Fear of cancer recurrence among Brazilian patients with cancer: Translation and cultural adaptation of FCR4/7 and FCRI-SF measures
Bibliographic record
Abstract
OBJECTIVE: Fear of cancer recurrence or progression (FCR) is considered one of the most common unmet needs among patients with cancer. This study sought to translate and evaluate the psychometric properties of the Fear of Cancer Recurrence scale (FCR4/7) and Fear of Cancer Recurrence Inventory-Short Form (FCRI-SF). METHODS: This study involved three phases: (1) translation and cultural adaptation of the FCR4/7 and FCRI-SF measures, (2) validity and reliability testing of the Portuguese version of these measures, and (3) examining patient's perceptions of these measures. Eligible patients were diagnosed with localized breast cancer, and patients with metastatic cancer. Descriptive analyses were collated, and psychometric analysis were conducted (confirmatory factor analysis). RESULTS: A total of 200 patients were recruited (100 patients with localized and 100 patients with metastatic cancer). A significant proportion of patients reported moderate to severe FCR (FCR7: 32.0% and FCRI-SF: 43.0%). Female gender, younger age and metastatic cancer were associated with higher levels of FCR. Psychometric analyses suggested that the Portuguese versions of the FCR4/7 and FCRI-SF were valid, unidimensional in nature, with acceptable reliability coefficients across all scales. In a sub-sample qualitative analysis (n = 75), most patients were satisfied with the relevance of both measures. CONCLUSION: Our findings suggest the Portuguese versions of the FCR4/7 and FCRI-SF are valid tools to assess FCR among patients with localized and metastatic cancer. Future research can now extend our understanding of FCR and assess this construct among Portuguese speaking patients, to guide the development of effective and targeted interventions for patients globally.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".