{"id":72587,"date":"2024-09-18T08:43:55","date_gmt":"2024-09-18T00:43:55","guid":{"rendered":"https:\/\/medicine.nus.edu.sg\/taps\/?post_type=issues&p=72587"},"modified":"2025-01-07T08:26:31","modified_gmt":"2025-01-07T00:26:31","slug":"career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years","status":"publish","type":"issues","link":"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/","title":{"rendered":"Career choice in medical graduates \u2013 A national, quantitative analysis over five years"},"content":{"rendered":"

Submitted: 19 December 2023
\r\nAccepted: 26 April 2024
\r\nPublished online: 1 October, TAPS 2024, 9(4), 50-56
\r\nhttps:\/\/doi.org\/10.29060\/TAPS.2024-9-4\/SC3194<\/a><\/p>\r\n

Craig S. Webster1<\/sup>, Jack Forsythe2<\/sup>, Antonia Verstappen1<\/sup>, Phillippa Poole3<\/sup>, Tim Wilkinson4<\/sup> & Marcus A. Henning1<\/sup><\/span><\/p>\r\n

1<\/span><\/sup><\/i>Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland, Auckland, New Zealand; 2<\/sup>Auckland District Health Board, Te Whatu Ora, Auckland, New Zealand; 3<\/sup>School of Medicine, University of Auckland, Auckland, New Zealand; 4<\/sup>Education Unit, University of Otago, Christchurch, New Zealand<\/span><\/i><\/p>\r\n

Abstract <\/span><\/b><\/p>\r\n

Introduction:<\/span><\/b> A valid, longitudinal approach is critical for service planning in healthcare and to understand career choice in medical graduates. <\/span><\/p>\r\n

Methods:<\/span><\/b> We quantitatively analysed self-reported influences underlying career choice in a national cohort of medical graduates over the first five years of their careers. Participants rated career influences on importance across 26 items using a 5-point Likert scale (1=not at all, 5=a great deal).<\/span><\/p>\r\n

Results:<\/span><\/b> We included 659 New Zealand medical graduates (mean 25.4 years old, 376 F, 283 M) from the University of Auckland and the University of Otago, graduating in 2012 and 2013 (85% response rate). Responses were linked longitudinally over their post-graduate years 1, 3 and 5, and underwent principal component analyses. At graduation the factor rated as the most important in career choice had a mean (SD) item score of 3.9 (0.7) and comprised: Medical School Experiences; Specialty Experience; Mentors; and Self-Appraisal \u2013 consistent with graduates securing initial employment. Factors which explained the most variance in career choice over the five years after graduation indicated that the costs of medical school and further training were consistently rated as the least important in career choices, while flexibility in working hours were consistently rated as the most important. Factors remained relatively stable over time, showing variation in scores of only a median of 0.5 Likert points, indicating further opportunities for career choice research.<\/span><\/p>\r\n

Conclusion:<\/span><\/b> Our results regarding costs of medical training are reassuring, and suggest that greater flexibility in working hours may attract graduates to underserved specialties.<\/span><\/p>\r\n

Keywords<\/span><\/b>:<\/span><\/b>\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 <\/span>Medical Education, Career Choice, Career Influences, Cost, Debt, Measurement, Medical Graduates, National Longitudinal Study, Working Hours, Work Culture<\/span><\/i><\/span><\/b><\/p>\r\n

<\/span>I. INTRODUCTION<\/span><\/strong><\/p>\r\n

A common strategic aim of medical schools throughout the world is to supply the range of graduates who will best meet the healthcare needs of their communities (Gorman, 2018). However, fulfilling this aim is far from straight-forward, with perhaps the most critical difficulty involving understanding the influences that underlie career choice in medical graduates and how these vary over time.<\/span><\/p>\r\n

