This version may be subject to change during the production process.
The Mount Sinai Health Hackathon is designed to provide a novel forum to foster experiential team science training. Utilizing a Social Network Analysis survey, we studied the impact of the Mount Sinai Health Hackathon on the nature of collaborative relationships of hackathon participants. After the event, the number of links between participants from different disciplines increased and network density overall increased, suggesting a more interconnected network with greater interdisciplinary communication. This social network approach may be a useful addition to the evaluation strategies for team science education initiatives.
This version may be subject to change during the production process.
Background It is not known how learners feel about free open access medical education (FOAMed) as they progress through their training from medical school to fellowship. Love and breakup letter methodology (LBM) is a technique that has been used extensively in user experience technology-based research but has not previously been used in evaluating medical education tools. LBM asks participants to creatively write a “love” or “breakup” letter to a product under study to capture their thoughts and emotions when engaging with it. We conducted qualitative analysis of data from focus groups to explore how attitudes toward a learning platform change at various training stages and to broaden our understanding of how we meet learners' needs through a nephrology FOAMed tool, NephSIM. Methods Three virtual, recorded focus groups were conducted with second-year medical students, internal medicine residents, and nephrology fellows (N=18). At the start of the focus group, participants composed and read their love and breakup letters. Semistructured discussions were then led by facilitator-driven questions and peer comments. After transcription, inductive data analysis was conducted using Braun and Clarke's six-step thematic analysis. Results Four main themes were seen across all groups: attitudes toward teaching tool, perception of nephrology, learning needs and approach, and application to practice. Preclinical students positively viewed the opportunity to simulate the clinical setting and unanimously wrote love letters. Reactions from residents and fellows were mixed. Residents were interested in brevity and speed of learning, preferring algorithms and succinct approaches to meet their practice-based learning needs. Fellows' learning needs were driven by a desire to prepare for the nephrology board examination and review cases uncommonly seen in practice. Conclusions LBM provided a valuable methodology through which to identify trainee reactions to a FOAMed tool and highlighted the challenges of meeting learning needs of a continuum of trainees with a single learning platform.
OBJECTIVES/SPECIFIC AIMS: The study aims to (1) investigate the structural patterns of professional communication that exist at the Mount Sinai Health Hackathon (2) explore if and how the professional networks of the participants change after engaging in the Mount Sinai Health Hackathon (3) explore any associations between the characteristics of participants’ professional networks and successful innovation development. METHODS/STUDY POPULATION: The recruitment pool consists of all 78 Mount Sinai Health Hackathon 2018 participants. Characteristics of the social network of Health Hackathon participants are assessed via an SNA data collection instrument at three time points: T1 directly before the Health Hackathon event, T2 directly after the event, T3 six months post-event. The Icahn School of Medicine at Mount Sinai Institutional Review Board approved this study as exempt. In order to explore patterns of communication between Health Hackathon participants during event, whole network data is collected at T2. Participants are provide with a roster of Mount Sinai Health hackathon participant names and asked to report the nature, frequency and perceived importance of their interaction with each of the other participants over the duration of the 48 hour event. In order capture any network change in the wider professional networks of the individual participants, known as “ego networks”, participants are asked to complete an SNA ego network survey at time points T1, T2 and T3. Open ended questions asked participants to report up to 20 people they consider being most important to them in their professional network and record the professional background of each person, the nature of the communication and the importance of each person to their success. Finally, at T3 participants are also asked to report on their project success (determined by businesses formed, filed provisional patents, financial income generation). This will be reviewed in relation to their social network data, to see if there is any relationship between the two. Data is analyzed using the specialized SNA software, UCiNET, which creates network sociograms to visualize network data. Descriptive statistics are used to report individual-level characteristics of respondents.RESULTS/ANTICIPATED RESULTS: To describe the structural patterns of communication at each time point, the following network-level indices are calculated: density (a measure of network cohesion), degree centrality (how many connections the individual has), betweenness centrality (whether the individual provides connections to other people in a network) and closeness centrality (how close the individual is to other people in the network). Network sociograms are generated for each time point to provide a visualization of the network. To explore the hypothesis that participating in the Mount Sinai Health Hackathon increases diversity of a professional network, analysis will focus on whether and how network-level indices change pre- and post- Hackathon. It will also explore any association betw...
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