Fear of recurrence in long-term cancer survivors—Do cancer type, sex, time since diagnosis, and social support matter?
Bibliographic record
Abstract
OBJECTIVE: Fear of recurrence (FoR) is among the most important concerns for cancer survivors. Studies on potentially influencing variables, like time since diagnosis, cancer type, and sex, have yielded heterogeneous results. Also social support has rarely been examined as an influencing factor. This study aims to increase knowledge on these factors. METHOD: Analyses are based on cross-sectional data of long-term survivors of breast, colorectal, and prostate cancer (5-16 years postdiagnosis), recruited by 6 German population-based cancer registries. Six thousand fifty-seven women and men were included in the analyses. FoR was assessed using the short form of the Fear of Progression Questionnaire (FoP-Q-SF). The associations of cancer type, age, sex, time since diagnosis, and social support with moderate/high FoR were identified via multiple logistic regression analyses. RESULTS: The majority of long-term cancer survivors reported experiencing FoR, mostly in low intensity. Female survivors, survivors ≤54 or 55-59 years of age, 5 to 7 years postdiagnosis, with a lower education, with recurrence/metastases, or being socially isolated were at greater risk to experience moderate/high FoR. Cancer type and stage at diagnosis did not reach statistical significance. CONCLUSION: Our results indicate a potential vulnerability for women to experience FoR in moderate/high severity. Also younger and socially isolated survivors were at greater risk to suffer from moderate/high levels of FoR and should thus be monitored for high levels of FoR and be offered the support needed to manage their fears. (PsycINFO Database Record
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".