The mediating role of illness cognitions in the relationship between caregiving demands and caregivers' psychological adjustment
Bibliographic record
Abstract
The present study investigated whether illness cognitions mediated the relationship between caregiving demands and positive and negative indicators of adjustment in partners of patients with chronic pain. The sample of this cross-sectional study consisted of 151 partners (mean age=61.4 y, SD=13.6 y, 57% male) of patients with chronic pain (eg, back pain). The study was conducted in the Pain Centre of the University Medical Centre Groningen, The Netherlands, during November 2014 to June 2015. Participants completed questionnaires that assessed caregiving demands, illness cognitions, perceived burden, distress, positive affect, and life satisfaction. The results showed that among illness cognitions, acceptance of the illness mediated the association between caregiving demands and burden (b=0.16, 95% confidence interval [CI]: 0.05-0.28) and positive affect (b=−0.21, CI: −0.41 to −0.06). Helplessness mediated the association between caregiving demands and burden (b=0.46, CI: 0.26-0.69) and distress (b=0.35, CI: 0.19-0.53). Perceived benefits did not mediate any of these associations. The findings indicate that partners who experience more demands tend to appraise the consequences of the patients’ pain condition more negatively, which in turn is associated with their emotional adjustment.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".