ChecKAP: A Checklist for Reporting a Knowledge, Attitude, and Practice (KAP) Study
Year: 2024
Type: article
Abstract: INTRODUCTION: The Knowledge, Attitudes, and Practices (KAP) model is a foundational tool in public health research. KAP surveys play a vital role in this process by gauging a population's current level of knowledge about a specific health issue. Rigorous evaluation is essential for ensuring the validity and reliability of KAP studies. Therefore, in this study, a comprehensive checklist for reporting Knowledge, Attitude, and Practices (KAP) Studies was developed. METHODOLOGY: This study was conducted using a systematic six-step roadmap. A comprehensive review of available relevant quality assessment tools led to the development of specific new items. An expert panel reviewed the initial draft, and after corrections were made, the second draft was finalized and subjected to psychometric analysis by experts. RESULTS: The development of ChecKAP (Checklist for Reporting Items for Knowledge, Attitude, and Practice) represents a significant contribution to KAP studies. The final tool consists of 46 items across 8 fields: title (1 item), abstract (6 items), keywords (1 item), introduction (6 items), method (11 items), findings (7 items), discussion (15 items), and conclusion (1 item). CONCLUSION: ChecKAP assesses the inherent complexity of KAP research methods and ensures consistent reporting. It fills an important gap in the KAP research literature and serves a dual purpose. First, it acts as a quality assessment tool for reviewers, enabling them to evaluate the methodological rigor and clarity of submitted manuscripts. Second, it serves as a guideline for authors, promoting a more systematic and transparent approach to reporting.
Institutions: Tarbiat Modares University, Kerman University of Medical Sciences, Shahid Beheshti University, Shahid Beheshti University of Medical Sciences, Khon Kaen University, Government of Himachal Pradesh, Research Institute for Endocrine Sciences, Kurdistan Higher Council of Medical Specialties
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $200
OpenAlex ID: W4401062020
