Lavaan Package Research Articles

Spanish Validation of the Adolescent Self-Consciousness Questionnaire.

Self-consciousness development takes place mainly in adolescence because the brain undergoes certain structural changes that facilitate abstract thinking and metacognition, thus favoring the development of identity. Despite the importance of self-consciousness for mental health, there are no specific measurement instruments for Spanish adolescents. The objective of this study was to explore the dimensions of self-consciousness among Spanish adolescents aged between 13 and 18 years and validate the Chinese Adolescent Self-Consciousness Questionnaire (ASC) in this population. A second-order confirmatory factor analysis (CFA) was conducted in accordance with previous validations of the ASC, using R Studio and the Lavaan package, to test its adequacy in a Spanish sample. Internal consistency and temporal stability were also tested, and evidence of validity was found. The results showed a good fit to the model eliminating four items with poor fit indices, CFI = .90, TLI = .89, RMSEA = .078, 95% CI [.076, .080]. Higher self-consciousness was associated with greater self-esteem and lower depressive symptomatology. No significant gender differences were found. This study provides a valid measure to evaluate self-consciousness in Spanish adolescents. The relationship established between self-consciousness and anxiety and depression requires further study as self-consciousness is involved in the development and maintenance of adolescent psychopathology.

ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R

Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model.
 Keywords: SEM, Multiple Group, R Program

Abstract P197: Factors Contributing to the Success of a Multicomponent Intervention for Blood Pressure Control in Argentina: A Mediation Analysis

Introduction: The Hypertension Control Program in Argentina (HCPIA), a cluster-randomized trial of a community health worker-led multicomponent intervention on blood pressure (BP) control in low-income patients in Argentina, previously reported a significant reduction in systolic BP in the intervention compared to the control group over 18 months (6.6 mm Hg net difference; p<0.001). Understanding which elements of a multicomponent intervention are important contributors to its success is critical for future BP control efforts. We conducted a mediation analysis to determine the contributions of seven measured intervention targets to the systolic BP intervention effect. Methods: HCPIA randomized 18 primary healthcare clinics treating uninsured patients to either a multicomponent intervention, consisting of health coaching, home blood pressure monitoring, blood pressure audit and feedback, physician education, and a mobile health intervention, or usual care. A total of 1,357 hypertensive participants completed the trial and are included in the mediation analyses. Changes in seven potential mediators over the 18-month intervention were assessed: medication adherence score, medication adjustments (addition of new medication or dose titration), waist circumference, physical activity, fruit and vegetable consumption, sodium consumption, and alcohol consumption. Generalized estimating equations were used to compare changes in potential mediators between intervention groups. Path analytic models were used to test single-mediator and multiple mediator indirect intervention effects using the Lavaan package in R statistical software. Mediation was considered significant at p<0.10. Results: All potential mediators were significantly improved in the intervention group compared to the control group. Fruit and vegetable consumption, medication adherence, physical activity, and salt consumption are each significant mediators accounting for 4.3, 3.8, 3.3, and 3.2%, respectively, of the intervention effect in single-mediator models. The multiple mediation model explained 15.5% (1.3 mm Hg) of the total intervention effect. Changes in fruit and vegetable consumption and medication adherence remained significant mediators in multiple mediation analysis, responsible for 3.8% and 4.3% of the net reduction in systolic BP, respectively. Other potential mediators did not account for a significant proportion of the intervention effect. Conclusions: Increases in medication adherence and fruit and vegetable consumption were responsible for the largest proportions of the explained intervention effect.

