An audit of dementia education and training in UK health and social care: a comparison with national benchmark standards
Bibliographic record
Abstract
BACKGROUND: Despite people living with dementia representing a significant proportion of health and social care users, until recently in the United Kingdom (UK) there were no prescribed standards for dementia education and training. This audit sought to review the extent and nature of dementia education and training offered to health and social care staff in the UK against the standards described in the 2015 Dementia Training Standards Framework, which describes the knowledge and skills required of the UK dementia workforce. METHODS: This audit presents national data concerning the design, delivery, target audience, length, level, content, format of training, number of staff trained and frequency of delivery within existing dementia training programmes offered to health and social care staff. The Dementia Training Standards Framework was used as a reference for respondents to describe the subjects and learning outcomes associated with their training. RESULTS: The findings are presented from 614 respondents offering 386 training packages, which indicated variations in the extent and quality of training. Many training packages addressed the subjects of 'person-centred care', 'communication', 'interaction and behaviour in dementia care', and 'dementia awareness'. Few training packages addressed subjects concerning 'pharmacological interventions in dementia care', 'leadership' and 'end of life care'. Fewer than 40% of The Dementia Training Standards Framework learning outcomes targeted to staff with regular contact with people with dementia or in leadership roles were covered by the reported packages. However, for training targeted at increasing dementia awareness more than 70% of the learning outcomes identified in The Dementia Training Standards Framework were addressed. Many training packages are not of sufficient duration to derive impact; although the majority employed delivery methods likely to be effective. CONCLUSIONS: The development of new and existing training and education should take account of subjects that are currently underrepresented and ensure that training reflects the Training Standard Framework and evidence regarding best practice for delivery. Lessons regarding the limitations of training in the UK serve as a useful illustration of the challenge of implementing national dementia training standards; particularly for countries who are developing or have recently implemented national dementia strategies.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".