A Qualitative Evaluation of a Plate-Method Dietary Self-Monitoring Tool in a Sample of Adults Over 50
Bibliographic record
Abstract
Background: Self-monitoring is an important behavioral change technique to help users initiate and maintain dietary changes. Diet self-monitoring tools often involve the itemization of foods and recording of serving sizes. However, this traditional method of tracking does not conform to food guides using plate-based approach to nutrition education, such as the 2019 Canada's Food Guide (CFG). Objective: To explore the acceptability, facilitators and barriers of using a plate-based dietary self-monitoring tool based on the 2019 CFG (Plate Tool) compared with a traditional Food Journal (Food Journal). Methods: = 45) were conducted after completing the second tool. A qualitative description of the interviews was conducted through an inductive determination of themes. Results: Facilitators to using the Plate Tool were its simplicity, quick completion time compared with the Food Journal and easiness to use, increased awareness of dietary habits and accountability, with participants expressing that it could help users make informed dietary changes aligning with the CFG. However, barriers to using the Plate Tool were its lack of precision, the participants' difficulty categorizing foods into the CFG categories and recording intake of foods not present on the CFG. Conclusions: The Plate Tool is an acceptable dietary self-monitoring tool for healthy adults over 50. Self-monitoring tools based on the plate method should take the barriers described in this study into account. Future studies should compare dietary self-monitoring methods to assess adherence and effectiveness at eliciting dietary behavior change.
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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 | 0.040 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".