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This research aims to develop and validate an instrument for measuring primary student teachers’ professional identity tensions. Based on dissonance theory, we transformed existing vignettes ( Pillen, Den Brok, & Beijaard, 2013 ) into to a quantitative Professional Identity Tensions Scale (PITS) and added tensions regarding teaching in urban contexts. We examined the psychometric quality of the PITS by administering this scale to primary student teachers from teacher education institutions in urban areas across the Netherlands. Two studies were conducted in the process of validating the PITS. First, items were tested among a sample of 211 students to explore whether they measure underlying constructs of professional identity tensions. Second, retained items were administered to a new sample of 271 students. Confirmatory factor analysis demonstrated a similar factor structure. The final instrument includes 34 items rated on a 5-point Likert scale measuring nine different professional identity tensions. Implications for future research and practice are discussed.

Er is geen duidelijk effect van de tijdsduur tussen de eerste toets en de herkansing op studiesucces. De resultaten van de herkansing zijn in grote mate afhankelijk van de leerstrategie van een leerling. Het is wenselijk om leerlingen te helpen bij het aanleren van een goede leerstrategie en planning. Er zijn verschillende methoden om het vergeten van studiestof tegen te gaan gedurende de tijd tot de herkansing.

This study aimed to disentangle the effects of Mild-to-Borderline Intellectual Disability (MBID) and Behavior Disorders (BD)on risk taking in circumstances where peer influence was absent or present. We studied 319 adolescents in four groups: MBID-only, MBID+BD, BD-only, and typically developing controls. The Balloon Analogue Risk-Task (BART), in a solo or peer condition, was used as a proxy of real-life risk-taking. Results show a significant main effect of BART condition. Post-hoc tests indicated higher risk-taking in the peer compared to the solo condition in all groups except BD-only. Moreover, risk taking was increased in adolescents with MBID compared to adolescents without MBID, but only under peer-influence. No main or interaction effects with BD were observed. Model based decomposition of BART performance in underlying processes showed that the MBID related increase in risk-taking under peer-influence was mainly related to increased risk-taking propensity, and in the MBID-only group also to increased safety estimates and increased confidence in these safety estimates. The present study shows that risk-taking in MBID may be better explained by low intellectual functioning than by comorbid BD, and may not originate in increased risk taking per se, but may rather be related to risk-taking under peer-influence, which is a complex, multifaceted risk-taking context. Therefore, interventions to decrease risk-taking by adolescents with MBID that specifically target peer-influence may be successful.

Experiencing child sexual abuse (CSA) is a major public health problem with serious consequences for CSA victims. For effective assessment and (preventive) intervention, knowledge on risk factors and their effects is crucial. Here, the aim was to synthesize research on associations between (putative) risk factors and CSA victimization. In total, 765 (putative) risk factors were extracted from 72 studies, which were classified into 35 risk domains. A series of three-level meta-analyses produced a significant mean effect for 23 of the 35 risk domains ranging from r = .101 to r = .360. The strongest effects were found for prior victimization of the child and/or its family members, such as prior CSA victimization of the child and/or siblings (r = .360), prior victimization of the child other than child abuse (r = .340), prior or concurrent forms of child abuse in the child's home environment (r = .267), and a parental history of child abuse victimization (r = .265). Other identified risks were related to parental problems (e.g., intimate partner violence, r = .188), parenting problems (e.g., low quality of parent-child relation, r = .292), a non-nuclear family structure (e.g., having a stepfather, r = .118), family problems (e.g., social isolation, r = .191), child problems (e.g., having a mental/physical chronic condition, r = .193), and other child characteristics (e.g., being female, r = .290). Moderator analyses suggested that contact CSA victimization may be better predicted than noncontact CSA victimization. It was concluded that an ecological perspective on preventing CSA victimization is necessary. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Background: Little is known about the nature and reactions to sexual abuse of children with intellectual disability (ID). The aim was to fill this gap.Method: Official reports of sexual abuse of children with ID in state care were examined (N = 128) and compared with children without ID (N = 48).Results: Clear signs of penetration or genital touching by male (adolescent) peers or (step/foster)fathers were found in most ID reports. Victims often received residential care and disclosed themselves. Type of perpetrator seemed to affect the nature and reaction to the abuse. Cases of children with and without ID seemed to differ in location and reports to police.Conclusions: Screening of (foster)homes seems crucial. Residential facilities should find a balance between independence of children and protection. Care providers should be trained in addressing sexual issues and sexual education, accounting for different types of perpetrators (peers/adults). Uniform reporting guidelines are needed.

This study investigated the long-term effects of a professional development intervention for beginning urban teachers and explored which characteristics and activities in school organisations contributed to the sustainability of these effects. A quasi-experimental study (n = 72) investigated whether the positive effects of the programme were observed one year after the programme ended. Interviews with teachers and principals (n = 19) were used to explore which characteristics and activities in schools contributed to those positive effects. A significant long-term effect of the programme was found on teachers’ competences and professional orientation. An open culture in the schools was experienced as an important factor for the sustainability of the programme’s effects.

