The relevance and impact of political scientists' professional activities outside of universities has become the focus of public attention, partly due to growing expectations that research should... Show moreThe relevance and impact of political scientists' professional activities outside of universities has become the focus of public attention, partly due to growing expectations that research should help address society's grand challenges. One type of such activity is policy advising. However, little attention has been devoted to understanding the extent and type of policy advising activities political scientists engage in. This paper addresses this gap by adopting a classification that distinguishes four ideal types of policy advisors representing differing degrees of engagement. We test this classification by calculating a multi-level latent class model to estimate key factors explaining the prevalence of each type based on an original dataset obtained from a survey of political scientists across 39 European countries. Our results challenge the wisdom that political scientists are sitting in an "ivory tower": the vast majority (80%) of political scientists in Europe are active policy advisers, with most of them providing not only expert guidance but also normative assessments. Show less
Meijer, E.; Gebhardt, W.A.; Laar, C. van; Chavannes, N.H.; Putte, B. van den 2022
Identity, or 'who I am', is important for smoking behaviour. Identity constructs (parts of a person's identity) are typically examined as separate entities, but emerging evidence suggests that the... Show moreIdentity, or 'who I am', is important for smoking behaviour. Identity constructs (parts of a person's identity) are typically examined as separate entities, but emerging evidence suggests that the multifaceted nature of identity is relevant in the context of smoking. This cross-sectional study examined how smoking-related self- and group-identity constructs cluster within adult daily smokers (N = 231), whether classes of smokers can be distinguished based on clusters of identity constructs, and which factors explain class membership. Data were collected online in The Netherlands and Belgium, 2017-2018. Latent class and regression tree analyses showed that participants in Class 1 of 'Identified smokers' (estimated population share 54%) reported stronger smoker self- and group-identities, stronger expected identity loss when quitting smoking, and weaker quitter self-identities and non-smoker self- and group-identities (vs. Class 2 of 'Conflicted smokers'). Class membership was explained by the interaction between mental smoking dependence (dominant explanatory variable), consideration of future consequences, age of smoking onset, self-efficacy, and future self thought clarity. Models had good fit. The identity of more dependent smokers is more strongly oriented toward smoking. Smoking is also more strongly embedded in the identity of smokers who started smoking young, are less inclined to think about the future, and have lower self-efficacy. Show less
Meijer, E.; Gebhardt, W.A.; Laar, C. van; Chavannes, N.H.; Putte, B. van den 2022
Identity, or ‘who I am’, is important for smoking behaviour. Identity constructs (parts of a person’s identity) are typically examined as separate entities, but emerging evidence suggests that the... Show moreIdentity, or ‘who I am’, is important for smoking behaviour. Identity constructs (parts of a person’s identity) are typically examined as separate entities, but emerging evidence suggests that the multifaceted nature of identity is relevant in the context of smoking. This cross-sectional study examined how smoking-related self- and group-identity constructs cluster within adult daily smokers (N = 231), whether classes of smokers can be distinguished based on clusters of identity constructs, and which factors explain class membership. Data were collected online in The Netherlands and Belgium, 2017–2018. Latent class and regression tree analyses showed that participants in Class 1 of ‘Identified smokers’ (estimated population share 54%) reported stronger smoker self- and group-identities, stronger expected identity loss when quitting smoking, and weaker quitter self-identities and non-smoker self- and group-identities (vs. Class 2 of ‘Conflicted smokers’). Class membership was explained by the interaction between mental smoking dependence (dominant explanatory variable), consideration of future consequences, age of smoking onset, self-efficacy, and future self thought clarity. Models had good fit. The identity of more dependent smokers is more strongly oriented toward smoking. Smoking is also more strongly embedded in the identity of smokers who started smoking young, are less inclined to think about the future, and have lower self-efficacy. Show less
Populations in war-torn regions are exposed to a wide array of traumatic events that can cause an enormous psychological burden. Individual characteristics influence the likelihood of being exposed... Show morePopulations in war-torn regions are exposed to a wide array of traumatic events that can cause an enormous psychological burden. Individual characteristics influence the likelihood of being exposed to certain events, pointing to systematic interindividual differences in trauma exposure. However, there is a dearth of studies examining potential patterns of trauma exposure in war regions. In this cross-sectional epidemiological study, we applied a person-centered approach to identify patterns in the exposure to conflict-related traumatic events and determine their impact on commonly reported mental health problems in a population-based sample (N = 1000) from the eastern Democratic Republic of Congo. We implemented multi-stage random cluster sampling to randomly select adults from 100 villages. Of 1000 adults (Mage = 43.19 years) included in the study, 50% were female. Results showed high prevalence of PTSD (17.0%), depression (27.8%), anxiety (25.4%) and suicidality (15.1%) following exposure to conflict-related traumatic events since 2002. Latent Class Analysis identified three distinct classes of trauma exposure: Class 1 “low-trauma-exposure” (51.4%, n = 514) was characterized by the lowest probabilities of trauma exposure. Class 2 “non-physical-trauma” (39.1%, n = 391) consisted of individuals with a high probability for exposure to non-physical trauma types only. Class 3 “interpersonal-trauma” (9.5%, n = 95) had the overall highest probability of exposure to traumatic events and was the only class affected by interpersonal-trauma types. Class membership was related to gender, age and place of living. Vulnerability to mental health problems increased from low-trauma-exposure to non-physical-trauma to interpersonal-trauma class. Our findings indicate that the exposure to traumatic events in conflict-affected populations underlies distinct patterns, with interpersonal trauma as a distinguishing marker. Vulnerability to psychopathology varies with trauma patterns, revealing patterns that include both non-physical and interpersonal traumata as most detrimental for mental health. Identification of underlying trauma patterns and their effects may improve mental health care in war-affected populations. Show less
Distance association models constitute a useful tool for the analysis and graphical representation of cross-classified data in which distances between points inversely describe the association... Show moreDistance association models constitute a useful tool for the analysis and graphical representation of cross-classified data in which distances between points inversely describe the association between two categorical variables. When the number of cells is large and the data counts result in sparse tables, the combination of clustering and representation reduces the number of parameters to be estimated and facilitates interpretation. In this article, a latent block distance-association model is proposed to apply block clustering to the outcomes of two categorical variables while the cluster centers are represented in a low dimensional space in terms of a distance-association model. This model is particularly useful for contingency tables in which both the rows and the columns are characterized as profiles of sets of response variables. The parameters are estimated under a Poisson sampling scheme using a generalized EM algorithm. The performance of the model is tested in a Monte Carlo experiment, and an empirical data set is analyzed to illustrate the model. Show less
Veltman, E.M.; Lamers, F.; Comijs, H.C.; Stek, M.L.; Mast, R.C. van der; Rhebergen, D. 2018
This study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable- and person-based level, and to determine their associated behavioral... Show moreThis study was designed to examine whether proactive and reactive aggression are meaningful distinctions at the variable- and person-based level, and to determine their associated behavioral profiles. Data from 587 adolescents (mean age 15.6; 71.6 % male) from clinical samples of four different sites with differing levels of aggression problems were analyzed. A multi-level Latent Class Analysis (LCA) was conducted to identify classes of individuals (person-based) with similar aggression profiles based on factor scores (variable-based) of the Reactive Proactive Questionnaire (RPQ) scored by self-report. Associations were examined between aggression factors and classes, and externalizing and internalizing problem behavior scales by parent report (CBCL) and self-report (YSR). Factor-analyses yielded a three factor solution: 1) proactive aggression, 2) reactive aggression due to internal frustration, and 3) reactive aggression due to external provocation. All three factors showed moderate to high correlations. Four classes were detected that mainly differed quantitatively (no ‘proactive-only’ class present), yet also qualitatively when age was taken into account, with reactive aggression becoming more severe with age in the highest affected class yet diminishing with age in the other classes. Findings were robust across the four samples. Multiple regression analyses showed that ‘reactive aggression due to internal frustration’ was the strongest predictor of YSR and CBCL internalizing problems. However, results showed moderate to high overlap between all three factors. Aggressive behavior can be distinguished psychometrically into three factors in a clinical sample, with some differential associations. However, the clinical relevance of these findings is challenged by the person-based analysis showing proactive and reactive aggression are mainly driven by aggression severity. Show less
Geluk, C.A.M.L.; Domburgh, L. van; Doreleijers, T.A.H.; Jansen, L.M.C.; Bouwmeester, S.; Garre, F.G.; Vermeiren, R. 2014
This thesis focuses on primary school students’ mathematical ability in the Netherlands. Starting with a systematic research synthesis of performance outcomes of different mathematics programs in... Show moreThis thesis focuses on primary school students’ mathematical ability in the Netherlands. Starting with a systematic research synthesis of performance outcomes of different mathematics programs in Chapter 1, the remaining Chapters 2 to 7 report the results of six empirical studies. These studies address the determinants of students’ ability in the domain of arithmetic (addition, subtraction, multiplication, and division). Moreover, they can be said to cross the border between the academic fields of substantive (educational and cognitive) psychology on the one hand, and psychometrics on the other. Chapters 2 and 3 report on the results of secondary analyses on data collected for CITO’s national mathematics assessment in grade six (12-year-olds) focusing on the strategies students used to solve the problems. Chapters 4 and 5 aimed to more systematically investigate the distinction between mental and written solution strategies for solving division problems. Finally, Chapters 6 and 7 address the role of realistic contexts in mathematics problems, both for students in early grades as well as in grade six. The data analyzed in the empirical studies are complex, requiring advanced psychometric modeling. It is argued that latent variable models incorporating explanatory variables are appropriate to analyze data on solution strategies and performance. Show less
