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Record W4405691689 · doi:10.1108/bfj-04-2024-0380

Food well-being: a review of its conceptualization and measurement

2024· review· en· W4405691689 on OpenAlexaff
Tian Zeng, Eduard Xavier Montesinos-Sansaloni

Bibliographic record

VenueBritish Food Journal · 2024
Typereview
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsCégep de RimouskiUniversité du Québec à Rimouski
Fundersnot available
KeywordsNomological networkConceptualizationCLARITYMarketingContext (archaeology)Conceptual frameworkConstruct (python library)OriginalityPsychologyBusinessSociologyKnowledge managementService (business)Qualitative researchComputer scienceSocial scienceGeography

Abstract

fetched live from OpenAlex

Purpose This study aimed to improve understanding of the phenomenon of food well-being (FWB) (conceptualization, measurement, antecedents and outcomes) so as to lead future empirical work on measurement, development and theory testing. The hope is to improve the societal benefits of FWB and sustainable food system transformation. Design/methodology/approach A domain-based systematic review of FWB was conducted using databases (Web of Science, ABI/INFORM, EBSCO and Scopus). The well-established theory, context, characteristics and methodology framework were used to structure the review. Findings This study synthesized conceptual definitions and measurements of consumer FWB from hedonic, eudemonistic and mixed research streams and a nomological network that distinguishes this construct from its antecedents and outcomes. Practical implications This study provides recommendations for consumers, food designers, retailers and policymakers to improve FWB. Originality/value This study assessed the conceptualizations of FWB from hedonic, eudemonistic and mixed perspectives for conceptual clarity. It summarized ten measurement tools for FWB-allied concepts (Well-being Related to Food Questionnaires, Satisfaction with Food-Related Life Scale and World Health Organization-Five Well-Being Index), which revealed the need for novel measurement. This study developed a holistic nomological network of FWB by identifying the categories of antecedents (food-related, consumer-related and contextual factors) and outcomes (general well-being, life satisfaction and food consumption). This study provides a research agenda for FWB measurement and theoretical development.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.101
GPT teacher head0.372
Teacher spread0.271 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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