In multigroup factor analysis, configural measurement invariance is accepted as tenable when researchers either (a) fail to reject the null hypothesis of exact fit using a χ2 test or (b) conclude that a model fits approximately well enough, according to one or more alternative fit indices (AFIs). These criteria fail for two reasons. First, the test of perfect fit confounds model fit with group equivalence, so rejecting the null hypothesis of perfect fit does not imply that the null hypothesis of configural invariance should be rejected. Second, treating common rules of thumb as critical values for judging approximate fit yields inconsistent results across conditions because fixed cutoffs ignore sampling variability of AFIs. As a solution, we propose replacing χ2 and fixed AFI cutoffs with permutation tests. Iterative permutation of group assignment yields an empirical distribution of any fit measure under the null hypothesis of invariance. Simulations show the permutation test of configural invariance controls Type I error rates better than χ2 or AFIs when a model has parsimony error (i.e., negligible misspecification) but the factor structure is equivalent across groups (i.e., the null hypothesis is true).

The present randomized controlled trial examined the four months follow-up effectiveness of Parent Management Training Oregon (PMTO) for parents with foster children (aged 4–12) with severe externalizing behavior problems in long-term foster care arrangements. The aim of PMTO, a relative long and intensive (6–9 months, with weekly sessions) parent management training is to reduce children's problem behavior through improvement of parenting practices. We specifically investigated whether PMTO is effective to reduce foster parenting stress. It was expected that PMTO would reduce parenting stress in foster parents, improve the quality of parenting practices, and reduce children's problem behavior. Multi-informant (foster mothers, foster fathers, and teachers) data were used from 86 families. Multilevel analyses based on the intention to treat principle (retention rate 73%) showed that PMTO, compared to care as usual, had no significant direct, nor indirect or sleeper effects at follow-up on parenting stress, parenting behavior and child behavior problems. Earlier reported immediate effects of PMTO on reduced parenting stress at posttest disappeared at follow-up. Additional analyses on the role of non-specific intervention factors in PMTO effects showed that higher therapist fidelity scores resulted in stronger effects of PMTO on parenting responsiveness, parental explaining and autonomy granting. Unexpectedly, higher fidelity scores also predicted less decrease of parenting stress at follow-up.

Although bright light therapy seems a promising treatment for sleep problems, research shows inconclusive results. This meta-analysis is the first to systematically review the effect of light therapy on sleep problems in general and on specific types of sleep problems in particular (circadian rhythm sleep disorders, insomnia, sleep problems related to Alzheimer's disease and dementia). Fifty-three studies with a total of 1154 participants were included. Overall effects and effects on separate circadian and sleep outcomes were examined. We calculated Hedges' g effect sizes and we investigated the effects of twelve moderators (design-related, treatment-related, participant-related). Light therapy was found effective in the treatment of sleep problems in general (g = 0.39), and for circadian rhythm sleep disorders (g = 0.41), insomnia (g = 0.47), and sleep problems related to Alzheimer's disease/dementia (g = 0.30) specifically. For circadian rhythm sleep disorders, effects were smaller for randomised controlled trials. For insomnia, we found larger effects for studies using a higher light intensity, and for sleep problems related to Alzheimer's disease/dementia larger effects were found for studies with more female participants. There was indication of publication bias. To conclude, light therapy is effective for sleep problems in general, particularly for circadian outcomes and insomnia symptoms. However, most effect sizes are small to medium.

The effects of Home-Start compared to Home-Start extended with Triple P group training were studied. The underlying theoretical models of change of both programs complement each other and therefore it was assumed that combined support leads to increased positive outcomes. Outcomes related to parental wellbeing, parenting behaviour and child behaviour were included. One hundred forty four parents, all mothers, were randomly assigned to either the Home-Start program or the combined support of Home-Start and Triple P group level 4. Parents reported on wellbeing, parenting behaviour, and child behaviour at baseline, post-program and at 6-month follow-up. Based on intention to treat analyses, families in the combined intervention condition showed similar effects on the majority of primary and secondary outcomes as the only receiving Home-Start condition. A negative effect on parental depression and on two subscales of the Child Behavioral Checklist (anxiety and oppositional defiant behaviour) was found for families in the combined Home Start and Triple-P condition. The hypothesized stronger positive effect of combining Home-Start and Triple P support on selected outcome measures was not confirmed. Combining promising evidence-based parenting programs with complementary underlying theoretical frameworks does not necessarily lead to better results.

The present study examined the link between financial problems and delinquency in adolescents and young adults ( N = 1,258). Using three measurement waves that covered a time span of 6 years, we conducted cross-lagged panel analyses. Overall, we found evidence that financial problems increase the risk of delinquency, and vice versa. Effects of delinquency on financial problems were larger than the other way around. In addition, a longer term (6 year) effect of delinquency on financial problems was found, whereas this effect was not found for financial problems to delinquency. Gender and age did not moderate the financial problem–delinquency link, suggesting that the bidirectional effect between financial problems and delinquency applies to adolescent and young adult males and females. Finally, we found some evidence to suggest that the indirect effects became stronger over time.

Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation tool that may offer several advantages in comparison to a standard LC model. When using an LC model for density estimation, a considerable number of increasingly large LC models may have to be estimated before sufficient model-fit is achieved. A DLC model consists of a sequence of small LC models. Therefore, a DLC model can be estimated much faster and can easily utilize multiple processor cores, meaning that this model is more widely applicable and practical. In this study we describe the algorithm of fitting a DLC model, and discuss the various settings that indirectly influence the precision of a DLC model as a density estimation tool. These settings are illustrated using a synthetic data example, and the best performing algorithm is applied to a real-data example. The generated data example showed that, using specific decision rules, a DLC model is able to correctly model complex associations amongst categorical variables.

