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Record W3211215077 · doi:10.1093/pch/pxab061.004

8 Food Insecurity during COVID-19 in a Canadian Academic Pediatric Hospital

2021· article· en· W3211215077 on OpenAlexaffabout
Meta van den Heuvel, Anne Fuller, Nusrat Zaffar, Xuedi Li, Carolyn E Beck, Catherine S. Birken

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsFood insecurityMedicineDistressPandemicDescriptive statisticsFood securityEnvironmental healthCoronavirus disease 2019 (COVID-19)Family medicineClinical psychologyGeographyDiseaseAgriculture

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Social Paediatrics Background There are concerns of increased food insecurity rates during the COVID-19 pandemic, but there is no evidence to date about families with children with an acute or chronic illness. Parents with a child admitted to the hospital may also experience hospital-based food insecurity, defined as the inability of caregivers to afford adequate food during their child’s hospitalization. Objectives We aimed to measure the prevalence of household and hospital-based food insecurity in an academic pediatric hospital setting during the COVD-19 pandemic. We also explored the effects of food insecurity on parental distress and overall caregivers’ experiences obtaining food during their hospital stay. Design/Methods This was a cross-sectional study from April to October 2020. Household food insecurity was measured using the 18-item U.S. Household Food Security Survey Module. Three adapted questions about hospital-based food insecurity were added. Parental distress was measured with the validated Distress Thermometer for Parents: “0” indicates “no distress” and “10” indicates “extreme distress”. Descriptive statistics were used to assess the proportions of food insecurity. Linear regression models were used to explore the relationship between food insecurity and parental distress adjusted for potential confounders. To explore caregivers’ experiences we included one open-ended question in our survey, asking: “Do you have any other feedback regarding your food situation during your child’s hospital admission?”. Recurrent themes were identified using qualitative analysis. Results 851 families were reached by telephone and 775 (91.0%) provided consent to participate. 435 (56.1%) completed at least one questionnaire [Figure 1 Study Flow Diagram]. Caregivers described a high prevalence of household (34.2%) and hospital-based (38.0%) food insecurity. Both adult (B= 0.21 [95% CI 0.07-0.36]), child (B= 0.38 [95% CI 0.10-0.66]) and hospital-based (B= 0.56 [95% CI 0.30-0.83]) food insecurity were significantly associated with parental distress independent of covariates [Table]. In the qualitative analysis, the financial burden and emotional and practical barriers obtaining food in the hospital were identified as important themes. Parents also commented that they “need to eat to be able to take part in the care of their child during hospitalization”. Conclusion Both household and hospital-based food insecurity were highly prevalent in caregivers and significantly associated with parental distress, independent of covariates. High parental distress is known to be associated with a child’s maladjustment to illness and adherence with medical treatment. Hospitals need to strongly consider reducing barriers for parents to obtain food for themselves during their child’s admission in order to reduce parental distress.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.077
GPT teacher head0.404
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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