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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.

The 21st Century Cures Act provides funding for key initiatives relevant to the behavioral and social sciences and includes administrative provisions that facilitate health research and increase the privacy protections of research participants. At about the same time as the passage of the Act, the National Institutes of Health Office of Behavioral and Social Sciences Research released its Strategic Plan 2017-2021, which addresses three scientific priorities: (a) improve the synergy of basic and applied behavioral and social sciences research; (b) enhance and promote the research infrastructure, methods, and measures needed to support a more cumulative and integrated approach to behavioral and social sciences; and (c) facilitate the adoption of behavioral and social sciences research findings in health research and in practice. This commentary describes the implications of the Cures Act on these scientific priorities and on the behavioral and social sciences more broadly.

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., Author(s): Susan M. Czajkowski [sup.1], William T. Riley [sup.2], Catherine M. Stoney [sup.3], William M. P. Klein [sup.1], Robert T. Croyle [sup.1] Author Affiliations: (1) 0000 0001 2297 5165, grid.94365.3d, [...]

ObjectiveTo create upper-extremity and mobility subdomain scores from the Patient-Reported Outcomes Measurement Information System (PROMIS) physical functioning adult item bank.DesignExpert reviews were used to identify upper-extremity and mobility items from the PROMIS item bank. Psychometric analyses were conducted to assess empirical support for scoring upper-extremity and mobility subdomains.SettingData were collected from the U.S. general population and multiple disease groups via self-administered surveys.ParticipantsThe sample (N=21,773) included 21,133 English-speaking adults who participated in the PROMIS wave 1 data collection and 640 Spanish-speaking Latino adults recruited separately.InterventionsNot applicable.Main outcome measuresWe used English- and Spanish-language data and existing PROMIS item parameters for the physical functioning item bank to estimate upper-extremity and mobility scores. In addition, we fit graded response models to calibrate the upper-extremity items and mobility items separately, compare separate to combined calibrations, and produce subdomain scores.ResultsAfter eliminating items because of local dependency, 16 items remained to assess upper extremity and 17 items to assess mobility. The estimated correlation between upper extremity and mobility was .59 using existing PROMIS physical functioning item parameters (r=.60 using parameters calibrated separately for upper-extremity and mobility items).ConclusionsUpper-extremity and mobility subdomains shared about 35% of the variance in common, and produced comparable scores whether calibrated separately or together. The identification of the subset of items tapping these 2 aspects of physical functioning and scored using the existing PROMIS parameters provides the option of scoring these subdomains in addition to the overall physical functioning score.

Creative use of new mobile and wearable health information and sensing technologies (mHealth) has the potential to reduce the cost of health care and improve well-being in numerous ways. These applications are being developed in a variety of domains, but rigorous research is needed to examine the potential, as well as the challenges, of utilizing mobile technologies to improve health outcomes. Currently, evidence is sparse for the efficacy of mHealth. Although these technologies may be appealing and seemingly innocuous, research is needed to assess when, where, and for whom mHealth devices, apps, and systems are efficacious. In order to outline an approach to evidence generation in the field of mHealth that would ensure research is conducted on a rigorous empirical and theoretic foundation, on August 16, 2011, researchers gathered for the mHealth Evidence Workshop at NIH. The current paper presents the results of the workshop. Although the discussions at the meeting were cross-cutting, the areas covered can be categorized broadly into three areas: (1) evaluating assessments; (2) evaluating interventions; and (3) reshaping evidence generation using mHealth. This paper brings these concepts together to describe current evaluation standards, discuss future possibilities, and set a grand goal for the emerging field of mHealth research.

Abstract Background The Consortium of Hospitals Advancing Research on Tobacco (CHART) is a network of six projects and a research coordinating unit funded by the National Heart, Lung, and Blood Institute, the National Cancer Institute, the National Institute on Drug Abuse, and the National Institutes of Health (NIH) Office of Behavioral and Social Science Research. The CHART projects will assess the effectiveness and cost-effectiveness of smoking cessation interventions initiated during hospitalization and continued post-discharge. Methods/design Along with a seventh project funded previously under the NIH Challenge grants, the CHART projects will assess smoking cessation strategies delivered to approximately 10,000 hospitalized smokers across a geographically diverse group of nearly 20 private, public, academic, and community hospitals. The CHART research coordinating unit at Kaiser Permanente Center for Health Research provides organizational and data coordination support, facilitating the development of common measures for combining data from multiple CHART projects. Discussion The targeted enrollment in CHART, if achieved, will represent the largest, most diverse pooled dataset of hospitalized smokers receiving smoking cessation assistance, and is designed to contribute to the dissemination and implementation of smoking cessation interventions provided by hospital systems.