A conceptual framework is presented to understand and study the role of students’ agency in their school (dis-)engagement from a Funds of Identity (FoI) perspective. The framework includes the notion of agency combined with Funds of Learner Identity (FoLI): learning preferences that can be considered part of people’s Funds of Identity. The framework holds that students manifest agency to negotiate engaging learning experiences when the school’s affordances and constraints are considerably relatable to their FoLI and allow them to define themselves in desired ways. However, adolescents who feel that possibilities to engage their FoLI are rather limited in school are expected to turn to other contexts to learn, such as home, peer groups and workplaces. An exemplary case study is presented to illustrate the framework and implications are discussed.

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.

Selective mutism (SM) is a relatively rare anxiety disorder, characterized by a child's consistent failure to speak in various specific social situations (e.g., at school), while being able to speak in other situations (e.g., at home). Prevalence rates vary from 0.2% to 1.9%. SM is usually identified between the ages of 3-5 years. It is often underdiagnosed and consequently children receive no or inadequate treatment, with negative consequences for school and social functioning. If left untreated, SM can result in complex, chronic anxiety and/or mood disorders in adolescence and impaired working careers in adulthood. Currently, no evidence-based treatment for SM is available in the Netherlands, therefore this study aims to [1] test the effectiveness of a treatment protocol for SM that is carried out at school, and to [2] identify baseline predictors for treatment success. This article presents the design of a randomized controlled trial into the effectiveness of a behavioral therapeutic protocol for selective mutism in children (age 3-18). The expected study population is n = 76. Results of the treatment group (n = 38) will be compared with those of a waiting list control group (WCG) (n = 38). Pre and post treatment assessments will be conducted at comparable moments in both groups, with baseline assessment at intake, the second assessment at 12 weeks and post-assessment at the end of treatment. If proven effective, we aim to structurally implement this protocol as evidence-based treatment for SM.

As the focus of this chapter, we discuss nonparametric item response theory for ordinal person scales, specifically the monotone homogeneity model and Mokken scale analysis, which is the data-analysis procedure used for investigating the compliance between the monotone homogeneity model and data. Next, we discuss the unrestricted latent class model as an even more liberal model for investigating the scalability of a set of items, producing nominal scales, but we also discuss an ordered latent class model that one can use to investigate assumptions about item response functions in the monotone homogeneity model and other nonparametric item response models. Finally, we discuss cognitive diagnostic models, which are the core of this volume, and which are a further deepening of latent class models, providing diagnostic information about the people who responded to a set of items. A data analysis example, using item scores of 1210 respondents on 44 items from the Millon Clinical Multiaxial Inventory III, demonstrates how the monotone homogeneity model, the latent class model, and two cognitive diagnostic models can be used jointly to understand one’s data.

We simulated Bayesian CFA models to investigate the power of PPP to detect model misspecification by manipulating sample size, strongly and weakly informative priors for nontarget parameters, degree of misspecification, and whether data were generated and analyzed as normal or ordinal. Rejection rates indicate that PPP lacks power to reject an inappropriate model unless priors are unrealistically restrictive (essentially equivalent to fixing nontarget parameters to zero) and both sample size and misspecification are quite large. We suggest researchers evaluate global fit without priors for nontarget parameters, then search for neglected parameters if PPP indicates poor fit.

This study investigates the usefulness of item-score reliability as a criterion for item selection in test construction. Methods MS, λ6, and CA were investigated as item-assessment methods in item selection and compared to the corrected item-total correlation, which was used as a benchmark. An ideal ordering to add items to the test (bottom-up procedure) or omit items from the test (top-down procedure) was defined based on the population test-score reliability. The orderings the four item-assessment methods produced in samples were compared to the ideal ordering, and the degree of resemblance was expressed by means of Kendall's τ. To investigate the concordance of the orderings across 1,000 replicated samples, Kendall's W was computed for each item-assessment method. The results showed that for both the bottom-up and the top-down procedures, item-assessment method CA and the corrected item-total correlation most closely resembled the ideal ordering. Generally, all item assessment methods resembled the ideal ordering better, and concordance of the orderings was greater, for larger sample sizes, and greater variance of the item discrimination parameters.

In een opvoedkundige context moet vaak beoordeeld worden: een onderwijzer beslist of het gedrag van een leerling bestraft wordt, een docent beoordeelt een scriptie of een raadsonderzoeker geeft een complexe assessment van een verdachte jongere. De interbeoordelaarsbetrouwbaarheid (IBB) geeft de mate weer waarin verschillende beoordelaars het met elkaar eens zijn. In dit paper behandelen we drie vragen over de IBB. De eerste vraag - Hoe bepaal je de IBB? - is niet eenduidig te beantwoorden omdat er veel coëfficiënten zijn om de IBB te schatten, die vaak verschillende resultaten opleveren. De keuze voor een IBB-coëfficiënt wordt bepaald door het doel en het design van het onderzoek, en door persoonlijke voorkeur. Het antwoord op de tweede vraag - Hoe kun je de IBB verhogen? - behelst het verhogen van de kwaliteit van de items, de rubrics en de beoordelingsprocedure, en de kunde van de beoordelaars. De derde vraag - Wanneer is de IBB hoog genoeg? - kan ook niet ondubbelzinnig worden beantwoord. We presenteren methoden om benchmarks voor één IBB-coëfficiënt in een andere te transformeren, maar stellen dat meer methodologisch onderzoek naar IBB vereist is om betere antwoorden op deze vraag te bieden.

