We investigated the relationship between process quality in early childhood education and care (ECEC) and children’s socio-emotional development in a meta-analysis of longitudinal studies. Our multi-level meta-analysis of 31 publications reporting on 16 longitudinal studies (N = 17,913 children, age: 2.5–18 yrs) demonstrates that the process quality of ECEC is a small but significant predictor of children’s socio-emotional development over time (ES = 0.103, SE = 0.026, p < 0.001, 95% CI: 0.052–0.155). This longitudinal association extends to the age of 18 years in our sample. Process quality of ECEC is, thus, a significant and stable predictor of children’s socio-emotional development and well-being from toddlerhood to adolescence. The longitudinal relationship was moderated by the type of care (center-based vs. home-based) and the informant (parent, professional caregiver, external assessor, or self-report of the child). Implications for future ECEC research are discussed.
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Previous research has suggested that professional youth work settings empower socially vulnerable youngsters, strengthening their personal development and social participation. It is expected that youth work can prevent personal and social problems of youngsters, which may have longer term positive social returns. How the underlying methodical way of acting of youth workers contributes to prevention-focused outcomes remains unclear. This article presents a four-wave longitudinal cohort study (16 months) that investigated longitudinal associations between 12 individual methodical principles that youth workers apply in interactions with youngsters and four prevention-focused outcomes: prosocial skills, self-mastery, social network and civic participation. The sample consisted of 1,597 Dutch youngsters with a mean age of 16.5 years (SD = 3.60). Findings: Linear mixed models analysis found that all individual methodical principles were longitudinally associated with one or more outcome. The strongest associations were observed with regard to prosocial skills and civic participation. Depending on the outcome measure, methodical principles seem to be more effective for boys, for youngsters who participate for 3 years or longer in youth work settings and for youngsters between 10 and 19 years old. With regard to the effect of methodical principles on improving self-mastery, 9 of the 12 principles appeared to play no positive role in increasing self-mastery of youngsters. Applications: This study provides youth workers with a better understanding of which methodical principles are positively associated with prevention-focused outcomes as well as reinforcing the evidence-based practice of professional youth work.
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Background:Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology.Objective:In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern.Methods:We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray’s work was combined with an inductive approach in which new themes were discovered.Results:Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of “whom” to believe, the machine or one’s self.Conclusions:There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally “dumb” body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.
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Vacation travel is an essential ingredient in quality of life. However, the contriubtion of vacations to quality of life could be improved in two ways: by optimizing the decisions people make when planning and undertaking their vacations, and by travel industry testing and implementing––based on evidence––innovative experience products which touch customers' emotions. Secondary analysis of two longitudinal panel datasets will address the impact of people's decisions in planning and undertaking their vacations, on their quality of life. Field experiments in cooperation with travel industry partners will address the effects of innovative experience products, such as apps designed to help vacationers meet fellow travelers, or personalized memory books designed to help people relive their vacations after return home. Experience data in these field experiments will be collected using technology of the Breda University of Applied Sciences' Experience Measurement Lab, a unique facility for measuring emotions continuously from research participants' body and mind. Thus, the project will contribute to general understanding of quality of life, will feed valuable knowledge about experience design, measurement, and implementation to the Dutch travel industry, and will support the Breda University of Applied Sciences' key research theme of Designing, Measuring, and Managing Experiences. Inspiring examples from the project will reinforce research methods courses in the academic Bachelor of Science in Tourism, the HBO Master in Tourism Destination Management, and the academic Master of Science in Leisure Studies. Wearable emotion measurement from the field experiment will be a cornerstone of the fourth-year HBO-bachelor module Business Intelligence, where students will conduct their own research projects on experience measurement using consumer wearables, based on knowledge from this postdoc project. Finally, a number of methodological and content questions within the project will serve as suitable thesis assignments for graduation students in the above educational tracks.
Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
