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Record W4229001020 · doi:10.2196/34302

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

2022· article· en· W4229001020 on OpenAlexafffundabout
Sheila Dunn, Sarah Munro, Courtney Devane, Édith Guilbert, Dahn Jeong, Eleni Stroulia, Judith A. Soon, Wendy V. Norman

Bibliographic record

VenueJournal of Medical Internet Research · 2022
Typearticle
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
FundersDepartment of Family and Community Medicine, University of TorontoCanadian Institutes of Health ResearchCollege of Family Physicians of CanadaAssociation des pharmaciens du CanadaUniversity of TorontoMichael Smith Health Research BCSociety of Family Planning
KeywordsDescriptive statisticsFamily medicineAbortionNursingMedical educationMedicine

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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): 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 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)0.073
metaresearch head score (Gemma)0.050
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0730.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.211
GPT teacher head0.591
Teacher spread0.381 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2022
Admission routes3
Has abstractyes

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