Purpose To describe the prevalence of burnout among healthcare professionals dealing with COVID-19 patients and the associated factors. Methods In this cross-sectional survey, healthcare workers at six university-affiliated hospitals, who had been taking care of COVID-19 patients were studied. Age, gender, marital status, having children, hospital, job category, experience, and work load, as well as the level of burnout in each subscale were measured. Results 326 persons (53.0%) experienced high levels of burnout. The average score in emotional exhaustion, depersonalization and lack of personal accomplishment was 26.6, 10.2, and 27.3, respectively. The level of burnout in the three subscales varied based on the personal as well as work-related factors and gender was the only variable that was associated with high levels of all three domains. Conclusions Burnout is prevalent among healthcare workers caring for COVID-19 patients. Age, gender, job category, and site of practice contribute to the level of burnout that the staff experience.

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Background: The unpredictable nature of the new COVID-19 pandemic and the already alarming incidence of healthcare workers being affected can have a significant impact on the psychological well-being of the staff. Objective: To describe the prevalence of burnout among healthcare professionals and the associated factors. Design: Cross-sectional survey. Setting: Eight university affiliated hospitals in the capital city of Tehran, Iran. Participants: All healthcare workers at the study sites who had been taking care of COVID-19 patients. Measurements: Age, gender, marital status, having children, hospital, job category, experience, and work load, as well as the level of burnout in each subscale. Results: 326 persons (53.0%) experienced high levels of burnout. The average score in emotional exhaustion, depersonalization and lack of personal accomplishment was 26.6, 10.2, and 27.3, respectively. The level of burnout in the three subscales varied based on the personal as well as work related factors and gender was the only variable that was associated with high levels of all three domains. Limitations: There was no control group and thus we cannot claim a causal relationship between COVID-19 and the observed level of burnout. Not all confounding factors might have been accounted for. Conclusions: Burnout is prevalent among healthcare workers caring for COVID-19 patients. Age, gender, job category, and site of practice contribute to the level of burnout that the staff experience.

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The purpose of this study was to utilize the Context, Input, Process and Product (CIPP) evaluation model as a comprehensive framework to guide initiating, planning, implementing and evaluating a revised undergraduate medical education programme. The eight-year longitudinal evaluation study consisted of four phases compatible with the four components of the CIPP model. In the first phase, we explored the strengths and weaknesses of the traditional programme as well as contextual needs, assets, and resources. For the second phase, we proposed a model for the programme considering contextual features. During the process phase, we provided formative information for revisions and adjustments. Finally, in the fourth phase, we evaluated the outcomes of the new undergraduate medical education programme in the basic sciences phase. Information was collected from different sources such as medical students, faculty members, administrators, and graduates, using various qualitative and quantitative methods including focus groups, questionnaires, and performance measures. The CIPP model has the potential to guide policy makers to systematically collect evaluation data and to manage stakeholders’ reactions at each stage of the reform in order to make informed decisions. However, the model may result in evaluation burden and fail to address some unplanned evaluation questions.

ContextUnderstanding self‐regulated learning (SRL) is complicated due to the different measures used to identify the key SRL processes. There is a growing trend in applying event measures of SRL (microanalysis and trace) but aptitude measures (questionnaires) continue to be widely used in medical education. A major concern is whether aptitude measures are a valid approach to capture the dimensions of SRL processes. This study examined correlations between SRL microanalysis, SRL trace and the Motivated Strategies for Learning Questionnaire (MSLQ) and how these measures were associated with biomedical science performance.MethodsAn SRL microanalysis assessment interview was administered to 76 first‐year medical students individually when performing a biomedical science learning task. All written materials by students were collected for further trace analysis. Students completed an MSLQ 2 weeks before completing their biomedical science course. Correlation analyses were used to determine the correlations between the three SRL assessment measures. Bivariate and multiple analyses were conducted to compare students on different course or task performance using the three SRL assessment measures.ResultsMicroanalytic metacognitive monitoring (κ = 0.30, P < .001) and causal attributions (κ = 0.17, P = .009) had statistically significant correlations with use of the SRL trace strategy. MSLQ self‐efficacy correlated with microanalytic self‐efficacy (r = .39, P = .001). Bivariate tests showed that microanalytic metacognitive monitoring, causal attributions and adaptive inferences, and SRL trace strategy use had significant associations with task performance (P < .05). Microanalytic self‐efficacy, metacognitive monitoring and causal attributions, SRL trace strategy use and MSLQ self‐efficacy had significant associations with course performance (P < .05). Measures of use of the SRL trace strategy and MSLQ subscales did not show significant associations with task and course outcomes in multiple analyses (P > .05).ConclusionsEvent measures, specifically SRL microanalysis, had greater associations with both task and course outcomes compared with the MSLQ measure. The SRL microanalysis is recommended for the assessment of SRL in biomedical science learning. However, to fully understand medical students’ SRL a multidimensional assessment approach that combines event and aptitude measures should be used.