose whether or not the materials are posted to a trusted repository. In both the Author Note and the Transparency and Openness subsection in the Method section, state whether the data are available, and if so, where to access them. The preferred method is to provide a link to a trusted repository. Trusted discipline-specific, institutional, and open research repositories are acceptable. See the  OpenAIRE Guide  for information and  re3data.org  help with finding repositories.
• Analytic Methods (Code) Transparency: Level 2, Required—Provide the computer code needed to reproduce the major analyses in a supplement or via a link to a trusted repository in the Transparency and Openness subsection in the Method section. Explain exceptions in the Statistical Analysis section.
• Research Materials Transparency: Level 2, Required—Provide key nonproprietary materials such as questionnaires or survey forms in a supplement or via a link to a trusted repository in the Transparency and Openness subsection in the Method section. Provide citations for proprietary materials. Explain exceptions in the Method section.
• Reporting Standards; Design and Analysis Transparency: Level 2, Required—Adhere to relevant  Equator Network  reporting guidelines, such as CONSORT for randomized trials or PRISMA for systematic reviews and meta-analyses. Submit a completed reporting guideline checklist as a Document for Reviewers and include a participant flow diagram in the manuscript. Adhere to the APA Journal Article Reporting Standards  (JARS)  for items that are not addressed in the Equator Network guidelines.
• Study preregistration is defined as creation of time stamped, read-only documentation of study design and, if applicable, hypotheses, before the participants are enrolled.
• Access to a masked version of the preregistered study should be available at submission via stable link or supplemental material.
• Study design includes items such as experimental conditions, operationaliza­tion of variables, sampling plans, etc. For studies other than RCTs, a protocol or methods paper may be cited in lieu of study preregistration if it was published prior to the enrollment of study participants.
• The analysis plan may include information about planned analytic strategies, specific planned models, statistical decision rules, assumption checks, etc. It may also identify analyses that are meant to be confirmatory tests of a priori hypotheses. The goal is to clearly differentiate between preplanned vs. post hoc (and perhaps data-dependent) analyses.
• A priori analysis plans are defined as ones that are preregistered before the data are collected.  Blinded ex post  analyses are defined as ones that were not preregistered but that were planned before the relevant data were seen.  Post hoc  analyses are defined as ones that are conducted after the analyst or investigator has seen the data.
• Access to a masked version of the preregistered analysis plan should be available at submission via stable link or supplemental material.
• Replication: Level 1, Disclose—The journal encourages submission of replication studies. Submissions should include “A Replication of XX Study” in the subtitle of the manuscript as well as in the abstract.

Equity, diversity, and inclusion statement

Health Psychology is strongly committed to advancing diversity in all areas including but not limited to age, socioeconomic background, race/ethnicity, culture, gender, sexual orientation, religion, language, abilities, and the intersection of multiple underserved identities. In this context, the editorial team strives for inclusive excellence ; the belief that our mission to advance population health is facilitated by promoting diversity in who we are (representation), the scope of work, and how that work is achieved. Through these efforts we aim to create a more welcoming space to advance understanding of public health challenges, optimize the associated research efforts, harmonize research with the very communities we aim to benefit, and establish a sustainable pipeline of inclusion and representation for the journal’s future stewardship.

Please review the journal’s full EDI statement and a summary of the journal’s practices in support of equity, diversity, and inclusion.

Equity, diversity, and inclusion in Health Psychology

Health Psychology is committed to improving equity, diversity, and inclusion (EDI) in scientific research, in line with the  APA Publishing EDI framework and APA’s trio of 2021 resolutions to address systemic racism in psychology.

The journal encourages submissions which extend beyond Western, educated, industrialized, rich, and democratic (WEIRD) samples ( Henrich, et al., 2010 ). The journal welcomes submissions which feature Black, Indigenous, and People of Color (BIPOC) and other historically marginalized sample populations. The journal particularly welcomes submissions which feature collaborative research models (e.g., community-based participatory research [CBPR]; see  Collins, et al., 2018 ) and study designs that address heterogeneity within diverse samples. Studies focused exclusively on BIPOC and other historically excluded populations are also welcome.

To promote a more equitable research and publication process, Health Psychology has adopted the following standards for inclusive research reporting.

Author contribution statements using CRediT

The  APA Publication Manual ( 7th ed. ) stipulates that "authorship encompasses…not only persons who do the writing but also those who have made substantial scientific contributions to a study." In the spirit of transparency and openness, Health Psychology has adopted the Contributor Roles Taxonomy (CRediT) to describe each author's individual contributions to the work. CRediT offers authors the opportunity to share an accurate and detailed description of their diverse contributions to a manuscript.

Submitting authors must identify the contributions of all authors at initial submission according to the CRediT taxonomy. If the manuscript is accepted for publication, the CRediT designations will be published as an author contributions statement in the author note of the final article. All authors should have reviewed and agreed to their individual contribution(s) before submission.

Authors can claim credit for more than one contributor role, and the same role can be attributed to more than one author. Not all roles will be applicable to a particular scholarly work.

Participant description, sample justification, and informed consent

Authors must include a detailed description of the study participants in the Method section of each empirical report, including (but not limited to) the following:

• racial identity
• nativity or immigration history
• socioeconomic status
• clinical diagnoses and comorbidities (as appropriate)
• any other relevant demographics (e.g., disability status; sexual orientation)

In both the abstract and in the discussion section of the manuscript, authors must discuss the diversity of their study samples and the generalizability of their findings (see also the constraints on generality section below).

Authors must justify their sample demographics in the discussion section. If Western, educated, industrialized, rich, and democratic (WEIRD) or all-White samples are used, authors should justify their samples and describe their sample inclusion efforts (see  Roberts, et al., 2020  for more information on justifying sample demographics).

The method section also must include a statement describing how informed consent was obtained from the participants (or their parents/guardians), including for secondary use of data if applicable, and indicate that the study was conducted in compliance with an appropriate Internal Review Board.

Reporting year(s) of data collection

Authors must disclose the year(s) of data collection in both the abstract and in the method section in order to appropriately contextualize the study. 

Positionality statements

Authors are encouraged to include a positionality statement in the author note. Positionality statements are intended to address potential author bias by transparently reporting how the identities of the authors relate to the research/article topic and to the identity of the participants, as well as the extent to which those identities are represented in the scientific record. The statement should be included in the author note and expanded upon in the Discussion section. See this example from Jovanova, et al. (2022) :

• Sample positionality statement: “Mindful that our identities can influence our approach to science ( Roberts, et al. 2020) , the authors wish to provide the reader with information about our backgrounds. With respect to gender, when the manuscript was drafted, four authors self-identified as women and four authors as men. With respect to race, six authors self-identified as white, one as South Asian and one as East Asian.”

For more guidance on writing positionality statements, see Roberts, et al. (2020) and  Hamby (2018) .

Reflexivity

The journal welcomes submissions that proactively challenge racism and other forms of oppression. In line with the  APA Guidelines on Race and Ethnicity in Psychology (2019) , authors are encouraged to include reflexive statements in the Discussion section, addressing the following questions.

• What are the policy implications of these findings?
• Could this research be misinterpreted or misused to negatively affect underrepresented groups? Does the research have the potential to cause harm to vulnerable groups? If so, how can this be addressed and mitigated?
• Does the design or framing of this research reinforce negative stereotypes about marginalized populations?
• What roles do the researcher(s)’ values and worldview play in the selection of this topic or design of the study?

Data, materials, and code

Authors must state whether data, code, and study materials are posted to a trusted repository and, if so, how to access them, including their location and any limitations on use. If they cannot be made available, authors must state the legal or ethical reasons why they are not available. Trusted repositories adhere to policies that make data discoverable, accessible, usable, and preserved for the long term. Trusted repositories also assign unique and persistent identifiers. Recommended repositories include  APA’s repository  on the Open Science Framework (OSF), or authors can access a full  list of other recommended repositories .

In a subsection titled "Transparency and Openness" in the Methods section, specify whether and where the data and material will be available or note the legal or ethical reasons for not doing so. For submissions with quantitative or simulation analytic methods, state whether the study analysis code is posted to a trusted repository, and, if so, how to access it (or the legal or ethical reason why it is not available).

For example:

• All data have been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].
• Materials and analysis code for this study are not available.
• The code behind this analysis/simulation has been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].

Constraints on generality

In a subsection of the discussion titled "Constraints on generality," authors are encouraged to include a detailed discussion of the limits on generality (see  Simons, Shoda, & Lindsay, 2017 ). In this section, authors should detail grounds for concluding why the results are may or may not be specific to the characteristics of the participants. They should address limits on generality not only for participants but for materials, procedures, and context. Authors should also specify which methods they think could be varied without affecting the result and which should remain constant.

Public significance statements

Authors submitting manuscripts to Health Psychology must include a brief statement (2-3 sentences/70 words max) summarizing the public health significance/implications of their work. For example, this statement may describe how the current research advances some fundamental knowledge of health and disease, vulnerable populations, sheds light on hypothesized mechanisms, or contributes knowledge that may enhance prevention and health, contribute to illness management, or aid coping and recovery. Hyperlinks and URLs are not permitted in this description. The statement should be included within the manuscript on the abstract/keywords page and should be written clearly for the educated public.

Peer review policy

All manuscripts submitted to Health Psychology undergo an initial editorial evaluation which may result in rejection without external peer review.

Manuscripts that are sent out for external peer review receive single-masked reviews. This means that the reviewers are anonymous, but the authors are not.

The manuscript’s title page should include the name and affiliation of every author. Identifying information should not be masked on the title page, in the Abstract or in body of the manuscript, or in citations or references. Masked manuscripts may be returned to the authors without review.

Technical specifications

Tables should adhere to APA Style . Use Word’s Insert Table function to create tables, and do not insert tabs or extra spaces to align columns as this will create problems when the table is typeset.

Preferred formats for graphics files are TIFF and JPG, and preferred format for vector-based files is EPS. Graphics downloaded or saved from web pages are not acceptable for publication. Multipanel figures (i.e., figures with parts labeled a, b, c, d, etc.) should be assembled into one file. When possible, please place symbol legends below the figure instead of to the side.

• All color line art and halftones: 300 DPI
• Black and white line tone and gray halftone images: 600 DPI

Line weights

• Color (RGB, CMYK) images: 2 pixels
• Grayscale images: 4 pixels
• Stroke weight: 0.5 points

APA offers authors the option to publish their figures online in color without the costs associated with print publication of color figures.

The same caption will appear on both the online (color) and print (black and white) versions. To ensure that the figure can be understood in both formats, authors should add alternative wording (e.g., “the red (dark gray) bars represent”) as needed.

For authors who prefer their figures to be published in color both in print and online, original color figures can be printed in color at the editor's and publisher's discretion provided the author agrees to pay:

• $900 for one figure
• An additional $600 for the second figure
• An additional $450 for each subsequent figure

Equations and computer code

Use Times or Symbol font or Microsoft’s Equation Editor for equations or formulas.

If possible, provide executable source code in an online-only supplement, not in the manuscript itself. If it is essential to include code in the manuscript, submit a separate file with the code exactly as you want it to appear. Use 8-point Courier New font and do not add any extra indents, line spaces, or line breaks. Segments >40 characters will be printed as images; shorter snippets of code will be typeset in Courier New and run with the rest of the text.

List references in alphabetical order. Each listed reference should be cited in text, and each text citation should be listed in the References section.

Examples of basic reference formats:

Journal article

McCauley, S. M., & Christiansen, M. H. (2019). Language learning as language use: A cross-linguistic model of child language development. Psychological Review , 126 (1), 1–51. https://doi.org/10.1037/rev0000126

Authored book

Brown, L. S. (2018). Feminist therapy (2nd ed.). American Psychological Association. https://doi.org/10.1037/0000092-000

Chapter in an edited book

Balsam, K. F., Martell, C. R., Jones. K. P., & Safren, S. A. (2019). Affirmative cognitive behavior therapy with sexual and gender minority people. In G. Y. Iwamasa & P. A. Hays (Eds.), Culturally responsive cognitive behavior therapy: Practice and supervision (2nd ed., pp. 287–314). American Psychological Association. https://doi.org/10.1037/0000119-012

Data set citation

Alegria, M., Jackson, J. S., Kessler, R. C., & Takeuchi, D. (2016). Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003 [Data set]. Inter-university Consortium for Political and Social Research. http://doi.org/10.3886/ICPSR20240.v8

Ethical Principles

It is a violation of APA Ethical Principles to publish “as original data, data that have been previously published” (Standard 8.13).

APA Ethical Principles also state that “after research results are published, psychologists do not withhold the data on which their conclusions are based from other competent professionals who seek to verify the substantive claims through reanalysis and who intend to use such data only for that purpose, provided that the confidentiality of the participants can be protected and unless legal rights concerning proprietary data preclude their release” (Standard 8.14).

APA expects authors to make their data available if asked during the editorial process and for at least five years after the date of publication.

If the manuscript is accepted, the corresponding author is required to sign and submit a Certification of Compliance with APA Ethical Principles (PDF, 26KB) .

See the APA Ethical Principles and Code of Conduct for further guidance.

Publication policies and forms

For full details on publication policies, including use of Artificial Intelligence tools, please see APA Publishing Policies .

APA policy prohibits authors from submitting the same manuscript for concurrent consideration by two or more publications.

See APA’s Internet Posting Guidelines for information about posting copies of manuscripts prior to publication in Health Psychology.

APA requires all authors of accepted manuscripts to complete a form that lists any possible conflicts of interest in the conduct and reporting of research, such as financial interests in a test or procedure, or funding by pharmaceutical companies for drug research.

• Download Full Disclosure of Interests Form (PDF, 41KB)

All necessary permissions to reproduce in print and electronic form any copyrighted work, including test materials, photographs, and other graphic images (including those used as stimuli in experiments) must be provided for accepted papers.  On advice of counsel, APA may decline to publish any image whose copyright status is unknown.

• Download Permissions Alert Form (PDF, 13KB)

The APA Journals Publishing Resource Center provides further guidance for authors and reviewers.

Other information

See APA’s Publishing Policies page for more information on publication policies, including information on author contributorship and responsibilities of authors, author name changes after publication, the use of generative artificial intelligence, funder information and conflict-of-interest disclosures, duplicate publication, data publication and reuse, and preprints.

Visit the Journals Publishing Resource Center for more resources for writing, reviewing, and editing articles for publishing in APA journals.

Editorial leadership biographies and research specializations

Editor-in-chief

John M. Ruiz, PhD University of Arizona, United States

Senior associate editor

Frank J. Penedo, PhD University of Miami, United States

Associate editors

Carmela Alcántara, PhD Columbia University, United States

Diana A. Chirinos, PhD Northwestern University, United States

Lori A. Francis, PhD Penn State University, United States

Paige A. Green, PhD, MPH, FABMR National Institutes of Health/National Cancer Institute, United States

Aric A. Prather, PhD University of California, San Francisco, United States

Eli Puterman, PhD The University of British Columbia, Vancouver, Canada

A. Janet Tomiyama, PhD University of California, Los Angeles, United States

Bert N. Uchino, PhD University of Utah, United States

Anna C. Whittaker, PhD University of Stirling, United Kingdom

Editorial fellows

Isabel Almeida, PhD University of California, Irvine, United States

James Garcia, PhD California State University, Fullerton, United States

Sarah Javier, PhD Palo Alto VA, United States

Thomas Le Bryn Mawr College, United States

Lydia Poole University of Surrey, United Kingdom

Ruben Tinajero, PhD West Virginia University, United States

Consulting editors

Chul Ahn, PhD University of Texas Southwestern, United States

Mustafa al'Absi, PhD University of Minnesota, United States

Norman Anderson, PhD Florida State University, United States

Bernard Appiah, PhD Syracuse University, United States

Elva Arredondo, PhD San Diego State University, United States

Simon Bacon, PhD Concordia University, Canada

Austin S. Baldwin, PhD Southern Methodist University, United States

Kelly Glazer Baron, PhD University of Utah, United States

Gary Bennett, PhD Duke University, United States

Wendy Birmingham, PhD Brigham Young University, United States

Julia K. Boehm, PhD Chapman University, United States

Kyle Bourassa, PhD Duke University, United States

Lisa Bowleg, PhD The George Washington University, United States

Elizabeth Brondolo, PhD St. John's University, United States

Matthew Burg, PhD Yale University, United States

Jessica L. Burris, PhD University of Kentucky, United States

Belinda Campos, PhD University of California, Irvine, United States

Lisa Carter-Bawa, PhD, APRN Center for Discovery and Innovation at Hackensack Meridian Health, United States

David Chae, ScD Tulane University, United States

Edith Chen, PhD Northwestern University, United States

Irma Corral, PhD East Carolina University, United States

Matthew Cribbet, PhD University of Alabama, United States

Jenny M. Cundiff, PhD University of Alabama, United States

Kimberly D'Anna-Hernandez, PhD Marquette University, United States

Lisa Diamond, PhD University of Utah, United States

Blaine Ditto, PhD McGill University, Canada

Tessa L. Dover, PhD Portland State University, United States

Christine Dunkel Schetter, PhD University of California, Los Angeles, United States

Genevieve Dunton, PhD University of South California, United States

Elissa Epel, PhD University of California, San Francisco, United States

Paul Estabrooks, PhD University of Utah, United States

Carolyn Y. Fang, PhD Fox Chase Cancer Center, United States

Melissa Flores, PhD University of Arizona, United States

James J. García, PhD California State Fullerton, United States

Peter J. Gianaros, PhD University of Pittsburgh, United States

Martin S. Hagger, PhD University of California, Merced, United States and University of Jyväskylä, Finland

Chanita Hughes-Halbert, PhD USC Norris Comprehensive Cancer Center, United States

Heidi A. Hamann, PhD University of Arizona, United States

Mark L. Hatzenbuehler, PhD Harvard University, United States

Rashelle Hayes, PhD VCU Health, United States

Jonathan Helm, PhD San Diego State University, United States

Rosalba Hernandez, PhD University of Illinois Urbana-Champaign, United States

Kisha Holden, PhD Morehouse School of Medicine, United States

David Huebner, PhD The George Washington University, United States

Tristen K. Inagaki, PhD San Diego State University, United States

Michael R. Irwin, MD University of California, United States

Charles R. Jonassaint, PhD University of Pittsburgh, United States

Nataria Tennille Joseph, PhD Pepperdine University, United States

Robert-Paul Juster, PhD University of Montreal, Canada

Robert M. Kaplan, PhD Stanford University, United States

Gaston Kapuku, PhD Augusta University, United States

Tasneem Khambaty, PhD University of Maryland, Baltimore County, United States

Shin Ye Kim, PhD Texas Tech University, United States

Youngmee Kim, PhD University of Miami, United States

Nina Knoll, PhD Freie Universität Berlin, Germany

Richard D. Lane, MD, PhD University of Arizona, United States

Simon Craddock Lee, PhD The University of Kansas, United States

Tené T. Lewis, PhD Emory University, United States

Maria Magdalena Llabre, PhD University of Miami, United States

Travis I. Lovejoy PhD, MPH Oregon Health & Science University, United States

Carissa A. Low, PhD University of Pittsburgh, United States

Mark A. Lumley, PhD Wayne State University, United States

Lesley Lutes, PhD The University of British Columbia Okanagan, Canada

David X. Marquez, PhD University of Illinois Chicago, United States

Becky Marquez, PhD University of California, San Diego, United States

David G. Marrero, PhD University of Arizona, United States

Anna Marsland, PhD University of Pittsburgh, United States

Kevin S. Masters, PhD University of Colorado Denver, United States

Jessica McCurley, PhD San Diego State University, United States

Marcellus M. Merritt, PhD University of Wisconsin Milwaukee, United States

Gregory E. Miller, PhD Northwestern University, United States

Matthew F. Muldoon University of Pittsburgh, United States

Enrique W. Neblett, Jr., PhD University of Michigan, United States

Rory O' Connor, PhD University of Glasgow, United Kingdom

KayLoni L. Olson, PhD Brown Medical School, United States

Anthony D. Ong, PhD Cornell University, United States

Manuel S. Ortiz, PhD Universidad de La Frontera, Chile

Gozde Ozakinci, PhD University of Stirling, Scotland

Martin Picard, PhD Columbia University, United States

Rachel Povey, PhD Staffordshire University, United Kingdom

Wizdom Powell, PhD UConn Health, United States

Tiffany M. Powell-Wiley, MD, MPH National Institutes of Health, United States

Ravi Prasad, PhD University of California-Davis School of Medicine, United States

Rebecca G. Reed, PhD University of Pittsburgh, United States

Tracey A. Revenson, PhD Hunter College and the Graduate Center, City University of New York, United States

Jamie Rhudy, PhD The University of Tulsa, United States

Christine M. Rini, PhD Northwestern University, United States

Theodore F. Robles, PhD University of California, Los Angeles, United States

Carlos J. Rodriguez, MD, MPH Albert Einstein College of Medicine, United States

Andrea Romero, PhD University of Arizona, United States

Joseph E. Schwartz, PhD Columbia University, United States

Elizabeth K. Seng, PhD Yeshiva University, United States

Jonathan Shaffer, PhD University of Colorado Denver, United States

George Slavich, PhD University of California, United States

Timothy W. Smith, PhD University of Utah, United States

Kim G. Smolderen, PhD Yale University, United States

Anna V. Song, PhD University of California, Merced, United States

Michael V. Stanton, PhD California State University, East Bay, United States

Annette L. Stanton, PhD University of California, United States

Jesse C. Stewart, PhD Indiana University-Purdue University Indianapolis, United States

Christian Swann, PhD Southern Cross University, Australia

Vivien Swanson, PhD University of Stirling, Scotland

Julian Thayer, PhD University of California, Irvine, United States

Rebecca C. Thurston, PhD University of Pittsburgh, United States

Lianne Tomfohr-Madsen, PhD The University of British Columbia Vancouver, Canada

Ranak Trivedi, PhD Stanford University, United States

Zina Trost, PhD Virginia Commonwealth University, United States

Claudia Trudel-Fitzgerald, PhD Université du Québec à Trois-Rivières, Canada

William Tsai, PhD New York University, United States

Julie M. Turner-Cobb, PhD Bournemouth University, United Kingdom

Shari Waldstein, PhD University of Maryland, Baltimore County, United States

Baldwin M. Way, PhD The Ohio State University

Kristi E. White, PhD, ABPP University of Minnesota, United States

Paula G. Williams, PhD The University of Utah, United States

DeWayen P. Williams, PhD University of California, Irvine, United States

Matthew J. Zawadzki, PhD University of California, Merced, United States

Abstracting and indexing services providing coverage of Health Psychology ®

• Abstracts in Anthropology
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• ASSIA: Applied Social Sciences Index & Abstracts
• Cabell's Directory of Publishing Opportunities in Psychology
• CINAHL Complete
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• Current Abstracts
• Current Contents: Clinical Medicine
• Current Contents: Social & Behavioral Sciences
• Educational Research Abstracts Online
• Embase (Excerpta Medica)
• Environmental Science and Pollution Management
• ERIH (European Reference Index for the Humanities and Social Sciences)
• Expanded Academic ASAP
• Family & Society Studies Worldwide
• General OneFile
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• Health & Wellness Resource Center and Alternative Health Module
• Health Reference Center Academic
• InfoTrac Custom
• Journal Citations Report: Social Sciences Edition
• Mosby's Nursing Consult
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• Nursing and Allied Health Collection
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• OmniFile Full Text Mega
• Psychology Collection
• Russian Academy of Sciences Bibliography
• Science Citation Index Expanded
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• Supplemental Index
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• Women's Studies International

Special issue of the APA journal Health Psychology, Vol. 42, No. 12, December 2023. The empirical reports in this special issue of Health Psychology showcase the work of a diverse array of accomplished early-stage investigators who are members of the Adolescent Brain Cognitive Development (ABCD) study consortium and who are drawn from the community of female and underrepresented scientists.

