Combining elements of the CO-OP Approach™ with education to promote healthy eating among older adults: A pilot study
Bibliographic record
Abstract
This paper describes an exploratory study developing the Baycrest Brain-healthy Eating Approach (BBEA). Poor diet is a modifiable risk factor for many health problems including dementia. Mediterranean type diets, high in plant-based foods, rich in poly- and mono- unsaturated fatty acids with minimal consumption of saturated fat, red meat, and processed foods, are considered brain healthful. While several dementia prevention trials randomized controlled trials have included nutritional counselling in favor of these diets as one component of their interventions, the extent to which dietary change occurred is not known. Based on observations that a strategy training approach, the Cognitive Orientation to daily Occupational Performance (CO-OP) Approach, was beneficial for promoting lifestyle changes in older adults with complaints of cognitive changes, we undertook to develop the BBEA combining elements of CO-OP with didactic nutrition education. This exploratory, descriptive study assesses the feasibility and acceptability of the BBEA. Healthy community dwelling older adults (n = 5) were recruited using convenience sampling. Participants received five, 2 h, group sessions. During these sessions participants were supported in adopting dietary practices consistent with brain healthy eating. Each participant set specific dietary goals important to them. Feasibility of the intervention was demonstrated through high levels of attendance and by the findings that at each session, all participants set personally meaningful goals and received education on selected brain healthy eating topics. Acceptability was demonstrated through participants' positive reports of their experiences and perspectives obtained via semi-structured interviews. Thus, the BBEA appears to be feasible and acceptable.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".