Instagram Feed Post

damoncentola

In my most recent study, we tested the impact of s

In my most recent study, we tested the impact of structured information-sharing networks by using a phone app. Our app resembled continuing medical education (CME) activities, but we had two different versions of the app. One version enabled structured information–sharing networks, while the other version did not include these networks. The egalitarian structure of the networks we set up is particularly important because it retains the wisdom and experience of senior participants and adds the knowledge from younger members with more recent training.

#networks #sociology #networksharing #app #phoneappstudy #egalitariannetworks #medical #clinicalbias

The keys to overcoming partisan bias in networks a

The keys to overcoming partisan bias in networks are: 1) wide bridges 2) proper framing and 3) reduced centralization. Once these factors were taken into account, we found that cross-party networks improved the abilities of members of both parties to forecast climate data, effectively eliminating belief polarization between liberals and conservatives about climate trends.

#networkbias #partisanbias #bias #politicalparty #climatechange #sociology

If you’re not familiar with the phenomenon of “the wisdom of the crowd”, it actually has roots in Aristotle's writings! Centuries ago, people realized that a group estimate was often more accurate than the estimate of most individuals within the group. This has been studied by many, but in my recent study I apply it to clinical practices. Swipe to see the full definition of “wisdom of the crowd”!

#wisdomofthecrowd #sociology #whatis #aristotle #philosophy

The Penn Leonard Davis Institute for Health Econom

The Penn Leonard Davis Institute for Health Economics recently published a blog post written by Chris Tachibana (PhD, MS) discussing my most recent research. I have a conversation about my initial interest in studying peer networks, as well as the findings of our study. The full blog post is available on the LDI website, or use this link: https://bit.ly/ldiblog

#ldi #blogpost #medicalbias #interview #sociology

Clinical treatment and diagnosis errors are much m

Clinical treatment and diagnosis errors are much more common than you may think. A surprising 10-15% of all clinical decisions regarding diagnosis and treatment are inaccurate. This is one of the reasons why we choose to study the “wisdom of the crowd” within clinical practices. In our most recent study, “Experimental evidence for structured information–sharing networks reducing medical errors”, we found a significant improvement in the treatment recommendations of peer-sharing enabled clinician groups. These results get us closer to improving patient treatment.

#healthcare #patienttreatment #medicalbias #medicalerrors #upenn #sociology

My recent publication was featured in TIME Magazin

My recent publication was featured in TIME Magazine in an article titled, "A Hive Mind of Doctors Can Mean Better Care for Patients". The article breaks down the findings and implications of the study and includes quotes from myself and colleagues discussing our work. Read the full article at: https://bit.ly/43LC6Mz

#time #featurearticle #research #discussion #sociology #healthcare

Exciting news! My paper, "Experimental evidence fo

Exciting news! My paper, "Experimental evidence for structured information–sharing networks reducing medical errors" was published this week by the Proceedings for the National Academy of Sciences. I will be sharing more on these findings in the coming weeks, but for now, check out the paper by using this link: bit.ly/medical_errors

#newpaper #newpublication #medicalerrors #networks #sociology #publication #PNAS

In my last post, I discussed how framing through p

In my last post, I discussed how framing through political images can influence network bias. In this graph, we can see significant improvements from round 1 to round 3 of forecasting, but especially in the participant group without partisan cues.

We discovered that the simple graphic reminding people of their party loyalties can have a very powerful influence on how social networks operate. When the party icons were removed, people from both parties learned from one another to remarkable effect.

#networkbias #partisanbias #bias #politicalparty #climatechange #sociology

From looking at the chart in this picture, do you

Load More... Follow on Instagram

Tweets by DamonCentola