Do diagnostic criteria for ME matter to patient experience with services and interventions? Key results from an online RDS survey targeting fatigue patients in Norway
Bibliographic record
Abstract
Public health and welfare systems request documentation on approaches to diagnose, treat, and manage myalgic encephalomyelitis and assess disability-benefit conditions. Our objective is to document ME patients’ experiences with services/interventions and assess differences between those meeting different diagnostic criteria, importantly the impact of post-exertional malaise. We surveyed 660 fatigue patients in Norway using respondent-driven sampling and applied validated DePaul University algorithms to estimate Canadian and Fukuda criteria proxies. Patients on average perceived most interventions as having low-to-negative health effects. Responses differed significantly between sub-groups for some key interventions. The PEM score was strongly associated with the experience of most interventions. Better designed and targeted interventions are needed to prevent harm to the patient group. The PEM score appears to be a strong determinant and adequate tool for assessing patient tolerance for certain interventions. There is no known treatment for ME, and “do-no-harm” should be a guiding principle in all practice.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.072 | 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".