Barriers to increasing fruit and vegetable intakes in the older population of Northern Ireland: low levels of liking and low awareness of current recommendations
Bibliographic record
Abstract
OBJECTIVE: To investigate barriers to increasing fruit and vegetable (f + v) intakes in a large sample of the older population of Northern Ireland (NI), in relation to current intakes. DESIGN: The study was conducted using a telephone survey assessing f + v intakes, barriers to increasing intakes and various demographic and lifestyle characteristics. Barriers to increasing intakes were investigated using twenty-two closed-response items and one open-response item. SETTING: NI. SUBJECTS: Four hundred and twenty-six older people from NI, representative of the older population of NI. RESULTS: Principal component analysis of the twenty-two closed-response items revealed five factors affecting f + v consumption. Significant associations with current intakes were found where greater f + v consumption was associated with greater 'liking' for f + v (B = 0.675, P < 0.01), greater 'awareness of current recommendations' for consumption (B = 0.197, P < 0.01) and greater 'willingness to change' (B = 0.281, P < 0.01). 'Ease of consumption' and 'difficulties in achieving consumption' were not associated with f + v intakes. Similar associations between f + v intakes and 'liking' and 'awareness' were also found in those consuming low intakes of f + v or those at risk of consuming low intakes. Low awareness and knowledge of recommendations were also found in response to the open-ended question in all groups, although some weight was also given here to environmental difficulties, such as cost and access. CONCLUSIONS: These findings suggest that interventions aiming to increase f + v intakes in the older population of NI should focus predominantly on improving liking and improving knowledge and awareness of current recommendations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".