Evidence-Based Therapist-Supported Digital Mental Health Intervention for Patients Experiencing Medical Multimorbidity: A Retrospective Cohort Intent-to-Treat Study.

OBJECTIVE: Multimorbidity or the co-occurrence of multiple health conditions is increasing globally and is associated with significant psychological complications. It is unclear whether digital mental health (DMH) interventions for patients experiencing multimorbidity are effective, particularly given that this patient population faces more treatment resistance. The goal of the current study was to examine the impact of smartphone-delivered DMH interventions for patients presenting with elevated internalizing symptoms that have reported multiple lifetime medical conditions. METHODS: This preregistered (see https://osf.io/vh2et/ ) retrospective cohort intent-to-treat study with 2819 patients enrolled in a therapist-supported DMH intervention examined the associations between medical multimorbidity (MMB) and mental health outcomes. RESULTS: Results indicated that more MMB was significantly associated with greater presenting mental health symptom severity. MMB did not have a deleterious influence on depressive symptom trajectories across treatment, although having one medical condition was associated with a steeper decrease in anxiety symptoms compared to patients with no medical conditions. Finally, MMB was not associated with time to dropout, but was associated with higher dropout and was differentially associated with fewer beneficial treatment outcomes, although this is likely attributable to higher presenting symptom severity, rather than lesser symptom reductions during treatment. CONCLUSIONS: Overall, the Meru Health Program was associated with large effect size decreases in depressive and anxiety symptoms regardless of the number of MMB. Future DMH treatments and research might investigate tailored barrier reduction and extended treatment lengths for patients experiencing MMB to allow for greater treatment dose to reduce symptoms below clinical outcome thresholds.

Demographic and clinical characteristics associated with anxiety and depressive symptom outcomes in users of a digital mental health intervention incorporating a relational agent.

BACKGROUND: Digital mental health interventions (DMHIs) may reduce treatment access issues for those experiencing depressive and/or anxiety symptoms. DMHIs that incorporate relational agents may offer unique ways to engage and respond to users and to potentially help reduce provider burden. This study tested Woebot for Mood & Anxiety (W-MA-02), a DMHI that employs Woebot, a relational agent that incorporates elements of several evidence-based psychotherapies, among those with baseline clinical levels of depressive or anxiety symptoms. Changes in self-reported depressive and anxiety symptoms over 8 weeks were measured, along with the association between each of these outcomes and demographic and clinical characteristics. METHODS: This exploratory, single-arm, 8-week study of 256 adults yielded non-mutually exclusive subsamples with either clinical levels of depressive or anxiety symptoms at baseline. Week 8 Patient Health Questionnaire-8 (PHQ-8) changes were measured in the depressive subsample (PHQ-8 ≥ 10). Week 8 Generalized Anxiety Disorder-7 (GAD-7) changes were measured in the anxiety subsample (GAD-7 ≥ 10). Demographic and clinical characteristics were examined in association with symptom changes via bivariate and multiple regression models adjusted for W-MA-02 utilization. Characteristics included age, sex at birth, race/ethnicity, marital status, education, sexual orientation, employment status, health insurance, baseline levels of depressive and anxiety symptoms, and concurrent psychotherapeutic or psychotropic medication treatments during the study. RESULTS: Both the depressive and anxiety subsamples were predominantly female, educated, non-Hispanic white, and averaged 38 and 37 years of age, respectively. The depressive subsample had significant reductions in depressive symptoms at Week 8 (mean change =-7.28, SD = 5.91, Cohen's d = -1.23, p < 0.01); the anxiety subsample had significant reductions in anxiety symptoms at Week 8 (mean change = -7.45, SD = 5.99, Cohen's d = -1.24, p < 0.01). No significant associations were found between sex at birth, age, employment status, educational background and Week 8 symptom changes. Significant associations between depressive and anxiety symptom outcomes and sexual orientation, marital status, concurrent mental health treatment, and baseline symptom severity were found. CONCLUSIONS: The present study suggests early promise for W-MA-02 as an intervention for depression and/or anxiety symptoms. Although exploratory in nature, this study revealed potential user characteristics associated with outcomes that can be investigated in future studies. TRIAL REGISTRATION: This study was retrospectively registered on ClinicalTrials.gov (#NCT05672745) on January 5th, 2023.

Digital mental health interventions as stand-alone vs. augmented treatment as usual.

