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Self‐Efficacy Predicts Physical Activity in Individuals With Fibromyalgia1

2003· article· en· W2079986510 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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