Relationships among current alexithymia, social relational quality and quality of life in breast cancer patients after chemotherapy
Bibliographic record
Abstract
Objective To investigate the relationships among current alexithymia, social relational quality and quality of life in breast cancer patients receiving chemotherapy. Methods By convenient sampling method, from April 2015 to September 2016, totally 151 patients were invited to complete demographic questionnaire, Toronto alexithymia scale, social relational quality scale and functional assessment of cancer therapy-breast. The Pearson correlation method was used to analyze the relationship among current alexithymia, social relational quality and quality of life. Results All of the patients got the average score (59.11±15.75) on Toronto alexithymia scale, which was moderate level. The total scores of social relational quality and life quality were (53.45±5.13) and (93.84±15.17) . There was a negative relationship between alexithymia with social relational quality (r=-0.441) and quality of life (r=-0.597) (P<0.05) . Conclusions Breast cancer patients has serious alexithymia after the operation. Nurses can carry out activities which gives patients more opportunities to express emotion, encourage patients to face difficulties and challenges, communicate with others actively, and get more support from others and encourage family members participate in the patient care process to reduce alexithymia and improve quality of life. Key words: Breast neoplasms; Antineoplastic combined chemotherapy protocols; Quality of life; Alexithymia; Social relational quality
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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 | 0.002 |
| 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".