Effects of Chinese medicine aromatherapy combined with positive thought stress reduction training in advanced cancer patients: An unrandomized quasi-experimental trial
Bibliographic record
Abstract
BACKGROUND: Pain and sleep disorders are highly prevalent in advanced cancer patients, seriously affecting their quality of life. At present, the application value of Chinese medicine aromatherapy and positive thought stress reduction training in improving patients' negative emotions and sleep disorders has been confirmed; however, its intervention role for advanced cancer patients has not yet been widely studied in China. This study investigated the effects of Chinese medicine aromatherapy combined with positive stress reduction training on pain conditions, sleep quality, and quality of life in advanced cancer patients. METHODS: This study is a quasi-experimental study, which included advanced cancer patients admitted to the oncology department of our hospital from July 2022 to December 2022 as the study subjects; the patients were categorized into control and experimental groups according to their wards, with the first ward as the control group and the second ward as the experimental group; the control group implemented the routine nursing care in the oncology department, and the experimental group implemented Chinese medicine aromatherapy combined with positive stress reduction training on the basis of the routine nursing care. McGill Pain Questionnaire Short-Form, Pittsburgh Sleep Quality Index, and Functional Assessment of Cancer Therapy were used to assess the pain, sleep quality, and quality of life before and after the intervention in the 2 groups, and were compared. RESULTS: A total of 83 patients with advanced cancer aged (59.60 ± 11.29) years completed the study. After the intervention, McGill Pain Questionnaire Short-Form and Pittsburgh Sleep Quality Index scores were lower in the experimental group than in the control group (P < .05), and Functional Assessment of Cancer Therapy scores were higher in the experimental group than in the control group (P < .05). CONCLUSION: Chinese medicine aromatherapy combined with positive stress reduction training can alleviate the pain and sleep condition of advanced cancer patients and improve their quality of life, which is worth promoting.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".