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Record W4210319946 · doi:10.2196/preprints.34302

A Virtual Community of Practice to Support Physician Uptake of a Novel Abortion Practice: Mixed Methods Case Study (Preprint)

2021· preprint· en· W4210319946 on OpenAlexaffabout
Sheila Dunn, Sarah Munro, Courtney Devane, Édith Guilbert, Dahn Jeong, Eleni Stroulia, Judith A. Soon, Wendy V. Norman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsProvincial Health Services AuthorityUniversity of AlbertaUniversité LavalCentre for Advancing Health OutcomesUniversity of British ColumbiaWomen's College HospitalWomen's Health Research InstituteUniversity of Toronto
Fundersnot available
KeywordsAbortionMedical educationFamily medicineMedicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND Virtual communities of practice (VCoPs) have been used to support innovation and quality in clinical care. The drug mifepristone was introduced in Canada in 2017 for medical abortion. We created a VCoP to support implementation of mifepristone abortion practice across Canada. OBJECTIVE The aim of this study was to describe the development and use of the Canadian Abortion Providers Support-Communauté de pratique canadienne sur l’avortement (CAPS-CPCA) VCoP and explore physicians’ experience with CAPS-CPCA and their views on its value in supporting implementation. METHODS This was a mixed methods intrinsic case study of Canadian health care providers’ use and physicians’ perceptions of the CAPS-CPCA VCoP during the first 2 years of a novel practice. We sampled both physicians who joined the CAPS-CPCA VCoP and those who were interested in providing the novel practice but did not join the VCoP. We designed the VCoP features to address known and discovered barriers to implementation of medication abortion in primary care. Our secure web-based platform allowed asynchronous access to information, practice resources, clinical support, discussion forums, and email notices. We collected data from the platform and through surveys of physician members as well as interviews with physician members and nonmembers. We analyzed descriptive statistics for website metrics, physicians’ characteristics and practices, and their use of the VCoP. We used qualitative methods to explore the physicians’ experiences and perceptions of the VCoP. RESULTS From January 1, 2017, to June 30, 2019, a total of 430 physicians representing all provinces and territories in Canada joined the VCoP and 222 (51.6%) completed a baseline survey. Of these 222 respondents, 156 (70.3%) were family physicians, 170 (80.2%) were women, and 78 (35.1%) had no prior abortion experience. In a survey conducted 12 months after baseline, 77.9% (120/154) of the respondents stated that they had provided mifepristone abortion and 33.9% (43/127) said the VCoP had been important or very important. Logging in to the site was burdensome for some, but members valued downloadable resources such as patient information sheets, consent forms, and clinical checklists. They found email announcements helpful for keeping up to date with changing regulations. Few asked clinical questions to the VCoP experts, but physicians felt that this feature was important for isolated or rural providers. Information collected through member polls about health system barriers to implementation was used in the project’s knowledge translation activities with policy makers to mitigate these barriers. CONCLUSIONS A VCoP developed to address known and discovered barriers to uptake of a novel medication abortion method engaged physicians from across Canada and supported some, including those with no prior abortion experience, to implement this practice. CLINICALTRIAL INTERNATIONAL REGISTERED REPORT RR2-10.1136/bmjopen-2018-028443

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)0.018
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.031
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0140.004
Scholarly communication0.0040.003
Open science0.0030.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.094
GPT teacher head0.479
Teacher spread0.384 · 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 designQualitative
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
Published2021
Admission routes2
Has abstractyes

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