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Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study

BACKGROUND: Depression is an extremely prevalent issue in the United States, with an estimated 7% of adults experiencing at least one major depressive episode in 2017. Although psychotherapy and medication management are effective treatments for depression, significant barriers in accessing care per...

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Autores principales: Kunkle, Sarah, Yip, Manny, Ξ, Watson, Hunt, Justin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333067/
https://www.ncbi.nlm.nih.gov/pubmed/32554387
http://dx.doi.org/10.2196/17902
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author Kunkle, Sarah
Yip, Manny
Ξ, Watson
Hunt, Justin
author_facet Kunkle, Sarah
Yip, Manny
Ξ, Watson
Hunt, Justin
author_sort Kunkle, Sarah
collection PubMed
description BACKGROUND: Depression is an extremely prevalent issue in the United States, with an estimated 7% of adults experiencing at least one major depressive episode in 2017. Although psychotherapy and medication management are effective treatments for depression, significant barriers in accessing care persist. Virtual care can potentially address some of these obstacles. OBJECTIVE: We conducted a preliminary investigation of utilization characteristics and effectiveness of an on-demand health system for reducing depression symptoms. METHODS: Data were analyzed from 1662 users of an on-demand mental health system that includes behavioral health coaching, clinical services (therapy and psychiatry), and self-guided content and assessments primarily via a mobile app platform. Measures included engagement characterized by mobile app data, member satisfaction scores collected via in-app surveys, and depression symptoms via the Patient Health Questionnaire-2 (PHQ-2) at baseline and 8-12 week follow-up. Descriptive statistics are reported for measures, and pre/post-PHQ-2 data were analyzed using the McNemar test. A chi-square test was used to test the association between the proportion of individuals with an improvement in PHQ-2 result and care modality (coaching, therapy, and psychiatry, or hybrid). RESULTS: During the study period, 65.5% of individuals (1089/1662) engaged only in coaching services, 27.6% of individuals (459/1662) were engaged in both coaching and clinical services, 3.3% of individuals (54/1662) engaged only in clinical services, and 3.7% of individuals (61/1662) only used the app. Of the 1662 individuals who completed the PHQ-2 survey, 772 (46.5%) were considered a positive screen at intake, and 890 (53.6%) were considered a negative screen at intake. At follow-up, 477 (28.7%) of individuals screened positive, and 1185 (71.3%) screened negative. A McNemar test showed that there was a statistically significant decrease in the proportion of users experiencing depressed mood and anhedonia more than half the time at follow-up (P<.001). A chi-square test showed there was no significant association between care modality and the proportion of individuals with an improvement in PHQ-2 score. CONCLUSIONS: This study provides preliminary insights into which aspects of an on-demand mental health system members are utilizing and levels of engagement and satisfaction over an 8-12 week window. Additionally, there is some signal that this system may be useful for reducing depression symptoms in users over this period. Additional research is required, given the study limitations, and future research directions are discussed.
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spelling pubmed-73330672020-07-06 Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study Kunkle, Sarah Yip, Manny Ξ, Watson Hunt, Justin J Med Internet Res Original Paper BACKGROUND: Depression is an extremely prevalent issue in the United States, with an estimated 7% of adults experiencing at least one major depressive episode in 2017. Although psychotherapy and medication management are effective treatments for depression, significant barriers in accessing care persist. Virtual care can potentially address some of these obstacles. OBJECTIVE: We conducted a preliminary investigation of utilization characteristics and effectiveness of an on-demand health system for reducing depression symptoms. METHODS: Data were analyzed from 1662 users of an on-demand mental health system that includes behavioral health coaching, clinical services (therapy and psychiatry), and self-guided content and assessments primarily via a mobile app platform. Measures included engagement characterized by mobile app data, member satisfaction scores collected via in-app surveys, and depression symptoms via the Patient Health Questionnaire-2 (PHQ-2) at baseline and 8-12 week follow-up. Descriptive statistics are reported for measures, and pre/post-PHQ-2 data were analyzed using the McNemar test. A chi-square test was used to test the association between the proportion of individuals with an improvement in PHQ-2 result and care modality (coaching, therapy, and psychiatry, or hybrid). RESULTS: During the study period, 65.5% of individuals (1089/1662) engaged only in coaching services, 27.6% of individuals (459/1662) were engaged in both coaching and clinical services, 3.3% of individuals (54/1662) engaged only in clinical services, and 3.7% of individuals (61/1662) only used the app. Of the 1662 individuals who completed the PHQ-2 survey, 772 (46.5%) were considered a positive screen at intake, and 890 (53.6%) were considered a negative screen at intake. At follow-up, 477 (28.7%) of individuals screened positive, and 1185 (71.3%) screened negative. A McNemar test showed that there was a statistically significant decrease in the proportion of users experiencing depressed mood and anhedonia more than half the time at follow-up (P<.001). A chi-square test showed there was no significant association between care modality and the proportion of individuals with an improvement in PHQ-2 score. CONCLUSIONS: This study provides preliminary insights into which aspects of an on-demand mental health system members are utilizing and levels of engagement and satisfaction over an 8-12 week window. Additionally, there is some signal that this system may be useful for reducing depression symptoms in users over this period. Additional research is required, given the study limitations, and future research directions are discussed. JMIR Publications 2020-06-18 /pmc/articles/PMC7333067/ /pubmed/32554387 http://dx.doi.org/10.2196/17902 Text en ©Sarah Kunkle, Manny Yip, Watson Ξ, Justin Hunt. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.06.2020. 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
Kunkle, Sarah
Yip, Manny
Ξ, Watson
Hunt, Justin
Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title_full Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title_fullStr Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title_full_unstemmed Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title_short Evaluation of an On-Demand Mental Health System for Depression Symptoms: Retrospective Observational Study
title_sort evaluation of an on-demand mental health system for depression symptoms: retrospective observational study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333067/
https://www.ncbi.nlm.nih.gov/pubmed/32554387
http://dx.doi.org/10.2196/17902
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