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Gender-related explanatory models of depression: a critical evaluation of medical articles
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine.
Umeå University, Faculty of Social Sciences, Department of Sociology.
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2009 (English)In: Public Health, ISSN 0033-3506, E-ISSN 1476-5616, Vol. 123, no 10, 689-693 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier , 2009. Vol. 123, no 10, 689-693 p.
Keyword [en]
Public health, Depression, Gender, Explanatory models, Bibliometric methods, Intersectionality, Multifactoriality
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-30096DOI: 10.1016/j.puhe.2009.09.010PubMedID: 19853877OAI: oai:DiVA.org:umu-30096DiVA: diva2:279591
Available from: 2009-12-04 Created: 2009-12-04 Last updated: 2012-05-10Bibliographically approved

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Hammarström, AnneLehti, ArjaDanielsson, UllaBengs, Carita

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