Relationship beliefs and illness appraisals are differentially associated with specific ways of coping in spouses of patients with type 2 diabetes
Bibliographic record
Abstract
Using data from 117 spouses of patients diagnosed with type 2 diabetes and multiple-group path analysis, the current study explored the association of four relationship beliefs (satisfaction, sacrifice, confidence and instability) and four diabetes appraisals (consequences, distress, control and efficacy) with illness-specific coping behaviour: active engagement, protective buffering and overprotection. The potential moderating effect of gender was also tested. Results indicated gender did moderate the associations among the variables in the model, with the association of relationship satisfaction and active engagement being significantly stronger for men, while diabetes control was more strongly related to protective buffering for women. The only variables associated with active engagement were three relationship-specific cognitions: higher levels of relationship satisfaction (for men only), satisfaction with sacrifice and relationship confidence were all related to higher active engagement. The diabetes appraisals were the only variables associated with protective buffering and overprotection. Higher diabetes distress and diabetes control (for women only) and lower diabetes efficacy were predictive of greater protective buffering. Lower diabetes efficacy and higher diabetes control were associated with greater overprotection. Implications for theory, research and practice are discussed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".