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The closing of schools and sports clubs during theCOVID-19 lockdown raised questions about thepossible impact on children’s motor skilldevelopment. Therefore we compared motorcompetence development over a one-year periodamong four different cohorts of primary schoolchildren. A total of 992 children from 9 primaryschools participated in this study (age 5 – 7; 47,5%boys) and were assessed two times, in grade 3 (T1)and in grade 4 (T2). Children in control group 1 and lockdown group 1 were assessed a third time aftertwo years (T3). Motor competence was measuredusing the 4-Skills Test. The mixed factorial ANOVAwith post hoc tests shows no significant differencesin motor development over the study period betweenthe lockdown groups and control groups (p > 0.05),but does show a difference between the twolockdown groups from T1 to T2 (p = 0.008). Whilesocioeconomic status (SES) was a modifier, sex andmotor ability did not modify the effects of thelockdowns. Our data show that the COVID-19lockdowns in the Netherlands did not generallyaffect motor development of young children. Incontrast, many studies have confirmed clear effectsof the pandemic lockdowns on physicalactivity1,2,3. Our study highlights the complexity ofboth motor skill development and the factors relatedto the pandemic lockdowns. We therefore suggestthat children’s motor skill development should beclosely monitored in the upcoming years.Specifically, we should pay attention to individualdifferences since it is still possible that certainchildren are impacted by the pandemic lockdowns.Moreover, long-term effects might emerge in thefuture.References1. de Sá, C. dos S. C., Pombo, A., Luz, C.,Rodrigues, L. P., & Cordovil, R. (2021). Covid-19social isolation in brazil: effects on the physicalactivity routine of families with children. RevistaPaulista de Pediatria, 39, e2020159.2. Hurter, L., McNarry, M., Stratton, G., &Mackintosh, K. (2022). Back to school afterlockdown: The effect of COVID-19 restrictions onchildren’s device-based physical activity metrics.Journal of Sport and Health Science, 11(4), 530–536.3. Moore, S. A., Faulkner, G., Rhodes, R. E.,Brussoni, M., Chulak-Bozzer, T., Ferguson, L. J.,Mitra, R., O’Reilly, N., Spence, J. C., Vanderloo, L.M., & Tremblay, M. S. (2020). Impact of theCOVID-19 virus outbreak on movement and playbehaviours of Canadian children and youth: Anational survey. International Journal of BehavioralNutrition and Physical Activity, 17(1), 85.
In recent years, a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organizations alike. This article discusses the current state of the art in the adoption of Industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of Industry 4.0 technologies. This article discusses the relevance of the following key Industry 4.0 technologies to construction: data analytics and artificial intelligence, robotics and automation, building information management, sensors and wearables, digital twin, and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This article also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector, a three-phase use of intelligent assets from the point of manufacture up to after build, and a four-staged R&D process for the implementation of smart wearables in a digital enhanced construction site.
Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI. Objective: The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement. Methods: A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage. Results: Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age. Conclusions: This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.
The healthcare sector has been confronted with rapidly rising healthcare costs and a shortage of medical staff. At the same time, the field of Artificial Intelligence (AI) has emerged as a promising area of research, offering potential benefits for healthcare. Despite the potential of AI to support healthcare, its widespread implementation, especially in healthcare, remains limited. One possible factor contributing to that is the lack of trust in AI algorithms among healthcare professionals. Previous studies have indicated that explainability plays a crucial role in establishing trust in AI systems. This study aims to explore trust in AI and its connection to explainability in a medical setting. A rapid review was conducted to provide an overview of the existing knowledge and research on trust and explainability. Building upon these insights, a dashboard interface was developed to present the output of an AI-based decision-support tool along with explanatory information, with the aim of enhancing explainability of the AI for healthcare professionals. To investigate the impact of the dashboard and its explanations on healthcare professionals, an exploratory case study was conducted. The study encompassed an assessment of participants’ trust in the AI system, their perception of its explainability, as well as their evaluations of perceived ease of use and perceived usefulness. The initial findings from the case study indicate a positive correlation between perceived explainability and trust in the AI system. Our preliminary findings suggest that enhancing the explainability of AI systems could increase trust among healthcare professionals. This may contribute to an increased acceptance and adoption of AI in healthcare. However, a more elaborate experiment with the dashboard is essential.
The potential for Artificial Intelligence is widely proclaimed. Yet, in everyday educational settings the use of this technology is limited. Particularly, if we consider smart systems that actually interact with learners in a knowledgeable way and as such support the learning process. It illustrates the fact that teaching professionally is a complex challenge that is beyond the capabilities of current autonomous robots. On the other hand, dedicated forms of Artificial Intelligence can be very good at certain things. For example, computers are excellent chess players and automated route planners easily outperform humans. To deploy this potential, experts argue for a hybrid approach in which humans and smart systems collaboratively accomplish goals. How to realize this for education? What does it entail in practice? In this contribution, we investigate the idea of a hybrid approach in secondary education. As a case-study, we focus on learners acquiring systems thinking skills and our recently for this purpose developed pedagogical approach. Particularly, we discuss the kind of Artificial Intelligence that is needed in this situation, as well as which tasks the software can perform well and which tasks are better, or necessarily, left with the teacher.
Het voorkomen van voedselverspilling en het verduurzamen van de voedselproductie staan hoog op de politieke en maatschappelijke agenda. In de glastuinbouwsector doen zich ziekten voor bij de teelt van gewassen en treedt bederf op in de logistieke keten. Conventionele, handmatige bestrijdingsmethoden brengen hoge kosten met zich mee en leiden tot overmatig gebruik van bestrijdingsmiddelen. Het lectoraat Fotonica van De Haagse Hogeschool leidt het brede praktijkgerichte onderzoeksproject The Detectable Vegetable om met de (door)ontwikkeling van contactloze sensortechnologie en data-intelligentie ziekte en bederf van tuinbouwgroenten vroegtijdig te detecteren.
