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 🧵 each week. #wellbeingwednesday#burnout#medtwitter#meded
2/ To start Year 2, I’ll link to the threads from July 2020.
First, from July 15, a thread on #burnout history back to Freudenberger.
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!
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 will be brief because the point is simple:
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”.