Measuring fear of cancer recurrence in survivors of childhood cancer: Development and preliminary validation of the Fear of Cancer Recurrence Inventory (FCRI)‐Child and Parent versions
Bibliographic record
Abstract
OBJECTIVE: Fear of cancer recurrence (FCR) is a common and distressing psychosocial concern for adult cancer survivors. Data on this construct in child survivors is limited and there are no validated measures for this population. This study aimed to adapt the Fear of Cancer Recurrence Inventory-Short Form (FCRI-SF) for survivors of childhood cancer aged 8-18 years (Fear of Cancer Recurrence Inventory-Child version [FCRI-C]) and their parents (Fear of Cancer Recurrence Inventory-Parent version [FCRI-P]) to self-report on their own FCR and to examine the initial psychometric properties. METHODS: = 14.58 years, SD = 2.90) and 106 parents (90% mothers). RESULTS: All FCRI-SF items were retained for the FCRI-C with simplified language. The internal consistencies of the FCRI-C (α = 0.88) and FCRI-P (α = 0.83) were good. Exploratory factor analyses yielded one-factor structures for both measures. Higher scores on the FCRI-C and FCRI-P were associated with greater intolerance of uncertainty and pain catastrophizing. Higher child FCR was also related to more hypervigilance to bodily symptoms. Parents with higher FCR reported contacting their child's doctors and nurses and scheduling medical appointments for their child more frequently. Children reported significantly lower FCR compared to parents. CONCLUSIONS: The FCRI-C and FCRI-P demonstrated strong reliability and preliminary validity. This study offers preliminary data to support the use of the FCRI-C and FCRI-P to measure FCR in survivors of childhood cancer aged 8-18 years and their parents.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".