A Smartphone-Based Self-Management Intervention for Individuals with Bipolar Disorder (LiveWell): Qualitative Study on User Experiences of the Behavior Change Process

Effects of a Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder on Relapse, Symptom Burden, and Quality of Life: A Randomized Clinical Trial

Importance

Bipolar disorder-specific psychotherapy combined with pharmacotherapy improves relapse risk, symptom burden, and quality of life, but psychotherapy is not easily accessible.

Objective

To determine if a smartphone-based self-management intervention (LiveWell) can assist individuals with bipolar disorder to maintain wellness.

Design, Setting, and Participants

An assessor-blind randomized clinical trial enrolled participants from March 20, 2017, to April 25, 2019, with 48-week follow-up ending on April 10, 2020. Participants were randomly assigned to usual care or usual care plus the smartphone intervention stratified by relapse risk based on initial clinical status (low risk: asymptomatic recovery; high risk: continued symptomatic, prodromal, recovering, symptomatic recovery). Participants with bipolar disorder I were recruited from clinics in the Chicago and Minneapolis-Saint Paul areas. Data were analyzed from June 19, 2020, to May 25, 2022.

Interventions

The smartphone-based self-management intervention consisted of an application (app), coach, and website. Over 16 weeks, participants had a coach visit followed by 6 phone calls, and they completed daily and weekly app check-ins. The app provided adaptive feedback and information for developing a personalized wellness plan, the coach provided support, and the website provided summary data and alerts.

Main Outcomes and Measures

The primary outcome was time to relapse. Secondary outcomes were percentage-time symptomatic, symptom severity, and quality of life.

Results

Of the 205 randomized participants (mean [SD] age, 42 [12] years; 125 female individuals [61%]; 5 Asian [2%], 21 Black [10%], 13 Hispanic or Latino [6%], 7 multiracial [3%], 170 White [83%], 2 unknown race [1%]), 81 (40%) were randomly assigned to usual care, and 124 (60%) were randomly assigned to usual care plus the smartphone intervention. This clinical trial did not detect a reduction in relapse risk for the smartphone intervention (hazard ratio [HR], 0.65; 95% CI, 0.39-1.09; log-rank P = .08). However, decreased relapse was observed for low-risk individuals (HR, 0.32; 95% CI, 0.12-0.88; log-rank P = .02) but not high-risk individuals (HR, 0.86; 95% CI, 0.47-1.57; log-rank P = .62). Reduced manic symptom severity was observed for low-risk individuals (mean [SE] difference, -1.4 [0.4]; P = .001) but not for high-risk individuals (mean [SE] difference, 0 [0.3]; P = .95). The smartphone-based self-management intervention decreased depressive symptom severity (mean [SE] difference, -0.80 [0.34]; P = .02) and improved relational quality of life (mean [SE] difference, 1.03 [0.45]; P = .02) but did not decrease percentage-time symptomatic (mean [SE] difference, -5.6 [4.3]; P = .20).

Conclusions and Relevance

This randomized clinical trial of a smartphone-based self-management intervention did not detect a significant improvement in the primary outcome of time to relapse. However, a significant decrease in relapse risk was observed for individuals in asymptomatic recovery. In addition, the intervention decreased depressive symptom severity and improved relational quality of life. These findings warrant further work to optimize the smartphone intervention and confirm that the intervention decreases relapse risk for individuals in asymptomatic recovery.

Trial Registration

ClinicalTrials.gov Identifier: NCT03088462.

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

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.