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Digital therapeutics can overcome many of the barriers to translation of evidence-based treatment for substance use, mental health, and other behavioral health conditions. Delivered via nearly ubiquitous platforms such as the web, smartphone applications, text messaging, and videoconferencing, digital therapeutics can transcend the time and geographic boundaries of traditional clinical settings so that individuals can access care when and where they need it. There is strong empirical support for digital therapeutic approaches for behavioral health, yet implementation science with regard to scaling use of digital therapeutics for behavioral health is still in its early stages. In this paper, we summarize the proceedings of a day-long workshop, “Implementation Science and Digital Therapeutics,” sponsored and hosted by the Center for Technology and Behavioral Health at Dartmouth College. The Center for Technology and Behavioral Health is an interdisciplinary P30 Center of Excellence funded by the National Institute on Drug Abuse, with the mission of promoting state-of-the-technology and state-of-the-science for the development, evaluation, and sustainable implementation of digital therapeutic approaches for substance use and related conditions. Workshop presentations were grounded in current models of implementation science. Directions and opportunities for collaborative implementation science research to promote broad adoption of digital therapeutics for behavioral health are offered.

The article examines whether the Incretin hype should be the same for older adults. Topics discussed include lifestyle interventions that have demonstrated significant improvements in physical function, the classes of incretins that are increasingly valid and widely covered in persons with diabetes, and actions that can help in the identification of the right candidate for these medications.

BackgroundSarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. ObjectiveThis study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis MethodsThrough a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. ResultsThe mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; P=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. ConclusionsInvolving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults.

The study purpose was to determine how self-reported lifestyle physical activity levels, exercise self-efficacy and outcome expectancies, and health status differ by body mass index for persons with chronic pain. From U.S. clinics and community networks, 209 adults reporting chronic musculoskeletal pain were recruited for the cross-sectional survey. Data were analyzed using analysis of variance. Participants with self-described obesity reported the lowest physical activity, reduced exercise self-efficacy and positive outcome expectancies, and poorer health status. Promoting graded activity while addressing motivational factors from health behavior theory for people with chronic pain and obesity should be encouraged in rehabilitation programs.Keywords: chronic illness, health and well-being, health promotion, Chronic musculoskeletal pain refers to over a hundred conditions with the most common diagnoses including osteoarthritis, rheumatoid arthritis, fibromyalgia, and low back pain (Hootman, Helmick, & Brady, 2012; Turk & [...]

Introduction: Sarcopenic obesity (SarcO) is defined as the confluence of reduced muscle mass and function and excess body fat. The scientific community is increasingly recognizing this syndrome, which affects a subgroup of persons across their lifespans and places them at synergistically higher risk of significant medical comorbidity and disability than either sarcopenia or obesity alone. Joint efforts in clinical and research settings are imperative to better understand this syndrome and drive the development of urgently needed future interventions. Areas covered: Herein, we describe the ongoing challenges in defining sarcopenic obesity and the current state of the science regarding its epidemiology and relationship with adverse events. The field has demonstrated an emergence of data over the past decade which we will summarize in this article. While the etiology of sarcopenic obesity is complex, we present data on the underlying pathophysiological mechanisms that are hypothesized to promote its development, including age-related changes in body composition, hormonal changes, chronic inflammation, and genetic predisposition. Expert opinion: We describe emerging areas of future research that will likely be needed to advance this nascent field, including changes in clinical infrastructure, an enhanced understanding of the lifecourse, and potential treatments. [ABSTRACT FROM AUTHOR]