Interest and Participation in Support Group Programs Among Patients With Colorectal Cancer
Bibliographic record
Abstract
Previous studies have demonstrated that support intervention improved quality of life and survival for patients with breast, melanoma, prostate, and gastrointestinal cancer. A standardized approach to encourage participation in support group programs among patients with colorectal cancer (CRC) had been initiated at this study site. The purpose of this study was to examine the characteristics of patients with CRC interested in this type of intervention and to identify barriers to attendance at an established patient support program. Consecutive patients with CRC were informed and encouraged to attend Wellspring, a nonprofit patient support program that offers a wide range of services. A patient survey was conducted and correlated with data on the clinical, social, and demographic characteristics of patients. Factors predictive of interest in the Wellspring support program and barriers to attendance were examined.Fifty-eight patients were eligible for this study. A total of 44 (76%) surveys were completed. Predictors of interest in patient support were age less than 65 years, encouragement from medical staff to attend, level of education, comfort in spiritual beliefs, religious affiliation, and complementary/alternative medicine use. Disease stage, gender, ethnicity, and level of social supports were not significant in this population. Although patients were routinely informed about the program in a standardized fashion, a significant proportion (36.4%) of patients did not recall receiving encouragement. Multiple logistic regression showed that level of education and recollection of encouragement from medical staff were independent predictors of interest. Although 14 patients were interested in attending (32%), only 4 ultimately attended Wellspring programs (9.1%). The most frequently cited barrier to attendance was a perception of adequate support at home, followed by living too far away, no perceived need of supports, and not feeling well.A significant proportion of patients with CRC are interested in structured support programs, but only a minority of patients ultimately participate in such programs. Further participation may be achieved by recognizing common barriers to participation and optimizing strategies to enhance attendance. Optimizing use of support services such as Wellspring has the potential to improve the effectiveness of the multidisciplinary cancer care of patients with CRC.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".