Behavioral skill practice as a predictor of mood and family functioning in adolescents with bipolar and depressive mood disorders: Results of a 6-month randomized trial of family-focused therapy.

OBJECTIVE: Behavioral interventions require considerable practice of treatment skills in between therapy sessions. The effects of these treatments may vary with the degree to which patients are able to implement these practices. In offspring of parents with bipolar and major depressive disorders, we examined whether youth who frequently practiced communication and problem-solving skills between family-focused therapy (FFT) sessions had less severe mood symptoms and better psychosocial functioning over 6 months than youth who practiced less frequently. METHODS: We randomly assigned offspring (ages 12-19) of parents with mood disorders to 12 sessions of FFT plus a mobile app that encouraged the practice of communication, problem-solving and mood management skills (FFT-MyCoachConnect [MCC] condition) or 12 sessions of FFT with an app that only allowed for tracking of symptoms and stress (FFT-Track condition). Independent evaluators assessed youths' mood and psychosocial functioning at 9-week intervals over 27 weeks. Clinicians rated participants' between-session skill practice at each FFT session. RESULTS: FFT-MCC was associated with more frequent skill practice than FFT-Track over 18 weeks of treatment. Skill practice was associated with reductions in youths' mood instability and perceptions of family conflict over 27 weeks in both app conditions. Skill practice mediated the effects of app condition on youths' mood instability and family functioning. CONCLUSIONS: Mobile applications as adjuncts to family therapy for youth with mood disorders can help increase skill practice. These findings provide preliminary causal evidence for behavioral skill practice improving mood symptoms and family functioning among youth with mood disorders.

Exercise behaviours and motivation after a first psychotic episode: A digital intervention.

AIM: Research has demonstrated that participation in aerobic exercise can have significant beneficial effects across both physical and mental health domains for individuals who are in the early phase of schizophrenia. Despite these notable benefits of exercise, deficits in motivation and a lack of methods to increase engagement are significant barriers for exercise participation, limiting these potentially positive effects. Fortunately, digital health tools have the potential to improve adherence to an exercise program. The present study examined the role of motivation for exercise and the effects of an automated digital text messaging program on participation in an aerobic exercise program. METHODS: A total of 46 first-episode psychosis participants from an ongoing 12-month randomized clinical trial (Enhancing Cognitive Training through Exercise Following a First Schizophrenia Episode (CT&E-RCT)) were included in an analysis to examine the efficacy of motivational text messaging. Personalized motivational text message reminders were sent to participants with the aim of increasing engagement in the exercise program. RESULTS: We found that participants with higher levels of intrinsic motivation to participate in a text messaging program and in an exercise intervention completed a higher proportion of individual, at-home exercise sessions. In a between groups analysis, participants who received motivational text messages, compared to those who did not, completed a higher proportion of at-home exercise sessions. CONCLUSION: These results indicate the importance of considering a person's level of motivation for exercise and the potential utility of using individualized and interactive mobile text messaging reminders to increase engagement in aerobic exercise in the early phase of psychosis. We emphasize the need for understanding how individualized patient preferences and needs interplay between intrinsic motivation and digital health interventions for young adults.

A Randomized Clinical Trial of Technology-Enhanced Family-Focused Therapy for Youth in the Early Stages of Mood Disorders.

