Tele-rehabilitation interventions for individuals living with dementia during the COVID-19 pandemic: Mixed-method systematic review
Bibliographic record
Abstract
Background: Considering COVID-19, individuals living with dementia are more vulnerable, and tele-rehabilitation can be incorporated into dementia care. Objective: To analyse the evidence of the availability and effectiveness of tele-rehabilitation interventions for individuals living with dementia in the community during the COVID-19 pandemic. Methods: A mixed-method systematic review was conducted. Cochrane, ProQuest, PubMed and Google Scholar databases were searched using keywords that include dementia, tele-rehabilitation, and COVID-19. Article quality was assessed using the Mixed Methods Appraisal tool. Results: Thirteen articles were included. Finding suggest, most tele-interventions were being implemented in European and high-income countries. These interventions included: videoconferences, telephone-based interventions, television-based assistive technology, and human-robot. Conclusion: Despite the lack of rigorous studies, tele-rehabilitation is effective in improving cognition, behavioural and psychological symptoms, quality of life, and social connectedness. Rigorous methodologies, i.e., randomised control trials, are recommended.
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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 | 0.024 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".