SBM's two journals, Annals of Behavioral Medicine and Translational Behavioral Medicine: Practice, Policy, Research (TBM), continuously publish online articles, many of which become available before issues are printed. Three recently published Annals and TBM articles are listed below.
SBM members who have paid their 2021 membership dues are able to access the full text of all Annals and TBM online articles via the SBM website by following the steps below.
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Background
Investigating antecedents of behaviors, such as wearing face coverings, is critical for developing strategies to prevent SARS-CoV-2 transmission.
Purpose
The purpose of this study was to determine associations between theory-based behavioral predictors of intention to wear a face covering and actual wearing of a face covering in public.
Methods
Data from a cross-sectional panel survey of U.S. adults conducted in May and June 2020 (N = 1,004) were used to test a theory-based behavioral path model. We (a) examined predictors of intention to wear a face covering, (b) reported use of cloth face coverings, and (c) reported use of other face masks (e.g., a surgical mask or N95 respirator) in public.
Results
We found that being female, perceived importance of others wanting the respondent to wear a face covering, confidence to wear a face covering, and perceived importance of personal face covering use was positively associated with intention to wear a face covering in public. Intention to wear a face covering was positively associated with self-reported wearing of a cloth face covering if other people were observed wearing cloth face coverings in public at least “rarely” (aOR = 1.43), with stronger associations if they reported “sometimes” (aOR = 1.83), “often” (aOR = 2.32), or “always” (aOR = 2.96). For other types of face masks, a positive association between intention and behavior was only present when observing others wearing face masks “often” (aOR = 1.25) or “always” (aOR = 1.48).
Conclusions
Intention to wear face coverings and observing other people wearing them are important behavioral predictors of adherence to the CDC recommendation to wear face coverings in public.
Background
Cross-sectional studies have found that the coronavirus disease 2019 (COVID-19) pandemic has negatively affected population-level mental health. Longitudinal studies are necessary to examine trajectories of change in mental health over time and identify sociodemographic groups at risk for persistent distress.
Purpose
To examine the trajectories of mental distress between March 10 and August 4, 2020, a key period during the COVID-19 pandemic.
Methods
Participants included 6,901 adults from the nationally representative Understanding America Study, surveyed at baseline between March 10 and 31, 2020, with nine follow-up assessments between April 1 and August 4, 2020. Mixed-effects logistic regression was used to examine the association between date and self-reported mental distress (measured with the four-item Patient Health Questionnaire) among U.S. adults overall and among sociodemographic subgroups defined by sex, age, race/ethnicity, household structure, federal poverty line, and census region.
Results
Compared to March 11, the odds of mental distress among U.S. adults overall were 1.84 (95% confidence interval [CI] = 1.65–2.07) times higher on April 1 and 1.92 (95% CI = 1.62–2.28) times higher on May 1; by August 1, the odds of mental distress had returned to levels comparable to March 11 (odds ratio [OR] = 0.80, 95% CI = 0.66–0.96). Females experienced a sharper increase in mental distress between March and May compared to males (females: OR = 2.29, 95% CI = 1.85–2.82; males: OR = 1.53, 95% CI = 1.15–2.02).
Conclusions
These findings highlight the trajectory of mental health symptoms during an unprecedented pandemic, including the identification of populations at risk for sustained mental distress.
Background
Priming is a process in which exposure to a stimulus activates relevant mental representations that are given increased weight in subsequent judgment tasks. Affective primes can influence affective evaluations and associations. Such influence has meaningful implications for the promotion of exercise behavior, yet there is scant research on priming effects in exercise settings.
Purpose
The purpose of the present pair of studies was to examine the efficacy of music (M), music video (MV), and music video with affective primes (PRIME) in modulating psychological responses during and immediately following an exercise bout among two distinct populations.
Methods
In Study 1, physically active participants completed a brisk walking task on a treadmill under four conditions: M, MV, PRIME, and control. Affective valence and rating of perceived exertion (RPE) were assessed during exercise and remembered/forecasted pleasure was measured immediately following each exercise bout. In Study 2, largely inactive and overweight participants completed a brisk walking task on a treadmill under two conditions: MV and PRIME. Affective valence was assessed during exercise, while exercise enjoyment and remembered/forecasted pleasure were assessed postexercise.
