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Record W1998765609 · doi:10.1002/art.21324

Perceived self-efficacy gained from, and health effects of, a rehabilitation program after hip joint replacement

2005· article· en· W1998765609 on OpenAlexaff
Birte Dohnke, Bärbel Knaüper, W. Müller-Fahrnow

Bibliographic record

VenueArthritis & Rheumatism · 2005
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsRehabilitationMedicinePhysical therapySelf-efficacyJoint replacementMultidisciplinary approachArthroplastySurgeryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine whether a routine multidisciplinary inpatient rehabilitation program can increase patient self-efficacy, and to investigate the effects of high self-efficacy at admission, and increases in self-efficacy, on health changes in patients who undergo such rehabilitation after hip joint replacement. METHODS: Participants in this longitudinal study were 1,065 patients who underwent inpatient rehabilitation after hip joint replacement. Questionnaires were administered at admission, discharge, and 6-month followup. The main outcome variables were disability, pain, depressive symptomatology, and self-efficacy to cope with disability and pain. RESULTS: Significant improvements from admission to discharge from the inpatient rehabilitation program in disability, pain, depressive symptoms, and self-efficacy were found. In addition, higher levels of self-efficacy at admission and larger increases in self-efficacy over the course of the program predicted larger health changes (i.e., greater decreases in disability, pain, and depressive symptoms). Results were generally similar for health changes from discharge to 6-month followup. CONCLUSION: A routine multidisciplinary inpatient rehabilitation program after hip joint replacement can result in enhanced 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)0.000
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 score0.930
Threshold uncertainty score0.935

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)0.0000.000

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 head0.009
GPT teacher head0.267
Teacher spread0.259 · 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

Citations70
Published2005
Admission routes1
Has abstractyes

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