A cross-cultural investigation into the dimensional structure and stability of the Barriers to Research and Utilization Scale (BARRIERS Scale)

BMC Res Notes. 2015 Oct 24:8:601. doi: 10.1186/s13104-015-1579-9.

Abstract

Background: It is important that scales exhibit strong measurement properties including those related to the investigation of issues that impact evidence-based practice. The validity of the Barriers to Research Utilization Scale (BARRIERS Scale) has recently been questioned in a systematic review. This study investigated the dimensional structure and stability of the 28 item BARRIERS Scale when completed by three groups of participants from three different cross-cultural environments.

Method: Data from the BARRIERS Scale completed by 696 occupational therapists from Australia (n = 137), Taiwan (n = 413), and the United Kingdom (n = 144) were analysed using principal components analysis, followed by Procrustes Transformation. Poorly fitting items were identified by low communalities, cross-loading, and theoretically inconsistent primary loadings, and were systematically removed until good fit was achieved. The cross-cultural stability of the component structure of the BARRIERS Scale was examined.

Results: A four component, 19 item version of the BARRIERS Scale emerged that demonstrated an improved dimensional fit and stability across the three participant groups. The resulting four components were consistent with the BARRIERS Scale as originally conceptualised.

Conclusion: Findings from the study suggest that the four component, 19 item version of the BARRIERS Scale is a robust and valid measure for identifying barriers to research utilization for occupational therapists in paediatric health care settings across Australia, United Kingdom, and Taiwan. The four component 19 item version of the BARRIERS Scale exhibited good dimensional structure, internal consistency, and stability.

MeSH terms

  • Adult
  • Australia
  • Evidence-Based Practice
  • Female
  • Health Services Research*
  • Humans
  • Male
  • Middle Aged
  • Principal Component Analysis
  • Taiwan
  • United Kingdom
  • Young Adult