An Investigation of the Effect of Attachment on Distress among Partners of Patients with Ovarian Cancer and Their Relationship with the Cancer Care Providers
Bibliographic record
Abstract
Caregivers of patients with ovarian cancer experience distress related to caregiving difficulties within cancer care. Attachment insecurity is a well-known protector of distress, particularly as it relates to support from others. Using multivariate analyses, this study sought to determine the contribution of attachment insecurity and experiences with cancer care on symptoms of depression and anxiety, and investigated whether attachment insecurity moderated the relationship between caregiving experiences and distress. Multiple hierarchical regression analyses were conducted as part of a larger cross-sectional questionnaire study of distress among partners of patients with ovarian cancer. Participants (n = 82) were predominantly male, white, had household incomes over $100,000 and postsecondary education. Caregiving experiences explained 56% of the variance in depression, and 28% of the variance in anxiety. Specifically, lack of time for social relations as a result of caregiving significantly predicted depression and anxiety. Attachment anxiety correlated with both depression and anxiety, but attachment avoidance did not. Neither attachment anxiety nor attachment avoidance significantly contributed to distress variance, and neither moderated any of the relationships between caregiving experiences and distress outcomes. This study highlights the importance for cancer care to recognize the effect of caregiving responsibilities upon caregivers’ mental health, regardless of vulnerability to distress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".