The financial burden of completing medical school and further training has been one of the most widely studied influences underlying career choice, with suggestions that rising costs may encourage graduates to pursue specialties perceived to be more highly paid, often in cities, thus undersupplying primary healthcare and rural locations. However, in New Zealand medical graduates are otherwise free to choose their preferred career path and choices may be influenced by many things other than training costs and debt, including personal interest, employment conditions, specialty availability and lifestyle preferences (Webster et al., 2020; Webster et al., 2017).<\/span><\/p>\r\n

Therefore, in the following, we analyse the self-reported influences underlying career choice in a national cohort of medical school graduates during the first five years of their careers using quantitative data drawn from the existing longitudinal Medical Schools Outcomes Database (MSOD).<\/span><\/p>\r\n

<\/span>II. METHODS<\/span><\/strong><\/p>\r\n

The MSOD project is a bi-national longitudinal questionnaire study that aims to improve healthcare delivery in Australia and New Zealand (Poole et al., 2019). At graduation and in postgraduate years (PGY), graduates are asked to specify their preferred area(s) of medicine, and complete a schedule of influencing items, indicating the degree to which each was important in their choice, using a 5-point Likert scale with anchors of 1 (not at all) to 5 (a great deal) \u2013 see Supplementary Table 1 for full question set.<\/span><\/p>\r\n

<\/span><\/i>A. Data Analysis<\/span><\/i><\/p>\r\n

We conducted a series of principal component analyses (SPSS v27, IBM Corporation, New York) of the responses to the 26 influencing item questions at each time point to identify factors within responses, and describe them over time.<\/span><\/p>\r\n

<\/span>III. RESULTS<\/span><\/strong><\/p>\r\n

Data from a national cohort of 659 New Zealand medical school graduates who had graduated from the University of Auckland and the University of Otago in 2012 and 2013 were included. The response rate for completed questionnaires in the Exit cohort was 85% \u2013 representing a sampling margin of error of only 1% at the 95% level of confidence. The mean (SD) age of participants in the cohort was 25.4 (2.7) years, with a higher proportion of female graduates (376 F vs 283 M). Over the next five years, this Exit cohort self-reported on the same set of influences underlying career choice at PGY1, PGY3 and PGY5 \u2013 maintaining a response rate between 53% and 56%, and a sampling margin of error of 3%.<\/span><\/p>\r\n

We used conventional settings during analysis, comprising varimax rotation and suppression of loadings below 0.3. The Kaiser-Meyer-Olkin measure of sampling adequacy across time points demonstrated a median (range) of 0.77 (0.75 to 0.82), indicating distinct and reliable factors at each time point. In addition, Bartlett\u2019s test of sphericity was highly significant at each time point, (2338<<\/span>c<\/span>2<\/span><\/sup><3498, p<0.0001), demonstrating correlation with little redundancy in items (Kaiser, 1974).<\/span><\/p>\r\n

\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
\r\n

Influencing items*<\/b><\/p>\r\n<\/td>\r\n

\r\n

Factor numbers and item loadings<\/b><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

A: Exit (yrs 2012 and 2013)<\/b><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

1<\/i><\/p>\r\n<\/td>\r\n

\r\n

2<\/i><\/p>\r\n<\/td>\r\n

\r\n

3<\/i><\/p>\r\n<\/td>\r\n

\r\n

4<\/i><\/p>\r\n<\/td>\r\n

\r\n

5<\/i><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Voc. Training<\/p>\r\n<\/td>\r\n

\r\n

0.855<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Costs Med. School<\/p>\r\n<\/td>\r\n

\r\n

0.832<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Insurance Risk<\/p>\r\n<\/td>\r\n

\r\n

0.675<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Parents\/Relatives<\/p>\r\n<\/td>\r\n

\r\n

0.536<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Prestige<\/p>\r\n<\/td>\r\n

\r\n

0.528<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Training Yrs<\/p>\r\n<\/td>\r\n

\r\n

0.508<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Financial Prospects<\/p>\r\n<\/td>\r\n

