Predictive Analytics In Mental Health Prevention for Colleges/Universities
Colleges/universities could benefit from using predictive analytics in mental health prevention. Predictive analytics is a quintessential type of advanced analysis that uses past data in conjunction with statistical modeling, data mining, and machine learning, to predict future outcomes. Predictive analytics is crucial for mental health prevention especially considering the recent wave of mental health crises on college campuses.
What is predictive analytics? Transforming data into future insights
Why Predictive Analytics?
Universities can seize the opportunity for mental health prevention through data analytics to protect their students and remain cost-effective. Further, employing predictive analytics can reduce total costs for universities making it a great option. For instance, data analytics to tackle student mental health is a much more feasible, and cost-effective solution for universities given that counseling services are “rising unsustainably” on campuses.
Additionally, in a study examining trends in college student mental health and help-seeking by race/ethnicity, students of color were reported to have significantly poorer mental health, coupled with lower rates of accessing mental health services compared to their white counterparts. These disparities can be attributed to the stigma surrounding mental health within communities of color. According to the study, topics such as depression, anxiety, or suicide are often considered taboo within communities of color, leading many students of color to refrain from using mental health services. Given the frequent emphasis on campus diversity by universities, it is their responsibility to meet a wide range of needs. Moreover, college students are often expected to self-identify their mental health issues and seek help, but such self awareness is not developmentally conducive especially among young college students. Therefore, designing preventive interventions using predictive analytics is more effective for reducing risk of mental health issues on campuses in addition to traditional treatment models.
Predictive Analytics For Chronic Stress Prevention
A compelling factor as to why universities may consider using predictive analytics for mental health prevention is how effective it has in preventing chronic health issues. Predictive analytics has transformed chronic disease management considering that “predictive analytics based on machine learning was able to identify undiagnosed Peripheral Arterial Disease with greater accuracy than the traditional gold standard risk assessment.” Thus, predictive analytics has proven to be a valuable tool for prevention. Moreover, predictive analytics has immense potential in assessing risk factors and detecting early signs of mental health issues for college students, ultimately demonstrating why universities may consider implementing it.
Predictive Analytics Can Be Revolutionary in Colleges/Universities
Implementing predictive analytics for mental health prevention will change the scope of mental health issues in higher education. Mental health challenges pose a major obstacle to one’s college readiness with nearly a third of students reporting “that mental health concerns are a reason they may choose not to attend college.” The sobering statistics underscore the urgent need for proactive intervention. By utilizing predictive analytics to identify and mitigate potential mental health issues before they escalate, we can empower students to focus on their academic goals, personal growth, and overall well-being. This approach not only fosters a more supportive and inclusive campus environment but also enables students to thrive academically and pursue their dreams without the burden of mental health struggles.