Special issue of APA's journal Health Psychology, Vol. 42, No. 8, August 2023. This special issue examines various aspects of vaccine hesitancy using a health psychology lens.

Special issue of APA's journal Health Psychology, Vol. 41, No. 10, October 2022. This special issue reflects where cardiovascular behavioral medicine has been, where the field needs to go, and how we might get there.

Special issue of APA's Health Psychology, Vol. 40, No. 12, December 2021. This special issue presents novel research that advances translational behavioral science, focusing primarily on the early phases of behavioral translation that are not as well recognized as later-phase translational science.

Special issue of the APA journal Health Psychology, Vol. 39, No. 9, September 2020. This special issue showcases how investigators working in different areas of health behavior change are utilizing early phase studies to advance intervention development.

Special issue of the APA journal Health Psychology, Vol. 38, No. 9, September 2019. Topics include relevance, measurement, mechanisms, and interventions for multimorbidity.

Special issue of the APA journal Health Psychology, Vol. 38, No. 5, May 2019. The issue features outcomes research and applications of universal health-related quality of life measures produced under the Patient-Reported Outcomes Measurement Information System initiative.

Special issue of the APA journal Health Psychology, Vol. 35, No. 8, August 2016. Includes articles about tobacco use, eating behavior, physical activity, alcohol consumption, condom use, and the impact of implicit prejudice on physical and mental health.

Special issue of the APA journal Health Psychology, Vol. 35, No. 4, April 2016. The papers offer windows into cutting-edge themes, methodologies, challenges, and future directions in understanding psychosocial factors and sociocultural sequelae as they relate to cardiovascular health disparities.

Special issue of the APA journal Health Psychology, Vol. 34, No. S, December 2015. The issue includes 11 papers that address the need for more rigorous methodology, valid assessment, innovative interventions, and increased access to evidence-based programs and interventions.

Special issue of the APA journal Health Psychology, Vol. 34, No. 4, April 2015. The issue showcases a range of qualitative research projects conducted by health psychologists with a view to promoting greater uptake and development of qualitative research methods in the field.

Special issue of the APA journal Health Psychology, Vol. 33, No. 6, June 2014. The studies used diverse measures to quantify social relationships, ranging from network size or composition and social integration to availability of a confidante and quality of social interactions.

Special issue of the APA journal Health Psychology, Vol. 32, No. 9, September 2013. The issue was designed to attract both conceptual and empirical articles, to present a wide spectrum of thinking and methods, and to illustrate how behavioral economics might address today's pressing health problems.

Special issue of the APA journal Health Psychology, Vol. 32, No. 5, May 2013. Articles highlight major areas of innovation in recent social/personality psychology that hold promise for synergistic integration with health psychology and related fields in the pursuit of adequate health promotion, health care, and population health.

Special issue of the APA journal Health Psychology, Vol. 32, No. 1, January 2013. The first section focuses on public health issues, including physical exercise, alcohol consumption, and help-seeking. The second section covers illness-related phenomena, including male-specific cancers, sports-induced disability, and male sterilization.

Special issue of the APA journal Health Psychology, Vol. 27, No. 3 (Suppl.), May 2008. Articles discuss psychosocial processes underlying smoking; modern science and tobacco research; initiation and maintenance of smoking cessation; depressive symptoms and cigarette smoking; functional beliefs about smoking and quitting activity; processing of anti-smoking messages; and effect of regulatory focus on performance in smoking and weight loss interventions.

Special issue of the APA journal Health Psychology, Vol. 27, No. 2 (Supplement), March 2008. Includes articles about mediation and moderation of psychological factors in patients with diabetes; chronic pain; cancer caregivers; and high blood pressure, as well as adolescent health; physical activity; and sexual risk reduction in women.

Special issue of the APA journal Health Psychology, Vol. 27, No. 1, Suppl, January 2008. It was developed to highlight some of the fundamental issues from a biological, cognitive, social, and environmental perspective for understanding the impact of intervention effects on behavior change processes and ultimate health.

Special issue of the APA journal Health Psychology, Vol. 24, No. 4, July 2005. Includes articles about decision making strategies; linking decision making research and cancer prevention and treatment; communication models in shared decision making; regret; coping; and advanced directives and end-of-life decisions.

Work submitted to Health Psychology should adhere to the Transparency and Openness Promotion (TOP) Guidelines . For empirical reports, include a brief Transparency and Openness subsection at the beginning of the Methods section. The purpose is to gather all required disclosures and links in one location to make it easier for readers, reviewers, and editors to find this information. This is an example of a brief transparency and openness statement for an RCT:

In this article, we report how we determined our sample size, all data exclusions, all manipulations, and all measures that were included in the study, and we follow the CONSORT guideline for reporting parallel group randomized trials. All data, analysis code, and research materials are available at [ stable link to repository ]. Data were analyzed using R version 4.0.0 (R Core Team, 2020). The trial was pre-registered on clinicaltrials.gov (NCT99999999).

• Citation Standards: Level 2, Required—All data, program code, and other methods developed by others must be cited in the text and listed in the References section.
• Data Transparency: Level 1, Disclose—In the Transparency and Openness subsection in the Method section, state whether the data are posted to a trusted repository, and if so, how to access them. Trusted discipline-specific, institutional, and open research repositories are acceptable. See the  OpenAIRE Guide  for information and  re3data.org  help with finding repositories.
• Replication: Level 1, Disclose—The journal encourages submission of replication studies.

Journal equity, diversity, and inclusion statement

Representation.

Diversity in representation is central to perceptions of affiliation, fairness, and receptivity. It is also a critical facilitator of how we understand population health priorities, the types of research questions asked, the way those questions are approached, and how findings are disseminated to maximize impact. The new editorial team of Health Psychology has prioritized representation of diverse identities through action including but not limited to the following:

• Selection of a highly diverse, all-star team of experts in key domains. The 11-member executive team of the Editor-In-Chief (EIC) and Associate Editors (AEs) includes 6 women, 6 scholars of color, 2 international scholars, and members identifying as sexual and gender minorities (SGM). All have a demonstrated record in health equity.
• To foster the goal of representation, the EIC and AE members provide their photos, pronouns, and bios with identity on the journal webpage which can be found here: 2023–28 Health Psychology editorial team.
• A new Consulting Editor (CE) team was assembled with consideration of areas of expertise and inclusivity to meet the goals of peer review for the revised journal mission encompassing population health (see below). This team of over 100 scholars includes a range of disciplines from psychology, medicine, public health, epidemiology, and anthropology with expertise in health psychology, specific conditions, key populations, health policy, and a variety of methods, approaches, and frameworks. Approximately 50% of the team identifies as scholars of color/people of the global majority with nearly two thirds identifying with a range of underrepresented identities.
• Like the EIC and AEs, CE members will be invited to share their photos, pronouns, and bios with identity on the journal webpage in the spirit of fostering perceptions of representation. This is a work in progress and will be updated by early January 2023.
• Finally, the editorial team encourages all reviewers and authors to complete the new APA demographic survey so we can assess who we are and the degree to which our efforts are having an impact. Advancing inclusivity is the responsibility of all and this action is critical to supporting future efforts.

Contemporary inclusive mission

The mission of Health Psychology reflects its values for inclusive excellence and is consistent with APA’s recent ratification of a population health approach to address critical issues in society ( Psychology’s Role in Advancing Population Health ). Health Psychology’s mission statement reads in part,

“Adhering to the highest standards of peer-review, the journal’s mission is to advance basic to translational science, policy, and practice to significantly impact population health. The journal actively encourages submissions that address psychological, behavioral, biobehavioral and sociocultural dimensions of the diversity of human experience, and which reflect a strong commitment to inclusive excellence to facilitate the goal of optimal health for all.”

The editorial team’s intent is to maintain the journals status as the flagship journal for the field and expand its impact as a premier scientific journal by drawing a more representative science. The expectation is that the population health perspective will be infused throughout the journal’s efforts from its editors to authors to content and readership.

Actions and policies

To achieve the scientific aims of inclusivity, the editorial team is undertaking a number of actions and policies. These include but are not limited to the following:

• use of commentaries and special issues to highlight population science issues
• Spanish translations of all abstracts
• openness to community and stakeholder models
• changing journal cover art each issue to highlight topics including issues of diversity, inclusivity, etc.
• required use of bias-free language
• mandatory reporting of SES for samples or an indication of why that data is not reported
• required impact statements
• required sample descriptions and justifications to ensure diversity and clearly communicate reasons for exceptions
• Access to knowledge is a critical equity issue. Health Psychology recognizes the challenge of accessing its content within the APA journal publishing structure and the knowledge disparities this may create and sustain. The journal team is working with the publishers to identify ways to improve access including participation in the Editor’s Choice program and use of various free-to-read mechanisms.

Pathways to improving the pipeline

The editorial team is committed to establishing a robust pipeline of inclusivity in its peer review and editorial ranks. Two specific examples are:

• Mentored reviewing:  The journal strongly supports the development, training, and mentoring of student/trainees in the peer review process. We are working with APA to identify ways to ensure credit for both the mentor and mentee including in ORCID and in the annual publication of reviewer names in the journal. The editorial team will also hold virtual trainings to facilitate reviewer basics and skill development and optimize the overall peer review process.
• paired mentoring with an AE specializing in their area of expertise or with broad experience in health psychology/behavioral medicine
• training on how the review process works, how to triage papers, how to choose reviewers, how to integrate reviews towards an editorial decision, and how to communicate with authors
• monthly meetings with the EIC to discuss the broader editorship of the journal and developing and implementing strategic aims such as pursuit of commentaries, developing special issues, recruiting reviewers, and identifying emerging topics
• credit on the journal masthead
• opportunities for letters of support for promotion or other career-related advances
• a $1000 honorarium

Inclusive study designs

• Collaborative research models
• Diverse samples

Definitions and further details on inclusive study designs are available on the Journals EDI homepage .

Inclusive reporting standards

• Bias-free language and community-driven language guidelines (required)
• Author contribution roles using CRediT (required)
• Reflexivity (recommended)
• Positionality statements (recommended)
• Data sharing and data availability statements (required)
• Impact statements (required)
• Year(s) of data collection (required)
• Participant sample descriptions (required)
• Sample justifications (required)
• Constraints on Generality (COG) statements (recommended)

More information on this journal’s reporting standards is listed under the submission guidelines tab .

Pathways to authorship and editorship

Editorial fellowships.

Editorial fellowships help early-career psychologists gain firsthand experience in scholarly publishing and editorial leadership roles. This journal offers an editorial fellowship program for early-career psychologists from historically excluded communities.

Reviewer mentorship program

This journal encourages reviewers to submit co-reviews with their students and trainees. The journal likewise offers a formal reviewer mentorship program where graduate students and postdoctoral fellows from historically excluded groups are matched with a senior reviewer to produce an integrated review.

Other EDI offerings

Orcid reviewer recognition.

Open Research and Contributor ID (ORCID) Reviewer Recognition provides a visible and verifiable way for journals to publicly credit reviewers without compromising the confidentiality of the peer-review process. This journal has implemented the ORCID Reviewer Recognition feature in Editorial Manager, meaning that reviewers can be recognized for their contributions to the peer-review process.

Announcements

• APA endorses the Transparency and Openness Promotion (TOP) Guidelines
• Guidelines for reviewers
• April 2021: Health Psychology adopts Transparency and Openness Promotion (TOP) Guidelines

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Nat. Med. (2021).

Chen, P.-H. C., Mermel, C. H. & Liu, Y.

The Lancet Digital Health (2021). doi:10.1016/S2589-7500(21)00216-8

Kelly, C. J., Brown, A. P. Y. & Taylor, J. A.

(eds. Lidströmer, N. & Ashrafian, H.) 1–18 (Springer International Publishing, 2021).

Poplin, R., Zook, J. M. & DePristo, M.

JAMA 326, 268–269 (2021).

Mitani, A., Hammel, N. & Liu, Y.

Nature Biomedical Engineering 1–3 (2021). [readcube]

Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., Liu, Y., Topol, E., Dean, J. & Socher, R.

npj Digital Medicine 4, 5 (2021).

Steiner, D. F., Chen, P.-H. C. & Mermel, C. H.

Biochim. Biophys. Acta Rev. Cancer 1875, 188452 (2021).

Liu, Y., Yang, L., Phene, S. & Peng, L.

Artificial Intelligence in Medicine 247–264 (2021).

Warnert, E. A. H., Kasper, L., Meltzer, C. C., Lightfoote, J. B., Bucknor, M. D., Haroon, H., Duggan, G., Gowland, P., Wald, L., Miller, K. L., Morris, E. A. & Anazodo, U. C.

J. Magn. Reson. Imaging (2020). doi:10.1002/jmri.27476 [readcube]

Rakha, E. A., Toss, M., Shiino, S., Gamble, P., Jaroensri, R., Mermel, C. H. & Chen, P.-H. C.

J. Clin. Pathol. (2020). doi:10.1136/jclinpath-2020-206908

Sayres, R., Hammel, N. & Liu, Y.

Annals of Eye Science 5, 18–18 (2020).

Ibrahim, A., Gamble, P., Jaroensri, R., Abdelsamea, M. M., Mermel, C. H., Chen, P.-H. C. & Rakha, E. A.

Breast 49, 267–273 (2020).

Liu, Y., Chen, P.-H. C., Krause, J. & Peng, L.

JAMA 322, 1806–1816 (2019). [readcube]

Kelly, C. J., Karthikesalingam, A., Suleyman, M., Corrado, G., & King, D.

BMC Med. 17, 195 (2019).

Rajkomar, A., Hardt, M., Howell, M. D., Corrado, G., & Chin, M. H.

Ann. Intern. Med. 169(12):866-872 (2018).

Curiel-Lewandrowski, C., Novoa, R. A., Berry, E., Celebi, M. E., Codella, N., Giuste, F., Gutman, D., Halpern, A., Leachman, S., Liu, Y., Liu, Y., Reiter, O. & Tschandl, P.

599–628. Springer New York (2019).

Chen, C. P.-H., Liu, Y., & Peng, L.

Nat. Mater. 18, 410–414 (2019). [readcube]

Rajkomar, A., Dean, J., & Kohane I.

N. Engl. J. Med. 380:1347-1358 (2019).

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S. & Dean, J.

Nat. Med. 25, 24–29 (2019). [readcube]

Rough K, Thompson J.

Ophthalmology. 125(8):1136-1138 (2018).

Wachter, R. M., Howell, M. D.

JAMA 320(1):25-26 (2018).

Cross-Specialty Applied AI

by Krishnamurthy (Dj) Dvijotham & Taylan Cemgil

Google Deepmind | 17-Jul-2023

by Shekoofeh Azizi & Laura Culp

Google Research Blog | 26-Apr-2023

by Alex D’Amour & Katherine Heller

Google Research Blog | 18-Oct-2021

by Shekoofeh Azizi

Google Research Blog | 13-Oct-2021

Publications

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., Arbel, T., Bakas, S., Benis, A., Buettner, F., Cardoso, M. J., Cheplygina, V., Chen, J., Christodoulou, E., Cimini, B. A., Farahani, K., Ferrer, L., Galdran, A., van Ginneken, B., Glocker, B., Godau, P., Hashimoto, D. A., Hoffman, M. M., Huisman, M., Isensee, F., Jannin, P., Kahn, C. E., Kainmueller, D., Kainz, B., Karargyris, A., Kleesiek, J., Kofler, F., Kooi, T., Kopp-Schneider, A., Kozubek, M., Kreshuk, A., Kurc, T., Landman, B. A., Litjens, G., Madani, A., Maier-Hein, K., Martel, A. L., Meijering, E., Menze, B., Moons, K. G. M., Müller, H., Nichyporuk, B., Nickel, F., Petersen, J., Rafelski, S. M., Rajpoot, N., Reyes, M., Riegler, M. A., Rieke, N., Saez-Rodriguez, J., Sánchez, C. I., Shetty, S., Summers, R. M., Taha, A. A., Tiulpin, A., Tsaftaris, S. A., Van Calster, B., Varoquaux, G., Yaniv, Z. R., Jäger, P. F. & Maier-Hein, L.

Nat. Methods 21, 182–194 (2024). [readcube]

Brown, A., Tomasev, N., Freyberg, J., Liu, Y., Karthikesalingam, A. & Schrouff, J.

Nat. Commun. 14, 4314 (2023).

Dvijotham, K., Winkens, J., Barsbey, M., Ghaisas, S., Stanforth, R., Pawlowski, N., Strachan, P., Ahmed, Z., Azizi, S., Bachrach, Y., Culp, L., Daswani, M., Freyberg, J., Kelly, C., Kiraly, A., Kohlberger, T., McKinney, S., Mustafa, B., Natarajan, V., Geras, K., Witowski, J., Qin, Z. Z., Creswell, J., Shetty, S., Sieniek, M., Spitz, T., Corrado, G., Kohli, P., Cemgil, T. & Karthikesalingam, A.

Nat. Med. 1–7 (2023).

Azizi, S., Culp, L., Freyberg, J., Mustafa, B., Baur, S., Kornblith, S., Chen, T., Tomasev, N., Mitrović, J., Strachan, P., Mahdavi, S. S., Wulczyn, E., Babenko, B., Walker, M., Loh, A., Chen, P.-H. C., Liu, Y., Bavishi, P., McKinney, S. M., Winkens, J., Roy, A. G., Beaver, Z., Ryan, F., Krogue, J., Etemadi, M., Telang, U., Liu, Y., Peng, L., Corrado, G. S., Webster, D. R., Fleet, D., Hinton, G., Houlsby, N., Karthikesalingam, A., Norouzi, M. & Natarajan, V.

Nature Biomedical Engineering 1–24 (2023). [readcube]

Schrouff, J., Harris, N., Koyejo, O. O., Alabdulmohsin, I., Schnider, E., Opsahl-Ong, K., Brown, A., Roy, S., Mincu, D., Chen, C., Dieng, A., Liu, Y., Natarajan, V., Karthikesalingam, A., Heller, K. A., Chiappa, S. & D’Amour, A.

NeurIPS (2022).

McKinney, S. M.

medRxiv (2022).

Freeman, B., Hammel, N., Phene, S., Huang, A., Ackermann, R., Kanzheleva, O., Hutson, M., Taggart, C., Duong, Q. & Sayres, R.

HCOMP 9, 60–71 (2021).

Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., Natarajan, V. & Norouzi, M.

Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 3478–3488 (2021).

Sadilek, A., Liu, L., Nguyen, D., Kamruzzaman, M., Serghiou, S., Rader, B., Ingerman, A., Mellem, S., Kairouz, P., Nsoesie, E. O., MacFarlane, J., Vullikanti, A., Marathe, M., Eastham, P., Brownstein, J. S., Arcas, B. A. Y., Howell, M. D. & Hernandez, J.

NPJ Digit Med 4, 132 (2021).

Mustafa, B., Loh, A., Freyberg, J., MacWilliams, P., Karthikesalingam, A., Houlsby, N. & Natarajan, V.

arXiv [cs.CV] (2021).

arXiv [eess.IV] (2021).

D’Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., Hormozdiari, F., Houlsby, N., Hou, S., Jerfel, G., Karthikesalingam, A., Lucic, M., Ma, Y., McLean, C., Mincu, D., Mitani, A., Montanari, A., Nado, Z., Natarajan, V., Nielson, C., Osborne, T. F., Raman, R., Ramasamy, K., Sayres, R., Schrouff, J., Seneviratne, M., Sequeira, S., Suresh, H., Veitch, V., Vladymyrov, M., Wang, X., Webster, K., Yadlowsky, S., Yun, T., Zhai, X. & Sculley, D.

arXiv [cs.LG] (2020).

Winkens, J., Bunel, R., Roy, A. G., Stanforth, R., Natarajan, V., Ledsam, J. R., MacWilliams, P., Kohli, P., Karthikesalingam, A., Kohl, S., Cemgil, T., Ali Eslami, S. M. & Ronneberger, O.

Hartman, T., Howell, M., Dean, J., Hoory, S., Slyper, R., Laish, I., Gilon, O, Vainstein, D., Corrado, G., Chou, K., Po, M., Williams, J., Ellis, S., Bee, G., Hassidim, A., Amira, R., Beryozkin, G., Szpektor, I., & Matias, Y.

BMC (2020).

