Assessment of Fear of Cancer Recurrence in Patients with Colorectal Cancer and Its Association with Pet Ownership: A Cross-Sectional Study
Bibliographic record
Abstract
Fear of cancer recurrence (FCR) is a frequent and distressing concern among colorectal cancer (CRC) survivors, often exerting a profound impact on psychological well-being, daily functioning, and treatment adherence. While several clinical and sociodemographic factors have been linked to FCR, the potential role of pet companionship has not been systematically investigated in this population. This cross-sectional study included 167 patients with CRC, assessing FCR with the Fear of Cancer Recurrence Inventory-Short Form (FCRI-SF), psychological distress with the DASS-21, and quality of life with the FACT-G. More than half of the participants (62.3%) met the threshold for high FCR. Multivariable logistic regression revealed that female sex, higher educational attainment, and increased depressive and anxiety symptoms were independently associated with greater odds of high FCR. Conversely, better overall quality of life was linked to lower FCR, with each additional FACT-G point reducing the likelihood of high fear by 5%. Notably, pet ownership emerged as a robust protective factor: pet owners demonstrated approximately one-quarter the odds of high FCR compared with non-owners. Subgroup analyses suggested that this protective effect was particularly evident among women and patients with fewer children, groups potentially more vulnerable to social isolation. These findings highlight pet ownership as a novel factor associated with reduced FCR in CRC patients and suggest potential directions for supportive interventions integrating companion animals into survivorship care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".