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.articleNumbere14045
dc.citation.issueNumber1
dc.citation.journalTitleJMIR Mental Health
dc.citation.volumeNumber7
dc.contributor.authorCao, Jian
dc.contributor.authorTruong, Anh Lan
dc.contributor.authorBanu, Sophia
dc.contributor.authorShah, Asim A.
dc.contributor.authorSabharwal, Ashutosh
dc.contributor.authorMoukaddam, Nidal
dc.date.accessioned2021-02-08T18:37:51Z
dc.date.available2021-02-08T18:37:51Z
dc.date.issued2020
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.
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.
dc.identifier.digitalTracking-and-Predicting
dc.identifier.doihttps://doi.org/10.2196/14045
dc.identifier.urihttps://hdl.handle.net/1911/109813
dc.language.isoeng
dc.publisherJMIR Publications
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.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.keywordSOLVD-Teen and SOLVD-Parent App
dc.subject.keywordadolescent depression
dc.subject.keywordsmartphone monitoring
dc.subject.keywordself-evaluation
dc.subject.keywordparental input
dc.subject.keywordsensory data
dc.titleTracking and Predicting Depressive Symptoms of Adolescents Using Smartphone-Based Self-Reports, Parental Evaluations, and Passive Phone Sensor Data: Development and Usability Study
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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