Development of a telephone questionnaire to assess parents' awareness, knowledge, beliefs and application of dietary fat recommendations for preschool children
Bibliographic record
Abstract
Health Canada recommends that the diet of young children should not be restricted in fat, however it advises adult Canadians to restrict fat to no more than 30% of energy. The objective of this study was to develop a telephone questionnaire to measure parents' awareness and understanding of dietary fat recommendations for children and their use of practices to lower fat when feeding their children. The three-step process used to develop the questionnaire included collecting qualitative data through focus group discussions (n = 14), review by a panel of nutrition experts (n = 12), and pretesting on a random sample of Manitoba parents of two to three year old preschoolers (n = 68) obtained from the Manitoba Health Administrative Database. Focus group findings showed that, in general, parents have low levels of awareness and understanding of fat recommendations, however, they express beliefs about the importance of fat for children. The focus groups also revealed that some parents were not concerned about the fat in their child's diet because their child already consumed a healthy diet that is lower in fat. Based on these findings, a telephone questionnaire was developed to determine parents' awareness, knowledge, beliefs, and level of and reasons for concern about fat. (Abstract shortened by UMI.)
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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 | 0.004 | 0.008 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".