Does the use of an automated tool for self-reporting mood by patients with bipolar disorder bias the collected data?

Department of Psychiatry and Psychotherapy, Charite-University Medicine Berlin, Campus Charite-Mitte, Germany.
MedGenMed: Medscape general medicine 02/2005; 7(3):21.
Source: PubMed

ABSTRACT Automating data collection from patients can improve data quality, enhance compliance, and decrease costs in longitudinal studies. About half of all households in industrialized countries now have a home computer.
While we previously validated the ChronoRecord software for self-reporting mood on a home computer with patients who have bipolar disorder, this study further investigates whether this technology created a bias in the collected data.
During the validation study, 80 of 96 (83%) patients returned 8662 days of data (mean, 114.7 +/- 32.3 SD days). The patients' demographics were compared with those of similar longitudinal studies in which patients used paper-based data collection tools. In addition, because demographic characteristics may influence attitudes toward technology, observer-rated scores on the Hamilton Depression Rating Scale and Young Mania Rating Scale were used to group patients by severity of illness, and the self-reported mood ratings were analyzed for evidence of bias from the patients' gender, ethnicity, diagnosis, age, disability status, or years of education. Analysis was performed using the 2-way analysis of variance and general linear model.
The patients' demographic characteristics were very similar to those of patients with bipolar disorder who participated in comparable longitudinal studies using paper-based tools. After grouping the patients by severity of illness, none of the demographic variables had a significant effect on the patients' self-reported mood using the automated tool.
The use of a computer does not seem to bias sample data. As with studies using paper-based self-reporting, results from studies of patients using ChronoRecord software on a home computer to report mood can be generalized.

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