Does Incorporating a Measure of Clinical Workload Improve Workplace-Based Assessment Scores? Insights for Measurement Precision and Longitudinal Score Growth From Ten Pediatrics Residency Programs.
Clicks: 265
ID: 34541
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
75.1
/100
265 views
217 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #35 of 146 articles by views in Academic medicine : journal of the Association of American Medical Colleges
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 146 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
This study investigates the impact of incorporating observer-reported workload into workplace-based assessment (WBA) scores on (1) psychometric characteristics of WBA scores and (2) measuring changes in performance over time using workload-unadjusted versus workload-adjusted scores.Structured clinical observations and multisource feedback instruments were used to collect WBA data from first-year pediatrics residents at 10 residency programs between July 2016 and June 2017. Observers completed items in 8 subcompetencies associated with Pediatrics Milestones. Faculty and resident observers assessed workload using a sliding scale ranging from low to high; all item scores were rescaled to a 1-5 scale to facilitate analysis and interpretation. Workload-adjusted WBA scores were calculated at the item level using three different approaches, and aggregated for analysis at the competency level. Mixed-effects regression models were used to estimate variance components. Longitudinal growth curve analyses examined patterns of developmental score change over time.On average, participating residents (n = 252) were assessed 5.32 times (standard deviation = 3.79) by different raters during the data collection period. Adjusting for workload yielded better discrimination of learner performance, and higher reliability, reducing measurement error by 28%. Projections in reliability indicated needing up to twice the number of raters when workload-unadjusted scores were used. Longitudinal analysis showed an increase in scores over time, with significant interaction between workload and time; workload also increased significantly over time.Incorporating a measure of observer-reported workload could improve the measurement properties and the ability to interpret WBA scores.
| Reference Key |
park2018doesacademic
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Park, Yoon Soo;Hicks, Patricia J;Carraccio, Carol;Margolis, Melissa;Schwartz, Alan;, ; |
| Journal | Academic medicine : journal of the Association of American Medical Colleges |
| Year | 2018 |
| DOI |
10.1097/ACM.0000000000002381
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.