Rethinking Data Collection Methods During the Pandemic: Development and Implementation of CATI for the All of Us Research Program.

The All of Us Research Program is a longitudinal cohort study aiming to build a diverse database to advance precision medicine. The COVID-19 pandemic hindered the ability of participants to receive in-person assistance at enrollment sites to complete digital surveys. Therefore, the program implemented Computer-Assisted Telephone Interviewing (CATI) to facilitate survey completion remotely to combat the disrupted data collection procedures. In January 2021, All of Us implemented a 1-year CATI Pilot supporting 9399 participants and resulting in 16 337 submitted surveys. The pilot showed that CATI was successful in increasing survey completion and retention activities for the All of Us Research Program, given the additional remote support offered to participants. Given the success of the CATI Pilot, multimodal survey administration will continue.

Design and Implementation of the All of Us Research Program COVID-19 Participant Experience (COPE) Survey.

In response to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021, covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all 6 surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, P < 0.001). This paper describes a data set with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a data set that is of additional scientific value when combined with the program's other data sources.

A Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder (LiveWell): Empirical and Theoretical Framework, Intervention Design, and Study Protocol for a Randomized Controlled Trial.

BACKGROUND: Bipolar disorder is a severe mental illness with high morbidity and mortality rates. Even with pharmacological treatment, frequent recurrence of episodes, long episode durations, and persistent interepisode symptoms are common and disruptive. Combining psychotherapy with pharmacotherapy improves outcomes; however, many individuals with bipolar disorder do not receive psychotherapy. Mental health technologies can increase access to self-management strategies derived from empirically supported bipolar disorder psychotherapies while also enhancing treatment by delivering real-time assessments, personalized feedback, and provider alerts. In addition, mental health technologies provide a platform for self-report, app use, and behavioral data collection to advance understanding of the longitudinal course of bipolar disorder, which can then be used to support ongoing improvement of treatment. OBJECTIVE: A description of the theoretical and empirically supported framework, design, and protocol for a randomized controlled trial (RCT) of LiveWell, a smartphone-based self-management intervention for individuals with bipolar disorder, is provided to facilitate the ability to replicate, improve, implement, and disseminate effective interventions for bipolar disorder. The goal of the trial is to determine the effectiveness of LiveWell for reducing relapse risk and symptom burden as well as improving quality of life (QOL) while simultaneously clarifying behavioral targets involved in staying well and better characterizing the course of bipolar disorder and treatment response. METHODS: The study is a single-blind RCT (n=205; 2:3 ratio of usual care vs usual care plus LiveWell). The primary outcome is the time to relapse. Secondary outcomes are percentage time symptomatic, symptom severity, and QOL. Longitudinal changes in target behaviors proposed to mediate the primary and secondary outcomes will also be determined, and their relationships with the outcomes will be assessed. A database of clinical status, symptom severity, real-time self-report, behavioral sensor, app use, and personalized content will be created to better predict treatment response and relapse risk. RESULTS: Recruitment and screening began in March 2017 and ended in April 2019. Follow-up ended in April 2020. The results of this study are expected to be published in 2022. CONCLUSIONS: This study will examine whether LiveWell reduces relapse risk and symptom burden and improves QOL for individuals with bipolar disorder by increasing access to empirically supported self-management strategies. The role of selected target behaviors (medication adherence, sleep duration, routine, and management of signs and symptoms) in these outcomes will also be examined. Simultaneously, a database will be created to initiate the development of algorithms to personalize and improve treatment for bipolar disorder. In addition, we hope that this description of the theoretical and empirically supported framework, intervention design, and study protocol for the RCT of LiveWell will facilitate the ability to replicate, improve, implement, and disseminate effective interventions for bipolar and other mental health disorders. TRIAL REGISTRATION: ClinicalTrials.gov NCT03088462; https://www.clinicaltrials.gov/ct2/show/NCT03088462. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30710.

Symptom burden profiles in men with advanced prostate cancer undergoing androgen deprivation therapy.