\r\n

0.463<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Research\/Teaching<\/p>\r\n<\/td>\r\n

\r\n

0.442<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Location<\/p>\r\n<\/td>\r\n

\r\n

0.440<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Flexible Hrs<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.862<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Working Hrs<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.838<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Domestic Circum.<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.633<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Work Culture<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.416<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Career Prospects<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.725<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Procedural Work<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n\r\n

0.698<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Job Security<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.555<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Voc. Training Avail.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

<\/td>\r\n\r\n

0.409<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/tr>\r\n
\r\n

Med. School Exp.<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.836<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/tr>\r\n
\r\n

Specialty Exp.<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.787<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/tr>\r\n
\r\n

Mentors<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.752<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/tr>\r\n
\r\n

Self-Appraisal<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.388<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/tr>\r\n
\r\n

Typical Patients<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.643<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Helping People<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.642<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Intel. Content<\/p>\r\n<\/td>\r\n

<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n\r\n

0.532<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Variance explained, %<\/p>\r\n<\/td>\r\n

\r\n

15.8<\/p>\r\n<\/td>\r\n

\r\n

11.1<\/p>\r\n<\/td>\r\n

\r\n

9.5<\/p>\r\n<\/td>\r\n

\r\n

9.3<\/p>\r\n<\/td>\r\n

\r\n

7.3<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Factor score, mean (SD)**<\/p>\r\n<\/td>\r\n

\r\n

2.3 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

3.6 (0.8)<\/p>\r\n<\/td>\r\n

\r\n

3.3 (0.9)<\/p>\r\n<\/td>\r\n

\r\n

3.9 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

3.8 (0.7)<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

B: PGY1 (yrs 2013 and 2014)<\/b><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

\u00a0<\/i><\/p>\r\n<\/td>\r\n

\r\n

2<\/i><\/p>\r\n<\/td>\r\n

\r\n

1<\/i><\/p>\r\n<\/td>\r\n

\r\n

4<\/i><\/p>\r\n<\/td>\r\n

\r\n

3<\/i><\/p>\r\n<\/td>\r\n

\r\n

5<\/i><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Working Hrs<\/p>\r\n<\/td>\r\n

\r\n

0.847<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Flexible Hrs<\/p>\r\n<\/td>\r\n

\r\n

0.831<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Domestic Circum.<\/p>\r\n<\/td>\r\n

\r\n

0.673<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Training Yrs<\/p>\r\n<\/td>\r\n

\r\n

0.538<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Voc. Training Avail.<\/p>\r\n<\/td>\r\n

\r\n

0.494<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Location<\/p>\r\n<\/td>\r\n

\r\n

0.411<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Job Security<\/p>\r\n<\/td>\r\n

\r\n

0.391<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Voc. Training<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.836<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Med. School<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.765<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Insurance Risk<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.673<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Research\/Teaching<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.547<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Specialty Exp.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.791<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Med. School Exp.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.777<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Training Exp.\/Doc.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.590<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Helping People<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.393<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Post-Grad. Work<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.302<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Prestige<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.730<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Financial Prospects<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.712<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Procedural Work<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.576<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

Intel. Content<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.604<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Career Prospects<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.566<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Work Culture<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.451<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Typical Patients<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.395<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Self-Appraisal<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.368<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Variance explained, %<\/p>\r\n<\/td>\r\n

\r\n

12.4<\/p>\r\n<\/td>\r\n

\r\n

11.4<\/p>\r\n<\/td>\r\n

\r\n

9.2<\/p>\r\n<\/td>\r\n

\r\n

8.8<\/p>\r\n<\/td>\r\n

\r\n

8.3<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Factor score, mean (SD)**<\/p>\r\n<\/td>\r\n