Objective: Family-focused therapy (FFT) is associated with enhanced outcomes in youth with bipolar and depressive disorders, but has not been evaluated in conjunction with mobile health tools. In symptomatic adolescents whose parents had histories of mood disorders, we examined whether the effects of telehealth-based FFT were augmented by mobile health apps that emphasized mood tracking and family coping skills. Method: Participants (aged 13-19 years) had active mood symptoms and a parent with major depressive or bipolar disorder. Participants received 12 sessions in 18 weeks of telehealth FFT, with random assignment to (1) a mobile app (MyCoachConnect, MCC) that enabled mood tracking, reviews of session content, and text reminders to practice mood management and family communication skills (FFT-MCC); or (2) a mobile app that enabled mood tracking only (FFT-Track). Independent evaluators assessed youth every 9 weeks over 6 months on depressive symptoms (primary outcome), anxiety, and psychosocial functioning. Results: Participants (N = 65; mean age 15.8 ± 1.6 years) significantly improved in depressive symptoms over 6 months (F1,170 = 45.02, p < .0001; ή2 = 0.21, 95% CI = 0.11-0.31), but there were no effects of treatment condition or treatment by time interactions on depression scores. When secondary outcome measures were considered, the subgroup of youth with bipolar spectrum disorders showed greater improvements in anxiety and global functioning in FFT-MCC compared with FFT-Track. Conclusion: Youth in the early stages of mood disorder may benefit from FFT enhanced by mobile health apps. Collaborations between researchers and information technologists on mobile app design and user experience may lead to increases in engagement among adolescents. Clinical trial registration information: Technology Enhanced Family Treatment; https://clinicaltrials.gov/; NCT03913013.

Word usage in spontaneous speech as a predictor of depressive symptoms among youth at high risk for mood disorders.

BACKGROUND: We examined whether digital phenotyping of spontaneous speech, such as the use of specific word categories during speech samples, was associated with depressive symptoms in youth who were at familial and clinical risk for mood disorders. METHODS: Participants (ages 13-19) had active mood symptoms, mood instability, and at least one parent with bipolar or major depressive disorder. During a randomized trial of family-focused therapy, participants were instructed to make weekly calls to a central voice server and leave speech samples in response to automated prompts. We coded youths' speech samples with the Linguistic Inquiry and Word Count system and used machine learning to identify the combination of speech features that were most closely associated with the course of depressive symptoms over 18 weeks. RESULTS: A total of 253 speech samples were collected from 44 adolescents (mean age = 15.8 years; SD = 1.6) over 18 weeks. Speech containing affective processes, social processes, drives toward risk or reward, nonfluencies, and time orientation words were correlated with depressive symptoms at concurrent time periods (ps < 0.01). Machine learning analyses revealed that affective processes, nonfluencies, drives and risk words combined to most strongly predict changes in depressive symptoms over 18 weeks of treatment. LIMITATIONS: Study results were limited by the small sample and the exclusion of paralinguistic or contextual variables in analyzing speech samples. CONCLUSIONS: In youth at high risk for mood disorders, knowledge of speech patterns may inform prognoses during outpatient psychosocial treatment.

Reduced Environmental Stimulation Therapy (REST) in anxiety and depression: An experience sampling study.

Background: Reduced Environmental Stimulation Therapy (REST) is a behavioral intervention that systematically attenuates external sensory input to the nervous system. Previous studies have demonstrated acute anxiolytic and antidepressant effects of single sessions of REST in anxious individuals, however the duration and time course of these effects is unknown. In the current study, we used experience sampling and multiple sessions of REST to explore the time course of the anxiolytic and antidepressant effects over a 48-hour time period. Methods: 75 adults with anxiety and/or depression were randomized to complete 6 sessions of REST (either pool-REST, pool-REST preferred, or chair-REST). Post-REST effects were tracked using experience sampling on a smartphone with a ten-item survey administered at 6 time points for each session (i.e., immediately before and after REST and then 4, 8, 24, and 48 hours later). Using principal component analysis, responses to survey items at baseline were reduced to broad symptom clusters of anxiety, depression, and serenity and were utilized in linear mixed effects models to determine the magnitude and time course of post-REST effects. Results: REST was associated with significant decreases in anxiety and depression, and significant increases in serenity, with effects lasting for 48 hours. Repeated exposure to REST was associated with lower baseline levels of anxiety at later sessions. Conclusion: These initial findings suggest that the anxiolytic and antidepressant effects of REST persist for at least two days, and that repeated REST sessions may have additive effects on lowering anxiety-related symptoms. These findings could help to determine the optimal intervention frequency of REST and facilitate future investigations focused on the combination of REST with standard treatments for anxiety and depression.