BACKGROUND: Smartphone-based digital mental health interventions (DMHI) have been described as a purported solution to meet growing healthcare demands and lack of providers, but studies often don't account for whether patients are concurrently in another treatment modality. METHODS: This preregistered quasi-experimental intent-to-treat study with 354 patients enrolled in a therapist-supported DMHI examined the treatment effectiveness of the Meru Health Program (MHP) as a stand-alone treatment as compared to the MHP in combination with any other form of treatment, including (1) in-person therapy, (2) psychotropic medication use, and (3) in-person therapy and psychotropic medication use. RESULTS: Patients with higher baseline depressive and anxiety symptoms were more likely to self-select into multiple forms of treatment, an effect driven by patients in the MHP as adjunctive treatment to in-person therapy and psychotropic medication. Patients in combined treatments had significantly higher depressive and anxiety symptoms across treatment, but all treatment groups had similar decreasing depressive and anxiety symptom trajectories. Exploratory analyses revealed differential treatment outcomes across treatment combinations. Patients in the MHP in combination with another treatment had higher rates of major depressive episodes, psychiatric hospitalization, and attempted death by suicide at baseline. CONCLUSIONS: Patients with higher depressive and anxiety symptoms tend to self-select into using DMHI in addition to more traditional types of treatment, rather than as a stand-alone intervention, and have more severe clinical characteristics. The use the MHP alone was associated with improvement at a similar rate to those with higher baseline symptoms who are in traditional treatments and use MHP adjunctively.

Equity in Digital Mental Health Interventions in the United States: Where to Next?

Health care technologies have the ability to bridge or hinder equitable care. Advocates of digital mental health interventions (DMHIs) report that such technologies are poised to reduce the documented gross health care inequities that have plagued generations of people seeking care in the United States. This is due to a multitude of factors such as their potential to revolutionize access; mitigate logistical barriers to in-person mental health care; and leverage patient inputs to formulate tailored, responsive, and personalized experiences. Although we agree with the potential of DMHIs to advance health equity, we articulate several steps essential to mobilize and sustain meaningful forward progression in this endeavor, reflecting on decades of research and learnings drawn from multiple fields of expertise and real-world experience. First, DMHI manufacturers must build diversity, equity, inclusion, and belonging (DEIB) processes into the full spectrum of product evolution itself (eg, product design, evidence generation) as well as into the fabric of internal company practices (eg, talent recruitment, communication principles, and advisory boards). Second, awareness of the DEIB efforts-or lack thereof-in DMHI research trials is needed to refine and optimize future study design for inclusivity as well as proactively address potential barriers to doing so. Trials should incorporate thoughtful, inclusive, and creative approaches to recruitment, enrollment, and measurement of social determinants of health and self-identity, as well as a prioritization of planned and exploratory analyses examining outcomes across various groups of people. Third, mental health care advocacy, research funding policies, and local and federal legislation can advance these pursuits, with directives from the US Preventive Services Taskforce, National Institutes of Health, and Food and Drug Administration applied as poignant examples. For products with artificial intelligence/machine learning, maintaining a "human in the loop" as well as prespecified and adaptive analytic frameworks to monitor and remediate potential algorithmic bias can reduce the risk of increasing inequity. Last, but certainly not least, is a call for partnership and transparency within and across ecosystems (academic, industry, payer, provider, regulatory agencies, and value-based care organizations) to reliably build health equity into real-world DMHI product deployments and evidence-generation strategies. All these considerations should also extend into the context of an equity-informed commercial strategy for DMHI manufacturers and health care organizations alike. The potential to advance health equity in innovation with DMHI is apparent. We advocate the field's thoughtful and evergreen advancement in inclusivity, thereby redefining the mental health care experience for this generation and those to come.

Longitudinal Patterns of Engagement and Clinical Outcomes: Results From a Therapist-Supported Digital Mental Health Intervention.

