The Brief Symptom Inventory-9 (BSI-9): Development and validation in a German general population sample
Bibliographic record
Abstract
Abstract Background The Brief Symptom Inventory-18 (BSI-18) is a self-report questionnaire with three subscales, somatisation, anxiety, and depression, based on longer measures of distress. The present study proposes a shorter, nine-item version (BSI-9) of the BSI-18 as a brief screening tool for distress. Methods Confirmatory factor analyses and reliability and validity analyses were carried out using a representative sample of the German general population. Confirmatory factor analysis demonstrates a good model fit for the three-dimensional BSI-9. Results The total scale was found to have strong internal consistency (α Cronbach = 0.87 for the global severity index). The internal consistency coefficients of the three-item subscales reflect the brevity of these scales (somatisation α Cronbach = 0.72, depression α Cronbach = 0.79, anxiety α Cronbach = 0.68). The subscales were found to be significantly related with subscales of the Patient Health Questionnaire-4 and Hopkins Symptom Checklist-25. Limitations The present study used a limited number of distress measures, and a more recent dataset would be useful to provide a more current picture of the general population’s distress levels. Conclusions The BSI-9 provides a short, valid, and reliable screener for distress in the general population. Future work should examine its utility in clinical settings and different cultural contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".