Dermatology

by Pooja Rao

Google Research Blog | 19-Mar-2024

by Mike Schaekermann & Ivor Horn

Google Research Blog | 15-Mar-2024

by Dave Steiner & Rory Pilgrim

Google Research Blog | 8-Mar-2024

by Lou Wang

Google Keyword Blog | 14-Jun-2023

Google Keyword Blog | 08-Feb-2022

by Abhijit Guha Roy & Jie Ren

Google Research Blog | 27-Jan-2022

by Miles Hutson & Aaron Loh

TensorFlow Blog | 11-Oct-2021

by Peggy Bui & Yuan Liu

Google Keyword Blog | 18-May-2021

by Ayush Jain & Peggy Bui

Google Keyword Blog | 28-Apr-2021

by Timo Kohlberger & Yuan Liu

Google Research Blog | 19-Feb-2020

by Yuan Liu & Peggy Bui

Google Research Blog | 12-Sep-2019

Schaekermann, M., Spitz, T., Pyles, M., Cole-Lewis, H., Wulczyn, E., Pfohl, S. R., Martin, D., Jr, Jaroensri, R., Keeling, G., Liu, Y., Farquhar, S., Xue, Q., Lester, J., Hughes, C., Strachan, P., Tan, F., Bui, P., Mermel, C. H., Peng, L. H., Matias, Y., Corrado, G. S., Webster, D. R., Virmani, S., Semturs, C., Liu, Y., Horn, I. & Cameron Chen, P.-H.

eClinicalMedicine (2024).

Rikhye, R. V., Hong, G. E., Singh, P., Smith, M. A., Loh, A., Muralidharan, V., Wong, D., Sayres, R., Phung, M., Betancourt, N., Fong, B., Sahasrabudhe, R., Nasim, K., Eschholz, A., Matias, Y., Corrado, G. S., Chou, K., Webster, D. R., Bui, P., Liu, Y., Liu, Y., Ko, J. & Lin, S.

Mayo Clinic Proceedings: Digital Health (2024).

Alabdulmohsin, I.M., Schrouff, J., Koyejo, S.

35. NeurIPS (2022).

Vemulapalli, R., Morningstar, W. R., Mansfield, P. A., Eichner, H., Singhal, K., Afkanpour, A. & Green, B.

arXiv [cs.LG] (2022).

Huang, S. J., Liu, Y., Kanada, K., Corrado, G. S., Webster, D. R., Peng, L., Bui, P. & Liu, Y.

Skin Health and Disease (2021).

Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., Vo, N., Bui, P., Winter, S., MacWilliams, P., Corrado, G. S., Telang, U., Liu, Y., Cemgil, T., Karthikesalingam, A., Lakshminarayanan, B. & Winkens, J.

Med. Image Analysis. 75, 102274 (2021). [ reading link ]

Weng, W.-H., Deaton, J., Natarajan, V., Elsayed, G. F. & Liu, Y.

JAMA Netw Open 4, e217249–e217249 (2021).

Machine Learning for Health NeurIPS Workshop (ML4H), PMLR 136:415-429 (2020).

Singh, N., Lee, K., Coz, D., Angermueller, C., Huang, S., Loh, A. & Liu, Y.

in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 3172–3181 (2020).

Liu, Y., Jain, A., Eng, C., Way, D. H., Lee, K., Bui, P., Kanada, K., de Oliveira Marinho, G., Gallegos, J., Gabriele, S., Gupta, V., Singh, N., Natarajan, V., Hofmann-Wellenhof, R., Corrado, G. S., Peng, L. H., Webster, D. R., Ai, D., Huang, S., Liu, Y., Carter Dunn, R. & Coz, D.

Nat. Med. (2020). [readcube]

Ghorbani, A., Natarajan, V., Coz, D. & Liu, Y.

Machine Learning for Health NeurIPS Workshop (ML4H), PMLR 116:155-170 (2020).

Eng, C., Liu, Y. & Bhatnagar, R.

Br. J. Dermatol. (2019). readcube

by Yossi Matias & Ehud Rivlin

Google Research Blog | 5-Aug-2021

by Robin Suchan

Verily Press | 5-Aug-2021

by Daniel Freedman & Ehud Rivlin

Google Research Blog | 28-Aug-2020

Golany, T., Aides, A., Freedman, D., Rabani, N., Liu, Y., Rivlin, E., Corrado, G. S., Matias, Y., Khoury, W., Kashtan, H. & Reissman, P.

Surg. Endosc. (2022).

Livovsky, D. M., Veikherman, D., Golany, T., Aides, A., Dashinsky, V., Rabani, N., Ben Shimol, D., Blau, Y., Katzir, L., Shimshoni, I., Liu, Y., Segol, O., Goldin, E., Corrado, G., Lachter, J., Matias, Y., Rivlin, E. & Freedman, D.

Gastrointest. Endosc. (2021).

Freedman, D., Blau, Y., Katzir, L., Aides, A., Shimshoni, I., Veikherman, D., Golany, T., Gordon, A., Corrado, G., Matias, Y. & Rivlin, E.

IEEE Trans. Med. Imaging 1–1 (2020).

Epidemiological Forecasting

by Joel Shor & Sercan Arik

by Tomas Pfister

Google Cloud Blog | 15-Nov-2020

by Dario Sava

Google Cloud Blog | 3-Aug-2020

Tsai, T. C., Arik, S., Jacobson, B. H., Yoon, J., Yoder, N., Sava, D., Mitchell, M., Graham, G. & Pfister, T.

NPJ Digit Med 5, 59 (2022).

Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., Gerding, A., Gneiting, T., House, K. H., Huang, Y., Jayawardena, D., Kanji, A. H., Khandelwal, A., Le, K., Mühlemann, A., Niemi, J., Shah, A., Stark, A., Wang, Y., Wattanachit, N., Zorn, M. W., Gu, Y., Jain, S., Bannur, N., Deva, A., Kulkarni, M., Merugu, S., Raval, A., Shingi, S., Tiwari, A., White, J., Abernethy, N. F., Woody, S., Dahan, M., Fox, S., Gaither, K., Lachmann, M., Meyers, L. A., Scott, J. G., Tec, M., Srivastava, A., George, G. E., Cegan, J. C., Dettwiller, I. D., England, W. P., Farthing, M. W., Hunter, R. H., Lafferty, B., Linkov, I., Mayo, M. L., Parno, M. D., Rowland, M. A., Trump, B. D., Zhang-James, Y., Chen, S., Faraone, S. V., Hess, J., Morley, C. P., Salekin, A., Wang, D., Corsetti, S. M., Baer, T. M., Eisenberg, M. C., Falb, K., Huang, Y., Martin, E. T., McCauley, E., Myers, R. L., Schwarz, T., Sheldon, D., Gibson, G. C., Yu, R., Gao, L., Ma, Y., Wu, D., Yan, X., Jin, X., Wang, Y.-X., Chen, Y., Guo, L., Zhao, Y., Gu, Q., Chen, J., Wang, L., Xu, P., Zhang, W., Zou, D., Biegel, H., Lega, J., McConnell, S., Nagraj, V. P., Guertin, S. L., Hulme-Lowe, C., Turner, S. D., Shi, Y., Ban, X., Walraven, R., Hong, Q.-J., Kong, S., van de Walle, A., Turtle, J. A., Ben-Nun, M., Riley, S., Riley, P., Koyluoglu, U., DesRoches, D., Forli, P., Hamory, B., Kyriakides, C., Leis, H., Milliken, J., Moloney, M., Morgan, J., Nirgudkar, N., Ozcan, G., Piwonka, N., Ravi, M., Schrader, C., Shakhnovich, E., Siegel, D., Spatz, R., Stiefeling, C., Wilkinson, B., Wong, A., Cavany, S., España, G., Moore, S., Oidtman, R., Perkins, A., Kraus, D., Kraus, A., Gao, Z., Bian, J., Cao, W., Lavista Ferres, J., Li, C., Liu, T.-Y., Xie, X., Zhang, S., Zheng, S., Vespignani, A., Chinazzi, M., Davis, J. T., Mu, K., Pastore Y Piontti, A., Xiong, X., Zheng, A., Baek, J., Farias, V., Georgescu, A., Levi, R., Sinha, D., Wilde, J., Perakis, G., Bennouna, M. A., Nze-Ndong, D., Singhvi, D., Spantidakis, I., Thayaparan, L., Tsiourvas, A., Sarker, A., Jadbabaie, A., Shah, D., Della Penna, N., Celi, L. A., Sundar, S., Wolfinger, R., Osthus, D., Castro, L., Fairchild, G., Michaud, I., Karlen, D., Kinsey, M., Mullany, L. C., Rainwater-Lovett, K., Shin, L., Tallaksen, K., Wilson, S., Lee, E. C., Dent, J., Grantz, K. H., Hill, A. L., Kaminsky, J., Kaminsky, K., Keegan, L. T., Lauer, S. A., Lemaitre, J. C., Lessler, J., Meredith, H. R., Perez-Saez, J., Shah, S., Smith, C. P., Truelove, S. A., Wills, J., Marshall, M., Gardner, L., Nixon, K., Burant, J. C., Wang, L., Gao, L., Gu, Z., Kim, M., Li, X., Wang, G., Wang, Y., Yu, S., Reiner, R. C., Barber, R., Gakidou, E., Hay, S. I., Lim, S., Murray, C., Pigott, D., Gurung, H. L., Baccam, P., Stage, S. A., Suchoski, B. T., Prakash, B. A., Adhikari, B., Cui, J., Rodríguez, A., Tabassum, A., Xie, J., Keskinocak, P., Asplund, J., Baxter, A., Oruc, B. E., Serban, N., Arik, S. O., Dusenberry, M., Epshteyn, A., Kanal, E., Le, L. T., Li, C.-L., Pfister, T., Sava, D., Sinha, R., Tsai, T., Yoder, N., Yoon, J., Zhang, L., Abbott, S., Bosse, N. I., Funk, S., Hellewell, J., Meakin, S. R., Sherratt, K., Zhou, M., Kalantari, R., Yamana, T. K., Pei, S., Shaman, J., Li, M. L., Bertsimas, D., Skali Lami, O., Soni, S., Tazi Bouardi, H., Ayer, T., Adee, M., Chhatwal, J., Dalgic, O. O., Ladd, M. A., Linas, B. P., Mueller, P., Xiao, J., Wang, Y., Wang, Q., Xie, S., Zeng, D., Green, A., Bien, J., Brooks, L., Hu, A. J., Jahja, M., McDonald, D., Narasimhan, B., Politsch, C., Rajanala, S., Rumack, A., Simon, N., Tibshirani, R. J., Tibshirani, R., Ventura, V., Wasserman, L., O’Dea, E. B., Drake, J. M., Pagano, R., Tran, Q. T., Ho, L. S. T., Huynh, H., Walker, J. W., Slayton, R. B., Johansson, M. A., Biggerstaff, M. & Reich, N. G.

Proc. Natl. Acad. Sci. U. S. A. 119, e2113561119 (2022).

Arık, S. Ö., Shor, J., Sinha, R., Yoon, J., Ledsam, J. R., Le, L. T., Dusenberry, M. W., Yoder, N. C., Popendorf, K., Epshteyn, A., Euphrosine, J., Kanal, E., Jones, I., Li, C.-L., Luan, B., Mckenna, J., Menon, V., Singh, S., Sun, M., Ravi, A. S., Zhang, L., Sava, D., Cunningham, K., Kayama, H., Tsai, T., Yoneoka, D., Nomura, S., Miyata, H. & Pfister, T.

NPJ Digit Med 4, 146 (2021).

Kapoor, A., Ben, X., Liu, L., Perozzi, B., Barnes, M., Blais, M. & O’Banion, S.

Arik, Li, Yoon, Sinha, Epshteyn, Le, Menon, Singh, Zhang, Nikoltchev, Sonthalia, Nakhost, Kanal & Pfister.

Adv. Neural Inf. Process. Syst. 2020.

Eye Diseases

by Michelle Budzyna & Molly McHugh-Johnson

Google Keyword Blog | 27-Sep-2023

by Kasumi Widner

Google Keyword Blog | 30-May-2023

by Angus Turner

Google Australia Blog | 7-Mar-2023

by Emma Beede

Google Keyword Blog | 25-Apr-2020

by Kasumi Widner & Sunny Virmani

Google Keyword Blog | 25-Feb-2019

Verily Blog | 25-Feb-2019

by Rory Sayres & Jonathan Krause

Google Research Blog | 13-Dec-2018

by Mustafa Suleyman

DeepMind Blog | 13-Aug-2018

by Lily Peng

Google Keyword Blog | 29-Nov-2016

by Lily Peng & Varun Gulshan

Google Research Blog | 29-Nov-2016

Bora, A., Tiwari, R., Bavishi, P., Virmani, S., Huang, R., Traynis, I., Corrado, G. S., Peng, L., Webster, D. R., Varadarajan, A. V., Pattanapongpaiboon, W., Chopra, R. & Ruamviboonsuk, P.

Transl. Vis. Sci. Technol. 12, 11 (2023).

Widner, K., Virmani, S., Krause, J., Nayar, J., Tiwari, R., Pedersen, E. R., Jeji, D., Hammel, N., Matias, Y., Corrado, G. S., Liu, Y., Peng, L. & Webster, D. R.

Nat. Med. 1–3 (2023). [readcube]

Srisubat, A., Kittrongsiri, K., Sangroongruangsri, S., Khemvaranan, C., Shreibati, J. B., Ching, J., Hernandez, J., Tiwari, R., Hersch, F., Liu, Y., Hanutsaha, P., Ruamviboonsuk, V., Turongkaravee, S., Raman, R. & Ruamviboonsuk, P.

Ophthalmol Ther (2023).

Chia, M. A., Hersch, F., Sayres, R., Bavishi, P., Tiwari, R., Keane, P. A. & Turner, A. W.

Br. J. Ophthalmol. (2023).

Ruamviboonsuk, P., Tiwari, R., Sayres, R., Nganthavee, V., Hemarat, K., Kongprayoon, A., Raman, R., Levinstein, B., Liu, Y., Schaekermann, M., Lee, R., Virmani, S., Widner, K., Chambers, J., Hersch, F., Peng, L. & Webster, D. R.

The Lancet Digital Health (2022).

Pedersen Elin Rønby, Cuadros Jorge, Khan Mahbuba, Fleischmann Sybille, Wolff Gregory, Hammel Naama, Liu Yun & Leung Geoffrey.

NEJM Catalyst (2021).

Wilson, M., Chopra, R., Wilson, M. Z., Cooper, C., MacWilliams, P., Liu, Y., Wulczyn, E., Florea, D., Hughes, C. O., Karthikesalingam, A., Khalid, H., Vermeirsch, S., Nicholson, L., Keane, P. A., Balaskas, K. & Kelly, C. J.

JAMA Ophthalmol. (2021).

Limwattanayingyong, J., Nganthavee, V., Seresirikachorn, K., Singalavanija, T., Soonthornworasiri, N., Ruamviboonsuk, V., Rao, C., Raman, R., Grzybowski, A., Schaekermann, M., Peng, L. H., Webster, D. R., Semturs, C., Krause, J., Sayres, R., Hersch, F., Tiwari, R., Liu, Y. & Ruamviboonsuk, P.

Journal of Diabetes Research, 1–8 (2020).

Hsu J, Phene S, Mitani A, Luo J, Hammel N, Krause J, Sayres R.

in ACM-CHIL [arXiv] (2020)

Bresnick, G., Cuadros, J. A., Khan, M., Fleischmann, S., Wolff, G., Limon, A., Chang, J., Jiang, L., Cuadros, P. & Pedersen, E. R.

BMJ Open Diabetes Research and Care 8, e001154 (2020).

Beede, E., Baylor, E., Hersch, F., Iurchenko, A., Wilcox, L., Ruamviboonsuk, P. & Vardoulakis, L. M.

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems 1–12. Association for Computing Machinery (2020).

Schaekermann, M., Cai, C. J., Huang, A. E. & Sayres, R.

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems 1–13. Association for Computing Machinery (2020).

Phene, S., Dunn, R. C., Hammel, N., Liu, Y., Krause, J., Kitade, N., Schaekermann, M., Sayres, R., Wu, D. J., Bora, A., Semturs, C., Misra, A., Huang, A. E., Spitze, A., Medeiros, F. A., Maa, A. Y., Gandhi, M., Corrado, G. S., Peng, L. & Webster, D. R.

Ophthalmology 126, 1627–1639 (2019).

Schaekermann, M., Hammel, N., Terry, M., Ali, T. K., Liu, Y., Basham, B., Campana, B., Chen, W., Ji, X., Krause, J., Corrado, G. S., Peng, L., Webster, D. R., Law, E. & Sayres, R.

Transl. Vis. Sci. Technol. 8, 40 (2019).

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Open Health Stack

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Open Health Stack Blog | 2-Sep-2023.

by Abirami Sukumaran & Omar Ismail

Google Cloud Blog | 17-Aug-2023.

by Fred Hersch

Google Keyword Blog | 14-Mar-2023.

by Katherine Chou & Sudhi Herle

Android Developers Blog | 24-Mar-2022

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Mehl, G. L., Seneviratne, M. G., Berg, M. L., Bidani, S., Distler, R. L., Gorgens, M., Kallander, K. E., Labrique, A. B., Landry, M. S., Leitner, C., Lubell-Doughtie, P. B., Marcelo, A. D., Matias, Y., Nelson, J., Nguyen, V., Nsengimana, J. P., Orton, M., Otzoy Garcia, D. R., Oyaole, D. R., Ratanaprayul, N., Roth, S., Schaefer, M. P., Settle, D., Tang, J., Tien-Wahser, B., Wanyee, S. & Hersch, F.

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Nature Portfolio Health Community Blog | 10-May-2023

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Google Research Blog | 14-Mar-2023

Google Cloud Blog | 12-Dec-2022

Verily Blog | 16-Mar-2022

by Po-Hsuan Cameron Chen & Maggie Demkin

Google Research Blog | 11-Feb-2022

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Google Keyword Blog | 23-Sept-2021

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Google Cloud Blog | 2-Sep-2020

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Google Keyword Blog | 23-Jul-2020

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Google Research Blog | 19-July-2019

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Google Research Blog | 12-Oct-2018

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Public & Environmental Health

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Google Research Blog | 12-Nov-2019

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• Research article
• Open access
• Published: 01 December 2006

Describing the impact of health research: a Research Impact Framework

• Shyama Kuruvilla 1 ,
• Nicholas Mays 2 ,
• Andrew Pleasant 3 &
• Gill Walt 4  

BMC Health Services Research volume  6 , Article number:  134 ( 2006 ) Cite this article

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Researchers are increasingly required to describe the impact of their work, e.g. in grant proposals, project reports, press releases and research assessment exercises. Specialised impact assessment studies can be difficult to replicate and may require resources and skills not available to individual researchers. Researchers are often hard-pressed to identify and describe research impacts and ad hoc accounts do not facilitate comparison across time or projects.

The Research Impact Framework was developed by identifying potential areas of health research impact from the research impact assessment literature and based on research assessment criteria, for example, as set out by the UK Research Assessment Exercise panels. A prototype of the framework was used to guide an analysis of the impact of selected research projects at the London School of Hygiene and Tropical Medicine. Additional areas of impact were identified in the process and researchers also provided feedback on which descriptive categories they thought were useful and valid vis-à-vis the nature and impact of their work.

We identified four broad areas of impact:

I. Research-related impacts;

II. Policy impacts;

III. Service impacts: health and intersectoral and

IV. Societal impacts.

Within each of these areas, further descriptive categories were identified. For example, the nature of research impact on policy can be described using the following categorisation, put forward by Weiss:

Instrumental use where research findings drive policy-making;

Mobilisation of support where research provides support for policy proposals;

Conceptual use where research influences the concepts and language of policy deliberations and

Redefining/wider influence where research leads to rethinking and changing established practices and beliefs.

Researchers, while initially sceptical, found that the Research Impact Framework provided prompts and descriptive categories that helped them systematically identify a range of specific and verifiable impacts related to their work (compared to ad hoc approaches they had previously used). The framework could also help researchers think through implementation strategies and identify unintended or harmful effects. The standardised structure of the framework facilitates comparison of research impacts across projects and time, which is useful from analytical, management and assessment perspectives.

Researchers are increasingly, and regularly, requested to describe the impact of their work in:

Grant proposals, especially sections on research users, beneficiaries, communication and expected impact;

Research project evaluations and reports, particularly to provide accountability for funds invested in research;

Publicity information e.g. for institutional annual reports and press releases that highlight "success stories";

Research dissemination and implementation strategies;

Assessments of the impact of research on policy, practice and public opinion;

Individual and institutional research assessment exercise (RAE) submissions.

However, researchers are often hard-pressed to come up with coherent and comprehensive narratives of actual or potential research impacts and produce ad hoc accounts that do not facilitate comparison across time or learning across cases. More specialised research impact assessment studies can be difficult to replicate and may require resources and skills not available to individual researchers [ 1 , 2 ]. Further, the specialised focus of these models, for example on publications and economic benefits, may not cover a range of other areas where research could have impact. For example with regards to health research, environmental effects and social capital are increasingly associated with health outcomes and are areas where research can have impact [ 3 – 5 ], but are often neglected in existing health research impact assessment models and frameworks. A research impact scoping exercise at the London School of Hygiene and Tropical Medicine (LSHTM) identified some additional areas in which health research can have impact, such as on policy networks and on other sectors such as energy, that are also often missing in existing frameworks and models of health research impact [ 6 ].

In this paper we take a practical approach to help researchers describe the impact of their work. We present the Research Impact Framework , which is designed as a 'DIY' approach with descriptive categories that prompt researchers to systematically think through and describe the impact of their work. The framework was also designed with some additional goals in mind: to develop a standardised framework to help describe impacts across research topics and methods and facilitate comparison across time and cases; to guide researchers in planning research implementation and evaluation strategies; to facilitate researchers in looking at the broader influences and effects on and of their work in society; to promote research accountability in relation to the use of resources and the consequences of research; to help in the attribution of effects to health research given the range of other determinants of health and societal impacts; and to contribute to more extensive or specialised evaluations of research impact.

