A Randomized Control Trial of the Effectiveness of Risk Communication in Two Contraceptive Fact Sheets
Phase: NA
Conditions: Contraception, Knowledge, Attitudes, Practice
Sponsor: University of North Carolina, Chapel Hill

Testing the Impact of Two Posters on Contraceptive Knowledge, Contraceptive 
Preferences, and Perceived Pregnancy Risk 
NCT number NCT03372369 
Document Date December 22, 2017 
Primary Investigator Seri Anderson, MPH PhD 
Co-Primary Investigator Kristen Hassmiller Lich, PhD 
Co-Investigators Stephanie Wheeler, Phd; Leah Frerichs, PhD; 
Alexander Kaysin, MD; Carolyn Tucker 
Halpern, PhD 

Study Design 
We survey women before and after random administration of one of two educational posters 
informing readers about contraception. Baseline data for both groups will be collected on our 
three outcomes: contraceptive knowledge, willingness to use effective contraception, and 
perceived pregnancy risk. Participants will then be randomly shown one of the two fact sheets. 
Then post-exposure questions on the three outcomes will be asked.  
Comparators 
Shown in Figures 1 and 2 are the two posters that will be tested in this clinical trial.  
Procedures 
We will use Amazon Mechanical Turk to recruit participants.  
The survey will first be tested with N=20 participants using the procedures described below. 
This will be done to estimate the length of time necessary to complete the survey so that 
accurate time estimates can be provided to potential participants. This will also enable the 
researchers to ensure that any technical problems with the survey are corrected before the 
main research data is collected. Data collected in this phase will not be analyzed unless no 
changes are made to the study materials after reviewing the data.  
Once the survey procedures are tested, we will recruit approximately N=1000 participants to 
complete the survey (final N=990).  

 
Figure 1: CDC Contraceptive Poster 
 
 
 
 
 

Figure 2: New Contraceptive Poster
 

The study uses an online survey. Subjects will be recruited through Amazon Mechanical Turk’s 
website. Amazon Mechanical Turk is an online service, which allows individuals to post surveys 
to be completed for a small amount of money. The job posting will include a very general 
description of the study, but no indications about the eligibility criteria. If a person is interested 
in participating, they will click on a link, which will take them to a short screening Qualtrics 
survey. If the person is eligible based on the screening survey, they will be given permission to 
view and complete the full survey. Data from the screening survey will not be downloaded or 
kept. The full survey will also be posted on Amazon Mechanical Turk, with the same general 
description of the study methods. If an eligible person is interested in completing the full 
survey, they will click on the link in the posting, which will take them to the full Qualtrics survey. 
There they will see the informed consent information and will be required to give their 
informed consent before they participate in the survey. We expect that the survey will take 30 
minutes, on average, to complete.  
After completing the survey, the survey will show the participant a unique code that they can 
enter into the Amazon Mechanical Turk form. This will be used to ensure that study participants 
are compensated for completing the survey. This code will not be recorded in our data set. 
Study compensation $0.05 for the screening survey and $3.60 for the full survey. This is 
approximately equivalent to the federal minimum hourly wage, which should be a reasonable 
but not coercive incentive for participants.  
The study was approved by the University of North Carolina at Chapel Hill Institutional Review 
Board (IRB number 17-2955). 

Measures 
This study measured change in the mean scores for three primary outcomes: 
contraceptive knowledge, effectiveness of most likely contraceptive method used in the next 
year, and accuracy of perceived pregnancy risk. We gathered baseline and follow-up measures 
for each of these outcomes immediately before and after the intervention, respectively.  
Contraceptive knowledge was measured objectively using the 25-item Contraceptive 
Knowledge Assessment.1 This produced a score between 0 (0% correct) and 25 (100% correct). 
Our contraceptive knowledge outcome was the change in this score between baseline and 
follow-up.  
Effectiveness of most likely contraceptive method was operationalized using a woman’s 
intention to continue using her current contraceptive method and the contraceptive method 
she reported being most likely to switch to were she to change methods in the next year. This 
measure was intended to be a realistic measure of the contraceptive method that women were 
most likely to use in the next year. We first asked women at both baseline and follow-up: “Do 
you intend to use the same birth control method(s) that you are currently using for the next 
year?” If the woman said she intended to keep her contraceptive method(s), the effectiveness 
of the most effective method she used in the past three months was used as her most likely 
method of contraception. The effectiveness of contraceptive methods was scored using the 
following WHO-defined categories2: IUDs, implants, and sterilization were considered highly 
effective (score = 3, 0-1% annual failure rate); the pill, patch, ring, and injection were 
considered effective (2, 2-9% annual failure rate); condoms, withdrawal, fertility tracking, and 
other methods were considered less effective (1, 10-30% annual failure rate); and no method 

was its own category (0, 85% annual failure rate). If a woman said she did not intend to keep 
her current contraceptive method, we used the effectiveness of the most likely alternative 
contraceptive she would use. We measured this with the question, “If you had to change to a 
new birth control method in the next year, which of the following methods would you consider 
using?” Participants selected each method they would consider and then ranked the selected 
methods from most to least likely method. Our “effectiveness of most likely contraceptive 
method” outcome was the difference between a woman’s score at baseline and follow-up.  
Finally, accuracy of perceived pregnancy risk was assessed by comparing a woman’s 
current contraceptive method to her perceived pregnancy risk. Perceived pregnancy risk was 
measured using the following question: “What is your chance of getting pregnant this year?” 
with possible responses being very high (score = 5, annual pregnancy risk >50%), high (4, annual 
pregnancy risk 25-50%), moderate (3, annual pregnancy risk 5-25%), low (2, annual pregnancy 
risk 1-5%), and very low (1, annual pregnancy risk ≤1%). We assessed the accuracy of perceived 
risk based on the most effective birth control method a woman used in the past three months. 
In accordance with the WHO categories2, for highly effective methods, we coded an accurate 
perception to be very low risk; for effective methods, an accurate perception was low or 
moderate risk; for less effective methods, an accurate perception was moderate or high risk; for 
no method, an accurate perception was very high risk. An accurate perception was assigned a 
score of 1 and an inaccurate perception, 0. Our accuracy in perceived pregnancy risk outcome 
was the change in this score between baseline and follow-up.  
Baseline data were collected on factors that might influence these outcomes. We 
measured prospective pregnancy intentions with the question, “Are you currently trying to get 

pregnant or avoid pregnancy?”3 We measured past pregnancy scares by asking: “Have you ever 
had a pregnancy scare; that is, thought you were pregnant when you didn’t want to be, but 
later discovered that you weren’t pregnant after all?”  We measured numeracy using the Berlin 
single item numeracy scale.4 This scale has been tested and validated to show that people who 
answer this question correctly are in the top 50% of the population in numeracy.4 Data were 
also collected on the sexes of the woman’s past sex partners, whether she had ever seen the 
poster before, and whether there were any types of birth control the woman could not use for 
health/safety or cost reasons. The following variables were measured using questions from the 
National Survey of Family Growth (NSFG): biological sex, age, whether the participant was 
trying to conceive or was currently pregnant, sexual intercourse in the past three months, 
education, time since first sex, and marital status. Finally, the following variables were 
measured using questions from the National Longitudinal Survey of Adolescent to Adult Health 
(Add Health): race/ethnicity (Wave V), income (Wave IV), relationship status (Wave IV), and 
health insurance type (Wave IV).  
 
Analysis 
We first tested whether the demographic and other factors were balanced between our 
randomized groups using two-sample t-tests and likelihood-ratio tests as appropriate. We did 
not find any statistically significant imbalances for any of the variables. We conducted two-
sample t-tests on the change in the mean score for each of our outcomes to test whether each 
poster improved the three primary outcomes relative to baseline and in comparison to the 
other poster. We used the Bonferroni correction to account for multiple comparisons. Using the 

same methods, we also tested the hypothesis that the three pre-specified subgroups (low 
numeracy, pregnancy scares, and no birth control) had greater increases in their mean scores 
for the patient-centered poster versus the CDC poster. We chose these subgroups because the 
patient-centered poster was designed to appeal to the needs of these groups. Finally, because 
correct answers to some of the questions on the Contraceptive Knowledge Assessment were 
not given by either poster, we could determine the proportion of the change in contraceptive 
knowledge that was attributable to the posters. We did this by analyzing the change in 
contraceptive knowledge separately for questions that did and did not have the correct answer 
provided by either poster. All analyses were conducted in Stata (Stata/SE 15, College Station, 
TX, US). 
For our power calculations, we assumed an alpha of 1% and a power of 80%. For our final 
analysis sample of N=936, comparing the two posters we can detect a 3 percentage point 
difference in mean change in contraceptive knowledge (standard deviation of 0.181), a 0.8 
percentage point difference in accuracy of perceived pregnancy risk (standard deviation of 
0.05), and a 6 percentage point difference in the mean change in effectiveness of most likely 
contraceptive method (standard deviation of 0.355).  
References 
1. 
Haynes MC, Ryan N, Saleh M, Winkel AF, Ades V. Contraceptive Knowledge Assessment: 
Validity and reliability of a novel contraceptive research tool. Contraception. 2017; 95:190-7. 

2. 
Steiner MJ, Dalebout S, Condon S, Dominik R, Trussell J. Understanding risk: A 
randomized controlled trial of communicating contraceptive effectiveness. Obstetrics & 
Gynecology. 2003; 102:709-17. 
3. 
Schwarz EB, Lohr PA, Gold MA, Gerbert B. Prevalence and correlates of ambivalence 
towards pregnancy among nonpregnant women. Contraception. 2007; 75:305-10. 
4. 
Cokely ET, Galesic M, Schulz E, Ghazal S, Garcia-Retamero R. Measuring risk literacy: The 
Berlin numeracy test. Judgment and Decision Making. 2012; 7:25. 
5. 
Antonishak J, Kaye K, Swiader L. Impact of an online birth control support network on 
unintended pregnancy. Social Marketing Quarterly. 2015; 21:23-36.