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Record W2136333930 · doi:10.1080/17461390601012512

Self‐efficacy and imagery use in older adult exercisers

2006· article· en· W2136333930 on OpenAlexaff
Natascha N. Wesch, Marcia I. Milne, Shauna M. Burke, Craig Hall

Bibliographic record

VenueEuropean Journal of Sport Science · 2006
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWestern University
FundersCenters for Disease Control and Prevention
KeywordsSelf-efficacyPsychologyMental imageGuided imageryTask (project management)Physical activityPhysical therapyPhysical medicine and rehabilitationMedicineCognitionPsychotherapistAnxietyPsychiatry

Abstract

fetched live from OpenAlex

Abstract The aim of the present study was to investigate the relationship between self‐efficacy and imagery use in older male ( n = 40) and female ( n = 52) exercisers. Participants’ self‐efficacy was evaluated using the Self‐Efficacy Questionnaire for Exercisers, and their use of imagery was evaluated using the Exercise Imagery Questionnaire. Results revealed that older adult exercisers were most efficacious in terms of the task, followed by scheduling physical activity into their daily routines, and finally overcoming barriers related to physical activity. Older adult exercisers also reported using appearance and technique imagery to much the same extent, but used both significantly more than energy imagery. In addition, energy imagery predicted task self‐efficacy but none of the three functions of imagery predicted barrier and scheduling self‐efficacy.

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)0.002
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 score0.027
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.279
Teacher spread0.264 · 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

Citations24
Published2006
Admission routes1
Has abstractyes

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