Researchers' narratives of the impact of their work could also serve as building blocks for a variety of more specialised analytical purposes. For example, researchers' accounts are considered a starting point for more specialised research impact assessments and can provide similar findings, though the level of detail and analysis may differ [ 7 ]. In analysing the role of research in diffusion of innovations, Greenhalgh et al. [ 8 ] found that "researchers in different traditions had conceptualised, explained and investigated diffusion of innovations differently and had used different criteria for judging the quality of empirical work. Moreover, they told very different over-arching stories of the progress of their research." Thus researchers' narratives also facilitate analysis of differences in the 'doing', diffusion and impact of research within and across research fields [ 8 ].

While the Research Impact Framework provides a simple, practical approach to developing research impact narratives, it is important to recognise that these narratives are generated and assessed in the context of historically rich and complex, often contending, views on the role of science and its relationship with society. Some may align with Bacon's [ 9 ] utopian vision wherein wise and benevolent rulers coordinate and disseminate research for the good of the state. Others take a 'Republic of Science' view, espoused by Polyani [ 10 ] and Vannevar Bush [ 11 ], where science is idealised as an independent enterprise, separate from societal concerns and having intrinsic value in and of itself. However, researchers on the sociology of scientific knowledge posit that science and society are interlinked and mutually influential [ 12 , 13 ]. Further, Kuhn [ 14 ] and Callon [ 15 ] among others, discuss how science itself is a social enterprise with researchers interacting within specific scientific cultures and communities.

There may also be different types of impact expected from different types of research, for example basic, applied, action, clinical, user driven, translational or curiosity-driven research. Then there are contesting and complementary theories and models of causal pathways of research impacts associated with different levels and types of impact on research, policy and practice [ 16 – 19 ]. Several academic disciplines including communication, diffusion of innovation studies, policy science, sociology of scientific knowledge and organisational research all offer valuable perspectives on different aspects of assessing the production, communication, utilisation and impact of research [ 20 ]

Further considerations in describing research impacts include questions of accountability, for example, whether there is a different standard of accountability for researchers compared with practitioners with regards to impact [ 21 ]. There are also concerns about whether research impacts are positive or negative (and for whom) and what individual or institutional biases and incentives may operate in describing impact. Prioritisation of impact is another assessment issue, though priorities may vary in accordance with different funders' priorities, in different research fields and in different socio-political contexts.

Researchers may variously ascribe to different worldviews and may take into account various assessment considerations, either knowingly or unknowingly, when describing the impact of their work. However, the Research Impact Framework presented in this paper is not aligned with any particular philosophy, is not in itself evaluative and does not prioritise impacts or propose causal pathways. The Research Impact Framework was primarily designed as a practical tool to help researchers think through and describe the impact of their work; this could then serve a range of practical and analytical purposes as required.

While much of the framework presented in this paper could apply to research impact narratives in general, specific considerations warrant a topical focus on health research, which is defined as "the generation of new knowledge using the scientific method to identify and deal with health problems" [ 22 ]. While health research is nested within the larger science and technology enterprise, there are a multitude of social, governmental, academic, service, manufacturing and legal institutions specifically in place to deliver the products of health research to society [ 23 ]. Further, a systematic review on the diffusion of innovations, including research, emphasized the need for "building up a rich picture of process and impact" in health services [ 24 ].

To address the gaps in existing approaches to and models of health research impact assessments, we first drew from the literature on health research impact assessment models and criteria to map out a framework of health research impacts. This framework was then tested and modified against impacts identified by LSHTM researchers working on a wide range of health research topics. Using the Research Impact Framework allowed individual researchers to identify and select impacts relevant to their work and develop impact narratives without requiring specialised skill in the field of research impact assessment. The standardised descriptive categories also facilitated analysis across the narratives. The methods used to develop the Research Impact Framework are described in the following section.

Our objective was to develop a conceptual framework to help health researchers think through and describe the possible outcomes of their work. A framework is a way of setting out a range of possible variables related to the issue of interest, but does not necessarily identify the relationships between them [ 25 ] or provide an evaluative judgement of the variables. For example, the fallout from the controversy of research linking the MMR vaccine with autism received substantial coverage in scientific journals and in the media and had various adverse effects such as a drop in immunisation rates [ 21 ]; a framework would include these areas of impact, but would not evaluate the nature of this impact. We developed a conceptual framework that covered a wide range of potential areas of health research impact, and standardised ways of describing them, so that individual researchers without any specific training in research impact assessment could use the framework to describe the impact of their work, selecting descriptive categories as per relevant purposes, priorities and assessment criteria.

To develop the Research Impact Framework, we first mapped out potential research impact areas based on a review of the main health research impact assessment approaches. The goal was not to conduct an exhaustive review of the literature, or to analyse the causal claims of different impact assessment models, but only to identify and map out the scope and coverage of potential areas of health research impact across a range of models, frameworks and criteria. The approaches we drew on to map the health research impact areas, and there were was overlap between them, were the Payback Model of health research benefits [ 18 ], a framework to analyse Health Research Systems [ 23 ], a 'knowledge transfer' approach to assessing the impact of research [ 26 ], a model of the path from evidence generation to clinical application [ 27 ] as well as economic approaches to assessing health research impact, such as the Funding First approach, which includes calculations of the economic value of increased life expectancy resulting from investments in research [ 28 ]. We also drew on frameworks that did not explicitly focus on health research, but explicated the links between globalization and health [ 3 ], pathways of communication and social change [ 29 ] outcomes of health promotion [ 30 ] and the non-financial constraints in health systems [ 31 ] as these are all areas where health research potentially could have impact. Research assessment criteria, for example, as proposed in the OECD's Oslo Manual [ 32 ], criteria for the initiation and evaluation of National Institutes for Health (NIH) Extramural Center Programs [ 33 ] and the UK Research Assessment Exercise [ 34 ], further informed the development of the Research Impact Framework by highlighting contemporaneous criteria against which the significance and impact of research are judged.

We turned this initial mapping of potential research impact areas into a semi-structured interview guide, designed to be used in interviews with researchers to develop narratives, or case studies of research impact (See Table 1 ). LSHTM-based projects were purposefully selected for maximum variation [ 35 ] with reference to project topics and with regards to the familiarity of the principal investigators with research impact assessment concepts. The study was initially developed in the Department of Public Health and Policy (PHP) at LSHTM and included primary analysis of the impact of seven research health services and policy research projects and secondary analysis of four other research projects based on impact assessments previously conducted [ 6 ]. These projects covered a wide range of topics: health care financing reform, bilingual young people's agency in facilitating health care access for their families, climate change and health, primary care-led commissioning in the NHS, a clinical audit of sino-nasal surgery, epidemiological analysis of cold-related morbidity and mortality, the public health implications of the trafficking of women and adolescents, the UK National Prospective Tonsillectomy Audit and HIV/AIDS-related research [ 6 ]. The study was then expanded beyond PHP to further develop the Research Impact Framework based on analysis of four 'basic' or 'technical' research projects selected from the departments of Epidemiology and Public Health (EPH) and Infectious and Tropical Disease (ITD). These research projects focused on insecticide treated bed nets to prevent malaria, handwashing with soap to prevent diarrhoeal diseases, morbidity and mortality related to road traffic injuries, and the use of epidemiological methods in genomics research.

The principal investigators (or LSHTM focal points in collaborative projects) of the selected research projects were interviewed using the semi-structured interview guide that was structured according to the mapping of research impact areas (See Table 1 ). Principal investigators were selected as the main interviewees because they were primarily responsible for drawing up descriptions of research impact in grant proposals as well as in final project reports. In addition, LSHTM colleagues whose expertise included research impact assessment as well as the heads of the research units were interviewed, not on the substance of the individual projects per se, but on the development of the Research Impact Framework. One investigator conducted all the interviews that took around 45 minutes each, and took contemporaneous notes. Information was also gathered from research project documents including reports, published papers and correspondence. The data were analysed based on a thematic analysis using the descriptive categories of the framework as the main themes.

This process helped to both test and further develop the framework, for example, through the identification of additional areas of impact, such as intersectoral services related to vector control, road safety and climate change, that were not included in the initial mapping based on the literature review alone. These data were used to further develop and refine the initial mapping of health research impact areas to produce a final version of the Research Impact Framework (See Table 2 ).

Within each impact area in the Research Impact Framework, we also identified descriptive categories in the literature, discussed in following sections, to support and help standardise the development of research impact narratives to enable comparative analysis across projects. Through an iterative and consultative process with LSHTM researchers involved in the selected projects, we determined which terms and categories were most useful to help researchers structure narratives of research impact.

The Research Impact Framework was thus validated through congruence with the literature on health research impact assessment, as well as through empirical analysis of research projects. Researchers in the LSHTM study found the approach more systematic than the more usual ad hoc and guess work-based process. The framework also provided new perspectives on potential and actual health research impacts and allowed for comparison of impact and assessment-related issues across the selected projects [ 6 ].

In this paper, the Research Impact Framework is presented, including the main health research impact areas and the descriptive categories within them. Examples from the LSHTM study and from the research impact assessment literature are used to illustrate key points.

Results: the Research Impact Framework

We identified four broad areas to structure a framework of health research impacts, based on a literature review as well as an empirical analysis of selected LSHTM research projects:

Research-related impacts

Policy impacts

Services impacts: health and intersectoral

Societal impacts

Within each of these areas, key descriptive categories were identified (See Table 2 ). By listing this broad range of health research impact areas, we do not propose that all these impacts should be expected or targeted all the time. Neither do we suggest that these are necessarily mutually exclusive categories. Rather, the framework offers an overview of potential, and sometimes overlapping, research impact areas that can serve as a series of prompts or a checklist that researchers can select from or modify, as appropriate to the research being described and taking into account, for example, funders' priorities or research assessment criteria.

I. Research-related impacts

Research can have impacts within the research field itself that can be described using the following categories:

Type of problem/knowledge

Research methods

Publications and papers, products, patents and translatability potential.

Research networks

• Leadership and awards

Research management

Communication

Type of problem/knowledge addressed.

The type of problems addressed and knowledge generated through research are primary areas in which to describe impact. The following adaptation of a categorization by Nutley, Walter and Davies [ 16 ] helps think through this area of research impact and research projects may address more than one of these categories.

Data about a problem/phenomenon: e.g. statistics and trends showing declining vulnerability to temperature-related mortality in London over the 20th century [ 36 ].

Definitions and concepts: e.g. the concept of equity in health care financing.

Rationale for action/possible solutions: e.g. rationale for health promotion strategies based on evidence that hand washing with soap helps prevent diarrhoeal diseases [ 37 ].

Evidence of effectiveness of interventions: e.g. through clinical audits of different surgical techniques.

Information on how to implement solutions: e.g. methods to promote the purchase and treatment of bed nets with insecticide by communities themselves, an effective, equitable and sustainable strategy to prevent malaria [ 38 – 40 ].

New research topics in a field: e.g. public health research has been extended to topics such as the public health implications of climate change [ 41 ] or road traffic injuries [ 42 ] and new knowledge on the determinants of health is continually produced.

Addressing research gaps and testing new hypotheses: e.g. gaps in existing research can be identified through systematic reviews of the literature on a topic and studies may be designed to address these gaps or to test new hypotheses.

Ethical debates and guidelines: e.g. the development of new ethical guidelines for research on violence against women [ 43 ].

Responsiveness/public interest: e.g. research responding to topics of public interest or on government and media agendas, such as research on obesity or teenage pregnancy; or research that contributes to issues becoming topical in the media or in policy and analysis of the same.

This area of impact covers the mode of research employed or a researcher's methodological contribution to the overall study. Knowledge evolves along a continuum that ranges from applying models that have worked elsewhere to trying out something completely new [ 16 ]. Thus, in addition to describing the actual methods used (e.g. survey research, face-to-face interviews, case studies, multi-variate analysis) categories to describe methodological impact include:

Replication of a study.

Application of established methods.

Further development / extension of methods, such as the application of Bayesian modeling techniques in emerging genomics research to study genotype-phenotype associations around a causative site, including relative risk of a causative allele and mode of inheritance [ 44 ].

Innovation in terms of developing new research methods, for example, new methods for accessing "hard-to-reach" groups, and the use of new technologies such as GIS in research.

Synthesis of research involves review and appraisal across several research projects and can help determine whether theories are adequately tested before applying them to practice and policy, indicates if resources are being wasted on new research on topics previously and conclusively studied, facilitates analysis of new evidence in the context of previous evidence, and highlights gaps in current knowledge. There are a variety of methods used to synthesise diverse forms of qualitative and quantitative evidence, for example systematic reviews as set out by the Cochrane [ 45 ] and Campbell Collaborations [ 46 ]; methodological development in the area of research synthesis is ongoing [ 47 ].

This is the perhaps most familiar part of the framework for researchers, as the impact of research is commonly described based on publications, in tenure and performance reviews to research utilisation analysis and research assessment exercised, using measures such as [ 33 , 34 , 48 ]:

Publications in scientific journals and the 'impact factors' of the journals

Technical reports , project reports, position statements etc, which while often considered as 'grey literature', can sometimes be more rigorously peer-reviewed than scientific publications and are widely read.

Citations of research publications by other researchers.

Products and processes . The OECD Oslo Manual [ 32 ] classifies technological innovation as comprising:

◦ Introduction of a new product

◦ Qualitative change in an existing product, for example improved technologies, sometimes referred to as 'better mousetrap' solutions

◦ Process innovation that is new to an industry

◦ Opening of a new market

◦ Development of new sources of supply for raw materials or other inputs; and changes in industrial organisation.

Other specific examples of research products include vaccines and drugs, decision algorithms, mathematical models, information tools and resources e.g. geographical information systems; training manuals, databases, health education materials etc.

Patents of research information or products and citations of patents by other researchers, are another area of potential research impact [ 32 ]. For example, an analysis of citations of U.S. industry patents showed a strong national linkage with "each country's inventors preferentially citing papers authored in their own country, by a factor of between two and four" [ 49 ].

Commercial development of scientifically developed products including commercial licences and spin off companies. This may also include the influence of research on product development and marketing processes [ 32 ].

Translatability potential of research refers to the potential for the translation of research findings, particularly in basic science, to clinical applications [ 33 ] or to technological opportunities and outcomes [ 32 ]. Indicators of translatability potential include publications in clinically oriented journals, patent applications, licenses issued and clinical trials underway or completed [ 33 ]. The term is also used to discuss the extent to which the research can be applied in other study contexts as well as in other disciplinary fields. This area of research impact is receiving increased attention as new, and at times controversial, partnerships between industry and business, government and non-governmental organizations and university-based research units and researchers continue to develop [ 50 ].

Research networks and user involvement

Developing and maintaining research collaborations as well as client and user involvement in research are increasingly desired goals as they are seen to increase the reach, responsiveness, relevance, dissemination and impact of research [ 19 , 51 , 52 ]. Research partnerships usually involve researchers, research groups and institutes who jointly submit a research grant application, for example, and work together on a research project. Other partners as well as potential research clients and users may be involved at various stages of the research process from ethics review processes to research commissioning, collaborative research and project evaluation. For example, the Canadian Health Services Research Foundation specifically focuses on building 'linkage and exchange' between researchers and policy-makers in research priority setting, funding, proposal assessment and in the conduct and communication of research, in order to enhance the utilisation and impact of research on policy as well as to evaluate this impact [ 53 ]. Listing research collaborators, other partners, clients and users, as well as their specific involvement in the research, provides a useful description of this area of research impact.

Research leadership

Leadership in research, is often a key area of interest in research assessment exercises [ 34 ] and may be related to a specific project or to a body of work. Research leadership can be documented by referring to:

Role in setting the agenda or standards for a field of research or setting out a vision for the same.

Leadership in coordinating and managing research projects and multi-institutional research collaborations.

Public recognition of leadership including prestigious fellowships, named lectures and keynote addresses, awards that mark significant achievement in research, or membership in honorary scientific societies.

Membership of regional, national or international research bodies , review boards and funding bodies.

Editorship of journals or membership on journal editorial boards and advisory committees.

Research system management

A health research system is defined as the people, institutions, networks and activities whose primary purpose is to generate, communicate and promote the utilization of scientifically validated knowledge that can be used to enhance, restore and/or maintain the health status of populations [ 23 ]. Research can have an impact on research system management by:

Expanding health research system linkages for multidisciplinary and cross-sectoral research [ 33 ]. For example, the advantages of coordinating health and environmental impact assessments are increasingly recognized [ 54 ].

Changing research priority setting, investment strategies, resource allocation and accounting processes . Research can highlight gaps in resource allocation for research, for example in relation to health research priorities and in terms of equitable allocation of research resources to address the needs of different populations [ 33 , 55 ].

Developing capacities to conduct research and providing opportunities for training and development of researchers [ 23 , 33 , 56 ].

Changing the research environment in relation to working conditions, incentives, job retention rates, recruiting and retaining women in science and overall researcher satisfaction [ 23 , 33 ].

Influencing health research system performance and assessing comparative advantages of different research systems [ 23 , 32 ].

Studies have long shown that researchers feel handicapped in their involvement in research communication due to lack of time, resources and incentives and that research is disseminated mainly through existing networks within the scientific community [ 52 ]. This is not only due to limited capacity, but also because the 'popularisation' of research has been perceived to be in conflict with the norms and standards of science [ 57 ]. These findings were reflected in the LSHTM study as well [ 6 ]. Nevertheless, as found in the LSHTM study, researchers do employ various modes of research dissemination, often on their own initiative. Potential target audiences and modes of dissemination for research are listed below.

Target audiences

Academic/research institutions and programmes

Donor government/bilateral agencies (e.g. DFID, USAID)

Public/consumer organisations and groups

Government offices/agencies

Health insurance organizations

Hospitals and clinics, practising physicians, nurses, allied health professionals etc.

International organisations (e.g. UN, WHO, World Bank)

Media and entertainment groups

Non-governmental organisations (NGOs)

Other private sector companies/institutes

Pharmaceutical companies

Professional associations

Research funding councils/foundations/charities

Other research networks e.g. with more informal structures, sometimes termed epistemic communities [ 58 ]

Modes of research dissemination and implementation strategies [ 16 , 59 ]

Audit and feedback processes

Books: textbooks; technical; 'popular'

Conferences and workshops

Decision aids/algorithms/computer reminder systems

E-mail/list serve discussions

Face-to-face interaction/meetings

Films, documentaries

Health education and health promotion

Incentive systems (financial/professional) for use of research products

Interventions targeting health that apply research findings, for example social marketing of soap to promote hand washing and prevent diarrhoeal disease

Mass media: press releases and newspapers – articles and op eds; television; radio; magazine; and Internet

Opinion leaders

Organisational/systems-level strategies

Policy briefs/recommendations

Public engagement activities

Formal academic talks/presentations

Translation of research for different users

Beyond listing of research communication activities, specific impacts of research communication could also be usefully described [ 29 ], for example in curricular use or media coverage as described below.

Curricular/educational use

The use of research findings and papers in educational curricula and courses is a key area of research impact [ 19 ]. In the LSHTM study, researchers noted as impacts in this area feedback from other researchers and institutions about the inclusion of publications on the selected research projects in course curricula or being invited as guest speakers on courses.

Media coverage

Research effects relating to media coverage include [ 60 , 61 ]:

Media coverage on a research project's findings; descriptive details including dates and any attribution or mention of a particular research project or researcher.

The nature of the coverage in terms of scientific accuracy and whether the research was viewed favourable or unfavourably; e.g. using headlines or quotes to illustrate the nature of media coverage.

Media coverage of individual researchers, e.g. their work, profile or personality; including whether researchers are depicted as being average everyday individuals or somehow different than the social norm; i.e. whether scientists are considered part of society or separate from it.

The long-term trends in covering health research in the mass media; e.g. the extent individual researchers are used as sources of information in the media, the position of health research within the news agenda; and the representation of health research and researchers in entertainment content.

II. Policy impacts

Increasingly, one of the main objectives of health research is to inform and influence policy and there are several potential impacts in this area:

Level of policy-making

Type of policy.

Nature of policy impact

Policy networks

Political capital.

Research can have an impact on policy-making at different levels and including different groups, for example, national and local politicians, health services administrators and managers/directors, representatives of local, national and international professional groups, NGOs and business leaders. In describing impact, the geopolitical level of policy impact, i.e. whether at international, national, or sub-national level, can be described as well as if the changes were localised to a particular organisation or network of organisations within those levels.

The type of policy influenced by research is another way that impact can be described. For example, Black [ 62 ] endorses a distinction made between: practice policies, service policies and governance policies. Type of policies may also be described in relation to particular types of policy institutions, for example, researchers in the LSHTM study discussed how findings on home temperature-related morbidity and mortality [ 63 ] were used in the UK parliament in support of the Housing Bill (2004). The publication of WHO guidelines on ethics related to research on women and adolescents who had been trafficked [ 43 ] that had been developed on the basis of a research project was cited another example of policy impact in the LSHTM study [ 6 ].

Nature of policy influence

There are several ways in which research can influence policy and Weiss (1998) identified four main modes of influence listed below [ 64 ]. There are a wide range of other categorisations of research to policy impact [ 65 ], including in Weiss's earlier work [ 17 ], describing rational, tactical and symbolic use of research in policy-making. In the LSHTM study, the following categories were found to be conceptually clear and relevant to policy impacts identified by researchers:

Instrumental use where research findings directly drive or define policy.

Mobilisation of support [supportive evidence] where research findings provide persuasive evidence to back ongoing and proposed policy activities or raise awareness and support for new policy-making, for example through writing policy briefs. As one LSHTM researcher noted, "Writing policy briefs gives us the opportunity to discuss the wider policy implications of our research and to anticipate and rehearse policy arguments ... Our work adds weight to policy deliberations." [ 6 ]

Conceptual use where research leads to new ideas and language that influence the nature and substance of policy discourse, for example the concept of equity is increasingly used in considerations of health care financing [ 66 , 67 ].