Engagement, Use, and Impact of Digital Mental Health Resources for Diverse Populations in COVID-19: Community-Partnered Evaluation.

BACKGROUND: The COVID-19 pandemic increased disparities for communities burdened by structural barriers such as reduced affordable housing, with mental health consequences. Limited data are available on digital resources for public mental health prevention during the COVID-19 pandemic. OBJECTIVE: The study aim was to evaluate engagement in and impact of free digital resources on the Together for Wellness/Juntos por Nuestro Bienestar (T4W/Juntos) website during COVID-19 in California. METHODS: A pilot evaluation of T4W/Juntos was performed, with partner agencies inviting providers, clients, and partners to visit the website and complete surveys at baseline (September 20, 2021, to April 4, 2022) and at 4-6-week follow-up (October 22, 2021, to May 17, 2022). Website use was assessed by three engagement items (ease of use, satisfaction, relevance), comfort in use, and use of six resource categories. Primary outcomes at follow-up were depression and anxiety (scores≥3 on Patient Health Questionnaire-2 item [PHQ2] and Generalized Anxiety Disorder-2 item [GAD2] scales). Secondary outcomes were post-pre differences in PHQ2 and GAD2 scores, and use of behavioral health hotlines and services the month before follow-up. RESULTS: Of 366 eligible participants, 315 (86.1%) completed baseline and 193 (61.3%) completed follow-up surveys. Of baseline participants, 72.6% identified as female, and 21.3% identified as lesbian, gay, bisexual, transgender, queer/questioning, and others (LGBTQ+). In terms of ethnicity, 44.0% identified as Hispanic, 17.8% as African American, 26.9% as non-Hispanic white, and 11.4% as other ethnicity. Overall, 32.7% had moderate anxiety or depression (GAD2/PHQ2≥3) at baseline. Predictors of baseline website engagement included being Hispanic versus other race/ethnicity (ß=.27, 95% CI .10-.44; P=.002) and number of COVID-19-related behavior changes (ß=.09, 95% CI .05-.13; P<.001). Predictors of comfort using the website were preferring English for website use (odds ratio [OR] 5.57, 95% CI 2.22-13.96; P<.001) and COVID-19-related behavior changes (OR 1.37, 95% CI 1.12-1.66; P=.002); receiving overnight behavioral health treatment in the prior 6 months (OR 0.15, 95% CI 0.03-0.69, P=.015) was associated with less comfort in website use. The main predictor of depression at follow-up (PHQ2≥3) was baseline depression (OR 6.24, 95% CI 2.77-14.09; P<.001). Engagement in T4W/Juntos was associated with lower likelihood of depression (OR 0.54, 95% CI 0.34-0.86; P=.01). Website use the month before follow-up was associated with a post-pre reduction in PHQ2 score (ß=-.62, 95% CI -1.04 to -0.20; P=.004). The main predictor of GAD2≥3 at follow-up was baseline GAD2≥3 (OR 13.65, 95% CI 6.06-30.72; P<.001). Greater baseline website engagement predicted reduced hotline use (OR 0.36, 95% CI 0.18-0.71; P=.004). CONCLUSIONS: Ethnicity/language and COVID-19-related behavior changes were associated with website engagement; engagement and use predicted reduced follow-up depression and behavioral hotline use. Findings are based on participants recommended by community agencies with moderate follow-up rates; however, significance was similar when weighting for nonresponse. This study may inform research and policy on digital mental health prevention resources.

Co-created Mobile Apps for Palliative Care Using Community-Partnered Participatory Research: Development and Usability Study.

