Daily mood ratings via text message as a proxy for clinic based depression assessment

J Affect Disord. 2015 Apr 1;175:471-4. doi: 10.1016/j.jad.2015.01.033. Epub 2015 Jan 29.

Abstract

Background: Mobile and automated technologies are increasingly becoming integrated into mental health care and assessment. The purpose of this study was to determine how automated daily mood ratings are related to the Patient Health Questionnaire-9 (PHQ-9), a standard measure in the screening and tracking of depressive symptoms.

Results: There was a significant relationship between daily mood scores and PHQ-9 scores, and between one-week average mood scores and PHQ-9 scores, controlling for linear change in depression scores. PHQ-9 scores were not related to the average of two week mood ratings. This study also constructed models using variance, maximum, and minimum values of mood ratings in the preceding week and two-week periods as predictors of PHQ-9. None of these variables significantly predicted PHQ-9 scores when controlling for daily mood ratings and the corresponding averages for each period.

Limitations: This study only assessed patients who were in treatment for depression, therefore findings might not generalize to the relationship between text message mood ratings for those who are not depressed. The sample was also predominantly Spanish speaking and low-income making generalizability to other populations uncertain.

Conclusions: Our results show that automatic text message based mood ratings can be a clinically useful proxy for the PHQ-9. Importantly, this approach avoids the limitations of the PHQ-9 administration, which include length and a higher requirement for literacy.

Keywords: Depression; Digital health; Disparities; PHQ-9; Text messaging; mHealth.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Affect*
  • Depression / diagnosis*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Symptom Assessment / methods*
  • Telemedicine / methods*
  • Text Messaging*