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The objective of this study was to present lessons learned about engagement, delivery modality and pandemic impact while delivering a collaborative care intervention with a socioeconomically, racially and ethnically diverse sample. Participants completed a post-intervention survey (n = 41) on experiences and preferred intervention delivery modality, coronavirus 2019 (COVID-19) Impact Survey (n = 50) and provided open-ended feedback about the intervention (n = 27). Intervention process data included attendance, modality, and withdrawals. Data were analyzed using descriptive statistics and inductive content analyses. Of 71 intervention participants, 6 (8%) withdrew before session 1. Completers adhered to intervention timeline better than withdrawals. Participants liked the in-person interaction, efficient coach support, accountability of in-person and Zoom vs. phone sessions and the flexibility and convenience of phone and Zoom vs. in-person sessions. A majority of participants reported experiencing pandemic impacts such as heightened emotional distress, decreased activity engagement, poorer eating behaviors and being unable to meet basic needs. Participants deviating from intervention timelines may be re-engaged by targeted outreach attempts. Videoconference has the potential for providing as-needed coaching. Future interventions may be optimized to account for and address areas impacted by the pandemic. Findings revealed specific strategies that can be implemented in future interventions to improve emotional and physical health among diverse populations.

Background Artificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care–related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated. Objective This study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety. Methods A total of 26 participants completed 2 therapy sessions—an introductory (session 1) and a problem-solving (session 2)—with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants’ perspectives regarding Lumen use. Results Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen’s on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions. Conclusions On the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services.

Artificial intelligence (AI)-based voice technology offers considerable promise in healthcare; however, its application for behavioral therapy in a real-world or research setting has yet to be determined. We describe the design and evaluation of 1Lumen™, a fully functional voice-only virtual coach that delivers evidence-based, problem-solving treatment (PST) for patients with mild-to-moderate depression and/or anxiety. Participants (N=26) completed surveys and semi-structured interviews after two therapy sessions with Lumen. Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions. Participants emphasized its on-demand accessibility and the delivery of a complex PST task with a simplistic structure for achieving therapy goals. Suggestions for improvement included streamlining and improved personalization and pacing of conversations and providing additional context during therapy sessions. Lumen offers a realistic and cognitively plausible verbal interaction that can potentially lead to personalized and accessible mental health care, filling a gap in traditional mental health services.

Background: Integrated treatments for depression (and associated anxiety) and obesity are lacking; mechanisms are poorly investigated. This mechanistic pilot trial tested the degree to which engaging pre-specified neural targets at 2 months produces desired outcomes at 6 months. Methods: Adults with a body mass index (BMI) of ≥30 (≥27, if Asian) and Patient Health Questionnaire-9 (PHQ-9) score of ≥10 were recruited from academic internal medicine clinics between March 1, 2019 and March 19, 2020, and followed for 6 months until August 31, 2020. Participants were randomized to receive usual care (n=35) or an integrated collaborative care intervention (n=71), providing 6 problem-solving therapy (PST) sessions for depression by 2 months, 3 additional PST sessions and 11 home videos on lifestyle changes for weight loss by 6 months. Outcomes were changes in BMI, Depression Symptom Checklist 20-item (SCL-20) scores, and Generalized Anxiety Disorder Scale (GAD-7) scores at 6 months. Neural targets were changes in affective, cognitive control, and default mode circuits by functional neuroimaging at 2 months. Outcomes: Among 106 participants (mean [SD] age 47.0 [11.9] years, 76% women, 55% Blacks, 20% Latino, BMI 37.1 [6.0], SCL-20 1.2 [0.7], GAD-7 6.9 [4.8]), 86.8% completed the trial. The intervention led to significant reductions in SCL-20 (-0.3 [95% CI: -0.6, -0.1]) and GAD-7 (-2.9 [-4.7, -1.1]), but not BMI, at 6 months compared with usual care. Changes in the activation or functional connectivity of neural targets in the negative affect (anterior insula, subgenual and pregenual ACC, amygdala) and cognitive control circuits (dlPFC, dACC) at 2 months significantly correlated with changes in GAD-7, but not SCL-20 or BMI, at 6 months, and the correlations differed by the intervention vs. usual care. Effect sizes were medium to large (0.41ꟷ1.18 SDs). Changes in the neural targets of the cognitive control circuit, but not the negative affect circuit, at 2 months differed by treatment group. Effect sizes were medium (0.58ꟷ0.79 SDs). Interpretation: Short-term changes in the cognitive control circuit mediated changes in anxiety symptoms, suggesting possible neural mechanisms to target for enhanced treatment effect. Clinical Trial Registration Details: ClinicalTrials.gov Identifier: NCT03841682. Funding Information: National Heart, Lung, and Blood Institute grant number UH2HL132368 and UH3HL132368. Declaration of Interests: Dr. Jun Ma is a paid scientific consultant for Health Mentor, Inc. (San Jose, CA). Dr. Leanne M. Williams is on the Scientific Advisory Board for One Mind Psyberguide and the External Advisory Board for the Laureate Institute for Brain Research. Dr. Olusola A. Ajilore is the co-founder of Keywise AI and serves on the advisory boards of Blueprint Health and Embodied Labs. The other authors report no conflicts of interest. Dr. Thomas Kannampallil is a paid consultant for Pfizer, Inc, outside of this work Ethics Approval Statement: The Institutional Review Boards for the University of Illinois at Chicago and Stanford University approved the study. All participants provided written consent.

