Can Visual Art Therapy Be Implemented With Illiterate Older Adults With Mild Cognitive Impairment? A Pilot Mixed-Method Randomized Controlled Trial
Bibliographic record
Abstract
Older adults with mild cognitive impairment (MCI) with no literacy are at increased risk of progression to dementia. Whether it is feasible to engage this population in visual art therapy (VAT) and yield effects on cognition and depression remained unclear. A pilot mixed-method single-blinded randomized controlled trial was conducted in a sample of community-dwelling older adults with MCI. The experimental group (n = 21) was assigned to 12 sessions of VAT over 6 weeks, and the control group (n = 18) was assigned to 6 weekly health education (HE) on nonbrain health topics. Participants were evaluated at baseline using Montreal Cognitive Assessment-5-minute protocol (MoCA-5-min) and Geriatric Depression Scale Short Form (GDS-SF). A focus group discussion (FGD) was also conducted to the experimental group to explore their experiences of participating in the VAT. Findings indicated that both VAT and HE groups had significant improvement in MoCA-5-min scores and depressed mood over time; however, the significant group × time interaction effect was noted only for the psychological outcome. Findings from the FGD indicated that participants had challenging experiences at the beginning of the therapy, but later, they were able to cope and found that the VAT was relevant and beneficial for their cognitive and psychosocial health. This pilot study provided initial evidence about the potential benefit of VAT in improving cognitive and psychological well-being of older adults with MCI and low literacy and provided insights on how to better engage them in this cognitive stimulating intervention. A full-scale trial is recommended for a stringent evaluation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".