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Self‐Efficacy Predicts Physical Activity in Individuals With Fibromyalgia1

2003· article· en· W2079986510 on OpenAlexaff
S. Nicole Culos‐Reed, Lawrence R. Brawley

Bibliographic record

VenueJournal of Applied Biobehavioral Research · 2003
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of WaterlooUniversity of Calgary
Fundersnot available
KeywordsPsychologyPhysical activitySelf-efficacyClinical psychologyDevelopmental psychologyPsychotherapistPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

The purpose of the current study was to prospectively examine the relationship between physical activity patterns and psychosocial predictors in a sample of individuals with fibromyalgia (FM). Individuals with FM (N= 61) tracked their physical activity over a 1 ‐month period and completed baseline and endpoint questionnaires. Self‐efficacy provided the framework for the investigation, with both self‐efficacy and intention examined as predictors of physical activity. Exploratory analyses examined the addition of attitude and social influence as predictors of intention and behavior. The results supported the importance of self‐efficacy as a direct prospective predictor of the physical activity of FM individuals. Future research should examine whether maintaining strong intentions is helpful or realistic in motivating physical activity as a treatment option for individuals with FM.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.147
GPT teacher head0.481
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), 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
Published2003
Admission routes1
Has abstractyes

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