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Related Experiment Video

Updated: Dec 23, 2025

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Using the Delphi expert consensus method in mental health research.

Anthony F Jorm1

  • 1Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia ajorm@unimelb.edu.au.

The Australian and New Zealand Journal of Psychiatry
|August 23, 2015
PubMed
Summary
This summary is machine-generated.

The Delphi method, a consensus-building technique, offers a systematic approach for mental health research. It is valuable for addressing complex questions where traditional research methods are insufficient.

Keywords:
Delphi methodexpert consensusresearch methods

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Area of Science:

  • Mental Health Research
  • Expert Consensus Methods
  • Psychiatry

Background:

  • The Delphi method is a structured communication technique.
  • It relies on expert opinion to reach consensus.
  • Its application in mental health research is growing.

Purpose of the Study:

  • To provide an overview of the Delphi method in mental health research.
  • To explain the rationale and stages of conducting a Delphi study.
  • To examine the diverse applications of the Delphi method in this field.

Main Methods:

  • A systematic literature search was conducted using PubMed.
  • The study reviewed existing literature on Delphi applications in mental health.
  • It also considered "wisdom of crowds" research implications.

Main Results:

  • The Delphi method effectively establishes expert consensus for complex questions.
  • It is applicable for estimations (e.g., dementia prevalence), predictions (e.g., suicide prevention), value determination (e.g., research priorities), and concept definition (e.g., relapse).
  • Diverse experts, including clinicians, researchers, consumers, and caregivers, participate in Delphi studies.

Conclusions:

  • The Delphi method demonstrates significant potential for various applications within mental health research.
  • It provides a robust framework for addressing research gaps and advancing the field.