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The volume of and interest in unstructured participatory science data has increased dramatically in recent years. However, unstructured participatory science data contain taxonomic biases—encounters with some species are more likely to be reported than encounters with others. Taxonomic biases are driven by human preferences for different species and by logistical factors that make observing certain species challenging. We investigated taxonomic bias in reports of butterflies by characterizing differences between a dedicated participatory semi‐structured dataset, eButterfly, and a popular unstructured dataset, iNaturalist, in spatiotemporally explicit models. Across 194 butterfly species, we found that 53 species were overreported and 34 species were underreported in opportunistic data. Ease of identification and feature diversity were significantly associated with overreporting in opportunistic sampling, and strong patterns in overreporting by family were also detected. Quantifying taxonomic biases not only helps us understand how humans engage with nature but also is necessary to generate robust inference from unstructured participatory data. [ABSTRACT FROM AUTHOR]

Biostatistics courses are integral to many undergraduate biology programs. Such courses have often been taught using point-and-click software, but these programs are now seldom used by researchers or professional biologists. Instead, biology professionals typically use programming languages, such as R, which are better suited to analyzing complex data sets. However, teaching biostatistics and programming simultaneously has the potential to overload the students and hinder their learning. We sought to mitigate this overload by using cognitive load theory (CLT) to develop assignments for two biostatistics courses. We evaluated the effectiveness of these assignments by comparing student cohorts who were taught R using these assignments (n = 146) with those who were taught R through example scripts or were instructed on a point-and-click software program (control, n = 181). We surveyed all cohorts and analyzed statistical and programming ability through students' lab reports or final exams. Students who learned R through our assignments rated their programming ability higher and were more likely to put the usage of R as a skill in their curricula vitae. We also found that the treatment students were more motivated, less frustrated, and less stressed when using R. These results suggest that we can use CLT to teach challenging material.

Abstract Background Illicit drug users have a high prevalence of HCV and represent the majority of newly infected persons in the U.S. Despite the availability of effective HCV treatment, few drug users have been evaluated or treated for HCV. Racial and ethnic minorities have a higher incidence and prevalence of HCV and higher HCV-related mortality. Factors contributing to poor engagement in care are incompletely understood. Methods Fourteen mixed-gender focus groups of either African American or Latino/a drug users (N = 95) discussed barriers to HCV testing and treatment. Themes were identified through content analysis of focus group discussions. Results Many drug users were tested for HCV in settings where they were receiving care. Outside of these settings, most were unaware of voluntary test sites. After testing HCV positive, drug users reported not receiving clear messages regarding the meaning of a positive HCV test, the impact of HCV infection, or appropriate next steps including HCV clinical evaluations. Many drug users perceived treatment as unimportant because they lacked symptoms, healthcare providers minimized the severity of the diagnosis, or providers did not recommend treatment. Mistrust of the motivations of healthcare providers was cited as a barrier to pursuing treatment. Social networks or social interactions were a source of HCV-related information and were influential in shaping drug users perceptions of treatment and its utility. Conclusion Drug users perceived a paucity of settings for self-initiated HCV testing and poor provider-patient communication at test sites and during medical encounters. Notably, drug users reported having an unclear understanding about the meaning of a positive HCV test, the health implications of HCV infection, the importance of clinical evaluations and monitoring, and of treatment options for HCV. Efforts to improve the delivery of clinical messages about HCV infection for drug users at test settings and clinical encounters are needed.

Aim: Animals couple habitats by three types of movement: dispersal, migration, and foraging, which dynamically link populations, communities, and ecosystems. Across these types, movement distances tend to correlate with each other, potentially reflecting allometric scaling with body mass, but ecological and evolutionary species' traits may constrain movement distances and weaken these correlations. Here, we investigate multivariate "movement profiles" to better understand patterns in movement across movement types, with the aim of improving predictions in ecology from populations to ecosystems. Location: Global. Time period: 1945–2019. Major taxa studied: Vertebrates. Methods: We synthesized distances of all three movement types (dispersal, migration, and foraging) across 300+ vertebrate species and investigated how the relationships between movement types and body mass were modified by evolutionary history and trophic guild. Results: We found that the strength of relationships between movement types and body mass varied among taxa and trophic guilds, for example, strongly positive for mammals but weak for birds, or positive across trophic guilds for foraging and dispersal but not migration. Notably, movement profiles interacted with the effects of shared evolutionary history and trophic guild to diminish covariance between movement types. Main conclusions: Overall, we find that movement types with distinct ecological consequences (foraging, migration) are often correlated, although some species seem able to overcome biomechanical, evolutionary, and metabolic constraints by reducing correlations among movement types. This integrative assessment of movement can improve ecological prediction by allowing estimation of unobserved movement distances for parameterization of models based on estimation of other movement types. [ABSTRACT FROM AUTHOR]

The purpose of the present study was to analyse possible developmental trends in sustained attention through the pre-school period, as well as the influence of social and physical distractions. Three samples of children, one per each pre-school grade, were observed during learning activities required by the teacher. Children's behaviour was coded as sustained attention, and as social and non-social categories of disengagement. Sustained attention was observed to linearly increase with pre-school level, while the frequency of social interference of attention decreased. These findings are discussed within the context of studies on developmental trends of sustained attention in natural settings, the influence of social stimuli and the possible involvement of self-control abilities.