Development and psychometric validation of a KAP questionnaire on biomedical waste management among Ayurveda healthcare workers

BACKGROUND: Biomedical waste management is an essential element of hospital infection control, particularly in Ayurveda facilities where panchakarma procedures generate diverse and potentially infectious waste. Despite its significance, there is absence of standardized tools to comprehensively measure the knowledge, attitude, and practice (KAP) of healthcare workers in this field. Hence the present research work aims to design and validate a questionnaire that is crucial to capture accurate, comparable data, identify knowledge gaps, and guide targeted training or policy interventions. METHODS: A single-centre, cross-sectional psychometric study using convenience sampling was conducted on 190 Ayurveda healthcare workers in a tertiary care Ayurveda healthcare setting in Kerala, India. An initial 38-item questionnaire draft was generated on the basis of review of literature and focus group discussion with relevant area experts. Then judgement of questionnaire was based on Content validity and Face validity by expert panel. Test-retest reliability, internal consistency reliability, and construct validity of instrument were established later by using SPSS version 25. Measurement model and structural components were derived using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. Goodness- of- fit between model and actual data of study was determined through various fit indices. RESULTS: Item-level content validity (I-CVI > 0.79) and face validity (scores ≥ 8/10) confirmed relevance and clarity. Four items with weak test-retest reliability were removed. The final 34-item questionnaire demonstrated good internal consistency (Cronbach's α = 0.788-0.830, overall α = 0.877) and stability (ICC = 0.769-0.812, overall ICC = 0.771). Exploratory factor analysis (EFA) supported a three-factor structure (Knowledge, Attitude, Practice) explaining 54.98% of variance. PLS-SEM indicated large effect sizes for Knowledge and Attitude (f² = 0.492, 0.466) and moderate explanatory power for Practice (R² = 0.443), with overall good model fit. CONCLUSION: Results showed evidence for validity and reliability of questionnaire assessing knowledge, attitude and practice regarding biomedical waste management among Ayurveda healthcare workers. The tool was developed and validated in a single Ayurveda tertiary care centre; further validation is needed in other settings.

Authors

Institutions

Publication Details

Journal
BMC Health Services Research
Published
2026-06-29
DOI
https://doi.org/10.1186/s12913-026-14970-9
Primary Topic
Healthcare and Environmental Waste Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and psychometric validation of a KAP questionnaire on biomedical waste management among Ayurveda healthcare workers

Mala Rani, Anusree Dileep, S. Meera, Delvin T. Robin et al.
BMC Health Services Research
Healthcare and Environmental Waste Management
article

Development and psychometric validation of a KAP questionnaire on biomedical waste management among Ayurveda healthcare workers

Mala Rani, Anusree Dileep, S. Meera, Delvin T. Robin, S. Archana
article en

Abstract

BACKGROUND: Biomedical waste management is an essential element of hospital infection control, particularly in Ayurveda facilities where panchakarma procedures generate diverse and potentially infectious waste. Despite its significance, there is absence of standardized tools to comprehensively measure the knowledge, attitude, and practice (KAP) of healthcare workers in this field. Hence the present research work aims to design and validate a questionnaire that is crucial to capture accurate, comparable data, identify knowledge gaps, and guide targeted training or policy interventions. METHODS: A single-centre, cross-sectional psychometric study using convenience sampling was conducted on 190 Ayurveda healthcare workers in a tertiary care Ayurveda healthcare setting in Kerala, India. An initial 38-item questionnaire draft was generated on the basis of review of literature and focus group discussion with relevant area experts. Then judgement of questionnaire was based on Content validity and Face validity by expert panel. Test-retest reliability, internal consistency reliability, and construct validity of instrument were established later by using SPSS version 25. Measurement model and structural components were derived using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. Goodness- of- fit between model and actual data of study was determined through various fit indices. RESULTS: Item-level content validity (I-CVI > 0.79) and face validity (scores ≥ 8/10) confirmed relevance and clarity. Four items with weak test-retest reliability were removed. The final 34-item questionnaire demonstrated good internal consistency (Cronbach's α = 0.788-0.830, overall α = 0.877) and stability (ICC = 0.769-0.812, overall ICC = 0.771). Exploratory factor analysis (EFA) supported a three-factor structure (Knowledge, Attitude, Practice) explaining 54.98% of variance. PLS-SEM indicated large effect sizes for Knowledge and Attitude (f² = 0.492, 0.466) and moderate explanatory power for Practice (R² = 0.443), with overall good model fit. CONCLUSION: Results showed evidence for validity and reliability of questionnaire assessing knowledge, attitude and practice regarding biomedical waste management among Ayurveda healthcare workers. The tool was developed and validated in a single Ayurveda tertiary care centre; further validation is needed in other settings.

BMC Health Services Research
Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 7%
Healthcare and Environmental Waste Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.