Analysis of Perceived Physical and Motor Competence in 10- to 13-year-old Spanish Children

It was our objective to analyze the perceived physical and motor competence in 10- to 13-year-old Spanish children, and to validate to the Spanish language and context the questionnaire of Scrabis-Fletcher and Silverman (2010). The perception of competence was analysed in 27 schools of Albacete (Spain), with a total of 389 boys and 391 girls, whose age ranged from 10 to 13 (average=11.08 and SD=0.43). Different analyses were performed, starting with a forward analysis of the items, using graphics and statistics. After this, an internal consistence study was performed, through Cronbach's alpha, using a multilevel package, version 2.3. Finally, the constructs structure was analyzed through a factorial confirmatory analysis (FCA), which used a Lavaan package, version 0.5-11. The consistence was high as a whole (Cronbach's alpha: 0.74). There was a high correlation between all items, even those from different factors. Regarding the analysis of students´ perceived physical and motor competence, the best values were obtained in the perceptions they had about their teachers and classmates, although they had worse values about their own personal experiences. Two questionnaires of 2 and 3 factors, using 7 and 14 items, respectively were established. Therefore, the instrument Perception of Competence in Middle School Physical Education was validated within the Spanish social context. The main practical application is the possibility of using this questionnaire in the PE lessons in Spain to know and increase the perceived physical and motor competence of the children.

A robust alternative estimator for small to moderate sample SEM: Bias-corrected factor score path analysis

Structural equation modeling with full information maximum likelihood estimation is the predominant method to empirically assess complex theories involving multiple latent variables in addiction research. Although full information estimators have many desirable properties including consistency, a major limitation in structural equation models is that they often sustain significant bias when implemented in small to moderate size studies (e.g., fewer than 100 or 200). Recent literature has developed a limited information estimator designed to address this limitation—conceptually implemented through a bias-corrected factor score path analysis approach—that has been shown to produce unbiased and efficient estimates in small to moderate sample settings. Despite its theoretical and empirical merits, literature has suggested that the method is underused because of three primary reasons—the methods are unfamiliar to applied researchers, there is a lack of practical and accessible guidance and software available for applied researchers, and comparisons against full information methods that are grounded in discipline-specific examples are lacking. In this study, I delineate this method through a step-by-step analysis of a sequential mediation case study involving internet addiction. I provide example R code using the lavaan package and data based on a hypothetical study of addiction. I examine the differences between the full and limited information estimators within the example data and subsequently probe the extent to which these differences are indicative of a consistent divergence between the estimators using a simulation study. The results suggest that the limited information estimator outperforms the conventional full information maximum likelihood estimator in small to moderate sample sizes in terms of bias, efficiency, and power.

Revisiting mediational models of sport commitment with female gymnasts

The purpose of this study was to test alternative models of sport commitment with a youth sport sample. Competitive female gymnasts (N = 792; Levels 4–10), ages 8–19 years (M = 11.68, SD = 2.33), completed measures designed to assess the determinants of commitment. Data were analysed via path analysis models in the lavaan package in R. Three separate models were fitted: (a) direct effects model, (b) a mediational model testing the indirect effects of the predictors via enjoyment, and (c) direct and indirect effects of the predictors on sport commitment. Of the models tested, the direct and indirect effects model yielded the best fit of the data (RMSE = .03 90% CI [.000, .057], TLI = .989, CFI = .997, NFI = .989; 67% of the variance in commitment explained). The model revealed that enjoyment, involvement opportunities, investments, and attractive alternatives had a direct effect on commitment. With regard to the indirect effects of the determinants on commitment via enjoyment, attractive alternatives, involvement opportunities, investments, costs, parent and best friend social constraints, and coach and teammate social support had direct effects on enjoyment, which predicted the level of gymnastics commitment. Additionally, some differences emerged in the salient predictors of commitment for high versus low level competitors. The role of enjoyment within commitment is complex depending on competitive level, and future research should consider alternative models when examining the role of social influence on sport commitment.

The Effectiveness of Health Care Information Technologies: Evaluation of Trust, Security Beliefs, and Privacy as Determinants of Health Care Outcomes.

