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Abstract Background The decline in physical activity (PA) during adolescence is well-established. However, while some subgroups of adolescents follow the general pattern of decreased activity, others increase or maintain high or low activity. The correlates and determinants of different PA patterns may vary, offering valuable information for targeted health promotion. This study aimed to examine how psychosocial factors, health behaviours, and PA domains are associated with longitudinal PA patterns from adolescence to young adulthood. Methods This prospective study encompassed 254 participants measured at mean ages 15 and 19. Device-measured moderate-to-vigorous PA was grouped into five patterns (activity maintainers, inactivity maintainers, decreasers from moderate to low PA, decreasers from high to moderate PA, increasers) via a data-driven method, K-Means for longitudinal data. Multinomial logistic regression was used to analyse the associations between health behaviours, psychosocial factors, PA domains, and different PA patterns. Results A lack of sports club participation characterised inactivity maintainers throughout adolescence. Difficulties in communicating with one’s father at age 15 were associated with higher odds of belonging to inactivity maintainers and to decreasers from moderate to low PA. Lower fruit and vegetable consumption at age 19 was also related to increased odds of belonging to the groups of inactivity maintainers and decreasers from moderate to low PA. Smoking at age 19 was associated with being a decreaser from moderate to low PA. Conclusions Diverse factors characterise longitudinal PA patterns over the transition to young adulthood. Sports club participation contributes to maintained PA. Moreover, a father-adolescent relationship that supports open communication may be one determinant for sustained PA during adolescence. A healthier diet and non-smoking as a young adult are associated with more favourable PA development.

Although eye tracking has been successfully used in science education research, exploiting its potential in collaborative knowledge construction has remained sporadic. This article presents a novel approach for studying collaborative knowledge construction in a simulation-based environment by combining both the spatial and temporal dimensions of eye-tracking data with video data. For this purpose, we have investigated two undergraduate physics student pairs solving an electrostatics problem in a simulation-based environment via Zoom. The analysis of the video data of the students’ conversations focused on the different collaborative knowledge construction levels (new idea, explication, evaluation, and non-content-related talk and silent moments), along with the temporal visualizations of the collaborative knowledge construction processes. The eye-tracking data of the students’ gaze, as analyzed by epistemic network analysis, focused on the pairs’ spatial and temporal gaze behavior. We illustrate how gaze behavior can shed light on collaborative knowledge construction in terms of the quantity of the talk (e.g., gaze behavior can shed light on the different activities of the pairs during the silent moments), quality of the talk (e.g., gaze behavior can shed light on the different approaches when constructing knowledge on physical phenomena), and temporality of collaborative knowledge construction processes [e.g., gaze behavior can shed light on (the lack of) attempts to acquire the supporting or contrasting evidence on the initial ideas on the physical phenomena]. We also discuss the possibilities and limitations of gaze behavior to reveal the critical moments in the collaborative knowledge construction processes.

Abstract Background Longitudinal studies demonstrate an average decline in physical activity (PA) from adolescence to young adulthood. However, while some subgroups of adolescents decrease activity, others increase or maintain high or low activity. Activity domains may differ between subgroups (exhibiting different PA patterns), and they offer valuable information for targeted health promotion. Hence, the aim of this study was to identify PA patterns from adolescence to young adulthood; also to explore the associations of (i) changes in PA domains and in sedentary time, (ii) sociodemographic factors, and (iii) self-rated health with diverging PA patterns. Methods The observational cohort study data encompassed 254 adolescents at age 15 and age 19. K-means cluster analysis for longitudinal data was performed to identify participant clusters (patterns) based on their accelerometry-measured moderate-to-vigorous PA (MVPA). Logistic regressions were applied in further analysis. Results Five PA patterns were identified: inactivity maintainers (n = 71), activity maintainers (n = 70), decreasers from moderate (to low) PA (n = 61), decreasers from high (to moderate) PA (n = 32), and increasers (n = 20). At age 15, participation in sports clubs (SC, 41–97%) and active commuting (AC, 47–75%) was common in all the patterns. By age 19, clear dropout from these activities was prevalent (SC participation mean 32%, AC 31–63%). Inactivity maintainers reported the lowest amount of weekly school physical education. Dropout from SC – in contrast to non-participation in SC – was associated with higher odds of being a decreaser from high PA, and with lower odds of being an inactivity maintainer. Maintained SC participation was associated with higher odds of belonging to the decreasers from high PA, and to the combined group of activity maintainers and increasers; also with lower odds of being an inactivity maintainer. Maintenance/adoption of AC was associated with decreased odds of being an inactivity maintainer. Self-reported health at age 19 was associated with the patterns of maintained activity and inactivity. Conclusions PA patterns diverge over the transition to adulthood. Changes in SC participation and AC show different associations with diverging PA patterns. Hence, tailored PA promotion is recommended.

The COVID-19 pandemic forced teachers to undergo a sudden shift toward technology-enhanced teaching and learning, challenging their capacities for change in many ways. This study explores those factors constraining teachers’ wellbeing and agency that influenced their capacities as teachers in a Finnish university during the first year of the pandemic. Two sets of data were collected, with an online survey in the spring (n = 297) and autumn (n = 246) of 2020. At both times, challenges with workload, time management, and interactions with colleagues were found to be the most constraining factors. Difficulties with work–life balance and home office facilities seemed more of an issue in the spring, whereas transforming teaching and adopting new technological tools were reported as more burdensome in the autumn. The findings show the need for teachers to be heard and holistically supported, particularly when extensive changes in teaching arrangements are expected on a rapid schedule.

This study was conducted to determine how total fundamental movement skill (FMS) score and, separately, locomotor skill (LMS), and object control skill scores in children 3-8 years old predicted their specific-intensity physical activity 3 years later. Overall, 441 Finnish children (51.7% female, baseline mean age of 5.6 years) participated in the study. Total FMS, LMS, and object control skill scores were assessed using the Test of Gross Motor Development, third edition. The time spent engaged in physical activity of different intensities (light, moderate, vigorous, moderate-to-vigorous, light-to-vigorous, and sedentary behavior) was determined using accelerometers. A two-level regression model was used in the analysis, considering potential covariates and interactions. The results showed that moderate physical activity, vigorous physical activity, and moderate-to-vigorous physical activity were predicted by the total FMS score ([beta] = 0.177 to 0.203, p = 0.001-0.003) and the LMS score ([beta] = 0.140 to 0.164, p = 0.004-0.014), but not the object control skill score. Moreover, the LMS score inversely predicted sedentary behavior ([beta] = -0.116, p = 0.042). In conclusion, higher FMS and, specifically, LMS scores seem to predict more engagement in moderate-to-vigorous physical activity and less sedentary behavior over time. However, most of the variance in physical activity remains unexplained.