The English version of the four-dimensional symptom questionnaire (4DSQ) measures the same as the original Dutch questionnaire: A validation study
Bibliographic record
Abstract
BACKGROUND: Translations of questionnaires need to be carefully validated to assure that the translation measures the same construct(s) as the original questionnaire. The four-dimensional symptom questionnaire (4DSQ) is a Dutch self-report questionnaire measuring distress, depression, anxiety and somatization. OBJECTIVE: To evaluate the equivalence of the English version of the 4DSQ. METHODS: 4DSQ data of English and Dutch speaking general practice attendees were analysed and compared. The English speaking group consisted of 205 attendees, aged 18-64 years, in general practice, in Canada whereas the Dutch group consisted of 302 general practice attendees in the Netherlands. Differential item functioning (DIF) analysis was conducted using the Mantel-Haenszel method and ordinal logistic regression. Differential test functioning (DTF; i.e., the scale impact of DIF) was evaluated using linear regression analysis. RESULTS: DIF was detected in 2/16 distress items, 2/6 depression items, 2/12 anxiety items, and 1/16 somatization items. With respect to mean scale scores, the impact of DIF on the scale level was negligible for all scales. On the anxiety scale DIF caused the English speaking patients with moderate to severe anxiety to score about one point lower than Dutch patients with the same anxiety level. CONCLUSION: The English 4DSQ measures the same constructs like the original Dutch 4DSQ. The distress, depression and somatization scales can employ the same cut-off points as the corresponding Dutch scales. However, cut-off points of the English 4DSQ anxiety scale should be lowered by one point to retain the same meaning as the Dutch anxiety cut-off points.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".