Clusters of Psychological Symptoms in Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Breast cancer patients tend to experience numerous concurrent psychological symptoms that form clusters. It has been proposed that a common psychological mechanism may underlie the membership of symptoms in a given cluster, but this hypothesis has never been investigated. Maladaptive emotion regulation (ER) is one possible common mechanism. OBJECTIVE: This study examined cross-sectional and prospective relationships between subjective (experiential avoidance, expressive suppression, and cognitive reappraisal) and objective (high-frequency heart rate variability) measures of ER and clusters of psychological symptoms among women receiving radiation therapy for breast cancer. METHOD: A total of 81 women completed a battery of self-report scales before (T1) and after (T2) radiotherapy, including measures of anxiety, depression, fear of cancer recurrence, insomnia, fatigue, pain, and cognitive impairments. Resting high-frequency heart rate variability was measured at T1. RESULTS: Latent profile analyses identified between 2 and 3 clusters of patients with similar levels of symptoms at T1 and T2 and with a similar profile of symptom changes between T1 and T2. Discriminant analyses showed that higher levels of avoidance and suppression predicted membership in symptom clusters that included more severe symptoms cross-sectionally at T1 and at T2 (both P values < .0001). However, ER at T1 did not significantly predict membership in clusters of symptom changes between T1 and T2 (P = .15). CONCLUSION: Maladaptive ER strategies, more particularly suppression and avoidance, are a possible psychological mechanism underlying clusters of cancer-related psychological symptoms. IMPLICATIONS FOR PRACTICE: Psychological interventions targeting maladaptive ER strategies have the potential to treat several psychological symptoms simultaneously.
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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 | 0.000 | 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 | 0.000 |
| 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 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".