Towards the validation of a new, blended theoretical model of fear of cancer recurrence
Bibliographic record
Abstract
OBJECTIVE: Fear of cancer recurrence (FCR) is defined as "fear, worry, or concern about cancer returning or progressing". To date, only the seminal model proposed by Lee-Jones and colleagues has been partially validated, so additional model testing is critical to inform intervention efforts. The purpose of this study is to examine the validity of a blended model of FCR that integrates Leventhal's Common Sense Model, Mishel's Uncertainty in Illness Theory, and cognitive theories of worry. METHODS: Participants (n = 106) were women diagnosed with stage I to III breast or gynecological cancer who were enrolled in a Randomized Controlled Trial of a group cognitive-existential intervention for FCR. We report data from standardized questionnaires (Fear of Cancer Recurrence Inventory-Severity and Triggers subscales; Illness Uncertainty Scale; perceived risk of recurrence; Intolerance of Uncertainty Scale; Why do people Worry about Health questionnaire; Reassurance-seeking Behaviors subscale of the Health Anxiety Questionnaire, and the Reassurance Questionnaire) that participants completed before randomization. Path analyses were used to test the model. RESULTS: Following the addition of four paths, the model showed an excellent fit (χ2 = 13.39, P = 0.20; comparative fit index = 0.99; root mean square error of approximation = 0.06). Triggers, perceived risk of recurrence, and illness uncertainty predicted FCR. FCR was associated with maladaptive coping. Positive beliefs about worrying and intolerance of uncertainty did not predict FCR but led to more maladaptive coping. CONCLUSIONS: These results provide support for a blended FCR model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".