Investigating the Association Between Computer-Mediated Communication (CMC) and the Health of Canadian Young People: A Mixed Methods Study

Canadian young people are increasingly more connected through technological devices. This computer-mediated communication (CMC) can result in heightened connection and social support but can also lead to inadequate personal and physical connections. As technology evolves, its influence on health and well-being is important to investigate, especially among youth. This study aims to investigate the potential influences of computer-mediated communication (CMC) on the health of Canadian youth, using both quantitative and qualitative research approaches. This mixed-methods study utilized data from the 2013-2014 Health Behaviour in School-aged Children survey for Canada (n=30,117) and focus group data involving Ontario youth (7 groups involving 40 youth). In the quantitative component, a random-effects multilevel Poisson regression was employed to identify the effects of CMC on loneliness, stratified to explore interaction with family communication quality. A qualitative, inductive content analysis was applied to the focus group transcripts using a grounded theory inspired methodology. Through open line-by-line coding followed by axial coding, main categories and themes were identified. The quality of family communication modified the association between CMC use and loneliness. Among youth experiencing the highest quartile of family communication, daily use of verbal and social media CMC was significantly associated with reports of loneliness. The qualitative analysis revealed two overarching concepts that: (1) the health impacts of CMC are multidimensional and (2) there exists a duality of both positive and negative influences of CMC on health. Four themes were identified within this framework: (1) physical activity, (2) mental and emotional disturbance, (3) mindfulness, and (4) relationships. Overall, there is a high proportion of loneliness among Canadian youth, but this is not uniform for all. The associations between CMC and health are influenced by external and contextual factors, including family communication quality. Further, the technologically rich world in which young people live has a diverse impact on their health. For youth, their relationships with others and the context of CMC use shape overall influences on their health.

Using the interact system model to analyze computer mediated communication during a small group problem-solving task

The Interact System Model (ISM) developed by Fisher and Hawes (1971) for the analysis of face-to-face communication during small-group problem solving activities was used to study online communication. This tool proved to be of value in the analysis, but the conversation patterns reported by Fisher (1980) did not fully appear in the online environment. Participants displayed a habit of "being too polite" and not fully voicing their disagreements with ideas posed by others. Thus progress towards task completion was slow and incomplete.

The differential impact of oxytocin receptor (OXTR) genotypes on the risk of autism spectrum disorder (ASD) and resulting social communication deficits

Background: Autism spectrum disorder (ASD) is multifactorial and is likely the result of complex interactions between multiple environmental and genetic factors. Recently, it has been suggested that each symptom cluster of the disorder, such as poor social communication, may be mediated by different genetic influences. Genes in the oxytocin pathway, which mediates social behaviours in humans, have been studied with single nucleotide polymorphisms (SNPs) in the oxytocin receptor gene (OXTR) being implicated in ASD. This thesis examines the presence of different oxytocin receptor genotypes, and their associations with ASD and resulting social communication deficits. Methods: The relationship between four OXTR variants and ASD was evaluated in 607 ASD simplex (SPX) families. Cases were compared to their unaffected siblings using a conditional logistic approach. Odds ratios and associated 95 percent confidence intervals were obtained. A second sample of 235 individuals with a diagnosis of ASD was examined to evaluate whether these four OXTR variants were associated with social communication scores on the Autism Diagnostic Interview – Revised (ADI-R). Parameter estimates and associated 95 percent confidence intervals were generated using a linear regression approach. Multiple testing issues were addressed using false discovery adjustments. Results: The rs53576 AG genotype was significantly associated with a lower risk of ASD (OR = 0.707, 95% CI: 0.512-0.975). A single genotype (AG) provided by the rs2254298 marker was found to be significantly associated with higher social communication scores (Parameter estimate = 1.833, SE = 0.762, p = 0.0171). This association was also seen in a Caucasian only and mothers as the respondent samples. No association was significant following false discovery rate adjustments. Conclusion: The findings from these studies provide limited support for the role of OXTR SNPs in ASD, especially in social communication skills. The clinical significance of these associations remains unknown, however, it is likely that these associations do not play a role in the severity of symptoms associated with ASD. Rather, they may be important in the appearance of social deficits due to the rs2254298 markers association with enlarged amygdalas.

ADVANCED ISLANDING DETECTION METHODS FOR SINGLE PHASE GRID CONNECTED PV INVERTERS

Due to the growing concerns associated with fossil fuels, emphasis has been placed on clean and sustainable energy generation. This has resulted in the increase in Photovoltaics (PV) units being integrated into the utility system. The integration of PV units has raised some concerns for utility power systems, including the consequences of failing to detect islanding. Numerous methods for islanding detection have been introduced in literature. They can be categorized into local methods and remote methods. The local methods are categorically divided into passive and active methods. Active methods generally have smaller Non-Detection Zone (NDZ) but the injecting disturbances will slightly degrade the power quality and reliability of the power system. Slip Mode Frequency Shift Islanding Detection Method (SMS IDM) is an active method that uses positive feedback for islanding detection. In this method, the phase angle of the converter is controlled to have a sinusoidal function of the deviation of the Point of Common Coupling (PCC) voltage frequency from the nominal grid frequency. This method has a non-detection zone which means it fails to detect islanding for specific local load conditions. If the SMS IDM employs a different function other than the sinusoidal function for drifting the phase angle of the inverter, its non-detection zone could be smaller. In addition, Advanced Slip Mode Frequency Shift Islanding Detection Method (Advanced SMS IDM), which has been introduced in this thesis, eliminates the non-detection zone of the SMS IDM. In this method the parameters of SMS IDM change based on the local load impedance value. Moreover, the stability of the system is investigated by developing the dynamical equations of the system for two operation modes; grid connected and islanded mode. It is mathematically proven that for some loading conditions the nominal frequency is an unstable point and the operation frequency slides to another stable point, while for other loading conditions the nominal frequency is the only stable point of the system upon islanding occurring. Simulation and experimental results show the accuracy of the proposed methods in detection of islanding and verify the validity of the mathematical analysis.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.