Typical hierarchical processing in autistic adults

Previous research suggests that autistic individuals exhibit atypical hierarchical processing, however, most of these studies focused solely on children. Thus, the main aim of the current study was to investigate the presence of atypical local or global processing in autistic adults using a traditional divided attention task with Navon’s hierarchical figures. Reaction time data of 27 autistic and 25 neurotypical (NT) adults was analysed using multilevel modelling and Bayesian analysis. The results revealed that autistic, like NT, adults experienced a global precedence effect. Moreover, both autistic and NT participants experienced global and local interference effects. In contrast to previous findings with children, the current study suggests that autistic adults exhibit a typical, albeit unexpected, processing of hierarchical figures

Attentional Bias towards Social Interactions during Viewing of Naturalistic Scenes

Human visual attention is readily captured by the social information in scenes. Multiple studies have shown that social areas of interest (AOIs) such as faces and bodies attract more attention than non-social AOIs (e.g., objects or background). However, whether this attentional bias is moderated by the presence (or absence) of a social interaction remains unclear. Here, the gaze of 70 young adults was tracked during the free viewing of 60 naturalistic scenes. All photographs depicted two people, who were either interacting or not. Analyses of dwell time revealed that more attention was spent on human than background AOIs in the interactive pictures. In non-interactive pictures, however, dwell time did not differ between AOI type. In the time-to-first-fixation analysis, humans always captured attention before other elements of the scene, although this difference was slightly larger in interactive than non-interactive scenes. These findings confirm the existence of a bias towards social information in attentional capture and suggest our attention values social interactions beyond the presence of two people

Time Spent Gaming, Device Type, Addiction Scores, and Well-being of Adolescent English Gamers in the 2021 OxWell Survey: Latent Profile Analysis.

BACKGROUND: The shift in the last decades to screen-based and increasingly web-based gaming activity has raised concerns about its impact on the development of children and adolescents. Despite decades of research into gaming and related psychosocial effects, the question remains how best to identify what degree or context of gaming may be a cause for concern. OBJECTIVE: This study aimed to classify adolescents into gamer profiles based on both gaming behaviors and well-being. Once we distinguished the different gamer profiles, we aimed to explore whether membership to a specific profile could be predicted based on a range of personal characteristics and experiences that could then help identify those at risk. METHODS: We explored gaming and well-being in an adolescent school population (aged 12-18 years) in England as part of the 2021 OxWell student survey. Self-report measures of time spent playing games on computers or consoles, time spent playing games on mobile phones, the Game Addiction Scale, and the Warwick-Edinburgh Mental Well-being Scale were used to classify adolescent heavy gamers (playing games for at least 3.5 hours a day) using latent profile analysis. We used multinomial logistic regression analysis to predict the profile membership based on a range of personal characteristics and experiences. RESULTS: In total, 12,725 participants answered the OxWell gaming questions. Almost one-third (3970/12,725, 31.2%) indicated that they play games for at least 3.5 hours a day. The correlation between time spent playing video games overall and well-being was not significant (P=.41). The latent profile analysis distinguished 6 profiles of adolescent heavy gamers: adaptive computer gamers (1747/3970, 44%); casual computer gamers (873/3970, 22%); casual phone gamers (595/3970, 15%); unknown device gamers (476/3970, 12%); maladaptive computer gamers (238/3970, 6%); and maladaptive phone gamers (79/3970, 2%). In comparison with adaptive computer gamers, maladaptive phone gamers were mostly female (odds ratio [OR] 0.08, 95% CI 0.03-0.21) and were more likely to have experienced abuse or neglect (OR 3.18, 95% CI 1.34-7.55). Maladaptive computer gamers, who reported gaming both on their mobile phones and on the computer, were mostly male and more likely to report anxiety (OR 2.25, 95% CI 1.23-4.12), aggressive behavior (OR 2.83, 95% CI 1.65-4.88), and web-based gambling (OR 2.18, 95% CI 1.24-3.81). CONCLUSIONS: A substantial number of adolescents are spending ≥3.5 hours gaming each day, with almost 1 in 10 (317/3970, 8%) reporting co-occurring gaming and well-being issues. Long hours gaming using mobile phones, particularly common in female gamers, may signal poorer functioning and indicate a need for additional support. Although increased time gaming might be changing how adolescents spend their free time and might thus have public health implications, it does not seem to relate to co-occurring well-being issues or mental ill-health for the majority of adolescent gamers

Influences of Parental Snacking-Related Attitudes, Behaviours and Nutritional Knowledge on Young Children's Healthy and Unhealthy Snacking:The ToyBox Study