To identify symptom burden profiles among men with advanced prostate cancer undergoing androgen-deprivation therapy and examine their association with baseline sociodemographic and medical characteristics and psychosocial outcomes over time. Latent profile analysis was employed to identify distinct groups based on the Expanded Prostate Index Composite and the McGill Pain Questionnaire at baseline. Psychosocial outcomes were assessed at baseline, 6- and 12-month follow-ups. Three profiles emerged: "high symptom burden," "high sexual bother," and "low symptom burden." Men with "high symptom burden" were younger and exhibited higher baseline levels of depression, stress, cancer-specific distress, and anxiety than men in the other two groups. However, men with "high symptom burden" also demonstrated improvement in these psychosocial outcomes over time. Men with advanced prostate cancer who experience multiple co-occurring symptoms demonstrate worse psychosocial adjustment. Patients with substantial symptom burden, and specifically young men, may benefit from prompt referral to supportive care services.

A Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder (LiveWell): Protocol Development for an Expert System to Provide Adaptive User Feedback.

BACKGROUND: Bipolar disorder is a severe mental illness that results in significant morbidity and mortality. While pharmacotherapy is the primary treatment, adjunctive psychotherapy can improve outcomes. However, access to therapy is limited. Smartphones and other technologies can increase access to therapeutic strategies that enhance self-management while simultaneously augmenting care by providing adaptive delivery of content to users as well as alerts to providers to facilitate clinical care communication. Unfortunately, while adaptive interventions are being developed and tested to improve care, information describing the components of adaptive interventions is often not published in sufficient detail to facilitate replication and improvement of these interventions. OBJECTIVE: To contribute to and support the improvement and dissemination of technology-based mental health interventions, we provide a detailed description of the expert system for adaptively delivering content and facilitating clinical care communication for LiveWell, a smartphone-based self-management intervention for individuals with bipolar disorder. METHODS: Information from empirically supported psychotherapies for bipolar disorder, health psychology behavior change theories, and chronic disease self-management models was combined with user-centered design data and psychiatrist feedback to guide the development of the expert system. RESULTS: Decision points determining the timing of intervention option adaptation were selected to occur daily and weekly based on self-report data for medication adherence, sleep duration, routine, and wellness levels. These data were selected for use as the tailoring variables determining which intervention options to deliver when and to whom. Decision rules linking delivery of options and tailoring variable thresholds were developed based on existing literature regarding bipolar disorder clinical status and psychiatrist feedback. To address the need for treatment adaptation with varying clinical statuses, decision rules for a clinical status state machine were developed using self-reported wellness rating data. Clinical status from this state machine was incorporated into hierarchal decision tables that select content for delivery to users and alerts to providers. The majority of the adaptive content addresses sleep duration, medication adherence, managing signs and symptoms, building and utilizing support, and keeping a regular routine, as well as determinants underlying engagement in these target behaviors as follows: attitudes and perceptions, knowledge, support, evaluation, and planning. However, when problems with early warning signs, symptoms, and transitions to more acute clinical states are detected, the decision rules shift the adaptive content to focus on managing signs and symptoms, and engaging with psychiatric providers. CONCLUSIONS: Adaptive mental health technologies have the potential to enhance the self-management of mental health disorders. The need for individuals with bipolar disorder to engage in the management of multiple target behaviors and to address changes in clinical status highlights the importance of detailed reporting of adaptive intervention components to allow replication and improvement of adaptive mental health technologies for complex mental health problems.

Effect of a Digital Intervention on Depressive Symptoms in Patients With Comorbid Hypertension or Diabetes in Brazil and Peru: Two Randomized Clinical Trials.

