Psychosomatic Symptoms in Terminally Ill Cancer Patients and Its Relation With Using Complementary and Alternative Medicines: A Cross-Sectional Study in Southeast Iran
Bibliographic record
Abstract
Background Cancer patients face various problems and complications, which they address through various complementary and alternative medicines (CAM). The aim of this study was to investigate the relationship between CAM and psychosomatic symptoms in terminally ill cancer patients. Methods This cross-sectional study was performed on 221 terminally ill cancer patients (based on metastatic stage and according to the physicin diagnosis) in southeastern Iran. Convenience sampling was used to select terminally ill cancer patients. Using questionnaires like the demographic and clinical information questionnaire, Edmonton Symptom Assessment Scale (ESAS), Hospital Anxiety and Depression Scale (HADS), CAM questionnaire and satisfaction with the use of CAM, the researcher was able to compile a comprehensive picture of the population. Results The mean age of the participants was 51.66 ± 13.34 years. The majority of the samples were female, married, educated, and unemployed. The mean score for the physical symptoms of the participants according to ESAS was 22.25 ± 17.57 which was less than the midpoint of the scale (the possible score of ESAS was 0–100). Only 2.7% ( n = 6) and 0.9% ( n = 2) of the participants had mild and moderate anxiety, respectively, and the other participants' anxiety levels were normal. Only 7.7% ( n = 17) and 4.1% ( n = 9) of the participants had mild and moderate depression, respectively, and the other participants' depression levels were normal. Last year, 87.3% of the participants used at least one type of CAM. Aside from prayer, 42.1% of the participants used at least one type of CAM in the last year. Prayer was used by 83.7% of the participants, medicinal plants by 35.8%, massage by 9.5%, dietary supplements by 3.6%, wet cupping by 3.2%, relaxation and meditation by 2.7%, dry cupping by 2.4%, and acupuncture by 0.5%. The common reason for using CAM was to reduce the stress and anxiety caused by cancer and to treat it. There were no significant differences in physical and psychological symptoms between the CAM-users and non-CAM users. Conclusion Patients with cancer have a relatively low level of psychosomatic symptoms, and the primary reason for using CAM was to relieve stress and anxiety associated with cancer and treat it. However, psychosomatic symptoms were the same for CAM and non-CAM users. Because so many people with cancer use CAM, future studies should look into why and how CAM is used.
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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 | 0.001 | 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".