A Cluster Within the Continuum of Biopsychosocial Distress Can Be Labeled “Fibromyalgia Syndrome” — Evidence from a Representative German Population Survey
Bibliographic record
Abstract
OBJECTIVE: We tested the hypothesis that "fibromyalgia syndrome" is a biopsychosocial continuum disorder. METHODS: A cross-sectional survey of a representative sample of the German general population with persons >or= 14 years of age was conducted based on face-to-face contacts. Physical distress was measured by the regional pain scale (RPS) and the Patient Health Questionnaire 15 (PHQ-15), psychological distress by the PHQ-9, and social distress by the Oslo Social Support Scale. Health-related quality of life (HRQOL) was measured by the 12-item form of the Medical Outcome Study Short Form Health Survey. A k-means clustering procedure with 2-8 clusters preset was used to classify the scores of the RPS, PHQ-9, and PHQ-15. The number of clusters retained was based on the stability and interpretability of the clusters. The cluster analysis was first performed with a randomly selected half of the sample and then cross-validated on the second half of the total sample. RESULTS: A 4-cluster solution produced the most stable and meaningful results. Cluster 1 was very low on all symptom scores. Cluster 2 was low on pain sites, somatic symptoms, and depression. Cluster 3 was high on pain scores, moderate on somatic symptoms, and low on depression. Cluster 4 was high on all symptom scores. The centroids of cluster 4 met the survey criteria of fibromyalgia syndrome. Cluster 4 reported a lower HRQOL and less social support compared to the other 3 groups. CONCLUSION: A cluster within the continuum of biopsychosocial distress can be labeled fibromyalgia syndrome.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".