Content validation of the Kamath and Stothard questionnaire for carpal tunnel syndrome diagnosis: a cognitive interviewing study
Bibliographic record
Abstract
BACKGROUND: Accurate diagnosis of carpal tunnel syndrome (CTS) is essential for directing appropriate treatment; and for making decisions about work injury claims. The Kamath and Stothard Questionnaire (KSQ) is a self-reported tool used for the diagnosis of CTS. Comprehensibility and comprehensiveness of this questionnaire are critical to diagnostic performance and need to be established. The purpose of the study was to describe how potential respondents, clinicians, and measurement researchers interpret KSQ questions in order to identify and resolve potential sources of misclassification. METHODS: Hand therapists, measurement researchers, participants with CTS, and a control group were interviewed using cognitive interviewing techniques (talk aloud, semi-structured interview probes) in Hamilton, Canada. All interviews were recorded and transcribed verbatim. A directed content analysis was done to analyze the interviews using a previously established framework. FINDINGS: Eighteen participants were interviewed. Areas, where questions were unclear to some participants, were recorded and categorized into five themes: Clarity and Comprehension (52%), Relativeness (38%), Inadequate Response Definition (4%), Perspective Modifiers (4%), and Reference Point (2%). Respondents also identified several symptoms of CTS that are not covered by the KSQ that might be of diagnostic value, e.g., weakness and dropping items. CONCLUSION: The content validity of the current iteration of the KSQ was not established. The problematic questions identified in the study have been reported to have low specificity and negative predictive values in a previous quantitative study. The content validity issues identified may explain the poor performance. Recommendations were made to modify the wording of the KSQ and the potential addition of three new questions. Future studies should determine whether the modified questionnaire can provide better diagnostic accuracy and psychometric properties. The results of this study may assist in ruling in or out CTS diagnosis to a wide variety of target audience, such as hand specialists, physical and occupational therapists, as well as family doctors.
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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 | 0.050 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".