New Zealand's Psychiatrist Workforce: Profile, Recruitment and Retention
Bibliographic record
Abstract
OBJECTIVE: New Zealand is suspected of sharing other countries' difficulties of having inadequate numbers of practising psychiatrists and attracting psychiatrists to work outside its main urban centres, but there is no contemporary data on the socio-demographic and professional practice profile of its psychiatrists. This paper highlights some interesting trends about New Zealand's psychiatric workforce. METHOD: A postal questionnaire was sent to all actively practising vocationally registered psychiatrists with a New Zealand mailing address requesting information about basic demographic data, professional training experiences, current professional status, practise intentions, why they chose to work where they do and what factors might influence them to leave for another region of New Zealand or overseas. RESULTS: Of the 277 doctors on the vocational register for psychiatry, 159 responded, giving a response rate of 59.8%. Most psychiatrists were male (n = 102; 64.2%), European (n = 144; 90.6%), aged between 41 and 60 (69.2%), born overseas (n = 90; 56%), had English as their primary language (n = 142; 89.3%) and were in a long-term relationship with dependent children (n = 99; 62.3%). Nearly all (n = 149; 95%) did their psychiatry training in a metropolitan area and most (n = 108; 67.9%) held the Fellowship of the Royal Australian and New Zealand College of Psychiatry (FRANZCP). Most worked in a metropolitan area (n = 136; 85.5%) and either wholly or partly in the public sector (n = 145; 93%). Nearly one-quarter expected to retire over the next decade. Professional factors were rated more important as a reason for staying by metropolitan psychiatrists compared with their non-metropolitan counterparts (p < 0.001). Psychiatrists who did not have an FRANZCP (57%vs. 27%, p = 0.05), those who had spent more than 50% of their professional life in New Zealand (86%vs. 74%, p = 0.02) or those who had obtained their primary medical degree outside New Zealand were more likely to be in non-metropolitan areas (81%vs. 49%, p = 0.04). Metropolitan psychiatrists rated personal and social reasons more highly than non-metropolitan psychiatrists did for factors which might induce them to leave for another area, whereas professional development was ranked lower. CONCLUSIONS: This is the first contemporary study of New Zealand's psychiatric workforce and it highlights some interesting trends and has significant implications for those concerned with the recruitment and retention of psychiatrists. Further investigation is suggested, as a more complete picture of New Zealand's specialist psychiatric workforce would be gained by including psychiatrists who are not vocationally registered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".