By on September 29, 2016

As of now, the most common method of teaching cervical examinations for women during labor includes medical students performing an examination before or after the teacher performs the same analysis. This way of teaching has the possibility to increase patient discomfort or anxiety. Additionally, prior studies have shown poor reliability with this method of instruction.

For education efforts, if given the ability to create a training model specifically for cervical examinations, this examination skill potentially could be improved and practiced before examining a laboring woman. In a recent study, 98 third-year medical students were randomized to receive cervical examination simulation training or not. The final assessment involved examinations on 10 task trainers.

The Effectiveness of Cervical Examination Simulation Training

The students who had cervical examination simulation training were more accurate in estimating cervical dilation and effacement than students without simulation training. This finding provides support that simulation models can be used to teach medical students the skill of cervical examination properly, allowing them to be competent before examining women in labor. However, this study only examined competency in an artificial model of a cervix and not women in labor. Therefore, more research needs to be done to determine how this training will improve accuracy in actual cervical examinations.

This article highlights the role that simulation can play in medical student education.

Abstract Discussed in this Article:

Nitsche JF, Shumard KM, Fino NF, Denney JM, Quinn KH, Bailey JC, et al. Effectiveness of labor cervical examination simulation in medical student education. Obstet Gynecol 2015;126:13S–20S.

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Maternal Fetal Medicine blogs are intended for educational purposes only and do not replace certified professional care. Medical conditions vary and change frequently. Please ask your doctor any questions you may have regarding your condition to receive a proper diagnosis or risk analysis. Thank you!