Content validation of the COST for patient questionnaire (COPAQ) for patients with low back pain: a qualitative study
Bibliographic record
Abstract
Abstract Introduction The costs of low back pain (LBP) are complex and difficult to estimate. This study aims to adapt the Cost for Patients Questionnaire (CoPaQ) for use in LBP populations. Materials and methods In a cross-sectional qualitative study, we conducted cognitive interviews to assess the CoPaQ’s suitability for addressing costs related to LBP. Three groups of participants were included (n = 5 each): (i) persons with a history of LBP or primary caregiver, (ii) researchers with expertise in LBP, and (iii) primary care providers specialized in treating LBP. The interpretation, analysis, and summary of results used Knafl et al.’s qualitative content analysis method. Results Persons with a history of LBP (n = 5), had a median age of 60 years (Interquartile Range (IQR): 26–71.5), and varying durations of LBP, the median duration of LBP 7 years (IQR: 4–32.5). Researchers (n = 5) had a median age of 33 years (IQR: 29–45). Primary care providers (n = 5) had a median age of 40 years (IQR: 37.5–65), and a background in chiropractic care (n = 3) and physiotherapy (n = 2). Content analysis of the interviews revealed sources of error with five pre-determined themes (clarity/comprehension, relevance, inadequate response definition, reference point, perspective modifiers) and one developed theme (organization). We modified the questionnaire for LBP populations based on the feedback. Conclusion Our study evaluated the content validity of a questionnaire that assesses the direct and indirect costs associated with LBP. Future studies should pilot this questionnaire with persons of varying LBP severity and compare it with cost diaries.
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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 | 0.097 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".