Effect of a Text Messaging–Based Educational Intervention on Cesarean Section Rates Among Pregnant Women in China: Quasirandomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Consensus exists that appropriate regional cesarean rates should not exceed 15% of births, but China's cesarean rate exceeds 50% in some areas, prompting numerous calls for its reduction. At present, China's 2016 two-child policy has heightened the implications of national cesarean section trends. OBJECTIVE: This study leveraged pervasive cellular phone access amongst Chinese citizens to test the effect of a low-cost and scalable prenatal advice program on cesarean section rates. METHODS: Participants were pregnant women presenting for antenatal care at a clinic in Xi'an, China. Assignment was quasirandomized and utilized factorial assignment based on the expecting mother's birthday. Participants were assigned to one of the following four groups, with each receiving a different set of messages: (1) a comparison group that received only a few "basic" messages, (2) a group receiving messages primarily regarding care seeking, (3) a group receiving messages primarily regarding good home prenatal practices, and (4) a group receiving text messages of all groups. Messages were delivered throughout pregnancy and were tailored to each woman's gestational week. The main outcome was the rates of cesarean delivery reported in the intervention arms. Data analysts were blinded to treatment assignment. RESULTS: In total, 2115 women completed the trial and corresponding follow-up surveys. In the unadjusted analysis, the group receiving all texts was associated with an odds ratio of 0.77 (P=.06), though neither the care seeking nor good home prenatal practice set yielded a relevant impact. Adjusting for potentially confounding covariates showed that the group with all texts sent together was associated with an odds ratio of 0.67 (P=.01). Notably, previous cesarean section evoked an odds ratio of 11.78 (P<.001), highlighting that having a cesarean section predicts future cesarean section in a subsequent pregnancy. CONCLUSIONS: Sending pregnant women in rural China short informational messages with integrated advice regarding both care-seeking and good home prenatal practices appears to reduce women's likelihood of undergoing cesarean section. Reducing clear medical indications for cesarean section seems to be the strongest potential pathway of the effect. Cesarean section based on only maternal request did not seem to occur regularly in our study population. Preventing unnecessary cesarean section at present may have a long-term impact on future cesarean section rates. TRIAL REGISTRATION: ClinicalTrials.gov NCT02037087; https://clinicaltrials.gov/ct2/show/NCT02037087. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2015-011016.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".