Providing the Resident Wellness Scale for Broad, Open-Source Use

Overview

Background:

Residency training is emotionally and physically demanding and residents have a high incidence of depression, burnout, and suicide ideation. No well-validated instruments exist to measure resident wellness. The Accreditation Council for Graduate Medical Education (ACGME) has issued new accreditation requirement on assuring resident wellbeing as of July 1, 2017. All institutions, including WSU, will need to determine appropriate interventions and monitor outcomes. This project is the evaluation of a novel wellness instrument as part of an effort to improve the emotional and physical wellness of residents.

Hypothesis:

The 10-item Resident Wellness Scale, developed by the Wayne State Office of Graduate Medical Education, should prove to be a useful measure in a broad sample on residents at many different institutions. We predict that the scale will have high unidimensionality (Cronbach’s alpha greater than .80), but may show evidence of more than one sub-factor (an exploratory factor analysis should fit response data slightly better than a single-factor model). Wellness should increase in the sample from post-graduate year (PGY) 1 through PGY 3. The distribution of Wellness scores should be stable across institutions, but some types of institutions, programs, or specialties may show higher levels of Wellness than others.

Protocol

Developing optimal learning environment and measuring resident wellness is a moral and accreditation obligation of any residency program, and determining the appropriate use of the RWS is a necessary step towards meeting that obligation. By making the RWS freely available to many institutions through a data sharing agreement, we will facilitate the improvement of residents’ health and well-being not only at WSU as a sponsoring institution, but also nationally.

The Resident Wellness Scale will be utilized by the graduate medical education programs at WSU as part of monitoring the new ACGME requirements. Other interested institutions will volunteer to use the Resident Wellness Scale (RWS) by contacting the WSU GME office. Per a data sharing agreement (DSA) partner institutions may use the RWS and log on to a custom-built web interface to access data from their institution. The DSA allows the Wayne State University investigators (PI) to analyze the data and compute variance between institutions and types of institutions. Per the DSA, the PI shall not publish or generally share identifiable institutional statistics or data.

Resident responses to the RWS will be collected through a web page. Responses will include resident’s self-reported Institution, Position (Resident/Fellow, Faculty, Other), PGYear (1, 2, 3, 4, or 5+), Specialty (free text), and Gender (male, female, other). Responses on the RWS are on a 5-point frequency scale (1=Never, 2=Seldom, 3=Sometimes, 4=Often, 5=Very Often) with no items reverse-coded. Data will be anonymous and collected through a web server and saved to a secure database for access by the data administrator (the PI).

The following analyses will be conducted on data from participating institutions.

  1. Exploratory and Confirmatory Factor Analyses (EFA and CFA): Parallel analysis will be used to determine the appropriate number of factors and EFA will be run using maximum likelihood with oblimin rotation to estimate factor loadings of each item on each factor. Factor meaning will be inferred by examination of loading matrix. If the multi-factor solution explains significantly more variance than a single-factor model in a comparative CFA, then a multi-factor scoring rubric will be developed.
  2. Group Effects: institutional and collected demographic factors (gender, specialty, and post-graduate training year) will be compared. Observed effects will be tested for correlations with observable institutional and specialty-related factors.
  3. Longitudinal Effects: because the accrediting board of graduate medical education (the ACGME) has mandated wellness monitoring and improvement, we expect to see rises in RWS scores over time. A multi-institution dataset will allow the estimate of the impact of this policy change.

The RWS is a unique measure and we are offering it for broad use with few caveats. We anticipate the scale will have a large and positive impact on residency training and the physicians being trained.