Rahul S Patel1, Tanesha Walker2, Zachary T Weber3, Sarah D Kelley4, Ryan Hansen1. 1. Counseling and Consultation Service, Office of Student Life, The Ohio State University, Columbus, Ohio, USA. 2. Department of Counselor Education, University of Toledo, Toledo, Ohio, USA. 3. College of Medicine, Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA. 4. School of Rehabilitation and Communication Sciences, Ohio University, Dublin, Ohio, USA.
Abstract
Objective: Our pilot study tests whether university counseling centers (UCC) can apply the concept of cluster analysis, and geospatial analysis to identify clusters of "hot spots". Participants: Study participants were university students who received services from a large mid-western UCC between August 2015 and July 2016. The study was approved by the University's Institutional Review Board (IRB). Data collected include demographics, address, educational level and declared major. Methods: Data analysis, conducted using SYSTAT 13.1, IBM SPSS Statistics, ArcGIS Desktop and 10.2, ArcOnline, Microsoft excel to clean and analyze demographic data. Analysis included optimized cluster analysis with a p-value < 0.05 as statistically significant. Results: 927 participants, average age was 21.6. We identified "hotspots" using cluster analysis based on age, address, and country of origin. Conclusions: Our study shows that UCCs can apply cluster analysis, and geospatial analysis to identify clusters of "hot spots" to target risk populations.
Objective: Our pilot study tests whether university counseling centers (UCC) can apply the concept of cluster analysis, and geospatial analysis to identify clusters of "hot spots". Participants: Study participants were university students who received services from a large mid-western UCC between August 2015 and July 2016. The study was approved by the University's Institutional Review Board (IRB). Data collected include demographics, address, educational level and declared major. Methods: Data analysis, conducted using SYSTAT 13.1, IBM SPSS Statistics, ArcGIS Desktop and 10.2, ArcOnline, Microsoft excel to clean and analyze demographic data. Analysis included optimized cluster analysis with a p-value < 0.05 as statistically significant. Results: 927 participants, average age was 21.6. We identified "hotspots" using cluster analysis based on age, address, and country of origin. Conclusions: Our study shows that UCCs can apply cluster analysis, and geospatial analysis to identify clusters of "hot spots" to target risk populations.
Entities:
Keywords:
College health outreach and prevention; college health utilization; college mental health geospatial analysis; college mental health outreach and prevention; college mental health utilization