How are you? Do people with inflammatory bowel disease experience response shift on this question?
Bibliographic record
Abstract
BACKGROUND: As individuals experience changes in their health, they may alter the way they evaluate health and quality of life. The purpose of this study is to estimate the extent to which individuals with IBD change their rating of health over time because of response shift (RS). METHODS: This is a reanalysis of a population-based longitudinal study of IBD in Manitoba, Canada (n = 388). RS was examined using trajectories of the difference between observed and predicted health. Logistic regression and dual trajectories were used to identify predictors of RS. RESULTS: Disease activity, vitality, pain, somatization, and physical and social function explained 51% of the variation in general health over two years with no evidence of RS in 82% of the sample. Negative RS was found for 8%, who initially rated health better than predicted; positive RS was found for 6%. The positive RS group was younger and had better baseline scores on measures of general health, hostility, pain, mental health and social and role function; less pain and better social function scores at baseline were predictors of negative RS. CONCLUSIONS: In conclusion, the majority of people with IBD did not demonstrate a RS indicating that the health rating over time was stable in relation to that predicted by known time varying clinical variables. This adds to the evidence that the single question on self-rated health is useful for monitoring individuals over time.
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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 | 0.003 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".