902 resultados para Treatment-seeking behavior


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The rationalizability of a choice function on arbitrary domains by means of a transitive relation has been analyzed thoroughly in the literature. Moreover, characterizations of various versions of consistent rationalizability have appeared in recent contributions. However, not much seems to be known when the coherence property of quasi-transitivity or that of P-acyclicity is imposed on a rationalization. The purpose of this paper is to fill this significant gap. We provide characterizations of all forms of rationalizability involving quasi-transitive or P-acyclical rationalizations on arbitrary domains.

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Plus de la moitié des adolescents suicidaires dont une large proportion présente un trouble de personnalité limite (TPL) abandonnent leur traitement. Les conséquences de leur défection sont préoccupantes considérant la récurrence de leurs conduites suicidaires et le fait que cette pathologie augmente le risque d’une évolution défavorable à l’âge adulte. À partir d’une méthode de théorisation ancrée constructiviste, cette étude visait à comprendre les processus associés à l’instabilité du mode de consultation des adolescents avec TPL. Elle a permis de spécifier les vulnérabilités à l’abandon des adolescents avec TPL et celles de leurs parents et mis au jour que l’atténuation des problèmes d’accessibilité, la préparation au traitement, l’adaptation des soins aux particularités du TPL et finalement la prise en compte de la disposition à traiter des soignants constituent des réponses déterminantes pour leur engagement. Les processus de désengagement ont également été spécifiés. Des perceptions négatives à l’égard du traitement, du soignant ou du fait d’être en traitement génèrent une activation émotionnelle. Celle-ci induit ensuite des attitudes contre-productives qui évoluent vers des comportements francs de désengagement. Dans ce contexte, des réponses du dispositif de soins telles une régulation insuffisante de l’engagement, des impairs thérapeutiques et des demandes paradoxales précipitent l’abandon de traitement. Finalement, les processus impliqués dans l’abandon de traitement ont été formalisés dans le Modèle de l’engagement et de l’abandon de traitement des adolescents avec TPL. Celui-ci illustre que des processus distincts caractériseraient les abandons précoces et les abandons tardifs des adolescents avec TPL. L’abandon précoce résulterait de l’échec du dispositif de soins à profiter de l’impulsion de la demande d’aide pour engager l’adolescent et le parent lors de ce premier moment critique de sa trajectoire de soins. En contrepartie, les abandons tardifs traduiraient les défaillances du dispositif de soins à adopter des mesures correctives pour les maintenir en traitement lors d’un deuxième moment critique marqué par leur désengagement. Les taux d’abandon de traitement de ces jeunes pourraient être diminués par un dispositif de soins qui reconnaît les périls inhérents au traitement de cette clientèle, se montre proactif pour résoudre les problèmes de désengagement, intègre des mécanismes de soutien aux soignants et favorise une pratique réflexive.

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Driving while impaired (DWI) is a grave and persistent high-risk behavior. Previous work demonstrated that DWI recidivists had attenuated cortisol reactivity compared to non-DWI drivers. This suggests that cortisol is a neurobiological marker of high-risk driving. The present study tested the hypothesis that this initial finding would extend to first-time DWI (fDWI) offenders compared to non-DWI drivers. Male fDWI offenders (n = 139) and non-DWI drivers (n = 31) were exposed to a stress task, and their salivary cortisol activity (total output and reactivity) was measured. Participants also completed questionnaires on sensation seeking, impulsivity, substance use, and engagement in risky and criminal behaviors. As hypothesized, fDWI offenders, compared to non-DWI drivers, had lower cortisol reactivity; fDWI offenders also showed lower total output. In addition, cortisol activity was the most important predictor of group membership, after accounting for alcohol misuse patterns and consequences and other personality and problem behavior characteristics. The findings indicate that attenuated cortisol activity is an independent factor associated with DWI offending risk at an earlier stage in the DWI trajectory than previously detected.

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Biological systems exhibit rich and complex behavior through the orchestrated interplay of a large array of components. It is hypothesized that separable subsystems with some degree of functional autonomy exist; deciphering their independent behavior and functionality would greatly facilitate understanding the system as a whole. Discovering and analyzing such subsystems are hence pivotal problems in the quest to gain a quantitative understanding of complex biological systems. In this work, using approaches from machine learning, physics and graph theory, methods for the identification and analysis of such subsystems were developed. A novel methodology, based on a recent machine learning algorithm known as non-negative matrix factorization (NMF), was developed to discover such subsystems in a set of large-scale gene expression data. This set of subsystems was then used to predict functional relationships between genes, and this approach was shown to score significantly higher than conventional methods when benchmarking them against existing databases. Moreover, a mathematical treatment was developed to treat simple network subsystems based only on their topology (independent of particular parameter values). Application to a problem of experimental interest demonstrated the need for extentions to the conventional model to fully explain the experimental data. Finally, the notion of a subsystem was evaluated from a topological perspective. A number of different protein networks were examined to analyze their topological properties with respect to separability, seeking to find separable subsystems. These networks were shown to exhibit separability in a nonintuitive fashion, while the separable subsystems were of strong biological significance. It was demonstrated that the separability property found was not due to incomplete or biased data, but is likely to reflect biological structure.

