Digital mental health interventions for chronic serious mental illness: Findings from a qualitative study on usability and scale-up of the Life Goals app for bipolar disorder.
Frontiers Digit. Health(2022)
Abstract
The Life Goals (LG) application is an evidence-based self-management tool intended to help individuals with bipolar disorder (BD) by aligning symptom coping strategies with personal goals. The program has traditionally been offered in-person or via the web, but has recently been translated into an individualized, customizable mobile intervention to improve access to care and reduce provider burden. The LG app previously showed acceptability with ease of use and satisfaction with user interface, but less success in encouraging self-management. To better understand patient needs, our team conducted semi-structured interviews with 18 individuals with BD who used the LG app for 6 months. These interviews also investigated participant interest in sharing LG app data with their provider through an online dashboard. Using affinity mapping, a collaborative, qualitative data analysis technique, our team identified emerging common themes in the interviews. Through this process, team members identified 494 pieces of salient information from interviews that were mapped and translated into three main findings: (1) many participants found Mood Monitoring and LG modules helpful/interesting and stated the app overall had positive impacts on their mental health, (2) some components of the app were too rudimentary or impersonal to be beneficial, and (3) feedback was mixed regarding future implementation of an LG provider dashboard, with some participants seeing potential positive impacts and others hesitating due to perceived efficacy and privacy concerns. These findings can help researchers improve app-based interventions for individuals with BD by increasing app usage and improving care overall.
MoreTranslated text
Key words
DMHI,affinity mapping,bipolar disorder,mental health,qualitative study,self-managament
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined