Effectiveness of Virtual and In-person Methods of Education on Pregnant Women’s Satisfaction With Childbirth Preparation Classes: A Pilot Study

Childbirth preparation classes are among the most important components of pregnancy education. This pilot study was conducted to compare the level of satisfaction of pregnant women from holding childbirth preparation classes using two methods of virtual and in-person training. 

This is a quasi-experimental post-test pilot study that was performed on 30 nulliparous women in Milad Hospital affiliated with Iran’s Social Security Organization, Tehran, Iran from September 2019 to June 2020. The subjects were recruited by convenience sampling and then were assigned voluntarily to two groups of virtual (n=15) and in-person (n=15) training. Both groups received the same educational content on childbirth preparation at 20 to 37 weeks of pregnancy. The virtual educational content was designed based on Mayer’s multimedia principles and shared through the Telegram application. The courses were held in eight 2-hour sessions. The satisfaction questionnaire was completed by the participants at 36-38 weeks of pregnancy. The significance level was set at P≤0.05. 

There was a significant difference between the total score of satisfaction with childbirth preparation courses between the virtual group compared to the in-person training group (P=0.028). Also, the results showed that the virtual group was able to significantly attract the spouse’s participation in accepting the role of parent compared to the in-person group (P=0.05). Also, 100% and 46.7% of the virtual and in-person groups, respectively, were completely satisfied with the way the educational content was presented (P<0.01).

Considering the greater satisfaction of pregnant women with virtual training compared to in-person training and its important role in attracting the participation of the spouse and considering that in-person classes are held as a national routine, virtual classes are recommended to be held alongside in-person classes. It is also recommended to use a larger sample size and random allocation in future studies.