BackgroundThe diffusion of health information technologies (HITs) within the health care sector continues to grow. However, there is no theory explaining how success of HITs influences patient care outcomes. With the increase in data breaches, HITs’ success now hinges on the effectiveness of data protection solutions. Still, empirical research has only addressed privacy concerns, with little regard for other factors of information assurance.ObjectiveThe objective of this study was to study the effectiveness of HITs using the DeLone and McLean Information Systems Success Model (DMISSM). We examined the role of information assurance constructs (ie, the role of information security beliefs, privacy concerns, and trust in health information) as measures of HIT effectiveness. We also investigated the relationships between information assurance and three aspects of system success: attitude toward health information exchange (HIE), patient access to health records, and perceived patient care quality.MethodsUsing structural equation modeling, we analyzed the data from a sample of 3677 cancer patients from a public dataset. We used R software (R Project for Statistical Computing) and the Lavaan package to test the hypothesized relationships.ResultsOur extension of the DMISSM to health care was supported. We found that increased privacy concerns reduce the frequency of patient access to health records use, positive attitudes toward HIE, and perceptions of patient care quality. Also, belief in the effectiveness of information security increases the frequency of patient access to health records and positive attitude toward HIE. Trust in health information had a positive association with attitudes toward HIE and perceived patient care quality. Trust in health information had no direct effect on patient access to health records; however, it had an indirect relationship through privacy concerns.ConclusionsTrust in health information and belief in the effectiveness of information security safeguards increases perceptions of patient care quality. Privacy concerns reduce patients’ frequency of accessing health records, patients’ positive attitudes toward HIE exchange, and overall perceived patient care quality. Health care organizations are encouraged to implement security safeguards to increase trust, the frequency of health record use, and reduce privacy concerns, consequently increasing patient care quality.

Emotional dysregulation is a primary symptom in adult Attention-Deficit/Hyperactivity Disorder (ADHD)

BackgroundClinical observations suggest that adults have more diverse deficits than children with Attention Deficit/Hyperactivity Disorder (ADHD). These seem to entail difficulties with emotionality, self-concept and emotion regulation in particular, along with the cardinal symptoms of inattention, impulsivity, and hyperactivity for adult patients. Here, we probed a model that explicitly distinguished positive and negative affect, problems with self-concept and emotion regulation skills as distinct but correlating factors with the symptom domains of inattention, hyperactivity, and impulsivity. MethodsParticipants were 213 newly diagnosed adults with ADHD (62.9% male, mean age 33.5 years). Symptoms were assessed via self-report on the Conners’ Adult ADHD Rating Scales, a modified version of the Positive and Negative Affect Scale and the Emotion Regulation Skill Questionnaire. A confirmatory factor analysis with the R package lavaan, using a robust Maximum Likelihood estimator (MLR) for non-normal data, was conducted to test our new non-hierarchical 7-factor model. ResultsAll calculated model-fit statistics revealed good model-fit (χ2/df ratio = 2.03, robust RMSEA = .07). The SRMR in our model reached .089, indicating an acceptable model fit. Factor loadings on the postulated factors had salient loadings ≥ .31 except for one item on the hyperactivity factor. Latent factor associations were especially salient between emotional dysregulation and problems with self-concept, and also partially with impulsivity/emotional lability. LimitationsThe three models of ADHD and emotion regulation as suggested by Shaw et al. (2014) could not be disentangled in this study, though the overall results support the model with shared neurocognitive deficits. Further, we did not separately analyze ADHD with or without comorbid disorders. As our sample of clinical cases with ADHD is highly comorbid (47.9%), other disorders than ADHD might account for the emotion regulation deficits, though a sensitivity analysis revealed no such differences. ConclusionsOur model adequately characterizes the relations between and among clinically and therapeutically relevant symptoms in adult ADHD, thus potentially informing future therapeutic interventions by targeting the successful and flexible use of adaptive emotion regulation skills.

