MétaCan
Menu
Back to cohort
Record W4381542555 · doi:10.5334/jeps.546

Improving attitudes towards breaks from sitting using affective and cognitive messages

2022· article· en· W4381542555 on OpenAlexaff
Hoda Gharib, Monica LaBarge, Lucie Lévesque

Bibliographic record

VenueJournal of European Psychology Students · 2022
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsCognitionContext (archaeology)PsychologyMatching (statistics)SittingAffect (linguistics)Attitude changeSocial psychologyPositive attitudeMedicineCommunication

Abstract

fetched live from OpenAlex

This study tested for (mis)matching effects between affective and cognitive messages promoting breaks from sitting at home (H) and work (W) and attitude basis. Working adults (n=198) were randomised into an affective or cognitive message group and completed a pre- and post-message questionnaire assessing overall, affective, and cognitive attitudes. The main outcome was change in attitudes towards breaks (H/W). Participants with weak-to-strong affective attitudes and moderate-to-strong cognitive attitudes showed greater attitude change (H) after exposure to the matching message, but not participants with weaker attitude bases. No (mis)matching effect was found for attitude change (W). This study suggests that the need to match messages to attitude basis may depend on how strong the attitude basis is and the decision-making context.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.076
GPT teacher head0.463
Teacher spread0.387 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of European Psychology StudentsSame topicBehavioral Health and InterventionsFrench-language works237,207