Sam Cacace

Areas of interest

Stigma: Examining impacts of internalized and societal stigma on group identities in vulnerable populations (e.g., Armed Services, LGBTQIA+) on help-seeking, social integration and connection; exploring influence of compartmentalized stigma on concealable identities; understanding influence of technologies (e.g., social media, LLMs) on public perception of vulnerable groups.

Suicide risk and prevention: Uncovering innovative methods to assess suicide risk (e.g., supervised machine learning techniques incorporating public data; influence of social support sources on military and veteran suicide risk); evaluating feasibility and efficacy of suicide risk training programs for mental health professionals (e.g., Core Competency Model, Veteran Support Services Specialist Training); psychometric validation of new and existing suicide risk, prevention knowledge, and suicide competency measures.

Advanced statistical models: Utilizing contemporary analytic techniques to improve measurement and investigation into stigma and suicide-related variables, such as latent variable modelling (e.g., structural equation modelling, item response theory, differential item functioning, common variance factor analysis, measurement invariance, latent class/profile analysis, latent growth curve analysis), multilevel modelling, intensive longitudinal analysis, and/or supervised machine learning (e.g., regression and classification trees).