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Record W1973696333 · doi:10.1007/s12160-008-9039-6

Promoting Fruit and Vegetable Intake through Messages Tailored to Individual Differences in Regulatory Focus

2008· article· en· W1973696333 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Behavioral Medicine · 2008
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsQueen's University
FundersNational Cancer InstituteYale Cancer CenterYale University
KeywordsPromotion (chess)Health psychologyHealth promotionRegulatory focus theoryFocus groupMedicineBaseline (sea)PsychologyPublic healthSocial psychologyMarketingBusinessPolitical scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Researchers must identify strategies to optimize the persuasiveness of messages used in public education campaigns encouraging fruit and vegetable (FV) intake. PURPOSE: This study examined whether tailoring messages to individuals' regulatory focus (RF), the tendency to be motivated by promotion versus prevention goals, increased the persuasiveness of messages encouraging greater FV intake. METHOD: Participants (n = 518) completed an assessment of their RF and were randomly assigned to receive either prevention- or promotion-oriented messages. Messages were mailed 1 week, 2 months, and 3 months after the baseline interview. Follow-up assessments were conducted 1 and 4 months after the baseline assessment. RESULTS: Regression analyses revealed that at Month 4, the messages were somewhat more efficacious when congruent with participants' RF. CONCLUSION: RF may be a promising target for developing tailored messages promoting increased FV intake, and particularly for encouraging individuals to meet FV guidelines.

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.

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 score0.109
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.290
GPT teacher head0.450
Teacher spread0.160 · 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