Following debates in psychology on the importance of replication research, we have also started to see pleas for a more prominent role for replication research in medical education. To enable replication research, it is of paramount importance to carefully study the reliability of the instruments we use. Cronbach’s alpha has been the most widely used estimator of reliability in the field of medical education, notably as some kind of quality label of test or questionnaire scores based on multiple items or of the reliability of assessment across exam stations. However, as this narrative review outlines, Cronbach’s alpha or alternative reliability statistics may complement but not replace psychometric methods such as factor analysis. Moreover, multiple-item measurements should be preferred above single-item measurements, and when using single-item measurements, coefficients as Cronbach’s alpha should not be interpreted as indicators of the reliability of a single item when that item is administered after fundamentally different activities, such as learning tasks that differ in content. Finally, if we want to follow up on recent pleas for more replication research, we have to start studying the test-retest reliability of the instruments we use.

A wide array of digital supports (such as apps) have been developed for the autism community, many of which have little or no evidence to support their effectiveness. A Delphi study methodology was used to develop a consensus on what constitutes good evidence for digital supports among the broader autism community, including autistic people and their families, as well as autism-related professionals and researchers. A four-phase Delphi study consultation with 27 panel members resulted in agreement on three categories for which evidence is required: reliability, engagement and effectiveness of the technology. Consensus was also reached on four key sources of evidence for these three categories: hands-on experience, academic sources, expert views and online reviews. These were differentially weighted as sources of evidence within these three categories. Lay abstract Digital supports are any type of technologies that have been intentionally developed to improve daily living in some way. A wide array of digital supports (such as apps) have been developed for the autism community specifically, but there is little or no evidence of whether they work or not. This study sought to identify what types of evidence the autistic community valued and wanted to see provided to enable an informed choice to be made regarding digital supports. A consensus was developed between autistic people and their families, practitioners (such as therapists and teachers) as well as researchers, to identify the core aspects of evidence that everyone agreed were useful. In all, 27 people reached agreement on three categories for which evidence is required: reliability, engagement and the effectiveness of the technology. Consensus was also reached on four key sources of evidence for these three categories: hands-on experience, academic sources, expert views and online reviews. The resulting framework allows for any technology to be evaluated for the level of evidence identifying how effective it is. The framework can be used by autistic people, their families, practitioners and researchers to ensure that decisions concerning the provision of support for autistic people is informed by evidence, that is, ‘evidence-based practice’.

We report on a nine-month-long observational study with teachers and students with autism in a classroom setting. We explore the impact of motion-based activities on students' behavior. In particular, we examine how the playful gaming activity impacted students' engagement, peer-directed social behaviors, and motor skills. We document the effectiveness of a collaborative game in supporting initiation of social activities between peers, and in eliciting novel body movements that students were not observed to produce outside of game play. We further identify the positive impact of game play on overall classroom engagement. This includes an "audience effect" whereby non-playing peers direct initiations to those playing the game and vice versa, and a positive "spillover" effect of the activity on students' social behavior outside of game play. We identify key considerations for designing and deploying motion-based activities for children with autism in a classroom setting. Copyright is held by the owner/author(s)

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In relative terms, Spanish motorcyclists are more likely to be involved in crashes than other drivers and this tendency is constantly increasing. The objective of this study is to identify the factors that are related to being an offender in motorcycle accidents. A binary logit model is used to differentiate between offender and non-offender motorcyclists. A motorcyclist was considered to be offender when s/he had committed at least one traffic offense at the moment previous to the crash. The analysis is based that inexperienced, older females, not using helmets, absent-minded and non-fatigued riders are more likely to be offenders. Moreover, riding during the night, on weekends, for leisure purposes and along roads in perfect condition, mainly on curves, predict offenses among motorcyclists. The findings of this study are expected to be useful in developing traffic policy decisions in order to improve motorcyclist safety.

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The aim of this systematic review is to identify recent digital technologies used to detect early signs of autism spectrum disorder (ASD) in preschool children (i.e., up to six years of age). A systematic literature search was performed for English language articles and conference papers indexed in Pubmed, PsycInfo, ERIC, CINAHL, WoS, IEEE, and ACM digital libraries up until January 2020. A follow-up search was conducted to cover the literature published until December 2020 for the usefulness and interest in this area of research during the Covid-19 emergency. In total, 2427 articles were initially retrieved from databases search. Additional 481 articles were retrieved from follow-up search. Finally, 28 articles met the inclusion criteria and were included in the review. The studies included involved four main interface modalities: Natural User Interface (e.g., eye trackers), PC or mobile, Wearable, and Robotics. Most of the papers included (n = 20) involved the use of Level 1 screening tools. Notwithstanding the variability of the solutions identified, psychometric information points to considering available technologies as promising supports in clinical practice to detect early sign of ASD in young children. Further research is needed to understand the acceptability and increase use rates of technology-based screenings in clinical settings.