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Record W2135226626 · doi:10.1123/krj.2.1.4

Powering Adherence to Physical Activity by Changing Self-Regulatory Skills and Beliefs: Are Kinesiologists Ready to Counsel?

2013· article· en· W2135226626 on OpenAlexaboutno aff
Lawrence R. Brawley, Madelaine Gierc, Sean Locke

Bibliographic record

VenueKinesiology Review · 2013
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsKinesiologyCertificationPsychological interventionIntervention (counseling)PsychologyMedical educationResource (disambiguation)CognitionQuality (philosophy)MedicineGerontologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

There are multiple avenues to gain health promoting and disease preventing benefits of physical activity (PA) but nonadherence makes health benefits short-lived. Gains obtained through structured exercise training and therapy quickly decay once participants leave programs. Scientific position statements underscore cognitive-behavioral strategies (CBS) as an essential intervention component to increase and maintain PA and recommend transfer of CBS knowledge to practice. Our review of reviews indicates high quality PA interventions involving CBS consistently demonstrate medium effect sizes. Kinesiologists are the human resource capacity to translate this knowledge. Building capacity to implement CBS knowledge is potentially large given North American kinesiology programs and American College of Sports Medicine and Canadian Society for Exercise Physiology certification routes. Yet CBS training of kinesiologists by universities and organizations is minimal. Immediate change in CBS training and practice is needed. Professional organizations/institutions can either be leaders in developing human resources or part of the problem should they fail to address the challenge of CBS training.

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 score0.888
Threshold uncertainty score0.923

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)0.0000.001

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 head0.030
GPT teacher head0.341
Teacher spread0.311 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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