6609 Penny-wise and pound-foolish? Car park tax & morale
Bibliographic record
Abstract
Objectives Background As per the 2023 National Trainees survey, over two-thirds of trainees said they always or often feel worn out at the end of the working day. Objective We tried to understand the factors that may influence the morale of trainees in the Paediatric department. Methods An anonymous survey was designed with input from key stakeholders of our organization for the current batch of trainees (March-August’2023) working in the Paediatric department. Results Respondents Profile Eighty percent (17/21) of trainees responded to the survey. Eighty percent of respondents were in acute and the rest were in community settings. Induction issues One-fifth of respondents reported that their login details were inactive when they commenced their work. Rota issues A quarter of the respondents said that they received rota less than two weeks prior to commencing their work causing some practical difficulties. Parking issues Fifty percent of the respondents were paying for car parking using salary sacrifice (many trainees did not have this option, as they were not directly employed by the Trust but by the deanery). Supervision About forty percent of respondents reported that they feel supported to undertake SLEs during social hours whilst at work. Well-being Only one-fifth of the trainees said they have an adequate resting facility on a night shift. Forty-five percent said they were able to take breaks as per EWTD. Suggestions for improvement Some of the suggestions are introducing an electronic format for Rota and leave applications, improving rest facilities during long/night shifts, a free car park and more support/time to undertake supervised learning events during working hours. Providing more exposure to clinics, management meetings & streamlining handovers Conclusion NHS is experiencing an unprecedented risk of burnout among doctors and other staff. Authors feel that organisations need to focus on the bigger picture. A few changes like introducing free car parks, comfortable places to rest while on long/night shifts, and providing snacks and drinks during break times can make a massive difference to the morale of our workforce and ultimately positively impact patient care. References https://www.gmc-uk.org/-/media/documents/national-training-survey-2023-initial-findings-report_pdf-101939815.pdf https://www.hee.nhs.uk/sites/default/files/documents/Junior%20Doctors’%20Morale%20-%20understanding%20best%20practice%20working%20environments_0.pdf https://www.bma.org.uk/news-and-opinion/penalty-charge
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.347 | 0.084 |
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".