Occupational and consumer risk estimates for nanoparticles emitted by laser printers

Previous research has shown that mock and actual jurors give little weight to actuarial sexual offending recidivism risk estimates when making decisions regarding civil commitment for so-called sexually violent predators (SVPs). We hypothesized that non-risk related factors, such as irrelevant contextual information and jurors’ information-processing style, would influence mock jurors’ perceptions of sexual recidivism risk. This preregistered experimental study examined the effects of mock jurors’ (N = 427) need for cognition (NFC), irrelevant contextual information in the form of the offender’s social attractiveness, and an actuarial risk estimate on mock jurors’ estimates of sexual recidivism risk related to a simulated SVP case vignette. Mock jurors exposed to negative risk-irrelevant characteristics of the offender estimated sexual recidivism risk as higher than mock jurors exposed to positive information about the offender. However, this effect was no longer significant after mock jurors had reviewed Static-99R actuarial risk estimate information. We found no support for the hypothesis that the level of NFC moderates the relationship between risk-irrelevant contextual information and risk estimates. Future research could explore additional individual characteristics or attitudes among mock jurors that may influence perceptions of sexual recidivism risk and insensitivity to actuarial risk estimates.

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Are perceived prevalences of infection also biased and how? Lessons from large epidemics of mosquito-borne diseases in tropical regions

10.31234/osf.io/zh84a ◽

2017 ◽

Author(s):

Jocelyn Raude

Keyword(s):

Infectious Diseases ◽

Cognitive Biases ◽

Adult Population ◽

Systematic Bias ◽

Tropical Regions ◽

Telephone Surveys ◽

Behavioral Decision ◽

Risk Estimates ◽

Representative Samples ◽

Actual Prevalence

Objectives: Although people have been repeatedly found to underestimate the frequency of risks to health from common diseases, we still do not know much about reasons for this systematic bias, which is also referred to as “primary bias” in the literature. In this study, we take advantage of a series of large epidemics of mosquito-borne diseases to examine the accuracy of judgments of risk frequencies. In this aim, we assessed the perceived versus the observed prevalence of infection by zika, chikungunya or dengue fever during these outbreaks, as well as their variations among different subpopulations and epidemiological settings.Design: We used data drawn from 4 telephone surveys, conducted between 2006 and 2016, among representative samples of the adult population in tropical regions (Reunion, Martinique, and French Guiana). The participants were asked to estimate the prevalence of these infections by using a natural frequency scale.Results: The surveys showed that (1) most people greatly overestimated the prevalence of infection by arbovirus, (2) these risk overestimations fell considerably as the actual prevalence of these diseases increased, (3) the better-educated and male participants consistently yielded less inaccurate risk estimates across epidemics, and (4) that these biases in the perception of prevalence of these infectious diseases are relatively well predicted by probability weighting function.Conclusions: These findings suggest that the cognitive biases that affect perception of prevalence of acute infectious diseases are not fundamentally different from those that characterize other types of probabilistic judgments observed in the field of behavioral decision-making. They also indicate that numeracy may play a considerable role in people’s ability to transform epidemiological observations from their social environment to more accurate risk estimates.

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Development and validation of risk stratification models for adult spinal deformity surgery

Journal of Neurosurgery Spine ◽

10.3171/2019.3.spine181452 ◽

2019 ◽

Vol 31 (4) ◽

pp. 587-599 ◽

Cited By ~ 4

Author(s):

Ferran Pellisé ◽

Miquel Serra-Burriel ◽

Justin S. Smith ◽

Sleiman Haddad ◽

Michael P. Kelly ◽

...

Keyword(s):

Spinal Deformity ◽

Adult Spinal Deformity ◽

The United States ◽

Adverse Outcomes ◽

High Rate ◽

Prognostic Models ◽

Time To Event ◽

European Continent ◽

Event Risk ◽

Risk Estimates

OBJECTIVEAdult spinal deformity (ASD) surgery has a high rate of major complications (MCs). Public information about adverse outcomes is currently limited to registry average estimates. The object of this study was to assess the incidence of adverse events after ASD surgery, and to develop and validate a prognostic tool for the time-to-event risk of MC, hospital readmission (RA), and unplanned reoperation (RO).METHODSTwo models per outcome, created with a random survival forest algorithm, were trained in an 80% random split and tested in the remaining 20%. Two independent prospective multicenter ASD databases, originating from the European continent and the United States, were queried, merged, and analyzed. ASD patients surgically treated by 57 surgeons at 23 sites in 5 countries in the period from 2008 to 2016 were included in the analysis.RESULTSThe final sample consisted of 1612 ASD patients: mean (standard deviation) age 56.7 (17.4) years, 76.6% women, 10.4 (4.3) fused vertebral levels, 55.1% of patients with pelvic fixation, 2047.9 observation-years. Kaplan-Meier estimates showed that 12.1% of patients had at least one MC at 10 days after surgery; 21.5%, at 90 days; and 36%, at 2 years. Discrimination, measured as the concordance statistic, was up to 71.7% (95% CI 68%–75%) in the development sample for the postoperative complications model. Surgical invasiveness, age, magnitude of deformity, and frailty were the strongest predictors of MCs. Individual cumulative risk estimates at 2 years ranged from 3.9% to 74.1% for MCs, from 3.17% to 44.2% for RAs, and from 2.67% to 51.9% for ROs.CONCLUSIONSThe creation of accurate prognostic models for the occurrence and timing of MCs, RAs, and ROs following ASD surgery is possible. The presented variability in patient risk profiles alongside the discrimination and calibration of the models highlights the potential benefits of obtaining time-to-event risk estimates for patients and clinicians.

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