Context moderates illness‐induced lifestyle disruptions across life domains: a test of the illness intrusiveness theoretical framework in six common cancers
Bibliographic record
Abstract
The illness intrusiveness theoretical framework maintains that illness-induced lifestyle disruptions compromise quality of life in chronic life-threatening conditions and that this effect is moderated by social, psychological, and contextual factors. Considerable evidence indicates that lifestyle disruptions compromise quality of life in cancer and other diseases and that the effects differ across life domains. The hypothesis that contextual factors (e.g. age, education, income, stressful life events) moderate these effects has not been tested extensively. We investigated whether age, income, education, and/or recent stressful life events modify the experience of illness intrusiveness across three central life domains (Relationships and Personal Development, Intimacy, and Instrumental life) in six common cancers. A sample of 656 cancer outpatients with one of six common cancers (breast, prostate, lymphoma, lung, head and neck, and gastrointestinal, all n's>100) completed the Illness Intrusiveness Ratings Scale while awaiting follow-up appointments with an oncologist. Results indicated statistically significant (all p's<0.05) interactions involving each of the hypothesized moderator variables and the Life Domain factor. In each case, greatest divergence was evident when illness intrusiveness involved instrumental life domains (e.g. work, finances, health, and active recreation). The findings substantiate the illness intrusiveness theoretical framework and support its relevance for people with cancer. The psychosocial impact of chronic life-threatening disease differs across life domains and depends on the context in which it is experienced.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".