Risk factors associated with online game addiction: A hierarchical model

Online gaming addiction has been increasingly recognized as a mental disorder. However, the predictive factors that lead to online gaming addiction are not well established. The aim of this study was to identify factors that may influence the development of online gaming addiction. A total of 263 patients with problematic online gaming addiction (255 males (97%) and 8 females (3%), age: mean = 20.4 ± 5.8 years) and153 healthy comparison subjects (118 males (77%) and 35 females (23%), age: 21.2 ± 5.5 years, range) were recruited for participation in the current study. Hierarchical logistic regression analyses among each set of variables were conducted. Individual factors (sex and age), cognitive factors (IQ and perseverative errors), psychopathological conditions (ADHD, depression, anxiety, and impulsivity), and social interaction factors (family environment, social anxiety, and self-esteem) were evaluated in a stepwise fashion. All four factors were associated with online gaming addiction, with psychopathological conditions being the strongest risk factors for the addiction. Individual factors, psychological factors, and social interactions were associated with the development of pure online gaming addiction. As before, psychological factors (attention, mood, anxiety and impulsivity) were the strongest risk factors for online gaming addiction in patients with pure online gaming addiction. Psychopathologies, including ADHD and depression, were the strongest factors associated with the development of online gaming addiction in individuals.     

On keys' meanings and modes: the impact of different key solutions on children's efficiency using a mobile phone

The present study investigates the impact of different key solutions of mobile phones on users' effectiveness and efficiency using the devices. In the first experiment, 36 children (9 - 14 years) and in the second experiment 45 young adults (19 - 33 years) completed four common phone tasks twice consecutively on three simulated phones that had identical menus, but different key solutions. An approach was undertaken to quantify the complexity of keys in three models, incorporating different factors contributing to the keys' complexity (number of key options, number of modes and number of modes with a semantically dissimilar meaning), in order to predict users' performance decrements. As a further main factor, the degree of the users' locus of control (LOC) was measured and interactions with performance outcomes were studied. As dependent measures, the number of inefficient keystrokes, the number of tasks solved and the processing time were determined. Results showed a significant effect of control key solutions on users' efficiency and effectiveness for both children and young adults. Moreover, children's LOC values significantly interacted with performance: children with low LOC values showed the lowest performance and no learnability, especially when using keys with a high complexity. From the three factors contributing to the complexity of keys, keys exerting different functions with semantically inconsistent meanings had the worst effect on performance. It is concluded that in mobile user interface design keys with semantically inconsistent meanings should be generally avoided.     

Sociotechnical systems, risk management, and public health: comparing the North Battleford and Walkerton outbreaks

Accidents in different complex sociotechnical systems are rarely compared using the same theoretical framework for risk management. We conducted a comparative analysis of two Canadian public health disasters involving drinking water distribution systems, the North Battleford Cryptosporidium parvum outbreak in April 2001 and the Walkerton E. coli outbreak in May 2000. Both accidents resulted from a complex interaction between all levels of a complex sociotechnical system. However, the low-level physical and individual factors differed in the two cases, whereas, the high-level governmental and regulatory factors tended to be the same. These findings may have implications for the design of public policies to minimize risk in complex sociotechnical systems.     

Emergency department status boards: user-evolved artefacts for inter- and intra-group coordination

Large, easily viewed status boards are commonly used in some healthcare settings such as emergency departments, operating theaters, intensive care units, and inpatient wards. Because these artefacts were developed by front-line users, and have little to no supervisory or regulatory control, they offer valuable insights into the theories of work and hazard held by those users. Although the status boards case were locally developed over many years for within-group coordination, they have also become useful for between-group coordination across organizational boundaries. In this paper, we compare and contrast the use of such status boards in two disparate settings: a US emergency department, and a UK pediatric ward, and note striking similarities in their form and usage, despite the large differences in setting.     

Fodor and Pylyshyn on connectionism

Fodor and Pylyshyn (1988) have argued that the cognitive architecture is not Connectionist. Their argument takes the following form: (1) the cognitive architecture is Classical; (2) Classicalism and Connectionism are incompatible; (3) therefore the cognitive architecture is not Connectionist. In this essay I argue that Fodor and Pylyshyn's defenses of (1) and (2) are inadequate. Their argument for (1), based on their claim that Classicalism best explains the systematicity of cognitive capacities, is an invalid instance of inference to the best explanation. And their argument for (2) turns out to be question-begging. The upshot is that, while Fodor and Pylyshyn have presented Connectionists with the important empirical challenge of explaining systematicity, they have failed to provide sufficient reason for inferring that the cognitive architecture is Classical and not Connectionist.     

Differentiating anxiety and depression in older adults with generalized anxiety disorder.

To examine affect and cognition in differentiating anxiety and depression, 83 older participants with generalized anxiety disorder completed the Cognitive Checklist (CCL) and the Positive and Negative Affect Schedule (PANAS). A 3-factor solution was found for the PANAS: positive affect (PA), anxiety and anger (Negative Affect 1 [NA-1]), and guilt and shame (Negative Affect 2 [NA-2]). A 2-factor structure was noted for the CCL. Correlations with anxiety and depression measures suggested that the CCL Depression (CCL-D) subscale showed stronger correlations with depression, whereas the CCL Anxiety subscale did not uniquely correlate with anxiety. The NA-1 subscale correlated positively with measures of depression and anxiety, whereas the PA subscale showed negative correlations. Hierarchical regression suggested that the CCL-D subscale was a significant predictor of self-reported depression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Co-evolution as a computational and cognitive model of design

Co-evolutionary design has been developed as a computational model that assumes two parallel search spaces: the problem space and the solution space. The design process iteratively searches each space using the other space as the basis for a fitness function when evaluating the alternatives. Co-evolutionary design can also be developed as a cognitive model of design by characterizing the way in which designers iteratively search for a design solution, making revisions to the problem specification. This paper presents the computational model of co-evolutionary design and then describes a protocol study of human designers looking for evidence of co-evolution of problem specifications and design solutions. The study shows that co-evolutionary design is a good cognitive model of design and highlights the similarities and differences between the computational model and the cognitive model. The results show that the two kinds of co-evolutionary design complement each other, having strengths in different aspects of the design process. Electronic Publication     

Résumés du congrès annuel 2007 de la SCCCSC.

Presents a collection of abstracts from the 2007 Canadian Society for Brain, Behaviour and Cognitive Science (CSBBCS) Annual Meeting. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bayesian inference in disputed authorship: A case study of cognitive errors and a new system for decision support

Bayesian inference provides a formal framework for assessing the odds of hypotheses in light of evidence. This makes Bayesian inference applicable to a wide range of diagnostic challenges in the field of chance discovery, including the problem of disputed authorship that arises in electronic commerce, counter-terrorism and other forensic applications. For example, when two documents are so similar that one is likely to be a hoax written from the other, the question is: Which document is most likely the source and which document is most likely the hoax? Here I review a Bayesian study of disputed authorship performed by a biblical scholar, and I show that the scholar makes critical errors with respect to several issues, namely: Causal Basis, Likelihood Judgment and Conditional Dependency. The scholar’s errors are important because they have a large effect on his conclusions and because similar errors often occur when people, both experts and novices, are faced with the challenges of Bayesian inference. As a practical solution, I introduce a graphical system designed to help prevent the observed errors. I discuss how this decision support system applies more generally to any problem of Bayesian inference, and how it differs from the graphical models of Bayesian Networks.