OBJECTIVE: Digital mental health interventions (DMHIs) are an effective treatment modality for common mental disorders like depression and anxiety; however, the role of intervention engagement as a longitudinal "dosing" factor is poorly understood in relation to clinical outcomes. METHODS: We studied 4978 participants in a 12-week therapist-supported DMHI (June 2020-December 2021), applying a longitudinal agglomerative hierarchical cluster analysis to the number of days per week of intervention engagement. The proportion of people demonstrating remission in depression and anxiety symptoms during the intervention was calculated for each cluster. Multivariable logistic regression models were fit to examine associations between the engagement clusters and symptom remission, adjusting for demographic and clinical characteristics. RESULTS: Based on clinical interpretability and stopping rules, four clusters were derived from the hierarchical cluster analysis (in descending order): a) sustained high engagers (45.0%), b) late disengagers (24.1%), c) early disengagers (22.5%), and d) immediate disengagers (8.4%). Bivariate and multivariate analyses supported a dose-response relationship between engagement and depression symptom remission, whereas the pattern was partially evident for anxiety symptom remission. In multivariable logistic regression models, older age groups, male participants, and Asians had increased odds of achieving depression and anxiety symptom remission, whereas higher odds of anxiety symptom remission were observed among gender-expansive individuals. CONCLUSIONS: Segmentation based on the frequency of engagement performs well in discerning timing of intervention disengagement and a dose-response relationship with clinical outcomes. The findings among the demographic subpopulations indicate that therapist-supported DMHIs may be effective in addressing mental health problems among patients who disproportionately experience stigma and structural barriers to care. Machine learning models can enable precision care by delineating how heterogeneous patterns of engagement over time relate to clinical outcomes. This empirical identification may help clinicians personalize and optimize interventions to prevent premature disengagement.

Trajectories of depression symptoms in a therapist-supported digital mental health intervention: a repeated measures latent profile analysis.

PURPOSE: Major depression affects 10% of the US adult population annually, contributing to significant burden and impairment. Research indicates treatment response is a non-linear process characterized by combinations of gradual changes and abrupt shifts in depression symptoms, although less is known about differential trajectories of depression symptoms in therapist-supported digital mental health interventions (DMHI). METHODS: Repeated measures latent profile analysis was used to empirically identify differential trajectories based upon biweekly depression scores on the Patient Health Questionnaire-9 (PHQ-9) among patients engaging in a therapist-supported DMHI from January 2020 to July 2021. Multivariate associations between symptom trajectories with sociodemographics and clinical characteristics were examined with multinomial logistic regression. Minimal clinically important differences (MCID) were defined as a five-point change on the PHQ-9 from baseline to week 12. RESULTS: The final sample included 2192 patients aged 18 to 82 (mean = 39.1). Four distinct trajectories emerged that differed by symptom severity and trajectory of depression symptoms over 12 weeks. All trajectories demonstrated reductions in symptoms. Despite meeting MCID criteria, evidence of treatment resistance was found among the trajectory with the highest symptom severity. Chronicity of major depressive episodes and lifetime trauma exposures were ubiquitous across the trajectories in a multinomial logistic regression model. CONCLUSIONS: These data indicate that changes in depression symptoms during DMHI are heterogenous and non-linear, suggesting a need for precision care strategies to address treatment resistance and increase engagement. Future efforts should examine the effectiveness of trauma-informed treatment modules for DMHIs as well as protocols for continuation treatment and relapse prevention.

Examining the temporal dynamics of anxiety and depressive symptoms during a therapist-supported, smartphone-based intervention for depression: Longitudinal observational study.

OBJECTIVE: This study examined the temporal dynamics of anxiety and depressive symptoms during a 12-week therapist-supported, smartphone-delivered digital health intervention for symptoms of depression and anxiety. METHODS: A total of 290 participants were included in the present analyses (age Mean = 39.64, SD = 10.25 years; 79% female; 54% self-reported psychotropic medication use). Linear mixed models were used to examine the concurrent anxiety-depression association and (2) the lead-lag anxiety-depression relationship, with greater anxiety predicted to precede an increase in depression. RESULTS: In support of Hypothesis 1, greater anxiety during the current biweekly assessment was associated with greater depressive symptoms during the current biweekly assessment. In support of Hypothesis 2, greater anxiety during the prior biweekly assessment was associated with greater depressive symptoms during the current biweekly assessment but not vice-versa. CONCLUSION: These findings demonstrate that anxiety and depressive symptoms may overlap and fluctuate in concert, with anxiety symptoms predicting subsequent depressive symptoms but not vice-versa. With sensitivity to study limitations, implications for future intervention designs are discussed.

Defining treatment-resistant depression.