BACKGROUND: Open design formats for mobile apps help clinicians and stakeholders bring their needs to direct, co-creative solutions. Palliative care for patients with advanced cancers requires intensive monitoring and support and remains an area in high need for innovation. OBJECTIVE: This study aims to use community-partnered participatory research to co-design and pretest a mobile app that focuses on palliative care priorities of clinicians and patients with advanced cancer. METHODS: In-person and teleconference workshops were held with patient and family stakeholders, researchers, and clinicians in palliative care and oncology. Question prompts, written feedback, semistructured interviews, and facilitated group discussions identified the core palliative care needs. Using Chorus, a no-code app-building platform, a mobile app was co-designed with the stakeholders. A pretest with 11 patients was conducted, with semistructured interviews of clinician and patient users for feedback. RESULTS: Key themes identified from the focus groups included needs for patient advocacy and encouragement, access to vetted information, patient-clinician communication support, and symptom management. The initial prototype, My Wellness App, contained a weekly wellness journal to track patient-reported symptoms, goals, and medication use; information on self-management of symptoms; community resources; and patient and caregiver testimonial videos. Initial pretesting identified value in app-based communication for clinicians, patients, and caregivers, with suggestions for improving user interface, feedback and presentation of symptom reports, and gamification and staff coordinators to support patient app engagement. CONCLUSIONS: The development of a mobile app using community-partnered participatory research is a low-technology and feasible intervention for palliative care. Iterative redesign and user interface expertise may improve implementation.

Community-Partnered Development of a Digital Mental Health Resource Website to Support Diverse Communities During the COVID-19 Pandemic.

A state-academic-community partnership formed in response to the mental health needs fueled by the COVID-19 pandemic and the disproportionate effects on marginalized communities. Taking a community-partnered approach and using a health equity lens, the partnership developed a website to guide users through digital mental health resources, prioritizing accessibility, engagement, and community needs.

Visual mapping of body image disturbance in anorexia nervosa reveals objective markers of illness severity.

Body image disturbance (BID) is a core feature of eating disorders, for which there are few objective markers. We examined the feasibility of a novel digital tool, "Somatomap", to index BID related to anorexia nervosa (AN) severity. Fifty-five AN inpatients and 55 healthy comparisons (HC) outlined their body concerns on a 2-Dimensional avatar. Next, they indicated sizes/shapes of body parts for their current and ideal body using sliders on a 3-Dimensional avatar. Physical measurements of corresponding body parts, in cm, were collected for reference. We evaluated regional differences in BID using proportional z-scores to generate statistical body maps, and multivariate analysis of covariance to assess perceptual discrepancies for current body, ideal body, and body dissatisfaction. The AN group demonstrated greater regional perceptual inaccuracy for their current body than HC, greater discrepancies between their current and ideal body, and higher body dissatisfaction than HCs. AN body concerns localized disproportionately to the chest and lower abdomen. The number of body concerns and perceptual inaccuracy for individual body parts was strongly associated with Eating Disorder Examination Questionnaire (Global EDE-Q) scores across both groups. Somatomap demonstrated feasibility to capture multidimensional aspects of BID. Several implicit measures were significantly associated with illness severity, suggesting potential utility for identifying objective BID markers.

Using machine learning analyses of speech to classify levels of expressed emotion in parents of youth with mood disorders.

Expressed emotion (EE), a measure of attitudes among caregivers towards a patient with a psychiatric disorder, is a robust predictor of relapse across mood and psychotic disorders. Because the measurement of EE is time-intensive and costly, its use in clinical settings has been limited. In an effort to automate EE classification, we evaluated whether machine learning (ML) applied to lexical features of speech samples can accurately categorize parents as high or low in EE and in its subtypes (criticism, overinvolvement, and warmth). The sample was 123 parents of youth who had active mood symptoms and a family history of bipolar disorder. Using ML algorithms, we achieved 75.2-81.8% accuracy (sensitivities of ~0.7 and specificities of ~0.8) in classifying parents as high or low in EE and EE subtypes. Additionally, machine-derived EE classifications and observer-rated EE classifications had simiar relationships with youth mood symptoms, parental distress, and family conflict. Of note, criticism related to greater manic severity, parental distress, and family conflict. Study findings indicate that EE classification can be automated through lexical analysis and suggest potential for facilitating larger-scale applications in clinical settings. The results also provide initial indications of the digital phenotypes that underlie EE and its subtypes.

Development and Open Trial of a Technology-Enhanced Family Intervention for Adolescents at Risk for Mood Disorders.

