Double-Blind Reviews: A Step Toward Eliminating Unconscious Bias.
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ABSTRACT:
SUBMITTER: Shmidt E
PROVIDER: S-EPMC8806370 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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Double-Blind Reviews: A Step Toward Eliminating Unconscious Bias.
Shmidt Eugenia E Jacobson Brian C BC
Clinical and translational gastroenterology 20220111 1
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Project description:Background/Objectives: To assess the factors affecting the unconscious bias of healthcare professionals (HCPs) in obesity care. Methods: A cross-sectional, non-interventional, descriptive study collecting data via an online survey system was distributed via e-mail to 11,597 members of the Medical Chamber of Slovenia. Physicians were assigned into six HCP categories: (junior) resident physicians, primary care physicians (PCPs), internal medicine specialists, surgeons, dentists, and others. The online questionnaire was active for two weeks. Results: A total of 1248 physicians opened the survey link (10.8% response rate). Of the 898 physicians that engaged in the survey, 789 fully completed the questionnaire. Out of those physicians, 93.6% agreed that obesity is a disease, 83.7% were familiar with the definition, and 75.5% of HCPs were professionally interested in the subject. Overall, 39% of HCPs use the ICD obesity code, primarily primary care physicians and specialists in internal medicine. Notably, 82.0% of HCPs identified lifestyle change as the most effective intervention and believed that patients could lose weight with a serious attempt at a lifestyle change. This belief was particularly supported by male HCPs and HCPs under 40 years of age, who felt that patients were entirely responsible for their weight. The unconscious bias decreased with an increase in the HCPs' body mass index (BMI), but at the same time, physicians with a higher BMI found obesity to be less important than other diseases (p = 0.036). Using composite answers, we found that the unconscious bias of HCPs toward obesity and effective obesity care was significantly related to gender (p = 0.017), age (p < 0.001), and BMI (p = 0.005), and was independent of an area of expertise. Conclusions: HCPs' area of expertise impacted their professional standpoint (suggesting conscious bias), whereas male gender, a younger age, and a lower BMI affected unconscious bias toward obesity and its effective care. Despite their limitations, including the self-reported nature of the data, our findings can help to individualize educational strategies and create a more equitable environment in obesity healthcare.
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Project description:BackgroundAttentional bias toward sleep-related information is believed to play a key role in insomnia. If attentional bias is indeed of importance, changing this bias should then in turn have effects on insomnia complaints. In this double-blind placebo controlled randomized trial we investigated the efficacy of attentional bias modification training in the treatment of insomnia.MethodWe administered baseline, post-test, and one-week follow-up measurements of insomnia severity, sleep-related worry, depression, and anxiety. Participants meeting DSM-5 criteria for insomnia were randomized into an attentional bias training group (n = 67) or a placebo training group (n = 70). Both groups received eight training sessions over the course of two weeks. All participants kept a sleep diary for four consecutive weeks (one week before until one week after the training sessions).ResultsThere was no additional benefit for the attentional bias training over the placebo training on sleep-related indices/outcome measures.ConclusionsThe absence of the effect may be explained by the fact that there was neither attentional bias at baseline nor any reduction in the bias after the training. Either way, this study gives no support for attentional bias modification training as a stand-alone intervention for ameliorating insomnia complaints.
| S-EPMC5396867 | biostudies-literature
Project description:BackgroundUnconscious or implicit biases are universal and detrimental to health care and the learning environment but can be corrected. Historical interventions used the Implicit Association Test (IAT), which may have limitations.ObjectiveWe determined the efficacy of an implicit bias training without using the IAT.MethodsFrom April 2019 to June 2020, a 90-minute educational workshop was attended by students, residents, and faculty. The curriculum included an interactive unconscious biases presentation, videoclips using vignettes to demonstrate workplace impact of unconscious biases with strategies to counter, and reflective group discussions. The evaluation included pre- and postintervention surveys. Participants were shown images of 5 individuals and recorded first impressions regarding trustworthiness and presumed profession to unmask implicit bias.ResultsOf approximately 273 participants, 181 were given the survey, of which 103 (57%) completed it with significant increases from pre- to postintervention assessments for perception scores (28.87 [SEM 0.585] vs 32.73 [0.576], P < .001) and knowledge scores (5.68 [0.191] vs 7.22 [0.157], P < .001). For a White male physician covered in tattoos, only 2% correctly identified him as a physician, and 60% felt he was untrustworthy. For a smiling Black female astronaut, only 13% correctly identified her as an astronaut. For a brooding White male serial killer, 50% found him trustworthy.ConclusionsAn interactive unconscious bias workshop, performed without the use of an IAT, was associated with increases in perceptions and knowledge regarding implicit biases. The findings also confirmed inaccurate first impression stereotypical assumptions based on ethnicity, outward appearances, couture, and media influences.
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Project description:The relative contributions of transmission and reactivation of latent infection to TB cases observed clinically has been reported in many situations, but always with some uncertainty. Genotyped data from TB organisms obtained from patients have been used as the basis for heuristic distinctions between circulating (clustered strains) and reactivated infections (unclustered strains). Naïve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases. The hypergeometric distribution, which generates probabilities of observing clusters of a given size as realized clusters of all possible sizes, is analyzed in this paper to yield a formal estimator for genotype cluster sizes. Subtle aspects of numerical stability, bias, and variance are explored. This formal estimator is seen to be stable with respect to the epidemiologically interesting properties of the cluster size distribution (the number of clusters and the number of singletons) though it does not yield satisfactory estimates of the number of clusters of larger sizes. The problem that even complete coverage of genotyping, in a practical sampling frame, will only provide a partial view of the actual transmission network remains to be explored.
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