Melbourne Institute of Applied Economic and Social Research - Research Publications
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ItemMedicine in Australia: Balancing Employment and Life (MABEL)Yan, W ; Cheng, TC ; Scott, A ; Joyce, CM ; Humphreys, J ; Kalb, G ; Leahy, A (WILEY-BLACKWELL, 2011-03-01)
ItemThe "Medicine in Australia: Balancing Employment and Life (MABEL)" longitudinal survey - Protocol and baseline data for a prospective cohort study of Australian doctors' workforce participationJoyce, CM ; Scott, A ; Jeon, S-H ; Humphreys, J ; Kalb, G ; Witt, J ; Leahy, A (BIOMED CENTRAL LTD, 2010-02-25)BACKGROUND: While there is considerable research on medical workforce supply trends, there is little research examining the determinants of labour supply decisions for the medical workforce. The "Medicine in Australia: Balancing Employment and Life (MABEL)" study investigates workforce participation patterns and their determinants using a longitudinal survey of Australian doctors. It aims to generate evidence to support developing effective policy responses to workforce issues such as shortages and maldistribution. This paper describes the study protocol and baseline cohort, including an analysis of response rates and response bias. METHODS/DESIGN: MABEL is a prospective cohort study. All Australian doctors undertaking clinical work in 2008 (n = 54,750) were invited to participate, and annual waves of data collections will be undertaken until at least 2011. Data are collected by paper or optional online version of a questionnaire, with content tailored to four sub-groups of clinicians: general practitioners, specialists, specialists in training, and hospital non-specialists. In the baseline wave, data were collected on: job satisfaction, attitudes to work and intentions to quit or change hours worked; a discrete choice experiment examining preferences and trade-offs for different types of jobs; work setting; workload; finances; geographic location; demographics; and family circumstances. DISCUSSION: The baseline cohort includes 10,498 Australian doctors, representing an overall response rate of 19.36%. This includes 3,906 general practitioners, 4,596 specialists, 1,072 specialists in training, and 924 hospital non-specialists. Respondents were more likely to be younger, female, and to come from non-metropolitan areas, the latter partly reflecting the effect of a financial incentive on response for doctors in remote and rural areas. Specialists and specialists in training were more likely to respond, whilst hospital non-specialists were less likely to respond. The distribution of hours worked was similar between respondents and data from national medical labour force statistics. The MABEL survey provides a large, representative cohort of Australian doctors. It enables investigation of the determinants of doctors' decisions about how much, where and in what circumstances they practice, and of changes in these over time. MABEL is intended to provide an important resource for policy makers and other stakeholders in the Australian medical workforce.
ItemA randomised trial and economic evaluation of the effect of response mode on response rate, response bias, and item non-response in a survey of doctorsScott, A ; Jeon, S-H ; Joyce, CM ; Humphreys, JS ; Kalb, G ; Witt, J ; Leahy, A (BIOMED CENTRAL LTD, 2011-09-05)BACKGROUND: Surveys of doctors are an important data collection method in health services research. Ways to improve response rates, minimise survey response bias and item non-response, within a given budget, have not previously been addressed in the same study. The aim of this paper is to compare the effects and costs of three different modes of survey administration in a national survey of doctors. METHODS: A stratified random sample of 4.9% (2,702/54,160) of doctors undertaking clinical practice was drawn from a national directory of all doctors in Australia. Stratification was by four doctor types: general practitioners, specialists, specialists-in-training, and hospital non-specialists, and by six rural/remote categories. A three-arm parallel trial design with equal randomisation across arms was used. Doctors were randomly allocated to: online questionnaire (902); simultaneous mixed mode (a paper questionnaire and login details sent together) (900); or, sequential mixed mode (online followed by a paper questionnaire with the reminder) (900). Analysis was by intention to treat, as within each primary mode, doctors could choose either paper or online. Primary outcome measures were response rate, survey response bias, item non-response, and cost. RESULTS: The online mode had a response rate 12.95%, followed by the simultaneous mixed mode with 19.7%, and the sequential mixed mode with 20.7%. After adjusting for observed differences between the groups, the online mode had a 7 percentage point lower response rate compared to the simultaneous mixed mode, and a 7.7 percentage point lower response rate compared to sequential mixed mode. The difference in response rate between the sequential and simultaneous modes was not statistically significant. Both mixed modes showed evidence of response bias, whilst the characteristics of online respondents were similar to the population. However, the online mode had a higher rate of item non-response compared to both mixed modes. The total cost of the online survey was 38% lower than simultaneous mixed mode and 22% lower than sequential mixed mode. The cost of the sequential mixed mode was 14% lower than simultaneous mixed mode. Compared to the online mode, the sequential mixed mode was the most cost-effective, although exhibiting some evidence of response bias. CONCLUSIONS: Decisions on which survey mode to use depend on response rates, response bias, item non-response and costs. The sequential mixed mode appears to be the most cost-effective mode of survey administration for surveys of the population of doctors, if one is prepared to accept a degree of response bias. Online surveys are not yet suitable to be used exclusively for surveys of the doctor population.