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.
Purpose The aim of this study was to gain insight into the perspectives of older adults on the quality of geriatric rehabilitation (GR) during the trajectory of GR from admission until six weeks after discharge.Methods We conducted a longitudinal qualitative study. Participants were interviewed three times: at the start of rehabilitation, at discharge, and six weeks after discharge. The data were analysed using a thematic analysis.Results In total, 50 interviews were conducted, with 18 participants being interviewed multiple times. The following themes emerged: 1. A bond of trust with health care professionals (HCPs), 2. Being prepared and informed at all stages of GR, 3. Participants emphasise physical and occupational therapy rather than other aspects of care as comprising GR 4. Changing needs regarding (the extent of) involvement in decision-making, 5. Contact with family and peers.Conclusion For older adults, preparation for and good organisation of rehabilitation and social interaction with HCPs and other older adults were found to be important for the perceived quality of GR. Social interaction is infuenced by how HCPs engage with older adults in all the phases of the rehabilitation process. Older adults have varying preferences about involvement in decision-making during GR. These perspectives should be acknowledged and acted upon in clinical practice to further improve the quality of care in GR.
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Longitudinal criminological studies greatly improved our understanding of the longitudinal patterns of criminality. These studies, however, focused almost exclusively on traditional types of offending and it is therefore unclear whether results are generalizable to online types of offending. This study attempted to identify the developmental trajectories of active hackers who perform web defacements. The data for this study consisted of 2,745,311 attacks performed by 66,553 hackers and reported to Zone-H between January 2010 and March 2017. Semi-parametric group-based trajectory models were used to distinguish six different groups of hackers based on the timing and frequency of their defacements. The results demonstrated some common relationships to traditional types of crime, as a small population of defacers accounted for the majority of defacements against websites. Additionally, the methods and targeting practices of defacers differed based on the frequency with which they performed defacements generally.
Physical rehabilitation programs revolve around the repetitive execution of exercises since it has been proven to lead to better rehabilitation results. Although beginning the motor (re)learning process early is paramount to obtain good recovery outcomes, patients do not normally see/experience any short-term improvement, which has a toll on their motivation. Therefore, patients find it difficult to stay engaged in seemingly mundane exercises, not only in terms of adhering to the rehabilitation program, but also in terms of proper execution of the movements. One way in which this motivation problem has been tackled is to employ games in the rehabilitation process. These games are designed to reward patients for performing the exercises correctly or regularly. The rewards can take many forms, for instance providing an experience that is engaging (fun), one that is aesthetically pleasing (appealing visual and aural feedback), or one that employs gamification elements such as points, badges, or achievements. However, even though some of these serious game systems are designed together with physiotherapists and with the patients’ needs in mind, many of them end up not being used consistently during physical rehabilitation past the first few sessions (i.e. novelty effect). Thus, in this project, we aim to 1) Identify, by means of literature reviews, focus groups, and interviews with the involved stakeholders, why this is happening, 2) Develop a set of guidelines for the successful deployment of serious games for rehabilitation, and 3) Develop an initial implementation process and ideas for potential serious games. In a follow-up application, we intend to build on this knowledge and apply it in the design of a (set of) serious game for rehabilitation to be deployed at one of the partners centers and conduct a longitudinal evaluation to measure the success of the application of the deployment guidelines.
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.
