Facebook Groups as a Powerful and Dynamic Tool in Medical Education: Mixed-Method Study

Leo Nicolai, Moritz Schmidbauer, Maximilian Gradel, Sabine Ferch, Sofía Antón, Boj Hoppe, Tanja Pander, Philip von der Borch, Severin Pinilla, Martin Fischer, Konstantinos Dimitriadis, Leo Nicolai, Moritz Schmidbauer, Maximilian Gradel, Sabine Ferch, Sofía Antón, Boj Hoppe, Tanja Pander, Philip von der Borch, Severin Pinilla, Martin Fischer, Konstantinos Dimitriadis

Abstract

Background: Social networking sites, in particular Facebook, are not only predominant in students' social life but are to varying degrees interwoven with the medical curriculum. Particularly, Facebook groups have been identified for their potential in higher education. However, there is a paucity of data on user types, content, and dynamics of study-related Facebook groups.

Objective: The aim of this study was to identify the role of study-related Facebook group use, characterize medical students that use or avoid using Facebook groups (demographics, participation pattern, and motivation), and analyze student posting behavior, covered topics, dynamics, and limitations in Facebook groups with regards to educational usage.

Methods: Using a multi-method approach (interviews, focus groups, and qualitative and quantitative analysis of Facebook posts), we analyzed two representative Facebook groups of medical preclinical semesters at Ludwig-Maximilians-University (LMU) Munich. Facebook primary posts and replies over one semester were extracted and evaluated by using thematic content analysis. We developed and applied a coding scheme for studying the frequency and distribution of these posts. Additionally, we interviewed students with various degrees of involvement in the groups, as well as "new minorities," students not registered on Facebook.

Results: Facebook groups seem to have evolved as the main tool for medical students at LMU to complement the curriculum and to discuss study-related content. These Facebook groups are self-organizing and quickly adapt to organizational or subject-related challenges posed by the curriculum. A wide range of topics is covered, with a dominance of organization-related posts (58.35% [6916/11,853] of overall posts). By measuring reply rates and comments per category, we were able to identify learning tips and strategies, material sharing, and course content discussions as the most relevant categories. Rates of adequate replies in these categories ranged between 78% (11/14) and 100% (13/13), and the number of comments per post ranged from 8.4 to 13.7 compared with the average overall reply rate of 68.69% (1167/1699) and 3.9 comments per post. User typology revealed social media drivers (>30 posts per semester) as engines of group function, frequent users (11-30 posts), and a majority of average users acting rather as consumers or lurkers (1-10 posts).

Conclusions: For the moment, the medical faculty has no active involvement in these groups and therefore no influence on accuracy of information, professionalism, and ethical issues. Nevertheless, faculty could in the future benefit by extracting relevant information, identifying common problems, and understanding semester-related dynamics.

Keywords: Facebook; e-learning; faculty; medical education; networking; social media.

Conflict of interest statement

Conflicts of Interest: None declared.

©Leo Nicolai, Moritz Schmidbauer, Maximilian Gradel, Sabine Ferch, Sofía Antón, Boj Hoppe, Tanja Pander, Philip von der Borch, Severin Pinilla, Martin Fischer, Konstantinos Dimitriadis. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.12.2017.

Figures

Figure 1
Figure 1
(a) Qualitative coding scheme for preclinical year 1 (PCY1) and preclinical year 2 (PCY2) groups. Categories and subordinate categories were identified. The shaded boxes indicate categories used for quantitative coding. (b) Number of total posts (primary posts and comments) in PCY1 and PCY2, grouped into the four dominant categories.
Figure 2
Figure 2
(a) Percentage of total posts in preclinical year 1 (PCY1) and preclinical year 2 (PCY2) contributed by subgroups that posted 1 to 10 (lurkers), 11 to 30 (frequent posters), and >30 posts (social media drivers) through the course of one semester. (b) Contribution of social media drivers (>30 posts) to primary posts, comments, and overall posts (primary and comments). (c) Contribution of social media drivers to identified categories.
Figure 3
Figure 3
Number preclinical year 1 (PCY1) posts per semester week, divided into identified categories. Time axis (weeks) shows relevant semester events (arrows).
Figure 4
Figure 4
Number preclinical year 2 (PCY2) posts per semester week, divided into identified categories. Time axis (weeks) shows relevant semester events (arrows).
Figure 5
Figure 5
(a) In-detail analysis of comments per primary post, in all identified, coded categories. (b) Replies coded for percentage of constructive answers to questions in different categories.

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Source: PubMed

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