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Record W2594326394

Knowledge of and attitudes to the use of long acting reversible contraceptives among Malaysian women

2016· article· en· W2594326394 on OpenAlexaboutno aff
Kàren Morgan, A. Tan Yih Xin, N. Maneevasagam, A. Dayang Ridu Anak Dennis Gimang

Bibliographic record

VenueEuropean Health Psychologist · 2016
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsEmbarrassmentMedicineQuarter (Canadian coin)Ethnic groupFamily medicinePillGynecologyFamily planningDeveloped countryTraditional medicineDemographyPopulationResearch methodologyPsychologyNursingSocial psychologyEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Background: Long acting reversible contraceptives (LARCs) are effective methods of contraception which are less likely affected by user adherence compared to other forms of contraception. However uptake remains low in many countries. This study explored knowledge, attitudes and beliefs regarding LARCs among Malaysian women aged 18-50. Methods: A questionnaire was administered to women aged 18-50 years old in Klang Valley, Kuala Lumpur. The questionnaire assessed use of contraception, knowledge of LARC and attitudes to LARC use. Results: The majority of respondents (61.2%) had heard of LARCs. Serious side effects were a concern for a quarter (25.5%) of women and included bleeding, weight gain and permanent infertility. One third believed that other forms of contraception are more reliable and 1 in 4 women were concerned about the involvement of needles and having foreign objects in their body. A quarter of women find it embarrassing to make an appointment for LARC insertion. Younger women were more like to experience this embarrassment. Differences were noted between married and unmarried women as well as between ethnic groups. Discussion: Strategies to increase knowledge of LARC should be investigated as many misconceptions exist. Concern about side effects is of particular concern e.g bleeding among Muslims as this may impact religious practices.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.489
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.124
GPT teacher head0.391
Teacher spread0.267 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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