Development of a Resource: To Help Consumers Select Nutrition Supplements
Bibliographic record
Abstract
PURPOSE: In Canada, many people do not meet all the recommended nutrient intakes with food alone; the use of supplements may be one strategy to compensate for some of these inadequacies. Previous research has revealed several barriers to supplement use, including a lack of knowledge. In this qualitative study, we developed a resource to help inform and educate consumers on the selection of appropriate nutrition supplements. METHODS: Three focus groups with participants residing in low-income neighbourhoods in Saskatoon, Saskatchewan, and seven key informant interviews were conducted using a semi-structured interview guide and four resource examples. After transcription of the discussion and interviews, thematic analysis was used to identify emergent themes. RESULTS: Analysis yielded three overarching themes: barriers to use, interdisciplinary issues, and resource expectations. Each overarching theme had several subthemes. Subthemes of the overarching theme of resource expectations were subsequently used to create a new tool to help consumers select an appropriate multivitamin. CONCLUSIONS: A tool was developed after available resources were explored and stakeholders were interviewed. The new resource was based on community members' and health care professionals' expressed needs, ideas, and beliefs.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".