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This thesis theoretically studies the relationship between the informal sector (both in the labor and the housing market) and the city structure.

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Here, we identify the Arabidopsis thaliana ortholog of the mammalian DEAD box helicase, eIF4A-III, the putative anchor protein of exon junction complex (EJC) on mRNA. Arabidopsis eIF4A-III interacts with an ortholog of the core EJC component, ALY/Ref, and colocalizes with other EJC components, such as Mago, Y14, and RNPS1, suggesting a similar function in EJC assembly to animal eIF4A-III. A green fluorescent protein (GFP)-eIF4A-III fusion protein showed localization to several subnuclear domains: to the nucleoplasm during normal growth and to the nucleolus and splicing speckles in response to hypoxia. Treatment with the respiratory inhibitor sodium azide produced an identical response to the hypoxia stress. Treatment with the proteasome inhibitor MG132 led to accumulation of GFP-eIF4A-III mainly in the nucleolus, suggesting that transition of eIF4A-III between subnuclear domains and/or accumulation in nuclear speckles is controlled by proteolysis-labile factors. As revealed by fluorescence recovery after photobleaching analysis, the nucleoplasmic fraction was highly mobile, while the speckles were the least mobile fractions, and the nucleolar fraction had an intermediate mobility. Sequestration of eIF4A-III into nuclear pools with different mobility is likely to reflect the transcriptional and mRNA processing state of the cell.

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There is substantial evidence for the effectiveness of psychological treatments for OCD, and various approaches have been widely recommended. These approaches tend to be characterized by exposure and response prevention (ERP) and also tend to be applied equally to all forms of OCD. Patients/clients (and some therapists) often find ERP to be a difficult treatment, and both dropout and refusal rates are unacceptably high. Based on specific cognitive conceptualizations of different manifestations of OCD, new and refined cognitive treatment methods are now available. The present article describes a specific cognitively based approach to the treatment of compulsive checking.

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Objective: The aims of these studies were (a) to investigate the relationship between attentional bias and eating disorders and (b) examine the impact of psychological treatment on attentional bias. Method: The first study compared performance on a pictorial dot probe of 82 female patients with clinical eating disorders and 44 healthy female controls. The second study compared the performance of 31 patients with eating disorder on the same task before and after receiving 20 weeks of standardized cognitive behavior therapy. Twenty-four patients with eating disorder served as wait-list controls. Results: With the exception of neutral shape stimuli, attentional biases for eating, shape, and weight stimuli were greater in the patient sample than the healthy controls. The second study found that attentional biases significantly reduced after active treatment only. Conclusion: Attentional biases may be an expression of the eating disorder. The question of whether such biases warrant specific intervention requires further investigation. (C) 2008 by Wiley Periodicals, Inc.

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The recommended treatment for obsessive-compulsive disorder (OCD) is cognitive behavior therapy (CBT) incorporating exposure and response prevention (ERP), which is effective for approximately 50% of patients. However, there has been little advance in treatment outcomes since the introduction of ERP in 1979. It has been suggested that some progress can be made in treating contamination obsessions and washing compulsions by addressing feelings of dirtiness and contamination that arise without physical contact with a tangible contaminant. To date, the treatment of these “mental contamination” fears in OCD has not been systematically explored. This paper reports on a case series of 12 participants with OCD who received 10 to 20 sessions of a CBT-based treatment for mental contamination. At the end of treatment, 7 participants no longer met the diagnostic criteria for OCD and mental contamination and these gains were maintained at 6-month follow-up. The clinical implications of these findings are discussed.

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Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically informative. We describe a ‘risk-index’ approach combining genetic, demographic and clinical data and test its ability to predict diagnostic outcome following CBT in anxious children. Method. DNA and clinical data were collected from 384 children with a primary anxiety disorder undergoing CBT. We tested our risk model in five cross-validation training sets. Results. In predicting treatment outcome, six variables had a minimum mean beta value of 0.5: 5HTTLPR, NGF rs6330, gender, primary anxiety severity, comorbid mood disorder and comorbid externalising disorder. A risk index (range 0-8) constructed from these variables had moderate predictive ability (AUC = .62-.69) in this study. Children scoring high on this index (5-8) were approximately three times as likely to retain their primary anxiety disorder at follow-up as compared to those children scoring 2 or less. Conclusion. Significant genetic, demographic and clinical predictors of outcome following CBT for anxiety-disordered children were identified. Combining these predictors within a risk-index could be used to identify which children are less likely to be diagnosis free following CBT alone or thus require longer or enhanced treatment. The ‘risk-index’ approach represents one means of harnessing the translational potential of G×E data.

