Measuring Exercise Self-Efficacy After Stroke: Validity and Reliability of Current Measures
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Many physically capable stroke survivors are insufficiently active, with low self-efficacy considered an important contributor. However, validity and reliability of self-efficacy measures in stroke survivors have not been established. This research aims to evaluate the test-retest reliability and construct validity of 3 self-efficacy measures: Self-Efficacy for Exercise Scale (SEE), Spinal Cord Injury Exercise Self-Efficacy Scale (SCI-ESES), and Participation Strategies Self-Efficacy Scale (PS-SES). METHODS: A repeated measures study with community-dwelling, independently mobile adult stroke survivors (n = 51, mean age 74 years, 45% female, median 22 months poststroke) was completed. Test-retest reliability was assessed using intraclass correlation coefficients and Bland-Altman analyses. Construct validity was assessed using 8 pre-determined hypotheses concerning physical activity level (subjective and objective), comorbidities, work and volunteering, and measures of function. RESULTS: Retest reliability was established for the SEE (intraclass correlation coefficient, ICC = 0.77) and PS-SES (ICC = 0.78) but not for the SCI-ESES (ICC = 0.68). Bland-Altman analysis showed participants consistently scored higher on the second test for all measures. The SEE achieved construct validity by meeting 75% of hypotheses, whereas the PS-SES and SCI-ESES did not. Self-efficacy was positively related to steps/day, functional capacity, self-reported activity levels, and work or volunteering participation. DISCUSSION AND CONCLUSIONS: The SEE was found to be the most appropriate tool to measure exercise self-efficacy in independently mobile chronic stroke survivors in terms of retest reliability and validity. TRIAL REGISTRATION: N/A. VIDEO ABSTRACT AVAILABLE: for more insights from the authors (see the Video, Supplemental Digital Content 1 "Espernberger-JNPT-Video-Abstract," available at: http://links.lww.com/JNPT/A489 ).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".