Interpersonal communication and psychological well-being among couples coping with sensory loss: The mediating role of perceived spouse support
Bibliographic record
Abstract
Couples who are willing to discuss sensory loss-related issues typically report better well-being, while couples who avoid such discussions tend to report poorer well-being. Inspired by the relationship intimacy model, the present study examined whether the link between couples’ sensory loss-related communication and well-being can be explained by perceived spouse support and whether this mediation mechanism is stable over time. Adults with sensory loss (AWSLs) and their spouses ( N = 206 individuals) completed an online survey and were followed up 6 months later. A multi-group actor–partner interdependence mediation model was used to test the mediation mechanism as well as its stability over time. Results showed that the association between couples’ willingness to communicate about the sensory loss and psychological well-being was mediated by perceived spouse support for AWSLs only. Furthermore, this mediation effect remained stable over the 6-month period. These results support prior research that the manner in which couples communicate about the sensory loss is important for their well-being. However, because perceived spouse support was not found to mediate the association for spouses, future studies should investigate other factors as potential mediating mechanisms among spouses of adults with sensory loss.
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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 | 0.006 |
| 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 | 0.000 |
| 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".