Open AccessSampling and design challenges in studying the mental health consequences of disasters
Author(s) -
Galea Sandro,
Maxwell Andrea R.,
Norris Fran
Publication year - 2008
Publication title -
international journal of methods in psychiatric research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.275
H-Index - 73
eISSN - 1557-0657
pISSN - 1049-8931
DOI - 10.1002/mpr.267
Subject(s) - mental health , inference , field (mathematics) , psychology , sampling (signal processing) , disaster research , data science , computer science , risk analysis (engineering) , medicine , psychiatry , geography , artificial intelligence , mathematics , filter (signal processing) , meteorology , pure mathematics , computer vision
Disasters are unpredictable and frequently lead to chaotic post‐disaster situations, creating numerous methodologic challenges for the study of the mental health consequences of disasters. In this commentary, we expand on some of the issues addressed by Kessler and colleagues, largely focusing on the particular challenges of (a) defining, finding, and sampling populations of interest after disasters and (b) designing studies in ways that maximize the potential for valid inference. We discuss these challenges – drawing on specific examples – and suggest potential approaches to each that may be helpful as a guide for future work. We further suggest research directions that may be most helpful in moving the field forward. Copyright © 2008 John Wiley & Sons, Ltd.