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

BACKGROUND: Today, 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 stu...

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Autores principales: Meng, Jingbo, Hussain, Syed Ali, Mohr, David C, Czerwinski, Mary, Zhang, Mi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068382/
https://www.ncbi.nlm.nih.gov/pubmed/30021710
http://dx.doi.org/10.2196/10139
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author Meng, Jingbo
Hussain, Syed Ali
Mohr, David C
Czerwinski, Mary
Zhang, Mi
author_facet Meng, Jingbo
Hussain, Syed Ali
Mohr, David C
Czerwinski, Mary
Zhang, Mi
author_sort Meng, Jingbo
collection PubMed
description BACKGROUND: Today, 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. OBJECTIVE: The 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. METHODS: We 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. RESULTS: From 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. CONCLUSIONS: Although 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.
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spelling pubmed-60683822018-08-09 Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study Meng, Jingbo Hussain, Syed Ali Mohr, David C Czerwinski, Mary Zhang, Mi J Med Internet Res Original Paper BACKGROUND: Today, 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. OBJECTIVE: The 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. METHODS: We 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. RESULTS: From 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. CONCLUSIONS: Although 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. JMIR Publications 2018-07-17 /pmc/articles/PMC6068382/ /pubmed/30021710 http://dx.doi.org/10.2196/10139 Text en ©Jingbo Meng, Syed Ali Hussain, David C Mohr, Mary Czerwinski, Mi Zhang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.07.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Meng, Jingbo
Hussain, Syed Ali
Mohr, David C
Czerwinski, Mary
Zhang, Mi
Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title_full Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title_fullStr Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title_full_unstemmed Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title_short Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study
title_sort exploring user needs for a mobile behavioral-sensing technology for depression management: qualitative study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068382/
https://www.ncbi.nlm.nih.gov/pubmed/30021710
http://dx.doi.org/10.2196/10139
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