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Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis.

Darragh GlavinEoin Martino GruaCarina Akemi NakamuraMárcia ScazufcaEdinilza Ribeiro Dos SantosGloria Hoi-Yan WongWilliam HollingworthTim J PetersRicardo Araya BaltraPepijn Van de Ven
Published in: JMIR mental health (2023)
The PHQ-2 did not prove to be a more effective prescreening instrument when compared with other PHQ-9 item pairings. Evaluating all item pairings showed that, compared with alternative partner items, the anhedonia item underperformed alongside the depressed mood item. This suggests that the inclusion of anhedonia as a core symptom of depression and its presence in ultrabrief questionnaires may be incompatible with the empirical evidence. The use of the PHQ-2 to prescreen for depressive symptomatology could result in a greater number of misclassifications than alternative item pairings.
Keyphrases
  • psychometric properties
  • machine learning
  • bipolar disorder
  • healthcare
  • case report
  • artificial intelligence
  • sleep quality
  • hepatitis c virus
  • deep learning
  • human immunodeficiency virus
  • hiv testing