Anxiety and Symptom Assessment in Turkish Gynecologic Cancer Patients Receiving Chemotherapy
Bibliographic record
Abstract
Diagnosis and treatment procedures in cancers and resulting anxiety negatively affect the individual and the family. Particularly treatment methods may generate psychological symptoms. The aim of this study was to determine the level of such symptoms in Turkish gynecologic cancer patients receiving chemotherapy. A total of 41 patients who were referred to our gynecologic oncology research clinic between January-March 2012, receiving 3 months or more chemotherapy and who agreed to participate were enrolled in study. All the data were collected using a personal information form, Edmonton Symptom Assesment System and State-Trait Anxiety Inventory. Patients received highest point average from fatigue symptom (6.53±2.67) and lowest point average from dyspnea (1.53±3.03) according to Edmonton Symptom Assesment System. The mean State Anxiety score of patients was 43.1±9.77 and mean Trait Anxiety score was 46.7±7.01. Comparing symptoms of patients and mean State Anxiety score it was found that there was a statistically significant corelation with symptoms like pain (p<0.05), sadness (p<0.001), insomnia (p<0.05), state of well being (p<0.001) and dyspnea (p<0.05). Similarly comparing symptoms of patients and mean Trait Anxiety score demonstrated significant correlations for fatigue (p<0.05), sadness (p<0.01), insomnia (p<0.01) and state of well-being (p<0.01). As a result, patients with gynecological cancers experienced symptoms related to chemotherapy and a moderate level of anxiety. In accordance, appropriate interventions should recommended for the evaluation and improvement of anxiety and symptoms related to treatment in cancer patients.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".