BACKGROUND: Varying conceptualizations of treatment-resistant depression (TRD) have made translating research findings or systematic reviews into clinical practice guidelines challenging and inconsistent. METHODS: We conducted a review for the Centers for Medicare & Medicaid Services and the Agency for Healthcare Research and Quality to clarify how experts and investigators have defined TRD and to review systematically how well this definition comports with TRD definitions in clinical trials through July 5, 2019. RESULTS: We found that no consensus definition existed for TRD. The most common TRD definition for major depressive disorder required a minimum of two prior treatment failures and confirmation of prior adequate dose and duration. The most common TRD definition for bipolar disorder required one prior treatment failure. No clear consensus emerged on defining adequacy of either dose or duration. Our systematic review found that only 17% of intervention studies enrolled samples meeting the most frequently specified criteria for TRD. Depressive outcomes and clinical global impressions were commonly measured; functional impairment and quality-of-life tools were rarely used. CONCLUSIONS: Two key steps are critical to advancing TRD research: (a) Developing a consensus definition of TRD that addresses how best to specify the number of prior treatment failures and the adequacy of dose and duration; and (b) identifying a core package of outcome measures that can be applied in a standardized manner. Our recommendations about stronger approaches to designing and conducting TRD research will foster better evidence to translate into clearer guidelines for treating patients with this serious condition.

Feasibility and Efficacy of the Addition of Heart Rate Variability Biofeedback to a Remote Digital Health Intervention for Depression.

A rise in the prevalence of depression underscores the need for accessible and effective interventions. The objectives of this study were to determine if the addition of a treatment component showing promise in treating depression, heart rate variability-biofeedback (HRV-B), to our original smartphone-based, 8-week digital intervention was feasible and whether patients in the HRV-B ("enhanced") intervention were more likely to experience clinically significant improvements in depressive symptoms than patients in our original ("standard") intervention. We used a quasi-experimental, non-equivalent (matched) groups design to compare changes in symptoms of depression in the enhanced group (n = 48) to historical outcome data from the standard group (n = 48). Patients in the enhanced group completed a total average of 3.86 h of HRV-B practice across 25.8 sessions, and were more likely to report a clinically significant improvement in depressive symptom score post-intervention than participants in the standard group, even after adjusting for differences in demographics and engagement between groups (adjusted OR 3.44, 95% CI [1.28-9.26], P = .015). Our findings suggest that adding HRV-B to an app-based, smartphone-delivered, remote intervention for depression is feasible and may enhance treatment outcomes.

Residential Transience Among Adults: Prevalence, Characteristics, and Association with Mental Illness and Mental Health Service Use.

This study examined the association between frequent residential mobility (i.e., residential transience) and mental illness, mental health service use, and unmet need for services. Data are from the 2010 to 2014 National Surveys on Drug Use and Health (n = ~ 229,600). Logistic regression models examined the relationship between proximal (past year) and distal (past 2-5 years) residential transience and past year any mental illness (AMI), serious mental illness (SMI), mental health service use among adults with mental illness, and unmet need for services. Adults with transience had greater odds of AMI and SMI than those without transience. Proximal and distal transience were unrelated to past year mental health service use among adults with mental illness, but the odds of unmet need for services were greater among adults with transience compared with those without, suggesting a level of unmet service need among those with transience.

Screening for Depression in Pediatric Primary Care.

PURPOSE OF REVIEW: To review the clinical practice guideline landscape for depression screening in pediatric primary care and to identify current gaps in knowledge. RECENT FINDINGS: Various organizations have recommendations that support screening for depression in pediatric primary care, although some differ based on the age of the child. To date, guidelines have been made based on indirect evidence of efficacy. For example, indirect evidence shows that several screening tools exist for use in primary care, and various primary care-administered or referred treatments for childhood depression have some evidence of efficacy (particularly among adolescents). In addition to determining the applicability of this evidence to younger children, more research is needed on the direct net benefits of screening and to identify factors that facilitate its effective implementation. Indirect evidence supports the benefits of screening for depression in pediatric primary care; most organizations that publish screening guidelines recommend its use.

Which mental disorders are associated with the greatest impairment in functioning?

