Modeling Overview

After realizing that anyLogic did not fit our needs, we moved to Simscript to create a simulation with a series of barriers that might prevent students from going to Let’s Talk. The first three barriers are independent of student characteristics.



The first barrier to narrow down the population was student willingness to use a mental health resource. Many people on campus are very willing to use resources to get help, however there is a small minority that is completely opposed to receiving help with these issues and we used willingness as a general first barrier to seeking assistance.


The second barrier is the “self-stigma” restriction. This barrier filters people who say they would be willing to use mental health resources, but if or when they actually need one they do not seek help due to their own self-stigma. This varies from willingness because willingness is conscious and a self-reported willingness to go, whereas self-stigma is an unconscious bias against going. We determined this difference by using this paper.


The third barrier was knowledge of Let’s Talk. Based on our survey results, many students don’t know about the resource; since that isn’t a characteristic we can change, it significantly reduces the pool of students who can use it.

The next two barriers consider the mental health status of the student. When considering these barriers, a student would only need to meet one of the criteria in order to move into the pool of students who would attend Let’s Talk.



This group of students have recently suffered through some sort of traumatic event and need immediate assistance with their problem. They may have sought help elsewhere, but were referred to Let’s Talk by other professionals. These student cannot wait the three or four weeks for an appointment and would need help immediately for the crisis they are dealing with. This likelihood of crisis was determined based off student characteristics because we determined that certain things like gender, year, or school would affect their likelihood to experience a crisis.

“Above a 3.5 and No”

This criterion was a little bit more complicated for us to extrapolate. “Above a 3.5” refers to how a patient might score on our negative feelings questionnaire that we put in our survey. In essence, we determined that scoring a 3 on this questionnaire would put a student at an average and manageable amount of stress, anxiety, or depression. If a student scored at or above a 3.5 on this survey, we determined that their mental health status was risky and they might need help. The “No” part of this criterion refers to a student’s likelihood to answer “No” to the question “Have you sought help for your mental health?” In conjunction with the “Above a 3.5,” we are able to identify the likelihood that a student needs help, but does not know they need help or has not identified themselves as someone who might be at risk for struggling with mental health.

Location Accessibility

Finally, once we identified the subset of students who use Let’s Talk, we had to determine if the student would be able to attend Let’s Talk at a certain location based on its accessibility to the student. We also determined this barrier from the survey responses. This barrier changes based on year and school, but is not dependent on mental health status.

All of our criteria can be summarized by the following flow chart.