The Communities That Care (CTC) Family Attachment Scale: Measurement Invariance Across Family Structures

Familial protective factors are an integral part of prevention approaches aimed at problematic behaviour in adolescents. However, there is scarce evidence on the role of familial protective factors in families deviating from the two-parent family configuration. For evaluating targeted (preventive) interventions, a reliable and valid measurement of familial protective factors is crucial. We investigated the factor structure of the Communities That Care (CTC) Family Attachment Scale and tested its measurement invariance in different family structures. Adolescents (n = 2.459, grades 6–11) from Lower Saxony, Germany filled in the German version of the CTC Youth Survey. Our analyses focused on the CTC Family Attachment Scale measuring the adolescent’s attachment to the mother and the father with six items. We evaluated the postulated unidimensional structure of the scale by confirmatory factor analysis (CFA) and tested the measurement invariance using multigroup factor analyses across different family structures (two-parent family/single-parent family). We used SPSS V.23 and the R packages lavaan and semTools. The two-factor solution for the CTC Family Attachment Scale with one factor representing attachment to the mother and one indicating attachment to the father had an adequate model fit in the total sample (χ2(5) = 29.938; p < .001; CFI = .996; TLI = .988; RMSEA = .050, SRMR = .019). This two-factor solution of the CTC Family Attachment Scale showed strong measurement invariance regarding adolescents living in a two-parent family vs. those living with a single parent. The two-factor CTC Family Attachment Scale appears to be a suitable measure to assess family attachment in both two-parent and single-parent families with German adolescents.

MerDeriv: Derivative Computations for Linear Mixed Effects Models with Application to Robust Standard Errors

While robust standard errors and related facilities are available in R for many types of statistical models, the facilities are notably lacking for models estimated via lme4. This is because the necessary statistical output, including the Hessian and casewise gradient of random effect parameters, is not immediately available from lme4 and is not trivial to obtain. In this article, we supply and describe two new functions to obtain this output from Gaussian mixed models: estfun.lmerMod() and vcov.full.lmerMod(). We discuss the theoretical results implemented in the code, focusing on calculation of robust standard errors via package sandwich. We also use the Sleepstudy data to illustrate the code and compare it to a benchmark from package lavaan.

The mediating effect of transparency in the relationship between corporate social responsibility and corporate reputation

Purpose – This study attempts to shed light on the relationship between the implementation of corporate social responsibility (CSR) actions and the creation of corporate reputation. We go further and wonder which is the role of transparency – a step beyond disclosure – in that relationship. Design/methodology/approach – A structural equations model using the statistical package lavaan in R is applied to 22 Spanish listed companies during the period 2002-2015. Findings – The proposed model shows that transparency mediates the path between corporate social responsibility and corporate reputation. Originality/value – This paper highlights the importance of transparency beyond disclosure since information aims to meet certain criteria such as relevance, understandability and timeliness. A new measurement for transparency analyzed its mediating effect in the relationship between corporate social responsibility and corporate reputation.

Intergroup Reconciliation between Flemings and Walloons: The Predictive Value of Cognitive Style, Authoritarian Ideology, and Intergroup Emotions.

Testifying to the gap in fundamental research on positive intergroup outcomes, we investigated reconciliation attitudes in a non-violent intergroup context (i.e., the linguistic conflict in Belgium). By incorporating both important predictors of negative outgroup attitudes (i.e., individual differences in rigid cognitive styles and authoritarian ideologies), and important predictors of reconciliation (i.e., intergroup emotions), we aimed to contribute to a more comprehensive theoretical framework for the analysis of intergroup relations. We recruited one Flemish (N = 310) and one Walloon (N = 365) undergraduate students sample to test the proposed model. Structural equation analyses with maximum likelihood estimation were conducted using the Lavaan package. In both samples, similar patterns were found. More in particular, the need for cognitive closure appeared to be the basic predictor of right-wing attitudes (i.e., right-wing authoritarianism and social dominance orientation) and essentialist thinking, which were then associated with less outgroup empathy and trust, and more outgroup anger. Furthermore, outgroup trust and empathy were positively related to reconciliation. Interestingly, some differences between the Flemish and Walloon sample were found, such as the direct effects of need for closure and social dominance orientation in the first sample, and the non-significant effects of essentialism in the latter sample. Considering the ongoing public and political debate about the linguistic conflict in Belgium, these findings shed a new light on how individual differences relate to specific outgroup emotions, and how these are associated with important intergroup outcomes in the face of intergroup conflict.

Endangering one’s health to improve performance?