Importance: Depression is a leading contributor to disease burden globally. Digital mental health interventions can address the treatment gap in low- and middle-income countries, but the effectiveness in these countries is unknown. Objective: To investigate the effectiveness of a digital intervention in reducing depressive symptoms among people with diabetes and/or hypertension. Design, Setting, and Participants: Participants with clinically significant depressive symptoms (Patient Health Questionnaire-9 [PHQ-9] score ≥10) who were being treated for hypertension and/or diabetes were enrolled in a cluster randomized clinical trial (RCT) at 20 sites in São Paulo, Brazil (N=880; from September 2016 to September 2017; final follow-up, April 2018), and in an individual-level RCT at 7 sites in Lima, Peru (N=432; from January 2017 to September 2017; final follow-up, March 2018). Interventions: An 18-session, low-intensity, digital intervention was delivered over 6 weeks via a provided smartphone, based on behavioral activation principles, and supported by nurse assistants (n = 440 participants in 10 clusters in São Paulo; n = 217 participants in Lima) vs enhanced usual care (n = 440 participants in 10 clusters in São Paulo; n = 215 participants in Lima). Main Outcomes and Measures: The primary outcome was a reduction of at least 50% from baseline in PHQ-9 scores (range, 0-27; higher score indicates more severe depression) at 3 months. Secondary outcomes included a reduction of at least 50% from baseline PHQ-9 scores at 6 months. Results: Among 880 patients cluster randomized in Brazil (mean age, 56.0 years; 761 [86.5%] women) and 432 patients individually randomized in Peru (mean age, 59.7 years; 352 [81.5%] women), 807 (91.7%) in Brazil and 426 (98.6%) in Peru completed at least 1 follow-up assessment. The proportion of participants in São Paulo with a reduction in PHQ-9 score of at least 50% at 3-month follow-up was 40.7% (159/391 participants) in the digital intervention group vs 28.6% (114/399 participants) in the enhanced usual care group (difference, 12.1 percentage points [95% CI, 5.5 to 18.7]; adjusted odds ratio [OR], 1.6 [95% CI, 1.2 to 2.2]; P = .001). In Lima, the proportion of participants with a reduction in PHQ-9 score of at least 50% at 3-month follow-up was 52.7% (108/205 participants) in the digital intervention group vs 34.1% (70/205 participants) in the enhanced usual care group (difference, 18.6 percentage points [95% CI, 9.1 to 28.0]; adjusted OR, 2.1 [95% CI, 1.4 to 3.2]; P < .001). At 6-month follow-up, differences across groups were no longer statistically significant. Conclusions and Relevance: In 2 RCTs of patients with hypertension or diabetes and depressive symptoms in Brazil and Peru, a digital intervention delivered over a 6-week period significantly improved depressive symptoms at 3 months when compared with enhanced usual care. However, the magnitude of the effect was small in the trial from Brazil and the effects were not sustained at 6 months. Trial Registration: ClinicalTrials.gov: NCT02846662 (São Paulo) and NCT03026426 (Lima).

A Smartphone-Based Self-management Intervention for Bipolar Disorder (LiveWell): User-Centered Development Approach.

BACKGROUND: Bipolar disorder is a serious mental illness that results in significant morbidity and mortality. Pharmacotherapy is the primary treatment for bipolar disorder; however, adjunctive psychotherapy can help individuals use self-management strategies to improve outcomes. Yet access to this therapy is limited. Smartphones and other technologies have the potential to increase access to therapeutic strategies that enhance self-management while simultaneously providing real-time user feedback and provider alerts to augment care. OBJECTIVE: This paper describes the user-centered development of LiveWell, a smartphone-based self-management intervention for bipolar disorder, to contribute to and support the ongoing improvement and dissemination of technology-based mental health interventions. METHODS: Individuals with bipolar disorder first participated in a field trial of a simple smartphone app for self-monitoring of behavioral targets. To develop a complete technology-based intervention for bipolar disorder, this field trial was followed by design sessions, usability testing, and a pilot study of a smartphone-based self-management intervention for bipolar disorder. Throughout all phases of development, intervention revisions were made based on user feedback. RESULTS: The core of the LiveWell intervention consists of a daily self-monitoring tool, the Daily Check-in. This self-monitoring tool underwent multiple revisions during the user-centered development process. Daily Check-in mood and thought rating scales were collapsed into a single wellness rating scale to accommodate user development of personalized scale anchors. These anchors are meant to assist users in identifying early warning signs and symptoms of impending episodes to take action based on personalized plans. When users identified personal anchors for the wellness scale, the anchors most commonly reflected behavioral signs and symptoms (40%), followed by cognitive (25%), mood (15%), physical (10%), and motivational (7%) signs and symptoms. Changes to the Daily Check-in were also made to help users distinguish between getting adequate sleep and keeping a regular routine. At the end of the pilot study, users reported that the Daily Check-in made them more aware of early warning signs and symptoms and how much they were sleeping. Users also reported that they liked personalizing their anchors and plans and felt this process was useful. Users experienced some difficulties with developing, tracking, and achieving target goals. Users also did not consistently follow up with app recommendations to contact providers when Daily Check-in data suggested they needed additional assistance. As a result, the human support roles for the technology were expanded beyond app use support to include support for self-management and clinical care communication. The development of these human support roles was aided by feedback on the technology's usability from the users and the coaches who provided the human support. CONCLUSIONS: User input guided the development of intervention content, technology, and coaching support for LiveWell. Users valued the provision of monitoring tools and the ability to personalize plans for staying well, supporting the role of monitoring and personalization as important features of digital mental health technologies. Users also valued human support of the technology in the form of a coach, and user difficulties with aspects of self-management and care-provider communication led to an expansion of the coach's support roles. Obtaining feedback from both users and coaches played an important role in the development of both the LiveWell technology and human support. Attention to all stakeholders involved in the use of mental health technologies is essential for optimizing intervention development.