\r\n

3.1 (0.8)<\/p>\r\n<\/td>\r\n

\r\n

1.8 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

3.6 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

2.7 (0.9)<\/p>\r\n<\/td>\r\n

\r\n

3.6 (0.6)<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

C: PGY3 (yrs 2015 and 2016)<\/b><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

\u00a0<\/i><\/p>\r\n<\/td>\r\n

\r\n

1<\/i><\/p>\r\n<\/td>\r\n

\r\n

2<\/i><\/p>\r\n<\/td>\r\n

\r\n

5<\/i><\/p>\r\n<\/td>\r\n

\r\n

4<\/i><\/p>\r\n<\/td>\r\n

\r\n

3<\/i><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Voc. Training<\/p>\r\n<\/td>\r\n

\r\n

0.806<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Med. School<\/p>\r\n<\/td>\r\n

\r\n

0.803<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Financial Prospects<\/p>\r\n<\/td>\r\n

\r\n

0.635<\/p>\r\n<\/td>\r\n

\r\n

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Prestige<\/p>\r\n<\/td>\r\n

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0.621<\/p>\r\n<\/td>\r\n

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\r\n

Insurance Risk<\/p>\r\n<\/td>\r\n

\r\n

0.596<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Career Prospects<\/p>\r\n<\/td>\r\n

\r\n

0.544<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Job Security<\/p>\r\n<\/td>\r\n

\r\n

0.511<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Research\/Teaching<\/p>\r\n<\/td>\r\n

\r\n

0.367<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Flexible Hrs<\/p>\r\n<\/td>\r\n

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\r\n

0.849<\/p>\r\n<\/td>\r\n

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\r\n

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\r\n

Working Hrs<\/p>\r\n<\/td>\r\n

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\r\n

0.827<\/p>\r\n<\/td>\r\n

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\r\n

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\r\n

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\r\n

Domestic Circum.<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.732<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Voc. Training Avail.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.399<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Intel. Content<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.669<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Training Exp.\/Doc.<\/p>\r\n<\/td>\r\n

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\r\n

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\r\n

0.581<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Work Culture<\/p>\r\n<\/td>\r\n

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\r\n

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\r\n

0.576<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Post-Grad. Work<\/p>\r\n<\/td>\r\n

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\r\n

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\r\n

0.558<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Typical Patients<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.540<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Self-Appraisal<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.451<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Procedural Work<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.374<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Specialty Exp.<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

0.911<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Med. School Exp.<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

0.892<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

Training Yrs<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

0.521<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Location<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.476<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Helping People<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

0.464<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Variance explained, %<\/p>\r\n<\/td>\r\n

\r\n

13.7<\/p>\r\n<\/td>\r\n

\r\n

13.1<\/p>\r\n<\/td>\r\n

\r\n

11.5<\/p>\r\n<\/td>\r\n

\r\n

7.5<\/p>\r\n<\/td>\r\n

\r\n

5.4<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Factor score, mean (SD)**<\/p>\r\n<\/td>\r\n

\r\n

2.3 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

3.4 (0.9)<\/p>\r\n<\/td>\r\n

\r\n

3.8 (0.6)<\/p>\r\n<\/td>\r\n

\r\n

3.1 (1.2)<\/p>\r\n<\/td>\r\n

\r\n

3.1 (0.7)<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

D: PGY5 (yrs 2017 and 2018)<\/b><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

\u00a0<\/i><\/p>\r\n<\/td>\r\n

\r\n

2<\/i><\/p>\r\n<\/td>\r\n

\r\n

3<\/i><\/p>\r\n<\/td>\r\n

\r\n

1<\/i><\/p>\r\n<\/td>\r\n

\r\n

5<\/i><\/p>\r\n<\/td>\r\n

\r\n

4<\/i><\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Flexible Hrs<\/p>\r\n<\/td>\r\n

\r\n

0.822<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Working Hrs<\/p>\r\n<\/td>\r\n

\r\n

0.791<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Domestic Circum.<\/p>\r\n<\/td>\r\n