Background: Companies are increasingly applying both goal- and performance-oriented leadership practices. For employees, such indirect control practices make higher self-regulatory demands: They become responsible for their work outcomes and have to bear the consequences of failure just like the self-employed. The current study focuses on the concept of “self-endangering work behaviors” as representing a possible negative effect of indirect control and a possible mediator between work demands and negative outcomes. Method: An online survey was conducted with 607 employees, who reported to work in an indirect control setting. It assessed extension of working hours, intensification of working hours, sickness presenteeism, and faking as possible self-endangering work behaviors together with exhaustion as a subjective well-being measure. The lavaan package was used to test the mediation hypothesis with a structural equation model. Results: Results supported the assumption that self-endangering work behaviors might partly explain the association between work demands and exhaustion. A mediation effect was found for extension of working hours, intensification of working hours, and for faking. However, sickness presenteeism delivered no statistically significant mediation effect in the association between work demands and exhaustion. Discussion: As a mechanism for coping with high work demands, the new concept of self-endangering work behaviors offers one possible explanation for the negative association between high work demands and both subjective well-being and health. The concept needs to be addressed in occupational health prevention initiatives. Such interventions should balance the negative and positive effects of indirect control and take self-endangering work behavior into account.

A General Procedure for Testing Inequality Constrained Hypotheses in SEM

Abstract. Researchers in the social and behavioral sciences often have clear expectations about the order and/or the sign of the parameters in their statistical model. For example, a researcher might expect that regression coefficient β1 is larger than regression coefficients β2 and β3. To test such a constrained hypothesis special methods have been developed. However, the existing methods for structural equation models (SEM) are complex, computationally demanding, and a software routine is lacking. Therefore, in this paper we describe a general procedure for testing order/inequality constrained hypotheses in SEM using the R package lavaan. We use the likelihood ratio (LR) statistic to test constrained hypotheses and the resulting plug-in p value is computed by either parametric or Bollen-Stine bootstrapping. Since the obtained plug-in p value can be biased, a double bootstrap approach is available. The procedure is illustrated by a real-life example about the psychosocial functioning in patients with facial burn wounds.

Abstract WP218: Brain Reserve: A Protective Mechanism for Stroke Outcome

Introduction: Stroke is a leading cause of disability worldwide. Mechanisms of post-stroke recovery are complex, and conventional outcome prediction models are limited. “Brain reserve” (BR) has been proposed as a construct to model the brain’s capacity to withstand insults. BR has been shown to co-vary with white matter hyperintensity volume (WMHv) using structural equation modeling (SEM), a technique to test models with latent variables. Hypothesis: We hypothesize that BR is a protective mechanism that improves functional outcome after acute ischemic stroke (AIS). Methods: We define an effective brain reserve (eBR), the remaining brain reserve after other influences have been accounted for. Using SEM, we characterize eBR through intra-cranial volume (ICV), age and systolic blood pressure (SBP). Our model incorporates known relationships between age, SBP, WMHv, acute infarct volume on diffusion-weighted imaging (DWIv) and 90-day functional post-stroke outcome (modified Rankin Scale; mRS), as shown in Figure 1. Path analysis was performed (R; package lavaan) to estimate the relations within the model in a dataset of 451 AIS patients. No priors were used for the path coefficients. Results: The estimated model coefficients (Figure 1) show that eBR is negatively associated with age and SBP, but positively with ICV, while association between age, SBP and WMHv are positive. Outcome is positively associated with WMHv and DWIv and negatively with eBR, suggesting that eBR acts as a protective mechanism. All path coefficients are statistically significant, except for WMHv and mRS. Conclusion: Our analysis shows that eBR is negatively associated with post-stroke outcome (the higher eBR, the lower mRS), suggesting that eBR acts as a protective mechanism. Additionally we reproduced known relationships between WMHv, SBP, age, DWIv and mRS.

