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Abstract
Objective: Patient-reported mood charts are frequently used in management of bipolar disorder. Although mood charts have recently been programmed in electronic devices such as mobile phones, little is known about the impact of the method of data capture on the psychometric properties and validity of these data. Methods: In an ongoing pilot study, a sample of outpatients with bipolar disorder were randomized to complete mood charts either on a mobile phone or with standard paper and pencil as part of a 12-week intervention (primary outcomes for the trial await study completion). We compared these conditions across a single item rating of mood state, and we hypothesized that mobile phone-based data capture would produce greater compliance to mood ratings, variability between and within participants, and concurrent validity with blinded clinician-rated affective symptom severity. Results: A total of 56 participants were randomized and 40 participants were included in the analyses. There were no significant differences between conditions on demographic or clinical variables. The rate of compliance was significantly higher in paper-and-pencil versus mobile phone ratings. Ratings demonstrated significantly more variability within individuals in the mobile phone condition. Mobile phone mood ratings were significantly correlated with clinician-rated depressive symptom severity across the study and with manic symptom severity at the week-6 assessment, whereas paper-and-pencil ratings were not significantly associated with clinician-rated depression or mania. Conclusions: Although preliminary, our results suggest a lower rate of compliance with mobile phones compared to paper-and-pencil daily mood rating in bipolar disorder, yet a greater ability to capture variability and concurrent validity in quantifying affective symptoms. This clinical trial is registered at www.clinicaltrials.gov as NCT01670123.
ACKNOWLEDGMENTS
This study was supported by National Institute of Mental Health Grants MH091260, MH077225, and MH080002, a UCSD Von Leibig Center Southern California Healthcare Technology Acceleration Award, and by the Department of Veterans Affairs.