This study aims to contribute to the evaluation of online therapy during Covid-19 pandemic lockdowns, by exploring family therapists’ experiences of therapy for twelve Sibling Sexual Abuse (SSA) families in the Netherlands. Seven transcripts of interviews with highly specialised Dutch family therapists were analysed using thematic analysis (TA). Two main findings emerged from this study. First, the Dutch therapists reported no acute worries about their clients’ sexual safety during the pandemic lockdowns. Nonetheless, the switch to online therapy for the SSA families created concern regarding victim safety in speaking out freely at home. Second, while the sudden switch to online therapy enabled SSA therapists to stay connected with their SSA families, therapists experienced a decline in therapy quality and in their own well-being. In the therapists’ experience, it was almost impossible to conduct their most fundamental interventions online, such as intervening in family relationships.
When analysing the legitimacy of the welfare state, perceptions of the overuse and underuse of welfare are of great importance. Previous literature suggests that many people perceive overuse (misuse or fraud), and there is evidence that people also perceive underuse (non-take-up) of welfare benefits. Perceptions of overuse have therefore been called ‘the Achilles’ heel of welfare state legitimacy'. We analyse data from the European Social Survey for 25 countries and investigate the occurrence and the individual and contextual determinants of overuse and underuse perceptions. We find that both overuse and underuse perceptions are prevalent in all European countries. However, whereas overuse perceptions are more related to ideology, collective images of welfare recipients and selective welfare regimes, underuse perceptions are more shaped by self-interest and the levels of unemployment and social spending in a country. Instead of one Achilles' heel, welfare state legitimacy seems to have two weak spots.Key words: Benefit abuse, European Social Survey, non-take-up, welfare attitudes, welfare states
With these results at hand we developed a new program and evaluated it . In this presentation we will reflect on the merits of this program but also share with you the insight gained from other studies that we did to in the context of the program. First a study on the prevalence to give us an indication of how many people with SMI have responsibilities as a parent. Working through these figures we have been wondering about the international differeecs in this aspect. Maybe you as an international crowd can help us to gain more insight in this subject. Second I will describe the intervention that was developed based on the imput of clients and building on the vision and methods of the Boston approach to rehabilition. At this moment more then 100 counselors are trained in this approach. To evaluate the intervention offered and establish some figures on its effectiveness, a quasi experimental study was done and I will present some of the results in the ample time we have. When developing the program and making an effort in implementing it in mental helath care, we became aware that there was still a lot to learn from both parents and mental health workers. During the experimental study, we learned that not many parents actually ask for support and that workers were enthousiastic about the training but did not find ways to implenent the program at full course. In this line of reasoning it became important to speak with different parents with SMI about the meaning of parenthood, how they succesfully dealt with the demands of parenting, waht it meant for their recovery and what kind of resources they used.
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.
