Comparison of Informational Needs among Newly Diagnosed Breast Cancer Women Undergoing Different Surgical Treatment Modalities
Bibliographic record
Abstract
Breast cancer is the most commonly diagnosed cancer for women worldwide. Almost all women with breast cancer will have some type of surgery in the course of their treatment either breast conservation surgery or modified radical mastectomy. Informational needs for such types of patients are critical step in providing high quality care. Aim: Comparing the informational needs among newly diagnosed breast cancer women with different surgical treatment modalities. Sample: A purposeful sample of 100 adult women with breast cancer undergoing surgery divided into two equal groups according to type of surgery. Design: Comparative descriptive design was utilized. Setting: This study was conducted at National Cancer Institute affiliated to Cairo University. Tools: Structured Interview Questionnaire and The Arabic translated version of Toronto Informational Needs Questionnaire of Breast Cancer , scored with likert scale as low, moderate and high important informational needs . The study findings revealed that newly diagnosed women with breast cancer undergoing surgery either breast conservation surgery or modified radical mastectomy were different in regard to age, marital status, residence, education, income and type of breast cancer. Although both groups had informational needs in different rates related to disease, investigative tests and treatment; they expressed that the highest informational needs was related to physical information, while the least important was related to psychosocial needs. Conclusion: information related to physical, disease, investigative tests and treatment are important needs for newly diagnosed breast cancer women regardless their type of surgery. Key words : newly diagnosed , breast cancer women, informational needs, different surgical treatment modalities.
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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 | 0.003 |
| 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) | 0.001 | 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".