The results of a program of research designed to produce an adequate measure of the type A behavior pattern in children are reported. The type A pattern is a risk factor for heart disease in adulthood and is characterized by extremes of competitiveness, impatience, easily aroused anger, and aggression. A questionnaire called the Matthews Youth Test for Health (MYTH-Form O) contains 17 statements that characterize pattern A behaviors in children. Study 1 was conducted to provide psychometric data for the MYTH. Teachers rated how well these statements characterized 485 children enrolled in grades K, 2, 4 and 6. Those children remaining in the school district 3 months later (N = 420) were rated again. Statistical analyses of these ratings suggest that the MYTH-Form O is a reliable, internally consistent instrument, which yields 2 orthogonal factors: competitiveness and impatience-aggression. As expected, there were substantial gender differences in children's type A behavior. Study 2 tested the construct validity of the MYTH in a subsample of children who were challenged to win a car race against an experimenter; were given an opportunity to play with a variety of toys, including a plastic Bobo doll; and were asked to execute a frustrating task during 1 session. Results showed that type A's won a race against a female (not a male) experimenter by a larger margin than did type B's. Type A's aggressed against a Bobo doll earlier and were more impatient than were type B's throughout the session. These impatient behaviors exhibited by child type A's are similar to those exhibited by adult type A's during the standardized adult type A interview. In sum, these data are supportive of the reliability and validity of the MYTH and represent a first step in the development of an instrument to assess pattern A in elementary school-aged children.

Abstract. The use of mobile smart devices for storing sensitive information and accessing online services is increasing. At the same time, methods for authenticating users into their devices and online services that are not only secure, but also privacy and user-friendly are needed. In this paper, we present our initial explorations of the use of lock pattern dynamics as a secure and user-friendly two-factor authentication method. We developed an application for the Android mobile platform to collect data on the way individuals draw lock patterns on a touchscreen. Using a Random Forest machine learning classifier this method achieves an average Equal Error Rate (EER) of approximately 10.39%, meaning that lock patterns biometrics can be used for identifying users towards their device, but could also pose a threat to privacy if the users' biometric information is handled outside their control.

This paper discusses the approach taken within the PrimeLife project for providing userfriendly privacy policy interfaces for the PrimeLife Policy Language (PPL). We present the requirements, design process and usability testing of the "Send Data?" prototype, a browser extension designed and developed to deal with the powerful features provided by PPL. Our interface introduces the novel features of "on the fly" privacy management, predefined levels of privacy settings, and simplified selection of anonymous credentials. Results from usability tests showed that users understand and appreciate these features and perceive them as being privacy-friendly, and they are therefore suggested as a good approach towards usable privacy policy display and management. Additionally, we present our lessons learn in the design process of privacy policy interfaces.

Transparency is a basic privacy principle and social trust factor. However, in the age of cloud computing and big data, providing transparency becomes increasingly a challenge. This paper discusses privacy requirements of the General Data Protection Regulation (GDPR) for providing ex-post transparency and presents how the transparency-enhancing tool Data Track can help to technically enforce those principles. Open research challenges that remain from a Human Computer Interaction (HCI) perspective are discussed as well.

Shame is a self-conscious emotion marked by an intensely negative self-evaluation. It is exhibited by an individual upon realizing that she/he has violated an important (usually social) norm. Shame can be a source of emotional distress leading to social withdrawal and depression, with a significant negative impact on quality of life. In Parkinson’s disease (PD), shame is rarely addressed. Based on reports of persons affected with Parkinson’s disease (PwP) as well as a literature review, this article describes PD-related shame. PD-related shame may emerge from motor and non-motor symptoms, from self-perception of inadequacy due to loss of autonomy and need for help, or from perceived deterioration of body image. The neurobiology of shame delineates neuronal networks involved in cognitive and emotions regulation, self-representation and representation of the others mental states. Although this hypothesis remains to be demonstrated, these substrates could be modulated, at least partially, by dopaminergic depletion related to PD, which may open a window for pharmacotherapy. Owing to the negative impact that shame can produce, shame should be actively explored and addressed in the individual PwP. Teaching PwP how to develop resilience to shame may be a useful strategy in preventing the vicious circle of shame. The paucity of existing data on prevalence and management of PD-specific shame contrasts with the manifold reported situations inducing suffering from shame. There is a crucial need for further investigations of shame in PD and the development of interventions to reduce its impact on PwP’s quality of life.