Food insecurity during COVID-19 in a Canadian academic pediatric hospital: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Hospital-based food insecurity is defined as the inability of caregivers to obtain adequate food during their child's hospital admission. We aimed to measure the prevalence of household and hospital-based food insecurity, and to explore the associations with caregiver distress in an academic pediatric hospital setting. METHODS: We conducted a cross-sectional survey of caregivers of children admitted to the general pediatric ward of an academic pediatric hospital in Toronto, Ontario, from April to October 2020. We measured household food insecurity using the 18-item Household Food Security Survey Module, and included 3 adapted questions about hospital-based food insecurity. We measured caregiver distress with the Distress Thermometer for Parents. We used descriptive statistics to assess the proportion of respondents with food insecurity, and linear regression models to explore the relation of household (adult and child) and hospital-based food insecurity with caregiver distress. We used thematic analysis to explore caregivers' feedback. RESULTS: We contacted 851 caregivers, and 775 (91.1%) provided consent to participate. Overall, 430 (50.5%) caregivers completed at least part of the survey. Caregivers described a high prevalence of household (34.2%) and hospital-based (38.1%) food insecurity. Adult (β = 0.21, 95% confidence interval [CI] 0.07-0.36), child (β = 0.38, 95% CI 0.10-0.66) and hospital-based (β = 0.56, 95% CI 0.30-0.83) food insecurity were significantly associated with caregiver distress, independent of covariates. We identified financial burden, emotional and practical barriers, stress obtaining food and advocacy for food as important themes in caregiver feedback. INTERPRETATION: Both household and hospital-based food insecurity were highly prevalent among caregivers. To reduce caregiver distress, hospitals need to consider reducing barriers for caregivers in obtaining food for themselves during their child's admission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".