Telemedicine medical abortion service in Georgia: an evaluation of a strategy with reduced number of in-Clinic visits
Bibliographic record
Abstract
Purpose To evaluate feasibility and acceptability of a medical abortion service that offers: a telemedicine visit (in place of an in-person visit) during a mandatory waiting period, and at-home follow-up with the use of multi-level pregnancy tests (MLPT).Methods Participants were screened for eligibility in clinic, and during the waiting period, received a telephone call to confirm desire to proceed with the service. Participants were mailed a study package containing mifepristone, misoprostol, two multi-level pregnancy tests, and instructions for their use. Follow-up consultation took place by phone to evaluate abortion completeness. The analysis was descriptive.Results One-hundred twenty-two participants were enrolled in the study, and 120 chose to proceed with the abortion after the waiting period and were sent a study package. One participant was lost to follow up. The majority of participants did not experience problems receiving the study package (94.1%, n = 112), took mifepristone (100%, n = 119), misoprostol (99.2%, n = 118), and MLPTs (99.1%, n = 116) as instructed, and forwent additional clinic visits (91.6%, n = 109). All participants were satisfied with the service. Most participants had a complete abortion without a procedure (95.8%, n = 114).Conclusions The adapted telemedicine medical abortion service was feasible and satisfactory to participants and has the potential to make medical abortion more patient-centered where waiting periods are mandated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".