Integrating Mobile Phones into Medical Abortion Provision: Intervention Development, Use, and Lessons Learned From a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Medical abortion is legal in South Africa but access and acceptability are hampered by the current protocol requiring a follow-up visit to assess abortion completion. OBJECTIVE: To assess the feasibility and efficacy of information and follow-up provided via mobile phone after medical abortion in a randomized controlled trial (RCT). METHODS: Mobile phones were used in three ways in the study: (1) coaching women through medical abortion using short message service (SMS; text messages); (2) a questionnaire to assess abortion completion via unstructured supplementary service data (USSD, a protocol used by GSM mobile telephones that allows the user to interact with a server via text-based menus) and the South African mobile instant message and social networking application Mxit; and (3) family planning information via SMS, mobisite and Mxit. A needs and context assessment was done to learn about women's experiences undergoing medical abortion and their use of mobile phones. After development, the mobile interventions were piloted. Recruitment was done by field workers at the clinics. In the RCT, women were interviewed at baseline and exit. Computer logs were also analyzed. All study participants received standard of care at the clinics. RESULTS: In the RCT, 234 women were randomized to the intervention group. Eight did not receive the intervention due to invalid numbers, mis-registration, system failure, or opt-out, leaving 226 participants receiving the full intervention. Of the 226, 190 returned and were interviewed at their clinic follow-up visit. The SMSs were highly acceptable, with 97.9% (186/190) saying that the SMSs helped them through the medical abortion. In terms of mobile phone privacy, 86.3% (202/234) said that it was not likely or possible that someone would see SMSs on their phone, although at exit, 20% (38/190) indicated that they had worried about phone privacy. Having been given training at baseline and subsequently asked via SMS to complete the self-assessment questionnaire, 90.3% (204/226) attempted it, and of those, 86.3% (176/204) reached an endpoint of the questionnaire. For the family planning information, a preference for SMS was indicated by study clients, although the publicly available Mxit/mobisite was heavily used (813,375 pages were viewed) over the study duration. CONCLUSIONS: SMS provided a good medium for timed, "push" information that guided and supported women through medical abortion. Women were able to perform a self-assessment questionnaire via mobile phones if provided training and prompted by SMS. Phone privacy needs to be protected in similar settings. This study may contribute to the successful expansion of medical abortion provision aided by mobile phones. TRIAL REGISTRATION: Pan African Clinical Trials Registry (PACTR): PACTR201302000427144; http://www.pactr.org/ATMWeb/appmanager/atm/atmregistry?dar=true&tNo=PACTR201302000427144 (Archived by WebCite at http://www.webcitation.org/6N0fnZfzm).
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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 | 0.048 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".