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Enhancing vocational training in corrections: A type 1 hybrid randomized controlled trial protocol for evaluating virtual reality job interview training among returning citizens preparing for community re-entry

NCJ Number
Matthew J. Smith; Jamie A. Mitchell; Shannon Blajeski; Brittani Parham; Meghan M. Harrington; Brittany Ross; Brandy Sinco; Daphne M. Brydon; et al
Date Published

This paper reviews the authors’ efforts to evaluate the efficacy of virtual reality job interview training by comparing the virtual reality training to services-as-usual; the paper lays out their research methodology and outcomes.


The Michigan Department of Corrections operates the Vocational Villages, which are skilled trades training programs set within prisons that include an immersive educational community using virtual reality, robotics, and other technologies to develop employable trades. An enhancement to the Vocational Villages could be an evidence-based job interview training component. Recently, the authors conducted a series of randomized controlled trials funded by the National Institute of Mental Health to evaluate the efficacy of virtual reality job interview training (VR-JIT). The results suggested that the use of VR-JIT was associated with improved job interview skills and a greater likelihood of receiving job offers within six months. The primary goal of this study is to report on the protocol they developed to evaluate the effectiveness of VR-JIT at improving interview skills, increasing job offers, and reducing recidivism when delivered within two Vocational Villages via a randomized controlled trial and process evaluation. The authors’ aims were to: evaluate whether services-as-usual in combination with VR-JIT, compared to services-as-usual alone, enhances employment outcomes and reduces recidivism among returning citizens enrolled in the Vocational Villages; evaluate mechanisms of employment outcomes and explore mechanisms of recidivism; and conduct a multilevel, mixed-method process evaluation of VR-JIT implementation to assess the adoptability, acceptability, scalability, feasibility, and implementation costs of VR-JIT. Publisher Abstract Provided