6 resultados para Risk models

em Brock University, Canada


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The mediating roles of stress, social support, and health risk behaviours in the relationships between dispositional forgiveness and mental and physical health were examined. Participants were 748 undergraduate students (554 women, 194 men) entering their first year of studies at Brock University. Participants, ranging in age from 17 to 25 years, completed the Brock University First Year Health Study and were provided monetary compensation. Dispositional forgiveness, stress, social support, health risk behaviours, mental health, and physical health were measured using self-report methods. The data were analyzed separately for women and men because there were significant mean differences on many of the study'S variables. Analyses revealed that the mediated relationships between dispositional forgiveness and health were generally stronger for women than men. Stress was the most robust mediator of the forgiveness-health relation for both women and men. The only health risk behaviour that mediated the forgivenesshealth relation was physical fitness and this result was found for women only. Social support mediated several of the relationships between forgiveness and health but not others. Results were discussed with reference to the literature on forgiveness and health. Several directions for future research were offered, such as conducting longitudinal research designs to assess the direction of causality better, investigating moderator variables of the forgiveness-health relation, and building models, which incorporate multiple mediators using structural equation modelling techniques.

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Multiple measures have been devised by clinicians and theorists from many different backgrounds for the purpose of assessing the influence of the frontal lobes on behaviour. Some utilize self-report measures to investigate behavioural characteristics such as risktaking, sensation seeking, impulsivity, and sensitivity to reward and punishment in an attempt to understand complex human decision making. Others rely more on neuroimaging and electrophysiological investigation involving experimental tasks thought to demonstrate executive functions in action, while other researchers prefer to study clinical populations with selective damage. Neuropsychological models of frontal lobe functioning have led to a greater appreciation of the dissociations among various aspects of prefrontal cortex function. This thesis involves (1) an examination of various psychometric and experimental indices of executive functions for coherence as one would predict on the basis of highly developed neurophysiological models of prefrontal function, particularly those aspects of executive function that involve predominantly cognitive abilities versus processes characterized by affect regulation; and (2) investigation of the relations between risk-taking, attentional abilties and their associated characteristics using a neurophysiological model of prefrontal functions addressed in (1). Late adolescence is a stage in which the prefrontal cortices undergo intensive structural and functional maturational changes; this period also involves increases in levels of risky and sensation driven behaviours, as well as a hypersensitivity to reward and a reduction in inhibition. Consequently, late adolescence spears to represent an ideal developmental period in which to examine these decision-making behaviours due to the maximum variability of behavioural characteristics of interest. Participants were 45 male undergraduate 18- to 19-year olds, who completed a battery of measures that included self-report, experimental and behavioural measures designed to assess particular aspects of prefrontal and executive functioning. As predicted, factor analysis supported the grouping of executive process by type (either primarily cognitive or affective), conforming to the orbitofrontal versus dorsolateral typology; risk-taking and associated characteristics were associated more with the orbitofrontal than the dorsolateral factor, whereas attentional and planning abilities tended to correlate more strongly with the dorsolateral factor. Results are discussed in light of future assessment, investigation and understanding of complex human decision-making and executive functions. Implications, applications and suggestions for future research are also proposed.

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BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.

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People with intellectual disability who sexually offend commonly live in community-based settings since the closing of all institutions across the province of Ontario. Nine (n=9) front line staff who provide support to these individuals in three different settings (treatment setting, transitional setting, residential setting) were interviewed. Participants responded to 47 questions to explore how sex offenders with intellectual disability can be supported in the community to prevent re-offenses. Questions encompassed variables that included staff attitudes, various factors impacting support, structural components of the setting, quality of life and the good life, staff training, staff perspectives on treatment, and understanding of risk management. Three overlapping models that have been supported in the literature were used collectively for the basis of this research: The Good Lives Model (Ward & Gannon, 2006; Ward et al., 2007), the quality of life model (Felce & Perry, 1995), and variables associated with risk management. Results of this research showed how this population is being supported in the community with an emphasis on the following elements: positive and objective staff attitude, teamwork, clear rules and protocols, ongoing supervision, consistency, highly trained staff, and environments that promote quality of life. New concepts arose which suggested that all settings display an unequal balance of upholding human rights and managing risks when supporting this high-risk population. This highlights the need for comprehensive assessments in order to match the offender to the proper setting and supports, using an integration of a Risk, Need, Responsivity model and the Good Lives model for offender rehabilitation and to reduce the likelihood of re-offenses.

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The study aim was to investigate the relationship between factors related to personal cancer history and lung cancer risk as well as assess their predictive utility. Characteristics of interest included the number, anatomical site(s), and age of onset of previous cancer(s). Data from the Prostate, Lung, Colorectal and Ovarian Screening (PLCO) Cancer Screening Trial (N = 154,901) and National Lung Screening Trial (N = 53,452) were analysed. Logistic regression models were used to assess the relationships between each variable of interest and 6-year lung cancer risk. Predictive utility was assessed through changes in area-under-the-curve (AUC) after substitution into the PLCOall2014 lung cancer risk prediction model. Previous lung, uterine and oral cancers were strongly and significantly associated with elevated 6-year lung cancer risk after controlling for confounders. None of these refined measures of personal cancer history offered more predictive utility than the simple (yes/no) measure already included in the PLCOall2014 model.

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Despite being considered a disease of smokers, approximately 10-15% of lung cancer cases occur in never-smokers. Lung cancer risk prediction models have demonstrated excellent ability to discriminate cases from non-cases, and have been shown to be more efficient at selecting individuals for future screening than current criteria. Existing models have primarily been developed in populations of smokers, thus there was a need to develop an accurate model in never-smokers. This study focused on developing and validating a model using never-smokers from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Cox regression analysis, with six-year follow-up, was used for model building. Predictors included: age, body mass index, education level, personal history of cancer, family history of lung cancer, previous chest X-ray, and secondhand smoke exposure. This model achieved fair discrimination (optimism corrected c-statistic = 0.6645) and good calibration. This represents an improvement on existing neversmoker models, but is not suitable for individual-level risk prediction.