Validation of the Dutch Version of the Brief Negative Symptom Scale
Bibliographic record
Abstract
Birgit L Seelen-de Lang,1 Christien E Boumans,2 Henk LI Nijman3 1Flexible Assertive Community Treatment-Team, GGZ Oost Brabant, Boekel, the Netherlands; 2Long-Term Clinical Care, GGZ Oost Brabant, Boekel, the Netherlands; 3Behavioural Science Institute, Radboud University, Nijmegen, the NetherlandsCorrespondence: Birgit L Seelen-de LangGGZ Oost Brabant, PO Box 3, Boekel 5427 ZG, the NetherlandsTel +31 6 52612286Email bl.seelen-delang@ggzoostbrabant.nlPurpose: The Brief Negative Symptom Scale (BNSS) was developed to measure negative symptoms of schizophrenia. However, the Dutch translation of this instrument, called the “Korte Schaal voor Negatieve Symptomen” (KSNS), has not yet been validated. This study investigates the validity and reliability of this Dutch version of the instrument.Patients and Methods: The Psychotic Symptom Rating Scale (PSYRATS), Calgary Depression Scale for Schizophrenia (CDSS), the Health of the Nation Scale (HoNOS) and the KSNS were used for routine outcome monitoring to measure symptoms in 28 patients with a psychotic disorder who were being treated on a long-stay ward.Results: The internal consistency of the KSNS is fair to good. The inter-rater reliability is excellent. The concurrent validity is moderate but acceptable. The correlations between the KSNS and scales for depression and positive symptoms were not significant, which indicate good divergent validity.Conclusion: Despite the small sample size of the current study, we conclude that the BNSS, called the KSNS in Dutch, appears to be a reliable and valid tool for investigating negative symptoms in detail in patients with psychotic disorders.Keywords: BNSS, Dutch translation, negative symptoms, schizophrenia, validation
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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 | 0.009 | 0.026 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".