Analysis of the health economics portfolio funded by the National Institutes of Health in response to published guidance.

Health services, economics, and outcomes research (referred to as health economics research hereinafter) is one of the interdisciplinary sciences that the National Institutes of Health (NIH) supports in order to pursue its overall mission to improve health. In 2015, NIH guidance was published to clarify the type of health economics research that NIH would continue to fund. This analysis aimed to determine if there were changes in the number of health economics applications received and funded by NIH after the release of the guidance. Health economics applications submitted to NIH both before and after publication of the guidance were identified using a machine learning approach with input from subject matter experts. Application and funding trends were examined by fiscal year, method of application (solicited vs. unsolicited), and activity code. This study found that application and funding rates of health economics research were decreasing prior to guidance. Following publication of this guidance, the application and funding rate of health economics applications increased.

Advancing digital health equity: Directions for behavioral and social science research.

The field of digital health is evolving rapidly and encompasses a wide range of complex and changing technologies used to support individual and population health. The COVID-19 pandemic has augmented digital health expansion and significantly changed how digital health technologies are used. To ensure that these technologies do not create or exacerbate existing health disparities, a multi-pronged and comprehensive research approach is needed. In this commentary, we outline five recommendations for behavioral and social science researchers that are critical to promoting digital health equity. These recommendations include: (i) centering equity in research teams and theoretical approaches, (ii) focusing on issues of digital health literacy and engagement, (iii) using methods that elevate perspectives and needs of underserved populations, (iv) ensuring ethical approaches for collecting and using digital health data, and (v) developing strategies for integrating digital health tools within and across systems and settings. Taken together, these recommendations can help advance the science of digital health equity and justice.

The field of digital health is quickly growing and changing. Digital health technologies have the potential to increase access to health-related information and healthcare and improve wellbeing, but it is important that those technologies don't widen existing health disparities or create new ones. Behavioral and social science researchers have a key role to play in centering equity in their research teams and theoretical approaches, focusing on key barriers to access, uptake, and usage, studying digital health in ways that elevate the voices and needs of historically underserved groups, being thoughtful about how digital health data are collected and used, and making sure that digital health tools are designed to be used in real-world settings.

Ending Sexual Harassment in Science: Designing and Administering a Survey That Can Lead to an Improved Organizational Climate.

Workplace harassment, particularly sexual harassment, has substantial negative implications for individuals and organizations and for scientific advancement. The National Institutes of Health (NIH) is uniquely positioned to lead the effort to prevent sexual harassment in the scientific community and mitigate its detrimental effects. Recognizing the need for benchmark data, NIH developed and validated the 2019 NIH Workplace Climate and Harassment Survey. The goal was to use best practices in survey design methods to create an instrument for rigorous assessment of harassment incidence and organizational climate predictors of sexual harassment in scientific research environments. This article summarizes the processes used to design and administer the NIH survey and provides brief descriptions of 3 products of the process developed to guide scientific institutions wishing to embark on a data-driven approach to assess and prevent harassment: a document detailing survey development and methods, a survey implementation guide, and the key findings obtained from the survey, including recommendations for interventions targeting the organizational climate at NIH and limitations of the survey. The survey identified that 1 in 5 respondents had experienced sexual harassment in the 12 months preceding their participation in the survey and that women, sexual and gender minorities, younger respondents, trainees/students, and individuals with a disability were more likely to have experienced sexual harassment. Those who had experienced sexual harassment during that period were also more likely to have experienced incivility, bullying, and intimidating behaviors in the workplace. NIH intends to use the survey findings as a quality assurance and quality improvement guide to inform future activities to prevent and address harassment across NIH.

Social Determinants of Health and Implementation Research: Lessons from the COVID-19 Pandemic.

During the past three decades, the world has experienced many clinical and public health challenges that require implementation of practices and policies informed by an understanding of social determinants of health and health inequities, but perhaps none as global and pervasive as the current COVID-19 pandemic. In the context of this special themed issue on Social Determinants of Health and Implementation Research: Three Decades of Progress and a Need for Convergence, we highlight the application of social determinants of health and implementation research on various aspects of the COVID-19 pandemic.

Publication rates from biomedical and behavioral and social science R01s funded by the National Institutes of Health.

Prior research has shown a serious lack of research transparency resulting from the failure to publish study results in a timely manner. The National Institutes of Health (NIH) has increased its use of publication rate and time to publication as metrics for grant productivity. In this study, we analyze the publications associated with all R01 and U01 grants funded from 2008 through 2014, providing sufficient time for these grants to publish their findings, and identify predictors of time to publication based on a number of variables, including if a grant was coded as a behavioral and social sciences research (BSSR) grant or not. Overall, 2.4% of the 27,016 R01 and U01 grants did not have a publication associated with the grant within 60 months of the project start date, and this rate of zero publications was higher for BSSR grants (4.6%) than for non-BSSR grants (1.9%). Mean time in months to first publication was 15.2 months, longer for BSSR grants (22.4 months) than non-BSSR grants (13.6 months). Survival curves showed a more rapid reduction of risk to publish from non-BSSR vs BSSR grants. Cox regression models showed that human research (vs. animal, neither, or both) and clinical trials research (vs. not) are the strongest predictors of time to publication and failure to publish, but even after accounting for these and other predictors, BSSR grants continued to show longer times to first publication and greater risk of no publications than non-BSSR grants. These findings indicate that even with liberal criteria for publication (any publication associated with a grant), a small percentage of R01 and U01 grantees fail to publish in a timely manner, and that a number of factors, including human research, clinical trial research, child research, not being an early stage investigator, and conducting behavioral and social sciences research increase the risk of time to first publication.

