Revision of the fear of cancer recurrence cognitive and emotional model by Lee‐Jones et al with women with breast cancer
Bibliographic record
Abstract
Abstract Background Fear of cancer recurrence (FCR) is among the top unmet concerns reported by breast cancer survivors. Despite the sizable literature on FCR, few theoretical models have been empirically tested. One of the most cited is the FCR model. Aim This study seeks to understand the nature of women's cognitive and emotional issues from FCR using specific guidance from the model by Lee‐Jones and to provide suggestions for modifications to the model based on empirical results from the reported experiences of women living with breast cancer. Methods and results A qualitative descriptive study using semi‐structured interviews was conducted at an urban hospital. Recruited by convenience sampling, 12 breast cancer survivors concerned with FCR and who had recently completed active treatment participated in the study. Seven thematic categories emerged from the women's descriptions of their cognitive and emotional experiences with FCR: (a) FCR is always there; (b) beliefs about risk of recurrence; (c) beliefs about eradication of cancer; (d) preferences not to seek information about recurrence; (e) derailment of normal life; (f) worries related to recurrence; and (g) need for support. Adjustments to the model by Lee‐Jones et al1 specifically to women living with breast cancer include the addition of new variables—the fear is always present, a preference not to seek information, and the need for support beyond treatment—and the merging of two variables, anxiety and worry, as participants viewed these concepts as interchangeable and experienced in similar ways. Lastly, participants did not report any remorse related to not opting for more aggressive treatments. Conclusion The refinement of a more comprehensive FCR theoretical model, such as through the modifications derived from this study, provides a deeper understanding of breast cancer survivors' experiences with FCR and can more effectively guide health care professionals to develop appropriately tailored interventions aimed at decreasing FCR levels.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| 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".