Why are some children more socially anxious than others? One theory holds that socially anxious children are poor mindreaders, which hampers their social interactions; another that socially anxious children are advanced mindreaders leading to heightened self-consciousness in social situations. To test these theories simultaneously, this study (N = 105, ages 8–12) assessed children’s mindreading (accuracy in detecting mental states from the eye region), self-consciousness (indexed as physiological blushing during public performance), and social anxiety levels. Results support both theories, showing a quadratic relation between mindreading and social anxiety. Low mindreading was related to clinical levels of social anxiety. High mindreading was related to subclinical levels of social anxiety through blushing. Our findings suggest two social-cognitive pathways to heightened social anxiety.

Structural equation modeling (SEM) is becoming the central and arguably most popular analytical tool in social sciences. Many classical and modern statistical techniques such as regression analysis, path analysis, confirmatory factor analysis, and models with both measurement and structural components have been shown to fall under the umbrella of SEM. The flexibility of SEM makes it applicable to many research designs, including experimental and non-experimental data, cross-sectional and longitudinal data, and multiple-group and multilevel problems.Recently, there have been exciting advancements in SEM, from fundamental issues like alternative estimation methods that are robust to often violated assumptions to the expansions of SEM to incorporate complex multilevel and cross-classified data that are common in the social sciences. This Research Topic aims to bring in a collection of SEM papers which not only tackle technical estimation issues, but also examine and demonstrate the applications of SEM to more complex settings. The proposed topics include (but are not limited to): applying robust estimation method, testing interaction effect, examining measurement invariance, and specifying and evaluating models applied to more complex data including meta-analytic data, multilevel and longitudinal data.

Abstract. The Screener and Opioid Assessment for Patients with Pain – Revised (SOAPP-R) is a 24-item self-report questionnaire that assesses risk of aberrant medication-related behavior among chronic pain patients. Recently, an 8-item version of the SOAPP-R that weights items differentially was proposed. However, no previous study had compared the 8-item form with other short versions of the SOAPP-R, including a static 12-item short form and computer-based versions customizing the test length to the individual respondent. Moreover, no prior research had investigated combining the 8-item short form with customized computer-based stopping rules to further enhance efficiency. The objectives of this study were to compare the 8-item version with previously recommended short forms of the SOAPP-R, and to develop and evaluate a new version of the SOAPP-R combining the 8-item version with computer-based stopping rules. Versions were compared via sensitivity, specificity, and mean test length using real-data simulation of three datasets. Although results varied across datasets, the 8-item SOAPP-R compared favorably to previously recommended forms. Combining the 8-item form with computer-based stopping rules reduced the mean test length without affecting sensitivity or specificity; thus, the combined approach is recommended. The methodology used to shorten questionnaires via computer-based testing can also be applied to other instruments.

A study of parental wellbeing in the U.K., France, and the Netherlands compared parents in 38 gay father families, 61 lesbian mother families, and 42 heterosexual parent families. In all family types, the parents had just become parents for the first time and had an infant aged around 4 months. The infants in the gay father families were born through surrogacy, and those in the lesbian mother families were conceived after insemination with donor sperm. The heterosexual parent families had used in vitro fertilization without sperm or egg donation. Standardized measures of parental wellbeing (parental stress, psychological adjustment, and partner relationship satisfaction) were used to collect data via a password-protected online survey. Both parents in all families completed the survey. The parents’ scores on the studied variables were similar regardless of family type or caregiver role. The findings of the present study contribute to the theoretical understanding of the role of family type and caregiver role in families whose first child was conceived by means of assisted reproductive technologies, and especially our knowledge of gay fathers who became parents through surrogacy.

In dit onderzoek is de interbeoordelaarsbetrouwbaarheid (IBB) onderzocht van het Landelijk Instrumentarium Jeugdstrafrechtketen (LIJ). Het LIJ is een instrument voor de signalering, screening en risicotaxatie bij iedere jongere die verdachte is in een strafzaak in Nederland. Het LIJ wordt ingevuld door een raadsonderzoeker van de Raad voor de Kinderbescherming, aan de hand van dossieronderzoek, gesprekken met de jongere en zijn of haar ouders of verzorgers en aanvullende informatie. De IBB van het LIJ is de mate van overeenstemming tussen verschillende raadsonderzoekers wanneer zij dezelfde jongere beoordelen met behulp van het LIJ. Omdat het strafadvies van de jongere en een eventueel behandelingsplan gebaseerd is op de LIJ beoordeling, heeft de LIJ beoordeling een grote impact op de toekomst van de jongere en is een hoge IBB gewenst. In dit rapport is de IBB geschat van zowel het dynamisch risicoprofiel als alle afzonderlijke vragen van het LIJ.

Meta-analytic structural equation modeling (MASEM) is a statistical technique to pool correlation matrices and test structural equation models on the pooled correlation matrix. In Stage 1 of MASEM, correlation matrices from independent studies are combined to obtain a pooled correlation matrix, using fixed- or random-effects analysis. In Stage 2, a structural model is fitted to the pooled correlation matrix. Researchers applying MASEM may have hypotheses about how certain model parameters will differ across subgroups of studies. These moderator hypotheses are often addressed using suboptimal methods. The aim of the current article is to provide guidance and examples on how to test hypotheses about group differences in specific model parameters in MASEM. We illustrate the procedure using both fixed- and random-effects subgroup analysis with two real datasets. In addition, we present a small simulation study to evaluate the effect of the number of studies per subgroup on convergence problems. All data and the R-scripts for the examples are provided online.

