Sexual harassment and patterns of symptoms and functional abilities in a psychiatric sample of adolescents.

PURPOSE: To investigate how commonly adolescent psychiatric outpatients with symptoms of depression and anxiety report having been subjected to sexual harassment, and to explore how symptoms and functional abilities differ between adolescent psychiatric outpatients with symptoms of depression and anxiety who do report and those who do not report having been subjected to sexual harassment. METHODS: Swedish adolescent psychiatric outpatients with symptoms of depression or anxiety (n = 324; 66 boys and 258 girls, aged 12-19 years, M = 15.6, SD = 1.7) answered the PROMIS paediatric measures. Logistic regression analyses were performed to assess differences between the respondents classified as 'Sexually harassed' and 'Not sexually harassed' based on these self-report questionnaires. RESULTS: About 60% of the adolescents reported having been subjected to sexual harassment, and reported higher levels of suicidal ideation, disturbed sleep, fatigue, anxiety, depression, anger, and pain interference, as well as lower functional ability in terms of school problems, alcohol consumption, and poor family relationships. Logistic regression analyses showed that the strongest associations were with suicidal ideation, disturbed sleep, anger, and alcohol consumption. CONCLUSIONS: About 60% of the adolescents in the studied psychiatric cohort reported having been subjected to sexual harassment. Reported experiences were high in all three subtypes, with the most reports on having been subjected to verbal harassment. Clinicians should ask about experiences of sexual harassment and give information about the consequences of sexual violence and treatment options. Alcohol consumption should be addressed and tested for. Structured assessment of suicidality should always be done.

Efficiency Analysis of Item Response Theory Kernel Equating for Mixed-Format Tests.

This study aims to evaluate the performance of Item Response Theory (IRT) kernel equating in the context of mixed-format tests by comparing it to IRT observed score equating and kernel equating with log-linear presmoothing. Comparisons were made through both simulations and real data applications, under both equivalent groups (EG) and non-equivalent groups with anchor test (NEAT) sampling designs. To prevent bias towards IRT methods, data were simulated with and without the use of IRT models. The results suggest that the difference between IRT kernel equating and IRT observed score equating is minimal, both in terms of the equated scores and their standard errors. The application of IRT models for presmoothing yielded smaller standard error of equating than the log-linear presmoothing approach. When test data were generated using IRT models, IRT-based methods proved less biased than log-linear kernel equating. However, when data were simulated without IRT models, log-linear kernel equating showed less bias. Overall, IRT kernel equating shows great promise when equating mixed-format tests.

Nonparametric item response models: a comparison on recovering true scores / Modelos de resposta ao item não-paramétricos: comparando a recuperação de escores verdadeiros / Modelos de respuesta al item no-paramétricos: comparando la recuperación de puntuaciones verdaderas

Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the present study is to compare the performance of these procedures in recovering simulated true scores, using sum scores as benchmarks. The secondary aim is to compare their performances in terms of practical equivalence with real data. Overall, the results show that, apart from the DC-IRT, which is the model that performs the worse, all the other models give results quite similar to those when sum scores are used. These results are followed by a discussion with practical implications and recommendations for future studies.(AU)

Procedimentos não paramétricos são usados para adicionar flexibilidade aos modelos. Três modelos não paramétricos de resposta ao item foram propostos, mas não comparados diretamente: o Kernel smoothing (KS-IRT); a Curva Davidiana (DC-IRT); e o modelo semiparamétrico Rasch Bayesiano (SP-Rasch). O objetivo principal do presente estudo é comparar o desempenho desses procedimentos na recuperação de escores verdadeiros simulados, utilizando escores de soma como benchmarks. O objetivo secundário é comparar seus desempenhos em termos de equivalência prática com dados reais. De forma geral, os resultados mostram que, além do DC-IRT, que é o modelo que apresenta o pior desempenho, todos os outros modelos apresentam resultados bastante semelhantes aos de quando se usam somatórios. Esses resultados são seguidos de uma discussão com implicações práticas e recomendações para estudos futuros.(AU)

Se utilizan procedimientos no paramétricos para agregar flexibilidad a los modelos. Se propusieron tres modelos de respuesta al ítem no paramétricos, pero no se compararon directamente: Kernel smoothing (KS-IRT); la curva davidiana (DC-IRT); y el modelo bayesiano de Rasch semiparamétrico (SP-Rasch). El objetivo principal del presente estudio es comparar el desempeño de estos procedimientos en la recuperación de puntajes verdaderos simulados, utilizando puntajes de suma como puntos de referencia. El objetivo secundario es comparar su desempeño en términos de equivalencia práctica con datos reales. En general, los resultados muestran que, a excepción de DC-IRT, que es el modelo con peor desempeño, todos los otros modelos presentan resultados bastante similares a los obtenidos cuando se utilizan sumatorios. Estos resultados son seguidos por una discusión con implicaciones prácticas y recomendaciones para estudios futuros.(AU)

Evaluating Equating Transformations in IRT Observed-Score and Kernel Equating Methods.