Effects of web-based cognitive behavioral stress management and health promotion interventions on neuroendocrine and inflammatory markers in men with advanced prostate cancer: A randomized controlled trial.

Cognitive behavioral stress management (CBSM) improves quality of life and mitigates stress biology in patients with early-stage cancer, including men with localized prostate cancer. However, treatments for advanced prostate cancer like androgen deprivation therapy (ADT) can lead to significant symptom burden that may be further exacerbated by stress-induced inflammation and cortisol dysregulation. The aim of this study was to examine the effects of CBSM (versus an active health promotion control) on circulating inflammatory markers and cortisol in men with advanced prostate cancer. METHODS: Men with stage III or IV prostate cancer (N = 192) who had undergone ADT within the last year were randomized to CBSM or health promotion. Both interventions were 10 weeks, group-based, and delivered online. Venous blood was drawn at baseline, 6 months, and 12 months to measure circulating levels of CRP, IL-6, IL-8, IL-10, and TNF-α. Saliva samples were collected at awakening, 30 min after awakening, evening, and night for two consecutive days at baseline, 6-months, and 12-months to measure diurnal cortisol slopes. RESULTS: Mixed modeling analyses demonstrated that changes in inflammatory markers and cortisol did not differ by intervention. Men in both CBSM and health promotion showed decreases in IL-10, IL-8, and TNF-α from baseline to 6 months (ß = -3.85--5.04, p's = 0.004-<0.001). However, these markers generally demonstrated a rebound increase from 6 to 12 months (ß = 1.91-4.06, p's = 0.06-<0.001). Men in health promotion also demonstrated a flatter diurnal cortisol slope versus men in CBSM at 6 months (ß = -2.27, p = .023), but not at 12 months. There were no intervention effects on CRP, IL-6, or overall cortisol output. CONCLUSIONS: Contrary to hypotheses, CBSM did not lead to changes in the circulating inflammatory markers and cortisol relative to health promotion. CBSM may be associated with healthy diurnal cortisol rhythm because of its focus on cognitive behavioral approaches to stress management. More research is needed to understand the impact of CBSM and health promotion on biomarkers among men with advanced prostate cancer.

Technology-Based Psychosocial Intervention to Improve Quality of Life and Reduce Symptom Burden in Men with Advanced Prostate Cancer: Results from a Randomized Controlled Trial.