BackgroundTwo important goals when using questionnaires are (a) measurement: the questionnaire is constructed to assign numerical values that accurately represent the test taker’s attribute, and (b) prediction: the questionnaire is constructed to give an accurate forecast of an external criterion. Construction methods aimed at measurement prescribe that items should be reliable. In practice, this leads to questionnaires with high inter-item correlations. By contrast, construction methods aimed at prediction typically prescribe that items have a high correlation with the criterion and low inter-item correlations. The latter approach has often been said to produce a paradox concerning the relation between reliability and validity [1, 2, 3], because it is often assumed that good measurement is a prerequisite of good prediction.ObjectiveTo answer four questions: (1) Why are measurement-based methods suboptimal for questionnaires that are used for prediction? (2) How should one construct a questionnaire that is used for prediction? (3) Do questionnaire-construction methods that optimize measurement and prediction lead to the selection of different items in the questionnaire? (4) Is it possible to construct a questionnaire that can be used for both measurement and prediction?Illustrative exampleAn empirical data set consisting of scores of 242 respondents on questionnaire items measuring mental health is used to select items by means of two methods: a method that optimizes the predictive value of the scale (i.e., forecast a clinical diagnosis), and a method that optimizes the reliability of the scale. We show that for the two scales different sets of items are selected and that a scale constructed to meet the one goal does not show optimal performance with reference to the other goal.DiscussionThe answers are as follows: (1) Because measurement-based methods tend to maximize inter-item correlations by which predictive validity reduces. (2) Through selecting items that correlate highly with the criterion and lowly with the remaining items. (3) Yes, these methods may lead to different item selections. (4) For a single questionnaire: Yes, but it is problematic because reliability cannot be estimated accurately. For a test battery: Yes, but it is very costly. Implications for the construction of patient-reported outcome questionnaires are discussed.

Background: Children exposed to antiepileptic drugs (AEDs) in utero are at higher risk for congenital malformations. Less is known about the long-term association with neurocognition and behavior. Research into family factors related to long-term developmental outcomes of children of women with epilepsy is also rare. We present a protocol to investigate the neurocognitive and behavioral development in children of mothers with epilepsy from a family perspective. Methods: This is a prospective observational longitudinal study, of children exposed in utero to monotherapy carbamazepine, lamotrigine, valproate or levetiracetam whose mother were previously included in the European Registry of Antiepileptic Drugs and Pregnancy (EURAP-NL) database. Children are tested at age six or seven years (T1) and at eight or nine years (T2). Children, mothers and fathers are asked to undergo neuropsychological assessments and to complete questionnaires on behavioral functioning and distinct family factors. Discussion: This study contributes to future counseling of women with epilepsy who have children or wishes to start a family. Strengths are the inclusion of levetiracetam, the longitudinal design, and alongside neurocognition, the inclusion of differential behavioral and family outcome measures. Anticipated limitations are discussed.

Previous evidence revealed links between maternal negative emotions and infants' attention to facial expressions of emotion in clinical and community samples. This study investigated the associations between infants' attention to emotional faces and infants' and parents' negative emotions in a community sample. Infants' (N = 57, Mage = 14.26 months) fixations and pupil responses to fearful, sad, angry versus happy and neutral faces were measured with an eye-tracker. Mothers' and fathers' negative emotions (negative affect, depression, and anxiety), and infants' negative temperament were measured with questionnaires. Infants looked longer at fearful than happy or neutral faces, while they showed less pupil dilation to fearful than to happy or neutral faces. Higher levels of maternal negative emotions were related to less pupillary arousal to emotional facial expressions in infants, while paternal negative emotions did not predict infants' pupil responses. Exploratory analyses suggested a significant link between paternal but not maternal negative emotions and infants' fixations that was moderated by infant negative temperament: Higher levels of negative emotions in fathers were related to longer fixations in children with high levels of negative temperament, while it was related to shorter fixations in infants with low levels of negative temperament. The findings provide support for the idea that exposure to mothers' and fathers' negative emotions play a role on the development of infants' attention to facial expressions in typical development.

The ordinal, unidimensional monotone latent variable model assumes unidimensionality, local independence, and monotonicity, and implies the observable property of conditional association. We investigated three special cases of conditional association and implemented them in a new procedure that aims at identifying locally dependent items, removing these items from the initial item set, and producing an item subset that is locally independent. A simulation study showed that the new procedure correctly identified 89.5% of the model-consistent items and up to 90% of the model-inconsistent items. We recommend using this procedure for selecting locally independent item sets. The procedure may be used in combination with Mokken scale analysis.Keywords: conditional association, local independence, model-fit assessment, monotonicity, nonparametric item response theory, unidimensionality

This study aimed to examine the relationship between teachers’ perceived psychological distance and structural distance from management and teachers’ affective organisational commitment (AOC) and organisational citizenship behaviour (OCB). Teachers’ trust in management was expected to mediate these relationships. Furthermore, the adequacy and openness of communication and participation in decision making were expected to reduce psychological distance. At 10 Dutch schools for vocational education and training, 884 teachers completed a questionnaire. The data were analysed using structural equation modelling. Teachers’ psychological distance had a negative effect on trust in management (supervisor and higher management) and AOC. Trust in management had a positive effect on AOC, and trust in the supervisor had a positive effect on OCB. Structural distance did not influence teacher outcomes. Communication and participation in decision making reduced teachers’ psychological distance from management. The discussion focuses on the implications of the findings to improve the effectiveness of schools.

