Barriers and facilitators to telemedicine contraception among patients that speak Spanish: a qualitative study
Bibliographic record
Abstract
Background: Telemedicine contraception services have increased since the COVID-19 pandemic. There may be unique equity implications and language barriers for patients who speak Spanish. Objective: To identify the barriers and facilitators of telemedicine for contraception care among patients who speak Spanish using a community-based participatory research approach. Study Design: The study was designed and conducted in consultation with a community advisory board. We interviewed 20 patients after telemedicine and in-person contraception visits conducted in Spanish at Planned Parenthood of the Pacific Southwest in Southern California between April 2022 and May 2023. Telemedicine visits were conducted by audio only. Two coders analyzed the data using thematic analysis. Results: The average age of the participants was 32.5 years old (range 19-45). Most participants had some college education (13/20, 65.0%) and public insurance (18/20, 90.0%). Most chose a short-acting contraceptive method (11/20, 55.0%). Five key themes were identified. (1) Participants reported less comfort with video technology and a preference to not be seen during the appointment, therefore preferring audio-only for telemedicine visits. (2) Participants did not report difficulty with Spanish interpreters using telemedicine. (3) Telemedicine has conveniences related to time, work, childcare, and transportation but may have inconveniences related to method receipt. (4) Preference for physical exam and preventative care and familiarity with the in-clinic model motivated people who sought in-person care rather than technology barriers with telemedicine. (5) There is trust in the privacy and confidentiality of the visits, but privacy at home for the individual may impact choice for in-person care. Conclusion: Among patients who speak Spanish, telemedicine contraception care was acceptable and had many conveniences. Many patients who speak Spanish preferred audio-only for telemedicine contraception visits. Use of interpreters and technology were not perceived barriers to care.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".