Phonological precision for word recognition in skilled readers

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Evaluation of Serum SARS-CoV-2 Nucleocapsid Antigen as a Diagnostic Tool in COVID-19 Patients

COVID-19 has caused millions of casualties and deaths around the world. Countries all over the world exert great efforts to control the fast spread of the disease. Rapid diagnosis is a key tool in controlling the infection; therefore, numerous diagnostic techniques were developed quickly and are available commercially. This study evaluated the use of nucleocapsid antigen (N-antigen) as a diagnostic tool in COVID-19 patients. A cross-sectional investigation was carried out on 164 people undergoing Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) PCR testing at various government laboratories in Alexandria. The research was carried out between March 2021 and January 2022. Data such as symptoms, lab investigations and real-time reverse transcription polymerase chain reaction (RT-PCR) cycle threshold (Ct) values were collected by interviewing participants and from medical records. A serum sample was collected from each participant for detection of N-antigen by ELISA kit. Ninety-eight (59.8%) of the 164 examined participants had positive SARS-CoV-2 RT-PCR results. Thirteen individuals (18.9%) exhibited varying quantities of the SARS-CoV-2 N-antigen. Antigen concentrations were significantly inversely connected with RT-PCR Ct values and positively correlated with CRP levels in SARS-CoV-2 N-antigen positive subjects. Furthermore, a strong correlation was found between N-antigen concentrations and hospitalization, fever, body aches, and pneumonia. SARS-CoV-2 N-antigen detection has high specificity (98.5%) but very low sensitivity (30.6%). Despite the high specificity of the SARS-CoV-2 N-antigen enzyme-linked immunosorbent assay (ELISA) evaluated in this study, its diagnostic utility is limited by its low sensitivity. The assay’s poor sensitivity undermines its standalone diagnostic value, especially when compared to RT-PCR

We don't know what you did last summer. On the importance of transparent reporting of reaction time data pre-processing

In behavioral, cognitive, and social sciences, reaction time measures are an important source of information. However, analyses on reaction time data are affected by researchers' analytical choices and the order in which these choices are applied. The results of a systematic literature review, presented in this paper, revealed that the justification for and order in which analytical choices are conducted are rarely reported, leading to difficulty in reproducing results and interpreting mixed findings. To address this methodological shortcoming, we created a checklist on reporting reaction time pre-processing to make these decisions more explicit, improve transparency, and thus, promote best practices within the field. The importance of the pre-processing checklist was additionally supported by an expert consensus survey and a multiverse analysis. Consequently, we appeal for maximal transparency on all methods applied and offer a checklist to improve replicability and reproducibility of studies that use reaction time measures

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Bestiary of Questionable Research Practices in Psychology

Questionable research practices (QRPs) pose a significant threat to the quality of scientific research. However, historically, they remain ill-defined, and a comprehensive list of QRPs is lacking. In this article, we address this concern by defining, collecting, and categorizing QRPs using a community-consensus method. Collaborators of the study agreed on the following definition: QRPs are ways of producing, maintaining, sharing, analyzing, or interpreting data that are likely to produce misleading conclusions, typically in the interest of the researcher. QRPs are not normally considered to include research practices that are prohibited or proscribed in the researcher’s field (e.g., fraud, research misconduct). Neither do they include random researcher error (e.g., accidental data loss). Drawing from both iterative discussions and existing literature, we collected, defined, and categorized 40 QRPs for quantitative research. We also considered attributes such as potential harms, detectability, clues, and preventive measures for each QRP. The results suggest that QRPs are pervasive and versatile and have the potential to undermine all stages of the scientific enterprise. This work contributes to the maintenance of research integrity, transparency, and reliability by raising awareness for and improving the understanding of QRPs in quantitative psychological research

A template and tutorial for preregistering studies using passive smartphone measures

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures

A guide for social science journal editors on easing into open science

Journal editors have a large amount of power to advance open science in their respective fields by incentivising and mandating open policies and practices at their journals. The Data PASS Journal Editors Discussion Interface (JEDI, an online community for social science journal editors: www.dpjedi.org) has collated several resources on embedding open science in journal editing (www.dpjedi.org/resources). However, it can be overwhelming as an editor new to open science practices to know where to start. For this reason, we created a guide for journal editors on how to get started with open science. The guide outlines steps that editors can take to implement open policies and practices within their journal, and goes through the what, why, how, and worries of each policy and practice. This manuscript introduces and summarizes the guide (full guide: https://doi.org/10.31219/osf.io/hstcx)