Comparing the use of open and closed questions for web-based measures of the continued influence effect

Open-ended questions, in which participants write or type their responses, are used in many areas of the behavioral sciences. Although effective in the lab, they are relatively untested in online experiments, and the quality of responses is largely unexplored. Closed-ended questions are easier to use online because they generally require only single key- or mouse-press responses and are less cognitively demanding, but can bias responses. We compared data quality obtained using open and closed response formats using the continued influence effect, in which participants read a series of statements about an unfolding event, one of which is unambiguously corrected later. Participants typically continue to refer to the corrected misinformation when making inferential statements about the event. We implemented this basic procedure online (Experiment 1A, n = 78), comparing standard open-ended responses to an alternative procedure using closed-ended responses (Experiment 1B, n = 75). Finally, we replicated these findings in a larger preregistered study (Experiments 2A and 2B, n = 323). We observed the CIE in all conditions: Participants continued to refer to the misinformation following a correction, and references to target misinformation were broadly similar in number across open- and closed-ended questions. We found that participants’ open-ended responses were relatively detailed (writing an average of 75 characters for inference questions), and almost all responses attempted to address the question. Responses for closed-ended questions were, however, faster. Overall, we suggest that with caution it may be possible to use either method for gathering CIE data

(Dis)continuing the continued influence effect of misinformation

Misinformation can often have a lasting impact on the causal inferences people make about events even after it is unambiguously corrected. This is known as the continued influence effect of misinformation. Understanding the underlying cognitive processes involved in correcting misinformation is important for developing effective counter-misinformation strategies. A review of continued influence studies suggests that methodological factors, such as the scenario in which misinformation appears, can affect the strength of a correction independently of experimental manipulations. This thesis’ primary aim was to advance understanding the continued influence effect and the conditions that give rise to it, by addressing issues with the methodological approach. Experiments 1A-2B developed and validated a methodology for web-based testing of the continued influence effect in order to target larger and more diverse samples. Two key claims from the continued influence literature were replicated; and the introduction of a novel control condition showed that misinformation is referred to even if it is only mentioned as part of the correction. Experiments 3-5 re-examined the claim that corrections, which explain how misinformation occurred, reduce reliance on misinformation. Findings showed no evidence that explanatory corrections reduce misinformation reliance in multiple scenarios; and continued influence of misinformation was observed in some scenarios but not others. Experiments 6-7 revisited the claim that misinformation, which implies a likely cause of an outcome is more impervious to correction than explicitly stated misinformation. Findings showed no evidence for this claim in three scenarios. I argue that the continued influence effect is a tenuous claim predicated on findings from a small set of scenarios that are unrepresentative of real-world situations in which misinformation is encountered. I propose that the conditions under which continued influence of misinformation occurs are poorly understood and recommend formally modelling the continued influence effect to gain a better understanding of this phenomenon

Does explaining the origins of misinformation improve the effectiveness of a given correction?

Misinformation often has a continuing influence on event-related reasoning even when it is clearly and credibly corrected; this is referred to as the continued influence effect. The present work investigated whether a correction’s effectiveness can be improved by explaining the origins of the misinformation. In two experiments, we examined whether a correction that explained misinformation as originating either from intentional deception or an unintentional error was more effective than a correction that only identified the misinformation as false. Experiment 2 found no evidence that corrections explaining the reason the misinformation was presented, were more effective than a correction not accompanied by an explanation, and no evidence of a difference in effectiveness between a correction that explained the misinformation as intentional deception and one that explained it as unintentional error. We replicated this in Experiment 2 and found substantial attenuation of the continued influence effect in a novel scenario with the same underlying structure. Overall, the results suggest that informing people of the cause leading to presentation of misinformation, whether deliberate or accidental, may not be an effective correction strategy over and above stating that the misinformation is false