AIM: Integrating psychosocial interventions with mobile apps may increase treatment engagement among adolescents. We examined the user experience, uptake, and clinical effects of a mobile-enhanced family-focused therapy (FFT) among adolescents at risk for mood disorders. METHOD: We created a mobile app containing 12 lesson plans corresponding to content of weekly FFT sessions, with modules concerning mood management, family communication and problem-solving. We pilot tested the app in an open trial of FFT (12 sessions in 18 weeks) for adolescents who had active depressive or hypomanic symptoms, a parent with mood disorder, and at least one parent who expressed high levels of criticism. Teens and parents made daily and weekly ratings of youths' moods, amount of parent/offspring criticism, and practice of FFT psychoeducational, communication or problem-solving skills. Independent evaluators interviewed adolescents at baseline and every 9 weeks over 27 weeks to measure symptom trajectories. RESULTS: Participants were adolescents (n=22; mean age 15.4 ± 1.8 years; 45.5% female) and their 34 parents. Completion of requested app assessment and skill practices averaged 46%-65% among adolescents and parents over 18 weeks of treatment. Adolescents showed significant improvement in clinician-rated depression scores over 27 weeks (Cohen's d=1.58, 95% CI, 0.83 to 2.32) and reported reductions in the amount of perceived criticism expressed by parents. LIMITATIONS: The uncontrolled design limits inferences about whether the mobile app augmented the effects of FFT on moods or family relationships. CONCLUSIONS: Mobile applications may enhance users' responses to family therapy and provide clinicians with information regarding clinical status. Clinicaltrials.gov NCT03913013.

Mental Health Community and Health System Issues in COVID-19: Lessons from Academic, Community, Provider and Policy Stakeholders.

The coronavirus pandemic of 2019 (COVID-19) has created unprecedented changes to everyday life for millions of Americans due to job loss, school closures, stay-at-home orders and health and mortality consequences. In turn, physicians, academics, and policymakers have turned their attention to the public mental health toll of COVID-19. This commentary reporting from the field integrates perceptions of academic, community, health system, and policy leaders from state, county, and local levels in commenting on community mental health needs in the COVID-19 pandemic. Stakeholders noted the broad public health scope of mental health challenges while expressing concern about exacerbation of existing disparities in access and adverse social determinants, including for communities with high COVID-19 infection rates, such as African Americans and Latinos. They noted rapid changes toward telehealth and remote care, and the importance of understanding impacts of changes, including who may benefit or have limited access, with implications for future services delivery. Needs for expanded workforce and training in mental health were noted, as well as potential public health value of expanding digital resources tailored to local populations for enhancing resilience to stressors. The COVID-19 pandemic has led to changes in delivery of health care services across populations and systems. Concerns over the mental health impact of COVID-19 has enhanced interest in remote mental care delivery and preventive services, while being mindful of potential for enhanced disparities and needs to address social determinants of health. Ongoing quality improvement across systems can integrate lessons learned to enhance a public mental well-being.

Patient and Provider Cocreation of Mobile Texting Apps to Support Behavioral Health: Usability Study.

BACKGROUND: Mobile technologies hold potential for improving the quality of care and engagement of patients. However, there are considerable challenges in ensuring that technologies are relevant, useful, and engaging. While end users such as patients and providers are increasingly involved in the design of health technologies, there are limited examples of their involvement in directly creating technologies for their personal use. OBJECTIVE: We aim to evaluate the feasibility and acceptability of patients and providers creating mobile texting apps to support treatment goals. METHODS: In an 11-month usability study, we enrolled 4 providers and 28 patients in an intensive outpatient program for obsessive-compulsive disorder. Patients and providers created their own mobile texting apps using a visual app development platform. A subsample of 10 patients and 4 providers completed a usability measure. RESULTS: Participants created a total of 360 unique mobile text messages (1787 total messages sent). There were 4 types of messages identified, including personalized reminders, clinical exposures, interactive prompts, and encouraging/informational messages. A total of 9 out of 10 (90%) patients agreed that the messages were relevant to their recovery, and 8 out of 10 (80%) agreed that the messages were effective at helping complete treatment plans. CONCLUSIONS: Enabling patients and providers to cocreate apps for their own use by using a visual application platform is feasible and holds potential for increasing the relevance, sustainability, and effectiveness of digital health technologies.

