METHODS: A cross-sectional survey study utilising snowball sampling was performed involving doctors, nurses and allied health professions from 23 hospitals in Singapore, Malaysia, India and Indonesia between 29 May 2020 and 13 July 2020. This survey collated demographic data and workplace conditions and included three validated questionnaires: the Safety Attitudes Questionnaire (SAQ), Oldenburg Burnout Inventory and Hospital Anxiety and Depression Scale. We performed multivariate mixed-model regression to assess independent associations with the SAQ total percentage agree rate (PAR).
RESULTS: We obtained 3,163 responses. The SAQ total PARs were found to be 35.7%, 15.0%, 51.0% and 3.3% among the respondents from Singapore, Malaysia, India and Indonesia, respectively. Burnout scores were highest among respondents from Indonesia and lowest among respondents from India (70.9%-85.4% vs. 56.3%-63.6%, respectively). Multivariate analyses revealed that meeting burnout and depression thresholds and shifts lasting ≥12 h were significantly associated with lower SAQ total PAR.
CONCLUSION: Addressing the factors contributing to high burnout and depression and placing strict limits on work hours per shift may contribute significantly towards improving safety culture among HCWs and should remain priorities during the pandemic.
METHODS AND ANALYSIS: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk.
ETHICS AND DISSEMINATION: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3).