OBJECTIVE: The objective of this study is to estimate the comparative associations of mental disorders with three measures of functional impairment: the Global Assessment of Functioning (GAF); the number of days in the past 12 months of total inability to work or carry out normal activities because of emotions, nerves, or mental health (i.e., days out of role); and a modified version of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). METHODS: Secondary data analysis of the linked Mental Health Surveillance Study and the National Survey on Drug Use and Health (n = 5653), nationally representative population surveys conducted in the United States. Generalized linear models assessed the independent effects of mental disorders on each measure of functional impairment, controlling for mental disorder comorbidity, physical health disorders, and sociodemographic factors. RESULTS: The results varied across measures of functional impairment. However, mood disorders generally tended to be associated with the greatest functional impairment, anxiety disorders with intermediate impairment, and substance use disorders with the least impairment. All 15 disorders were significantly associated with the GAF score in multiple regression models, eight disorders were significantly associated with the WHODAS score, and three disorders were significantly associated with days out of role. CONCLUSIONS: Our results highlight the value of complementary measures of functional impairment.

Primary Care Interventions to Prevent Child Maltreatment: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force.

Importance: Child maltreatment, also referred to as child abuse and neglect, can result in lifelong negative consequences. Objective: To update the evidence on interventions provided in or referable from primary care to prevent child maltreatment for the US Preventive Services Task Force. Data Sources: PubMed, Cochrane Library, EMBASE, and trial registries through December 18, 2017; references; experts; literature surveillance through July 17, 2018. Study Selection: English-language fair- and good-quality randomized clinical trials that (1) included children with no known exposure to maltreatment and no signs or symptoms of current or past maltreatment, (2) evaluated interventions feasible in a primary care setting or that could result from a referral from primary care, and (3) reported abuse or neglect outcomes or proxies for abuse or neglect (eg, injury with a specificity for abuse, visits to the emergency department, hospitalization). Data Extraction and Synthesis: Two reviewers independently assessed titles/abstracts, full-text articles, and study quality; a third resolved conflicts when needed. When at least 3 similar trials were available, random-effects meta-analyses were conducted. Main Outcomes and Measures: Direct measures (including reports to child protective services and removal of the child from the home) or proxy measures of abuse or neglect; behavioral, emotional, mental, or physical well-being; and harms. Results: Twenty-two trials (33 publications) were included (N = 11 132). No significant association was found between interventions and reports to child protective services within 1 year of intervention completion (10.6% vs 11.9%; pooled odds ratio [OR], 0.94 [95% CI, 0.72-1.23]; 10 trials [n = 2444]) or removal of the child from the home within 1 to 3 years of follow-up (3.5% vs 3.7%; pooled OR, 1.09 [95% CI, 0.16-7.28]; 4 trials [n = 609]). No statistically significant associations were observed between interventions and outcomes for emergency department visits in the short term (<2 years), hospitalizations, child development, school performance, and prevention of death. Nonsignificant results from single trials led to a conclusion of insufficient evidence for injuries, failure to thrive, failure to immunize, school attendance, and other measures of abuse or neglect. Inconsistent results led to a conclusion of insufficient evidence for long-term (≥2 years) outcomes for reports to child protective services (ORs range from 0.48 to 1.13; 3 trials [n = 1690]), emergency department visits (1 of 2 trials reported significant differences) and internalizing and externalizing behavior symptoms (3 of 6 trials reported reductions in behavior difficulties). No eligible trials on harms of interventions were identified. Conclusions and Relevance: Interventions provided in or referable from primary care did not consistently prevent child maltreatment. No evidence on harms is available.

Screening for Major Depressive Disorder in Children and Adolescents: A Systematic Review for the U.S. Preventive Services Task Force.

BACKGROUND: Major depressive disorder (MDD) is common among children and adolescents and is associated with functional impairment and suicide. PURPOSE: To update the 2009 U.S. Preventive Services Task Force (USPSTF) systematic review on screening for and treatment of MDD in children and adolescents in primary care settings. DATA SOURCES: Several electronic searches (May 2007 to February 2015) and searches of reference lists of published literature. STUDY SELECTION: Trials and recent systematic reviews of treatment, test-retest studies of screening, and trials and large cohort studies for harms. DATA EXTRACTION: Data were abstracted by 1 investigator and checked by another; 2 investigators independently assessed study quality. DATA SYNTHESIS: Limited evidence from 5 studies showed that such tools as the Beck Depression Inventory and Patient Health Questionnaire for Adolescents had reasonable accuracy for identifying MDD among adolescents in primary care settings. Six trials evaluated treatment. Several individual fair- and good-quality studies of fluoxetine, combined fluoxetine and cognitive behavioral therapy, escitalopram, and collaborative care demonstrated benefits of treatment among adolescents, with no associated harms. LIMITATION: The review included only English-language studies, narrow inclusion criteria focused only on MDD, high thresholds for quality, potential publication bias, limited data on harms, and sparse evidence on long-term outcomes of screening and treatment among children younger than 12 years. CONCLUSION: No evidence was found of a direct link between screening children and adolescents for MDD in primary care or similar settings and depression or other health-related outcomes. Evidence showed that some screening tools are accurate and some treatments are beneficial among adolescents (but not younger children), with no evidence of associated harms. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Disability status, mortality, and leading causes of death in the United States community population.

