Gender-related explanatory models of depression: a critical evaluation of medical articles

Public Health. 2009 Oct;123(10):689-93. doi: 10.1016/j.puhe.2009.09.010. Epub 2009 Oct 23.

Abstract

Objectives: Although research has consistently shown a higher prevalence of depression among women compared with men, there is a lack of consensus regarding explanatory factors for these gender-related differences. The aim of this paper was to analyse the scientific quality of different gender-related explanatory models of depression in the medical database PubMed.

Study design: Qualitative and quantitative analyses of PubMed articles.

Methods: In a database search in PubMed for 2002, 82 articles on gender and depression were selected and analysed with qualitative and quantitative content analyses. In total, 10 explanatory factors and four explanatory models were found. The ISI Web of Science database was searched in order to obtain the citation number and journal impact factor for each article.

Results: The most commonly used gender-related explanatory model for depression was the biomedical model (especially gonadal hormones), followed by the sociocultural and psychological models. Compared with the other models, the biomedical model scored highest on bibliometric measures but lowest on measures of multifactorial dimensions and differences within the group of men/women.

Conclusion: The biomedical model for explaining gender-related aspects of depression had the highest quality when bibliometric methods were used. However, the sociocultural and psychological models had higher quality than the biomedical model when multifactoriality and intersectionality were analysed. There is a need for the development of new methods in order to evaluate the scientific quality of research.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Research
  • Depression / epidemiology*
  • Female
  • Humans
  • Journal Impact Factor
  • Male
  • Models, Psychological*
  • Qualitative Research
  • Risk Factors
  • Sex Factors