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Record W4403501043 · doi:10.3389/fgwh.2024.1401779

Aya Contigo: evaluation of a digital intervention to support self-managed medication abortion in Venezuela

2024· article· en· W4403501043 on OpenAlexafffund
Kathryn Cleverley, Anjali Sergeant, Nina Zamberlín, Susana Medina, Genevieve Tam, Roopan Gill

Bibliographic record

VenueFrontiers in Global Women s Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaQueen's University
FundersGrand Challenges Canada
KeywordsAbortionReproductive healthMedicineFamily medicineDescriptive statisticsIntervention (counseling)PregnancyNursingPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Background: Venezuela continues to face a humanitarian crisis, where healthcare is difficult to access and abortion is legally restricted. In response to a growing need for life-saving abortion and sexual and reproductive health (SRH) services, a digital application called Aya Contigo was co-developed with local partners to support self-managed medication abortion. We sought to evaluate this digital health tool among pregnant people seeking abortion in Venezuela. Methods: This is a mixed-methods pilot evaluation of Aya Contigo, a digital tool for pregnant people seeking abortion in Venezuela. From April to June of 2021, people in the first trimester of pregnancy were recruited via passive sampling. Once enrolled, participants accessed information and resources on the application and were supported by study team members over an encrypted chat. Following medication abortion, participants completed an online survey and a semi-structured interview. Descriptive statistics were used to evaluate the survey responses. Interviews were coded thematically and analyzed qualitatively with NVivo. Results: Forty participants seeking medication abortion in Venezuela were recruited to the study and given access to Aya Contigo. Seventeen completed the online survey (42.5%), with all participants identifying as women and a mean age of 28 (range 19-38; SD 5.55). Participants expressed confidence in Aya Contigo; 53% (9/17) felt "very supported" and the remaining 47% (8/17) felt "somewhat supported" by the app throughout the self-managed abortion process. The app was rated as highly usable, with an overall System Usability Scale score of 83.4/100. Thirteen respondents participated in a semi-structured phone interview, and qualitative analysis identified key themes relating to the experience of seeking abortion in Venezuela, the user experience with Aya Contigo, and the app's role in the existing ecosystem of abortion and contraceptive care in Venezuela. Discussion: This mixed-methods pilot study demonstrates that the Aya Contigo mobile application may support pregnant people seeking medication abortion and post-abortion contraceptive services in Venezuela. Participants valued the provision of evidence-based information, virtual accompaniment services, and locally-available sexual and reproductive health resources via the digital tool. Further research and interventions are needed to ensure that all pregnant people in Venezuela can access safe abortion and contraceptive resources.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.442
Teacher spread0.413 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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