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

LiveWell, a smartphone-based self-management intervention for bipolar disorder: Intervention participation and usability analysis

BACKGROUND

Understanding how individuals utilize and perceive digital mental health interventions may improve engagement and effectiveness. To support intervention improvement, participant feedback was obtained and app use patterns were examined for a randomized clinical trial evaluating a smartphone-based intervention for individuals with bipolar disorder.

METHODS

App use and coaching engagement were examined (n = 124). Feedback was obtained via exit questionnaires (week 16, n = 81) and exit interviews (week 48, n = 17).

RESULTS

On average, over 48 weeks, participants used the app for 4.4 h and engaged with the coach for 3.9 h. Participants spent the most time monitoring target behaviors and receiving adaptive feedback and the least time viewing self-assessments and skills. Participants reported that the daily check in helped increase awareness of target behaviors but expressed frustration with repetitiveness of monitoring and feedback content. Participants liked personalizing their wellness plan, but its use did not facilitate skills practice. App use declined over time which participants attributed to clinical stability, content mastery, and time commitment. Participants found the coaching supportive and motivating for app use.

LIMITATIONS

App engagement based on viewing time may overestimate engagement. The delay between intervention delivery and the exit interviews and low exit interview participation may introduce bias.

CONCLUSION

Utilization patterns and feedback suggest that digital mental health engagement and efficacy may benefit from adaptive personalization of targets monitored combined with adaptive monitoring and feedback to support skills practice and development. Increasing engagement with supports may also be beneficial.

The Effect of the Web-Based Psychosocial Health Promotion Program on the Burden of Care in Family Caregivers of Patients with Chronic Mental Disorders

Background

Family members of Chronic Mental Disorders (CMD), who are responsible for patient care, face many physical, psychological, and social problems which make them face the burden of care. This study aimed to investigate the effect of a psychosocial health promotion program on the care burden of family caregivers of patients with CMD.

Materials and Methods

This is a quasi-experimental study that was conducted in two intervention and control groups in the form of pretest and posttest. This study was performed on 67 family caregivers of patients with CMD in Farabi and Noor centers in Isfahan, Iran. Participants in this study were randomly divided into two intervention and control groups. Data from the intervention and control groups were collected in two stages, before and after the intervention by demographic information form and Zarit burden questionnaire. The intervention group received a web-based psychosocial health promotion program in eight sessions in 4 weeks. At the end of the intervention, the Zarit questionnaire was completed by the intervention and control groups.

Results

The mean score of care burden between the intervention and control groups was not statistically significantly different before the implementation of the program (p = 0.534). But after the intervention, the mean score of care burden was significantly different between the two groups (t65 = 3.43, p = 0.001).

Conclusions

This study provides evidence for the benefits of web-based psychosocial health promotion program in reducing the perceived care burden of the caregiver of CMD.

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.

Supporting safe and gradual reduction of long‐term benzodiazepine receptor agonist use: Development of the SAFEGUARDING‐BZRAs toolkit using a codesign approach

Introduction

Long‐term benzodiazepine receptor agonist (BZRA) use persists in healthcare settings worldwide and poses risks of patient harm.

Objective

This study aimed to develop an intervention to support discontinuation of long‐term BZRA use among willing individuals.

Methods

The intervention development process aligned with the UK Medical Research Council's complex intervention framework. This involved a previous systematic review of brief interventions targeting long‐term BZRA use in primary care and qualitative interviews based on the Theoretical Domains Framework that explored barriers and facilitators to discontinuing long‐term BZRA use. A codesign approach was used involving an active partnership between experts by experience, researchers and clinicians. Intervention content was specified in terms of behaviour change techniques (BCTs).

Results

The SAFEGUARDING‐BZRAs (Supporting sAFE and GradUAl ReDuctIon of loNG‐term BenZodiazepine Receptor Agonist uSe) toolkit comprises 24 BCTs and includes recommendations targeted at primary care‐based clinicians for operationalizing each BCT to support individuals with BZRA discontinuation.

Conclusion

The SAFEGUARDING‐BZRAs toolkit has been developed using a systematic and theory‐based approach that addresses identified limitations of previous research. Further research is needed to assess its usability and acceptability by service users and clinicians, as well as its potential to effectively support safe and gradual reduction of long‐term BZRA use.

Patient or Public Contribution

The qualitative interview phase included patients as participants. The codesign process included ‘experts by experience’ with either current or previous experience of long‐term BZRA use as collaborators.

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.