Cited by 28Digital Mental Health InterventionsMental Health Research TopicsMobile Health and mHealth Applications

Findings From a Trial of the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) Application: What Do Apps Really Tell Us About Patients with Depression? Concordance Between App-Generated Data and Standard Psychiatric Questionnaires for Depression and Anxiety

MOUKADDAM, NIDAL, TRUONG, ANH, CAO, JIAN, SHAH, ASIM, SABHARWAL, ASHUTOSH·2019·Journal of Psychiatric Practice

Abstract

Objective: Depression imposes a notable societal burden, with limited treatment success despite multiple available psychotherapy and medications choices. Potential reasons may include the heterogeneity of depression diagnoses and the presence of comorbid anxiety symptoms. Despite technological advances and the introduction of many mobile phone applications (apps) claiming to relieve depression, major gaps in knowledge still exist regarding what apps truly measure and how they correlate with psychometric questionnaires. The goal of this study was to evaluate whether mobile daily mood self-ratings may be useful in monitoring and classifying depression symptoms in a clinically depressed population compared with standard psychometric instruments including the Patient Health Questionaire-9 (PHQ-9), the Hamilton Rating Scale for Depression (HAM-D), and the Hamilton Anxiety Rating Scale (HAM-A). Method: For this study, 22 patients with major depressive disorder with or without comorbid anxiety disorder were recruited. The diagnosis of depression was confirmed through the Mini International Neuropsychiatric Interview (MINI). Over an 8-week period, daily moods were self-reported through the Smartphone and OnLine Usage-based eValuation for Depression (SOLVD) application, a custom-designed application that was downloaded onto patients’ mobile devices. Depression and anxiety symptoms were also measured biweekly using the HAM-D, HAM-A, and PHQ-9. Results: Significant correlations were observed among self-evaluated mood, daily steps taken, SMS (text) frequency, average call duration, and biweekly psychometric scores (|r|>0.5, P<0.05). The correlation coefficients were higher in individuals with more severe depressive symptoms. Conclusions: Although this study, given its limited sample size, was exploratory in nature, it helps fill a significant gap in our knowledge of the concordance between ratings obtained on the Ham-D, Ham-A, and the PHQ-9 psychometric instruments and data obtained via a smartphone app. These questionnaires represent gold-standard, commonly used psychiatric research/clinical instruments, and, thus, this information can serve as a foundation for digital phenotyping for depression and pave the way for interventional studies using smartphone applications.

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Authors
MOUKADDAM, N., TRUONG, A., CAO, J., SHAH, A., & SABHARWAL, A.
Affiliations
Baylor College of Medicine (US)
Venue
Journal of Psychiatric Practice
Published
2019-09
Volume
25
Issue
5
Pages
365-373
ISSN
  • 1527-4160 (ISSN-L)
  • 1538-1145
OpenAlex
W2987725842
Cited by
28
References
38
Citations by year
2025: 2 · 2024: 5 · 2023: 4 · 2022: 9 · 2021: 4 · 2020: 3 · 2019: 1
FWCI
4.80
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Psychiatric Practice (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
depression, mobile application, digital phenotyping, major depressive disorder, anxiety comorbidity, PHQ-9, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, mobile health, physical activity
MeSH terms
Smartphone, Adult, Anxiety Disorders, Depression, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Male, Psychiatric Status Rating Scales, Psychometrics, Surveys and Questionnaires, Telemedicine, Comparative Effectiveness Research, Self Report, Mobile Applications

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