Cognitive stimulation therapy as a sustainable intervention for dementia in sub-Saharan Africa: feasibility and clinical efficacy using a stepped-wedge design
Bibliographic record
Abstract
BACKGROUND: Cognitive stimulation therapy (CST) is a psychosocial group-based intervention for dementia shown to improve cognition and quality of life with a similar efficacy to cholinesterase inhibitors. Since CST can be delivered by non-specialist healthcare workers, it has potential for use in low-resource environments, such as sub-Saharan Africa (SSA). We aimed to assess the feasibility and clinical effectiveness of CST in rural Tanzania using a stepped-wedge design. METHODS: Participants and their carers were recruited through a community dementia screening program. Inclusion criteria were DSM-IV diagnosis of dementia of mild/moderate severity following detailed assessment. No participant had a previous diagnosis of dementia and none were taking a cholinesterase inhibitor. Primary outcomes related to the feasibility of conducting CST in this setting. Key clinical outcomes were changes in quality of life and cognition. The assessing team was blind to treatment group membership. RESULTS: Thirty four participants with mild/moderate dementia were allocated to four CST groups. Attendance rates were high (85%) and we were able to complete all 14 sessions for each group within the seven week timeframe. Substantial improvements in cognition, anxiety, and behavioral symptoms were noted following CST, with smaller improvements in quality of life measures. The number needed to treat was two for a four-point cognitive (adapted Alzheimer's Disease Assessment Scale-Cognitive) improvement. CONCLUSIONS: This intervention has the potential to be low-cost, sustainable, and adaptable to other settings across SSA, particularly if it can be delivered by non-specialist health workers.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".