850 resultados para Regression (Psychology)
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Purpose: Progression to the castration-resistant state is the incurable and lethal end stage of prostate cancer, and there is strong evidence that androgen receptor (AR) still plays a central role in this process. We hypothesize that knocking down AR will have a major effect on inhibiting growth of castration-resistant tumors. Experimental Design: Castration-resistant C4-2 human prostate cancer cells stably expressing a tetracycline-inducible AR-targeted short hairpin RNA (shRNA) were generated to directly test the effects of AR knockdown in C4-2 human prostate cancer cells and tumors. Results:In vitro expression of AR shRNA resulted in decreased levels of AR mRNA and protein, decreased expression of prostate-specific antigen (PSA), reduced activation of the PSA-luciferase reporter, and growth inhibition of C4-2 cells. Gene microarray analyses revealed that AR knockdown under hormone-deprived conditions resulted in activation of genes involved in apoptosis, cell cycle regulation, protein synthesis, and tumorigenesis. To ensure that tumors were truly castration-resistant in vivo, inducible AR shRNA expressing C4-2 tumors were grown in castrated mice to an average volume of 450 mm3. In all of the animals, serum PSA decreased, and in 50% of them, there was complete tumor regression and disappearance of serum PSA. Conclusions: Whereas castration is ineffective in castration-resistant prostate tumors, knockdown of AR can decrease serum PSA, inhibit tumor growth, and frequently cause tumor regression. This study is the first direct evidence that knockdown of AR is a viable therapeutic strategy for treatment of prostate tumors that have already progressed to the castration-resistant state.
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Focuses on a study which introduced an iterative modeling method that combines properties of ordinary least squares (OLS) with hierarchical tree-based regression (HTBR) in transportation engineering. Information on OLS and HTBR; Comparison and contrasts of OLS and HTBR; Conclusions.
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Red light cameras (RLCs) have been used in a number of US cities to yield a demonstrable reduction in red light violations; however, evaluating their impact on safety (crashes) has been relatively more difficult. Accurately estimating the safety impacts of RLCs is challenging for several reasons. First, many safety related factors are uncontrolled and/or confounded during the periods of observation. Second, “spillover” effects caused by drivers reacting to non-RLC equipped intersections and approaches can make the selection of comparison sites difficult. Third, sites selected for RLC installation may not be selected randomly, and as a result may suffer from the regression to the mean bias. Finally, crash severity and resulting costs need to be considered in order to fully understand the safety impacts of RLCs. Recognizing these challenges, a study was conducted to estimate the safety impacts of RLCs on traffic crashes at signalized intersections in the cities of Phoenix and Scottsdale, Arizona. Twenty-four RLC equipped intersections in both cities are examined in detail and conclusions are drawn. Four different evaluation methodologies were employed to cope with the technical challenges described in this paper and to assess the sensitivity of results based on analytical assumptions. The evaluation results indicated that both Phoenix and Scottsdale are operating cost-effective installations of RLCs: however, the variability in RLC effectiveness within jurisdictions is larger in Phoenix. Consistent with findings in other regions, angle and left-turn crashes are reduced in general, while rear-end crashes tend to increase as a result of RLCs.
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It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.
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Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.
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Now in its second edition, this book describes tools that are commonly used in transportation data analysis. The first part of the text provides statistical fundamentals while the second part presents continuous dependent variable models. With a focus on count and discrete dependent variable models, the third part features new chapters on mixed logit models, logistic regression, and ordered probability models. The last section provides additional coverage of Bayesian statistical modeling, including Bayesian inference and Markov chain Monte Carlo methods. Data sets are available online to use with the modeling techniques discussed.
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Background: The C allele of a common polymorphism of the serotonin 2A receptor (HTR2A) gene, T102C, results in reduced synthesis of 5-HT2A receptors and has been associated with current smoking status in adults. The -1438A/G polymorphism, located in the regulatory region of this gene, is in linkage disequilibrium with T102C, and the A allele is associated with increased promoter activity and with smoking in adult males. We investigated the contributions of the HTR2A gene, chronic psychological stress, and impulsivity to the prediction of cigarette smoking status and dependence in young adults. Methods: T102C and -1438A/G genotyping was conducted on 132 healthy Caucasian young adults (47 smokers) who completed self-report measures of chronic stress, depressive symptoms, impulsive personality and cigarette use. Results: A logistic regression analysis of current cigarette smoker user status, after adjusting for gender, depressive symptom severity and chronic stress, indicated that the T102C TT genotype relative to the CC genotype (OR = 7.53), and lower punishment sensitivity (OR = 0.91) were each significant predictive risk factors. However, for number of cigarettes smoked, only lower punishment sensitivity was a significant predictor (OR = 0.81). Conclusions: These data indicate the importance of the T102C polymorphism to tobacco use but not number of cigarettes smoked for Caucasian young adults. Future studies should examine whether this is explained by effects of nicotine on the serotonin system. Lower punishment sensitivity increased risk of both smoking and of greater consumption, perhaps via a reduced sensitivity to cigarette health warnings and negative physiological effects.