Clinical state tracking in serious mental illness through computational analysis of speech.

Individuals with serious mental illness experience changes in their clinical states over time that are difficult to assess and that result in increased disease burden and care utilization. It is not known if features derived from speech can serve as a transdiagnostic marker of these clinical states. This study evaluates the feasibility of collecting speech samples from people with serious mental illness and explores the potential utility for tracking changes in clinical state over time. Patients (n = 47) were recruited from a community-based mental health clinic with diagnoses of bipolar disorder, major depressive disorder, schizophrenia or schizoaffective disorder. Patients used an interactive voice response system for at least 4 months to provide speech samples. Clinic providers (n = 13) reviewed responses and provided global assessment ratings. We computed features of speech and used machine learning to create models of outcome measures trained using either population data or an individual's own data over time. The system was feasible to use, recording 1101 phone calls and 117 hours of speech. Most (92%) of the patients agreed that it was easy to use. The individually-trained models demonstrated the highest correlation with provider ratings (rho = 0.78, p<0.001). Population-level models demonstrated statistically significant correlations with provider global assessment ratings (rho = 0.44, p<0.001), future provider ratings (rho = 0.33, p<0.05), BASIS-24 summary score, depression sub score, and self-harm sub score (rho = 0.25,0.25, and 0.28 respectively; p<0.05), and the SF-12 mental health sub score (rho = 0.25, p<0.05), but not with other BASIS-24 or SF-12 sub scores. This study brings together longitudinal collection of objective behavioral markers along with a transdiagnostic, personalized approach for tracking of mental health clinical state in a community-based clinical setting.

Preparedness and Community Resilience in Disaster-Prone Areas: Cross-Sectoral Collaborations in South Louisiana, 2018.

Objectives. To determine how community-based organizations (CBOs) define priorities for bolstering community resilience, challenges in addressing these priorities, and strategies to address challenges.Methods. The Community Resilience Learning Collaborative and Research Network (C-LEARN) is a multiphase study examining opportunities to improve community resilience to the threats of disaster and climate change in South Louisiana. Phase I of C-LEARN involved using the National Health Security Strategy and Implementation Plan for directed content analysis of key informant interviews with CBO representatives from 47 agencies within South Louisiana between February and May 2018.Results. CBO interviewees highlighted the importance of forging relationships and building trust through diverse cross-sector collaborations and partnerships before disasters. Such collaborations and partnerships were shown to tailor disaster response to the needs of particular communities and populations as well as address key challenges such as gaps in information, services, and resources.Conclusions. Our results encourage a culture of community resilience and community preparedness through partnerships and community-engaged strategies. C-LEARN will utilize the results of our interviews in the design of phase II of our agency-level coalition-building intervention.

A Novel Mobile Tool (Somatomap) to Assess Body Image Perception Pilot Tested With Fashion Models and Nonmodels: Cross-Sectional Study.