\r\n

0.687<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Location<\/p>\r\n<\/td>\r\n

\r\n

0.454<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

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\r\n

Career Prospects<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.790<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Prestige<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.633<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Job Security<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.613<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Financial Prospects<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.604<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Procedural Work<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.521<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

Research\/Teaching<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.508<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

Voc. Training Avail.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.355<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Costs Voc. Training<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.859<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Costs Med. School<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.831<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Insurance Risk<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.604<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Training Yrs<\/p>\r\n<\/td>\r\n

\r\n

 <\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.563<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Parents\/Relatives<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

0.350<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

Typical Patients<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

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\r\n

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\r\n

0.600<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

Helping People<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

<\/p>\r\n<\/td>\r\n

\r\n

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\r\n

0.585<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Intel. Content<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.562<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Self-Appraisal<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.507<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Work Culture<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.464<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Training Exp.\/Doc.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.432<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Post-Grad. Work<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.429<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Specialty Exp.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.896<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Med. School Exp.<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

<\/p>\r\n<\/td>\r\n

\r\n

0.881<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Variance explained, %<\/p>\r\n<\/td>\r\n

\r\n

12.1<\/p>\r\n<\/td>\r\n

\r\n

11.3<\/p>\r\n<\/td>\r\n

\r\n

11.1<\/p>\r\n<\/td>\r\n

\r\n

8.3<\/p>\r\n<\/td>\r\n

\r\n

7.8<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

Factor score, mean (SD)**<\/p>\r\n<\/td>\r\n

\r\n

3.4 (0.9)<\/p>\r\n<\/td>\r\n

\r\n

2.8 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

1.8 (0.7)<\/p>\r\n<\/td>\r\n

\r\n

3.9 (0.6)<\/p>\r\n<\/td>\r\n

\r\n

2.9 (1.2)<\/p>\r\n<\/td>\r\n<\/tr>\r\n

\r\n

*See Supplementary Table 1 for full item descriptors<\/p>\r\n

**Mean (SD) of 5-point Likert scores making up factor<\/p>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n

Table 1. Principal component analyses of influences underlying career choice in medical graduates to five years after graduation<\/span><\/p>\r\n

Table 1 shows the results of the principal component analyses, demonstrating well-formed factors at each time point. Factors are reported in the descending order of their variance explained (VE), and with a factor score, being the mean (SD) of the Likert question scores making up the factor. The VE is a measure of the amount of variability in the participants\u2019 responses that can be explained by the factor, hence higher levels of VE indicate agreement by a larger number of graduates. The factor score indicates the degree to which graduates consider the factor to be important or unimportant in their choices. <\/span>\u00a0<\/span><\/p>\r\n

For example, at Exit from medical school (Table 1A), Factor 1 accounts for the largest VE (15.8%), comprising the 9 question items that are, on average, the least influential in determining career choice for graduates, with a factor score of 2.3 (out of 5). These least influential items are: Costs of Vocational Training; Costs of Medical School; Insurance Risk; Parents\/Relatives; Prestige; Training Years; Financial Prospects; Research\/Teaching; and Location. By contrast, Factor 4 at Exit, with the highest factor score of 3.9 and explaining 9.3% of the variance, contains the 4 items rated as the most influential by graduates in determining career choice. These most influential items are: Medical School Experiences; Specialty Experience; Mentors; and Self-Appraisal. These results are consistent with new graduates making the most of their abilities and opportunities to secure their first healthcare role. Other factors at Exit fall within these two extremes.<\/span>\u00a0<\/span><\/p>\r\n