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This paper addresses reflective practice in research and practice and takes the issue of consciousness of social class in vocational psychology as a working example. It is argued that the discipline’s appreciation of social class can be advanced through application of the qualitative research method autoethnography. Excerpts from an autoethnographic study are used to explore the method’s potential. This reflexive research method is presented as a potential vehicle to improve vocational psychologists’ own class consciousness, and to concomitantly enhance their capacity to grasp social class within their own spheres of research and practice. It is recommended that autoethnography be used for research, training, and professional development for vocational psychologists.
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Background: Young motorists engaging in anti-social and often dangerous driving manoeuvres (which is often referred to as “hooning” within Australia) is an increasing road safety problem. While anecdotal evidence suggests that such behaviour is positively linked with crash involvement, researchers have yet to examine whether younger drivers who deliberately break road rules and drive in an erratic manner (usually with peers) are in fact over represented in crash statistics. This paper outlines research that aimed to identify the characteristics of individuals most likely to engaging in hooning behaviours, as well as examine the frequency of such driving behaviours and if such activity is linked with self-reported crash involvement.---------- Methods: A total of 717 young drivers in Queensland voluntarily completed a questionnaire to investigate their driving behaviour and crash history.---------- Results: Quantitative analysis of the data revealed that almost half the sample reported engaging in some form of “hooning” behaviour at least once in their lifetime, although only 4% indicated heavy participation in the behaviour e.g., >50 times. Street racing was the most common activity reported by participants followed by “drifting” and then “burnouts”. Logistic regression analysis indicated that being younger and a male was predictive of reporting such anti-social driving behaviours, and importantly, a trend was identified between such behaviour and self-reported crash involvement.---------- Conclusions: This research provides preliminary evidence that younger male drivers are more likely to engage in dangerous driving behaviours, which ultimately may prove to increase their overall risk of becoming involved in a crash. This paper will further outline the study findings in regards to current enforcement efforts to deter such driving activity as well as provide direction for future research efforts in this area.---------- Research highlights: ► The self-reported driving behaviours of 717 younger Queensland drivers were examined to investigate the relationship between deliberately breaking road rules and self-reported crash involvement. ► Younger male drivers were most likely to engage in such aberrant driving behaviours and a trend was identified between such behaviour and self-reported crash involvement.
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Drink driving causes more fatal crashes than any other single factor on Australian roads, with a third of crashes having alcohol as a contributing factor. In recent years there has been a plateau in the numbers of drink drivers apprehended by RBT, and around 12% of the general population in self report surveys admit to drinking and driving. There is limited information about the first offender group, particularly the subgroup of these offenders who admit to prior drink driving, the offence therefore being the “first time caught”. This research focuses on the differences between those who report drink driving prior to apprehension for the offence and those who don’t. Methods: 201 first time drink driving offenders were interviewed at the time of their court appearance. Information was collected on socio-demographic variables, driving behaviour, method of apprehension, offence information, alcohol use and self reported previous drink driving. Results: 78% of respondents reported that they had driven over the legal alcohol limit in the 6 months prior to the offence. Analyses revealed that those offenders who had driven over the limit previously without being caught were more likely to be younger and have an issue with risky drinking. When all variables were taken into account in a multivariate model using logistic regression, only risky drinking emerged as significantly related to past drink driving. High risk drinkers were 4.8 times more likely to report having driven over the limit without being apprehended in the previous 6 months. Conclusion: The majority of first offenders are those who are “first time apprehended” rather than “first time drink drivers”. Having an understanding of the differences between these groups may alter the focus of educational or rehabilitation countermeasures. This research is part of a larger project aiming to target first time apprehended offenders for tailored intervention.
