A staging approach to measuring patient‐centred subjective outcomes*
Bibliographic record
Abstract
INTRODUCTION: In assessing clinical change, measurement is often based on psychometric scales. However, change is best revealed within the constellation of problems salient to the patient, rather than in alterations in the abstract constructs, psychometrically measured. These patients' problems often serially unfold in qualitative stages, even before the full-blown disorder emerges. These qualitative stages constitute the natural history extending from early to late, fluctuating from mild to severe, and progressing from full-blown disorder to recovery. METHOD: We reviewed the literature on clinimetrics and patient-centred subjective measures, and related these findings to the use of the discretized-analogue scaling method. RESULTS: There is increasing recognition of clinimetric approaches that structure the pre-clinical and clinical material into a scale that reflects the symptoms, consequences and complications in a manner understandable to the patient, and enabling the quantification of severity or change. This monograph provides criteria and methods for developing these building blocks that enable the assessment of severity, stage or change. We show examples of their use in quantitative clinical outcome measurement. CONCLUSION: We encourage further studies in the ideology and procedures for measuring clinical change in terms of personally subjective experiences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".