Undergraduate nursing and medical students’ perceptions of food security and access to healthy food in Qatar: a photovoice study
Bibliographic record
Abstract
The present study explored nursing and medical students' perceptions of food security, their access to healthy food and the circumstances that affect their access to healthy food in Qatar. The photovoice method was adopted in the present study. Students submitted their photos pertaining to food security and their access to healthy food in Qatar. Afterwards, the students completed an online synchronous semi-structured interview. The interviews were transcribed verbatim and thematically analysed. After the data analysis, a focus group discussion was conducted for member checking. The present study is a collaborative project between two universities in Qatar: The University of Calgary in Qatar (UCQ) and Qatar University (QU). Undergraduate students (seven nursing students and nine medical students) were recruited, asked to collect photos and interviewed. Four themes emerged from the data. First, food retail environments promoted unhealthy eating. Second, fast food under stressful circumstances: a sense of comfort. Third, food as a symbol of culture and socialisation. Finally, the paradox of access to affordable and healthy food in Qatar. Undergraduate students highlighted various circumstances that affect their perceptions of food security and their access to healthy food in Qatar. Future research that aims at understanding the facilitators and barriers to access healthy food at the university campus may help to improve nutrition interventions targeting those students. Future initiatives should focus on leveraging various resources to assist universities in tailoring their food initiatives to suit their students' local needs.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".