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Objective: To understand the levels of substance abuse and dependence among impaired drivers by comparing the differences in patients in substance abuse treatment programs with and without a past-year DUI arrest based on their primary problem substance at admission (alcohol, cocaine, cannabis, or methamphetamine). Method: Records on 345,067 admissions to Texas treatment programs between 2005 and 2008 have been analyzed for differences in demographic characteristics, levels of severity, and mental health problems at admission, treatment completion, and 90-day follow-up. Methods will include t-tests,??, and multivariate logistic regression. Results: The analysis found that DUI arrestees with a primary problem with alcohol were less impaired than non-DUI alcohol patients, had fewer mental health problems, and were more likely to complete treatment. DUI arrestees with a primary problem with cannabis were more impaired than non-DUI cannabis patients and there was no difference in treatment completion. DUI arrestees with a primary problem with cocaine were less impaired and more likely to complete treatment than other cocaine patients, and there was little difference in levels of mental health problems. DUI arrestees with a primary problem with methamphetamine were more similar to methamphetamine non-arrestees, with no difference in mental health problems and treatment completion. Conclusions: This study provides evidence of the extent of abuse and dependence among DUI arrestees and their need for treatment for their alcohol and drug problems in order to decrease recidivism. Treatment patients with past-year DUI arrests had good treatment outcomes but closer supervision during 90 day follow-up after treatment can lead to even better long-term outcomes, including reduced recidivism. Information will be provided on the latest treatment methodologies, including medication assisted therapies and screening and brief interventions, and ways impaired driving programs and substance dependence programs can be integrated to benefit the driver and society.
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Background: A State-based industry in Australia is in the process of developing a programme to prevent AOD impairment in the workplace. The objective of this study was to determine whether the Theory of Planned Behaviour can help explain the mechanisms by which behaviour change occurs with regard to AOD impairment in the workplace. ---------- Method: A survey of 1165 employees of a State-based industry in Australia was conducted, and a response rate of 98% was achieved. The survey included questions relevant to the Theory of Planned Behaviour: behaviour; behavioural intentions; attitude; perceptions of social pressure; and perceived behavioural control with regard to workplace AOD impairment. ---------- Findings: Less than 3% of participants reported coming to work impaired by AODs. Fewer than 2% of participants reported that they intended to come to work impaired by AODs. The majority of participants (over 80%) reported unfavourable attitudes toward AOD impairment at work. Logistic regression analyses suggest that, consistent with the theory of planned behaviour: attitudes, perceptions of social pressure, and perceived behavioural control with regard to workplace AOD impairment, all predict behavioural intentions (P < .001); and behavioural intentions predict (self-reported) behaviour regarding workplace AOD impairment (P < .001). ---------- Conclusions: The Theory of Planned Behaviour appears to assist with understanding the mechanisms by which behaviour change occurs with regard to AOD impairment in the workplace. An occupational AOD programme which targets those mechanisms for change may improve its impact in preventing workplace AOD impairment.
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Background: Up to fifty percent of alcohol dependent individuals have alexithymia, a personality trait characterised by difficulties identifying and describing feelings, a lack of imagination and an externalised cognitive style. Although studies have examined alexithymia in relation to alcohol dependence, no research exists on mechanisms underlying this relationship. The present study examined the mediational effect of alcohol expectancies on alexithymia and alcohol dependence.----- ----- Methods: 230 outpatients completed the Toronto Alexithymia Scale (TAS-20), the Drinking Expectancy Questionnaire (DEQ) and the Alcohol Use Disorder Identification Test (AUDIT). Results: Regression analysis showed that alexithymia and alcohol dependence was, in two of three cases, partially mediated through alcohol expectancy.----- ----- Conclusions: Alcohol expectancies of assertion and affective change show promise as mediators of alcohol dependence in individuals with alexithymia.
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In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.
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Up to fifty per cent of individuals with Alcohol use disorders (AUD) also have alexithymia a personality construct hypothesized to be related to attachment difficulties. The relationship between alexithymia, craving, anxious attachment and alcohol-dependence severity was examined in 254 patients participating in a Cognitive-Behavioral Therapy (CBT) program for alcohol-dependence. Participants completed the Toronto Alexithymia Scale (TAS-20), the Obsessive Compulsive Drinking Scale (OCDS), the Revised Adult Attachment Anxiety Subscale (RAAS-Anxiety) and the Alcohol Use Disorder Identification Test (AUDIT). MANOVA indicated that individuals with alexithymia reported significantly higher levels of total OCDS, obsessive thoughts about alcohol, and compulsive drinking urges and behavior, compared to the non-alexithymic group. Regression analyses found that anxious attachment partially mediated the relationship between alexithymia and craving. Anxious attachment may be a potential treatment target to reduce alcohol consumption in those with alcohol-dependence and alexithymia. Research Highlights ► There were significant relationships of alexithymia, craving and anxious attachment. ► Alexithymic alcoholics reported higher levels of craving and alcoholism severity. ► Anxious attachment partially mediated the relationship of alexithymia and craving.