<i>Fruit and Vegetable Consumption:</i>Benefits and Barriers
Bibliographic record
Abstract
Few people on Prince Edward Island meet the goal of consuming five or more servings of vegetables and fruit a day. The main objective of this qualitative study was to explore the perceptions of the nutritional benefits and barriers to vegetable and fruit intake among adult women in Prince Edward Island. Participants were 40 women aged 20-49, with or without children at home, who were or were not currently meeting the objective of eating five or more fruit and vegetable servings a day. In-home, one-on-one interviews were used for data collection. Thematic analysis was conducted on the transcribed interviews. Data were examined for trustworthiness in the context of credibility, transferability, and dependability. Most participants identified one or more benefits of eating fruit and vegetables; however, comments tended to be non-specific. The main barriers that participants identified were effort, lack of knowledge, sociopsychological and socioenvironmental factors, and availability. Internal influences, life events, and food rules were identified as encouraging women to include vegetables and fruit in their diets. Given the challenges of effecting meaningful dietary change, dietitians must look for broader dietary behavioural interventions that are sensitive to women's perceptions of benefits and barriers to fruit and vegetable intake.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".