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Record W2004146621 · doi:10.1111/josh.12251

Longitudinal Changes in Beliefs by Stage of Physical Activity Adoption in Iranian Girls

2015· article· en· W2004146621 on OpenAlexaff
Parvaneh Taymoori, Tanya R. Berry

Bibliographic record

VenueJournal of School Health · 2015
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBoredomPsychological interventionLogistic regressionAction (physics)PsychologyPhysical activityTranstheoretical modelLongitudinal studyDevelopmental psychologyGerontologyDemographyMedicineSocial psychologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: The aims of this study were to examine the relationships among physical activity (PA)-related beliefs and to determine to what extent Iranian adolescents in different stages of PA adoption differ in perceived benefits and barriers during a 3-year transition from junior high school to high school. METHODS: Data were collected from female adolescents in 2010 (N = 558), of whom 412 provided follow-up data in 2013. One-way analysis of variance and logistic regression were conducted for statistical analysis. RESULTS: Participants in the action and maintenance stages reported the greatest agreement with benefits. Pre-contemplators were about 4 times more likely to cite "not enough time" than preparers (OR = 3.95). Pre-contemplators were over 4 times more likely to cite not liking exercise than those in action and maintenance stages at baseline (OR = 4.32 and 4.85), a finding which was maintained at follow-up (OR = 3.66 and 8.65). CONCLUSIONS: These findings could help with the creation of interventions tailored to encourage pre-contemplators to progress toward adoption of PA. Providing transportation supports, enhancing time management, and mitigating boredom may be helpful strategies either to prevent relapse in adoption stages or to move females in early stages of change toward action and maintenance.

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)0.001
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 score0.019
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.072
GPT teacher head0.369
Teacher spread0.297 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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