An evaluation of knowledge, attitudes, practice, and associated factors regarding oxygen therapy among resident doctors in a tertiary care teaching hospital: A mixed-methods study.

BACKGROUND

Despite oxygen therapy guidelines, suboptimal practices prevail among front-line resident doctors, highlighting knowledge and attitudinal barriers. Mixed-methods research can inform tailored quality improvements. This study aimed to assess the knowledge, attitudes, and practices of resident doctors regarding oxygen therapy, determine associated factors quantitatively, and explore experiences, barriers, and enablers qualitatively.

MATERIALS AND METHODS

This was a convergent parallel mixed-methods study conducted at a tertiary teaching hospital. An analytical cross-sectional survey of 410 resident doctors assessed knowledge, attitudes, and practices using a questionnaire. Qualitative phenomenology entailed in-depth interviews with 30 participants analyzing experiences and perspectives. Integration enabled corroborating and complementing findings. Logistic regression analysis and thematic analysis were used to make themes and subthemes.

RESULTS

Most demonstrated suboptimal knowledge (78% or 320/410 good), attitudes (61.7% or 253/410 positive), and practices (47.8% or 196/410 good). Significant factors were gender, experience, workload perceptions, and device familiarity. Males had 5.5 times higher odds of good knowledge (adjusted odds ratio (AOR) 5.5, 95% confidence interval (CI) 3.25-10). Those perceiving workload impact had 13 times higher odds of positive attitudes (AOR 13, 95% CI 9.4-20.9). Qualitative themes highlighted inadequate skills and time constraints as barriers and protocolization and decision tools as enablers.

CONCLUSION

Gaps exist in knowledge, attitudes, and practices regarding oxygen therapy among resident doctors attributable to varied factors. Tailored quality improvement strategies addressing demonstrated barriers, such as enablement workshops, order set integration, and pulse oximetry audits, are recommended based on mixed-methods insights.