Redefining/wider influence refers to research impact that leads to a wide change or transformation of accepted beliefs and practices. This may involve overturning orthodoxies, as in the revolutionary shift in eighteenth century medical science from the concepts of vapours and humours to the constructs of anatomy and pathology [ 68 ]. More contemporary examples also indicate how research can lead to the changes in existing beliefs and practices. For instance, a multi-country randomised control trial found that widely accepted practice of administering corticosteroids after head injury could be harmful [ 69 ] with implications for both policy and practice on this topic.

In relation to a specific policy problem, networks of actors and institutions with particular interests and perspectives on that issue may pre-exist or form and interact in policy-making [ 70 ]. At times, these networks are referred to as epistemic communities and extend across normally disparate elements of research, policy, practice and the public, but are based on a common research-based understanding of the issue [ 63 ]. As with the dissemination of research through research networks, policy ideas and interests are often developed through policy networks. The extent to which researchers are part of, or inform, policy networks is, therefore, an important aspect of research impact. Collaborations with policy advocacy groups, think tanks and government institutions can be listed as part of this description. In the LSHTM study, researchers emphasised the importance of establishing networks that extended beyond the formal bureaucracy as "knowledge users include policy-makers as well as the range of civil society organisations." [ 6 ]

Research impact on political capital takes into account the value of research evidence and researchers themselves in policy negotiations, in reaching in high quality agreements and improvements to the policy-making process, in the ability in societies to achieve agreed-upon ends, in the socio-political prestige resulting from innovations, and in increased national security [ 71 ]. For example, research on negotiation and consensus building methods on health issues could contribute to improving the quality of deliberations and reaching agreements that are reliable and satisfactory to the parties involved [ 72 , 73 ].

III. Service impacts

The following categories help describe the impact of research on both health and intersectoral services.

Type of services: health/intersectoral

Evidence-based practice

Quality of care, information systems.

Services management

Cost-containment and cost-effectiveness

Type of services.

Health research, often primarily targeted at improving clinical and public health services, can have a range of impacts in this area that are detailed in the following sections on evidence based practice, quality of care, health information systems and on health services and systems management, including cost-effectiveness and cost-containment. Research on prevention and control measures for newly emerging diseases such as avian flu is another example of an area in which research can have an impact on health services [ 74 ].

In addition, health research can influence a range of other service sectors that contribute to public health. For example, in the LSHTM study researchers described how the WHO ethical guidelines, developed on the basis of a research project, for research on women and adolescents who were trafficked [ 43 ], were now being used to train journalists who conduct interviews on this topic and were also used in police training courses in several countries [ 6 ].

Living and work environments are associated with negative or positive effects on human health and are, therefore, critical areas for health research impact assessment [ 75 ]. For example, research on the health benefits of well-lit and safe places to work and exercise can contribute to reducing injury and promoting physical activity [ 76 ]. Impacts can also be described in the areas of measures undertaken, as a result of research, to reduce indoor and outdoor air pollution as well as in the use of more energy efficient devices [ 77 ].

Road traffic injuries are increasingly recognised as a major public health problem. Research could influence road safety and health, for example by highlighting issues for the regulation of vehicular use to facilitate safe walking and cycling, particularly for children [ 42 ] or by showing how the growth in sales of SUVs and pick-up trucks in the US contributed to a slower decline in road fatality rates there than in other industrialised countries [ 78 ].

Health research may also have an impact on vector control services, for example as related to studies on the cost-effectiveness of different types of insecticides to prevent malaria as well as on their safety for humans [ 39 ]. Additionally, clean drinking water and soil fertility are critically important to human health [ 79 ]. Thus, if applicable, research impact narratives could include descriptions of research impacts on food production and safety, water access and quality.

The impact of climate change and weather events on public health is another intersectoral area that is receiving increasing attention in health research. For example, in 2003, a heat wave resulted in numerous deaths across Europe, in France alone there were around 14,000 deaths [ 41 ]. This event raised the profile of climate change as a public health issue in Europe. Changes in forecasting and early warning systems as well as on related response mechanisms and guidelines, informed by research findings, are examples possible health research impacts in this area.

The use of research evidence by different groups involved in clinical diagnosis and decision-making is an indicator of research impact in health services [ 27 ]. Studies also indicate that in clinical decision-making and interviews between patients, their families and health professionals, the use of decision aids that are based on research evidence, can have significant effects on treatment decisions, choices and costs [ 80 , 81 ].

Research can also influence clinical practice and service delivery through [ 19 , 24 , 59 ]:

Adoption of research findings and health technologies by health service providers

Adherence to research-informed policies and guidelines and

Addressing barriers to the use of research-informed interventions in the health system. Potential barriers include inflexible organisational workflows, inadequate resources and staff training as well as staff and patient attitudes and beliefs.

Research-influenced changes in health services can lead to improved information on quality of care and improvements in quality of care itself. Quality of health care addresses [ 82 ]:

Efficacy of health interventions. For example, one of the studies included in the LSHTM analysis was a clinical audit of tonsillectomy surgical techniques where the findings were that that 'hot' surgical techniques – diathermy or coblation – had a higher risk of complication than cold steel tonsillectomy methods [ 83 ].

Availability of services, for example in different geographical regions.

Accessibility of services, especially for disadvantaged and vulnerable individuals and groups.

Acceptability of services provided, for example in terms of quality and cultural appropriateness.

Utilisation and coverage of health services. Research can inform strategies to improve the coverage of health services and can also have impact through the development of methods to assess coverage. For example, availability and accessibility of services or interventions are often used as a proxy of health services coverage. However, it has been proposed that coverage should be assessed by estimating the probability that those who need a particular intervention will actually receive it, the probability of their requiring the intervention in the future and the probability of receiving effective health services based on previous experience [ 84 ].

Responsiveness of health services to population health needs is a further area that can have impact vis-à-vis the quality of services.

A portion of health research is also directed toward improving the quality and efficiency of public health monitoring, reporting and evaluation. Possible indicators of the effects of research in this area include the accuracy, completeness, efficiency, relevance and timeliness of health monitoring and reporting systems, e.g. health information systems and GIS tools. For example, research in Turkey compared health information systems across 729 hospitals run by either the Ministry of Labor and Social Security or the Ministry of Health [ 85 ]. The study highlighted several differences in the use of health information systems across the two ministries that would need to be addressed given a proposed merger of the hospitals. This type of research could have an impact on the way health information systems are developed and used.

Health systems and services management

The extent to which research contributes to changes in health systems management and administration is therefore another important area of potential impacts. For example, management of health services procurement and provisioning in both private and public sectors can also be influenced by research [ 86 ]. In assessing the impact of research on the management of health systems and markets, there is a broad range of considerations including health care financing and insurance. In addition, Hanson et al. [ 31 ] provide a conceptual framework to analyse non-financial constraints in health systems including sociopolitical changes, intersectoral issues, such as transport to health facilities and planning for long-term outcomes such as improving health by promoting female education.

Cost-containment , while obviously related to health systems management is often a particular focus for assessing the impact of research on health services provision and health system management. This can have far-reaching implications for how health systems resources are allocated and used [ 87 ].

Cost-effectiveness of health services is another common focus in health research impact assessment and can be studied by analysing research-related changes in health systems in terms of both expenditure and related health outcomes [ 87 ]. In the LSHTM study, some research projects specifically included economic evaluations of the interventions being researched, for example the cost-effectiveness of social marketing of insecticide treated bed nets [ 88 ].

IV. Societal impacts

Finally, research impacts can be described in terms of impacts at a societal level with reference to:

Knowledge, attitudes and behaviour

Health literacy

Health status, equity and human rights, macroeconomic/related to the economy, social capital and empowerment, culture and art.

Sustainable development outcomes

Knowledge, attitude and behaviour impacts

As a result of research dissemination and implementation strategies, various research impacts on knowledge, attitudes and behaviour could be expected or targeted. For example, research information could lead to changes in:

Knowledge about and attitudes toward health risks and resources including the development of health self-efficacy. For example, in a study that was part of the LSHTM analysis, researchers had found that bilingual young people, while previously mainly viewed as an at risk group also served as a resource, often playing the role of translators and mediators in promoting their families' access to health care services [ 89 ]. These findings also led to changes in service institutions working with bilingual young people, to focus on both risks and resources in strategies aimed at improving access to health care [ 6 ].

Healthy behaviours e.g. nutrition and diet, physical activity, safe sex, immunisations and improved hygiene practices can be promoted and adopted as a result of health research being disseminated, for example through health education and health promotion activities.

However, care must be taken in predicting or describing direct effects from research-based information being communicated and the desired effects occurring. There are a host of intermediary effects and influences that complicate that process, including culture, local and socio-historical contexts, the framing and relevance of the issues as well as perceived benefits and risks related to the research, so these should be noted if possible [ 29 , 90 ].

Health literacy encompasses the wide range of skills and competencies required to find, understand, evaluate and use health information and concepts to make informed choices, reduce health risks and increase quality of life [ 91 ]. As such, health literacy is a key component of the complex relationship between knowledge, attitudes, decision-making, behaviour and health outcomes [ 30 , 92 ]. Thus, health literacy is a potential impact of health research. In addition health literacy can facilitate successful communication of health research or can be a potential roadblock in situations when health research is communicated in a manner not commensurate with the health literacy skills of the intended audience.

As one example of research that can have an impact on health literacy, traditionally malaria control strategies rely on the free distribution of insecticide treated bed nets through public health and donor agencies. However, research shows that approaches to malaria control approaches that raise awareness in communities about the causes and prevention of malaria and promote community skills and capacities to purchase and treat bed nets on their own, provide a more sustainable and equitable method of malaria control and significantly improve health outcomes [ 39 , 40 ].

Research can contribute to improvements in health status by contributing to interventions that reduce morbidity, mortality and disability and promote health as well as by developing methods to measure and monitor health status. However, the attribution of health status effects to research can be challenging given the range of other influencing factors and there are ongoing efforts to address this challenge [ 18 , 28 ]. There are various measures for assessing health outcomes such as Quality Adjusted Life Years (QALYs); Disability Adjusted Life Years (DALYs); and Health Adjusted Life Expectancy (HALE) and a host of specific measures related to particular diseases/conditions. As is the case for assessment in general, the choice of measure usually reflects researchers' preferences, decision-makers' needs and the focus of assessment. Research can therefore also have impact by elucidating the values and assumptions underlying health status assessment measures so that these can be deliberated on by a broad range of stakeholders [ 93 ]. Research impact on health outcomes can thus be assessed both in terms of changes in health outcomes as well as in methods of measuring health outcomes.

Health equity and the realisation of human rights are increasingly discussed as desired health research outcomes and need be taken into account at different levels of assessment, be they related to structure, process or outcome [ 94 , 95 ]. Research can also influence health equity outcomes by explicitly focusing on the needs of disadvantaged and vulnerable populations [ 96 ] as well as through the application of research to facilitate more equitable access to health care [ 67 ]. For example, there is concern that by focussing on mass interventions and targets set at the overall population level, the Millennium Development Goals may fail to address the needs of the most vulnerable and marginalised groups such as indigenous communities [ 97 ].

Human rights also include the right of individuals to participate in decisions that influence their lives and the right to information on the same. Additionally, the impact of participation on health outcomes is increasingly recognised. For example a randomised control trial showed that birth outcomes in a poor rural population in Nepal improved greatly through a low cost, potentially sustainable community-based participatory intervention with women's groups [ 98 ]. This type of research potentially has equity, human rights, methodological and health impacts.

There are several areas in which the economic outcomes of health research can be assessed [ 87 ]. The term 'macroeconomic' is used here to distinguish between impact on the overall economy (though the scale of impact may vary) and impact in terms of cost-savings and cost-effectiveness in the health care system, which was described in an earlier section.

There are various ways in which health research can have impact on the economy. The extent to which individual researchers have access to this level of economic analysis may vary, but some multidisciplinary research collaborations explicitly include an economic analysis of the proposed research-based intervention or technology and others may rely on post hoc economic evaluations.

Commercial outcomes can result from research in terms of monetary returns on investments in product development and marketing as well as from new or more efficient industrial processes [ 32 , 87 ].

The impact of research on private markets, particularly with regard to the distribution of health interventions, needs to be further understood and assessed. For example, research evidence indicating that the distribution of soap to promote hygiene and nets to prevent malaria is more effective and as equitable when done through local markets than through the public health system, including to poor populations [ 38 , 99 ]. These findings have influenced how some public health programmes implement related strategies.

Healthy workforce outcomes can also impact the economy. For example, analyses of the economic impact of health services research combine cost savings in health care provision with the economic value of a research intervention in terms of working days lost and produce a single metric of economic impact [ 100 ].

The value of health gain (or loss) from research to societies in monetary terms. For example, the Funding First approach calculates the economic value of improved health and life expectancy resulting from investment in and application of research-based health interventions, e.g. to treat cardiovascular disease [ 28 ]. Evaluation of health outcomes in economic terms, however, is subject to criticism even from those who use the approach, as evaluating human life in monetary terms is ethically controversial. Other potential problems include the equity implications of such approaches, for instance, evaluating the impact of health research in terms of productivity could favour research primarily focused on those of working age and/or those with higher incomes [ 101 ].

Social capital is increasingly viewed as a desired resource in societies and studies also find that there are links between social capital and health outcomes [ 4 , 5 ]. Therefore the contribution of research to the development of social capital and its assessment is a key area of impact. Social capital is measured through a variety of social research techniques and the context of the assessment is an important consideration, but many authors seem to agree on the importance of the following as measures of social capital [ 4 , 5 ]:

Civic engagement and social cohesion (through social interaction, mobilisation and connections as well as the development of shared knowledge and concepts).

Self-efficacy and collective efficacy (the ability and resources for problem solving at individual and societal levels).

Trust (in other individuals and groups in society). For example, in a series of surveys in the UK on who people generally trusted to tell them the truth, doctors and teachers were listed first, scientists and the 'ordinary man/woman in the street' were near the middle and politicians and journalists were at the bottom of the list [ 102 ]. Similar surveys have been carried out in other countries [ 103 ]. Research can generate information that affects peoples' trust of different groups. In addition, trust in researchers themselves is associated with the support and use of science.

Research that empowers communities to access, understand and use health research informed interventions, as earlier discussed with reference to the malaria control example, and to take ownership of health promotion efforts [ 30 ] is another key area of health research impact.

Culture refers to patterns of human learning and activity that lead to shared communication, artefacts and characteristics in societies; including language, patterns of behaviour, beliefs, identity, customs, traditions and other modes of expression [ 104 ]. These learned characteristics enable group members to hold and communicate shared meanings. The ability to influence culture is the also the ability to influence conceptions and categories that guide behaviour [ 105 ], including health behaviour. Health research generates new concepts and knowledge that influences societal culture (though the relationship works both ways). Health researchers are also constantly renegotiating the boundaries between what is considered traditional medicinal practice and research-based evidence as well as on what constitutes health and ill health. For instance, Maori researchers in New Zealand found that they were able to apply the methods and values of both indigenous and scientific knowledge in order to reach more comprehensive understandings of health and illness [ 106 ].

Arts and entertainment is a particular area where the influence of and on health research has generated interest in 'lay' society [ 107 ]. Some scientists serve as advisors on movies and TV shows. For example, the Journal of Public Health Policy reviewed the film The Constant Gardener . The film was based on John le Carre's book of the same title, in which the author mentions talking with Peter Godfrey-Faussett, a senior researcher at LSHTM, among others, in doing background research for the book. The review concludes with an observation of the potential impact of such work noting that,

This one production will be seen by millions of people around the world [and] will have done more to present the pharmaceutical industry's obstacles to improving health in developing countries ... than all health and science journals can in a year [ 108 ].

The influence of science on art and of art on science as well as on health and wellbeing certainly bears further research [ 109 ]. However, the interpretation and communication of science through art is increasingly considered an important means of science communication, not only in the mass media and movies, but also in museum collections on art and health as well as the art collections and programmes of major health research funders, such as the Wellcome Trust [ 110 ].

Sustainable development

Sustainable development outcomes depend on a combination of several of the earlier described impacts. One commonly encountered conceptualization of sustainable development is that it enables all people throughout the world to satisfy their basic needs and enjoy a better quality of life without compromising the quality of life of future generations, for example as defined in the Rio Declaration on Environment and Development [ 111 ].

The UK was one of the first countries to establish a set of indicators to review sustainable development in 1996 and these have been reported on regularly and reviewed in annual reports [ 77 ]. Key elements of the UK sustainable development strategy are:

Living within environmental limits

Ensuring a strong, healthy and just society

Achieving a sustainable economy

Promoting good governance

Using sound science responsibly.

Additionally, the continued ability to learn and adapt to new knowledge as it is produced is a key aspect of sustainable development. Thus, research may have a direct impact on sustainable development outcomes through the production of new knowledge on a range of topics, but can also help further develop concepts and assessment methods and help collect, validate and analyse data to guide sustainable development.

Researchers are often hard pressed to come up with coherent accounts of the significance and impact of their work as regularly required in a range of situations, from writing grant proposals to designing implementation strategies and in submissions to research assessment exercises. Increasingly health research funders expect measurable outcomes from their investment in research. While some may decry this as neglecting the inherent value of science, others point out to the underutilisation or misutilisation of health research or to the need to prioritise research funding based on identified societal needs [ 16 – 19 ]. There is also evidence that researchers' accounts of the impact of their work provide a reliable starting point for more in-depth analyses and can provide similar information to more specialised assessments, although the scope and level of analysis may vary [ 7 ].

In this light, we pragmatically set out to identify the areas where health research could be expected to have an impact and then organized these areas into a framework. The validity and usefulness of the Research Impact Framework was tested at the London School of Hygiene and Tropical Medicine. The framework categories were finalised based on feedback from researchers working on a wider range of health research topics as to which areas they thought provided a valid indication of the impact of their work and which categories they found most useful to describe the same.

While initially sceptical, LSHTM researchers found that using the Research Impact Framework prompted them to identify a wide range of impacts related to their work in a relatively systematic manner (compared to the ad hoc approaches they had previously used) [ 6 ]. Researchers' narratives contained specific and verifiable evidence and the standardized structure of the narratives facilitated analysis across projects that could inform research management, practice and assessment [ 6 ]. One caution we offer is to be aware of various biases that may influence identification and description of research impact. For instance there may be strong historical and institutional biases and incentives to identify only positive impacts from research. However, researchers interviewed in the LSHTM study were aware of potential negative impacts of their research, for example, stigma that could arise with the publication of research findings related to a particular group or community. We will continue to learn as much, if not more, about the relationship of science and society and research impacts by maintaining focus on scientific controversies as well as scientific developments.

The Research Impact Framework provides a useful set of descriptive categories to help researchers identify and describe the impact of their work. It could also help researchers think through strategies to enhance the use of research-informed interventions as well as to identify unintended or harmful effects. The standardised structure of the framework also facilitates comparison of impact across projects, which is useful from an analytical and research management perspective. In addition, the framework should help health researchers systematically present the value of the work they have done as well as the work they wish to conduct in the future. This approach will further enable researchers to better explain what it is that they do and why they do it, not only to funders and governments, but also to review boards, colleagues, journalists and family and friends. This paper contributes to ongoing efforts seeking to understand, assess and explain the role, relevance and impact of health research.

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Acknowledgements

We acknowledge that this paper has been influenced by many discussions with colleagues over the years and insights from collaborative projects on the topic of assessing the impact of research, for example in consultations on a research utilisation project at WHO. We thank the two peer reviewers, Mark Petticrew and Liz Farmer for valuable comments and suggestions that have strengthened the paper. Special thanks also to Steve Hanney from the Health Economics Research Group (HERG) at Brunel University and to Andy Haines, Nick Black and Jo Lines at the London School of Hygiene and Tropical Medicine for their ongoing advice and support. We also thank John Browne, Val Curtis, Hazel Dockrell, Pat Doyle, Lucy Gilson, Judith Green, Sari Kovats, Anne Mills, Ian Roberts, Charlotte Watts, John Whittaker, Paul Wilkinson, Cathy Zimmerman, the LSHTM Senior Management Team and other colleagues who contributed to the development and testing of the Research Impact Framework at the London School of Hygiene and Tropical Medicine.

This project received no external funds and was supported by the authors' institutions in that the authors worked and consulted with colleagues there: the London School of Hygiene and Tropical Medicine for SK, NM and GW and Rutgers University for AP. The research ethics committee at the London School of Hygiene and Tropical Medicine approved the study that informed the development of the Research Impact Framework.

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All the authors were involved in developing the Research Impact Framework described as well as in writing the paper and approving the final version. SK, NM and GW also applied and tested the framework in a study to analyse the impact of selected research projects at the London School of Hygiene and Tropical Medicine.

