How Social Sharing and Social Support Explain Distress in Breast Cancer After Surgery: The Role of Alexithymia
Bibliographic record
Abstract
Perceived social support has shown to be key to adjustment along the cancer trajectory, but results remain contradictory about the disclosure of the experience of the illness (social sharing) and may reflect the importance of patients characteristics. The authors explored the associations between social sharing, perceived social support, and emotional adjustment in nonmetastatic breast cancer patients and how alexithymia may impact these associations. One hundred and thirteen women with breast cancer from a cancer care center in Villejuif (France) were assessed after breast surgery. Participants completed measures of depression, negative affect, and alexithymia together with a self-description of social sharing of their disease experience and perceived social support. Higher depression and negative affect were related to a high level of emotional sharing, a low satisfaction with confidant's reactions, and a high perceived negative support. In comparison with low-alexithymia patients, those with high alexithymia showed positive associations between negative emotional outcomes and (1) negative social support and (2) emotional sharing. These results suggest that the relationships between social sharing/support and emotional outcomes depend also on individual characteristics, such as alexithymia. Assessing perceived social support and alexithymia in cancer patients is useful to identify who might benefit from social sharing. Interventions could focus on helping the social network and environment to adjust to the socioemotional characteristics of breast cancer patients along the cancer trajectory.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".