International students’ perceptions of healthy eating before and after arrival in Canada: A qualitative study.
Bibliographic record
Abstract
Introduction: International student numbers in Canada are increasing with many students planning to reside in Canada after graduation. However, the health of this population tends to decline with time spent in Canada, leading to higher rates of chronic disease. Previous research suggests that international students perceive their traditional diet as healthier compared to that available in North America. However, there is a gap in the literature exploring the meaning of healthy eating to international students, both in their country of origin and in Canada. Objectives: To explore international studentsu2019 (1) perceptions of a healthy diet in their country of origin, (2) perceptions of a healthy diet in Canada, and (3) how their perception of a healthy diet has changed since their arrival in Canada.Methods: A qualitative descriptive design was used where in-depth, one-on-one interviews were conducted with 13 international students at UPEI. The interviews were transcribed from audio recordings and analyzed using thematic analysis. Results: Nine key themes were identified: Preference for traditional foods and meals, associating traditional foods with healthy eating, the transition from familial to individual cooking practices, reading labels on processed foods, distrust of the food supply, discovering non-traditional foods, traditional food availability in Canada, reliance on convenience foods, and changing views of healthy eating.Conclusions: International students coming to Canada have unique experiences with food due to a change in way of life, a lack of social ties, and a new food culture. Significance to the field of dietetics: There is increased interest in research of international studentsu2019 nutrition and health transitions due to the vulnerability of this subpopulation and the impact of the u201chealthy immigrant effectu201d on the health system. Researchers, policymakers, and dietitians will benefit from increased research in this area to support evidence-based, culturally-appropriate nutrition interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".