Validity and reliability of the Serbian version of Patient-Reported Impact of Spasticity Measure in multiple sclerosis
Bibliographic record
Abstract
The Patient-Reported Impact of Spasticity Measure (PRISM) has been developed recently to assess the impact of spasticity on quality of life after spinal cord injury. Although PRISM may also be useful in patients with multiple sclerosis (MS), its psychometric properties in MS have not been established and PRISM is currently available only in English. The aims of this cross-sectional study were to translate PRISM into the Serbian language (PRISMSR) and examine its validity (construct, convergent, divergent) and reliability (internal consistency, test-retest reliability) in 48 patients with spasticity because of MS diagnosed at least 1 year earlier and in remission at least 3 months. PRISMSR was administered twice 3 days apart. The validity of seven PRISMSR subscales was examined against the Modified Ashworth Scale (MAS), the Numerical Rating Scale (NRS) for spasticity, sex, and education. Internal consistency was assessed with Cronbach α and test-retest reliability with intraclass correlation coefficient for agreement (ICC2,1). During the forward-backward translation, only one PRISM item required minor cultural adaption. Almost all PRISMSR scores correlated significantly with MAS and NRS scores (r=0.29-0.51, 0.001≤P≤0.043). They were all significantly higher for MAS≥2 group versus the MAS<2 group (0.003≤P≤0.035) and for the NRS≥7 group versus the NRS<7 group (0.001≤P≤0.042), except for the Social Embarrassment subscale (P=0.083). The PRISMSR scores were not significantly different between sexes (P≥0.104) or those with high school versus college degree (P≥0.139). Both Cronbach α (0.78-0.93) and test-retest ICC2,1 (0.82-0.90) were high. The original PRISM may be translated successfully into other languages. PRISMSR shows adequate validity and reliability for assessing the impact of spasticity on quality of life in patients with MS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".