Child helplines around the world are an important mental health resource for many children. In this study, an international database was analysed with a total of 25 million registered calls at a total of 111 helplines affiliated with Child Helpline International. The research was aimed at discovering if there are differences between the reasons for calling of children from different parts of the world, and if shifts in the studied 10-year period can be observed. The data show that all child helplines are contacted by young people seek support with questions concerning abuse, sexual matters and school issues. The results from a mixed model also show significant differences in the reasons for calling between Africa, Asia, Europe, Latin America, North America, the Pacific region and the region Middle East and North Africa. Child helplines in Africa and other developing parts of the world received many calls related to safety and health (e.g. HIV/AIDS, commercial exploitation), whereas children and young people from Europe, North America and the Pacific more often discussed social and psychosocial issues with the helpline (e.g. mental health, peer and family relations). The reasons for calling were relatively stable for the studied period. © 2016 John Wiley & Sons Ltd and National Children’s Bureau

BackgroundSleep is vital for adolescent functioning. Those with optimal sleep duration have shown improved capacity to learn and decreased rate of motor vehicle accidents. This study explored the influence of numerous protective and risk factors on adolescents' school night sleep (bedtime, sleep latency, total sleep time) simultaneously to assess the importance of each one and compare within three countries.MethodOnline survey data were collected from Australia, Canada, and The Netherlands. Overall, 325 (137 male), 193 (28 male), and 150 (55 male) contributed to data from Australia, Canada, and The Netherlands, respectively (age range 12–19 years).ResultsRegression analyses showed mixed results, when comparing protective and risk factors for sleep parameters within different countries, with combined behavioural factors contributing to small to large shared portions of variance in each regression (9–50%). One consistent finding between countries was found, with increased pre-sleep cognitive emotional sleep hygiene related to decreased sleep latency (beta = −0.25 to −0.33, p ConclusionResults indicate that when designing interventions for adolescent sleep, multiple lifestyle factors need to be considered, whereas country of residence may play a lesser role.

Inclusive special needs education is prominent on the international education agenda. Research on the characteristics of inclusive education for students with special needs and schools providing this is scarce, however. Our aim in the present study was therefore to further theory-building with regard to inclusive special needs education. On the basis of the relevant literature, we identified three core aspects of inclusivity: the learning environment, the guidance provided by teachers and the general care structure. With the help of exploratory and confirmatory factor analyses conducted on data obtained from school professionals in 79 secondary schools in the Netherlands, we were able to identify 12 underlying characteristics for a conceptual framework to further research on the inclusive nature of schools and education. Multilevel structural equation modelling of the judgments of school professionals at the level of the school also showed that the inclusive special needs education in at least secondary schools can be characterised by two main factors: (1) learning environment and (2) guidance and care. The analyses showed considerable agreement on the important aspects of inclusivity for schools and thus how differences between schools can be explained. The results further showed the work of the care coordinator – which includes cooperation with external partners and teachers with mentoring roles – to be the clearest indicator of the extent of the inclusive special needs education within schools. This finding is interpreted as suggesting that the recommended teaching practices and student care for adequate included special needs education have not yet been integrated into teachers’ thinking and acting. Follow-up research drawing upon the developed framework is therefore called for to not only more generally validate the framework but also determine if the situation in school has changed, now that the policy and practices for inclusive education have become more familiar.

We show by simulations that the main premise underlying Gignac's (2016) rejection of the mutualism model of general intelligence is incorrect. We discuss our results in the context of the debate on g-factor theory and its alternatives, especially with regard to the claim that g-factor theory is much simpler than mutualism theory.

Meta-analytic structural equation modeling (MASEM) is increasingly applied to advance theories by synthesizing existing findings. MASEM essentially consists of two stages. In Stage 1, a pooled correlation matrix is estimated based on the reported correlation coefficients in the individual studies. In Stage 2, a structural model (such as a path model) is fitted to explain the pooled correlations. Frequently, the individual studies do not provide all the correlation coefficients between the research variables. In this study, we modify the currently optimal MASEM-method to deal with missing correlation coefficients, and compare its performance with existing methods. This study is the first to evaluate the performance of fixed-effects MASEM methods under different levels of missing correlation coefficients. We found that the often used univariate methods performed very poorly, while the multivariate methods performed well overall.

For four data sets of different measurement levels, we computed 20 coefficients that estimate interrater reliability. The results show that the coefficients provide very different numerical values when applied to the same data. We discuss possible explanations for the differences among coefficients and suggest further research that is needed to clarify which coefficient a researcher should use to estimate interrater reliability.

Categorical marginal models are flexible models for modelling dependent or clustered categorical data which do not involve any specific assumptions about the nature of the dependencies. Categorical marginal models are used for different purposes, including hypothesis testing, assessing model fit, and regression problems. Two different estimation methods are used to estimate marginal models: maximum likelihood (ML) and generalized estimating equations (GEE). We explored three different cases to find out to what extent the two types of estimation methods are appropriate for investigating different types of research questions. The results suggest that ML may be preferred for assessing model fit because GEE has limited fit indices, whereas both methods can be used to assess the effect of independent factors in regression. Moreover, ML is asymptotically efficient, while GEE loses efficiency when the working correlation matrix is not correctly specified. However, for parameter estimation in regression GEE is easier to apply from a computational perspective.

