Traits and states: Integrating personality and affect into a model of criminal decision making

We propose and test a model of criminal decision making that integrates the individual differences perspective with research and theorizing on proximal factors. The individual differences perspective is operationalized using the recent HEXACO personality structure. This structure incorporates the main personality traits, but it carries the advantage of also incorporating Self-Control within its personality sphere, and an additional trait termed Honesty-Humility. Furthermore, the model offers a new perspective on proximal predictors, "states," of criminal decisions by adding affect (i.e., feelings) to the rational choice-crime equation. The proposed model is tested using scenario data from a representative sample of the Dutch population in terms of gender, age, education level, and province (N = 495). As predicted by the model, personality was both directly and indirectly related to criminal decision making. Specifically, the traits Emotionality, Self-Control, and Honesty-Humility were mediated by both affect and rational choice variables. Conscientiousness operated only indirectly on criminal decision making via rational choice. Together, the findings support a trait-state model of criminal decision making. © 2012 American Society of Criminology

The co-development of friends’ delinquency with adolescents’ delinquency and short-term mindsets:The moderating role of co-offending

The companions in crime hypothesis suggests that co-offending moderates the link between peer delinquency and adolescent delinquency. However, this hypothesis has rarely been investigated longitudinally. Hence, this study investigated the co-development of friends’ delinquency and adolescents’ delinquency, as well as the co-development of friends’ delinquency and short-term mindsets (impulsivity and lack of school future orientation). Whether this co-development is stronger when adolescents engage in co-offending was also investigated. Three data waves with two year lags from an ethnically-diverse adolescent sample (at wave 1: N = 1365; 48.6% female; M(age) = 13.67; age range = 12.33–15.09 years) in Switzerland were used. The results from parallel process latent growth modeling showed that the co-development between friends’ delinquency and adolescents’ delinquency was stronger when adolescents engaged in co-offending. Thus co-offending likely provides direct access to a setting in which adolescents continue to model the delinquency they learned with their peers

Virtual reality as a research method in criminology

Education and Child Studie

Sanctions, short‐term mind-sets, and delinquency: Reverse causality in a sample of high school youth

Education and Child Studie

Looking back from the future: perspective taking in virtual reality increases future self-continuity

Education and Child Studie

Stimulating a future-oriented mindset and goal attainment through a smartphone-based intervention: study protocol for a randomized controlled trial

Background: Short-term mindsets interfere with the consideration of future consequences and therefore predict negative behaviors. We developed a smartphone-based intervention aiming to increase a future-oriented mindset and personal goal attainment by strengthening future self-identification and stimulating episodic future thinking. The aims of the study are 1) to examine users' experiences with the application and their treatment adherence, 2) to examine the effectiveness of the intervention, and 3) to explore which intervention modules generate the strongest changes in key outcomes. Methods: First-year university students (N = 166) will be randomly assigned to two conditions: 1) the smartphone-based intervention, or 2) a goal-setting control group. The intervention consists of three week-long modules. Data will be collected at the start of the intervention, at weekly intervals during the intervention, immediately after the intervention, and at 3-month follow-up (and at parallel time points for the control group). We will assess users' experiences, application usage data, primary intervention outcomes (e.g., self-defeating behavior, future orientation, future self-identification), and secondary intervention outcomes (e.g., psychosocial wellbeing, self-efficacy). Discussion: The study will provide information about users' experiences with the application, the intervention's general effectiveness, and which intervention modules show most promise. This information will be used to further develop the application and optimize this novel intervention. Trial registration: The trial is registered in the Netherlands Trial Register (number: NL9671) on 16 August 2021.Education and Child StudiesDevelopment Psychopathology in context: schoo

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p

Cardiovascular and renal multimorbidity increase risk of atrial fibrillation in the PREVEND cohort

Objective: Atrial fibrillation (AF) is a condition that occurs in the presence of comorbidities. With the accumulation of comorbidities (multimorbidity), some combinations may more often occur together than others. Information on the impact of clustering of these on incident AF is sparse. We aimed to investigate clustering of cardiovascular and renal comorbidities and study the association between comorbidity clusters and incident AF.Methods: We used the community-based Prevention of Renal and Vascular ENd-stage Disease (PREVEND) cohort in which 8592 individuals participated. Latent class analysis was performed to assess clustering of 10 cardiovascular and renal comorbidities.Results: We excluded individuals with prior AF or missing ECG data, leaving 8265 individuals for analysis (mean age 48.9±12.6 years, 50.2% women). During 9.2±2.1 years of follow-up, 251 individuals (3.0%) developed AF. A model with three clusters was the optimal model, with one cluster being young (44.5±10.8 years) and healthy, carrying a low (1.0%) risk of incident AF; one cluster being older (63.0±8.4 years) and multimorbid, carrying a high (16.2%) risk of incident AF and a third middle-aged (57.0±11.3 years), obese and hypertensive cluster carrying an intermediate risk (5.9%) of incident AF. While the prevalence of the comorbidities differed between classes, no clear combination(s) of comorbidities was observed within the classes.Conclusions: We identified three clusters of comorbidities in individuals in the community-based PREVEND cohort. The three clusters contained different amount of comorbidities carrying different risks of incident AF. However, there were no differences between the clusters regarding specific combination(s) of comorbidities.</p