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Record W2347162729 · doi:10.12669/pjms.316.8127

Emergency contraception: Awareness, attitudes and barriers of Saudi Arabian Women

2015· article· en· W2347162729 on OpenAlexfundno aff
Syed Irfan Karim, Farhana Irfan, Norah Al Rowais, Dr . Basma Al Zahrani, Riaz Qureshı, Bedoor H. Al Qadrah

Bibliographic record

VenuePakistan Journal of Medical Sciences · 2015
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
FundersDeanship of Scientific Research, King Saud UniversityUniversity of TorontoKing Saud University
KeywordsMedicineEmergency contraceptionMedical prescriptionFamily medicineIslamHealth professionalsHealth careFamily planningNursingPopulationEnvironmental healthResearch methodology

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess knowledge, attitude, and barriers about emergency contraception (EC) among married women of child bearing age. METHODS: A quantitative cross-sectional study was conducted over a 6-month period, commencing in March 2013 at Family Practice Clinics of King Khalid University Hospital (KKUH), Riyadh, Saudi Arabia. Data was collected using a structured pretested questionnaire and analyzed using SPSS version 21.0 statistical software. RESULT: A total of 242 women were enrolled in the study. Only 6.2% (15/242) had some knowledge of EC and of these only two had ever used it. Health care professionals were the least reported source of EC information (6.6%, n=1). Majority (73.3%) had negative attitude toward EC being available over-the-counter without a prescription. The most common barriers to using EC were concerns about possible health effects. Only two women (13.3%) considered religious belief as a major hindrance to its use. CONCLUSION: Awareness of emergency contraception is very low among women of Saudi Arabia. Health care professionals were the least reported source of information, which is a cause for concern. Our findings reveal an urgent need to educate women about EC, keeping in view the social norms and the Islamic values.

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)0.002
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 score0.045
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.397
Teacher spread0.341 · 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

Citations32
Published2015
Admission routes1
Has abstractyes

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