887 resultados para cognitif-behavioral


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Evidence supporting the benefits of exercise following the diagnosis of breast cancer is overwhelming and compelling. Exercise reduces the severity and number of treatment-related side effects, optimizes quality of life during and following treatment, and may optimize survival. Yet, exercise does not uniformly form part of the standards of care provided to women following a breast cancer diagnosis. This commentary summarizes the evidence in support of exercise as a form of adjuvant treatment and identifies and discusses potential issues preventing the formal integration of exercise into breast cancer care. Proposed within the commentary is a model of breast cancer care that incorporates exercise prescription as a key component but also integrates the need for surveillance and management for common breast cancer treatment-related morbidities, as well as education. While future research evaluating the potential cost savings through implementation of such amodel is required, a committed, collaborative approach by clinicians, allied health professionals, and researchers will be instrumental in bridging the gap between research and practice.

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Physical activity is important following breast cancer. Trials of non-face-to-face interventions are needed to assist in reaching women living outside major metropolitan areas. This study seeks to evaluate the feasibility and effectiveness of a telephone-delivered, mixed aerobic and resistance exercise intervention for non-urban Australian women with breast cancer. A randomized controlled trial comparing an 8-month intervention delivered by exercise physiologists (n = 73) to usual care (n = 70). Sixty-one percent recruitment rate and 96% retention at 12 months; 79% of women in the intervention group received at least 75% of calls; odds (OR, 95% CI) of meeting intervention targets favored the intervention group for resistance training (OR 3.2; 1.2, 8.9) and aerobic (OR 2.1; 0.8, 5.5) activity. Given the limited availability of physical activity programs for non-urban women with breast cancer, results provide strong support for feasibility and modest support for the efficacy of telephone-delivered interventions.

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Objective: Parental illness (PI) may have adverse impacts on youth and family functioning. Research in this area has suffered from the absence of a guiding comprehensive framework. This study tested a conceptual model of the effects of PI on youth and family functioning derived from the Family Ecology Framework (FEF; Pedersen & Revenson, 2005). Method. A total of 85 parents with multiple sclerosis and 127 youth completed questionnaires at Time 1 and 12 months later at Time 2. Results. Structural equation modeling results supported the FEF with regards to physical-illness disability. Specifically, the proposed mediators (role redistribution, stress, and stigma) were implicated in the processes that link parental disability to several domains of youth adjustment. The results suggest that the effects of parental depression (PD) are not mediated through these processes; rather, PD directly affects family functioning, which in turn mediates the effects onto youth adjustment. Family functioning further mediated between PD and youth well-being and behavioral-social difficulties. Conclusions. Although results support the effects of parental-illness disability on youth and family functioning via the proposed mediational mechanisms, the additive effects of PD on youth physical and mental health occur through direct and indirect (via family functioning) pathways, respectively.

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We explore theoretically and empirically whether corruption is contagious and whether conditional cooperation matters. We argue that the decision to bribe bureaucrats depends on the frequency of corruption within a society. We provide a behavioral model to explain this conduct: engaging in corruption results in a disutility of guilt. This disutility depends negatively on the number of people engaging in corruption. The empirical section presents evidence using two international panel data data sets, one at the micro and one at the macro level. Results indicate that corruption is influenced by the perceived activities of peers. Moreover, macro level data indicates that past levels of corruption impact current corruption levels.

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Purpose: Parenting style and early feeding practices have been linked to child intake, eating behaviour and weight status. The purpose of this study was to examine associations between general maternal parenting behaviours and feeding beliefs in Australian mothers of 11-17 month-old children. Methods: This cross-sectional analysis included 223 first-time mothers and their children (49% male, mean age 14 [sd 1] months) enrolled in the control group of the NOURISH trial. Mothers self-reported their feeding beliefs and parenting behaviours (overprotection, irritability, warmth, autonomy-encouraging) using modified questions from the Infant Feeding Questionnaire (Baughcum, 2001) and the Longitudinal Study of Australian Children. Multiple regression analyses were conducted, using feeding beliefs (four factors) as dependent and parenting behaviours as independent variables while adjusting for child gender, age, weight-for-age z-score and maternal age, education level, feeding mode (breast vs. non-breast), and perception of own pre-pregnancy and child weight status. Results/Findings: Two of four parenting behaviours were significantly associated with feeding beliefs. Maternal warmth was inversely associated with concerns that the child would become underweight (β=-0.156, p=0.022) and positively associated with mothers’ awareness of child’s hunger/satiety cues (β=0.303, p<0.001). Mothers’ overprotection was positively associated with concerns that the child would become underweight (β=0.213, p=0.001); become overweight (β=0.174, p=0.005); and mother’s responsive feeding (β=0.135, p=0.057). Weight-for-age z-score, mothers’ perception of their child and own weight status, education, feeding mode, and child’s age were significant covariates. Conclusions: Feeding occurs within the broader parenting context. Improving early feeding beliefs and practices may require addressing mother’s approaches to parenting, especially warmth and overprotection.

