Tools to Assess Behavioral and Social Science Competencies in Medical Education: A Systematic Review.

PURPOSE: Behavioral and social science (BSS) competencies are needed to provide quality health care, but psychometrically validated measures to assess these competencies are difficult to find. Moreover, they have not been mapped to existing frameworks, like those from the Liaison Committee on Medical Education (LCME) and Accreditation Council for Graduate Medical Education (ACGME). This systematic review aimed to identify and evaluate the quality of assessment tools used to measure BSS competencies. METHOD: The authors searched the literature published between January 2002 and March 2014 for articles reporting psychometric or other validity/reliability testing, using OVID, CINAHL, PubMed, ERIC, Research and Development Resource Base, SOCIOFILE, and PsycINFO. They reviewed 5,104 potentially relevant titles and abstracts. To guide their review, they mapped BSS competencies to existing LCME and ACGME frameworks. The final included articles fell into three categories: instrument development, which were of the highest quality; educational research, which were of the second highest quality; and curriculum evaluation, which were of lower quality. RESULTS: Of the 114 included articles, 33 (29%) yielded strong evidence supporting tools to assess communication skills, cultural competence, empathy/compassion, behavioral health counseling, professionalism, and teamwork. Sixty-two (54%) articles yielded moderate evidence and 19 (17%) weak evidence. Articles mapped to all LCME standards and ACGME core competencies; the most common was communication skills. CONCLUSIONS: These findings serve as a valuable resource for medical educators and researchers. More rigorous measurement validation and testing and more robust study designs are needed to understand how educational strategies contribute to BSS competency development.

Models of cognitive performance based on home monitoring data.

Modeling cognitive performance using home monitoring data is a new approach to managing neurologic conditions and for monitoring the effects of cognitive exercise interventions. The data consists of activity monitoring from motion sensors and specific cognitive metrics embedded within our adaptive computer games. The frequency and continuity of data collection allows us to analyze within subject trends of cognitive performance and to assess day to day variability. This approach provides a framework for clinicians and care managers to have the potential of detecting patients' cognitive problems early and to have timely feedback on treatment interventions.

The exploration & forensic analysis of computer usage data in the elderly.

Unobtrusive in-home computer monitoring could one day be used to deliver cost-effective diagnostic information about the cognitive abilities of the elderly. This could allow for early detection of cognitive impairment and would additionally be coupled with the cost advantages that are associated with a semi-automated system. Before using the computer usage data to draw conclusions about the participants, we first needed to investigate the nature of the data that was collected. This paper represents a forensics style analysis of the computer usage data that is being collected as part of a larger study of cognitive decline, and focuses on the isolation and removal of non user-generated activities that were recorded by our computer monitoring software (CMS).