Applying qualitative comparative analysis (QCA) in public health: a case study of a health improvement service for long-term incapacity benefit recipients

J Public Health (Oxf). 2014 Mar;36(1):126-33. doi: 10.1093/pubmed/fdt047. Epub 2013 May 3.

Abstract

Background: This paper explores the value of qualitative comparative analysis (QCA) in public health research using the example of a pilot case management intervention for long-term incapacity benefit recipients. It uses QCA to examine how the 'health improvement' effects of the intervention varied by individual and service characteristics.

Methods: Data for 131 participants receiving the intervention were collected over 9 months. Health improvement was measured using the EuroQual Visual Analogue Scale. Socio-demographic, health behaviour data were also collected. Data on service use was obtained from the provider's client records. Crisp set QCA was conducted to identify which individual and service characteristics were most likely to produce a health benefit after participation in the intervention.

Results: Health improvement was most likely amongst younger participants, men aged over 50 and those with an occupational history of skilled manual work or higher and less likely amongst older women, those with a musculoskeletal condition and those with semi- or un-skilled backgrounds. Service characteristics had no impact.

Conclusions: The QCA identified potential causal pathways for health improvement from the intervention with important potential implications for health inequalities. QCA should be considered as a viable and practical method in the public health evaluation tool box.

Keywords: health inequality; sickness absence; welfare; worklessness.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Case Management* / standards
  • Disabled Persons*
  • Female
  • Health Status
  • Humans
  • Male
  • Middle Aged
  • Program Evaluation
  • Quality Assurance, Health Care / methods*
  • Sex Factors