The impact of diagnostic method on sense of control and powerlessness and social support in endometriosis patients — A retrospective cohort study
Bibliographic record
Abstract
Objectives: To determine the impact of the diagnostic test method (clinical, diagnostic imaging, or diagnostic laparoscopy) of endometriosis on the individual’s sense of control over their disease and their perceived access to social supports. Design: Retrospective cohort study. Setting: International. Population: 1,634 people aged 18-55 who had received a diagnosis of endometriosis. Methods: This study reports on data collected by the validated Endometriosis Health Profile-30 (EHP-30) section of a larger survey conducted between May and July 2020. Participants were recruited by social media platforms. Scores on the dimensions of interest were analysed with diagnostic method as the variable of interest. Diagnostic method proportionality was also assessed as a secondary outcome by geographical region. Main Outcome Measures: Scores on the dimensions of control and powerlessness and social support on the EHP-30. Results: There was a difference between control and powerlessness scores for patients that received a diagnosis via imaging (ultrasound/magnetic resonance imaging) versus clinical diagnosis (P=0.049). However, this did not reach significance when co-variates were controlled for (P=0.054). No other comparisons between diagnostic method and EHP-30 scores demonstrated a difference. There was a statistically significant (P<0.0001) difference in the rate of utilization of the various diagnostic imaging techniques between geographical regions with diagnostic imaging being relatively uncommon and surgery being the most common method of diagnosis. Conclusions: The diagnostic method of endometriosis does not appear to have a clinically significant impact on an individual’s sense of control over their disease nor their access to social supports.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".