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[Psychiatric cases identification by multi-step epidemiological studies: methods, problems and applicability].

S B Andreoli1, N de Almeida Filho, E S Coutinho

  • 1Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, SP, Brasil. andreoli@psiquiatria.epm.br

Revista De Saude Publica
|December 6, 2000
PubMed
Summary

This study refines psychiatric case identification in epidemiology. The two-stage methodology, using screening and diagnostic tools, improves the accuracy of psychiatric morbidity prevalence estimates.

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Area of Science:

  • Psychiatry
  • Epidemiology
  • Public Health

Context:

  • Epidemiological studies are crucial for understanding population mental health.
  • Accurate identification of psychiatric cases is essential for reliable prevalence data.
  • Existing tools for psychiatric case identification can present methodological challenges.

Purpose:

  • To critically evaluate a two-stage methodology for identifying psychiatric cases in epidemiological research.
  • To analyze the methodological strengths and limitations of a large-scale psychiatric morbidity study.
  • To propose improvements for the accurate assessment of psychiatric disorders in population studies.

Summary:

  • The Multicentric Psychiatric Morbidity Study employed a two-stage approach: initial population screening with the Questionnaire of Psychiatric Morbidity of the Adult (QMPA), followed by diagnostic assessment using the Inventory of Symptoms of DSM-III for a subsample.

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  • This methodology, despite potential weaknesses in screening scales, provides a robust framework for estimating psychiatric prevalence.
  • The described procedure details how to manage and interpret data from both stages to achieve reliable results.

    • Impact:

    • This methodological approach enhances the precision of psychiatric case identification in epidemiological surveys.
    • The findings offer a validated strategy to mitigate distortions inherent in current diagnostic tools.
    • Improved accuracy in case identification can lead to more effective public mental health policies and interventions.