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Record W2095610163 · doi:10.1177/1359105312445798

Examining the use of message tailoring to promote physical activity among medically underserved adults

2012· article· en· W2095610163 on OpenAlexaff
Josefa L. Martinez‐Brockman, Lindsay R. Duncan, Susan E. Rivers, Amy E. Latimer‐Cheung, Peter Salovey

Bibliographic record

VenueJournal of Health Psychology · 2012
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsQueen's University
FundersNational Cancer Institute
KeywordsRegulatory focus theoryPromotion (chess)Health promotionPsychologyFocus (optics)Focus groupPhysical activityMatching (statistics)Sample (material)MedicineClinical psychologyApplied psychologyDevelopmental psychologySocial psychologyPublic healthPhysical therapyNursing

Abstract

fetched live from OpenAlex

The purpose of this study was to examine if messages tailored to an individual's regulatory focus (i.e. their tendency to focus on prevention or promotion) increased exercise intentions and behavior in a medically underserved sample. Adult English as a Second Language students (N = 58) were presented with tailored exercise messages. There was a significant main effect for message type; participants who received promotion messages reported greater exercise intentions than those who received prevention messages. Intentions and behavior were not higher among those who received messages matching their regulatory focus. Implications for message tailoring frameworks are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.348
GPT teacher head0.490
Teacher spread0.142 · 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

Citations20
Published2012
Admission routes1
Has abstractyes

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