title: Daily mood ratings via text message as a proxy for clinic based depression assessment.
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.
  
  
  CONCLUSIONS
  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.
authors: University of California, Berkeley, United States; University of California, San Francisco, United States. Electronic address: aguila@berkeley.edu.
authors: Adrian
authors: A
authors: Aguilera
authors: Northwestern University, United States.
authors: Stephen M
authors: SM
authors: Schueller
authors: University of California, San Francisco, United States.
authors: Yan
authors: Y
authors: Leykin
mesh_terms: D000339:Affect; D003863:Depression / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D063189:Symptom Assessment / Q000379:methods*; D017216:Telemedicine / Q000379:methods*; D060145:Text Messaging
keywords: Depression; Digital health; Disparities; PHQ-9; Text messaging; mHealth