OBJECTIVE: We examined the effect of functional disability on all-cause mortality and cause-specific deaths among community-dwelling US adults. METHODS: We used data from 142,636 adults who participated in the 1994-1995 National Health Interview Survey-Disability Supplement eligible for linkage to National Death Index records from 1994 to 2006 to estimate the effects of disability on mortality and leading causes of death. RESULTS: Adults with any disability were more likely to die than adults without disability (19.92% vs. 10.94%; hazard ratio=1.51, 95% confidence interval, 1.45-1.57). This association was statistically significant for most causes of death and for most types of disability studied. The leading cause of death for adults with and without disability differed (heart disease and malignant neoplasms, respectively). CONCLUSIONS: Our results suggest that all-cause mortality rates are higher among adults with disabilities than among adults without disabilities and that significant associations exist between several types of disability and cause-specific mortality. Interventions are needed that effectively address the poorer health status of people with disabilities and reduce the risk of death.

Improvements in Work Productivity and Activity Impairment Among Adults With Anxiety or Depressive Symptoms Participating in a Relational Agent-Delivered Digital Mental Health Intervention.

OBJECTIVES: The study aimed to assess changes between baseline and end of treatment in work-related absenteeism, presenteeism, productivity, and nonwork-related activity impairment and estimate cost savings associated with observed improvements. METHODS: Data from 91 employed adult participants who enrolled in a single-arm, exploratory study of a relational agent-delivered digital mental health intervention and completed Work Productivity and Activity Impairment assessments were analyzed; overall work productivity improvement was multiplied by the overall and education-adjusted US median annual salary to arrive at potential cost savings estimates. RESULTS: Adjusted models indicated more than 20% improvements in presenteeism, work productivity impairment, and activity impairment, yielding cost-savings estimates between $14,000 and more than $18,000 annually. CONCLUSIONS: Relational agent-delivered digital mental health interventions may be associated with improvements in work productivity and activity impairment, which could result in a sizable cost savings.

Longitudinal outcomes of a therapist-supported digital mental health intervention for depression and anxiety symptoms: A retrospective cohort study.

PURPOSE: This study examined treatment outcomes (depression and anxiety symptoms) up to 24 months after completion of a therapist-supported digital mental health intervention (DMHI). METHODS: The sample consisted of 380 participants who participated in an eight-week DMHI from February 6, 2017 to May 20, 2019. Participants reported depression and anxiety symptoms at eight timepoints from baseline to 24 months. Mixed-effects modelling was used to investigate symptom changes over time. The proportion of participants meeting criteria for treatment response, clinically significant change, and remission of depression and anxiety symptoms were calculated, including proportions demonstrating each outcome sustained up to each timepoint. RESULTS: Multivariate analyses yielded statistically significant reductions in depression (ß = -5.40) and anxiety (ß = -3.31) symptoms from baseline to end of treatment (8 weeks). Symptom levels remained significantly reduced from baseline through 24 months. The proportion of participants meeting criteria for clinical treatment outcomes remained constant over 24 months, although there were linear decreases in the proportions experiencing sustained clinical outcomes. CONCLUSIONS: Treatment gains were made for depression and anxiety symptoms at the end of treatment and up to 24 months. Future studies should determine the feasibility of integrating post-treatment programmes into DMHIs to address symptom deterioration.

Therapist-supported digital mental health intervention for depressive symptoms: A randomized clinical trial.