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Kuruvilla, S., Mays, N., Pleasant, A. et al. Describing the impact of health research: a Research Impact Framework. BMC Health Serv Res 6 , 134 (2006). https://doi.org/10.1186/1472-6963-6-134

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• Published: 11 June 2024

The Space Omics and Medical Atlas (SOMA) and international astronaut biobank

• Eliah G. Overbey   ORCID: orcid.org/0000-0002-2866-8294 1 , 2 , 3 , 4 ,
• JangKeun Kim   ORCID: orcid.org/0000-0002-8733-9925 1 , 2 ,
• Braden T. Tierney   ORCID: orcid.org/0000-0002-7533-8802 1 , 2 ,
• Jiwoon Park   ORCID: orcid.org/0000-0003-0045-1429 1 , 2 ,
• Nadia Houerbi 1 , 2 ,
• Alexander G. Lucaci 1 , 2 ,
• Sebastian Garcia Medina 1 , 2 ,
• Namita Damle 1 ,
• Deena Najjar   ORCID: orcid.org/0009-0009-7950-2866 5 ,
• Kirill Grigorev 1 , 2 ,
• Evan E. Afshin 1 , 2 ,
• Krista A. Ryon 1 ,
• Karolina Sienkiewicz 2 , 6 ,
• Laura Patras 7 , 8 ,
• Remi Klotz   ORCID: orcid.org/0000-0003-2100-0635 9 ,
• Veronica Ortiz 9 ,
• Matthew MacKay 6 ,
• Annalise Schweickart   ORCID: orcid.org/0000-0001-9691-3741 2 , 6 ,
• Christopher R. Chin   ORCID: orcid.org/0000-0002-2140-3197 1 ,
• Maria A. Sierra 6 ,
• Matias F. Valenzuela 10 ,
• Ezequiel Dantas   ORCID: orcid.org/0000-0003-4934-4632 11 , 12 ,
• Theodore M. Nelson   ORCID: orcid.org/0000-0002-8600-0444 13 ,
• Egle Cekanaviciute   ORCID: orcid.org/0000-0003-3306-1806 14 ,
• Gabriel Deards 6 ,
• Jonathan Foox 1 , 2 ,
• S. Anand Narayanan 15 ,
• Caleb M. Schmidt 16 , 17 , 18 ,
• Michael A. Schmidt 16 , 17 ,
• Julian C. Schmidt 16 , 17 ,
• Sean Mullane 19 ,
• Seth Stravers Tigchelaar 19 ,
• Steven Levitte 19 , 20 ,
• Craig Westover 1 ,
• Chandrima Bhattacharya 6 ,
• Serena Lucotti 7 ,
• Jeremy Wain Hirschberg 1 ,
• Jacqueline Proszynski 1 ,
• Marissa Burke   ORCID: orcid.org/0000-0001-5647-3358 1 ,
• Ashley Kleinman 1 ,
• Daniel J. Butler 1 ,
• Conor Loy 21 ,
• Omary Mzava 21 ,
• Joan Lenz 21 ,
• Doru Paul 22 ,
• Christopher Mozsary 1 ,
• Lauren M. Sanders 14 ,
• Lynn E. Taylor 23 ,
• Chintan O. Patel 24 ,
• Sharib A. Khan 24 ,
• Mir Suhail 24 ,
• Syed G. Byhaqui 24 ,
• Burhan Aslam 24 ,
• Aaron S. Gajadhar 25 ,
• Lucy Williamson 25 ,
• Purvi Tandel 25 ,
• Qiu Yang 25 ,
• Jessica Chu 25 ,
• Ryan W. Benz 25 ,
• Asim Siddiqui 25 ,
• Daniel Hornburg   ORCID: orcid.org/0000-0002-6618-7774 25 ,
• Kelly Blease 26 ,
• Juan Moreno 26 ,
• Andrew Boddicker   ORCID: orcid.org/0000-0001-7957-8283 26 ,
• Junhua Zhao   ORCID: orcid.org/0009-0006-7672-1084 26 ,
• Bryan Lajoie 26 ,
• Ryan T. Scott   ORCID: orcid.org/0000-0003-0654-5661 27 ,
• Rachel R. Gilbert 27 ,
• San-huei Lai Polo 27 ,
• Andrew Altomare 26 ,
• Semyon Kruglyak 26 ,
• Shawn Levy 26 ,
• Ishara Ariyapala 28 ,
• Joanne Beer   ORCID: orcid.org/0000-0001-8583-8467 28 ,
• Bingqing Zhang 28 ,
• Briana M. Hudson 29 ,
• Aric Rininger 29 ,
• Sarah E. Church   ORCID: orcid.org/0000-0002-7194-4282 29 ,
• Afshin Beheshti   ORCID: orcid.org/0000-0003-4643-531X 30 , 31 ,
• George M. Church   ORCID: orcid.org/0000-0001-6232-9969 32 ,
• Scott M. Smith   ORCID: orcid.org/0000-0001-9313-7900 33 ,
• Brian E. Crucian 33 ,
• Sara R. Zwart   ORCID: orcid.org/0000-0001-8694-0180 34 ,
• Irina Matei   ORCID: orcid.org/0000-0002-5712-8430 7 , 12 ,
• David C. Lyden   ORCID: orcid.org/0000-0003-0193-4131 7 , 12 ,
• Francine Garrett-Bakelman 35 , 36 ,
• Jan Krumsiek   ORCID: orcid.org/0000-0003-4734-3791 1 , 2 , 6 ,
• Qiuying Chen 37 ,
• Dawson Miller 37 ,
• Joe Shuga 38 ,
• Stephen Williams 38 ,
• Corey Nemec   ORCID: orcid.org/0000-0002-6566-1753 38 ,
• Guy Trudel   ORCID: orcid.org/0000-0001-5254-4294 39 , 40 , 41 ,
• Martin Pelchat 42 ,
• Odette Laneuville   ORCID: orcid.org/0000-0003-3124-3892 43 ,
• Iwijn De Vlaminck   ORCID: orcid.org/0000-0001-6085-7311 21 ,
• Steven Gross 37 ,
• Kelly L. Bolton 44 ,
• Susan M. Bailey   ORCID: orcid.org/0000-0001-5595-9364 23 , 45 ,
• Richard Granstein 46 ,
• David Furman   ORCID: orcid.org/0000-0002-3654-9519 10 , 47 , 48 , 49 ,
• Ari M. Melnick   ORCID: orcid.org/0000-0002-8074-2287 12 , 22 ,
• Sylvain V. Costes   ORCID: orcid.org/0000-0002-8542-2389 14 ,
• Bader Shirah   ORCID: orcid.org/0000-0001-6493-2155 50 ,
• Anil S. Menon   ORCID: orcid.org/0000-0002-6886-3553 34 ,
• Jaime Mateus 19 ,
• Cem Meydan   ORCID: orcid.org/0000-0002-0663-6216 1 , 2 , 22 &
• Christopher E. Mason   ORCID: orcid.org/0000-0002-1850-1642 1 , 2 , 3 , 51 , 52  

Nature ( 2024 ) Cite this article

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• Medical research
• Molecular biology

Spaceflight induces molecular, cellular, and physiological shifts in astronauts and poses myriad biomedical challenges to the human body, which are becoming increasingly relevant as more humans venture into space 1-6 . Yet, current frameworks for aerospace medicine are nascent and lag far behind advancements in precision medicine on Earth, underscoring the need for rapid development of space medicine databases, tools, and protocols. Here, we present the Space Omics and Medical Atlas (SOMA), an integrated data and sample repository for clinical, cellular, and multi-omic research profiles from a diverse range of missions, including the NASA Twins Study 7 , JAXA CFE study 8,9 , SpaceX Inspiration4 crew 10-12 , plus Axiom and Polaris. The SOMA resource represents a >10-fold increase in publicly available human space omics data, with matched samples available from the Cornell Aerospace Medicine Biobank. The Atlas includes extensive molecular and physiological profiles encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiome data sets, which reveal some consistent features across missions, including cytokine shifts, telomere elongation, and gene expression changes, as well as mission-specific molecular responses and links to orthologous, tissue-specific murine data sets. Leveraging the datasets, tools, and resources in SOMA can help accelerate precision aerospace medicine, bringing needed health monitoring, risk mitigation, and countermeasures data for upcoming lunar, Mars, and exploration-class missions.

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A Second Space Age Spanning Omics, Platforms, and Medicine Across Orbits

Single-cell multi-ome and immune profiles of the Inspiration4 crew reveal conserved, cell-type, and sex-specific responses to spaceflight

Collection of biospecimens from the inspiration4 mission establishes the standards for the space omics and medical atlas (SOMA)

Author information, authors and affiliations.

Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA

Eliah G. Overbey, JangKeun Kim, Braden T. Tierney, Jiwoon Park, Nadia Houerbi, Alexander G. Lucaci, Sebastian Garcia Medina, Namita Damle, Kirill Grigorev, Evan E. Afshin, Krista A. Ryon, Christopher R. Chin, Jonathan Foox, Craig Westover, Jeremy Wain Hirschberg, Jacqueline Proszynski, Marissa Burke, Ashley Kleinman, Daniel J. Butler, Christopher Mozsary, Jan Krumsiek, Cem Meydan & Christopher E. Mason

The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

Eliah G. Overbey, JangKeun Kim, Braden T. Tierney, Jiwoon Park, Nadia Houerbi, Alexander G. Lucaci, Sebastian Garcia Medina, Kirill Grigorev, Evan E. Afshin, Karolina Sienkiewicz, Annalise Schweickart, Jonathan Foox, Jan Krumsiek, Cem Meydan & Christopher E. Mason

BioAstra, Inc, New York, NY, USA

Eliah G. Overbey & Christopher E. Mason

Center for STEM, University of Austin, Austin, TX, USA

Eliah G. Overbey

Albert Einstein College of Medicine, Bronx, NY, USA

Deena Najjar

Tri-Institutional Biology and Medicine program, Weill Cornell Medicine, New York, NY, USA

Karolina Sienkiewicz, Matthew MacKay, Annalise Schweickart, Maria A. Sierra, Gabriel Deards, Chandrima Bhattacharya & Jan Krumsiek

Children’s Cancer and Blood Foundation Laboratories, Departments of Pediatrics and Cell and Developmental Biology, Drukier Institute for Children’s Health, Weill Cornell Medicine, New York, NY, USA

Laura Patras, Serena Lucotti, Irina Matei & David C. Lyden

Department of Molecular Biology and Biotechnology, Center of Systems Biology, Biodiversity and Bioresources, Faculty of Biology and Geology, Babes-Bolyai University, Cluj-Napoca, Romania

Laura Patras

Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

Remi Klotz, Veronica Ortiz & Min Yu

Buck Institute for Research on Aging, Novato, CA, USA

Matias F. Valenzuela & David Furman

Division of Endocrinology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA

Ezequiel Dantas

Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA

Ezequiel Dantas, Irina Matei, David C. Lyden & Ari M. Melnick

Department of Microbiology & Immunology, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY, USA

Theodore M. Nelson

Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA

Egle Cekanaviciute, Lauren M. Sanders & Sylvain V. Costes

Department of Health, Nutrition, and Food Sciences, Florida State University, Tallahassee, FL, USA

S. Anand Narayanan

Sovaris Aerospace, Boulder, Colorado, USA

Caleb M. Schmidt, Michael A. Schmidt & Julian C. Schmidt

Advanced Pattern Analysis and Human Performance Group, Boulder, Colorado, USA

Department of Systems Engineering, Colorado State University, Fort Collins, Colorado, USA

Caleb M. Schmidt

Space Exploration Technologies Corporation (SpaceX), Hawthorne, CA, USA

Sean Mullane, Seth Stravers Tigchelaar, Steven Levitte & Jaime Mateus

Division of Pediatric Gastroenterology, Stanford University, Palo Alto, CA, USA

Steven Levitte

Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA

Conor Loy, Omary Mzava, Joan Lenz & Iwijn De Vlaminck

Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA

Doru Paul, Ari M. Melnick & Cem Meydan

Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA

Lynn E. Taylor & Susan M. Bailey

TrialX Inc., New York, NY, USA

Chintan O. Patel, Sharib A. Khan, Mir Suhail, Syed G. Byhaqui & Burhan Aslam

Seer, Inc., Redwood City, CA, USA

Aaron S. Gajadhar, Lucy Williamson, Purvi Tandel, Qiu Yang, Jessica Chu, Ryan W. Benz, Asim Siddiqui & Daniel Hornburg

Element Biosciences, San Diego, CA, USA

Kelly Blease, Juan Moreno, Andrew Boddicker, Junhua Zhao, Bryan Lajoie, Andrew Altomare, Semyon Kruglyak & Shawn Levy

KBR; Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA

Ryan T. Scott, Rachel R. Gilbert & San-huei Lai Polo

Alamar Biosciences, Inc, 47071 Bayside Parkway, Fremont, CA, USA

Ishara Ariyapala, Joanne Beer & Bingqing Zhang

NanoString Technologies, Seattle, WA, USA

Briana M. Hudson, Aric Rininger & Sarah E. Church

Blue Marble Space Institute of Science; Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA

• Afshin Beheshti

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

Harvard Medical School and the Wyss Institute, Boston, MA, USA

George M. Church

National Aeronautics and Space Administration, Johnson Space Center, Human Health and Performance Directorate, Biomedical Research and Environmental Sciences Division, Houston, TX, USA

Scott M. Smith & Brian E. Crucian

University of Texas Medical Branch, Galveston, TX, USA

Sara R. Zwart & Anil S. Menon

Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA

Francine Garrett-Bakelman

Department of Medicine, Division of Hematology & Oncology, University of Virginia, Charlottesville, VA, USA

Department of Pharmacology, Weill Cornell Medicine, New York, NY, USA

Qiuying Chen, Dawson Miller & Steven Gross

10x Genomics, Pleasanton, CA, USA

Joe Shuga, Stephen Williams & Corey Nemec

Bone and Joint Research Laboratory, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, Canada

Department of Medicine, Division of Physiatry, The Ottawa Hospital, Room 2505G, 505 Smyth Road, Ottawa, Ontario, Canada

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Department of Biochemistry, Microbiology, and Immunology, Roger Guindon Hall, Room 4111A, University of Ottawa, Ottawa, Canada

Martin Pelchat

Department of Biology, Gendron Hall Room 3-372, University of Ottawa, Ottawa, Canada

Odette Laneuville

Division of Oncology, Department of Medicine, Washington University School of Medicine, St Louis, MO, USA

Kelly L. Bolton

Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO, USA

Susan M. Bailey

Department of Dermatology, Weill Cornell Medicine, New York, NY, USA

Richard Granstein

Cosmica Biosciences Inc., San Francisco, CA, USA

David Furman

Stanford 1000 Immunomes Project, Stanford School of Medicine, Stanford University, Stanford, CA, USA

Institute for Research in Translational Medicine, Universidad Austral, CONICET, Pilar, Buenos Aires, Argentina

Department of Neuroscience, King Faisal Specialist Hospital & Research Centre, Jeddah, Saudi Arabia

Bader Shirah

The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, NY, USA

Christopher E. Mason

WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA

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Corresponding authors

Correspondence to Eliah G. Overbey , Cem Meydan or Christopher E. Mason .

Supplementary information

Supplementary information.

This file contains Supplementary Figures 1-3, Supplementary Tables 4 and 9, Supplementary Note 1 and additional references.

Reporting Summary

Supplementary table 1.

Sample Information. Comprehensive list of samples collected from each crew member, at each timepoint, for each assay. Tab 1 is an overview of which samples are present at each timepoint. Tab 2 is an itemized list of each sample, including the number of sequenced DNA/RNA molecules for sequencing assays.

Supplementary Table 2

OSDR Studies. Comprehensive list of prior studies in OSDR for previous assays on human, metagenomic, and metatranscriptomic samples.

Supplementary Table 3

Sequencing and Mass Spectrometry Stats Tables. Sequencing and mass spectrometry statistics for multiome, TCR, BCR, cfRNA, dRNA, and proteomics assays.

Supplementary Table 5

cfRNA Calculations. Tissue of origin analysis from cfRNA sequencing. Tab 1 contains fractions of cell type specific RNA enrichment. Tab 2 contains comparisons between timepoints.

Supplementary Table 6

Recovery Profile Pathways. Overrepresented KEGG pathways during recovery from spaceflight in PBMCs. Tabs are split for CD4+ T cells, CD8+ T cells, CD14+ monocyte and CD16+ monocytes.

Supplementary Table 7

Metagenome and Metatranscriptome CVs. Species-level CV calculations across crew members for metagenomic and metatranscriptomic samples from oral, nasal, and skin swab samples.

Supplementary Table 8

Human Omics CVs. Gene/analyte-level CV calculations across crew members for NULISAseq, EVP proteomic, plasma proteomic, metabolomic, dRNA-seq and short read RNA-seq assays. GSEA pathway enrichment is calculated for pre-flight, post-flight (R+1), and recovery time intervals.

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Overbey, E.G., Kim, J., Tierney, B.T. et al. The Space Omics and Medical Atlas (SOMA) and international astronaut biobank. Nature (2024). https://doi.org/10.1038/s41586-024-07639-y

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Received : 30 December 2022

Accepted : 31 May 2024

Published : 11 June 2024

DOI : https://doi.org/10.1038/s41586-024-07639-y

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Addressing the unprecedented behavioral-health challenges facing Generation Z

Nearly two years after the COVID-19 pandemic began in the United States, Gen Zers, ranging from middle school students to early professionals, are reporting higher rates of anxiety, depression, and distress than any other age group. 1 Ages for Generation Z can vary, with some analysis including ages as young as nine. In this article, we focus on those between the ages of 16 and 24, and define millennials as 25 to 40; Ramin Mojtabai and Mark Olfson, “National trends in mental health care for US adolescents,” JAMA Psychiatry , March 25, 2020, Volume 77, Number 7; Martin Seligman, The Optimistic Child: A Revolutionary Approach to Raising Resilient Children , Boston, MA: Mariner Books, 2007; Gen Z respondents are 1.5 times as likely to report having felt anxious or depressed, compared with the average respondent, according to the McKinsey Consumer Health Insights Survey, conducted in June 2021—a nationally representative survey of 2,906 responses, including 316 Gen Z responses. The mental-health challenges among this generation are so concerning that US surgeon general Vivek Murthy issued a public health advisory on December 7, 2021, to address the “youth mental health crisis” exacerbated by the COVID-19 pandemic. 2 Protecting youth mental health: US surgeon general’s advisory , Office of the Surgeon General, December 7, 2021.

About the authors

The article is a collaborative effort by Erica Coe , Jenny Cordina , Kana Enomoto , Raelyn Jacobson , Sharon Mei, and Nikhil Seshan, representing views of the McKinsey’s Healthcare Systems & Services and Public & Social Sector Practices.

A series of consumer surveys and interviews conducted by McKinsey indicate stark differences among generations, with Gen Z  reporting the least positive life outlook, including lower levels of emotional and social well-being than older generations. One in four Gen Z respondents reported feeling more emotionally distressed (25 percent), almost double the levels reported by millennial and Gen X respondents (13 percent each), and more than triple the levels reported by baby boomer respondents (8 percent). 3 These research efforts have been focused on Gen Zers between the ages of 16 and 24 when compared with samples of millennials (aged 25 to 40), Gen Xers (aged 41 to 56), and baby boomers (aged 57 to 76). And the COVID-19 pandemic has only amplified this challenge (see sidebar, “The disproportionate impact of the COVID-19 pandemic”). While consumer surveys are, of course, subjective and Gen Z is not the only generation to experience distress, employers, educators, and public health leaders may want to consider the sentiment of this emerging generation as they plan for the future.

The disproportionate impact of the COVID-19 pandemic

While Gen Z is less vulnerable to the physical impacts of the COVID-19 pandemic, they bear unique burdens due to their life stage, including emotional stress and grief from the pandemic, high rates of job loss and unemployment, and educational challenges from remote or interrupted learning. The effects of the pandemic may be especially felt by recent college graduates, many of whom have encountered difficulties finding jobs, had their previously secured job offers rescinded, or were unable to apply to graduate school due to the timing of the lockdowns in March 2020. In April 2020, workers aged 18 to 24 faced 27 percent unemployment, with 13 percent of this segment ceasing to look for work. While employment has largely recovered, this segment has exited the workforce at twice the rate of other age groups  since the start of the pandemic. The inequitable impact of the pandemic by race extends to Gen Z employment as well, where Black, Hispanic/Latino, and Asian American and Pacific Islander (AAPI) workers aged 18 to 24 faced up to 1.8 times the unemployment rates of their White counterparts. 1 McKinsey analysis of the US Census Bureau Current Population Survey as of November 2020.

In our sample, Gen Z respondents were more likely to report having been diagnosed with a behavioral-health condition (for example, mental or substance use disorder) than either Gen Xers or baby boomers. 4 Gen Z respondents were 1.4 to 2.3 times more likely to report that they had been diagnosed with a mental-health condition and 1.9 to 4.1 times more likely to be diagnosed with a substance-use disorder than both Gen Xers and baby boomers. Based on the McKinsey Consumer Behavioral Health Survey conducted in November–December 2020—a nationally representative survey of 1,523 responses, including an oversample of Gen Z respondents (aged 16 to 24, n = 874). Gen Z respondents were also two to three times more likely than other generations to report thinking about, planning, or attempting suicide in the 12-month period spanning late 2019 to late 2020.

Gen Z also reported more unmet social needs than any other generation. 5 Also referred to as social determinants of health or social needs, including income, employment, education, food, housing, transportation, social support, and safety. These basic needs, if unmet, can negatively affect health. In addition, factors such as race, ethnicity, gender and sexual orientation, disability, and age can influence health status. Fifty-eight percent of Gen Z reported two or more unmet social needs, compared with 16 percent of people from older generations. These perceived unmet social needs, including income, employment, education, food, housing, transportation, social support, and safety, are associated with higher self-reported rates of behavioral-health conditions. As indicated in a recent nationwide survey, people with poor mental health were two times as likely to report an unmet basic need as those with good mental health, and four times as likely to have three or more unmet basic needs. 6 2019 McKinsey Social Determinants of Health Survey, n = 2,010, where respondents included those with Medicare or Medicaid coverage, individuals with coverage through the individual market who had household incomes below 250 percent of the federal poverty level, and individuals who were uninsured and had household income below 250 percent of the federal poverty level.

As these young adults work to develop their resilience, Gen Zers may seek out the holistic approach to health they have come to expect, which includes physical health, behavioral health, and social needs, as future students, employees, and customers.

Characteristics of Gen Z consumers in the healthcare ecosystem

Gen Z’s specific needs suggest that improving their behavioral healthcare will require stakeholders to increase access and deliver appropriate, timely services.

Gen Z is less likely to seek help

Gen Z respondents were more likely to report having a behavioral-health diagnosis but less likely to report seeking treatment compared with other generations (Exhibit 1). For instance, Gen Z is 1.6 to 1.8 times more likely to report not seeking treatment for a behavioral-health condition than millennials. There are several factors that may account for Gen Z’s lack of seeking help: developmental stage, disengagement from their healthcare, perceived affordability, and stigma associated with mental or substance use disorders within their families and communities. 7 Before age 25, the human brain is not fully developed. Awareness of long-term consequences and the ability to curb impulsive behavior are some of the last functions to mature. Thus, adolescents and young adults, across generations and not just Gen Z, may be less likely to engage in activities such as routine or preventive healthcare. For more, see Investing in the health and well-being of young adults , Institute of Medicine and National Research Council, 2015.