This study investigated parental influences on preschool children’s healthy and unhealthy snacking in relation to child obesity in a large cross-sectional multinational sample. Parents and 3– 5 year-old child dyads (n = 5185) in a kindergarten-based study provided extensive sociodemographic, dietary practice and food intake data. Parental feeding practices that were derived from questionnaires were examined for associations with child healthy and unhealthy snacking in adjusted multilevel models, including child estimated energy expenditure, parental education, and nutritional knowledge. Parental healthy and unhealthy snacking was respectively associated with their children’s snacking (both p < 0.0001). Making healthy snacks available to their children was specifically associated with greater child healthy snack intake (p < 0.0001). Conversely, practices that were related to unhealthy snacking, i.e., being permissive about unhealthy snacking and acceding to child demands for unhealthy snacks, were associated with greater consumption of unhealthy snacks by children, but also less intake of healthy snacks (all p < 0.0001). Parents having more education and greater nutritional knowledge of snack food recommendations had children who ate more healthy snacks (all p < 0.0001) and fewer unhealthy snacks (p = 0.002, p < 0.0001, respectively). In the adjusted models, child obesity was not related to healthy or unhealthy snack intake in these young children. The findings support interventions that address parental practices and distinguish between healthy and unhealthy snacking to influence young children’s dietary patterns

Gaming Profiles of School Aged English Adolescents

Pre-registratio

Time spent gaming, device type, addiction scores, and well-being of adolescent english gamers in the 2021 Oxwell survey: latent profile analysis

Background: The shift in the last decades to screen-based and increasingly web-based gaming activity has raised concerns about its impact on the development of children and adolescents. Despite decades of research into gaming and related psychosocial effects, the question remains how best to identify what degree or context of gaming may be a cause for concern. Objective: This study aimed to classify adolescents into gamer profiles based on both gaming behaviors and well-being. Once we distinguished the different gamer profiles, we aimed to explore whether membership to a specific profile could be predicted based on a range of personal characteristics and experiences that could then help identify those at risk. Methods: We explored gaming and well-being in an adolescent school population (aged 12-18 years) in England as part of the 2021 OxWell student survey. Self-report measures of time spent playing games on computers or consoles, time spent playing games on mobile phones, the Game Addiction Scale, and the Warwick-Edinburgh Mental Well-being Scale were used to classify adolescent heavy gamers (playing games for at least 3.5 hours a day) using latent profile analysis. We used multinomial logistic regression analysis to predict the profile membership based on a range of personal characteristics and experiences. Results: In total, 12,725 participants answered the OxWell gaming questions. Almost one-third (3970/12,725, 31.2%) indicated that they play games for at least 3.5 hours a day. The correlation between time spent playing video games overall and well-being was not significant (P=.41). The latent profile analysis distinguished 6 profiles of adolescent heavy gamers: adaptive computer gamers (1747/3970, 44%); casual computer gamers (873/3970, 22%); casual phone gamers (595/3970, 15%); unknown device gamers (476/3970, 12%); maladaptive computer gamers (238/3970, 6%); and maladaptive phone gamers (79/3970, 2%). In comparison with adaptive computer gamers, maladaptive phone gamers were mostly female (odds ratio [OR] 0.08, 95% CI 0.03-0.21) and were more likely to have experienced abuse or neglect (OR 3.18, 95% CI 1.34-7.55). Maladaptive computer gamers, who reported gaming both on their mobile phones and on the computer, were mostly male and more likely to report anxiety (OR 2.25, 95% CI 1.23-4.12), aggressive behavior (OR 2.83, 95% CI 1.65-4.88), and web-based gambling (OR 2.18, 95% CI 1.24-3.81). Conclusions: A substantial number of adolescents are spending ≥3.5 hours gaming each day, with almost 1 in 10 (317/3970, 8%) reporting co-occurring gaming and well-being issues. Long hours gaming using mobile phones, particularly common in female gamers, may signal poorer functioning and indicate a need for additional support. Although increased time gaming might be changing how adolescents spend their free time and might thus have public health implications, it does not seem to relate to co-occurring well-being issues or mental ill-health for the majority of adolescent gamers

The association between adolescents’ online behaviours and mental health and loneliness

Time spent online and on social media has risen rapidly amongst adolescents over the last decade. Over the same period of time, rates of suicide, non-suicidal self-harm, and common mental disorders have increased, particularly amongst females. Digital technologies have been linked to several positive outcomes, including peer and professional online support and social connection. However, research also indicates that some online behaviour, including exposure to harmful content, and excessive time spent online, may be linked to depression, suicide, and self-harm, particularly among girls and marginalised groups. Findings from several studies suggest that social media use may be associated with poorer mental health in adolescents. For example, data from the Millennium Cohort Study suggests that a greater amount of time spent on social media on a weekday is associated with an increased risk of self-harm for adolescent females, alongside increased depressive symptoms, and poor self-esteem. Similarly, research indicates that greater time spent on social networking websites can lead to higher psychological distress. Relatedly, young people may be exposed to harmful content while spending time online. Using the OxWell 2021 secondary school data, the overarching aim of this paper is to examine the association between adolescent online behaviours and mental health and loneliness

Mental health support seeking in adolescents: the moderating role(s) of self-harm and neurodiversity

Pre-registratio

Dataset: Examining the Relationship Between Children&rsquo;s Screen Use and Externalising Behaviours

The data set was used in the thesis entitled &#39;Examining the Relationship Between Children&rsquo;s Screen Use and Externalising Behaviours&#39; and includes data on the three primary outcome variables (child externalising problems, active and passive screen use) as well as data on the control variables (participant age, parental depression, anxiety and stress scores, parental educational attainment and child gender) at two time points.</span