Although rates of smoking among college-aged students continue to rise, few interventions that focus on college smokers' unique motivations and episodic smoking patterns exist. The authors developed and evaluated a prototype program targeting college students that integrates Web and cell phone technologies to deliver a smoking-cessation intervention. To guide the user through the creation and initialization of an individualized quitting program delivered by means of cell phone text messaging, the program uses assessment tools delivered with the program Web site. Forty-six regular smokers were recruited from local colleges and provided access to the program. At 6-week follow-up, 43% had made at least one 24-hour attempt to quit, and 22% were quit-based on a 7-day prevalence criterion. The findings provide support for using wireless text messages to deliver potentially effective smoking-cessation behavioral interventions to college students.Key Words: cell phones, college students, communication technologies, smoking cessation, text messaging

In recent years, there has been increasing discussion of the limitations of traditional randomized controlled trial (RCT) methodologies for the evaluation of eHealth and mHealth interventions, and in particular, the requirement that these interventions be locked down during evaluation. Locking down these interventions locks in defects and eliminates the opportunities for quality improvement and adaptation to the changing technological environment, often leading to validation of tools that are outdated by the time that trial results are published. Furthermore, because behavioral intervention technologies change frequently during real-world deployment, even if a tested intervention were deployed in the real world, its shelf life would be limited. We argue that RCTs will have greater scientific and public health value if they focus on the evaluation of intervention principles (rather than a specific locked-down version of the intervention), allowing for ongoing quality improvement modifications to the behavioral intervention technology based on the core intervention principles, while continuously improving the functionality and maintaining technological currency. This paper is an initial proposal of a framework and methodology for the conduct of trials of intervention principles (TIPs) aimed at minimizing the risks of in-trial changes to intervention technologies and maximizing the potential for knowledge acquisition. The focus on evaluation of intervention principles using clinical and usage outcomes has the potential to provide more generalizable and durable information than trials focused on a single intervention technology.

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. [ABSTRACT FROM AUTHOR]

Objective: Assess the effects of a prototype computerized food portion tutorial (CFPT). Design: Participants were randomly assigned to estimate portion sizes for selected food items either prior to or following CFPT training (between groups), and those estimating before CFPT training re-estimated portions after training (within groups). Setting: Research offices. Participants: Seventy-six adult participants without dietary restrictions. Intervention: The CFPT is a Web-based food portion training program that displays varied portions of 23 food items with user-controllable reference objects and viewing angles. Main Outcome Measures: Estimated vs. weighed portions of food items selected for a meal. Analysis: Nonparametric tests were performed on estimated vs. weighed portion differences and on accuracy ratios between and within groups. Results: A significant difference was found between conditions, both within and between groups, on the discrepancy between estimated and weighed portions for a number of the food items. Training exposure, however, resulted primarily in a shift from underestimation to overestimation, not more accurate estimation. Implications for Research and Practice: The CFPT produced a significant impact on food portion estimation but appeared to sensitize participants to underestimation errors, leading to overestimation errors. Computerization of food portion training programs holds promise for providing cost-efficient portion estimation training but requires further development and evaluation before being considered for clinical use. Key Words: computer-assisted instruction, dietary assessment, education-internet, nutrition education research

Increased adoption of empirically supported treatments (ESTs) has been hindered in part by inadequate and inconvenient access to EST information and training. To improve diffusion of ESTs, the authors developed a Web application to provide practitioners with concise information by disorder on ESTs. The resulting site, therapyadvisor.com, was evaluated by 239 practicing psychologists to assess the usefulness of the site and explore possible interactions of EST attitudes on ratings of usefulness and impact. Two thirds of participants indicated using ESTs in practice, and limited time and resources were cited as primary barriers to EST adoption. The Web application was rated positively by most participants and was reported to increase awareness of and commitment to try ESTs among approximately 60% of participants. The results of this project support the feasibility of a Web application to increase diffusion and promote further adoption of ESTs. Technological and e-learning advances are promising directions for encouraging the adoption of ESTs specifically and evidence-based practice generally, particularly among busy practitioners who have inadequate time and resources for more traditional forms of dissemination and training. Keywords: empirically supported treatment, treatment diffusion, evidence-based practice, Internet, technology