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Background: Excessive engagement with digital screens is harmful to children's health. However, new evidence suggests that exposure at moderate levels may not be harmful and may even provide benefit. Therefore, our objective was to determine if there are curvilinear relationships between different types of screen time and a diverse set of outcomes, including health and education., Methods: We address our objective using a repeated measures design. Children (N = 4013), initially aged 10-11 were assessed every 2 years between 2010 and 2014. Children's screen time behavior was measured using time-use diaries, and categorized into five types: social, passive, interactive, educational, or other. We used measures of children's physical health, health-related quality of life, socio-emotional outcomes, and school achievement. The analysis plan was pre-registered. Models were adjusted for gender, socio-economic status, ethnicity, number of siblings, and housing factors., Results: There were linear associations between total screen time and all outcomes, such that more screen time was associated with worse outcomes. However, there was variability when examined by screen time type. Passive screen time (e.g., TV) was associated with worse outcomes, educational screen time (e.g., computer for homework) was associated with positive educational outcomes and had no negative relations with other outcomes. Interactive screen time (e.g., video games) had positive associations with educational outcomes but negative associations with other outcomes. In all instances, these significant associations were small or very small, with standardised effects < 0.07. We found little evidence of curvilinear relationships., Conclusions: The small effects of screen time on children's outcomes appear to be moderated by the type of screen time. Policy makers, educators, and parents should consider the type of screen time when considering the benefits and harms of use.

Background: Abundant evidence demonstrates a relationship between physical activity and mental wellbeing. However, the strength of the relationship is not consistent. Factors contributing to variation in the strength of association are not well understood and, therefore, it remains difficult to optimize physical activity to ensure the strongest possible relationship with mental health. Self-determination theory suggests that more autonomously motivated behaviors lead to better mental health outcomes, when compared to more controlled behaviors. Therefore, we examined whether autonomous and controlled motivation moderated the relationships between physical activity and affective wellbeing within two domains (i.e., leisure-time and active travel)., Methods: Between February and April 2014, adolescents (N = 1632, M age = 12.94 years, SD = 0.54, 55% male) wore an accelerometer across seven-days and completed self-report measures of leisure-time physical activity and active travel. They also completed two measures of motivation (towards leisure-time physical activity and active travel) and an affective wellbeing measure., Results: Structural equation modeling revealed that greater self-reported leisure-time physical activity was associated with greater positive affect (β = .29) and less negative affect (β = -.19) and that motivation did not moderate these relationships. Self-reported active travel had no linear relationship with affective wellbeing, and motivation did not moderate these relationships. Accelerometer-measured leisure-time physical activity had no relationship with positive affect but, had a weak inverse association with negative affect (β = -.09), and neither relationship was moderated by motivation. Accelerometer-measured active travel had no association with positive affect; however, autonomous motivation significantly moderated this association such that active travel had a positive association with positive affect when autonomous motivation was high (β = .09), but a negative association when autonomous motivation was low (β = -.07). Accelerometer-measured active travel had no association with negative affect. Despite some significant moderation effects, motivation did not consistently moderate the relationship between all physical activity variables (leisure-time and active travel, and self-report and accelerometer) and affective outcomes., Conclusions: Tailoring physical activity interventions and guidelines to prioritize leisure-time ahead of other life domains could benefit wellbeing. Promoting autonomous participation in active travel may also be associated with increased wellbeing among adolescents.

Background: Gender bias within medical education is gaining increasing attention. However, valid and reliable measures are needed to adequately address and monitor this issue. This research conducts a psychometric evaluation of a short multidimensional scale that assesses medical students' awareness of gender bias, beliefs that gender bias should be addressed, and experience of gender bias during medical education., Methods: Using students from the University of Wollongong, one pilot study and two empirical studies were conducted. The pilot study was used to scope the domain space (n = 28). This initial measure was extended to develop the Gender Bias in Medical Education Scale (GBMES). For Study 1 (n = 172), confirmatory factor analysis assessed the construct validity of the three-factor structure (awareness, beliefs, experience) and enabled deletion of redundant items. Study 2 (n = 457) tested the generalizability of the refined scale to a new sample. Combining Study 1 and 2, invariance testing for program of study and gender was explored. The relationship of the GBMES to demographic and gender politics variables was tested. The results were analyzed in R using confirmatory factor analysis and Multiple-Indicator-Multiple-Indicator-Cause models., Results: After analysis of the responses from the original 16-item GBMES (Study 1), a shortened measure of ten items fitted the data well (RMSEA = .063; CFI = .965; TLI = .951; Mean R-square of items = 58.6 %; reliability: .720-.910) and was found to generalize to a new sample in Study 2 (RMSEA = .068; CFI = .952; TLI = .933; Mean R-square of items = 55.9 %; reliability: .711-.892). The GBMES was found to be invariant across studies, gender, and program of study. Female students and those who supported gender equality had greater agreement for each of the factors. Likewise, postgraduate students reported higher scores on experience of gender bias than undergraduate students., Conclusion: The GBMES provides a validated short multidimensional measure for use in research and policy. Given its good reliability across different target populations and its concise length, the GBMES has much potential for application in research and education to assess students' attitudes towards gender bias.