Examining Bidirectional Pathways Between Exposure to Political Violence and Adolescent Adjustment in Northern Ireland

Research on social ecologies of political violence has been largely confined to cross-sectional tests of the impact of political violence on child adjustment, limiting perspectives on more nuanced causal pathways, including tests of reciprocal relations between exposure to political violence and child adjustment. Based on a four-wave longitudinal study, this research breaks new ground in assessing bidirectional relations between exposure to political violence in the form of experience with sectarian antisocial behavior and adolescents’ adjustment problems. The study included 999 mother–adolescent dyads selected from working-class neighborhoods in Belfast ranked in the bottom quartile in terms of social deprivation in Northern Ireland, with approximately 35–40 families recruited to participate from each neighborhood. Across the four annual waves of data, adolescents (52% female) were 12.18 (SD = 1.82), 13.24 (SD = 1.83), 13.62 (SD = 1.99), and 14.66 (SD = 1.96) years old. Cross-lagged path models were tested through R package lavaan with full information maximum likelihood. Reflecting a reciprocal pathway, adjustment problems related to higher reports of experience with sectarian antisocial behavior 1 year later. Boys’ experience with sectarian antisocial behavior related to greater adjustment problems 1 year later, but this reciprocal path did hold for the girls. These findings offer promising directions toward better modeling of dynamic relations between exposure to political violence and adolescent adjustment over time.

Pairwise Likelihood Ratio Tests and Model Selection Criteria for Structural Equation Models with Ordinal Variables.

Correlated multivariate ordinal data can be analysed with structural equation models. Parameter estimation has been tackled in the literature using limited-information methods including three-stage least squares and pseudo-likelihood estimation methods such as pairwise maximum likelihood estimation. In this paper, two likelihood ratio test statistics and their asymptotic distributions are derived for testing overall goodness-of-fit and nested models, respectively, under the estimation framework of pairwise maximum likelihood estimation. Simulation results show a satisfactory performance of type I error and power for the proposed test statistics and also suggest that the performance of the proposed test statistics is similar to that of the test statistics derived under the three-stage diagonally weighted and unweighted least squares. Furthermore, the corresponding, under the pairwise framework, model selection criteria, AIC and BIC, show satisfactory results in selecting the right model in our simulation examples. The derivation of the likelihood ratio test statistics and model selection criteria under the pairwise framework together with pairwise estimation provide a flexible framework for fitting and testing structural equation models for ordinal as well as for other types of data. The test statistics derived and the model selection criteria are used on data on 'trust in the police' selected from the 2010 European Social Survey. The proposed test statistics and the model selection criteria have been implemented in the R package lavaan.

Mapping the soils of an Argentine Pampas region using structural equation modelling

Current digital soil mapping (DSM) methods have limitations. For instance, it is difficult to predict a large number of soil properties simultaneously, while preserving the relationships between them. Another problem is that prevalent prediction models use pedological knowledge in a very crude way only. To tackle these problems, we investigated the use of structural equation modelling (SEM). SEM has its roots in the social sciences and is recently also being used in other scientific disciplines, such as ecology. SEM integrates empirical information with mechanistic knowledge by deriving the model equations from known causal relationships, while estimating the model parameters using the available data. It distinguishes between endogenous and exogenous variables, where, in our application, the first are soil properties and the latter are external soil forming factors (i.e. climate, relief, organisms). We introduce SEM theory and present a case study in which we applied SEM to a 22,900km2 region in the Argentinian Pampas to map seven key soil properties. In this case study, we started with identifying the main soil forming processes in the study area and assigned for each process the main soil properties affected. Based on this analysis we defined a conceptual soil-landscape model, which was subsequently converted to a SEM graphical model. Finally, we derived the SEM equations and implemented these in the statistical software R using the latent variable analysis (lavaan) package. The model was calibrated using a soil dataset of 320 soil profile data and 12 environmental covariate layers. The outcomes of the model were maps of seven soil properties and a SEM graph that shows the strength of the relationships. Although the accuracy of the maps, based on cross-validation and independent validation, was poor, this paper demonstrates that SEM can be used to explicitly include pedological knowledge in prediction of soil properties and modelling of their interrelationships. It bridges the gap between empirical and mechanistic methods for soil-landscape modelling, and is a tool that can help produce pedologically sound soil maps.

