1/ Welcome to another edition of West’s Well-Being Wednesday! As a reminder, I’ll briefly highlight papers, topics, questions, etc. related to healthcare professional #wellbeing, with a new entry each week. #wellbeingwednesday#burnout#MedTwitter
2/ This week we’ll touch on the association of racial bias and burnout, prompted by @FutureDocs thread last week reflecting on #DrSusanMoore and so many other victims of systematic disparities and racism.
3/ As a biostatistician, I think it’s interesting that in statistics “bias” is defined as a systematic error or deviation from the truth. This is worth reflecting upon as we debate whether racism and other biases are inherent in our systems – by definition, bias is systematic!
5/ This report is part of the multisite longitudinal CHANGES study with @van_ryn as PI. I’m hopeful that this amazing all-star team might have additional clarifying comments: @dyrbye@RRHDr@Ivuoma@bcunningMDPHD
6/ We asked if symptoms of burnout might be associated with resident physicians’ implicit and explicit biases toward (against) black people. Of note, I am not capitalizing “black” here simply to align with the published text.
7/ Why might this association exist and why might it matter? Well, we know burnout is far too prevalent among health care professionals (mayoclinicproceedings.org/article/S0025-…) and that negative emotional states are associated with racial biases.
8/ The CHANGES study sampled first-year medical students in 2010-2011 from 49 US medical schools, with follow-up in 2014, 2016 (as PGY-2 residents), and 2017 (as PGY-3 residents). In the current study, we focused on data from nonblack physicians.
9/ Variables included burnout, depressive symptoms, a 0-100 feeling thermometer (FT) for explicit racial bias, and a -2 to +2 IAT for implicit racial bias. We looked at cross-sectional associations at PGY-2 and longitudinal patterns from PGY-2 to PGY-3.
10/ Key mean cross-sectional results:
FT score toward black people: 77.9
FT score toward white people: 81.1
IAT 0.4, favoring white people
11/ Increased burnout was a/w increased explicit bias against black people. Magnitude similar to the black-white overall difference, so pretty substantial.
12/ Increased depersonalization and overall burnout, but not emotional exhaustion, was associated with increased implicit bias against black people. Again, effect sizes were similar to the black-white overall difference, so their magnitude is …
13/ In the longitudinal analyses, biases improved from PGY-2 to PGY-3. Residents who recovered from burnout (burnout as PGY-2, not as PGY-3) had the greatest gain in mean FT score (reduction in explicit bias), nearly 5 points!
14/ We don’t know if these relationships are causal, or what factors may drive the observed changes. However, these data may suggest that efforts to reduce burnout might also help the fight against health care inequalities.
15/ Now, @FutureDocs co-authored a very nice editorial adding further insights on this work and its implications.
1⃣Unconscious and conscious biases are common, and we need to acknowledge them if we are to improve.
2⃣Burnout does not allow anyone to be their “best self”, and bias concerns appear to be no exception. Burnout may not cause bias, but rather unmask biases.
17/ 👇👇👇
3⃣“Intersectionality and the compounding nature of bias” across marginalized groups requires further attention.
4⃣Careful intervention studies are needed to learn what approaches best mitigate bias and its impacts.
18/ For many 2020 has been the year of #COVID19. We must not lose sight of a deeper truth – 2020 has laid bare deep systematic social injustices #blacklivesmatter. These were huge problems before COVID, but COVID has driven the wedge deeper and widened the gaps.
19/ We cannot truly address the impact of #COVID19 unless we demand efforts to advance social justice across all of society. As physicians, our commitment to public health requires that we be drivers of this change.
20/ Wishing you all an #MVP 2021 filled with Meaning, Values, and Purpose. Come back next week for more! /fin
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1/34 Okay #medtwitter#epitwitter , read on for an #EBM#Tweetorial on p-values, with specific attention to the implications of the recent remdesivir trial with p=0.059 for mortality (full report still not published, which is not ideal …).
2/ This is a follow-up to my prior #EBM#Tweetorial on diagnostic test performance study design
1/ Several provocative papers were published on #burnout last week in @JAMA_current. I have some thoughts on both the papers and the field. I hope these might stimulate further informed discussion. I will take part in that to the extent time permits, but I do have a day job. 😀
3/ Key findings include: “marked variation in burnout definitions, assessment methods, and study quality” which “preclude definitive conclusions about the prevalence of burnout”.