ORCID Profile
0000-0002-6362-4297
Current Organisation
Department of Health
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Publisher: Informa UK Limited
Date: 25-05-2018
Publisher: F1000 Research Ltd
Date: 2014
Publisher: Rural and Remote Health
Date: 29-01-2017
DOI: 10.22605/RRH4026
Publisher: John Wiley & Sons, Ltd
Date: 19-10-2005
Publisher: John Wiley & Sons, Ltd
Date: 19-10-2005
Publisher: BMJ
Date: 05-2019
DOI: 10.1136/BMJOPEN-2019-029585
Abstract: General practice in Australia, as in many countries, faces challenges in the areas of workforce capacity and workforce distribution. General practice vocational training in Australia not only addresses the training of competent independent general practitioners (GPs) but also addresses these workforce issues. This study aims to establish the prevalence and associations of early career (within 2 years of completion of vocational training) GPs’ practice characteristics and also to establish their perceptions of utility of their training in preparing them for independent practice. This will be a cross-sectional questionnaire study. Participants will be former registrars (‘alumni’) of three regional training organisations (RTOs) who achieved general practice Fellowship (qualifying them for independent practice) between January 2016 and July 2018 inclusive. The questionnaire data will be linked to data collected as part of the participants’ educational programme with the RTOs. Outcomes will include alumni rurality of practice socioeconomic status of practice retention within their RTO’s geographic footprint workload provision of nursing home care, after-hours care and home visits and involvement in general practice teaching and supervision. Associations of these outcomes will be established with logistic regression. The utility of RTO-provided training versus in-practice training in preparing the early career GP for unsupervised post-Ffellowship practice in particular aspects of practice will be assessed with χ 2 tests. Ethics approval is by the University of Newcastle Human Research Ethics Committee, approval numbers H-2018-0333 and H-2009-0323. The findings of this study will be widely disseminated via conference presentations and publication in peer-reviewed journals, educational practice translational workshops and the GP Synergy Research subwebsite.
Publisher: AMPCo
Date: 03-2018
DOI: 10.5694/MJA17.00400
Abstract: To estimate the efficacy of selection tools employed by medical schools for predicting the binary outcomes of completing or not completing medical training and passing or failing a key examination to investigate the potential usefulness of selection algorithms that do not allow low scores on one tool to be compensated by higher scores on other tools. Data from four consecutive cohorts of students (3378 students, enrolled 2007-2010) in five undergraduate medical schools in Australia and New Zealand were analysed. Predictor variables were student scores on selection tools: prior academic achievement, Undergraduate Medicine and Health Sciences Admission Test (UMAT), and selection interview. Outcome variables were graduation from the program in a timely fashion, or passing the final clinical skills assessment at the first attempt. Optimal selection cut-scores determined by discriminant function analysis for each selection tool at each school efficacy of different selection algorithms for predicting student outcomes. For both outcomes, the cut-scores for prior academic achievement had the greatest predictive value, with medium to very large effect sizes (0.44-1.22) at all five schools. UMAT scores and selection interviews had smaller effect sizes (0.00-0.60). Meeting one or more cut-scores was associated with a significantly greater likelihood of timely graduation in some schools but not in others. An optimal cut-score can be estimated for a selection tool used for predicting an important program outcome. A "sufficient evidence" selection algorithm, founded on a non-compensatory model, is feasible, and may be useful for some schools.
Location: No location found
Location: Australia
No related grants have been discovered for Allison Turnock.