BACKGROUND: Distorted perception of one's body and appearance, in general, is a core feature of several psychiatric disorders including anorexia nervosa and body dysmorphic disorder and is operative to varying degrees in nonclinical populations. Yet, body image perception is challenging to assess, given its subjective nature and variety of manifestations. The currently available methods have several limitations including restricted ability to assess perceptions of specific body areas. To address these limitations, we created Somatomap, a mobile tool that enables individuals to visually represent their perception of body-part sizes and shapes as well as areas of body concerns and record the emotional valence of concerns. OBJECTIVE: This study aimed to develop and pilot test the feasibility of a novel mobile tool for assessing 2D and 3D body image perception. METHODS: We developed a mobile 2D tool consisting of a manikin figure on which participants outline areas of body concern and indicate the nature, intensity, and emotional valence of the concern. We also developed a mobile 3D tool consisting of an avatar on which participants select individual body parts and use sliders to manipulate their size and shape. The tool was pilot tested on 103 women: 65 professional fashion models, a group disproportionately exposed to their own visual appearance, and 38 nonmodels from the general population. Acceptability was assessed via a usability rating scale. To identify areas of body concern in 2D, topographical body maps were created by combining assessments across individuals. Statistical body maps of group differences in body concern were subsequently calculated using the formula for proportional z-score. To identify areas of body concern in 3D, participants' subjective estimates from the 3D avatar were compared to corresponding measurements of their actual body parts. Discrepancy scores were calculated based on the difference between the perceived and actual body parts and evaluated using multivariate analysis of covariance. RESULTS: Statistical body maps revealed different areas of body concern between models (more frequently about thighs and buttocks) and nonmodels (more frequently about abdomen/waist). Models were more accurate at estimating their overall body size, whereas nonmodels tended to underestimate the size of individual body parts, showing greater discrepancy scores for bust, biceps, waist, hips, and calves but not shoulders and thighs. Models and nonmodels reported high ease-of-use scores (8.4/10 and 8.5/10, respectively), and the resulting 3D avatar closely resembled their actual body (72.7% and 75.2%, respectively). CONCLUSIONS: These pilot results suggest that Somatomap is feasible to use and offers new opportunities for assessment of body image perception in mobile settings. Although further testing is needed to determine the applicability of this approach to other populations, Somatomap provides unique insight into how humans perceive and represent the visual characteristics of their body.

Depression Remission From Community Coalitions Versus Individual Program Support for Services: Findings From Community Partners in Care, Los Angeles, California, 2010-2016.

Objectives. To explore effects of coalitions (Community Engagement and Planning [CEP]) versus technical assistance (Resources for Services [RS]) for depression collaborative care and the effects of social determinants on long-term remission outcomes. Methods. We randomized 95 health care and community programs in Los Angeles County, California, to CEP or RS. In 2010, 1246 depressed (Patient Health Questionnaire [PHQ-8] ≥ 10) adults enrolled and were invited for baseline and 6-, 12-, and 36-month surveys. Of 598 3-year completers, 283 participated at 4 years (2016). We examined effects of CEP versus RS, social factors (e.g., family income, food insecurity) on time to and periods in clinical (PHQ-8 < 10) and community-defined (PHQ-8 < 10 or PHQ-2 < 3; mental health composite score [MCS-12] > 40, or mental wellness) remission during the course of 3 years, and at 4 years. Results. We found that CEP versus RS increased 4-year depression remission and, for women, community-defined remission outcomes during the course of 3 years. Social factors and clinical factors predicted remission. Conclusions. At 4 years, CEP was more effective than RS at increasing depression remission. Public Health Implications. Coalitions may improve 4-year depression remission, while addressing social and clinical factors associated with depression may hold potential to enhance remission.

Community Engagement and Planning versus Resources for Services for Implementing Depression Quality Improvement: Exploratory Analysis for Black and Latino Adults.

Objective: Racial/ethnic minorities experience disparities in depression1 and there is a paucity of evidence-based interventions to improve depression care access and outcomes. Community Partners in Care (CPIC) is a community-partnered study of depression care quality improvement (QI) in under-resourced, urban communities: Community Engagement and Planning (CEP) for multi-sector coalitions, and Resources for Services (RS) for program technical assistance.2 CEP demonstrated benefits for the overall CPIC study population; effects for Black and Latino sub-populations are unknown. Methods: This sub-analysis examines outcomes for 409 Latino and 488 Black (non-Latino) adults recruited from 90 programs who completed baseline or 6-month follow-up. Regression analyses were used to estimate CEP vs RS intervention effects on primary (Mental Health Related Quality of Life [MHRQL], Patient Health Questionnaire-9 [PHQ-9]) and community-prioritized (mental wellness, physical activity, risk for homelessness) outcomes at 6-months. Results: Baseline characteristics did not differ significantly by intervention in either group. In the adjusted analysis for Black adults, CEP resulted in decreased odds of poor MHRQL (OR: .62, 95% CI=.41-.94, P=.028) with a trend for reducing homelessness risk (OR: .60, .35-1.05, P=.69). For Latino adults, CEP resulted in greater probability of mental wellness (OR: 1.81, 1.05-3.13, P=.034) and a trend for increased physical activity (OR: 1.52, .93-2.49, P=.091). Conclusions: Exploratory analyses of CEP for depression quality improvement suggests significant 6-month benefits in mental health outcomes for Black and Latino participants and trends for improvement in community-prioritized outcomes for both groups. Findings may inform research in multi-sector coalitions to promote equity in depression care.

