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Record W2999401214 · doi:10.21608/asnj.2017.60623

Informational Needs among Women with Newly Diagnosed Breast Cancer: Suggested Nursing Guidelines

2017· article· en· W2999401214 on OpenAlexaboutno aff
Soheir Shayboub Sayed, Shalabia El-Sayed Abo Zead, Ghona Ali, Ahmed El-Sayed Mohamed.

Bibliographic record

VenueAssiut Scientific Nursing Journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerMedicineFamily medicineNursingCancerOncologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Women with breast cancer require information to help them manage their illness, it assists patients in making treatment decisions and managing immediate effects of treatment. Aim: To identify informational needs among women with newly diagnosed breast cancer and to design a suggested nursing guidelines. Setting: This study was conducted at the outpatient clinic of Sohag Oncology Institute and Sohag University Hospital. Sample: A conveniente sample of (100) adult female patients diagnosed with breast cancer undergoing breast surgery, radiotherapy or chemotherapy the age of patient ranged between (18-65) years old during period of 6 months. Tools: The tools were used for data collection included: An interview questionnaire, Toronto informational needs questionnaire of breast cancer. The suggested nursing guidelines was developed by the researcher. Results: The present study revealed that about (83%) of the studied patients had unsatisfactory level of knowledge regarding breast cancer. There was a statistically significant difference among chemotherapy & surgery group between total information needs and educational level.Conclusion: Women with breast cancer lack information especially about their disease, treatments and examinations they are undergoing. Recommendations: Establishment of specialized resource centers in different governerates of Egypt,rural and urban areas for meeting informational needs among women with newly diagnosed breast cancer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.001
Scholarly communication0.0020.008
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.061
GPT teacher head0.449
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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