BACKGROUND: Men with advanced prostate cancer (APC) face multiple challenges including poor prognosis, poor health-related quality of life (HRQOL), and elevated symptom burden. This study sought to establish the efficacy of a tablet-delivered, group-based psychosocial intervention for improving HRQOL and reducing symptom burden in men with APC. We hypothesized that men randomized to cognitive-behavioral stress management (CBSM) would report improved HRQOL and reduced symptom burden relative to men randomized to an active control health promotion (HP) condition. Condition effects on intervention targets and moderators of these effects were explored. METHODS: Men with APC (N = 192) were randomized (1:1) to 10-week tablet-delivered CBSM or HP, and followed for 1 year. Multilevel modeling was used to evaluate condition effects over time. RESULTS: Changes in HRQOL and symptom burden did not differ between groups. Men in both groups improved across several intervention targets; men in the CBSM condition reported greater increases in self-reported ability to relax, and both conditions showed improvements in cancer-related anxiety, cancer-related distress, and feelings of cohesiveness with other patients over time. Moderating factors included baseline interpersonal disruption, fatigue, and sexual functioning. CONCLUSIONS: Tablet-delivered CBSM and HP were well received by men with APC. The hypothesized effects of CBSM on HRQOL and symptom burden were not supported, though improvements in intervention targets were observed across conditions. Participants reported high-baseline HRQOL relative to cancer and general population norms, possibly limiting intervention effects. The identified moderating factors should be considered in the development and implementation of interventions targeting HRQOL and symptom burden. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03149185.

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices.

BACKGROUND: With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable, and extensible platform is of high interest to the open source mHealth community. The European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field. OBJECTIVE: Wide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was to build a platform that would cater for large-scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security, and privacy. METHODS: RADAR-base is developed as a modular application; the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided. RESULTS: General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy, and Depression cohorts. CONCLUSIONS: RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.

Integrating PROMIS® computerized adaptive tests into a web-based intervention for prostate cancer.

OBJECTIVE: This study outlined the implementation and feasibility of delivering PROMIS® computer adaptive tests (CATs) using a web-based method to evaluate the impact of a technological adaptation of Cognitive-Behavioral Stress Management (CBSM) on the psychosocial functioning of men with advanced prostate cancer (APC) undergoing hormone therapy. METHOD: Patients were randomized to a CBSM group intervention (n = 95) or a health promotion (HP) attention-matched control condition (n = 97). Participants attended all sessions via video conference using tablets, and completed PROMIS® computer adaptive tests (CATs) assessing anxiety, depression, fatigue, pain interference, and physical function weekly during the 10-week intervention. RESULTS: Assessment completion rates >50% at week 1 and week 10 demonstrated moderate feasibility of repeatedly administering PROMIS® CATs using a web-based method. Multilevel modeling demonstrated no significant group-by-time interactions from week 1 to week 10 for any of the assessed PROMIS® domains adjusting for sociodemographic and medical covariates. However, simple effects demonstrated decreases in PROMIS® anxiety scores from week 1 to 10 for both groups. Results also demonstrated significant relationships of medical variables to psychosocial functioning across time points. CONCLUSIONS: Results highlight the feasibility and benefits of utilizing PROMIS® CATs to repeatedly assess psychosocial functioning using a web-based method and indicate that web-based interventions may be effective for decreasing psychosocial distress and adverse symptoms among men with APC undergoing hormone therapy. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Development of the Initial Surveys for the All of Us Research Program.

BACKGROUND: The All of Us Research Program is building a national longitudinal cohort and collecting data from multiple information sources (e.g., biospecimens, electronic health records, and mobile/wearable technologies) to advance precision medicine. Participant-provided information, collected via surveys, will complement and augment these information sources. We report the process used to develop and refine the initial three surveys for this program. METHODS: The All of Us survey development process included: (1) prioritization of domains for scientific needs, (2) examination of existing validated instruments, (3) content creation, (4) evaluation and refinement via cognitive interviews and online testing, (5) content review by key stakeholders, and (6) launch in the All of Us electronic participant portal. All content was translated into Spanish. RESULTS: We conducted cognitive interviews in English and Spanish with 169 participants, and 573 individuals completed online testing. Feedback led to over 40 item content changes. Lessons learned included: (1) validated survey instruments performed well in diverse populations reflective of All of Us; (2) parallel evaluation of multiple languages can ensure optimal survey deployment; (3) recruitment challenges in diverse populations required multiple strategies; and (4) key stakeholders improved integration of surveys into larger Program context. CONCLUSIONS: This efficient, iterative process led to successful testing, refinement, and launch of three All of Us surveys. Reuse of All of Us surveys, available at http://researchallofus.org, may facilitate large consortia targeting diverse populations in English and Spanish to capture participant-provided information to supplement other data, such as genetic, physical measurements, or data from electronic health records.