A Clinical Care Monitoring and Data Collection Tool (H3 Tracker) to Assess Uptake and Engagement in Mental Health Care Services in a Community-Based Pediatric Integrated Care Model: Longitudinal Cohort Study.

BACKGROUND: National recommendations for pediatric integrated care models include improved capacity for care coordination and communication across primary care and specialty mental health providers using technology, yet few practical, short-term solutions are available for low-resource, community-based pediatric integrated care clinics. OBJECTIVE: The goal of the paper is to describe the development and features of a Web-based tool designed for program evaluation and clinician monitoring of embedded pediatric mental health care using a community-partnered approach. In addition, a longitudinal study design was used to assess the implementation of the tool in program evaluation, including clinical monitoring and data collection. METHODS: Biweekly meetings of the partnered evaluation team (clinic, academic, and funding partners) were convened over the course of 12 months to specify tool features using a participatory framework, followed by usability testing and further refinement during implementation. RESULTS: A data collection tool was developed to collect clinic population characteristics as well as collect and display patient mental health outcomes and clinical care services from 277 eligible caregiver/child participants. Despite outreach, there was little uptake of the tool by either the behavioral health team or primary care provider. CONCLUSIONS: Development of the H3 Tracker (Healthy Minds, Healthy Children, Healthy Chicago Tracker) in two community-based pediatric clinics with embedded mental health teams serving predominantly minority children is feasible and promising for on-site program evaluation data collection. Future research is needed to understand ways to improve clinic integration and examine whether promotion of primary care/mental health communication drives sustained use. TRIAL REGISTRATION: ClinicalTrials.gov NCT02699814; https://clinicaltrials.gov/ct2/show/NCT02699814 (Archived by WebCite at http://www.webcitation.org/772pV5rWW).

Feasibility of Online Mental Wellness Self-assessment and Feedback for Pediatric and Neonatal Critical Care Nurses.

PURPOSE: The primary goal of this study was to test the feasibility of an educational online self-assessment of burnout, resilience, trauma, depression, anxiety, and common workplace stressors among nurses working in a pediatric intensive care unit or neonatal intensive care unit setting. The secondary, exploratory objectives were to estimate the prevalence of psychiatric symptoms in this sample and to identify those variables that most strongly predict burnout. DESIGN AND METHODS: Data from optional and anonymous online measures were analyzed for 115 nurses (67.9% aged 25-44; 61.7% Caucasian) working in an urban children's hospital pediatric or neonatal ICU. Multiple linear regressions identified demographic variables and workplace stressors that significantly predicted each of three components of burnout. RESULTS: Most respondents found the educational assessment and feedback to be helpful. Choosing nursing as a second career was associated with better resilience. Having worked in ICU settings longer and being older were both linked to lower levels of anxiety. Predictors of burnout varied across the three burnout subscales. CONCLUSIONS: Implementation of an online self-assessment with immediate educational feedback is feasible in critical care settings. The variability of predictors across the three burnout subscales indicates the need for tailored interventions for those at risk. Future research may include follow-up of nurses to examine changes in scores over time and expansion of the tool for other medical personnel. PRACTICE IMPLICATIONS: An educational online self-assessment can be a helpful tool for pediatric critical care nurses experiencing varying degrees of burnout and distress.