It is worth noting that the item Parent\/Relatives fails to load over the 0.3 threshold on any factor at PGY1 or PGY3 (hence does not appear). Some change in factor structures over time do occur, reflecting changing priorities for graduates. For example, Factor 2 at Exit has a relatively high factor score of 3.6 (VE=11.1%) indicating that the items Flexible Hours, Working Hours, Domestic Circumstances, and Work Culture are important for new graduates. However, by PGY1 (Table 1B) this factor then picks up the items of Training Years, Vocational Training Availability, Location and Job Security, and becomes important to a greater number of graduates by becoming the factor with the largest variance explained (VE=12.4%). This result suggests that graduates are adjusting to their new working lives and are planning for their futures in terms of further training.<\/span>\u00a0<\/span><\/p>\r\n

Factor 1 and Factor 2 consistently demonstrate high levels of variance explained and contain a common core of three influencing items. Factor 1, with a median (range) score of 2.1 (1.8 to 2.3) across all time points, continues to describe influences on career choice rated as the least important for medical graduates, and consistently contains the items Costs of Vocational Training, Costs of Medical School, and Insurance Risk. By contrast, Factor 2 is consistently rated as relatively important, with a median (range) score of 3.4 (3.1 to 3.6) across time points, and consistently contains the items Flexible Hours, Working Hours, and Domestic Circumstances. <\/span>\u00a0<\/span><\/p>\r\n

Our results demonstrate the existence of well-formed factors in the MSOD data at each time point. Despite some change in factor structure over time, the scores for each factor remain relatively stable, with a median (range) variation in scores of only 0.5 (0.3 to 1.0) Likert points. Table 1 contains results which allow substantial scope for hypothesis formation and future research, including targeted work to better understand the decision points in the critical first five years of a graduate\u2019s career.<\/span>\u00a0<\/span><\/p>\r\n

<\/span>IV. DISCUSSION<\/span><\/strong><\/p>\r\n

Better understanding the influences underlying career choice in medical graduates is a strategically important and practical concern when aiming to match graduate production with professional and community needs. This study is the among the first to conduct a quantitative analysis of the self-reported influences underlying medical graduate career choice in a prospective, national cohort of the same graduates over the critical first five years of their careers. <\/span>\u00a0<\/span><\/p>\r\n

The financial burden of completing medical school and vocational training is one of the most widely studied influences in career choice for medical graduates. It is therefore reassuring that our findings demonstrate that these costs are among the least influential considerations at all time points in the five years after graduation for our cohort. <\/span>\u00a0<\/span><\/p>\r\n

Factor 2 in the present study consistently contains the items Flexible Hours, Working Hours and Domestic Circumstances, and is rated as important over the first five years of graduates\u2019 careers. Flexibility around working hours and a desire to practice part-time has traditionally been thought of as largely important for female medical graduates (Heiliger & Hingstman, 2000). However, this is no longer the case, with many male graduates in recent decades also desiring more lifestyle-friendly working arrangements allowing the flexibility to spend more time with family (Heiliger & Hingstman, 2000). Taken together with the evidence that the costs of medical school and further training are the least influential in career choice, our results therefore strongly suggest that the ability to offer greater flexibility in working hours is likely to be useful in recruiting medical graduates to underserved specialties.<\/span>\u00a0<\/span><\/p>\r\n

It is a practical and pressing necessity that healthcare workforce planning is guided by the best available evidence. A strength of the current study is the ability to link the same participants longitudinally, thus eliminating an important source of bias. Women in the current study made up 57% of medical graduate respondents, reflecting the fact that in recent years in New Zealand and Australia female graduates have outnumbered male graduates. A further strength is the high response rates, yielding a sampling margin of error of only 3% or less at all time points, which compares favourably with many questionnaire studies of medical graduates.<\/span>\u00a0<\/span><\/p>\r\n

<\/span>V. CONCLUSION<\/span><\/strong><\/p>\r\n

Despite widespread concern over rising debt levels and the cost of medical school, our results are reassuring in that the costs of medical school and vocational training were consistently rated as the least important influences in career choice. Our results also suggest that offering greater flexibility around working hours may assist in attracting medical graduates to underserved specialties. Our description of well-formed factors in the influences underlying career choice in the national MSOD questionnaire data provides a useful basis for further research to better understand key decision points in the critical first five years of graduates\u2019 careers.<\/span>\u00a0<\/span><\/p>\r\n

