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Assessing the Training for Certified Peer Support Specialists Who Provide Mental Health and Substance Use Services.

Bernice K AdjabengLisa de Saxe Zerden
Published in: The journal of behavioral health services & research (2024)
The behavioral health system's peer support workforce must be adequately trained to perform peer support services, but evidence of the adequacy of their training needs to be improved. With survey data from 667 certified peer support specialists (CPSS) from North Carolina, Kentucky, Virginia, and Tennessee, this study used (a) binomial probability test to assess perceptions about the adequacy of the workforce's training, (b) latent profile analysis to identify patterns and predictors of perceptions about the SAMHSA core competencies covered in their training, and (c) thematic analysis to identify additional training needs. Most respondents identified as White (72%), female (73%), and had some college education (83%). Most of the workforce (>ā€‰90%) felt prepared to provide services, regardless of their state. Highly and moderately sufficient coverage emerged as two distinct response patterns regarding coverage of the SAMSHA core competencies, with respondents' years of experience, state of residence, education level, race, and sense of preparedness predicting the probability of fitting into either profile. Participants desired additional training in trauma-informed practices, motivational interviewing, and new treatment approaches. Peers' experiences and perspectives were similar across different states. The findings suggest booster training sessions or continuing education opportunities are needed to maintain a robust and well-prepared peer support workforce. States should consider reciprocity agreements to enable the trained workforce to practice across states. A key implication for the training content is the need to incorporate contemporary issues relating to mental health and substance use disorders to better meet behavioral health needs.
Keyphrases
  • healthcare
  • mental health
  • public health
  • primary care
  • virtual reality
  • machine learning
  • affordable care act
  • risk assessment
  • health promotion