Trial reportContraception2017
Does information about abortion safety affect Texas voters' opinions about restrictive laws? A randomized study.
Trial report in Contraception, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Women's knowledge of their state's abortion regulations. A national survey.Contraception · 2020Article
- The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias.Journal of medical Internet research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveThe objective was to assess whether information about abortion safety and awareness of abortion laws affect voters' opinions about medically unnecessary abortion regulations. STUDY
designBetween May and June 2016, we randomized 1200 Texas voters to receive or not receive information describing the safety of office-based abortion care during an online survey about abortion laws using simple random assignment. We compared the association between receiving safety information and awareness of recent restrictions and beliefs that ambulatory surgical center (ASC) requirements for abortion facilities and hospital admitting privileges requirements for physicians would make abortion safer. We used Poisson regression, adjusting for political affiliation and views on abortion.
resultsOf 1200 surveyed participants, 1183 had complete data for analysis: 612 in the information group and 571 in the comparison group. Overall, 259 (46%) in the information group and 298 (56%) in the comparison group believed that the ASC requirement would improve abortion safety (p=.008); 230 (41%) in the information group and 285 (54%) in the comparison group believed that admitting privileges would make abortion safer (p<.001). After multivariable adjustment, the information group was less likely to report that the ASC [prevalence ratio (PR): 0.82; 95% confidence interval (CI): 0.72-0.94] and admitting privileges requirements (PR: 0.76; 95% CI: 0.65-0.88) would improve safety. Participants who identified as conservative Republicans were more likely to report that the ASC (82%) and admitting privileges requirements (83%) would make abortion safer if they had heard of the provisions than if they were unaware of them (ASC: 52%; admitting privileges: 47%; all p<.001).
conclusionsInformational statements reduced perceptions that restrictive laws make abortion safer. Voters' prior awareness of the requirements also was associated with their beliefs. IMPLICATIONS: Informational messages can shift scientifically unfounded views about abortion safety and could reduce support for restrictive laws. Because prior awareness of abortion laws does not ensure accurate knowledge about their effects on safety, it is important to reach a broad audience through early dissemination of information about new regulations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.