Notes on Contributors<\/span><\/strong><\/p>\r\n

Craig Webster was involved in the conceptualisation of this paper, data analysis, writing and revision. <\/span><\/p>\r\n

Jack Forsythe was involved in the conceptualisation of this paper, data analysis, writing and revision. <\/span><\/p>\r\n

Antonia Verstappen was involved in accessing data for this paper, writing and revision.<\/span><\/p>\r\n

Phillippa Poole was involved in the writing and revision of this paper.<\/span><\/p>\r\n

Tim Wilkinson was involved in the writing and revision of this paper.<\/span><\/p>\r\n

Marcus Henning was involved in the writing and revision of this paper.<\/span>\u00a0<\/span><\/p>\r\n

Ethical Approval<\/span><\/strong><\/p>\r\n

This study was carried out in accordance with all regulations of the host organisations and with the approvals of the Human Participants Ethics Committees of the University of Auckland (approval numbers 022388 and 018456) and the University of Otago (approval number 07-155), New Zealand. All participants gave written informed consent to participate in the study, including for anonymised aggregated data to be published.<\/span>\u00a0<\/span><\/p>\r\n

Data Availability<\/span><\/strong><\/p>\r\n

The ethics approval for the longitudinal MSOD project currently does not permit the sharing of non-aggregated data. However, this restriction is under review and so non-aggregated data may be available from the corresponding author in the near future.<\/span><\/p>\r\n

Acknowledgement<\/span><\/strong><\/p>\r\n

We thank the Health Career Pathways Project, Faculty of Medical and Health Sciences, University of Auckland, and the Medical Schools Outcomes Database Longitudinal Tracking Project at the University of Auckland and the University of Otago for assistance and data access.<\/span>\u00a0<\/span><\/p>\r\n

Funding<\/span><\/strong><\/p>\r\n

JF received a summer studentship stipend from the Faculty of Medical and Health Sciences, University of Auckland, New Zealand in support of this research. The Medical Schools Outcomes Database Longitudinal Tracking Project is supported by a grant from Health Workforce New Zealand.<\/span>\u00a0<\/span><\/p>\r\n

Declaration of Interest<\/span><\/strong><\/p>\r\n

All authors have no potential conflicts of interest.<\/span>\u00a0<\/span><\/p>\r\n

References<\/span><\/strong><\/p>\r\n

Gorman, D. (2018). Matching the production of doctors with national needs. Medical Education, 52<\/i>(1), 103-113. <\/span>https:\/\/doi.org\/10.1111\/medu.13369<\/span><\/a><\/span><\/span><\/p>\r\n

Heiliger, P. J., & Hingstman, L. (2000). Career preferences and the work-family balance in medicine: Gender differences among medical specialists. Social Science and Medicine, 50<\/i>(9), 1235-1246. <\/span>https:\/\/doi.org\/10.1016\/s0277-9536(99)00363-9<\/span><\/a><\/span> <\/span><\/p>\r\n

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39<\/i>, 31\u201336. <\/span>https:\/\/doi.org\/10.1007\/BF02291575<\/a><\/span><\/span><\/p>\r\n

Poole, P., Wilkinson, T. J., Bagg, W., Freegard, J., Hyland, F., Jo, C. E., Kool, B., Roberts, E., Rudland, J., Smith, B., & Verstappen, A. (2019). Developing New Zealand’s medical workforce: Realising the potential of longitudinal career tracking. New Zealand Medical Journal, 132<\/i><\/span>(1495),<\/span> 65-73. <\/span><\/p>\r\n

