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Record W2463258157 · doi:10.1093/her/cyw021

Psychosocial predictors of changes in adolescent girls’ physical activity and dietary behaviors over the course of the<i>Go Girls!</i>group-based mentoring program

2016· article· en· W2463258157 on OpenAlexafffund
A. Justine Dowd, Michelle Y. Chen, Toni Schmader, Mary E. Jung, Bruno D. Zumbo, Mark R. Beauchamp

Bibliographic record

VenueHealth Education Research · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMinistère de l’Éducation, Gouvernement de l’Ontario
KeywordsPsychosocialPsychologyMultilevel modelDevelopmental psychologySelf-efficacyPhysical activityClinical psychologyPath analysis (statistics)Behavior changeHealth behaviorMedicineSocial psychologyEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

Changes in social cognitions targeted within a group-based mentoring program for adolescent girls were examined as predictors of changes in physical activity (PA) and dietary behavior (in two separate models) over the course of the 7-week program. Data were collected from 310 participants who participated in the program. Multilevel path models were used to assess changes in psychosocial variables predicting changes in behavioral outcomes from pre- to post-program. Analyses revealed that 24.4 and 12.3% of the variance in increases in PA and dietary behavior, respectively, was explained by increases in affective and instrumental attitudes, self-regulatory efficacy (SRE), and intentions. Increases in intentions partially mediated the effects of increases in SRE and affective attitudes on increases in PA behavior. In relation to improvements in dietary behavior, increases in intentions and SRE directly predicted improvements in dietary behavior. These findings suggest potential psychological mechanisms through which a group-based mentoring program may lead to changes in adolescent girls' health-enhancing PA and dietary behaviors.

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 score0.459
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.193
GPT teacher head0.560
Teacher spread0.367 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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