Fear of cancer recurrence therapy (FORT): A randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: Most fear of cancer recurrence (FCR) interventions have small effects, and few target FCR. This randomized controlled trial (RCT) with breast and gynecological cancer survivors evaluated the efficacy of a cognitive-existential fear of recurrence therapy (FORT) compared to an attention placebo control group (living well with cancer [LWWC]) on FCR. METHOD: One hundred and sixty-four women with clinical levels of FCR and cancer distress were randomly assigned to 6-weekly, 120 min FORT (n = 80) or LWWC (n = 84) group sessions. They completed questionnaires at baseline (T1), posttreatment (T2; primary endpoint), 3 (T3), and 6 months (T4) posttreatment. Generalized linear models were used to compare group differences in the fear of cancer recurrence inventory (FCRI) total score and secondary outcomes. RESULTS: FORT participants experienced greater reductions from T1 to T2 on FCRI total with a between-group difference of -9.48 points (p = .0393), resulting in a medium effect of -0.530, with a maintained effect at T3 (p = .0330) but not at T4. For the secondary outcomes, improvements were in favor of FORT, including FCRI triggers (p = .0208), FCRI coping (p = .0351), cognitive avoidance (p = .0155), need for reassurance from physicians (p = .0117), and quality of life (mental health; p = .0147). CONCLUSIONS: This RCT demonstrated that FORT, compared to an attention placebo control group, resulted in a greater reduction in FCR posttreatment and at 3 months posttreatment in women with breast and gynecological cancer, indicating its potential as a new treatment strategy. We recommend a booster session to sustain gains. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".