Zi-Yue Wang1, Li-Jie Zhang2,3, Yu-Hong Liu2,3, Wei-Xi Jiang4, Jing-Yun Jia5, Sheng-Lan Tang4, Xiao-Yun Liu6. 1. China Centre for Health Development Studies, Peking University, Beijing, 100191, China. 2. Beijing Chest Hospital, Capital Medical University, No. 97 Ma Chang, Tongzhou, Beijing, 101149, China. 3. Clinical Centre on Tuberculosis, Chinese Centre for Disease Control and Prevention, No. 97 Ma Chang, Tongzhou, Beijing, 101149, China. 4. Global Health Research Centre, Duke Kunshan University, No. 8 Duke Avenue, Kunshan, 215316, Jiangsu, China. 5. School of Mathematical Science, Nankai University, No 94. Weijin Road, Tianjin, 300071, China. 6. China Centre for Health Development Studies, Peking University, Beijing, 100191, China. xiaoyunliu@pku.edu.cn.
Abstract
BACKGROUND: Given the context of rapid technological change and COIVD-19 pandemics, E-learning may provide a unique opportunity for addressing the challenges in traditional face-to-face continuing medical education (CME). However, the effectiveness of E-learning in CME interventions remains unclear. This study aims to evaluate whether E-learning training program can improve TB health personnel's knowledge and behaviour in China. METHODS: This study used a convergent mixed method research design to evaluate the impact of E-learning programs for tuberculosis (TB) health workers in terms of knowledge improvement and behaviour change during the China-Gates TB Project (add the time span). Quantitative data was collected by staff surveys (baseline n = 555; final n = 757) and management information systems to measure the demographic characteristics, training participation, and TB knowledge. Difference-in-difference (DID) and multiple linear regression models were employed to capture the effectiveness of knowledge improvement. Qualitative data was collected by interviews (n = 30) and focus group discussions (n = 44) with managers, teachers, and learners to explore their learning experience. RESULTS: Synchronous E-learning improved the knowledge of TB clinicians (average treatment effect, ATE: 7.3 scores/100, P = 0.026). Asynchronous E-learning has a significant impact on knowledge among primary care workers (ATE: 10.9/100, P < 0.001), but not in clinicians or public health physicians. Traditional face-to-face training has no significant impact on all medical staff. Most of the learners (57.3%) agreed that they could apply what they learned to their practice. Qualitative data revealed that high quality content is the key facilitator of the behaviour change, while of learning content difficulty, relevancy, and hardware constraints are key barriers. CONCLUSIONS: The effectiveness of E-learning in CME varies across different types of training formats, organizational environment, and target audience. Although clinicians and primary care workers improved their knowledge by E-learning activities, public health physicians didn't benefit from the interventions.
BACKGROUND: Given the context of rapid technological change and COIVD-19 pandemics, E-learning may provide a unique opportunity for addressing the challenges in traditional face-to-face continuing medical education (CME). However, the effectiveness of E-learning in CME interventions remains unclear. This study aims to evaluate whether E-learning training program can improve TB health personnel's knowledge and behaviour in China. METHODS: This study used a convergent mixed method research design to evaluate the impact of E-learning programs for tuberculosis (TB) health workers in terms of knowledge improvement and behaviour change during the China-Gates TB Project (add the time span). Quantitative data was collected by staff surveys (baseline n = 555; final n = 757) and management information systems to measure the demographic characteristics, training participation, and TB knowledge. Difference-in-difference (DID) and multiple linear regression models were employed to capture the effectiveness of knowledge improvement. Qualitative data was collected by interviews (n = 30) and focus group discussions (n = 44) with managers, teachers, and learners to explore their learning experience. RESULTS: Synchronous E-learning improved the knowledge of TB clinicians (average treatment effect, ATE: 7.3 scores/100, P = 0.026). Asynchronous E-learning has a significant impact on knowledge among primary care workers (ATE: 10.9/100, P < 0.001), but not in clinicians or public health physicians. Traditional face-to-face training has no significant impact on all medical staff. Most of the learners (57.3%) agreed that they could apply what they learned to their practice. Qualitative data revealed that high quality content is the key facilitator of the behaviour change, while of learning content difficulty, relevancy, and hardware constraints are key barriers. CONCLUSIONS: The effectiveness of E-learning in CME varies across different types of training formats, organizational environment, and target audience. Although clinicians and primary care workers improved their knowledge by E-learning activities, public health physicians didn't benefit from the interventions.
Entities:
Keywords:
Continuing medical education; E-learning; Program evaluation; Training; Tuberculosis
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