Final Project: Social Impact Practicum¶
For our final course project, we are going to be applying the data science skills you learn in the course to an important matter of public policy: how have those with disabilities fared during COVID-19 and what racial inequalities do we see in its impact?
The START (Systemic, Therapeutic, Assessment, Resources, and Treatment) model at the University of New Hampshire is a comprehensive model of service supporting the optimization of independence, treatment, and community living for individuals with intellectual/developmental disabilities (IDD) and mental health needs. Here is a website with more information about their work: The Center for Start Services
Potential broad questions¶
The SIP process will be focused on narrowing down broad questions to use the data to investigate. A few potential ones include:
1. COVID-19 and changes in suicidal ideation:¶
The COVID-19 lockdowns dramatically changed the lives of START participants and caregivers. In particular, the lockdown might have led to increases in suicidal ideation through a variety of mechanisms:
Decreased access to mental health support: as lockdowns restricted medical care to emergency care provision, and mental health support moved to virtual formats, participants might have faced decreased access
Stress related to living situations: lockdowns also increased the amount of time that individuals spent in closely confined living situations. This might have affected mental health.
This project could analyze over-time variation in suicidal ideation and contrast this variation to the timing of lockdowns. While the START participant’s exact location is considered PII and not available for students, they could examine either (1) county-level variation in lockdown timing or (2) Region-level variation.
2. COVID-19 and interactions with law enforcement:¶
In addition to possible correlations with suicidal ideation, lockdowns might have impact interactions between START participants and law enforcement, who can face challenges in responding appropriately to young adults with disabilities. In turn, there may be racial/demographic differences in how members of law enforcement respond. This project could look at how interactions with law enforcement changed during the COVID-19 pandemic and how this varies across demographic subgroups. This work would build upon the analyses of Kalb et al. (2021) who show that one in three crisis events among START participants involved contact with police, with the police response often resulting in a referral to an Emergency Department (ED). Yet COVID-19 changes in ED availability and staffing could alter these patterns.
3. Text Analysis and Uncovering Demographic or Regional Differences in Family Caregiver Experiences:¶
START conducts semi-structured interviews with caregivers of participants using the Family Experiences with Severe Mental Illness Scale (FEIS) . The FEIS contains various open-ended responses that may cluster into themes. For instance, in response to questions about whether mental health professionals take the caregiver’s ideas and opinions into account and involve the caregiver in treatment, themes may cluster around (1) wanting a high degree of involvement but a lack of receptivity to that involvement by mental health professionals, (2) wanting a high degree of involvement and mental health professionals encouraging it, and other patterns. This project could involve (1) using automated text analysis methods to uncover themes in question responses and (2) examining how family demographics or things like the regional safety net support are correlated with those themes.
As described in the main section of the syllabus, you’ll be split into assigned groups to work on sub-components of the project. We’ll be working from a common repo that you’ll be added to, and have push/commit privileges for, when you’re set up on GitHub.