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Record W2483820676 · doi:10.14419/ijans.v5i2.6312

Awareness among glaucoma patient at upper Egypt

2016· article· en· W2483820676 on OpenAlexaboutno aff
Magda Mansour, Nermeen Mahmoud Abd El-Aziz, Mimi Mekkawy, Rania Mohammed Ahmed

Bibliographic record

VenueInternational Journal of Advanced Nursing Studies · 2016
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlaucomaResidenceOutpatient clinicFamily medicineSignificant differenceOptometryQuarter (Canadian coin)Sample (material)OphthalmologyDemographyInternal medicine

Abstract

fetched live from OpenAlex

Aim: To assess the awareness among glaucoma patients at Upper Egypt Governorate hospitals.Research design: Descriptive cross sectional research design was used in this studySetting: The study was conducted in ophthalmology outpatient clinics (male & female) at Assiut University Hospital & Al-rmad Hospital, Elmina and Sohag Governorate.Subjects: The sample of this study total coverage of glaucoma patients included (1000), the researcher taking the sample during one year, this sample aged 50 years and above.Tool of study: One tool was used in this study include three parts, part I: patient demographic characteristics, part II: medical data, part III: knowledge about risk factors and self-practice regard glaucoma.Results: The most of patients age ranged between 60:80 year, nearly three quarter (74.6%) of them were females, and 80% of them comes from urban areas. The majority of studied sample (84.5%) unaware about glaucoma disease and show statistical significant difference between awareness of them and their education, P≤0.05. Also, there was no significant difference between knowledge of studied sample and their residence.Conclusion: The majority of glaucoma patients complain from poor of knowledge & practice.Recommendation: Design & implement of health educational program about glaucoma are needed to improve patient knowledge & practice regard glaucoma.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.334
Teacher spread0.320 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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