Familial risk and protective factors in alcohol intoxicated adolescents: psychometric evaluation of the family domain of the Communities That Care Youth Survey (CTC) and a new short version of the Childhood Trauma Questionnaire (CTQ).

BackgroundAlcohol intoxicated adolescents (AIA) in emergency department are an important target group for prevention and valid information on their familial risk and protective factors (RPF) is crucial for implementing customized family-based counseling in hospitals. We therefore, examined the psychometric characteristics of scales which assess familial RPF.MethodsWe used seven family scales from the Communities That Care Youth Survey Instrument (CTC-F7); four assess risk factors: family conflicts, poor family management, parental attitudes favorable towards drug use/antisocial behavior; three assess protective factors: family attachment, opportunities and rewards for prosocial involvement. To assess physical and emotional abuse and emotional neglect, we created a new scale composed of six items from the Childhood Trauma Questionnaire (CTQ-6). We tested these eight scales on 342 AIA aged 13-17. Based on the classical test theory we calculated descriptive item and scale statistics and internal consistency. We assessed construct validity by confirmatory factor analysis with Maximum Likelihood (ML) estimation in a sample with imputed missing values (EM-Algorithm). To check robustness, we repeated the analyses with complete cases, with multiple imputed data, and with methods suitable for categorical data. We used SPSS 21, AMOS 21 and R (randomForrest and lavaan package).ResultsThree of seven CTC-F scales showed poor psychometric properties in the descriptive analysis. A ML-confirmatory model with five latent factors fitted the remaining CTC-F scales best (CTC-F5). The latent structure of the CTQ-6 is characterized by three first-order factors (physical abuse, emotional abuse, emotional neglect) and one second-order factor. The global goodness-of-fit indices for the CTC-F5 and the CTQ-6 demonstrated acceptable fit (for both models: TLI and CFI>0.97, RMSEA<0.05). The confirmatory evaluation based on complete cases (n=266), on multiple imputed data, and with alternative estimation methods produces global and local model-fit indices that are comparable to those from the main analysis. The final subscales CTC-F5 and CTQ-6 show acceptable to good internal consistency (α>0.7).ConclusionsThe final CTC-F5 and the newly developed CTQ-6 demonstrate acceptable to good psychometric properties for the AIA sample. The CTC-F5 and the CTQ-6 facilitate a psychometrically sound assessment of familial RPF for this vulnerable and important target group for prevention.

Heterogeneity in barriers regarding the motivation, the opportunity and the ability to choose low-calorie snack foods and beverages: associations with real-life choices.

Employing Rothschild's Motivation-Opportunity-Ability framework, the present study examines the extent to which heterogeneity in barriers regarding the motivation, the perceived opportunity and the perceived ability to choose low-calorie over high-calorie snacks is associated with the proportion of low-calorie snack choices in real life. Furthermore, the study investigates which dominant barrier profiles can be discerned. Data were obtained from a survey about participants' motivation, opportunity and ability to choose low-calorie over high-calorie snacks and an FFQ that measured habitual consumption of snack foods and beverages. Data were analysed using R packages lavaan and NbClust, and IBM SPSS Statistics. A representative sample (n 1318) of the Dutch population based on gender (686 women), age and education level. For both snack foods and beverages, motivation to choose low-calorie over high-calorie snacks was associated strongest with proportions of low-calorie choices. The perceived ability and perceived opportunity were also associated with proportions of low-calorie choices, albeit to a lesser extent. Furthermore, three dominant profiles of barriers were identified: the no-barrier profile, the lack-of-opportunity profile and the lack-of-motivation profile. These profiles differed significantly on proportions of low-calorie snack choices, daily meal consumption and sociodemographic characteristics. Heterogeneity in barriers regarding the motivation, the perceived opportunity and the perceived ability to choose low-calorie over high-calorie snacks is associated with the proportion of low-calorie snack choices in real life. By identifying and appreciating heterogeneity in barriers, the present study provides further incentives for the tailoring of intervention strategies.