Determining Knowledge and Behaviour Change: After Nutrition Screening Among Older Adults
Bibliographic record
Abstract
Two education interventions involving personalized messages after nutrition screening in older adults were compared to determine changes in nutrition knowledge and risk behaviour. Of 150 older adults randomly selected from a local seniors' centre, 61 completed baseline screening and a demographic and nutrition knowledge questionnaire and were randomized to one of two groups. Group A received personalized letters plus an educational booklet, and Group B received personalized letters only. All materials were sent through the mail. Forty-four participants completed post-test questionnaires to determine change in knowledge and risk behaviour. Both groups had reduced nutrition risk scores and increased knowledge scores at post-test. After the intervention, a significant difference was observed in knowledge change by treatment group. Group A participants experienced greater gains in knowledge, with a mean gain of 5.43 points, than did those in Group B, who had a mean gain of 1.36 points (p=0.018). Screening and education with print materials have the potential to change risk behaviour and nutrition knowledge in older adults. A specially designed booklet on older adults' nutrition risk factors plus a personalized letter provide an effective education strategy for older adults after screening.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".