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Record W2141158725 · doi:10.1123/jsep.2013-0114

Effects of Social Belonging and Task Framing on Exercise Cognitions and Behavior

2014· article· en· W2141158725 on OpenAlexaff
A. Justine Dowd, Toni Schmader, Benjamin D. Sylvester, Mary E. Jung, Bruno D. Zumbo, Luc J. Martin, Mark R. Beauchamp

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of LethbridgeUniversity of British Columbia
Fundersnot available
KeywordsPsychologyFeelingPsychological interventionFraming (construction)CognitionSocial psychologyPhysical activityDevelopmental psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

The objective of the studies presented in this paper was to examine whether the need to belong can be used to enhance exercise cognitions and behavior. Two studies examined the effectiveness of framing exercise as a means of boosting social skills (versus health benefits) for self-regulatory efficacy, exercise intentions, and (in Study 2) exercise behavior. In Study 1, inactive adults primed to feel a lack of social belonging revealed that this manipulation led to greater self-regulatory efficacy (but not exercise intentions). In Study 2, involving a sample of inactive lonely adults, all participants reported engaging in more exercise; however, those in the social skills condition also reported a greater sense of belonging than those in the health benefits comparison condition. These findings provide an important basis for developing physical activity interventions that might be particularly relevant for people at risk for feeling socially isolated or lonely.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.560

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)0.0000.000

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 head0.019
GPT teacher head0.362
Teacher spread0.344 · 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

Citations29
Published2014
Admission routes1
Has abstractyes

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