Technology-Assisted Behavioral Intervention to Extend Sleep Duration: Development and Design of the Sleep Bunny Mobile App.

BACKGROUND: Despite the high prevalence of short sleep duration (29.2% of adults sleep <6 hours on weekdays), there are no existing theory-based behavioral interventions to extend sleep duration. The popularity of wearable sleep trackers provides an opportunity to engage users in interventions. OBJECTIVE: The objective of this study was to outline the theoretical foundation and iterative process of designing the "Sleep Bunny," a technology-assisted sleep extension intervention including a mobile phone app, wearable sleep tracker, and brief telephone coaching. We conducted a two-step process in the development of this intervention, which was as follows: (1) user testing of the app and (2) a field trial that was completed by 2 participants with short sleep duration and a cardiovascular disease risk factor linked to short sleep duration (body mass index [BMI] >25). METHODS: All participants had habitual sleep duration <6.5 hours verified by 7 days of actigraphy. A total of 6 individuals completed initial user testing in the development phase, and 2 participants completed field testing. Participants in the user testing and field testing responded to open-ended surveys about the design and utility of the app. Participants in the field testing completed the Epworth Sleepiness Scale and also wore an actigraph for a 1-week baseline period and during the 4-week intervention period. RESULTS: The feedback suggests that users enjoyed the wearable sleep tracker and found the app visually pleasing, but they suggested improvements to the notification and reminder features of the app. The 2 participants who completed the field test demonstrated significant improvements in sleep duration and daytime sleepiness. CONCLUSIONS: Further testing is needed to determine effects of this intervention in populations at risk for the mental and physical consequences of sleep loss.

Patterns and Predictors of Compliance in a Prospective Diary Study of Substance Use and Sexual Behavior in a Sample of Young Men Who Have Sex With Men.

Behavioral diaries are used for observing health-related behaviors prospectively. Little is known about patterns and predictors of diary compliance to better understand differential attrition. An analytic sample of 241 young men who have sex with men (YMSM) from a 2-month diary study of substance use and sexual behavior were randomized to complete daily or weekly timeline followback diaries. Latent class growth analyses were used to analyze data. Weekly and daily diary groups produced similar compliance patterns: high, low, and declining compliance groups. Black YMSM were more likely to be in the declining compared with the high compliance group. YMSM who were randomly assigned to receive automated feedback about risk behaviors did not differ in compliance rate compared with those who did not. Risk behavior engagement did not predict compliance in the daily condition, but some substances predicted compliance in the weekly condition. Implications for observational and behavior change methods are discussed.

Design and evaluation of a peer network to support adherence to a web-based intervention for adolescents.

BACKGROUND: Depression during adolescence is common but can be prevented. Behavioral intervention technologies (BITs) designed to prevent depression in adolescence, especially standalone web-based interventions, have shown mixed outcomes, likely due to poor intervention adherence. BIT research involving adults has shown that the presence of coaches or peers promotes intervention use. Developmentally, adolescence is a time when peer-based social relationships take precedence. This study examines whether peer-networked support may promote adherence to BITs in this age group. OBJECTIVE: Adopting the framework of the Supportive Accountability model, which defines the types of human support and interactions required to maintain engagement and persistence with BITs, this paper presents a feasibility study of a peer-networked online intervention for depression prevention among adolescents. We described the development of the peer network, the evaluation of participant use of the peer networking features, and qualitative user feedback to inform continued BIT development. METHOD: Two groups of adolescents (N = 13) participated in 10-week programs of the peer networked based online intervention. Adolescents had access to didactic lessons, CBT based mood management tools, and peer networking features. The peer networking features are integrated into the site by making use expectations explicit, allow network members to monitor the activities of others, and to supportively hold each other accountable for meeting use expectations. The study collected qualitative feedback from participants as well as usage of site features and tools. RESULTS: Participants logged in an average of 12.8 sessions over an average of 10.4 unique days during the 10-week program. On average, 66% of all use sessions occurred within the first 3 weeks of use. The number of "exchange comments", that is, comments posted that were part of an exchange between two or more participants, was significantly positively correlated with mean time spent on site (r = 0.62, p = 0.032), use of the Activity Tracker (r = 0.70, p = 0.012) and Didactic Lesson (r = 0.73, p = 0.007). Qualitative interviews revealed that adolescents generally liked and were motivated by the peer networking features during the first weeks of the intervention when general site use by group members was high. However, the decrease of site use by group members during the subsequent weeks negatively affected participants' desire to log on or engage with group members. CONCLUSIONS: This pilot study highlights the potential that a BIT designed to harness the connection among a peer network, thereby promoting supportive accountability, may improve adolescent adherence to BITs for depression prevention.