Despite evidence for effective integrated behavior therapy for treating comorbid obesity and depression, treatment response is highly variable and the underlying neurobiological mechanisms remain unknown. This hampers efforts to identify mechanistic targets in order to optimize treatment precision and potency. Funded within the NIH Science of Behavior Change (SOBC) Research Network, the 2-phased ENGAGE research project applies an experimental precision medicine approach to address this gap. The Phase 1 study focused on demonstrating technical feasibility, target engagement and potential neural mechanisms of responses to an integrated behavior therapy. This therapy combines a video-based behavioral weight loss program and problem-solving therapy for depression, with as-needed intensification of antidepressant medications, and its clinical effectiveness was demonstrated within a parent randomized clinical trial. Here, we describe the ENGAGE Phase 2 (ENGAGE-2) study protocol which builds on Phase 1 in 2 ways: (1) pilot testing of an motivational interviewing-enhanced, integrated behavior therapy in an independent, primarily minority patient sample, and (2) evaluation of a priori defined neural targets, specifically the negative affect (threat and sadness) circuits which demonstrated engagement and malleability in Phase 1, as mediators of therapeutic outcomes. Additionally, the Phase 2 study includes a conceptual and methodological extension to explore the role of microbiome-gut-brain and systemic immunological pathways in integrated behavioral treatment of obesity and depression. This protocol paper documents the conceptualization, design and the transdisciplinary methodologies in ENGAGE-2, which can inform future clinical and translational research in experimental precision medicine for behavior change and chronic disease management. Trial registration: ClinicalTrials.gov #NCT 03,841,682.

High retention and treatment adherence are essential to ensure the quality of evidence from clinical trials. Strategies for improving these have been explored but actual rates in lifestyle intervention trials indicate challenges. This study examined the use of a motivational interviewing-informed strategy during interactive group orientations prior to obtaining informed consent, collecting baseline data and randomization in a healthy dietary pattern intervention trial for asthma control in adults. The themes generated from small group discussions and echoed in large group discussions during the orientation sessions helped potential participants better understand the scientific rationale of the research design and procedures and the practical implications for them to participate in the study. Potential participants reported significantly lower confidence of completing the study after the group orientation. This suggests that the group orientations helped potential participants identify challenges to completing the study, have more realistic expectations about participation and be prepared if enrolled. Both retention (92% of 90 participants at 6 months) and intervention attendance (99% of 46 intervention participants attended 80% of 11 weekly group/individual sessions) were high, suggesting the motivation interviewing-informed group orientation strategy may help improve retention and adherence in clinical trials.