Marital Status Predicts Change in Distress and Well-being in Women Newly Diagnosed With Breast Cancer and Their Peer Counselors
Bibliographic record
Abstract
We conducted a nonrandomized study matching 42 women newly diagnosed with breast cancer (sojourners) with 39 trained breast cancer survivors (navigators) who provided one-on-one peer counseling for 3-6 months. Because little is known about how marital status might impact participants in such an intervention, we tested whether being married/partnered buffered navigators and sojourners from distress at baseline and over time. We examined baseline and slopes over time for change in depression and trauma symptoms, and emotional well-being. We were particularly concerned that being matched with a newly diagnosed breast cancer patient might trigger a re-experiencing of trauma symptoms for the navigator, so we examined a re-experiencing subscale. All participants completed baseline, 3-, 6-, and 12-month assessments. Our hypotheses were tested in separate Analyses of Variance (married versus not) for the 39 sojourners and 34 navigators who provided baseline assessments, and the 29 sojourners and 24 navigators who were matched and provided at least one follow-up. We found no significant baseline associations for navigators or sojourners. Being single/not married was associated with increasing depression symptoms over time in both navigators and sojourners compared with being married/partnered. By 12 months, these increases crossed above the clinical cut-off for significant depression symptoms. Single status did not predict increasing trauma symptoms over time. However, being single/not married predicted a significant increase in navigators' re-experiencing of trauma symptoms. Over time, married sojourners increased significantly in emotional well-being, whereas single/not married navigators did not differ from married navigators. In addition to providing ongoing training and emotional support to navigators, our findings indicate the importance of providing additional support for women who are not married or partnered.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".