Gen Z respondents identified as less engaged in their healthcare than other respondents (Exhibit 2). About two-thirds of Gen Z respondents fell into lower engagement segments of healthcare consumers, compared with one-half of respondents from other generations. Gen Z and other people in these less engaged segments reported that they feel less in control of their health and lifespan, are less health-conscious, and are less proactive about maintaining good health. One-third of Gen Z respondents fell into the least engaged segment, who reported the lowest motivation to improve their health and the least comfort talking about behavioral-health challenges with doctors. 8 Disadvantaged, disconnected users are more resigned to their health and less engaged and active in improving it. They value convenience but are often not engaged digitally.

Another driver for Gen Z’s reduced help-seeking may be the perceived affordability of mental-health services. One out of four Gen Z respondents said they could not afford mental-health services, which had the lowest perceived affordability of all services surveyed. 9 Services surveyed include healthcare, health insurance, internet services, necessary transportation, financial services, housing, and nutritious food. Across the board, Americans with mental and substance use disorders bear a disproportionate share of out-of-pocket healthcare costs for a range of reasons, including the fact that many behavioral-health providers do not accept insurance . “I found the perfect therapist for me but I couldn’t afford her, even with insurance,” said one Gen Z respondent. “The absolute biggest barrier to gaining mental-health treatment has been financial,” added another.

In addition, stigma associated with mental and substance use disorders and a lack of family support may be a substantial barrier in seeking mental healthcare. Many Gen Zers rely on parents for transportation or health insurance and may fear interacting with their parents about mental-health topics. This factor is particularly relevant for communities of color, who report perceiving a higher level of stigma associated with behavioral-health conditions. 10 Mental health: Culture, race, and ethnicity; A supplement to mental health; A report of the surgeon general , US Department of Health and Human Services, August 2001: A 1998 study cited in the supplement found that only 12 percent of Asians would mention their mental-health problems to a friend or relative (compared with 25 percent of Whites), only 4 percent of Asians would seek help from a psychiatrist or specialist (compared with 26 percent of Whites), and only 3 percent of Asians would seek help from a physician (compared with 13 percent of Whites). Children of immigrants also may internalize guilt because of their parents’ sacrifices or may have behavioral-health concerns minimized by their parents, who may state or think their children “have it much easier” than they did growing up. 11 Mental Health America , “To be the child of an immigrant,” blog entry by Kenna Chick, accessed December 1, 2021.

Gen Z relies on emergency care, social media, and digital tools when they do seek help

When they do seek support for behavioral-health issues, Gen Z may not be turning to regular outpatient mental-health services and instead may rely on emergency care, social media, and digital tools .

Gen Zers rely on acute sites of care more often than older generations, with Gen Z respondents one to four times more likely to report using the ER, and two to three times more likely to report using crisis services or behavioral-health urgent care in the past 12 months. Gen Z also makes up nearly three-quarters of Crisis Text Line’s users. 12 Everybody hurts 2020: What 48 million messages say about the state of mental health in America , Crisis Text Line, February 10, 2020. One Gen Z respondent expressed her frustration, saying, “Seems [like the] only option is an emergency room visit, otherwise I have to wait weeks to see a psychiatrist.”

Almost one in four Gen Zers also reported that it is “extremely” or “very” challenging to get help during a behavioral-health crisis. This lack of access is concerning for a generation two to three times more likely to report seeking treatment in the past 12 months for suicidal ideation or attempted suicide, than any other generation.

Many Gen Zers also indicated their first step in managing behavioral-health challenges was going to TikTok or Reddit for advice from other young people, following therapists on Instagram, or downloading relevant apps. This reliance on social media may be due, in part, to the provider shortages in many parts of the country: 64 percent of counties in the United States have a shortage of mental-health providers. Furthermore, 56 percent of counties in the United States are without a psychiatrist (corresponding to 9 percent of the total population), and 73 percent of counties are without a child and adolescent psychiatrist (corresponding to 19 percent of the total population). 13 Oleg Bestsennyy, Greg Gilbert, Alex Harris, and Jennifer Rost, “ Telehealth: A quarter-trillion-dollar post-COVID-19 reality ?,” McKinsey, July 9, 2021; Vulnerable Populations dashboard, McKinsey’s Center for Societal Benefit through Healthcare, accessed December 1, 2021.

Gen Z is less satisfied with the behavioral-health services they receive

Gen Zers say the behavioral healthcare system overall is not meeting their expectations—Gen Zers who received behavioral healthcare were less likely to report being satisfied with the services they received than other generations. For example, compared with older generations, Gen Z reports lower satisfaction with behavioral-health services received through outpatient counseling/therapy (3.7 out of 5.0 for Gen Z, compared with 4.1 for Gen X) or intensive outpatient (3.1 for Gen Z, compared with 3.8 for older generations). 14 Mean differences are significantly different, at a 90 percent confidence level. One Gen Z respondent said, “Struggling to find a psychologist whom I was comfortable with and cared enough to remember my name and what we did the week before” was the most significant barrier to care. Another said, “I have trust issues and find it difficult to talk with therapists about my problems. I also had a very bad experience with a therapist, which made this problem worse.”

Although we have seen high penetration of telehealth in psychiatry (share of telehealth outpatient and office visits claims were at 50 percent in February 2021), 15 Vulnerable Populations: Data Over Time Database, McKinsey Center for Societal Benefit through Healthcare, April 2021. Gen Z has the lowest satisfaction with tele-behavioral health (Gen Z rates their satisfaction with telehealth at a 3.8 out of 5.0, compared with older generations, who rate it 4.1) and digital app/tools (3.5 out of 5.0 for Gen Z, compared with 4.0 for older generations). 16 Mean differences are significantly different, at a 90 percent confidence level. Around telehealth, Gen Zers cited reasons for dissatisfaction such as telehealth therapy feeling “less official” or “less professional,” as well as more difficult to form a trusting connection with a therapist. For apps, Gen Z respondents noted a lack of personalization, as well as a lack of diversity—both in terms of the racial and ethnic diversity of the stories they presented, and in the problems that the apps offered tools to address. In creating and improving behavioral-health tools, it is crucial to employ a user-centered design approach to develop functionality and experiences that Gen Zers actually want.

In creating and improving behavioral-health tools, it is crucial to employ a user-centered design approach to develop functionality and experiences that Gen Zers actually want.

Gen Z cares about diversity when choosing a healthcare provider

Racial and ethnic diversity in the behavioral-health workforce is also important. According to McKinsey’s COVID-19 Consumer Survey, racial and ethnic minority respondents reported valuing racial and ethnic diversity when choosing a physician, citing their physician’s race more frequently than White respondents as a consideration. 17 Thirteen percent of Black respondents, 9 percent of Asian respondents, and 8 percent of Hispanic/Latino respondents cited their physician’s race when selecting the physicians that they see, compared with 4 percent of Whites. Because Gen Z cares deeply about diversity, there are opportunities to integrate care and early intervention by offering a more racially and ethnically diverse behavioral-health workforce and culturally relevant digital tools. 18 According to surveys conducted by the Pew Research Center, most Gen Zers see the country’s growing racial and ethnic diversity as a good thing: Ruth Igielnik and Kim Parker, “On the cusp of adulthood and facing an uncertain future: What we know about Gen Z so far,” Pew Research Center, May 14, 2020.

Potential stakeholder actions to address the needs of Generation Z

In our article “ Unlocking whole person care through behavioral health ,” we outline six potential actions integral to improving the quality of care and experience for millions with behavioral-health conditions. Many of those levers apply to Gen Z, but further tailoring is needed to best meet the needs of this emerging generation. Promising areas to explore could include the emerging role of digital and telehealth; the need for stronger community-based response to behavioral-health crises; better meeting the needs of Gen Z where they live, work, and go to school; promoting mental-health literacy; investing in behavioral health at parity with physical health; and supporting a holistic approach that embraces behavioral, physical, and social aspects of health.

Need for action now

Gen Z is our next generation of leaders, activists, and politicians; many of them have already taken on adult responsibilities as they start climate movements, lead social justice marches, and drive companies to align more closely with their values. Healthcare leaders, educators, and employers all have a role to play in supporting the behavioral health of Gen Z. By taking a tailored, generational approach to designing messages, products, and services, stakeholders can meaningfully improve the behavioral health of Gen Z and help them achieve their full potential. This investment could be viewed as a down payment on our future that will bear social and economic returns for years to come.

Erica Coe is a partner in McKinsey’s Atlanta office and coleads the Center for Societal Benefit through Healthcare, Jenny Cordina is a partner in the Detroit office and leads McKinsey’s Consumer Health Insights research, Kana Enomoto is a senior expert in the Washington, DC, office and coleads the Center for Societal Benefit through Healthcare, Raelyn Jacobson is an associate partner in the Seattle office, Sharon Mei is an expert in the New York office, and Nikhil Seshan is a consultant in the Philadelphia office.

The authors wish to thank Tamara Baer, Eric Bochtler, Emma Dorn, Erin Harding, Brad Herbig, Jimmy Sarakatsannis, and Boya Wang for their contributions to this paper.

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• Sustainability

Microplastics Are Everywhere. Here’s How to Avoid Eating Them.

By Katie Okamoto

Katie Okamoto is an editor on the discovery team. She’s covered the intersections of products, sustainability, and health for more than a decade.

Microplastics and nanoplastics are everywhere.

The teeny tiny pieces of plastic have been found in everything from drinking water to chicken nuggets, apples, and broccoli.

Recent studies have linked these pollutants to heart disease , lung disorders , and more worrying health issues.

But unfortunately, microplastics are now so pervasive that they’re nearly impossible to avoid.

If you’re concerned about the health effects linked to microplastics, the experts I spoke with said that you can lower your risk by taking care of your general health: getting plenty of sleep and exercise, eating a balanced diet, lowering stress, and seeking preventative care.

Still, it’s probably a good idea to lower your exposure to microplastics even if you can’t avoid them completely. Although you can cut back your exposure in as many ways as there are sources of plastic, the experts I spoke with recommended focusing on exposures from water, food, and air.

I talked to three doctors and a research scientist for tips on how to reduce the amount of tiny plastics and their chemicals that you (or your kids ) might ingest. Here’s what they recommend.

1. Cut back on bottled water

Some research indicates plastic bottled water may be a significant source of microplastics. While scientists are still studying just how significant, one study from 2019 of water and other commonly consumed food and drink found it to be the most concentrated source .

There is emerging evidence that on average, bottled water contains more microplastics than tap. (One study published in 2024 suggests that we have underestimated measured concentrations.)

Drinking bottled water in a pinch isn't the end of the world, but if you have concerns about it, you could always consider carrying a reusable steel or glass bottle or tumbler when out and about.

2. Get an NSF-certified water filter

Switching to tap water from plastic bottled water will likely significantly reduce your routine exposure to plastics. But while the average plastic water bottle contains more microplastics and nanoplastics than tap, research shows that tap water may also be a source of microplastics.

Several of our water filter picks are specifically NSF/American National Standards Institute–certified to reduce microplastics, which means they’ve been rigorously tested in an accredited lab. They’re certified only to reduce since the filters cannot guarantee total elimination. Our picks include under-sink filters , such as the Aquasana AQ-5200 , and the Brita Elite , a pitcher filter .

Aquasana AQ-5200

Exceptional, affordable under-sink filtration.

Certified for the most contaminants, widely available, affordable, and compact.

Buying Options

$100 + FS w/code AQWC50

Brita Elite Filter

Ace filtration, long lifespan.

This 10-cup, user-friendly model is rated to last six months between replacements.

Yes, it’s ironic that most NSF/ANSI-certified water filters contain plastic. But any microplastic shedding from using the plastic filter is likely to be minimal, as long as you avoid running hot water through the filter and store your water in the fridge, since heat accelerates plastic degradation.

Research suggests that boiling tap water, cooling it, and then filtering it may be especially effective at reducing microplastics, although it’s less practical for most people than simply using a filter.

3. Don’t use plastic to store food

Plastic food storage and packaging is so common that it’s difficult to avoid entirely. But your safest bet is to avoid storing food or liquid in plastic when possible and to minimize exposing any plastic (even those that say they’re BPA-free or microwave-safe) to high heat. Sunlight, acids, and physical erosion can also degrade plastic.

4. Don’t reuse single-use plastics for food and drinks

It’s great to reuse single-use plastic —just not for food. Unless you’re using the plastic in the freezer, save it for something that isn’t food storage or reheating, said Dr. Gillian Goddard, an endocrinologist and author at ParentData , a science-based online resource for parents. That means don’t reuse plastic takeout containers, breastmilk bags, or drink bottles.

5. Don’t microwave in plastic

Avoid microwaving or heating food or water in plastic—even if it says it’s microwave-safe, said Tracey Woodruff, director of the Program on Reproductive Health and the Environment at University of California San Francisco. Instead, consider glass or ceramic. The Pyrex Simply Store 18-Piece Set is our pick for the best food storage containers , and they survived our drop tests, stack neatly, and come with user-friendly lids (although you may not want to microwave the plastic lids). Our runner-up, the leakproof Glasslock 18-Piece Container Set , is another great option.

Pyrex Simply Store 18-Piece Set

The best glass container set.

The Pyrex Simply Store containers stack neatly and are made from durable tempered glass. The colorful lids make it easier to match their shape to the corresponding container, though you may need to replace them over time.

Glasslock 18-Piece Container Set

The best leakproof glass container set.

The Glasslock containers have locking lids that will prevent leaks. But these lids also put stress on the lips of the containers, so the glass may be prone to chipping over time.

6. Wash plastic by hand

Dishwasher temperatures run very hot and can degrade plastic—even dishwasher-safe plastic—and lead to microplastic shedding. Try to wash your plastic food containers by hand.

7. Use wood or bamboo cutting boards

Some research suggests that plastic cutting boards can be a significant source of microplastics in your diet, since repeated cutting on their surface can dislodge particles that adhere to food. Wood cutting boards also have some other advantages: They’re better for your knife blades and last longer than plastic when properly maintained.

Teakhaus Medium Professional Carving Board with Juice Canal 109

The best wood cutting board.

This beautiful teak board requires more careful cleaning than a plastic board, but it feels better under a knife and is easier to maintain than the other wood boards we tested.

Our cutting board pick, the Teakhaus Medium Professional Carving Board with Juice Canal 109 , is made from sustainably harvested teak. If you still prefer plastic for certain uses, use it sparingly and replace it after heavy scarring.

8. Clean your air

The air we breathe is also a potential source of microplastics, in the form of dust. Reducing airborne dust in your home, then, may reduce your exposure to inhaled microplastics.

SEBO Airbelt K3 Premium

The best canister vacuum.

This bagged canister vacuum excels on both bare floors and carpets, and has many adjustment options and useful attachments. It should last for the long haul.

7-Year Standard Warranty

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That means doing boring stuff, like vacuuming regularly with a bagged, sealed-system vacuum that has a HEPA or S-class filter and mopping and wiping down surfaces with a damp sponge or cloth (since dusting kicks those tiny particles back up into the air).

Coway Airmega AP-1512HH Mighty

Exceptional, efficient, affordable.

Perfect for bedrooms, playrooms, and living rooms, this air purifier is one of the highest-performing, most-durable, and most-economical models we’ve tested.

You should also take care of seasonal chores like cleaning fans and AC unit filters and changing HVAC filters, and consider getting an air purifier if you live near a busy road.

Take special steps for infants and young children

Infants may be exposed to microplastics and nanoplastics in much higher concentrations than adults. Research shows that this exposure may be cause for concern, particularly at critical stages of early development. But much like health risks to adults, it’s important to think of microplastics exposure as just one piece of a child’s overall health.

“I emphasize that before putting much energy and resources into minimizing unknown risks, it is worth attending to reducing the risks we know about,” said Dr. Carlos Lerner, a pediatrician and professor of clinical pediatrics at UCLA Health. He cited following safe sleep recommendations for infants, avoiding secondhand smoke, and practicing good nutrition as examples.

If you want to take a more precautionary approach, avoid using plastic to warm formula or breastmilk. This is the main point of advice from the experts I spoke with, as well as the Cleveland Clinic .

1. Avoid microwaving or heating formula in plastic

Recent evidence shows that polypropylene-bottle-fed babies may swallow very high levels of tiny plastics due to the high temperatures used to sterilize bottles and prepare formula, as well as shaking the bottles to mix. If you want to feed your baby warmed formula and use plastic bottles, consider premixing the formula in a glass container, then cooling it down before transferring it to the feeding bottle.

2. Rinse heat-sterilized plastic bottles before adding formula or breastmilk

If you use heat to sterilize plastic bottles, leave them to cool then rinse them several times before filling them with formula or breastmilk, Lerner suggested.

3. Consider glass or silicone over plastic bottles

If your baby prefers warmed milk or formula, consider heating it in a glass or silicone bottle. (If you don't use a bottle warmer, we have advice about how to safely do this without one.) The Philips Avent Glass Natural Response Baby Bottle  is our recommendation for the best glass baby bottle.

Philips Avent Glass Natural Response Baby Bottle

Our favorite glass bottles.

With only three pieces and a large, easy-to-screw-on collar, this glass bottle is simple to use and didn’t leak in our test. But the very wide nipple may not work well for all babies.

4. Wash hands before eating

For young kids who eat with their hands, try to establish a habit of handwashing before eating, said Woodruff. While handwashing is not always possible, it can help reduce exposure from touching microplastics in dust and soil (and maybe, just maybe, stem the tide of germs).

How worried should you be about microplastics?

Scientists are still studying the exact connections between these teeny tiny pieces of plastic and human health. But it’s clear that exposure to plastic—whether it’s those tiny particles, the chemicals they leach, or a combination—is being linked to a variety of worrying health issues.

Some of those connections still require more research, such as ties to colon cancer , respiratory disease , metabolic function , and disruption to endocrine systems , while others—like a recent study that found those with levels of plastics in their arteries were at a higher risk for heart attacks, strokes, and death—seem a little more clear.

It’s important to remember that these links point to concerns about the impact of microplastics on public health, but they are not specific, predictable outcomes. “What I’m thinking about is population risk, not a risk to a specific individual,” said Goddard.

The tricky thing is that microplastics and nanoplastics are impossible to avoid, no matter how diligent you are: They’re in the air we breathe , our drinking water , and our food. But scientists aren’t sure what levels of microplastics and nanoplastics we’re each taking in from those sources.

The oft-cited estimate that the average person eats a credit card’s worth of plastic every week has been called into question . But our bodies are certainly taking in plastic, and that’s more than nature intended.

Given the growing body of evidence, it’s possible that we’ll start to see more public health measures that address microplastic pollution. Until then, taking care of your overall health is the first line of defense, followed by taking reasonable steps to reduce microplastic exposure.

This article was edited by Christine Cyr Clisset and Ben Frumin.

Tracey Woodruff, director of the Program on Reproductive Health and the Environment at UCSF , phone interview , April 25, 2024

Gillian Goddard, MD, endocrinologist and adjunct assistant professor at NYU Langone Hospital and author of “Hot Flash” newsletter from ParentData , phone interview , April 26, 2024

Carlos Lerner, MD, pediatrician at the Children’s Health Center at UCLA and professor and Jack H. Skirball endowed chair in Pediatrics at UCLA , email interview , April 26, 2024

Hayley Goldbach, MD, board-certified physician and dermatologic surgeon at Brown University , email interview , April 29, 2024

Meet your guide

Katie Okamoto

Katie Okamoto is an editor on the discovery team and leads Wirecutter’s sustainability coverage. She has been covering products—from food to furniture—and their intersections with environmental impact and environmental health for more than a decade. Previously, Katie was an editor at Metropolis Magazine.

Mentioned above

• With eight different picks, we’ve found water bottles suited for everyone from gym rats to frequent travelers. The 8 Best Water Bottles  
• The affordable, leak-resistant Simple Modern Classic Tumbler keeps drinks cold (or warm) for hours, and it comes with both a straw lid and a flip-top lid. The Best Tumbler  
• After more than 30 hours researching hundreds of models, we’ve found the best under-sink water filtration systems for most people. Here’s what we recommend. The Best Under-Sink Water Filter  
• Water filters and pitchers are the simplest, most affordable way to get reliable filtered water at home. The Best Water Filter Pitcher and Dispenser  
• Most plastic isn’t actually recycled. These 12 tips can help you reduce your overall plastic use—and make a difference in the global plastic pollution problem. 12 Ways to Break Up With Single-Use Plastics  
• After years of using and abusing food-storage containers, we recommend the glass Pyrex Simply Store 18-Piece Set and the Snapware Total Solution 20-Piece Set. The Best Food Storage Containers  

Further reading

Silicone Kitchen Gear Isn’t As Sustainable As Many People Think. Try These Solutions Instead.

by Katie Okamoto

We share how to get the most out of silicone items you may already own, and we recommend swaps you should consider instead of buying new tools and gadgets.

The Best Reusable Produce Bags, Beeswax Wraps, and Other Ways to Reduce Plastic Waste

by Anna Perling

Our favorite alternatives to plastic or disposable food storage include silicone food-storage bags, beeswax wraps, and cloth produce bags.

Laundry Detergent Sheets Are Poor Cleaners. And Their Sustainability Claims Are Debatable.

by Andrea Barnes

Laundry detergent sheets claim to be a more-sustainable option than traditional liquid, powder, or pod detergents. Unfortunately, they don’t clean well.

Expert Tips for Freezing Food and Reducing Food Waste

by Anna Perling and Katie Okamoto

We have the best freezer containers, plus expert advice on saving money and reducing waste by getting the most from your freezer.

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Nutrition, Food and Diet in Health and Longevity: We Eat What We Are

Suresh i. s. rattan.

1 Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus, Denmark

Gurcharan Kaur

2 Department of Biotechnology, Guru Nanak Dev University, Amritsar 143005, India

Associated Data

Not applicable.

