Engagement in an Online Cultural Competency Training

South Med J. 2018 Apr;111(4):199-202. doi: 10.14423/SMJ.0000000000000790.

Abstract

Objectives: Engagement with online cultural competency training has not been well studied. We examined knowledge, attitudes, and skills differences among medical students, physicians, and other professionals in an online cultural competency education program.

Methods: A total of 1745 participants completed up to four online modules aimed at exploring stereotype, bias, diet, and religion among African American patients with hypertension. We examined knowledge, attitudes, and self-reported skills with 17 multiple-choice questions embedded in the 4 modules. Participants received comparative responses with their peers.

Results: Between 75% and 84% of participants knew the definition of stereotype and <50% knew the definition of bias (47% students, 36% physicians, 33% others, P < 0.001). Most responded that minorities perceive bias (98%-100%) and believe that evidence exists showing that bias affects decision making (62%-69%). Although most perceive that religious and spiritual beliefs affect reaction to illness often (78% students, 68% physicians, 79% others, P < 0.001), few would ask about religious beliefs during a typical encounter (13% students, 16% physicians, 30% others, P < 0.001).

Conclusions: All of the participants struggled to define bias; however, most agreed that minorities perceive bias in the care they receive. We examined usage and interaction with the online content as a dimension of engagement.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Alabama / epidemiology
  • Black or African American / psychology
  • Cultural Competency / education*
  • Education / methods
  • Female
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Hypertension / ethnology*
  • Internet
  • Male
  • Physicians* / statistics & numerical data
  • Religion
  • Spirituality
  • Students, Medical / psychology
  • Students, Medical / statistics & numerical data*