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Record W3035862441 · doi:10.2196/18292

The Evolving Family Mealtime: Findings From Focus Group Interviews With Hispanic Mothers

2020· article· en· W3035862441 on OpenAlexvenueno aff
Amber J. Hammons, Elizabeth Villegas, Norma Olvera, Kimberly A. Greder, Barbara H. Fiese, Margarita Terán-Garcı́a

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2020
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureUniversity of Illinois at Urbana-ChampaignU.S. Department of Agriculture
KeywordsFocus groupThematic analysisPsychological interventionContext (archaeology)PsychologyDevelopmental psychologyQualitative researchSociologyGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Given the protective effects of shared family mealtimes and the importance of family in the Hispanic culture, this context should be explored further to determine how it can be leveraged and optimized for interventions. OBJECTIVE: This study aimed to explore contextual factors associated with family mealtimes in Mexican and Puerto Rican families. METHODS: A total of 63 mothers participated in 13 focus group interviews across 4 states. Thematic analysis was used to analyze transcripts. RESULTS: Seven overarching themes were identified through the thematic analysis. Themes reflected who was present at the mealtime, what occurs during mealtime, the presence of television, the influence of technology during mealtime, and how mealtimes have changed since the mothers were children. CONCLUSIONS: Hispanic mothers may be adapting family mealtimes to fit their current situations and needs, keeping the television and other devices on during mealtimes, and making additional meals for multiple family members to appease everyone's tastes. All of these are areas that can be incorporated into existing culturally tailored obesity prevention programs to help families lead healthier lives.

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 score0.012
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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Same venueJMIR Pediatrics and ParentingSame topicObesity, Physical Activity, DietFrench-language works237,207