Results
In Study 1, PRIME yielded more positively valenced affect, remembered/forecasted pleasure, and lower RPE when compared to the other conditions (MCohen’s d for all DVs = 0.91). In Study 2, PRIME elicited more positively valenced affect, greater enjoyment, and enhanced remembered/forecasted pleasure when compared to MV (MCohen’s d for all DVs = 0.64).
Conclusions
Subliminal primes embedded in music video can elicit positive changes in psychological responses during and immediately following exercise.
Megan A McVay, David E Conroy
Behavioral medicine aims to improve the health of individuals and communities by addressing behavioral, psychosocial, and environmental contributors to health. Succeeding in this endeavor requires rigorous research and effective communication of this research to relevant stakeholders and the public at large. Both research rigor and effective communication of research may benefit from adopting transparent and open research practices, sometimes called “open science.” Such practices include preregistering designs, hypotheses, and data analysis plans; making publically available study materials, data, and analytic code; sharing preprints (works-in-progress) of articles; and publishing open access. In this commentary, we describe the evolving pressures to increase the transparency and openness of research, examine the status of open science practices in behavioral medicine, and recommend a path forward to find the right fit for these practices in behavioral medicine research.
Madalina Sucala, Heather Cole-Lewis, Danielle Arigo, Megan Oser, Stephanie Goldstein, Eric B Hekler, Michael A Diefenbach
Abstract
Digital health promises to increase intervention reach and effectiveness for a range of behavioral health outcomes. Behavioral scientists have a unique opportunity to infuse their expertise in all phases of a digital health intervention, from design to implementation. The aim of this study was to assess behavioral scientists’ interests and needs with respect to digital health endeavors, as well as gather expert insight into the role of behavioral science in the evolution of digital health. The study used a two-phased approach: (a) a survey of behavioral scientists’ current needs and interests with respect to digital health endeavors (n = 346); (b) a series of interviews with digital health stakeholders for their expert insight on the evolution of the health field (n = 15). In terms of current needs and interests, the large majority of surveyed behavioral scientists (77%) already participate in digital health projects, and from those who have not done so yet, the majority (65%) reported intending to do so in the future. In terms of the expected evolution of the digital health field, interviewed stakeholders anticipated a number of changes, from overall landscape changes through evolving models of reimbursement to more significant oversight and regulations. These findings provide a timely insight into behavioral scientists’ current needs, barriers, and attitudes toward the use of technology in health care and public health. Results might also highlight the areas where behavioral scientists can leverage their expertise to both enhance digital health’s potential to improve health, as well as to prevent the potential unintended consequences that can emerge from scaling the use of technology in health care.
Jeffrey P Haibach, Katherine D Hoerster, Lindsey Dorflinger, Lisa M McAndrew, Daniel G Cassidy, David E Goodrich, Jill E Bormann, Julie Lowery, Steven M Asch, Susan D Raffa, Tannaz Moin, Alan L Peterson, Michael G Goldstein, Tracy Neal-Walden, Gerald W Talcott, Christopher L Hunter, Sara J Knight
Abstract
Military service presents unique challenges and opportunities for health care and public health. In the USA, there are over 2 million military servicemembers, 20 million veterans, and millions more military and veteran family members. Military servicemembers and eligible family members, many veterans, and retirees receive health care through the two largest learning health care systems in the USA, managed and delivered through the Departments of Defense (DoD), Veterans Affairs (VA), and contracted health care organizations. Through a network of collaborative relationships, DoD, VA, and partnering health care and research organizations (university, corporate, community, and government) accelerate research translation into best practices and policy across the USA and beyond. This article outlines military and veteran health research translation as summarized from a collaborative workshop led by experts across health care research, practice, and administration in DoD, VA, the National Institutes of Health, and affiliated universities. Key themes and recommendations for research translation are outlined in areas of: (a) stakeholder engagement and collaboration; (b) implementation science methods; and (c) funding along the translation continuum. Overall, the ability to rapidly translate research into clinical practice and policy for positive health outcomes requires collaborative relationships among many stakeholders. This includes servicemembers, veterans, and their families along with researchers, health care clinicians, and administrators, as well as policymakers and the broader population.