Article Figures & Data
Tables
Demographic Percent Gender Male 15.8 Female 84.2 Race/ethnicity White 69.6 Black/African American 23.1 Asian 5.1 American Indian/Alaska Native 1.4 Native Hawaiian/Other Pacific Islander 0.8 Hispanic/Latino 16.5 Education Associate’s degree or less 39.1 Undergraduate degree 39.4 Graduate degree 21.5 Profession Student 35.9 Counselor 19.6 Social worker 17.4 Peer professional 4.3 Community health worker 3.3 Nurse 2.6 Educator 2.4 Doctoral-level clinician (MD/PhD) 1.2 Years of experience Less than 1 year 54.3 1 to 3 years 20.1 4 to 6 years 8.8 7 to 10 years 5.9 More than 10 years 11.0 # Previous VRA trainings 0 57.4 1 to 2 30.7 3 or more 11.8 Outcome M SD How you understand issues related to privacy, obligations to third parties, and violence risk assessment and management 5.81 1.12 What you do to address questions related to risk of harm to others 5.78 1.11 How you interact with clients who pose a potential risk of harm to others 5.78 1.14 The amount of time you spend on threat or risk assessment 5.70 1.15 How you document confidentiality 5.79 1.17 How you document executing (or not) duty to warn or duty to protect 5.76 1.17 How you document the product of a violence risk assessment 5.77 1.16 The amount of time you spend documenting your work 5.71 1.17 How you collaborate with your colleagues 5.69 1.17 How you collaborate with other organizations in the community 5.70 1.18 Total IOTTAa score 5.77 1.07 aIOTTA: Impact of Training and Technical Assistance.
Model β t p Model 1: Quiz scores regressed on predictors Fixed effects Intercept — 21.36 .000 Paraprofessional vs. professional (dummy code) −.047 −1.02 .310 Student vs. professional (dummy code) .062 1.18 .239 Years of experience .226 4.67 .000 Model 2: Change scores regressed on predictors Fixed effects Intercept — 3.97 .000 Paraprofessional vs. professional (dummy code) −.002 −.05 .963 Student vs. professional (dummy code) .036 .63 .529 Years of experience −.023 −.44 .662 Model 3: Competence regressed on predictors Fixed effects Intercept v 25.14 .000 Paraprofessional vs. professional (dummy code) −.094 −2.33 .020 Student vs. professional (dummy code) −.085 −1.87 .062 Years of experience .216 5.19 .000 Model 3: Practice outcomes regressed on predictors Fixed effects Intercept — 51.52 .000 Paraprofessional vs. professional (dummy code) −.034 −.79 .429 Student vs. professional (dummy code) .058 1.20 .232 Years of experience .047 1.05 .294 Model β t p Model 1: Quiz scores regressed on predictors Fixed effects Intercept — 16.86 .000 Perceived importance of training .083 1.99 .047 Change from current practice −.203 −4.79 .000 Training level .093 2.19 .029 Number of trainings .030 0.75 .453 Pretraining competence −.075 −1.72 .085 Model 2: Change scores regressed on predictors Fixed effects Intercept — 3.26 .001 Perceived importance of training −.003 −.06 .953 Change from current practice −.088 −1.96 .051 Training level .086 1.86 .063 Number of trainings −.045 −1.08 .282 Pretraining competence −.050 −1.09 .279 Model 3: Competence regressed on predictors Fixed effects Intercept — 4.59 .000 Perceived importance of training .276 12.85 .000 Change from current practice .033 1.52 .129 Training level .140 6.33 .000 Number of trainings .045 2.27 .023 Pretraining competence .558 25.44 .000 Model 3: Practice outcomes regressed on predictors Fixed effects Intercept — 32.68 .000 Perceived importance of training .343 10.34 .000 Change from current practice .048 1.45 .149 Training level .177 5.20 .000 Number of trainings −.067 −2.19 .029 Pretraining competence −.056 −1.66 .097