Nutrition generally refers to the macro- and micro-nutrients essential for survival, but we do not simply eat nutrition. Instead, we eat animal- and plant-based foods without always being conscious of its nutritional value. Furthermore, various cultural factors influence and shape our taste, preferences, taboos and practices towards preparing and consuming food as a meal and diet. Biogerontological understanding of ageing has identified food as one of the three foundational pillars of health and survival. Here we address the issues of nutrition, food and diet by analyzing the biological importance of macro- and micro-nutrients including hormetins, discussing the health claims for various types of food, and by reviewing the general principles of healthy dietary patterns, including meal timing, caloric restriction, and intermittent fasting. We also present our views about the need for refining our approaches and strategies for future research on nutrition, food and diet by incorporating the molecular, physiological, cultural and personal aspects of this crucial pillar of health, healthy ageing and longevity.

1. Introduction

The terms nutrition, food and diet are often used interchangeably. However, whereas nutrition generally refers to the macro- and micro-nutrients essential for survival, we do not simply eat nutrition, which could, in principle, be done in the form of a pill. Instead, we eat food which normally originates from animal- and plant-based sources, without us being aware of or conscious of its nutritional value. Even more importantly, various cultural factors influence and shape our taste, preferences, taboos and practices towards preparing and consuming food as a meal and diet [ 1 ]. Furthermore, geo-political-economic factors, such as governmental policies that oversee the production and consumption of genetically modified foods, geological/climatic challenges of growing such crops in different countries, and the economic affordability of different populations for such foods, also influence dietary habits and practices [ 2 , 3 ]. On top of all this lurks the social evolutionary history of our species, previously moving towards agriculture-based societies from the hunter-gatherer lifestyle, now becoming the consumers of industrially processed food products that affect our general state of health, the emergence of diseases, and overall lifespan [ 1 , 4 ]. The aim of this article is to provide a commentary and perspective on nutrition, food and diet in the context of health, healthy ageing and longevity.

Biogerontological understanding of ageing has identified food as one of the three foundational pillars of health and survival. The other two pillars, especially in the case of human beings, are physical exercise and socio-mental engagement [ 5 , 6 , 7 ]. A huge body of scientific and evidence-based information has been amassed with respect to the qualitative and quantitative nature of optimal nutrition for human health and survival. Furthermore, a lot more knowledge has developed regarding how different types of foods provide different kinds of nutrition to different extents, and how different dietary practices have either health-beneficial or health-harming effects.

Here we endeavor to address these issues of nutrition, food and diet by analyzing the biological importance of macro- and micro-nutrients, and by discussing the health-claims about animal-based versus plant-based foods, fermented foods, anti-inflammatory foods, functional foods, foods for brain health, and so on. Finally, we discuss the general principles of healthy dietary patterns, including the importance of circadian rhythms, meal timing, chronic caloric restriction (CR), and intermittent fasting for healthy ageing and extended lifespan [ 8 , 9 ]. We also present our views about the need for refining our approaches and strategies for future research on nutrition, food and diet by incorporating the molecular, physiological, cultural and personal aspects of this crucial pillar of health, healthy ageing and longevity.

2. Nutrition for Healthy Ageing

The science of nutrition or the “nutritional science” is a highly advanced field of study, and numerous excellent books, journals and other resources are available for fundamental information about all nutritional components [ 10 ]. Briefly, the three essential macronutrients which provide the basic materials for building biological structures and for producing energy required for all physiological and biochemical processes are proteins, carbohydrates and lipids. Additionally, about 18 micronutrients, comprised of minerals and vitamins, facilitate the optimal utilization of macronutrients via their role in the catalysis of numerous biochemical processes, in the enhancement of their bioavailability and absorption, and in the balancing of the microbiome. Scientific literature is full of information about almost all nutritional components with respect to their importance and role in basic metabolism for survival and health throughout one’s life [ 10 ].

In the context of ageing, a major challenge to maintain health in old age is the imbalanced nutritional intake resulting into nutritional deficiency or malnutrition [ 11 , 12 ]. Among the various reasons for such a condition is the age-related decline in the digestive and metabolic activities, exacerbated by a reduced sense of taste and smell and worsening oral health, including the ability to chew and swallow [ 13 , 14 ]. Furthermore, an increased dependency of the older persons on medications for the management or treatment of various chronic conditions can be antagonistic to certain essential nutrients. For example, long term use of metformin, which is the most frequently prescribed drug against Type 2 diabetes, reduces the levels of vitamin B12 and folate in the body [ 15 , 16 ]. Some other well-known examples of the drugs used for the management or treatment of age-related conditions are cholesterol-lowering medicine statin which can cause coenzyme Q10 levels to be too low; various diuretics (water pills) can cause potassium levels to be too low; and antacids can decrease the levels of vitamin B12, calcium, magnesium and other minerals [ 15 , 16 ]. Thus, medications used in the treatment of chronic diseases in old age can also be “nutrient wasting” or “anti-nutrient” and may cause a decrease in the absorption, bioavailability and utilization of essential micronutrients and may have deleterious effects to health [ 11 ]. In contrast, many nutritional components have the potential to interact with various drugs leading to reduced therapeutic efficacy of the drug or increased adverse effects of the drug, which can have serious health consequences. For example, calcium in dairy products like milk, cheese and yoghurt can inhibit the absorption of antibiotics in the tetracycline and quinolone class, thus compromising their ability to treat infection effectively. Some other well-known examples of food sources which can alter the pharmacokinetics and pharmacodynamics of various drugs are grape fruits, bananas, apple juice, orange juice, soybean flour, walnuts and high-fiber foods (see: https://www.aarp.org/health/drugs-supplements/info-2022/food-medication-interaction.html (accessed on 13 November 2022)).

It is also known that the nutritional requirements of older persons differ both qualitatively and quantitatively from young adults [ 11 ]. This is mainly attributed to the age-related decline in the bioavailability of nutrients, reduced appetite, also known as ‘anorexia of ageing,’ as well as energy expenditure [ 12 , 17 , 18 ]. Therefore, in order to maintain a healthy energy balance, the daily uptake of total calories may need to be curtailed without adversely affecting the nutritional balance. This may be achieved by using nutritional supplements with various vitamins, minerals and other micronutrients, without adding to the burden of total calories [ 12 , 17 , 18 ]. More recently, the science of nutrigenomics (how various nutrients affect gene expression), and the science of nutrigenetics (how individual genetic variations respond to different nutrients) are generating novel and important information on the role of nutrients in health, survival and longevity.

3. Food for Healthy Ageing

The concept of healthy ageing is still being debated among biogerontologists, social-gerontologists and medical practioners. It is generally agreed that an adequate physical and mental independence in the activities of daily living can be a pragmatic definition of health in old age [ 7 ]. Thus, healthy ageing can be understood as a state of maintaining, recovering and enhancing health in old age, and the foods and dietary practices which facilitate achieving this state can be termed as healthy foods and diets.

From this perspective, although nutritional requirements for a healthy and long life could be, in principle, fulfilled by simply taking macro- and micro-nutrients in their pure chemical forms, that is not realistic, practical, attractive or acceptable to most people. In practice, nutrition is obtained by consuming animals and plants as sources of proteins, carbohydrates, fats and micronutrients. There is a plethora of tested and reliable information available about various food sources with respect to the types and proportion of various nutrients present in them. However, there are still ongoing discussions and debates as to what food sources are best for human health and longevity [ 19 , 20 ]. Often such discussions are emotionally highly charged with arguments based on faith, traditions, economy and, more recently, on political views with respect to the present global climate crisis and sustainability.

Scientifically, there is no ideal food for health and longevity. Varying agricultural and food production practices affect the nutritional composition, durability and health beneficial values of various foods. Furthermore, the highly complex “science of cooking” [ 21 ], evolved globally during thousands of years of human cultural evolution, has discovered the pros and cons of food preparation methods such as soaking, boiling, frying, roasting, fermenting and other modes of extracting, all with respect to how best to use these food sources for increasing the digestibility and bioavailability of various nutrients, as well as how to eliminate the dangers and toxic effects of other chemicals present in the food.

The science of food preparation and utilization has also discovered some paradoxical uses of natural compounds, especially the phytochemicals such as polyphenols, flavonoids, terpenoids and others. Most of these compounds are produced by plants as toxins in response to various stresses, and as defenses against microbial infections [ 22 , 23 ]. However, humans have discovered, mostly by trial and error, that numerous such toxic compounds present in algae, fungi, herbs and other sources can be used in small doses as spices and condiments with potential benefits of food preservation, taste enhancement and health promotion [ 23 ].

The phenomenon of “physiological hormesis” [ 24 ] is a special example of the health beneficial effects of phytotoxins. According to the concept of hormesis, a deliberate and repeated use of low doses of natural or synthetic toxins in the food can induce one or more stress responses in cells and tissues, followed by the stimulation of numerous defensive repair and maintenance processes [ 25 , 26 ]. Such hormesis-inducing compounds and other conditions are known as hormetins, categorized as nutritional, physical, biological and mental hormetins [ 27 , 28 , 29 ]. Of these, nutritional hormetins, present naturally in the food or as synthetic hormetins to be used as food supplements, are attracting great attention from food-researchers and the nutraceutical and cosmeceutical industry [ 27 , 30 ]. Other food supplements being tested and promoted for health and longevity are various prebiotics and probiotics strengthening and balancing our gut microbiota [ 31 , 32 , 33 ].

Recently, food corporations in pursuit of both exploiting and creating a market for healthy ageing products, have taken many initiatives in producing new products under the flagship of nutraceuticals, super-foods, functional foods, etc. Such products are claimed and marketed not only for their nutritional value, but also for their therapeutic potentials [ 10 ]. Often the claims for such foods are hyped and endorsed as, for example, anti-inflammatory foods, food for the brain, food for physical endurance, complete foods, anti-ageing foods and so on [ 34 , 35 , 36 ]. Traditional foods enriched with a variety of minerals, vitamins and hormetins are generally promoted as “functional foods” [ 37 ]. Even in the case of milk and dairy products, novel and innovative formulations are claimed to improve their functionality and health promotional abilities [ 38 ]. However, there is yet a lot to be discovered and understood about such reformulated, fortified and redesigned foods with respect to their short- and long-term effects on physiology, microbiota balance and metabolic disorders in the context of health and longevity.

4. Diet and Culture for Healthy and Long Life

What elevates food to become diet and a meal is the manner and the context in which that food is consumed [ 4 ]. Numerous traditional and socio-cultural facets of dietary habits can be even more significant than their molecular, biochemical, and physiological concerns regarding their nutritional ingredients and composition. For example, various well-known diets, such as the paleo, the ketogenic, the Chinese, the Ayurvedic, the Mediterranean, the kosher, the halal, the vegetarian, and more recently, the vegan diet, are some of the diverse expressions of such cultural, social, and political practices [ 1 ]. The consequent health-related claims of such varied dietary patterns have influenced their acceptance and adaptation globally and cross-culturally.

Furthermore, our rapidly developing understanding about how biological daily rhythms affect and regulate nutritional needs, termed “chrono-nutrition”, has become a crucial aspect of optimal and healthy eating habits [ 39 , 40 ]. A similar situation is the so-called “nutrient timing” that involves consuming food at strategic times for achieving certain specific outcomes, such as weight reduction, muscle strength, and athletic performance. The meal-timing and dietary patterns are more anticipatory of health-related outcomes than any specific foods or nutrients by themselves [ 41 , 42 , 43 , 44 ]. However, encouraging people to adopt healthy dietary patterns and meal-timing requires both the availability, accessibility and affordability of food, and the intentional, cultural and behavioral preferences of the people.

Looking back at the widely varying and constantly changing cultural history of human dietary practices, one realizes that elaborate social practices, rituals and normative behaviors for obtaining, preparing and consuming food, are often more critical aspects of health-preservation and health-promotion than just the right combination of nutrients. Therefore, one cannot decide on a universal food composition and consumption pattern ignoring the history and the cultural practices and preferences of the consumers. After all, “we eat what we are”, and not, as the old adage says, “we are what we eat”.

5. Conclusions and Perspectives

Food is certainly one of the foundational pillars of good and sustained health. Directed and selective evolution through agricultural practices and experimental manipulation and modification of food components have been among the primary targets for improving food quality. This is further authenticated by extensive research performed, mainly on experimental animal and cell culture model systems, demonstrating the health-promoting effects of individual nutritional components and biological extracts in the regulation, inhibition or stimulation of different molecular pathways with reference to healthy ageing and longevity [ 45 ]. Similarly, individual nutrients or a combination of a few nutrients are being tested for their potential use as calorie restriction mimetics, hormetins and senolytics [ 46 , 47 , 48 ]. However, most commonly, these therapeutic strategies follow the traditional “one target, one missile” pharmaceutical-like approach, and consider ageing as a treatable disease. Based on the results obtained from such experimental studies, the claims and promises made which can often be either naïve extrapolations from experimental model systems to human applications, or exaggerated claims and even false promises [ 49 ].

Other innovative, and possibly holistic, food- and diet-based interventional strategies for healthy ageing are adopting regimens such as caloric- and dietary-restriction, as well as time-restricted eating (TRE). Intermittent fasting (IF), the regimen based on manipulating the eating/fasting timing, is another promising interventional strategy for healthy ageing. Chrono-nutrition, which denotes the link between circadian rhythms and nutrient-sensing pathways, is a novel concept illustrating how meal timings alignment with the inherent molecular clocks of the cells functions to preserve metabolic health. TRE, which is a variant of the IF regimen, claims that food intake timing in alignment with the circadian rhythm is more beneficial for health and longevity [ 39 , 40 , 41 , 50 ]. Moreover, TRE has translational benefits and is easy to complete in the long term as it only requires limiting the eating time to 8–10 h during the day and the fasting window of 12–16 h without restricting the amount of calories consumed. Some pilot studies on the TRE regimen have reported improvement in glucose tolerance and the management of body weight and blood pressure in obese adults as well as men at risk of T2D. Meta-analyses of several pilot scale studies in human subjects suggest and support the beneficial effects of a TRE regimen on several health indicators [ 39 , 50 ]. Several other practical recommendations, based on human clinical trials have also been recommended for meeting the optimal requirements of nutrition in old age, and for preventing or slowing down the progression of metabolic syndromes [ 39 , 40 , 41 , 50 ].

What we have earlier discussed in detail [ 4 ] is supported by the following quote: “…food is more than just being one of the three pillars of health. Food is both the foundation and the scaffolding for the building and survival of an organism on a daily basis. Scientific research on the macro- and micro-nutrient components of food has developed deep understanding of their molecular, biochemical and physiological roles and modes of action. Various recommendations are repeatedly made and modified for some optimal daily requirements of nutrients for maintaining and enhancing health, and for the prevention and treatment of diseases. Can we envisage developing a “nutrition pill” for perfect health, which could be used globally, across cultures, and at all ages? We don’t think so” [ 4 ].

Our present knowledge about the need and significance of nutrients is mostly gathered from the experimental studies using individual active components isolated from various food sources. In reality, however, these nutritional components co-exist interactively with numerous other compounds, and often become chemically modified through the process of cooking and preservation, affecting their stability and bioavailability. There is still a lot to be understood about how the combination of foods, cooking methods and dietary practices affect health-related outcomes, especially with respect to ageing and healthspan.

An abundance of folk knowledge in all cultures about food-related ‘dos and don’ts’ requires scientific verification and validation. We also need to reconsider and change our present scientific protocols for nutritional research, which seem to be impractical for food and dietary research at the level of the population. It is a great scientific achievement that we have amassed a body of information with respect to the nature of nutritional components required for health and survival, the foods which can provide those nutritional components and the variety of dietary and eating practices which seem to be optimal for healthy survival and longevity.

Finally, whereas abundant availability of and accessibility to food in some parts of the world has led to over-consumption and consequent life-style-induced metabolic diseases and obesity, in many other parts of the world food scarcity and economic disparity continue to perpetuate starvation, malnutrition, poor health and shortened lifespan. Often, it is not a lack of knowledge about the optimal nutrition, food and diet that leads to making bad choices; rather, it is either our inability to access and afford healthy foods or our gullibility to fall prey to the exaggerated claims in the commercial interests of food producing and marketing companies. We must continue to gather more scientific information and knowledge about the biochemical, physiological and cultural aspects of nutrition, food and diet, which should then be recommended and applied wisely and globally, incorporating the social, cultural and environmental needs of all. After all, “we eat what we are”, and not merely “we are what we eat”!

Funding Statement

One of the authors, GK, was funded by the Department of Science & Technology (DST) under Cognitive Science Research Initiative (CSRI), Government of India, grant (DST/CSRI/2018/99). This funding agency has no role in study design, manuscript writing, and data interpretation.

Author Contributions

Both authors (S.I.S.R. and G.K.) conceptualized and wrote the paper equally. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Certificate of need laws con rural patients out of health care

By Sofia Hamilton and Thomas Kimbrell June 14, 2024

N ews watchers around the U.S. have likely seen the warnings: without certificate of need (CON) laws, hospitals will be forced to close their doors when for-profit organizations open and cherry pick commercially insured patients, leaving those in rural areas without care. The reality is that even with certificate of need laws in place, rural patients are already without care . States with these laws have 30% fewer rural hospitals and 13% fewer rural ambulatory surgical centers.

CON laws require a state government to approve the establishment or expansion of health care facilities, services, or equipment. These certificates are essentially a government-mandated permission slip that individual health care providers, physician groups, hospitals, and health systems must obtain before they are allowed to care for patients. Essentially, CON laws empower bureaucrats to decide what health care services are offered, instead of that decision being driven by patients’ needs.

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Facilities and services regulated under CON laws vary from state to state , but there is significant overlap. In many states, health care professionals or systems that want to open a nursing home , psychiatric or substance abuse treatment facility, birthing center , or ambulatory surgical center must first obtain a certificate of need. The same goes for those seeking to offer MRI , ultrasound, or other diagnostic services . Hospital systems that want to develop or expand neonatal intensive care units or burn units to provide necessary, lifesaving care must first navigate the lengthy CON process before being allowed to legally treat these vulnerable patients.

Certificate of need laws restrict access to health care services by artificially limiting the establishment and expansion of health care facilities. In some cases, CON schemes prevent providers from offering low-cost alternatives to hospital care. For example, CON laws barred an ophthalmologist from performing eye surgeries at his facility in North Carolina, and blocked an aspiring entrepreneur from opening a birthing center in Georgia. In other cases, CON programs stopped construction of hospitals in counties without one. In South Carolina, legal wrangling over certificate of need delayed the opening of a hospital for nearly two decades after the state identified the need for one in York County.

Related: Rural hospitals are closing labor and delivery services. Babies’ lives are in jeopardy

By 1972, more than half of U.S. states had enacted certificate of need laws. In 1974, the federal government coerced the remaining states to implement their own CON laws by threatening to withhold federal funding for health care facilities. But the federal government made a course correction in 1986 and repealed that law after CON laws failed to reduce health care costs. Since then, every presidential administration has implored state governments to repeal their certificate of need laws.

Like many bad policies, certificate of need laws were established with good intentions. Policymakers believed that certificates of need would control health care costs for patients by reducing waste and duplicity.

In practice, however, the aptly named CON laws artificially limit the health care market and drive up costs, effectively conning patients out of access to affordable care. Basic economics says that supply controls do not decrease prices — they actually do the opposite. CON laws negatively affect individuals in cities, suburbs, and beyond by increasing wait times, limiting choices , and inflating costs . In rural communities where the supply of health care is already limited, these controls can lead to life-threatening problems .

Unsurprisingly, the loudest defenders of certificate of need requirements are incumbent providers who benefit greatly from this monopolistic system that crowds out competition.

So far, 12 states have followed the federal government’s guidance to repeal their certificate of need laws. The current legislative session has seen some minor successes. Georgia passed a bill exempting psychiatric and substance abuse inpatient programs, basic prenatal services, birthing centers, and general acute hospitals from the state’s CON process. Likewise, Tennessee passed a bill removing CON requirements for several services as well as medical facilities in counties without an acute care hospital. Both bills follow last year’s massive success in South Carolina which passed a full repeal of certificates of need for virtually all services.

Related: Medicare offers financial perks for rural hospitals that convert to its new provider type. Will they bite?

These reforms follow a national trend of states reducing the regulatory burdens of their certificate of need laws: Montana reformed its CON law to cover only long-term care facilities in 2021; Florida eliminated CON requirements for numerous services in 2019; and West Virginia removed CON requirements for birthing centers and all hospital services in 2023 after exempting telehealth, remedial care, imaging services, and ambulatory health facilities in 2017.

Some states, however, continue to drag their heels. In 2023, the Kentucky General Assembly formed a legislative task force to study reforming its certificate of need program. After six months, the task force issued a disappointing one-sentence recommendation for “further study.” Earlier this year, the Mississippi House and Senate passed differing versions of a limited reform bill that would have exempted from its CON law chemical dependency and psychiatric services and birthing centers, but the bill died last month after the two chambers could not agree on the details, leaving in place unnecessary barriers between health care providers and some of Mississippi’s most vulnerable people.

Health care systems in states that have repealed their CON requirements have not fallen apart, as hospital associations had predicted. In actuality, states that have repealed their programs have seen increases in health care investment . Research also shows that safety-net hospitals in states without CON laws had considerably higher margins than safety-net hospitals in states with these laws.

The successes of these reforms have prompted some CON defenders to begin making concessions to their long-standing opposition to repealing these laws. In 2023, for example, the Kentucky Hospital Association proposed CON “modernization” reforms that would “provide flexibility for existing Kentucky hospitals to improve patient service” by allowing existing hospitals to receive expedited CON reviews for several types of services and facilities. These same conveniences, however, would not be extended to other providers that apply for certificates of need. The Georgia Hospital Association recommended similar reforms to allow existing hospitals to add, expand, or relocate services without a certificate of need but leave CON requirements in place for new providers.

Decades after their implementation, the touted benefits of certificate of need laws have not been realized. Instead, the regulations have unnecessarily limited the supply of, and access to, quality health care options for all Americans. The rollback and repeal of CON laws will allow patients and providers to access each other without the unnecessary intrusion of the government.

Maintaining CON regimes at the behest of incumbent providers will only enrich their bottom lines at the expense of the health and safety of rural communities.

Sofia Hamilton is a policy analyst at Americans for Prosperity. Thomas Kimbrell is an investigative analyst at Americans for Prosperity Foundation.

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