Mindfulness-Based Teaching Competency Assessment: Comparing Self-Assessment With Expert Evaluation in the Veterans Administration - Compassionate Awareness Learning Module Program.

Background: Meditation, including Mindfulness-Based Interventions (MBI), is a required Complementary and Integrative Health intervention at the US Department of Veterans Affairs (VA). Training VA clinicians to provide MBI at scale must address fidelity concerns and the assessment of clinician competency. Objective: The psychometric properties of the Mindfulness-Based Intervention: Teaching Assessment Criteria (MBI:TAC), a widely used tool for assessing facilitator competence, continue to be explored. To support the dissemination of MBI, the utility of using the MBI:TAC for self-assessment for clinicians in a national training program was evaluated. Methods: In a training cohort of VA clinicians (n = 39), participant self evaluations on 2 domains of the MBI:TAC are compared to the competency scores of 2 expert evaluators as based on the observations of a 10-minute exercise. Additionally, the inter-rater reliability between the 2 experts was explored. Results: Intraclass Correlation for the 2 expert evaluators for Guiding Practice was significant (ρ = .83, P = .003), but was not significant for Embodiment of Mindfulness (ρ = .34, P = .186). Self-evaluation scores were not significantly correlated to expert rater scores such that participants rate their level of competence higher than expert scores. Conclusion: The MBI:TAC, while an essential tool in teacher training, may not produce accurate scores when used for self-assessment. Instruction from a senior teacher is needed for accurate scoring. Interrater reliability may be improved with enhanced domain operationalization and training. Implications for MBI training are explored.

Colon cancer: risk perceptions and risk communication.

Members of a health maintenance organization (N=353) interacted with a computer program that provided personalized information about their risk of developing colon cancer in the next 20 years. Prior to computer feedback, most people greatly overestimated their numerical, absolute risk (chances per 1000) and also overestimated their relative risk compared to peers (e.g., "above average"). Their relative risk estimates were correlated with several risk factors, whereas their absolute risk estimates were not, suggesting that assessing individual risk perceptions with numerical, absolute risk scales may provide misleading information about what people believe. Computer feedback improved the accuracy of mean risk estimates, but about half of participants did not accept the personalized feedback as correct. In fact, correlations between actual and perceived risk were no greater among participants who received risk scores than among those who did not. Three possible explanations for resistance to lower-than-expected risk feedback are considered.