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Students who experience high levels of anger both in and out of school are at risk of exhibiting multiple negative developmental outcomes including poor school performance, peer problems, behavioral difficulties, and concurrent emotional distress. Given this developmental trajectory, it is important for mental health professionals working within school settings to accurately identify those students manifesting anger-related problems at an early age. This chapter provides an overview of instruments designed to assess levels of anger and associated cognitive and behavioral manifestations in children and youth. Among those instruments highlighted is the Multidimensional School Anger Inventory (MSAI)specifically designed to measure anger, hostility, and aggressive behavioral expression in school settings. The role of anger assessment in developing appropriate early intervention and anger management treatment plans is also discussed.

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Using the Global Financial Crisis as a natural experiment, we investigate how a major macro-economic crisis affects nascent (i.e., pre-operational) ventures. We hypothesize adverse effects on behaviors, behavioral plans, and expectations for the future, and that these effects would be more pronounced in ventures that are more innovative and/or more relying on loan funding. Overall, we find very limited support for our hypotheses. Our conclusion is that the main reason for the surprising absence of detrimental effects is that a large majority of nascent ventures are mostly affected by a relatively narrow, immediate task environment rather than directly by the fluctuations of the macro-economy.

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1. Overview of hotspot identification (HSID)methods 2. Challenges with HSID 3. Bringing crash severity into the ‘mix’ 4. Case Study: Truck Involved Crashes in Arizona 5. Conclusions • Heavy duty trucks have different performance envelopes than passenger cars and have more difficulty weaving, accelerating, and braking • Passenger vehicles have extremely limited sight distance around trucks • Lane and shoulder widths affect truck crash risk more than passenger cars • Using PDOEs to model truck crashes results in a different set of locations to examine for possible engineering and behavioral problems • PDOE models point to higher societal cost locations, whereas frequency models point to higher crash frequency locations • PDOE models are less sensitive to unreported crashes • PDOE models are a great complement to existing practice

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Flow-oriented process modeling languages have a long tradition in the area of Business Process Management and are widely used for capturing activities with their behavioral and data dependencies. Individual events were introduced for triggering process instantiation and activities. However, real-world business cases drive the need for also covering complex event patterns as they are known in the field of Complex Event Processing. Therefore, this paper puts forward a catalog of requirements for handling complex events in process models, which can be used as reference framework for assessing process definition languages and systems. An assessment of BPEL and BPMN is provided.

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Driver response (reaction) time (tr) of the second queuing vehicle is generally longer than other vehicles at signalized intersections. Though this phenomenon was revealed in 1972, the above factor is still ignored in conventional departure models. This paper highlights the need for quantitative measurements and analysis of queuing vehicle performance in spontaneous discharge pattern because it can improve microsimulation. Video recording from major cities in Australia plus twenty two sets of vehicle trajectories extracted from the Next Generation Simulation (NGSIM) Peachtree Street Dataset have been analyzed to better understand queuing vehicle performance in the discharge process. Findings from this research will alleviate driver response time and also can be used for the calibration of the microscopic traffic simulation model.

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This study describes the treatment of obese individuals who rated high on emotional eating using four case studies that involved 22 sessions of either cognitive behavioral therapy (CBT) or dialectical behavioral therapy (DBT). Outcomes measures relating to weight, body mass index, emotional eating, depression, anxiety, and stress were all assessed with each participant prior to each baseline (three weekly sessions), during treatment and posttherapy. At the 8-week follow-up, the two cases that had received DBT had lost 10.1% and 7.6% of their initial body weight, whereas the two cases that had received CBT had lost 0.7% and 0.6% of their initial body weight. The two DBT cases also exhibited reductions in emotional distress, frequency of emotional eating or quantity of food eating in response to emotions, whereas the two CBT cases showed no overall reductions in these areas. Important processes from all four cases are described as are the implications to clinicians for developing more effective interventions for obese clients who engage in emotional eating.

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This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

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This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.

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An extended theory of planned behavior (TPB) was used to predict young people’s intentions to donate money to charities in the future. Students (N = 210; 18-24 years) completed a questionnaire assessing their attitude, subjective norm, perceived behavioral control [PBC], moral obligation, past behavior and intentions toward donating money. Regression analyses revealed the extended TPB explained 61% of the variance in intentions to donate money. Attitude, PBC, moral norm, and past behavior predicted intentions, representing future targets for charitable giving interventions.

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While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood.The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking is not found to be significant. Defining personality types from aggression and risk-taking behavior, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business