Literature DB >> 20167340

Synthesizing diverse evidence: the use of primary qualitative data analysis methods and logic models in public health reviews.

S Baxter1, A Killoran, M P Kelly, E Goyder.   

Abstract

OBJECTIVES: The nature of public health evidence presents challenges for conventional systematic review processes, with increasing recognition of the need to include a broader range of work including observational studies and qualitative research, yet with methods to combine diverse sources remaining underdeveloped. The objective of this paper is to report the application of a new approach for review of evidence in the public health sphere. The method enables a diverse range of evidence types to be synthesized in order to examine potential relationships between a public health environment and outcomes. STUDY
DESIGN: The study drew on previous work by the National Institute for Health and Clinical Excellence on conceptual frameworks. It applied and further extended this work to the synthesis of evidence relating to one particular public health area: the enhancement of employee mental well-being in the workplace.
METHODS: The approach utilized thematic analysis techniques from primary research, together with conceptual modelling, to explore potential relationships between factors and outcomes.
RESULTS: The method enabled a logic framework to be built from a diverse document set that illustrates how elements and associations between elements may impact on the well-being of employees.
CONCLUSIONS: Whilst recognizing potential criticisms of the approach, it is suggested that logic models can be a useful way of examining the complexity of relationships between factors and outcomes in public health, and of highlighting potential areas for interventions and further research. The use of techniques from primary qualitative research may also be helpful in synthesizing diverse document types. Copyright 2010 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Mesh:

Year:  2010        PMID: 20167340     DOI: 10.1016/j.puhe.2010.01.002

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


  23 in total

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