Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study

Abstract

BackgroundToday, college students are dealing with depression at some of the highest rates in decades. As the primary mental health service provider, university counseling centers are limited in their capacity and efficiency to provide mental health care due to time constraints and reliance on students’ self-reports. A mobile behavioral-sensing platform may serve as a solution to enhance the efficiency and accessibility of university counseling services.ObjectiveThe main objectives of this study are to (1) understand the usefulness of a mobile sensing platform (ie, iSee) in improving counseling services and assisting students’ self-management of their depression conditions, and (2) explore what types of behavioral targets (ie, meaningful information extracted from raw sensor data) and feedback to deliver from both clinician and students’ perspectives.MethodsWe conducted semistructured interviews with 9 clinicians and 12 students with depression recruited from a counseling center at a large Midwestern university. The interviews were 40-50 minutes long and were audio recorded and transcribed. The interview data were analyzed using thematic analysis with an inductive approach. Clinician and student interviews were analyzed separately for comparison. The process of extracting themes involved iterative coding, memo writing, theme revisits, and refinement.ResultsFrom the clinician perspective, the mobile sensing platform helps to improve counseling service by providing objective evidence for clinicians and filling gaps in clinician-patient communication. Clinicians suggested providing students with their sensed behavioral targets organized around personalized goals. Clinicians also recommended delivering therapeutic feedback to students based on their sensed behavioral targets, including positive reinforcement, reflection reminders, and challenging negative thoughts. From the student perspective, the mobile sensing platform helps to ease continued self-tracking practices. Students expressed their need for integrated behavioral targets to understand correlations between behaviors and depression. They also pointed out that they would prefer to avoid seeing negative feedback.ConclusionsAlthough clinician and student participants shared views on the advantages of iSee in supporting university counseling, they had divergent opinions on the types of behavioral targets and feedback to be provided via iSee. This exploratory work gained initial insights into the design of a mobile sensing platform for depression management and informed a more conclusive research project for the future.

Patient and physician perspectives of a smartphone application for depression: a qualitative study

“…The expected aims of such apps found in the literature included psychoeducation [35], monitoring [27,32,35], providing a presence between face-to-face visits [27] and social connectivity [26,32]. Consistently with our result, other studies highlighted two main barriers to the use of apps cited by physicians: lack of time and medicolegal responsibility [27,28]. Financial aspects and deficiency in technological competencies are common barriers to the use of apps for patients [26,33,35].…”

“…Qualitative analysis is commonly used to assess patients' expectations in various domains. It has mostly been used to evaluate patients' use of pre-existing apps for depression [25,26] or to explore the expectations of an app for depression in young people [27,28]. To the best of our knowledge, no qualitative study has investigated both patient and physician expectations of a smartphone app dedicated to depression including patients with previous major depressive episodes (MDE), general practitioners and psychiatrists.…”

Online mental health interventions designed for students in higher education: A user-centered perspective

“…Co-design involved young people, supportive others, health professionals and service providers. Framework : Participatory Design of Evidence-based Online Youth Mental Health Promotion, Prevention, Early Intervention, and Treatment ( Hagen et al, 2012 ) N/A Coughlan et al (2019) Name : Our Journey Target : Mental health and wellbeing Type : Web-based platform Stage : Developed, not tested in a pilot Duration : N/A • Co-design workshop Process : Participatory design with students, student union representatives, and staff (in student support roles, and those supporting disabled students) Framework : None listed N/A Meng et al (2018) Name : ISee Target : Depression Type : Mobile sensing and a Mobile app Stage : Prototype Duration : N/A • Co-design workshop Process : Participatory design workshop with clinicians and students Framework : None listed N/A Gulliver et al (2015) Name : UniVirtual Clinic (understanding privacy needs) Target : Mental health Type : Mobile app Stage : Prototype Duration : N/A • Focus group • Prototype testing Process : Focus groups with students and iterative prototype testing sessions with students Framework : None listed N/A Farrer et al, (2015) Name : UniVirtual Clinic (end-user needs) Target : Mental health Type : Mobile app Stage : Prototype Duration : N/A • Focus group Process : Focus groups with students Framework : None listed N/A Farrer et al, (2020) Name : UniVirtual Clinic Target : Mental health Type : Web-based platform Stage : Developed, not tested in a pilot Duration : N/A • Focus group • Literature review • User survey • Prototype testing Process : Participatory design with young people, university stakeholders and other service providers Frame...…”

From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques

“…• Clinical Health Service and HCI -Providing straightforward and effective clinical health service with good HCI design for user experience is the most intuitive way to increase users' active engagement, since the essential motivation of the users downloading the app is to obtain personal health benefit [238], [239]. In practice, user engagement strategies can be organized as setting sensing health-related targets around users' personalized objectives, delivering adaptive therapeutic feedback including positive reinforcement, reflection reminders, and challenging negative thoughts [240], [241], and designing easyto-use platforms [188]. For instance, Rabbi et al [242] designed an app named SARA, which integrates engagement strategies including contingent rewards, badges for completing active health tasks, funny memes/gifs & lifeinsights, and health-related reminders or notifications.…”