Webster, C. S., Ling, C., Barrow, M., Poole, P., & Henning, M. (2017). A cross-disciplinary assessment of student loans debt, financial support for study and career preferences upon graduation. New Zealand Medical Journal, 130<\/i><\/span>(1459)<\/span>, 43-53.<\/span><\/i><\/p>\r\n

Webster, C. S., McKillop, A., Bennett, W., & Bagg, W. A. (2020). A qualitative and semiquantitative exploration of the experience of a rural and regional clinical placement programme. Medical Science Educator, 30<\/i>(2), 783-789. <\/span>https:\/\/doi.org\/10.1007\/s40670-020-00949-6<\/span><\/a><\/span> <\/span><\/p>\r\n

*Craig Webster
\r\nCentre for Medical and Health Sciences Education,
\r\nSchool of Medicine, University of Auckland,
\r\nPrivate Bag 92-019
\r\nAuckland 1142, New Zealand
\r\n+649 923 6525
\r\nEmail: c.webster@auckland.ac.nz
\r\n<\/span><\/p>\r\n<\/div>","protected":false},"featured_media":0,"parent":0,"menu_order":7,"template":"","issues_category":[17],"archive_category":[],"issue_type":[25],"volume_category":[61889],"class_list":["post-72587","issues","type-issues","status-publish","hentry","issues_category-short-communications","issue_type-past-issue","volume_category-volume-9-number-4-october-2024"],"acf":[],"yoast_head":"\nCareer choice in medical graduates \u2013 A national, quantitative analysis over five years - The Asia Pacific Scholar<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Career choice in medical graduates \u2013 A national, quantitative analysis over five years - The Asia Pacific Scholar\" \/>\n<meta property=\"og:description\" content=\"Submitted: 19 December 2023 Accepted: 26 April 2024 Published online: 1 October, TAPS 2024, 9(4), 50-56 https:\/\/doi.org\/10.29060\/TAPS.2024-9-4\/SC3194 Craig S. Webster1, Jack Forsythe2, Antonia Verstappen1, Phillippa Poole3, Tim Wilkinson4 & Marcus A. Henning1 1Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland, Auckland, New Zealand; 2Auckland District Health Board, Te Whatu Ora, […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/\" \/>\n<meta property=\"og:site_name\" content=\"The Asia Pacific Scholar\" \/>\n<meta property=\"article:modified_time\" content=\"2025-01-07T00:26:31+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"13 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/\",\"url\":\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/\",\"name\":\"Career choice in medical graduates \u2013 A national, quantitative analysis over five years - The Asia Pacific Scholar\",\"isPartOf\":{\"@id\":\"https:\/\/medicine.nus.edu.sg\/taps\/#website\"},\"datePublished\":\"2024-09-18T00:43:55+00:00\",\"dateModified\":\"2025-01-07T00:26:31+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/medicine.nus.edu.sg\/taps\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Career choice in medical graduates \u2013 A national, quantitative analysis over five years\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/medicine.nus.edu.sg\/taps\/#website\",\"url\":\"https:\/\/medicine.nus.edu.sg\/taps\/\",\"name\":\"The Asia Pacific Scholar\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/medicine.nus.edu.sg\/taps\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Career choice in medical graduates \u2013 A national, quantitative analysis over five years - The Asia Pacific Scholar","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/medicine.nus.edu.sg\/taps\/issues\/career-choice-in-medical-graduates-a-national-quantitative-analysis-over-five-years\/","og_locale":"en_US","og_type":"article","og_title":"Career choice in medical graduates \u2013 A national, quantitative analysis over five years - The Asia Pacific Scholar","og_description":"Submitted: 19 December 2023 Accepted: 26 April 2024 Published online: 1 October, TAPS 2024, 9(4), 50-56 https:\/\/doi.org\/10.29060\/TAPS.2024-9-4\/SC3194 Craig S. Webster1, Jack Forsythe2, Antonia Verstappen1, Phillippa Poole3, Tim Wilkinson4 & Marcus A. 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