Loneliness in Breast Cancer Patients with Early Life Adversity: An Investigation of the Effects of Childhood Trauma and Self-Regulation
Bibliographic record
Abstract
Childhood trauma may be prevalent in the general population, and the psychosocial treatment of patients with cancer may require consideration of the effects of such early adversity on the healing and recovery process. In this study, we investigated the long-term effects of childhood trauma in 133 women diagnosed with breast cancer (mean age 51, SD = 9) who had experienced physical, sexual, or emotional abuse or neglect. We examined their experience of loneliness and its associations with the severity of childhood trauma, ambivalence about emotional expression, and changes in self-concept during the cancer experience. In total, 29% reported experiencing physical or sexual abuse, and 86% reported neglect or emotional abuse. In addition, 35% of the sample reported loneliness of moderately high severity. Loneliness was directly influenced by the severity of childhood trauma and was directly and indirectly influenced by discrepancies in self-concept and emotional ambivalence. In conclusion, we found that childhood trauma was common in breast cancer patients, with 42% of female patients reporting childhood trauma, and that these early experiences continued to exert negative effects on social connection during the illness trajectory. Assessment of childhood adversity may be recommended as part of routine oncology care, and trauma-informed treatment approaches may improve the healing process in patients with breast cancer and a history of childhood maltreatment.
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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 | 0.003 |
| 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) | 0.001 | 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".