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Clinicians' Perspectives on Diagnostic Markers for Depression Among Adolescents in India: An Embedded Mixed-Methods Study.

Pankhuri AggarwalVaishali V RavalUttara ChariVijaya RamanKamalesh Kadnur SreenivasSanjana KrishnamurthyAshok Mysore Visweswariah
Published in: Culture, medicine and psychiatry (2021)
Limited research has investigated whether clinicians around the world find diagnostic criteria for depression that were originally developed in the West are useful with diverse populations. Using an embedded mixed-methods design in India, we examined (a) clinicians' and trainees' (n = 143) ratings of the usefulness of the criteria for Major Depressive Disorder (MDD) outlined in two major diagnostic systems (Diagnostic and Statistical Manual of Mental Disorders-5; DSM-5 and International Classification of Mental and Behavioral Disorders-Tenth Edition; ICD-10), and (b) narrative descriptions of clinical cases of adolescent depression and usefulness of diagnostic and screening instruments in day-to-day practice using semi-structured interviews in a subsample of clinicians (n = 24). Qualitative findings demonstrated that Indian clinicians identified markers of depression that were consistent with the current diagnostic manuals (affective, cognitive, somatic symptoms), and the numeric ratings suggested that clinicians found a majority of DSM-5 and ICD-10 criteria for MDD to be useful. However, Indian clinicians also identified additional markers of adolescent depression (i.e., interpersonal conflicts and issues, impairment in school-related functioning, anger-based symptoms, anxiety-based symptoms, additional somatic complaints not included in DSM-5 or ICD-10), highlighting the need to modify existing diagnostic criteria to be more inclusive. The findings suggest the need for culturally informed diagnostic practices that consider a wide range of clinical presentations of depression among adolescents worldwide.
Keyphrases
  • major depressive disorder
  • sleep quality
  • depressive symptoms
  • palliative care
  • mental health
  • bipolar disorder
  • healthcare
  • physical activity
  • machine learning
  • randomized controlled trial
  • mass spectrometry