Accompany caregivers to optimize learning with people living with a major neurocognitive disorder: A participatory action research
Bibliographic record
Abstract
For caregivers of people living with major neurocognitive disorders (MNCD), adapting and applying methods optimizing learning (MOL) to a specific situation, based on preserved cognitive skills, can be challenging. This study aimed to 1) co-develop workshops, a web application and accompanying materials to support the operationalization of MOL; 2) better understand the factors influencing caregivers’ use of MOL, and 3) evaluate the perceived effects of the workshops. A participatory action research study was conducted in collaboration with family caregivers of people living with MNCD and healthcare and community organization workers (HCOW). Qualitative questionnaires and interviews were conducted and transcribed in verbatim. Thematic content analysis was conducted. Workshops and accompanying materials were co-developed and continuously improved based on conceptual framework and feedback from the participants. The final version of the workshops consisted of seven two-hour sessions structured around the type of cognitive deficits affecting the realization of activities. Facilitators (e.g. help to identify the person’s capabilities) and barriers (e.g. fluctuation of MNCD symptoms) for caregivers’ use of the MOL were reported. The identification of the cause of reactive behavioral expressions could be challenging for some family caregivers, reducing the use of MOL. Caregivers mentioned their increased preparedness to support and relationship with the person living with MNCD and feeling of competence for analyzing the reactive behavioral expressions and to use MOL. This participatory action research has shown that caregivers can acquire abilities to adapt and apply MOL in specific situations with people living with MNCD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".