A multidimensional validation study of the Turkish version of the Comprehensive Lower-limb Amputee Socket Survey in veterans
Bibliographic record
Abstract
Technological and social advances have improved prosthetic devices; however, discomfort during prosthesis use remains a persistent problem. Therefore, ongoing assessment of socket fit is essential. This process is key to ensuring long-term functionality and comfort for prosthetic users. This study aimed to adapt the Comprehensive Lower-limb Amputee Socket Survey (CLASS) into Turkish and evaluate its validity and reliability in individuals with combat-related unilateral lower-limb amputation at K3 and K4 mobility levels. We performed cross-cultural adaptation and validation using multiple outcome measures reflecting various aspects of socket fit. A cross-sectional test-retest design was used with 80 prosthesis-using participants recruited from a rehabilitation hospital. Reliability was assessed using the intraclass correlation coefficient (ICC) and internal consistency via Cronbach's α . The Turkish CLASS demonstrated strong test-retest reliability across its domains (ICC = 0.80-0.90) and high internal consistency (Cronbach's α ranging from 0.73 to 0.87 across subscales). No significant floor effects were observed. Validity was examined through correlations with the Trinity Amputation and Prosthesis Experiences Scale (TAPES), Satisfaction with Prosthesis Questionnaire (SAT-PRO), and Socket Comfort Score (SCS). The comfort domain of Turkish CLASS showed strong correlations with SAT-PRO ( r = 0.62) and SCS ( r = 0.74), while other domains had moderate correlations with TAPES subscales ( r = 0.43-0.55), supporting concurrent validity. The minimum detectable change scores across the domains ranged from 9.3 (comfort) to 16.1 (appearance). These findings indicate that the Turkish CLASS is a valid and reliable instrument for assessing socket fit in unilateral lower-limb amputees and is suitable for routine clinical use.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".