Explaining Medically Unexplained Symptoms
Bibliographic record
Abstract
Patients with medically unexplained symptoms comprise from 15% to 30% of all primary care consultations. Physicians often assume that psychological factors account for these symptoms, but current theories of psychogenic causation, somatization, and somatic amplification cannot fully account for common unexplained symptoms. Psychophysiological and sociophysiological models provide plausible medical explanations for most common somatic symptoms. Psychological explanations are often not communicated effectively, do not address patient concerns, and may lead patients to reject treatment or referral because of potential stigma. Across cultures, many systems of medicine provide sociosomatic explanations linking problems in family and community with bodily distress. Most patients, therefore, have culturally based explanations available for their symptoms. When the bodily nature and cultural meaning of their suffering is validated, most patients will acknowledge that stress, social conditions, and emotions have an effect on their physical condition. This provides an entree to applying the symptom-focused strategies of behavioural medicine to address the psychosocial factors that contribute to chronicity and disability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".