Adverse drug event surveillance systems suffer from under-reporting and lags in data-processing (Freifeld et al., 2014). Meanwhile, patients are using Twitter social media to describe adverse drug events, real-time (Bian, Topaloglu, & Yu, 2012). Nursing students with limited clinical experience learn about real-world drug use and side effects from Twitter postings, while learning common pitfalls encountered when working with data. The purpose of this pre-test/post-test experimental study was to evaluate the impact of active learning strategies designed to appeal to six student learning styles: competitive, collaborative, avoidant, participant, dependent, and independent.
Scientific advances, new technologies, and volumes of big data are strong forces influencing the role of nurses, calling for new ways of thinking and teaching. Innovative educational models are needed to prepare safe, beginning practitioners to provide evidence-based care in a complex, rapidly changing healthcare environment. Broad-based skill sets are needed as advances in science and technology continue to emerge. In this Foundations of Research & Evidence Based Practice [EBP] undergraduate course, students learn principles of the research process and gain foundational competencies for EBP, as described by Melnyk & Fineout-Overholt (2015). Using a flipped classroom approach, students apply principles of the research process by comparing Federal Adverse Event Reporting System [FAERS] data and Twitter posts, reinforcing knowledge being learned in a patho-pharmacology course where they are concurrently enrolled.
Sophomore undergraduate students (N=65) enrolled in this course completed the 60-item Grasha-Riechmann Student Learning Styles Survey to identify the most and least preferred student learning styles. During week 1, a general (Pre-test) scale was used to assess attitudes and feelings toward courses taken up to that point in college. During week 14, students were instructed to assess attitudes and feelings toward the current course after exposure to active learning activities, using a specific (post-test) scale. Students were asked to use a 5-point Likert scale to rate attitudes and feelings (e.g., 1=strongly disagree; 5=strongly agree). Paired sample t-tests were used to compare the mean scores. Cohen’s d was calculated to magnitude of the intervention’s effect on six learning styles.
Students collaborate in groups to create a basic research question involving a drug, evaluate the level of concordance between Twitter posts mentioning adverse events and reports received by the U.S. Food & Drug Administration Adverse Event Reporting System (FAERS) and generate a visual display of data (e.g. bar chart). They conduct a modified integrative review of literature and create a professional poster. Posters are displayed at the School of Nursing; faculty members vote on best posters. The winning group(s) are awarded a ribbon and invited to submit abstracts to present their poster at the College of HHS Student Research Day. Mined Twitter data was compared to data available in the FAERS dataset, to determine if events found on Twitter were consistent with adverse events reported in FAERS. At week 14, they were asked to answer three questions: what I learned, what I most enjoyed in this class, and what I would do differently if I took this course again. Professional posters were developed from an integrative literature review drawn from the PICOT question, following tips for better visual elements in posters and podium presentations .
The average time taken to complete this electronic survey was 5.8 minutes. There were statistically significant decreases on the Independent, Dependent, Competitive, and Participant Style scores. The Independent Style results were: Time 1 (M=3.38, SD=0.36), Time 2 (M=3.21, SD=0.41), t = 2.22 (63 df), p <.05; Cohen’s d (0.42) indicating a moderate effect size. Dependent Style results were Time 1 (M=3.81, SD= 0.35), Time 2 (M=3.61, SD=0.34), t=3.46 (60 df), p<.001; Cohen’s d (0.57), indicating a large effect size. Competitive Style results were: Time 1 (M=2.66, SD=0.50), Time 2 (M=2.43, SD=0.53), t=2.34 (60 df), p<.05; Cohen’s d (0.43) indicated a moderate effect size, and Participant Style results were: Time 1 (M=3.96, SD= 0.38), Time 2 (M=3.75, SD=0.44), t=2.63 (62 df), p<.05; Cohen’s d (0.50), indicating a large effect size. There was a statistically significant increase on the Avoidant Style score as follows: Time 1: (M=2.56, SD=0.54), Time 2 (M=2.87, SD=0.58), t = -3.17 (60 df), p<.05; Cohen’s d (-0.56) indicating a large negative effect size. No significant differences were note for the Collaborative Styleof learning.
Key themes emerging from the question What I learned were: drug adverse events on Twitter are not always the same as those reported in the FAERS data, importance of teamwork, professionalism, and time management, and new skills (APA formatting, Excel, Zotero, One-Drive, Microsoft online, using GroupMe for communications, conducting literature searches, mining databases). What I most enjoyed: learning the importance of EBP in nursing and how it will help me in my role as a professional nurse, working in small groups, flipped classroom and active learning methods (as opposed to lectures), trying out new software, creating a professional poster. What I would do differently: change or revise my PICOT question, proofread for details, follow instructions more closely, time management skills, delegation in groups, read more of the assigned readings, start sooner to create the poster and literature tables.
Findings from this study have clear implications for nursing faculty who desire to try active learning strategies in the classroom and are ideally suited to those teaching evidence based practice courses. The cost-effective active learning techniques used in this course were designed to help students to become savvy consumers of research, while improving student engagement and satisfaction. Skills learned in this course may be transferred into subsequent courses (e.g. Leadership & Management), serving as a foundation for higher level coursework. Posters can be presented at upcoming university Undergraduate Research Event, showcasing what nursing students are learning. Students found the projects meaningful, interesting, and of importance for their future role as professional nurses and meeting graduate-level expectations. Using Twitter, the publicly available FAERS dataset (which also includes international event reporting), and working in group projects was a popular way to reinforce knowledge needed by nurses around the world (e.g., teamwork, delegation, basic data analysis, awareness of consumer issues, time management, awareness of adverse events, including off-label use of drugs).