Women who coped successfully with progressive MS learned to confront their diagnosis and live with its unpredictable changesCommentary
Bibliographic record
Abstract
How are 7 precursors of change expressed in women who are coping effectively with progressive multiple sclerosis (MS), and how do they change in intensity over time? Qualitative study. A midwestern state in the USA. 10 women who were 46–68 years of age (mean age 56 y); had progressive-relapsing, secondary progressive, or primary progressive MS for ⩾8 years (mean 17 y); did not have current major depression; and were assessed (by self or physician) as coping successfully with the disease. For each precursor of change, women were asked about the intensity of the precursor currently and at diagnosis, and to account for the change between the time of diagnosis and now. Interviews were transcribed and analysed thematically. Expressions of each of the 7 precursors to change are described. (1) Sense of necessity. Women felt a sense of necessity more intensely at the time of diagnosis; they urgently wanted to know what was going to happen to them. This feeling subsided with time as they learned how the disease changed from day to day. They learned to accept it. (2) Willingness to experience anxiety or difficulty. This precursor was stronger at …
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".