Cross-Cultural Adaptation of Korean Language Versions of Neck Pain and Disability Questionnaires and Their Psychometric Testing
Bibliographic record
Abstract
Objectives : It was to translate three neck and spinal pain disability questionnaires - the Neck Disability Index (NDI), the Neck Pain and Disability Scale (NPDS), and the Functional Rating Index (FRI) - into Korean language, and evaluate the psychometric properties of Korean versions of questionnaires to achieve a good cross-cultural adaptation. Methods : Forty (23 males, 17 females) subjects aged from 15 to 64 years old, participated to examine test-retest reliability. One hundred and eighty (76 males, 104 females) subjects with a primary diagnosis of non-specific neck pain and 81 healthy volunteers were undertaken to examine internal consistemcy, discriminative validity and longitudinal construct validity. Versions of each questionnaire in idiomatic modern Korean were developed using a procedure proposed by Beaton et al. (2000). To assess reliability, the Intraclass Correlation Coefficient (ICC ) was calculated. Internal consistency was evaluated by Cronbach's alpha. Discriminative validity was examined with independent-group t-tests. Responsiveness was tested by calculating the effect size and standardized response mean for each questionnaire and using Pearson' s r and the area under the receiver operating characteristic curve analysis. Results : Test-retest reliability ofthe translated versions of the three disability questionnaires was excellent (ICC = 0.86-0.90). High internal consistency was found in the three disability questionnaires (Cronbach's alpha ranged from for the FRI to for the NPDS and 0.82 for the Short Form McGill Pain Questionnaire(SFMPQ)). the VAS subscale of the SFMPQ was found to be the most responsive of the subscales (ES=1.44, SRM=1.37). The VAS was also the most responsive pain and disability index in internal responsiveness analysis, although disability indices showed marginally better responsiveness when compared with external standards. No floor or ceiling effects were observed. Conclusions : It is concluded that the questionnaires were successfully translated and exhibit acceptable measurement properties, and may suggest that they are suitable for use in clinical and research application.
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".