A quality improvement project to optimize access to psychosocial care for cancer survivors who experience fear of recurrence
Bibliographic record
Abstract
BACKGROUND: The prevalence of moderate to high levels of fear of cancer recurrence (FCR) in cancer survivors may vary from 22% to 87%, although most are not usually referred to psychosocial support. The After Cancer Treatment Transition (ACTT) clinic in Women's College Hospital (Toronto) provides follow-up care to cancer survivors but in a sample of 2893 patients seen April 2019 to March 2022, only 1.5% were referred to a social worker for psychosocial needs. A single-question screening tool is currently available to screen for FCR. OBJECTIVE: To evaluate the use of the single-question screening tool for FCR among cancer survivors and its impact on social work referrals. RESULTS: Between July and October 2022, 788 patients were seen in the ACTT clinic. Generally, most patients in ACTT are breast cancer survivors (75%), and the remaining survivors are a mix of other cancer types (colorectal cancer, ovarian cancer, thyroid cancer, melanoma). Three hundred thirty (41.9%) ACTT patients completed the single-question screening tool for FCR. Most screened patients were female (96%), the average age was 60 years, and most were diagnosed with breast cancer (90%). Among screened patients, 37 (11%) indicated a moderately severe to high level of FCR and efforts were made to refer these 37 patients to a social worker. In the end, 22 (59.5%) patients with moderately severe/high levels of FCR were offered and accepted referral to a social worker. In comparison to the 1.5% referred to social work (among 2893 patients) prior to FCR screening, referrals increased to 6.7% (among 330 screened). CONCLUSION: Use of a single-question FCR screening tool improved identifying cancer survivors in need of psychosocial support and improved access to a social worker.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".