Uptake and Usage of IntelliCare: A Publicly Available Suite of Mental Health and Well-Being Apps.

BACKGROUND: Treatments for depression and anxiety have several behavioral and psychological targets and rely on varied strategies. Digital mental health treatments often employ feature-rich approaches addressing several targets and strategies. These treatments, often optimized for desktop computer use, are at odds with the ways people use smartphone applications. Smartphone use tends to focus on singular functions with easy navigation to desired tools. The IntelliCare suite of apps was developed to address the discrepancy between need for diverse behavioral strategies and constraints imposed by typical app use. Each app focuses on one strategy for a limited subset of clinical aims all pertinent to depression and anxiety. This study presents the uptake and usage of apps from the IntelliCare suite following an open deployment on a large app marketplace. METHODS: Thirteen lightweight apps, including 12 interactive apps and one Hub app that coordinates use across those interactive apps, were developed and made free to download on the Google Play store. De-identified app usage data from the first year of IntelliCare suite deployment were analyzed for this study. RESULTS: In the first year of public availability, 5,210 individuals downloaded one or more of the IntelliCare apps, for a total of 10,131 downloads. Nearly a third of these individuals (31.8%) downloaded more than one of these apps. The modal number of launches for each of the apps was 1, however the mean number of app launches per app ranged from 3.10 to 16.98, reflecting considerable variability in the use of each app. CONCLUSIONS: The use rate of the IntelliCare suite of apps is higher than public deployments of other comparable digital resources. Our findings suggest that people will use multiple apps and provides support for the concept of app suites as a useful strategy for providing diverse behavioral strategies.

mHealth for Schizophrenia: Patient Engagement With a Mobile Phone Intervention Following Hospital Discharge.

BACKGROUND: mHealth interventions that use mobile phones as instruments for illness management are gaining popularity. Research examining mobile phone‒based mHealth programs for people with psychosis has shown that these approaches are feasible, acceptable, and clinically promising. However, most mHealth initiatives involving people with schizophrenia have spanned periods ranging from a few days to several weeks and have typically involved participants who were clinically stable. OBJECTIVE: Our aim was to evaluate the viability of extended mHealth interventions for people with schizophrenia-spectrum disorders following hospital discharge. Specifically, we set out to examine the following: (1) Can individuals be engaged with a mobile phone intervention program during this high-risk period?, (2) Are age, gender, racial background, or hospitalization history associated with their engagement or persistence in using a mobile phone intervention over time?, and (3) Does engagement differ by characteristics of the mHealth intervention itself (ie, pre-programmed vs on-demand functions)? METHODS: We examined mHealth intervention use and demographic and clinical predictors of engagement in 342 individuals with schizophrenia-spectrum disorders who were given the FOCUS mobile phone intervention as part of a technology-assisted relapse prevention program during the 6-month high-risk period following hospitalization. RESULTS: On average, participants engaged with FOCUS for 82% of the weeks they had the mobile phone. People who used FOCUS more often continued using it over longer periods: 44% used the intervention over 5-6 months, on average 4.3 days a week. Gender, race, age, and number of past psychiatric hospitalizations were associated with engagement. Females used FOCUS on average 0.4 more days a week than males. White participants engaged on average 0.7 days more a week than African-Americans and responded to prompts on 0.7 days more a week than Hispanic participants. Younger participants (age 18-29) had 0.4 fewer days of on-demand use a week than individuals who were 30-45 years old and 0.5 fewer days a week than older participants (age 46-60). Participants with fewer past hospitalizations (1-6) engaged on average 0.2 more days a week than those with seven or more. mHealth program functions were associated with engagement. Participants responded to prompts more often than they self-initiated on-demand tools, but both FOCUS functions were used regularly. Both types of intervention use declined over time (on-demand use had a steeper decline). Although mHealth use declined, the majority of individuals used both on-demand and system-prompted functions regularly throughout their participation. Therefore, neither function is extraneous. CONCLUSIONS: The findings demonstrated that individuals with schizophrenia-spectrum disorders can actively engage with a clinically supported mobile phone intervention for up to 6 months following hospital discharge. mHealth may be useful in reaching a clinical population that is typically difficult to engage during high-risk periods.

