Survivorship Care Plans for People with Colorectal Cancer: Do They Reflect the Research Evidence?
Bibliographic record
Abstract
AIM: In the present study, we synthesized the published literature about the psychosocial aspects of colorectal cancer (crc) survivorship to support an update of the evidentiary base of the survivorship care plans (scps) created in our jurisdiction. METHODS: The psychosocial topics identified in the crc scps created by two different initiatives in our province were used as search criteria: quality of life (qol), sexual function, fatigue, and lifestyle behaviors. An umbrella review was conducted to retrieve the best possible evidence. Only reviews that investigated the intended outcomes in crc survivors and those with moderate-to-high methodologic quality scores were included. RESULTS: Of 462 retrieved reports, eight reviews met the inclusion criteria for the synthesis. Of those eight, six investigated the challenges of crc survivors and two investigated the effect of physical activity on survivor well-being. Our results indicate that emotional and physical challenges are common in crc survivors and that physical activity is associated with clinically important benefits for the fatigue and physical functioning of crc survivors. CONCLUSIONS: Our study findings update the evidence and indicate that existing scps in our province concerning the physical and emotional challenges of crc survivors reflect the evidence at the time of their issue. However, the literature concerning cancer risks specific to crc survivors is lacking. Although systematic reviews are considered to be the "gold standard" in knowledge synthesis, our findings suggest that much remains to be done in the area of synthesis research to better guide practice in cancer survivorship.
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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 | 0.150 | 0.522 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".