Canadian Consensus Conference on Psychological and Non-Pharmacological Interventions for Dementia
Bibliographic record
Abstract
Abstract Psychological and non-pharmacological interventions that could have a positive effect on outcomes important to persons living with dementia are essential to identify given the the limited efficacy of dementia medications and the diverse needs of persons living. In 2019, for the first time the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD) created a working group to develop recommendations related to a broad range of psychosocial and non-pharmacological interventions exist, typically aimed at improving cognition, symptoms, or well-being, as well as improving caregiver well-being and coping. The recommendations, primarily intended for primary care physicians, may also allow clinicians, organizations, and communities and help to better meet the needs of people living with dementia and their caregivers. A group of 11 experts, including persons living with dementia and informal caregivers, as well as clinicians and researchers from various organizations both nationally and internationally were invited to participate. A rapid review of meta-analyses and literature reviews on psychological and non-pharmacological interventions was conducted. The synthesized results were submitted for a consensus building approach using a Delphi method, involving a panel of more than 50 Canadian participants. Recommendations with a positive vote of 80% or more were considered to have reached consensus. All proposed recommendations reached consensus using the Delphi process. Details of the recommendations are presented. Five recommendations are made: group or individual physical exercise, group cognitive stimulation therapy, psychoeducational interventions for caregivers, dementia friendly organizations/communities, and case management.
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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 | 0.164 | 0.150 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.011 | 0.007 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 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".