Using Research and Assessment to Make Data-Informed Decisions

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Research and Data drive the training program

Effective hazing prevention starts with a clear understanding of the problem. Collecting data and using research-backed strategies allow colleges and universities to move beyond assumptions and implement targeted, evidence-based solutions. By analyzing student experiences, organizational trends, and risk factors, institutions can identify key areas for intervention, tailor educational programs to their specific campus culture, and measure the impact of prevention efforts over time. Research-driven approaches ensure that hazing prevention education is not just theoretical but practical, relevant, and results-oriented—empowering students, faculty, and administrators to make informed decisions that foster lasting cultural change.

Mental Health and Hazing Assessment

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A comprehensive hazing prevention program is most effective when it is informed by real data—especially when that data includes insights into student mental health.

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Having been completed by over 200,000 students, the Mental Health and Hazing Assessment (TM) allows colleges and universities to identify key risk factors, understand the connection between hazing and student well-being, and tailor prevention efforts to meet the unique needs of their campus community.

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By collecting and analyzing this critical information, institutions can create targeted, research-based campaigns that not only addresses hazing behaviors and norms, but also supports overall student safety and mental health. This data-driven approach ensures that prevention strategies are proactive, relevant, and capable of driving meaningful, lasting change.

privacy

Secure. Anonymous. private.

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Assessment data is collected anonymously through a secure platform. University administrators receive access to their campus results through a dedicated Qualtrics dashboard that they can access 24/7. Higher Education Institutions alse receive an annual report, and access to anonymous peer institution data for comparison.

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