Model of Factors Influencing Health-Related Quality of Life among Thais with Colorectal Cancer and a Permanent Colostomy
Bibliographic record
Abstract
Enhancing health-related quality of life among colorectal cancer survivors with a colostomy has become a significant concern for healthcare professionals. An understanding of factors involved in this condition and treatment, and how these work to affect the health-related quality of life of cancer survivors is a foundation for developing effective interventions. This cross-sectional study aimed to develop and test a health-related quality of life model among people with colorectal cancer and a permanent colostomy. Data were collected from 232 Thais with colorectal cancer and a permanent colostomy from six tertiary hospitals in southern Thailand by using seven instruments, including the Demographic and Health-related Data Form, the Social Support Questionnaire, the Bowel Function Inventory-Colorectal Surgery, the Center for Epidemiologic Studies Depression Scale, the Body Image Scale, the Chula ADL Index, and the Quality of Life Index-Cancer version III. Descriptive statistics and structural equation modeling were used for analyzing the data. The results indicated that the final model fitted with the empirical data and explained 72% of the variance in health-related quality of life. Three factors, carcinoembryonic antigen, gender, and age, had an indirect effect on health-related quality of life through different paths. Six factors, religion, social support, bowel symptoms, depressive symptoms, body image disturbance, and functional status, had both direct and indirect effects on health-related quality of life, with body image disturbance being the strongest effect. Nurses and other health professionals can use the findings of this study to design a comprehensive intervention to improve the quality of life for this group of patients. Such an intervention needs to target all the factors of this study, especially improving body image, functional status, and social support, and managing bowel and depressive symptoms. This intervention should be further tested in clinical practice.
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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) | 0.000 | 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 | 0.001 |
| 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".