An Automated Mobile Mood Tracking Technology (Mood 24/7): Validation Study.

depression digital health ecological momentary assessment mobile phone patient monitoring short message service text messaging

Journal

JMIR mental health
ISSN: 2368-7959
Titre abrégé: JMIR Ment Health
Pays: Canada
ID NLM: 101658926

Informations de publication

Date de publication:
20 May 2020
Historique:
received: 20 09 2019
accepted: 09 02 2020
revised: 08 02 2020
entrez: 21 5 2020
pubmed: 21 5 2020
medline: 21 5 2020
Statut: epublish

Résumé

Electronic tracking has been utilized for a variety of health conditions. Previous studies have shown that there is higher adherence to electronic methods vs paper-and-pencil tracking modalities. Electronic tracking also ensures that there are no back-filled entries, where patients have-to appear compliant-entered their responses retrospectively just before their visits with their health care provider. On the basis of the recognition of an unmet need for a Web-based automated platform to track psychiatric outcomes, Johns Hopkins University partnered with Health Central (a subsidiary of Remedy Health Media LLC) to develop Mood 24/7, an electronic, mobile, automated, SMS-based mood tracker. This is a pilot study to validate the use of Mood 24/7 in anticipation of clinical trials to demonstrate the therapeutic benefit on patients' health outcomes of utilizing digital mood-tracking technology. Mood 24/7 is an electronic mood-monitoring platform developed to accurately and efficiently track mood over time through automated daily SMS texts or emails. This study was designed to assess the accuracy and validity of Mood 24/7 in an outpatient psychiatric setting. This pilot study involved a retrospective chart review for depressed outpatients (N=9) to compare their self-reported Mood 24/7 daily mood ratings with their psychiatrist's independent clinical mood assessment at the time of the patient's visit. Their mood ratings via Mood 24/7 were collected over 36 weeks. In addition, a mixed model analysis was applied to compare the weekly Montgomery-Åsberg Depression Rating Scale (MADRS) scores with Mood 24/7 scores over an average of 3 months. A 97.2% (315/324) digital mood reporting adherence was found over 36 weeks, and a significant correlation (r=0.86, P<.001) was observed between patients' Mood 24/7 scores and their psychiatrist's blinded clinical assessment of the patient's mood when seen in the clinic. In addition, a significant concordance (intraclass correlation of 0.69, 95% CI 0.33-0.91, P<.001) was observed in the mixed model analysis of the clinician-administered MADRS vs Mood 24/7 scores over time. Our chart review and mixed model analyses demonstrate that Mood 24/7 is a valid instrument for convenient, simple, noninvasive, and accurate longitudinal mood assessment in the outpatient clinical setting.

Sections du résumé

BACKGROUND BACKGROUND
Electronic tracking has been utilized for a variety of health conditions. Previous studies have shown that there is higher adherence to electronic methods vs paper-and-pencil tracking modalities. Electronic tracking also ensures that there are no back-filled entries, where patients have-to appear compliant-entered their responses retrospectively just before their visits with their health care provider. On the basis of the recognition of an unmet need for a Web-based automated platform to track psychiatric outcomes, Johns Hopkins University partnered with Health Central (a subsidiary of Remedy Health Media LLC) to develop Mood 24/7, an electronic, mobile, automated, SMS-based mood tracker. This is a pilot study to validate the use of Mood 24/7 in anticipation of clinical trials to demonstrate the therapeutic benefit on patients' health outcomes of utilizing digital mood-tracking technology.
OBJECTIVE OBJECTIVE
Mood 24/7 is an electronic mood-monitoring platform developed to accurately and efficiently track mood over time through automated daily SMS texts or emails. This study was designed to assess the accuracy and validity of Mood 24/7 in an outpatient psychiatric setting.
METHODS METHODS
This pilot study involved a retrospective chart review for depressed outpatients (N=9) to compare their self-reported Mood 24/7 daily mood ratings with their psychiatrist's independent clinical mood assessment at the time of the patient's visit. Their mood ratings via Mood 24/7 were collected over 36 weeks. In addition, a mixed model analysis was applied to compare the weekly Montgomery-Åsberg Depression Rating Scale (MADRS) scores with Mood 24/7 scores over an average of 3 months.
RESULTS RESULTS
A 97.2% (315/324) digital mood reporting adherence was found over 36 weeks, and a significant correlation (r=0.86, P<.001) was observed between patients' Mood 24/7 scores and their psychiatrist's blinded clinical assessment of the patient's mood when seen in the clinic. In addition, a significant concordance (intraclass correlation of 0.69, 95% CI 0.33-0.91, P<.001) was observed in the mixed model analysis of the clinician-administered MADRS vs Mood 24/7 scores over time.
CONCLUSIONS CONCLUSIONS
Our chart review and mixed model analyses demonstrate that Mood 24/7 is a valid instrument for convenient, simple, noninvasive, and accurate longitudinal mood assessment in the outpatient clinical setting.

Identifiants

pubmed: 32432558
pii: v7i5e16237
doi: 10.2196/16237
pmc: PMC7270850
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e16237

Informations de copyright

©Anupama Kumar, Michael Wang, Alison Riehm, Eileen Yu, Ted Smith, Adam Kaplin. Originally published in JMIR Mental Health (http://mental.jmir.org), 20.05.2020.

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Auteurs

Anupama Kumar (A)

Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States.

Michael Wang (M)

Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States.

Alison Riehm (A)

Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States.

Eileen Yu (E)

Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States.

Ted Smith (T)

Department of Pharmacology and Toxicology, University of Louisville, Louisville, KY, United States.

Adam Kaplin (A)

Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States.

Classifications MeSH