Interventions for people living with dementia: updates from 2024 Lancet Commission
Bibliographic record
Abstract
Abstract Background The progressive nature of dementia and the complex needs means that people living with dementia require tailored approaches to address their changing care needs over time. These include physical multimorbidity, psychological, behavioural, and cognitive symptoms and possible risks arising from these and helping family caregivers. However, provision of these interventions is highly variable between and within countries, partly due to uncertainty about their efficacy and scarce resources. In the 2024 update of the Lancet Commission we aimed to summarise published evidence about the effect of non‐pharmacological interventions for people with dementia and their carers on cognition, neuropsychiatric symptoms and other person‐centred outcomes. Method We reviewed and summarised evidence according to expert consensus opinion. Result There is moderate‐quality evidence from a Cochrane review of 25 studies for effect of cognitive stimulation therapy on cognition; 1.99 (1.24‐2.74) Mini‐Mental State Examination points higher compared to control groups, and clinically relevant improvements in communication and social interaction. Multicomponent interventions for family carers reduce family carer depression, burden, or stress and are cost‐effective but remote delivery of these interventions was not better than care as usual. A meta‐analysis of 7 studies of tailored activity programmes for people with dementia found a moderate effect on improving quality of life (standardised ES Cohen’s d 0.79, 0.39–1.18; 7 studies, n = 160), decreasing neuropsychiatric symptoms (0.62; 0.40–0.83) and decreasing carer burden (0.68, 0.29–1.07) but there is little evidence on cost‐effectiveness. Exercise interventions were not effective in improving neuropsychiatric symptoms, cognition or functioning. We discuss evidence for other treatments for specific neuropsychiatric symptoms. Conclusion There is developing evidence for benefit of psychological and social interventions on key outcomes including cognition, neuropsychiatric symptoms and quality of life, with sufficient strength of evidence and cost‐effectiveness to justify these being implemented and offered routinely to people with dementia. Interventions generally should be tailored to specific symptoms and individualised to patient preferences and goals. Most interventions have been tested in majority ethnic populations in high income countries: future interventions should be co‐designed with local communities to ensure that they are appropriate for the context, culture, beliefs and practices.
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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 | 0.053 | 0.125 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.027 | 0.009 |
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".