Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial.

BACKGROUND: The quality of user interaction with therapeutic tools has been positively associated with treatment response; however, no studies have investigated these relationships for voice-based digital tools. OBJECTIVE: This study evaluated the relationships between objective and subjective user interaction measures as well as treatment response on Lumen, a novel voice-based coach, delivering problem-solving treatment to patients with mild to moderate depression or anxiety or both. METHODS: In a pilot trial, 42 adults with clinically significant depression (Patient Health Questionnaire-9 [PHQ-9]) or anxiety (7-item Generalized Anxiety Disorder Scale [GAD-7]) symptoms or both received Lumen, a voice-based coach delivering 8 problem-solving treatment sessions. Objective (number of conversational breakdowns, ie, instances where a participant's voice input could not be interpreted by Lumen) and subjective user interaction measures (task-related workload, user experience, and treatment alliance) were obtained for each session. Changes in PHQ-9 and GAD-7 scores at each ensuing session after session 1 measured the treatment response. RESULTS: Participants were 38.9 (SD 12.9) years old, 28 (67%) were women, 8 (19%) were Black, 12 (29%) were Latino, 5 (12%) were Asian, and 28 (67%) had a high school or college education. Mean (SD) across sessions showed breakdowns (mean 6.5, SD 4.4 to mean 2.3, SD 1.8) decreasing over sessions, favorable task-related workload (mean 14.5, SD 5.6 to mean 17.6, SD 5.6) decreasing over sessions, neutral-to-positive user experience (mean 0.5, SD 1.4 to mean 1.1, SD 1.3), and high treatment alliance (mean 5.0, SD 1.4 to mean 5.3, SD 0.9). PHQ-9 (Ptrend=.001) and GAD-7 scores (Ptrend=.01) improved significantly over sessions. Treatment alliance correlated with improvements in PHQ-9 (Pearson r=-0.02 to -0.46) and GAD-7 (r=0.03 to -0.57) scores across sessions, whereas breakdowns and task-related workload did not. Mixed models showed that participants with higher individual mean treatment alliance had greater improvements in PHQ-9 (ß=-1.13, 95% CI -2.16 to -0.10) and GAD-7 (ß=-1.17, 95% CI -2.13 to -0.20) scores. CONCLUSIONS: The participants had fewer conversational breakdowns and largely favorable user interactions with Lumen across sessions. Conversational breakdowns were not associated with subjective user interaction measures or treatment responses, highlighting how participants adapted and effectively used Lumen. Individuals experiencing higher treatment alliance had greater improvements in depression and anxiety. Understanding treatment alliance can provide insights on improving treatment response for this new delivery modality, which provides accessibility, flexibility, comfort with disclosure, and cost-related advantages compared to conventional psychotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT04524104; https://clinicaltrials.gov/study/NCT04524104.

Mediating Effects of Neural Targets on Depression, Weight, and Anxiety Outcomes of an Integrated Collaborative Care Intervention: The ENGAGE-2 Mechanistic Pilot Randomized Clinical Trial.

Background: Integrated treatments for comorbid depression (often with anxiety) and obesity are lacking; mechanisms are poorly investigated. Methods: In a mechanistic pilot trial, adults with body mass index ≥30 and Patient Health Questionnaire-9 scores ≥10 were randomized to usual care (n = 35) or an integrated behavioral intervention (n = 71). Changes at 6 months in body mass index and Depression Symptom Checklist-20 scores were co-primary outcomes, and Generalized Anxiety Disorder Scale-7 score was a secondary outcome. Changes at 2 months in the activation and functional connectivity of regions of interest in the negative affect circuit were primary neural targets, and secondary targets were in the cognitive control, default mode, and positive affect circuits. Results: Participants were 47.0 years (SD = 11.9 years), 76% women, 55% Black, and 20% Latino. Depression Symptom Checklist-20 (between-group difference, -0.3 [95% CI: -0.6 to -0.1]) and Generalized Anxiety Disorder Scale-7 (-2.9 [-4.7 to -1.1]) scores, but not body mass index, decreased significantly at 6 months in the intervention versus usual care groups. Only Generalized Anxiety Disorder Scale-7 score changes at 6 months significantly correlated with neural target changes at 2 months in the negative affect (anterior insula, subgenual/pregenual anterior cingulate cortex, amygdala) and cognitive control circuits (dorsal lateral prefrontal cortex, dorsal anterior cingulate cortex). Effects were medium to large (0.41-1.18 SDs). Neural target changes at 2 months in the cognitive control circuit only differed by treatment group. Effects were medium (0.58-0.79 SDs). Conclusions: Compared with usual care, the study intervention led to significantly improved depression but not weight loss, and the results on neural targets were null for both outcomes. The significant intervention effect on anxiety might be mediated through changes in the cognitive control circuit, but this warrants replication.

Effects of a virtual voice-based coach delivering problem-solving treatment on emotional distress and brain function: a pilot RCT in depression and anxiety.