Depression is a chronic and debilitating mental disorder. Despite the existence of several evidence-based treatments, many individuals suffering from depression face myriad structural barriers to accessing timely care which may be alleviated by digital mental health interventions (DMHI). Accordingly, this randomized clinical trial (ClinicalTrials.gov: NCT04738084) investigated the efficacy of a newer version of the therapist-supported and guided DMHI, the Meru Health Program (MHP), which was recently enhanced with heart rate variability biofeedback and lengthened from 8- to 12-weeks duration, among people with elevated depression symptoms (N = 100, mean age 37). Recruited participants were randomized to the MHP (n = 54) or a waitlist control (n = 46) condition for 12 weeks. The MHP group had greater decreases in depression symptoms compared to the waitlist control (d = -0.8). A larger proportion of participants in the MHP group reported a minimal clinically important difference (MCID) in depression symptoms than participants in the waitlist control group (39.1 % vs. 9.8 %, χ2(1) = 9.90, p = .002). Similar effects were demonstrated for anxiety symptoms, quality of life, insomnia, and resilience. The results confirm the utility of the enhanced MHP in reducing depression symptoms and associated health burdens.

Preliminary Effectiveness of a Therapist-Supported Digital Mental Health Intervention in Reducing Suicidal Ideation.

Suicidal ideation (SI) is a significant public health concern with increasing prevalence. Therapist-supported digital mental health interventions (DMHI) are an emergent modality to address common mental health problems like depression and anxiety, although less is known about SI. This study examined SI trajectories among 778 patients who participated in a therapist-supported DMHI using multilevel models during and up to 6-months post-treatment. Estimates of associated suicide attempts and deaths by suicide were calculated using published data linking PHQ-9-assessed SI to records of suicide attempts and deaths by suicide. The proportion of participants reporting no SI significantly increased between baseline and end-of-treatment (78.02% to 91.00%). Effect sizes of SI changes between baseline and end-of-treatment, 3-month, and 6-month follow-ups were 0.33 (95%CI = 0.27-0.38), 0.32 (95%CI = 0.27-0.38), and 0.32 (95%CI = 0.27-0.38), respectively. Results also indicated an estimated 30.49% reduction (95%CI = 25.15%-35.13%) in suicide attempts and death by suicide across treatment. This study provides preliminary evidence of the effectiveness of a therapist-supported DMHI in reducing SI.

Changes in stress, burnout, and resilience associated with an 8-week intervention with relational agent "Woebot".

Background: Research investigating the potential for digital mental health interventions with integrated relational agents to improve mental health outcomes is in its infancy. By delivering evidence-based mental health interventions through tailored, empathic conversations, relational agents have the potential to help individuals manage their stress and mood, and increase positive mental health. Aims: The aims of this study were twofold: 1) to assess whether a smartphone app delivering mental health support through a relational agent, Woebot, is associated with changes in stress, burnout, and resilience over 8 weeks, and 2) to identify demographic and clinical factors associated with changes in these outcomes. Method: This exploratory, non-randomized, single-armed, open-labeled trial was conducted from May to July 2022. A total of 256 adults (mean age 39 ± 13.35; 72 % females) recruited through social media advertising enrolled in the study. Participants completed an 8-week intervention period during which they were invited to use a smartphone app called Woebot-LIFE that delivers cognitive behavioral therapy through a relational agent called "Woebot". Participant-reported measures of stress, burnout, and resilience were collected at Baseline, and Week 8. Changes in these outcomes during the study period were assessed. Bivariate and stepwise multiple regression modeling was used to identify sociodemographic and clinical factors associated with observed changes over the 8-week study period. Results: Exposure to Woebot-LIFE was associated with significant reductions in perceived stress and burnout and significantly increased resilience over the 8-week study period. A greater reduction in stress was observed among those with clinically elevated mood symptoms (i.e., Patient Health Questionnaire-8 or Generalized Anxiety Disorder 7-item scores ≥10) at baseline compared to those without; however, the differences in the improvements in resilience scores and burnout between the two groups were not statistically significant. Although a difference in the magnitude of change in stress was observed for participants with and without clinically elevated mood symptoms at baseline, significant improvements in stress, burnout, and resilience over the 8-week study period were observed for both groups. Bivariate analyses showed that race, insurance type, and baseline level of resilience were associated with changes in each of the outcomes, though baseline resilience was the only factor that remained significantly associated with changes in the outcomes in the stepwise multiple regression analyses. Conclusion: Results of this single-arm, exploratory study suggest that conversational agent-guided mental health interventions such as Woebot-LIFE may be associated with reduced stress and burnout and increased resilience in both clinical and non-clinical populations.