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Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale

Authors :
Nahum, Mor
Van Vleet, Thomas M
Sohal, Vikaas S
Mirzabekov, Julie J
Rao, Vikram R
Wallace, Deanna L
Lee, Morgan B
Dawes, Heather
Stark-Inbar, Alit
Jordan, Joshua Thomas
Biagianti, Bruno
Merzenich, Michael
Chang, Edward F
Source :
JMIR mHealth and uHealth, Vol 5, Iss 4, p e44 (2017)
Publication Year :
2017
Publisher :
JMIR Publications, 2017.

Abstract

BackgroundMood disorders are dynamic disorders characterized by multimodal symptoms. Clinical assessment of symptoms is currently limited to relatively sparse, routine clinic visits, requiring retrospective recollection of symptoms present in the weeks preceding the visit. Novel advances in mobile tools now support ecological momentary assessment of mood, conducted frequently using mobile devices, outside the clinical setting. Such mood assessment may help circumvent problems associated with infrequent reporting and better characterize the dynamic presentation of mood symptoms, informing the delivery of novel treatment options. ObjectivesThe aim of our study was to validate the Immediate Mood Scaler (IMS), a newly developed, iPad-deliverable 22-item self-report tool designed to capture current mood states. MethodsA total of 110 individuals completed standardized questionnaires (Patient Health Questionnaire, 9-item [PHQ-9]; generalized anxiety disorder, 7-Item [GAD-7]; and rumination scale) and IMS at baseline. Of the total, 56 completed at least one additional session of IMS, and 17 completed one additional administration of PHQ-9 and GAD-7. We conducted exploratory Principal Axis Factor Analysis to assess dimensionality of IMS, and computed zero-order correlations to investigate associations between IMS and standardized scales. Linear Mixed Model (LMM) was used to assess IMS stability across time and to test predictability of PHQ-9 and GAD-7 score by IMS. ResultsStrong correlations were found between standard mood scales and the IMS at baseline (r=.57-.59, P

Details

Language :
English
ISSN :
22915222
Volume :
5
Issue :
4
Database :
Directory of Open Access Journals
Journal :
JMIR mHealth and uHealth
Publication Type :
Academic Journal
Accession number :
edsdoj.5dc72c404b96433faa7b6aab7bb6411f
Document Type :
article
Full Text :
https://doi.org/10.2196/mhealth.6544