Consumer-based voice assistants have the ability to deliver evidence-based treatment, but their therapeutic potential is largely unknown. In a pilot trial of a virtual voice-based coach, Lumen, delivering problem-solving treatment, adults with mild-to-moderate depression and/or anxiety were randomized to the Lumen intervention (n = 42) or waitlist control (n = 21). The main outcomes included changes in neural measures of emotional reactivity and cognitive control, and Hospital Anxiety and Depression Scale [HADS] symptom scores over 16 weeks. Participants were 37.8 years (SD = 12.4), 68% women, 25% Black, 24% Latino, and 11% Asian. Activation of the right dlPFC (neural region of interest in cognitive control) decreased in the intervention group but increased in the control group, with an effect size meeting the prespecified threshold for a meaningful effect (Cohen's d = 0.3). Between-group differences in the change in activation of the left dlPFC and bilateral amygdala were observed, but were of smaller magnitude (d = 0.2). Change in right dlPFC activation was also meaningfully associated (r ≥ 0.4) with changes in self-reported problem-solving ability and avoidance in the intervention. Lumen intervention also led to decreased HADS depression, anxiety, and overall psychological distress scores, with medium effect sizes (Cohen's d = 0.49, 0.51, and 0.55, respectively), compared with the waitlist control group. This pilot trial showed promising effects of a novel digital mental health intervention on cognitive control using neuroimaging and depression and anxiety symptoms, providing foundational evidence for a future confirmatory study.

Associations between daily step count trajectories and clinical outcomes among adults with comorbid obesity and depression.

Purpose: To examine the relationship between features of daily measured step count trajectories and clinical outcomes among people with comorbid obesity and depression in the ENGAGE-2 Trial. Methods: This post hoc analysis used data from the ENGAGE-2 trial where adults (n=106) with comorbid obesity (BMI ≥30.0 or 27.0 if Asian) and depressive symptoms (Patient Health Questionnaire-9 score ≥10) were randomized (2:1) to receive the experimental intervention or usual care. Daily step count trajectories over the first 60 days (Fitbit Alta HR) were characterized using functional principal component analyses. 7-day and 30-day trajectories were also explored. Functional principal component scores that described features of step count trajectories were entered into linear mixed models to predict weight (kg), depression (Symptom Checklist-20), and anxiety (Generalized Anxiety Disorder Questionnaire-7) at 2-months (2M) and 6-months (6M). Results: Features of 60-day step count trajectories were interpreted as overall sustained high, continuous decline, and disrupted decline. Overall sustained high step count was associated with low anxiety (2M, ß=-0.78, p<.05; 6M, ß=-0.80, p<.05) and low depressive symptoms (6M, ß=-0.15, p<.05). Continuous decline in step count was associated with high weight (2M, ß=0.58, p<.05). Disrupted decline was not associated with clinical outcomes at 2M or 6M. Features of 30-day step count trajectories were also associated with weight (2M, 6M), depression (6M), and anxiety (2M, 6M); Features of 7-day step count trajectories were not associated with weight, depression, or anxiety at 2M or 6M. Conclusions: Features of step count trajectories identified using functional principal component analysis were associated with depression, anxiety, and weight outcomes among adults with comorbid obesity and depression. Functional principal component analysis may be a useful analytic method that leverages daily measured physical activity levels to allow for precise tailoring of future behavioral interventions.

Design and Formative Evaluation of a Virtual Voice-Based Coach for Problem-solving Treatment: Observational Study.

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.

Integrated collaborative care intervention for depression and obesity in primary care: translation from research to practice.

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.

Association of COVID-19 impact with outcomes of an integrated obesity and depression intervention: Posthoc analysis of an RCT.

OBJECTIVE: To examine the association between COVID-19 impact and clinical outcomes of an integrated collaborative care intervention for adults with obesity and comorbid depression. METHODS: Latent class analysis identified clusters of self-reported COVID-19 impact. Cluster characteristics were examined using Fishers' least significant difference method and canonical discriminant analysis. Intervention vs. usual care effects on primary (body mass index [BMI], depressive symptoms) and secondary (anxiety symptoms and other psychosocial) outcomes stratified by cluster were examined using linear mixed models. RESULTS: Three clusters were identified: mental health and sleep impact (cluster 1, n = 37), economic impact (cluster 2, n = 18), and less overall impact (cluster 3, n = 20). Clusters differed in age, income, diet, and baseline coping skills. The intervention led to improvements across several health outcomes compared with usual care, with medium to large effects on functional impairments (standardized mean difference, -0.7 [95% CI: -1.3, -0.1]) in cluster 1, depressive symptoms (-1.1 [95% CI: -2.0, -0.1]) and obesity-related problems (-1.6 [95% CI: -2.8, -0.4]) in cluster 2, and anxiety (-1.1 [95% CI: -1.9, -0.3]) in cluster 3. CONCLUSIONS: People with obesity and comorbid depression may have varied intervention responses based on COVID-19 impact. Interventions tailored to specific COVID-19 impact clusters may restore post-pandemic health.

Weight loss effects in usual primary care: Findings from 5 behavioral weight loss RCTs.

Primary care is an important setting for obesity treatment and behavior therapy is considered the first line. However, current practice often does not meet clinical guidelines and, furthermore, effects of usual care (UC) on weight loss are unclear. This makes it difficult to design sufficiently powered weight loss trials in primary care. This study analyzed data from UC control participants across 5 primary care-based randomized clinical trials of behavioral weight loss interventions to assess UC effects for 4 weight outcomes: body mass index (BMI), weight change (kg and %), and percent of participants achieving clinically significant 5% weight loss. Results indicated modest UC effects, suggesting modest weight loss is possible in usual primary care.

The ENGAGE-2 study: Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes in a randomized controlled trial (Phase 2).

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.

Use of a motivational interviewing-informed strategy in group orientations to improve retention and intervention attendance in a randomized controlled trial.

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.