National Institutes of Health social and behavioral research in response to the SARS-CoV2 Pandemic.

The COVID-19 pandemic has been mitigated primarily using social and behavioral intervention strategies, and these strategies have social and economic impacts, as well as potential downstream health impacts that require further study. Digital and community-based interventions are being increasingly relied upon to address these health impacts and bridge the gap in health care access despite insufficient research of these interventions as a replacement for, not an adjunct to, in-person clinical care. As SARS-CoV-2 testing expands, research on encouraging uptake and appropriate interpretation of these test results is needed. All of these issues are disproportionately impacting underserved, vulnerable, and health disparities populations. This commentary describes the various initiatives of the National Institutes of Health to address these social, behavioral, economic, and health disparities impacts of the pandemic, the findings from which can improve our response to the current pandemic and prepare us better for future infectious disease outbreaks.

Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions.

Mobile health (mHealth) technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social Cognitive Theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the MILES study) and 2) as a means for discerning the range of "ambitious but doable" daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts, and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

National Institutes of Health Support of Digital Health Behavior Research.

The National Institutes of Health (NIH) has increasingly supported research in digital health technologies to advance research and deliver behavior change interventions. We highlight some of the research supported by the NIH in eHealth, mHealth, and social media as well as research resources supported by the NIH to accelerate research in this area. We also describe some of the challenges and opportunities in the digital health field and the need to balance the promise of these technologies with rigorous scientific evidence.

Key milestones during 40 years of behavioral medicine at the National Institutes of Health.

The National Institutes of Health (NIH) has played a major role in promoting behavioral medicine research over the past 40 years through funding, review, and priority-setting activities and programs including scientific conferences, meetings, workgroups, intramural research, and training opportunities. In this review of NIH activities in support of behavioral medicine over the past four decades, we highlight key events, programs, projects, and milestones that demonstrate the many ways in which the NIH has supported behavioral and social sciences research and advanced the public health while contributing to the evolution of behavioral medicine as a scientific field.

The selection of comparators for randomized controlled trials of health-related behavioral interventions: recommendations of an NIH expert panel.

OBJECTIVES: To provide recommendations for the selection of comparators for randomized controlled trials of health-related behavioral interventions. STUDY DESIGN AND SETTING: The National Institutes of Health Office of Behavioral and Social Science Research convened an expert panel to critically review the literature on control or comparison groups for behavioral trials and to develop strategies for improving comparator choices and for resolving controversies and disagreements about comparators. RESULTS: The panel developed a Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials. The model indicates that the optimal comparator is the one that best serves the primary purpose of the trial but that the optimal comparator's limitations and barriers to its use must also be taken into account. CONCLUSION: We developed best practice recommendations for the selection of comparators for health-related behavioral trials. Use of the Pragmatic Model for Comparator Selection in Health-Related Behavioral Trials can improve the comparator selection process and help resolve disagreements about comparator choices.

Blood Pressure, Sexual Activity, and Erectile Function in Hypertensive Men: Baseline Findings from the Systolic Blood Pressure Intervention Trial (SPRINT).

INTRODUCTION: Erectile function, an important aspect of quality of life, is gaining increased research and clinical attention in older men with hypertension. AIM: To assess the cross-sectional association between blood pressure measures (systolic blood pressure [SBP]; diastolic blood pressure [DBP]; and pulse pressure [PP]) and (i) sexual activity and (ii) erectile function in hypertensive men. METHODS: We performed analyses of 1,255 male participants in a larger randomized clinical trial of 9,361 men and women with hypertension aged ≥50 years. MAIN OUTCOME MEASURES: The main outcome measures were self-reported sexual activity (yes/no) and erectile function using the 5-item International Index of Erectile Function (IIEF-5). RESULTS: 857 participants (68.3%) reported being sexually active during the previous 4 weeks. The mean (SD) IIEF-5 score for sexually active participants was 18.0 (5.8), and 59.9% of the sample reported an IIEF-5 score <21, suggesting erectile dysfunction (ED). In adjusted logistic regression models, neither SBP (adjusted odds ratio = 0.998; P = .707) nor DBP (adjusted odds ratio = 1.001; P = .929) was significantly associated with sexual activity. In multivariable linear regression analyses in sexually active participants, lower SBP (ß = -0.04; P = .025) and higher DBP (ß = 0.05; P = .029) were associated with better erectile function. In additional multivariable analyses, lower PP pressure was associated with better erectile function (ß = -0.04; P = .02). CLINICAL IMPLICATIONS: Blood pressure is an important consideration in the assessment of erectile function in men with hypertension. STRENGTHS & LIMITATIONS: Assessments of blood pressure and clinical and psychosocial variables were performed using rigorous methods in this multi-ethnic and geographically diverse sample. However, these cross-sectional analyses did not include assessment of androgen or testosterone levels. CONCLUSIONS: Erectile dysfunction was highly prevalent in this sample of men with hypertension, and SBP, DBP, and PP were associated with erectile function in this sample. Foy CG, Newman JC, Berlowitz DR, et al. Blood Pressure, Sexual Activity, and Erectile Function in Hypertensive Men: Baseline Findings from the Systolic Blood Pressure Intervention Trial (SPRINT). J Sex Med 2019;16:235-247.