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Low self-esteem is a common, disabling, and distressing problem that has been shown to be involved in the etiology and maintenance of range of Axis I disorders. Hence, it is a priority to develop effective treatments for low self-esteem. A cognitive-behavioral conceptualization of low self-esteem has been proposed and a cognitive-behavioral treatment (CBT) program described (Fennell, 1997, 1999). As yet there has been no systematic evaluation of this treatment with routine clinical populations. The current case report describes the assessment, formulation, and treatment of a patient with low self-esteem, depression, and anxiety symptoms. At the end of treatment (12 sessions over 6 months), and at 1-year follow-up, the treatment showed large effect sizes on measures of depression, anxiety, and self-esteem. The patient no longer met diagnostic criteria for any psychiatric disorder, and showed reliable and clinically significant change on all measures. As far as we are aware, there are no other published case studies of CBT for low self-esteem that report pre- and posttreatment evaluations, or follow-up data. Hence, this case provides an initial contribution to the evidence base for the efficacy of CBT for low self-esteem. However, further research is needed to confirm the efficacy of CBT for low self-esteem and to compare its efficacy and effectiveness to alternative treatments, including diagnosis-specific CBT protocols.

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Background Anorexia Nervosa (AN) is a highly life-threatening disorder that is extremely difficult to treat. There is evidence that family-based therapies are effective for adolescent AN, but no treatment has been proven to be clearly effective for adult AN. The methodological challenges associated with studying the disorder have resulted in recommendations that new treatments undergo preliminary testing prior to being evaluated in a randomized clinical trial. The aim of this study was to provide preliminary evidence on the effectiveness of a treatment program based on a novel adaptation of Dialectical Behavior Therapy (DBT) for adult Anorexia Nervosa (Radically Open-DBT; RO-DBT) that conceptualizes AN as a disorder of overcontrol. Methods Forty-seven individuals diagnosed with Anorexia Nervosa-restrictive type (AN-R; mean admission body mass index = 14.43) received the adapted DBT inpatient program (mean length of treatment = 21.7 weeks). Results Seventy-two percent completed the treatment program demonstrating substantial increases in body mass index (BMI; mean change in BMI = 3.57) corresponding to a large effect size (d = 1.91). Thirty-five percent of treatment completers were in full remission, and an additional 55% were in partial remission resulting in an overall response rate of 90%. These same individuals demonstrated significant and large improvements in eating-disorder related psychopathology symptoms (d = 1.17), eating disorder-related quality of life (d = 1.03), and reductions in psychological distress (d = 1.34). Conclusions RO-DBT was associated with significant improvements in weight gain, reductions in eating disorder symptoms, decreases in eating-disorder related psychopathology and increases in eating disorder-related quality of life in a severely underweight sample. These findings provide preliminary support for RO-DBT in treating AN-R suggesting the importance of further evaluation examining long-term outcomes using randomized controlled trial methodology.

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This paper presents a novel application of virtual environments to assist in encouraging behavior change in individuals who misuse drugs or alcohol. We describe the user-centered design of a series of scenes to engage users in the identification of triggers and to encourage discussions about relevant coping skills. Results from the initial testing of this application with six service users showed variation in user responses. Results also suggested that the system should encourage group discussion and that it was linked to a small improvement in users’ confidence in understanding and identifying triggers.

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Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

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Classical nova remnants are important scenarios for improving the photoionization modeling. This work describes the pseudo-three-dimensional code RAINY3D, which drives the photoionization code Cloudy as a subroutine. Photoionization simulations of old nova remnants are also presented and discussed. In these simulations we analyze the effect of condensation in the remnant spectra. The condensed mass fraction affects the Balmer lines by a factor of greater than 4 when compared with homogeneous models, and this directly impacts the shell mass determination. The He II 4686/H beta ratio decreases by a factor of 10 in clumpy shells. These lines are also affected by the clump size and density distributions. The behavior of the strongest nebular line observed in nova remnants is also analyzed for heterogeneous shells. The gas diagnoses in novae ejecta are thought to be more accurate during the nebular phase, but we have determined that at this phase the matter distribution can strongly affect the derived shell physical properties and chemical abundances.