Survey of National Health Service (NHS) orthodontic practitioners in Wales, UK. Part 1: working patterns 2021–2022
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To ascertain the working patterns of the NHS orthodontic workforce in Wales and any possible future changes. DESIGN: Descriptive cross-sectional survey. PARTICIPANTS: NHS orthodontic practitioners in Wales. METHODS: An anonymised email distributed an electronic two-part survey of the Welsh NHS orthodontic workforce. The survey consisted of three sections: (1) demographic information; (2) respondents' working pattern (part 1); and (3) perceptions of professional satisfaction (part 2). RESULTS: Part 1 of the survey yielded a 70.5% response rate (n = 79); 65.8% of the respondents were women. Of the respondents, 45.6% (n = 36) worked full time (F/T), 39.2% (n = 31) worked less than F/T and 15.2% (n = 12) worked more than F/T. Of the male respondents, 81.5% (n = 22) worked 10 sessions or more compared to 50% (n = 26) of women. The respondents undertook 508.5 orthodontic clinical sessions per week within Wales; of these sessions, 87.6% (n = 445.5) delivered NHS orthodontic care. Of the respondents, 8.4% (n = 7) were planning to increase their orthodontic clinical time within the next 2 years, 24.1% (n = 19) were planning to decrease it and 20.3% (n = 16) were unsure. One-quarter of respondents indicated that they were planning to stop clinical orthodontic activity within the next 5 years, including 53.3% (n = 8) of DwSIs, 37% (n = 10) of primary care specialists and 13.3% (n = 2) of consultants. The pandemic was an influencing factor for 80% of these clinicians. CONCLUSIONS: Part 1 of the survey suggested that the majority of the orthodontic workforce was female, were working full time or more, and spent most sessions delivering NHS care. One-quarter of respondents were planning to cease undertaking orthodontic activity within the next 5 years.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it