A combination sampling approach for epidemiologic research in humanitarian settings: a case analysis of a study of depressive disorder prevalence among refugees in Greece

BMC Public Health, vol. 21, pp. 272

Abstract

BACKGROUND: Understanding the burden of common mental health disorders, such as depressive disorder, is the first step in strengthening prevention and treatment in humanitarian emergencies. However, simple random sampling methods may lead to a high risk of coercion in settings characterized by a lack of distinction between researchers and aid organizations, mistrust, privacy concerns, and the overarching power differential between researchers and populations affected by crises. This case analysis describes a sampling approach developed for a survey study of depressive disorder in a Syrian refugee camp in Greece (n = 135). DISCUSSION: Syrian refugees face an extraordinarily high burden of depressive disorder during the asylum process (43%), necessitating population screening, prevention, and treatment. In order to preserve the informed consent process in this refugee camp setting, the research team developed a two-phase sampling strategy using a map depicting the geographical layout of the housing units within the camp. In the first phase, camp management announced a research study was being undertaken and individuals were invited to volunteer to participate. The participants' container (housing) numbers were recorded on the map, but were not linked to the survey data. Then, in the second phase, the camp map was used for complementary sampling to reach a sample sufficient for statistical analysis. As a result of the two phases of the sampling exercise, all eligible adults from half the containers in each block were recruited, producing a systematic, age- and sex-representative sample. CONCLUSIONS: Combining sampling procedures in humanitarian emergencies can reduce the risk of coerced consent and bias by allowing participants to approach researchers in the first phase, with a second phase of sampling conducted to recruit a systematic sample. This case analysis illuminates the feasibility of a two-phase sampling approach for drawing a quasi-random, representative sample in a refugee camp setting.

Authors 6

1. Danielle N. Poole corresponding

   Dartmouth College · Harvard University

   Affiliation as printed

   Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, 02115, USA. dani.poole@dartmouth.edu

   Harvard Humanitarian Initiative, Harvard T.H. Chan School of Public Health, 14 Story Street, Cambridge, MA, 02138, USA. dani.poole@dartmouth.edu

   Neukom Institute for Computational Science, Dartmouth College, Hanover, NH, 03755, USA. dani.poole@dartmouth.edu

   Neukom Institute for Computational Science, Dartmouth College, Hanover, NH, 03755, USA

2. Nathaniel A. Raymond

   Yale University

   Affiliation as printed

   Jackson Institute of Global Affairs, Yale University, 55 Hillhouse Avenue, New Haven, CT, 06520, USA

3. Jos Berens Aachen Centre for Innovation, Leiden University

   Leiden University

   Affiliation as printed

   Centre for Innovation, Leiden University, Den Haag, 2511 VA, The Netherlands

4. Mark Latonero

   Data & Society Research Institute

   Affiliation as printed

   Data & Society Research Institute, New York, NY, 10011, USA

5. Julie Ricard
   Affiliation as printed

   Data-Pop Alliance, New York, NY, 10016, USA

6. Bethany Hedt‐Gauthier

   Harvard University

   Affiliation as printed

   Department of Biostatistics, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, 02115, USA

   Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue, Boston, MA, 02115, USA