Fibromyalgia: can one distinguish it from simulation? An observer-blind controlled study.
Bibliographic record
Abstract
OBJECTIVE: A randomized controlled trial was conducted to assess reliability and accuracy in identification of fibromyalgia (FM), motivated simulation, and normal controls. METHODS: Eight female subjects with chronic FM were age matched with 19 healthy female volunteers. The volunteers were randomized to a financially motivated "simulator" group who were paid to simulate FM, or to a "normal control" group. Examiners under blinded conditions rated tender and control points, and illness behavior. Intraclass correlation coefficients and F values showed that counts of tender points significantly discriminated the 3 groups. Variance was mostly due to experimental groups and not to observer or error factors. In this study, simulators could not be discriminated from normals or FM subjects on the basis of tenderness at "control points." Examiner ratings of illness behavior (UAB), and subjects' self-ratings for pain showed that FM subjects had the highest scores, normals the lowest, and simulators had mean scores midway between the mean FM and simulator. On grip strength, the normals obtained the highest scores, the simulators the lowest, and the FM subjects had scores midway between those of the other 2 groups. Diagnostic accuracy of the blinded examiners in distinguishing FM from simulators and from normals was 80%, and for correct diagnosis the kappa value was significant at 0.69. Despite this, simulators were misidentified as FM in 1/3 of judgments, and FM was misidentified as simulators in 1/5 of judgments. CONCLUSION: Under randomized blinded conditions, examiners using the American College of Rheumatology criteria for FM and other bedside observations are able to distinguish chronic FM, normal individuals, and motivated simulators with 80% accuracy, with a good level of agreement and reliability in tender point counts. Our results do not provide a "test for malingering," and it is likely that an important minority of motivated simulators and of FM subjects will be misidentified.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".