Dental therapy in Western Australia: profile and perceptions of the workforce
Bibliographic record
Abstract
BACKGROUND: In 2002, the Centre for Rural and Remote Oral Health (CRROH) completed a rural oral health workforce survey which indicated that a high number of therapists, although registered, were not working as therapists. The aim of the present study was to develop a profile of the dental therapy workforce and analyse the perceptions of therapists. METHODS: In 2004, a postal questionnaire survey was undertaken amongst all registered dental and school dental therapists for 1999, 2000, 2001, 2002 and 2003. RESULTS: Valid information was obtained from 253 therapists (55 per cent response rate). The therapy workforce are almost exclusively female, have an average age of 40 years, are working in urban areas, obtained their qualification on average 20 years ago, work for the School Dental Service and qualified in Western Australia. More than a quarter no longer worked as therapists. Perceptions regarding the advantages and disadvantages of dental therapy as a career were identified. CONCLUSIONS: When trying to promote dental therapy and school dental therapy as a career, retain therapists and recruit new graduates, the opportunities identified in this survey should be embraced. A clear focus on the issues will be required to facilitate meeting the workforce objectives as outlined in Australia's National Oral Health Plan.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".