Information Needs of Patients With Breast Cancer Undergoing Treatment in Vietnam and Related Determinants
Bibliographic record
Abstract
BACKGROUND: Patients with cancer who are not well informed often experience dissatisfaction with care, difficulty coping with their disease, and feelings of helplessness. PURPOSE: This study was designed to investigate the information needs of women with breast cancer undergoing treatment in Vietnam and the determinants of these needs. METHODS: One hundred thirty women undergoing chemotherapy for breast cancer in the National Cancer Hospital in Vietnam enrolled as volunteers in this cross-sectional descriptive correlational study. Self-perceived information needs, body functions, and disease symptoms were surveyed using the Toronto Informational Needs Questionnaire and the 23-item Breast Cancer Module of the European Organization for Research and Treatment of Cancer questionnaire, which consists of two (functional and symptom) subscales. Descriptive statistical analyses included t test, analysis of variance, Pearson correlation, and multiple linear regression. RESULTS: The results revealed participants had high information needs and a negative future perspective. The highest information needs related to potential for recurrence, interpretation of blood test results, treatment side effects, and diet. Future perspective, income level, and educational level were identified as determinants of information needs, explaining 28.2% of the variance in the need for breast cancer information. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: This study was the first to use a validated questionnaire to assess information needs in women with breast cancer in Vietnam. Healthcare professionals may refer to the findings of this study when designing and delivering health education programs designed to meet the self-perceived information needs of women with breast cancer in Vietnam.
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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 | 0.004 |
| 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) | 0.002 | 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".