Measurement invariance of the Illness Intrusiveness Ratings Scale's three-factor structure in men and women with cancer.
Bibliographic record
Abstract
OBJECTIVE: Illness- and treatment-related disruptions to valued activities and interests (illness intrusiveness) are central to quality of life in chronic disease and are captured by three subscales of the Illness Intrusiveness Ratings Scale (IIRS): the Instrumental, Intimacy, and Relationships and Personal Development subscales. Using individual (CFA) and multisample confirmatory factor analyses (MSCFA), we evaluated measurement invariance of the IIRS's 3-factor structure in men and women with cancer. METHOD: Men (n = 210) and women (n = 206) with 1 of 4 cancer diagnoses (gastrointestinal, head and neck, lymphoma, lung) recruited from outpatient clinics completed the IIRS. In the MSCFA, we applied an analysis of means and covariance structures approach to test increasingly stringent equality constraints on factor structure parameters to evaluate weak, strong, and strict measurement invariance of the 3-factor structure between men and women. RESULTS: Individual CFAs demonstrated fit of the hypothesized 3-factor structure for men and women, although more consistently for men. The 3-factor structure was superior to an alternative 1-factor structure. MSCFA results indicated that parameters of the 3-factor structure could be considered equivalent between the sexes up to the level of strong invariance. Strict invariance was not supported. CONCLUSIONS: Overall, IIRS scores can be interpreted similarly for men and women with cancer. Illness intrusiveness can be considered as important in the psychosocial adaptation of people with cancer as it is for people affected by other chronic conditions.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".