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Record W2154263567 · doi:10.1093/gerona/62.10.1142

Self-Efficacy Mediates Walking Performance in Older Adults with Knee Osteoarthritis

2007· article· en· W2154263567 on OpenAlexafffund
Monica R. Maly, Patrick A. Costigan, Sandra J. Olney

Bibliographic record

VenueThe Journals of Gerontology Series A · 2007
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsWestern University
FundersMcMaster University
KeywordsOsteoarthritisPsychosocialSelf-efficacyPhysical therapyMedicinePhysical medicine and rehabilitationObesityPreferred walking speedKnee painPsychologyInternal medicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Self-efficacy is a determinant of walking performance in older adults with knee osteoarthritis. We examined whether self-efficacy mediated the effect of age, psychosocial, impairment, and mechanical factors on walking performance. METHODS: Fifty-four participants with knee osteoarthritis completed the Six Minute Walk test and Arthritis Self-Efficacy Scale. Independent variables reflected age, psychosocial (depressive symptoms), impairment (pain, stiffness), and mechanical (strength, obesity) factors. RESULTS: Self-efficacy fully mediated the effect of age and impairments on walking. The effects of strength were only partially mediated by self-efficacy. Depressive symptoms and obesity were not mediated by self-efficacy. CONCLUSIONS: These findings are consistent with Social Cognitive Theory, according to which age may alter outcome expectations, and impairments like pain and stiffness provide negative physiological feedback to influence performance. Mechanical factors like strength and obesity may better represent a person's capabilities and interact with other variables to influence physical performance in older adults with knee osteoarthritis.

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)0.008
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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

Citations54
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueThe Journals of Gerontology Series ASame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207