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Record W3039333969 · doi:10.11575/prism/37698

Long-Acting Reversible Contraceptive Device Regulations: Lessons for Canada

2019· article· en· W3039333969 on OpenAlexaboutno aff
Brooklyn Sutton

Bibliographic record

VenueOpen MIND · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsLong-acting reversible contraceptionBusinessPolitical scienceMedicineFamily planningPopulationResearch methodologyEnvironmental health

Abstract

fetched live from OpenAlex

Unintended pregnancy rates in Canada have remained relatively stable over the past decade, even though contraceptive use has increased over the same time period. Given these statistics, it is possible that Canadians are using contraceptives inconsistently, or are using less effective contraceptive methods. For example, Long-Acting Reversible Contraceptives (LARC), such as intrauterine devices and subdermal implants, have the lowest failure rates of all currently developed reversible methods but are only used by less than five percent of female contraceptive users in Canada. Several researchers and health care professionals have suggested that increasing LARC use could have a significant impact on reducing the unintended pregnancy rate, given their high efficacy rates and minimal room for user error. However, Canadian women have limited choices when it comes to LARC products, which may influence LARC uptake. For example, no type of subdermal implant is currently available on the Canadian market, and several types of intrauterine devices are also unavailable. While there are many market factors that may affect product variety in Canada, some researchers have determined that unnecessary regulatory hurdles are largely responsible for Canada’s dearth of contraceptive products. The first step to increasing LARC uptake is to ensure that the Canadian regulatory system is properly equipped to attract and approve safe and effective LARC products. This paper examines the regulatory process in some of Canada’s peer countries—namely The United Kingdom, the United States, and Australia—in order to discover regulatory best practices for LARCs. This paper compares each country’s classification system for LARCs, the overall pathway to regulatory approval, clinical trial requirements, post-market surveillance activities, and the transparency of each country’s regulatory process. After a review of the literature, it is evident that there are many lessons to be learned from other countries’ experiences with LARC regulations. The overarching lesson is that it is imperative to include a number of voices in both the pre-market approvals process and in postmarket surveillance. Academic researchers, doctors, medical professionals, consumers, distributors, manufacturers, government officials, and international regulators all have an important role to play in upholding safety and efficacy standards. In an increasingly globalized pharmaceutical industry, Canada would do well to increase participation from each of these groups in order to reduce unnecessary regulatory hurdles for manufacturers while simultaneously protecting consumers from unsafe devices. The paper concludes with specific recommendations for Health Canada. If adopted, these recommendations will make Canada a more attractive market for LARC products while ensuring that the highest standards of safety and efficacy are upheld for Canadian contraceptive users. As a result, more LARC products will seek to enter the Canadian market, which will provide women with diverse needs and preferences with more options when it comes to selecting an effective contraceptive method.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.156
Threshold uncertainty score0.979

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.005
Science and technology studies0.0140.007
Scholarly communication0.0100.006
Open science0.0040.003
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0100.001

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 head0.070
GPT teacher head0.370
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2019
Admission routes1
Has abstractyes

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