International Journal of Innovative Research in Health Science

Background: Cotton industry workers may be exposed to occupational hazards, including respiratory hazards related to cotton dust, noise-related hearing problems, and workplace injuries. Education is one approach used to improve workers’ awareness of prevention. Objective: To evaluate the effectiveness of a video-assisted teaching programme on knowledge and attitude regarding prevention of selected occupational health hazards among cotton industry workers in Dindigul, Tamil Nadu, India. Methods: A quasi-experimental, one-group pre-test–post-test design was used. Sixty cotton industry workers were selected by simple random sampling from a selected cotton industry. Data were collected using a demographic and health-history proforma, a 21-item structured knowledge questionnaire, and a 15-statement five-point Likert attitude scale. A video-assisted teaching programme of approximately 30 minutes was followed by group discussion, and the post-test was conducted one week later. Descriptive statistics, paired t-tests, Pearson correlation, and chi-square tests were reported. Results: Before the intervention, all 60 participants (100%) had inadequate knowledge. At post-test, 41 (68%) had adequate knowledge and 19 (32%) had moderate knowledge. Negative attitude was reported by 15 participants (25%) and neutral attitude by 45 (75%) at pre-test; at post-test, 57 (95%) had positive attitude and 3 (5%) had neutral attitude. Mean knowledge scores increased from 21.91 (SD 5.16) to 73.98 (SD 6.94), with a reported paired t value of 52.02. Mean attitude scores increased from 43.92 (SD 5.89) to 82.95 (SD 3.87), with a reported paired t value of 64.11. Post-test knowledge and attitude were moderately positively correlated (r=0.51). Educational qualification and years of work experience were reported to be associated with knowledge and attitude. Conclusion: The study reported improved knowledge and attitude scores following the video-assisted teaching programme. The findings should be interpreted in light of the single-group design and inconsistencies in the original report’s statistical notation.