The contribution of sensory information asymmetry and bias of attribution to egocentric tendencies in effort comparison tasks.

When comparing themselves with others, people often evaluate their own behaviors more favorably. This egocentric tendency is often categorized as a bias of attribution, with favorable self-evaluation resulting from differing explanations of one's own behavior and that of others. However, studies on information availability in social contexts offer an alternative explanation, ascribing egocentric biases to the inherent informational asymmetries between performing an action and merely observing it.

Incidence of Antimicrobial-Associated Acute Kidney Injury in Children: A Structured Review.

Acute kidney injury (AKI) is a commonly reported adverse effect of administration of antimicrobials. While AKI can be associated with poorer outcomes, there is little information available to understand rates of AKI in children exposed to various antimicrobials. We performed a structured review using the PubMed and Embase databases.

Going Asexual: A Survey of Mites of the Genus (Acari: Acaridae) Revealing a Large Number of New Parthenogenetic Species in the Holarctic Region.

Mites of the genus (Acari: Acaridae) are distributed worldwide; they inhabit concealed habitats and include several beneficial and economically important species. However, species identification is difficult because many species are poorly described or delimited and their phoretic stages are unknown or uncorrelated. Furthermore, is interesting because it includes entirely asexual (parthenogenetic) species.

No Visitors: Family Perceptions of Separation From Hospitalized Loved Ones.

Background/introduction: Restrictions on visitors during the coronavirus disease 2019 (COVID-19) pandemic had major implications for both patients and families, impacting health care outcomes. Policies included mandatory closures, masking, and visiting restrictions both in acute and long-term care. Despite visiting restrictions in health care systems, little is known about its effects.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages.

Importance: Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures.

Objective: To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages.

Design, Setting, And Participants: A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019.