Improving the experience of care for adults using NHS mental health services: summary of NICE guidance
Bibliographic record
Abstract
Excellent service user experience is part of high quality healthcare, as well as a right and a necessity for all service users in the NHS.1 2 3 It is especially relevant for people with mental health problems, who often have repeated and/or prolonged contact with services, with nearly a quarter of adults meeting criteria for a diagnosis of mental disorder in England.4 Moreover, mental health problems are associated with considerable stigma in the health service, and users of mental health services, unlike any other health service users, can be detained and treated against their will under the Mental Health Act.5 National surveys of mental health service users show that, although most are satisfied with their care, a substantial minority have a poor experience of care and many report finding it difficult to access services especially during crises.6 Concerns have also been expressed about the quality of inpatient mental health services.7 This article summarises the most recent recommendations from the National Institute for Health and Clinical Excellence (NICE) on service users’ experience of adult mental health services; these recommendations come from the first NICE guidance for which a development group was chaired by a service user (jointly with a healthcare professional).8 NICE recommendations are based on systematic reviews of the best available evidence. When minimal evidence is available, recommendations are based on the Guideline Development Group’s experience and opinion of what constitutes good practice. Evidence levels for the recommendations are given in italic in square brackets. ### Relationships, communication, and information provision Work in partnership with people using mental health services and their families or carers, ensuring that you:
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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 | 0.014 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".