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Record W4382345386 · doi:10.1177/10901981231179504

Cooking at Home: Correlates of Frequency and Intention in Fifth Graders

2023· article· en· W4382345386 on OpenAlexafffundabout
Danielle Boucher, Dominique Beaulieu, Dominic Simard

Bibliographic record

VenueHealth Education & Behavior · 2023
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversité du Québec à Rimouski
FundersUniversité du Québec à RimouskiUniversité Laval
KeywordsTheory of planned behaviorNormativePsychologyPsychological interventionAutonomyDescriptive statisticsDevelopmental psychologyMealIntervention (counseling)Variance (accounting)Focus groupSocial psychologyControl (management)Medicine

Abstract

fetched live from OpenAlex

Cooking at home is associated with health benefits, and 10- and 11-year-old children are capable of participating in meal preparation. However, opportunities for children to cook at home have declined. This study aimed to identify determinants of the frequency and the intention to cook at home in fifth graders using the Theory of Planned Behavior as a framework with quantitative methodology. A total of 241 participants across five elementary schools of the Chaudière-Appalaches region (Quebec, Canada) took part in this correlational study. Data were collected via a self-administered questionnaire based on the Theory of Planned Behavior. Regression analyses led to the identification of determinants of frequency and intention to cook at home. More than two-thirds of participants (69%) declared having cooked at home in the past 7 days. Intention was the only significant variable explaining 18% of the variance for frequency. Intention was determined by perceived behavioral control, attitude, descriptive norms, subjective norms, perceived barriers, being a girl, and normative beliefs, which explain 74% of the variance. Whereas other studies aiming at better understanding children's involvement in meal preparation at home focused on self-efficacy for cooking, this study highlights other behavioral determinants. For example, support from parents appears to be crucial to promote this behavior in this age group. Future research and interventions should be oriented toward determinants such as subjective norms and normative beliefs, and focus on children's autonomy.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.111
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.452
Teacher spread0.347 · 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 teacher head, 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

Citations3
Published2023
Admission routes3
Has abstractyes

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