To investigate the efficacy of cognitive behavioral therapy for insomnia (CBTI) in adolescents.A randomized controlled trial of CBTI in group therapy (GT), guided internet therapy (IT), and a waiting list (WL), with assessments at baseline, directly after treatment (post-test), and at 2 months follow-up.Diagnostic interviews were held at the laboratory of the Research Institute of Child Development and Education at the University of Amsterdam. Treatment for GT occurred at the mental health care center UvAMinds in Amsterdam, the Netherlands.One hundred sixteen adolescents (mean age = 15.6 y, SD = 1.6 y, 25% males) meeting DSM-IV criteria for insomnia, were randomized to IT, GT, or WL.CBTI of 6 weekly sessions, consisted of psychoeducation, sleep hygiene, restriction of time in bed, stimulus control, cognitive therapy, and relaxation techniques. GT was conducted in groups of 6 to 8 adolescents, guided by 2 trained sleep therapists. IT was applied through an online guided self-help website with programmed instructions and written feedback from a trained sleep therapist.Sleep was measured with actigraphy and sleep logs for 7 consecutive days. Symptoms of insomnia and chronic sleep reduction were measured with questionnaires. Results showed that adolescents in both IT and GT, compared to WL, improved significantly on sleep efficiency, sleep onset latency, wake after sleep onset, and total sleep time at post-test, and improvements were maintained at follow-up. Most of these improvements were found in both objective and subjective measures. Furthermore, insomnia complaints and symptoms of chronic sleep reduction also decreased significantly in both treatment conditions compared to WL. Effect sizes for improvements ranged from medium to large. A greater proportion of participants from the treatment conditions showed high end-state functioning and clinically significant improvement after treatment and at follow-up compared to WL.This study is the first randomized controlled trial that provides evidence that cognitive behavioral therapy for insomnia is effective for the treatment of adolescents with insomnia, with medium to large effect sizes. There were small differences between internet and group therapy, but both treatments reached comparable endpoints.This study was part of the clinical trial: Effectiveness of cognitive behavioral therapy for sleeplessness in adolescents; URL: http://www.isrctn.com/ISRCTN33922163; registration: ISRCTN33922163.

We discuss reliability definitions from the perspectives of classical test theory, factor analysis, and generalizability theory. For each method, we discuss the rationale, the estimation of reliability, and the goodness of fit of the model that defines the reliability coefficient to the data. Similarities and differences in the three approaches are highlighted. Finally, we provide a computational example using generated data to illustrate the differences among the different reliability methods.

Person misfit on a self-report measure refers to a response pattern that is unlikely given a theoretical measurement model. Person misfit may reflect low quality self-report data, for example due to random responding or misunderstanding of items. However, recent research in the context of psychopathology suggests that person misfit may reflect atypical symptom profiles that have implications for diagnosis or treatment. We followed-up on Wanders et al. (Journal of Affective Disorders, 180, 36–43, 2015) who investigated person misfit on the Inventory of Depressive Symptomatology (IDS) in the Netherlands Study of Depression and Anxiety (n = 2,981). Our goal was to investigate the extent to which misfit on the IDS reflects low-quality self-report patterns and the extent to which it reflects true atypical symptom profiles. Regression analysis showed that person misfit related more strongly to self-report quality indicators than to variables quantifying theoretically-derived atypical symptom profiles. A data-driven atypical symptom profile explained most variance in person misfit, suggesting that person misfit on the IDS mainly reflects a sample- and questionnaire-specific atypical symptom profile. We concluded that person-fit statistics are useful for detecting IDS scores that may not be valid. Further research is necessary to support the interpretation of person misfit as reflecting a meaningful atypical symptom combination.

Background: Practice guidelines for childhood posttraumatic stress disorder (PTSD) recommend trauma-focused psychotherapies, mainly cognitive behavioral therapy (CBT). Eye movement desensitization and reprocessing (EMDR) therapy is a brief trauma-focused, evidence-based treatment for PTSD in adults, but with few well-designed trials involving children and adolescents. Methods: We conducted a single-blind, randomized trial with three arms (n = 103): EMDR (n = 43), Cognitive Behavior Writing Therapy (CBWT; n = 42), and wait-list (WL; n = 18). WL participants were randomly reallocated to CBWT or EMDR after 6 weeks; follow-ups were conducted at 3 and 12 months posttreatment. Participants were treatment-seeking youth (aged 8–18 years) with a DSM-IV diagnosis of PTSD (or subthreshold PTSD) tied to a single trauma, who received up to six sessions of EMDR or CBWT lasting maximally 45 min each. Results: Both treatments were well-tolerated and relative to WL yielded large, intent-to-treat effect sizes for the primary outcomes at posttreatment: PTSD symptoms (EMDR: d = 1.27; CBWT: d = 1.24). At posttreatment 92.5% of EMDR, and 90.2% of CBWT no longer met the diagnostic criteria for PTSD. All gains were maintained at follow-up. Compared to WL, small to large (range d = 0.39–1.03) intent-to-treat effect sizes were obtained at posttreatment for negative trauma-related appraisals, anxiety, depression, and behavior problems with these gains being maintained at follow-up. Gains were attained with significantly less therapist contact time for EMDR than CBWT (mean = 4.1 sessions/140 min vs. 5.4 sessions/227 min). Conclusions: EMDR and CBWT are brief, trauma-focused treatments that yielded equally large remission rates for PTSD and reductions in the severity of PTSD and comorbid difficulties in children and adolescents seeking treatment for PTSD tied to a single event. Further trials of both treatments with PTSD tied to multiple traumas are warranted.