Nested Sets and Natural Frequencies

Is the nested sets approach to improving accuracy on Bayesian word problems simply a way of prompting a natural frequencies solution, as its critics claim? Conversely, is it in fact, as its advocates claim, a more fundamental explanation of why the natural frequency approach itself works? Following recent calls, we use a process-focused approach to contribute to answering these long-debated questions. We also argue for a third, pragmatic way of looking at these two approaches and argue that they reveal different truths about human Bayesian reasoning. Using a think aloud methodology we show that while the nested sets approach does appear in part to work via the mechanisms theorised by advocates (by encouraging a nested sets representation), it also encourages conversion of the problem to frequencies, as its critics claim. The ramifications of these findings, as well as ways to further enhance the nested sets approach and train individuals to deal with standard probability problems are discussed

Prevalence of elevated serum fatty acid synthase in chronic limb‑threatening ischemia

There are currently no serum-based evaluations that can corroborate the severity of peripheral artery disease (PAD). In this cross-sectional study, we assessed the prevalence of elevated serum fatty acid synthase (cFAS) in patients with chronic limb-threatening ischemia (CLTI) and evaluated the accuracy of its use in detecting this condition. Preoperative fasting serum samples from 87 patients undergoing vascular intervention were collected between October 2014 and September 2016. Median age was 62 years, with 56 (64%) men, and 32 (37%) with CLTI. We found that elevated cFAS content (OR 1.17; 95% CI 1.04–1.31), type 2 diabetes (T2D; OR 5.22; 95% CI 1.77–15.4), and smoking (OR 3.53; 95% CI 1.19–10.5) were independently associated with CLTI and could detect the presence of CLTI with 83% accuracy (95% CI 0.74–0.92). Furthermore, serum FAS content was positively correlated with FAS content in femoral artery plaque in patients with severe PAD ([Formula: see text] = 0.22; P =  0.023). Finally, significantly higher co-localization of FAS and ApoB were observed within lower extremity arterial media (P < .001). Our findings indicate that serum FAS content is a marker for disease severity in patients with PAD, independent of concomitant T2D and smoking, and may play a key role in FAS and ApoB peripheral plaque progression

Systematic Assessment of the Quality and Comprehensibility of YouTube Content on Ulnar Collateral Ligament Injury and Management

Background: Ulnar collateral ligament (UCL) reconstruction has received a unique level of attention in the press and social media. There has also been an increasing use of the internet by patients to seek medical information. Concern exists regarding the quality and comprehensibility of online information when used for patient education. Purpose: To evaluate the quality and comprehensibility of the most-viewed YouTube videos related to the diagnosis and management of UCL injuries. Based on our new evidence-based scoring rubrics, we hypothesized that the quality and comprehensibility of these videos would be poor. Study Design: Cross-sectional study. Methods: The YouTube platform was searched on September 7, 2021, with the terms “UCL injury,” “ulnar collateral ligament injury,” “UCL surgery,” “ulnar collateral ligament surgery,” and “Tommy John surgery,” and the 50 most-viewed videos from each search were compiled, yielding 250 videos. After removal of duplicates and application of exclusion criteria, the 100 most-viewed videos remained. Basic attributes, including duration of video and number of views, were recorded. Each video was then analyzed by 2 independent reviewers and evaluated for 4 key parameters (quality of diagnostic content [QAR-D], quality of treatment content [QAR-T], presence of inaccurate information, and comprehensibility) and graded on a novel scale from 1 to 4 (4 being the most appropriate for patient education). Results: The mean QAR-D was 4.83 ± 3.41 (fair quality), and the mean QAR-T was 2.76 ± 3.26 (poor quality). Physician-led educational videos had both the highest mean QAR-D (6.37) and the highest mean QAR-T (4.34). No correlation was observed between video quality and views/likes. A total of 12 videos included ≥1 inaccuracy. The mean comprehensibility score was 2.66 ± 1.12, with 39 videos falling below the acceptable comprehensibility threshold (score \u3c3). Conclusion: The overall quality of UCL injury–related YouTube content was low. In addition, the absence of correlation between video quality and views/likes suggests that patients are not preferentially utilizing the limited high-quality content that does exist on the YouTube platform. In addition, inaccurate videos were prevalent (12%), and almost half of all videos were deemed inappropriate for patient education in terms of comprehensibility, as defined by our comprehensibility parameter

A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe