Interventions that support the creation of dementia friendly environments in health care: protocol for a realist review
Bibliographic record
Abstract
BACKGROUND: Improving health-care outcomes for people living with dementia when they are admitted to hospital is a policy priority. Dementia friendly interventions in health care promote inclusion of patients and carers in decision-making and adapt practices and environments to be appropriate to the needs of people with cognitive impairment. While there has been a wealth of activity, the number of studies evaluating interventions is limited, and the majority focuses on reporting staff and organisational outcomes. By focusing on patient and carer outcomes, this review will aim to develop an explanatory account of how and in what circumstances dementia friendly environments in health care work for people living with dementia and with what outcomes. METHOD/DESIGN: Realist review is a theory-driven method which seeks to produce explanatory accounts of why interventions work and specifically, what combination of components are most effective in producing particular outcomes. Stakeholder interviews, a review of the literature, and an expert steering group workshop will be used to explore the assumptions behind interventions that are designed to enhance health care for people living with dementia to understand the underlying programme theories. The review will focus on studies that report patient and carer outcomes, including involvement in decision-making, length of stay and referral to long-term care, adverse incidents (e.g. patient distress, delirium falls, nutrition and hydration and infection), antipsychotic medication prescribing, evidence of patient-centred care and patient and carer satisfaction. DISCUSSION: The review will provide an explanatory model about how dementia friendly interventions in hospital settings improve outcomes for people living with dementia and their family carers and in what circumstances for future testing and evaluation of future dementia friendly initiatives. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015017562.
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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 | 0.071 | 0.084 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.097 | 0.017 |
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".