MedLink: A mobile intervention to improve medication adherence and processes of care for treatment of depression in general medicine.

BACKGROUND: Major depressive disorder is a common psychological problem affecting up to 20% of adults in their lifetime. The majority of people treated for depression receive antidepressant medication through their primary care physician. This commonly results in low rates of recovery. Failure points in the process of care contributing to poor outcomes include patient non-adherence to medications, failure of physicians to optimize dose and absence of communication between patients and physicians. OBJECTIVE: This pilot study evaluated the feasibility of a systemic digital intervention (MedLink) designed to address failure points and improve treatment of depression in primary care among patients during the first eight weeks of initiating a new course of antidepressant therapy. METHODS: Participants were provided with the MedLink mobile app that provided dose reminders, information and surveys of symptoms and side effects. A cellularly enabled pillbox monitored antidepressant medication adherence. Reports were provided to physicians and participants to prompt changes in medication regimen. Study outcomes were assessed via self-report and interview measures at baseline, week 4 and week 8. RESULTS: Medication adherence detected by the MedLink system was 82%. Participants demonstrated significant decreases in depressive symptoms on the patient health questionnaire-9 (PHQ-9) (p = 0.0005) and the Quick Inventory of Depressive Symptomatology (p = 0.0008) over the eight-week trial. Usability was generally rated favorably. CONCLUSIONS: The MedLink system demonstrated promise as an intervention to address failure points in the primary care treatment of major depressive disorder. Current findings support the further development of MedLink through a randomized controlled trial to evaluate the efficacy of improving processes of care, patient adherence and symptoms of depression.

Feasibility, acceptability, and preliminary efficacy of a technology-assisted psychosocial intervention for racially diverse men with advanced prostate cancer.

BACKGROUND: The utility of psychosocial interventions in reducing symptom burden and improving health-related quality of life (HRQOL) for men with localized prostate cancer has been demonstrated. However, studies have yet to demonstrate the efficacy of interventions in advanced prostate cancer (APC). This study examined the feasibility, acceptability, and preliminary efficacy of a technology-assisted, 10-week, group-based psychosocial intervention for diverse men with APC. METHODS: The participants were 74 men (mean age, 68.84 years; non-Hispanic white, 57%; black, 40.5%) who were randomized to a cognitive-behavioral stress management (CBSM) treatment or health promotion (HP) attention-control condition. The participants were assessed at the baseline, weekly throughout the 10-week program, and 6 months after the baseline. Outcomes were assessed with the Patient-Reported Outcomes Measurement Information System along with established measures of HRQOL, CBSM intervention targets (eg, relaxation skills), and patient-reported acceptability. RESULTS: Feasibility was demonstrated through good retention rates (>85%) and acceptable average attendance rates (>70%), and acceptability was demonstrated through very favorable weekly session evaluations (mean score, 4/5) and exit surveys (mean score, 3.6/4). Men randomized to the CBSM condition reported significant reductions (P < .05) in depressive symptoms and improvements in relaxation self-efficacy (P < .05) at the 6-month follow-up. CBSM participants reported trends for improvement in distress and functional well-being (P < .08) in comparison with those in the HP condition. Effect sizes ranged from medium (0.54) to large (1.87) and, in some instances, were clinically meaningful. CONCLUSIONS: Technology-based CBSM interventions among diverse men with APC may be feasible, acceptable, and efficacious.