Introduction: Formal mentoring programs have direct benefits for academic health care institutions, but it is unclear whether program designs use recommended components and whether outcomes are being captured and evaluated appropriately. The goal of this scoping review is to address these questions.
Methods: We completed a literature review using a comprehensive search in SCOPUS and PubMed (1998-2019), a direct solicitation for unpublished programs, and hand-searched key references, while targeting mentor programs in the United States, Puerto Rico, and Canada. After three rounds of screening, team members independently reviewed and extracted assigned articles for 40 design data items into a comprehensive database.
Results: Fifty-eight distinct mentoring programs were represented in the data set. The team members clarified specific mentor roles to assist the analysis. The analysis identified mentoring program characteristics that were properly implemented, including identifying program goals, specifying the target learners, and performing a needs assessment. The analysis also identified areas for improvement, including consistent use of models/frameworks for program design, implementation of mentor preparation, consistent reporting of objective outcomes and career satisfaction outcomes, engagement of program evaluation methods, increasing frequency of reports as programs as they mature, addressing the needs of specific faculty groups (eg, women and minority faculty), and providing analyses of program cost-effectiveness in relation to resource allocation (return on investment).
Conclusion: The review found that several mentor program design, implementation, outcome, and evaluation components are poorly aligned with recommendations, and content for URM and women faculty members is underrepresented. The review should provide academic leadership information to improve these discrepancies.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/CEH.0000000000000459 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!