Tracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study

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dc.citation.articleNumbere14045en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleJMIR Mental Healthen_US
dc.citation.volumeNumber7en_US
dc.contributor.authorCao, Jianen_US
dc.contributor.authorTruong, Anh Lanen_US
dc.contributor.authorBanu, Sophiaen_US
dc.contributor.authorShah, Asim A.en_US
dc.contributor.authorSabharwal, Ashutoshen_US
dc.contributor.authorMoukaddam, Nidalen_US
dc.date.accessioned2021-02-08T18:37:51Zen_US
dc.date.available2021-02-08T18:37:51Zen_US
dc.date.issued2020en_US
dc.description.abstractBackground: Depression carries significant financial, medical, and emotional burden on modern society. Various proof-of-concept studies have highlighted how apps can link dynamic mental health status changes to fluctuations in smartphone usage in adult patients with major depressive disorder (MDD). However, the use of such apps to monitor adolescents remains a challenge. Objective: This study aimed to investigate whether smartphone apps are useful in evaluating and monitoring depression symptoms in a clinically depressed adolescent population compared with the following gold-standard clinical psychometric instruments: Patient Health Questionnaire (PHQ-9), Hamilton Rating Scale for Depression (HAM-D), and Hamilton Anxiety Rating Scale (HAM-A). Methods: We recruited 13 families with adolescent patients diagnosed with MDD with or without comorbid anxiety disorder. Over an 8-week period, daily self-reported moods and smartphone sensor data were collected by using the Smartphone- and OnLine usage–based eValuation for Depression (SOLVD) app. The evaluations from teens’ parents were also collected. Baseline depression and anxiety symptoms were measured biweekly using PHQ-9, HAM-D, and HAM-A. Results: We observed a significant correlation between the self-evaluated mood averaged over a 2-week period and the biweekly psychometric scores from PHQ-9, HAM-D, and HAM-A (0.45≤|r|≤0.63; P=.009, P=.01, and P=.003, respectively). The daily steps taken, SMS frequency, and average call duration were also highly correlated with clinical scores (0.44≤|r|≤0.72; all P<.05). By combining self-evaluations and smartphone sensor data of the teens, we could predict the PHQ-9 score with an accuracy of 88% (23.77/27). When adding the evaluations from the teens’ parents, the prediction accuracy was further increased to 90% (24.35/27). Conclusions: Smartphone apps such as SOLVD represent a useful way to monitor depressive symptoms in clinically depressed adolescents, and these apps correlate well with current gold-standard psychometric instruments. This is a first study of its kind that was conducted on the adolescent population, and it included inputs from both teens and their parents as observers. The results are preliminary because of the small sample size, and we plan to expand the study to a larger population.en_US
dc.identifier.citationCao, Jian, Truong, Anh Lan, Banu, Sophia, et al.. "Tracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study." <i>JMIR Mental Health,</i> 7, no. 1 (2020) JMIR Publications: https://doi.org/10.2196/14045.en_US
dc.identifier.digitalTracking-and-Predictingen_US
dc.identifier.doihttps://doi.org/10.2196/14045en_US
dc.identifier.urihttps://hdl.handle.net/1911/109813en_US
dc.language.isoengen_US
dc.publisherJMIR Publicationsen_US
dc.rightsThis 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 JMIR Mental Health, is properly cited.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.subject.keywordSOLVD-Teen and SOLVD-Parent Appen_US
dc.subject.keywordadolescent depressionen_US
dc.subject.keywordsmartphone monitoringen_US
dc.subject.keywordself-evaluationen_US
dc.subject.keywordparental inputen_US
dc.subject.keywordsensory dataen_US
dc.titleTracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Studyen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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