Identification of subgroups of patients for which treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Several tree-based algorithms have been developed for the detection of such treatment-subgroup interactions. In many instances, however, datasets may have a clustered structure, where observations are clustered within, for example, research centers, studies or persons. In the current paper we propose a new algorithm, generalized linear mixed-effects model (GLMM) trees, that allows for detection of treatment-subgroup interactions, as well as estimation of cluster-specific random effects. The algorithm uses model-based recursive partitioning (MOB) to detect treatment-subgroup interactions, and a GLMM for the estimation of random-effects parameters. In a simulation study, we evaluate the performance of GLMM tree and compare it with that of MOB without random-effects estimation. GLMM tree was found to have a much lower Type I error rate than MOB trees without random effects (4% and 33%, respectively). Furthermore, in datasets with treatment-subgroup interactions, GLMM tree recovered the true treatment subgroups much more often than MOB without random effects (in 90% and 61% of the datasets, respectively). Also, GLMM tree predicted treatment outcome differences more accurately than MOB without random effects (average predictive accuracy of .94 and .88, respectively). We illustrate the application of GLMM tree on a patient-level dataset of a meta-analysis on the effects of psycho- and pharmacotherapy for depression. We conclude that GLMM tree is a promising algorithm for the detection of treatment-subgroup interactions in clustered datasets.

Data often have a nested, multilevel structure, for example when data are collected from children in classrooms. This kind of data complicate the evaluation of reliability and measurement invariance, because several properties can be evaluated at both the individual level and the cluster level, as well as across levels. For example, cross-level invariance implies equal factor loadings across levels, which is needed to give latent variables at the two levels a similar interpretation. Reliability at a specific level refers to the ratio of true score variance over total variance at that level. This paper aims to shine light on the relation between reliability, cross-level invariance, and strong factorial invariance across clusters in multilevel data. Specifically, we will illustrate how strong factorial invariance across clusters implies cross-level invariance and perfect reliability at the between level in multilevel factor models.

Norm statistics allow for the interpretation of scores on psychological and educational tests, by relating the test score of an individual test taker to the test scores of individuals belonging to the same gender, age, or education groups, et cetera. Given the uncertainty due to sampling error, one would expect researchers to report standard errors for norm statistics. In practice, standard errors are seldom reported; they are either unavailable or derived under strong distributional assumptions that may not be realistic for test scores. We derived standard errors for four norm statistics (standard deviation, percentile ranks, stanine boundaries and Z-scores) under the mild assumption that the test scores are multinomially distributed. A simulation study showed that the standard errors were unbiased and that corresponding Wald-based confidence intervals had good coverage. Finally, we discuss the possibilities for applying the standard errors in practical test use in education and psychology. The procedure is provided via the R function check.norms, which is available in the mokken package.

The Chronic Sleep Reduction Questionnaire is a validated questionnaire that measures symptoms of prolonged insufficient and/or poor sleep and therefore accounts for individuals' sleep need and sleep debt. This study extends its psychometric properties by providing cut-off scores, using a matched sample of 298 healthy adolescents (15.38 +/- 1.63years, 37.9% male, mean Chronic Sleep Reduction Questionnaire score: 32.98 +/- 6.51) and 298 adolescents with insomnia/delayed sleep-wake phase disorder (15.48 +/- 1.62years;37.9% male, mean Chronic Sleep Reduction Questionnaire score: 42.59 +/- 7.06). We found an area under the curve of 0.84 (95% confidence interval: 0.81-0.87). Cut-off scores for optimal sensitivity, optimal specificity and based on Youden's criterion are provided. These cut-off scores are highly relevant for use of the Chronic Sleep Reduction Questionnaire in future studies and clinical practice.

Objective: The latent factor structure of posttraumatic stress disorder (PTSD) remains a source of considerable variability. The current study compared several a priori factor structures, as well as a novel 2-factor structure of posttraumatic psychological distress as measured by the Clinician Administered PTSD scale for the DSM–5 (CAPS-5). In addition, variability in diagnostic rates according to the divergent DSM–5 and ICD-11 criteria were explored. Method: The setting for this study was a Level 1 trauma center in a U.S. metropolitan city. Data were pooled from 2 studies (N = 309) and participants were administered the CAPS-5 at 1 (n = 139) or 6 months postinjury (n = 170). Confirmatory factor analysis (CFA) was used to compare several factor models, and prevalence rates based on DSM–5 and ICD-11 criteria were compared via z tests and kappa. Results: CFAs of 5 factor structures indicated good fit for all models. A novel indices was then tested. The 2-factor model of the CAPS-5 performed as well or better on most indices compared to a 7-factor hybrid. Comparisons of PTSD prevalence rates found no significant differences, but agreement was variable. Conclusions: These findings indicate that the CAPS-5 can be seen as measuring 2 distinct phenomena: posttraumatic stress disorder and general posttraumatic dysphoria. This is an important contribution to the current debate on which latent factors constitute PTSD and may reduce discordance. 2-factor model based on competing models of PTSD symptoms and modification

The assumption of equivalence between measurement-model configurations across groups is typically investigated by evaluating overall fit of the same model simultaneously to multiple samples. However, the null hypothesis (H0) of configural invariance is distinct from the H0 of overall model fit. Permutation tests of configural invariance yield nominal Type I error rates even when a model does not fit perfectly (Jorgensen et al., 2017, in press). When the configural model requires modification, lack of evidence against configural invariance implies that researchers should reconsider their model's structure simultaneously across all groups. Application of multivariate modification indices is therefore proposed to help decide which parameter(s) to free simultaneously in all groups, and I present Monte Carlo simulation results comparing their Type I error control to traditional 1-df modification indices. I use the Holzinger and Swineford (1939) data set to illustrate these methods.