Serbian Validation of the Individualized Neuromuscular Quality of Life Questionnaire (INQoL) in Adults With Myotonic Dystrophy Type 1
Bibliographic record
Abstract
Background : To validate Individualized Neuromuscular Quality of Life Questionnaire (INQoL) in Serbian patients with myotonic dystrophy type 1 (DM1). Methods : This study included 102 patients with adult onset DM1. Validation included reliability analysis (internal consistency, reproducibility), content-related validity (psychometric evaluation, construct-related validity, criterion-related validity) and concurrent validity. Results : The internal consistency of the Serbian version of INQoL was excellent (Cronbach’s alpha 0.864-0.961). Test-retest reliability satisfied the requested level (intraclass correlation coefficient 0.713-0.979). Item internal consistency and discriminant validity were excellent. INQoL scores were significantly affected by age of patients, duration of disease and severity of muscular impairment (P less than 0.01), slightly affected by education (P less than 0.05) and not related to gender (P greater than 0.05). Correlation between INQoL scales and comparable SF-36 domains was significant (P less than 0.01) but INQoL also registered locking and body image omitted by SF-36. Conclusion : Serbian version of INQoL is reliable and valid quality of life (QoL) measure for patients with DM1, able to capture disease specific issues usually omitted by generic questionnaires. doi:10.4021/jnr54w
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".