Do Cancer-Related Beliefs Influence the Severity, Incidence, and Persistence of Psychological Symptoms?
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that negative beliefs about cancer may impair patients' psychological well-being, but only a few of these studies focused on specific psychological symptoms, and many were cross-sectional. OBJECTIVE: The aim of this study was to investigate longitudinally the relationship of cancer-related cognitions with the severity, incidence, and persistence of anxiety, fear of cancer recurrence, depression, and insomnia symptoms during an 18-month period. METHODS: Patients scheduled to undergo surgery for cancer (N = 962) completed a questionnaire assessing cancer-related cognitions at baseline (T1), the Hospital Anxiety and Depression Scale, the severity subscale of the Fear of Cancer Recurrence Inventory, and the Insomnia Severity Index at baseline (T1) and 2 (T2), 6 (T3), 10 (T4), 14 (T5), and 18 (T6) months later. RESULTS: Group × time factorial analyses using mixed models revealed that participants endorsing more negative cancer-related cognitions consistently reported more severe symptoms throughout the 18-month period. Logistic regression analyses suggested that endorsing more negative cancer-related cognitions at T1 significantly increased incidence and persistence rates of clinical levels of psychological symptoms. CONCLUSIONS: These findings suggest that the endorsement of negative cancer-related beliefs at the perioperative period influences the longitudinal evolution of anxiety, fear of cancer recurrence, depression, and insomnia symptoms in the following months. IMPLICATIONS FOR PRACTICE: These results highlight the relevance of using cognitive restructuring early during the cancer care trajectory to potentially revise erroneous beliefs about cancer and prevent the incidence and persistence of psychological disturbances over time.
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".