Test equating is a statistical procedure to ensure that scores from different test forms can be used interchangeably. There are several methodologies available to perform equating, some of which are based on the Classical Test Theory (CTT) framework and others are based on the Item Response Theory (IRT) framework. This article compares equating transformations originated from three different frameworks, namely IRT Observed-Score Equating (IRTOSE), Kernel Equating (KE), and IRT Kernel Equating (IRTKE). The comparisons were made under different data-generating scenarios, which include the development of a novel data-generation procedure that allows the simulation of test data without relying on IRT parameters while still providing control over some test score properties such as distribution skewness and item difficulty. Our results suggest that IRT methods tend to provide better results than KE even when the data are not generated from IRT processes. KE might be able to provide satisfactory results if a proper pre-smoothing solution can be found, while also being much faster than IRT methods. For daily applications, we recommend observing the sensibility of the results to the equating method, minding the importance of good model fit and meeting the assumptions of the framework.

Psychometric validity of the Montgomery and Åsberg Depression Rating Scale for Youths (MADRS-Y).

BACKGROUND: Because of all the serious consequences of major depressive disorder (MDD), it is important to screen for MDD in adolescents. The aim of this study was to test the psychometric properties of the newly developed self-report depression scale MADRS-Y for adolescents in a normative Swedish sample. METHODS: The study included 620 adolescents in the age range of 12-20 years old. The normative sample was randomly split into two equal parts, to perform principal component analysis (PCA) on sample one and confirmatory factor analysis (CFA) on sample two. We investigated the psychometrics. RESULTS: The result from the PCA suggested that all 12 potential items should be used, and the items loaded on the same construct of depression. The CFA supported the one-factor structure with good fit indices. Measurement invariance was confirmed, allowing interpretation regardless of gender or age differences. Reliability was good, α .89, for both samples separately. Test-retest reliability was good to excellent (intraclass correlation coefficients = .87 and .91). Evidence of convergent and discriminant validity was shown. CONCLUSIONS: The results in the current study suggest that the MADRS-Y is a brief, reliable, and valid self-report questionnaire of depressive symptoms for adolescents in the general population.

Situational optimization function analysis: An ideal performance analysis inspired on Lewin's equation.

This study presents the situational optimization function analysis (SOFA) and has three aims. First, to develop a Bayesian implementation of SOFA. Second, to compare this implementation with three other maximum likelihood-based models in their accuracy to estimate true scores. The third aim is to show how joint modeling can be used for validity research. A simulation study was used to examine the second aim, while an empirical example was used to illustrate the third aim. The simulation study used three data generating processes, with varying degrees of deviation from linear models and with different sample sizes. Results of the simulation study showed that the Bayesian implementation supersedes the other models. In the empirical example, data collected from 66 participants using an iterated prisoner dilemma and a scale measuring cooperation-competition attitudes were used. Results showed that joint modeling is the best fitting model, also increasing the correlation between the true scores of both measures (deviations from the iterated prisoner dilemma and the scale). Finally, implications, limitations and future studies are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How Important is the Choice of Bandwidth in Kernel Equating?

Kernel equating uses kernel smoothing techniques to continuize the discrete score distributions when equating test scores from an assessment test. The degree of smoothness of the continuous approximations is determined by the bandwidth. Four bandwidth selection methods are currently available for kernel equating, but no thorough comparison has been made between these methods. The overall aim is to compare these four methods together with two additional methods based on cross-validation in a simulation study. Both equivalent and non-equivalent group designs are used and the number of test takers, test length, and score distributions are all varied. The results show that sample size and test length are important factors for equating accuracy and precision. However, all bandwidth selection methods perform similarly with regards to the mean squared error and the differences in terms of equated scores are small, suggesting that the choice of bandwidth is not critical. The different bandwidth selection methods are also illustrated using real testing data from a college admissions test. Practical implications of the results from the simulation study and the empirical study are discussed.

Psychometrics of three Swedish physical pediatric item banks from the Patient-Reported Outcomes Measurement Information System (PROMIS)®: pain interference, fatigue, and physical activity.

BACKGROUND: The Patient-Reported Outcomes Measurement Information System (PROMIS®) aims to provide self-reported item banks for several dimensions of physical, mental and social health. Here we investigate the psychometric properties of the Swedish pediatric versions of the Physical Health item banks for pain interference, fatigue and physical activity which can be used in school health care and other clinical pediatric settings. Physical health has been shown to be more important for teenagers' well-being than ever because of the link to several somatic and mental conditions. The item banks are not yet available in Sweden. METHODS: 12- to 19-year-old participants (n = 681) were recruited in public school settings, and at a child- and psychiatric outpatient clinic. Three one-factor models using CFA were performed to evaluate scale dimensionality. We analyzed monotonicity and local independence. The items were calibrated by fitting the graded response model. Differential Item analyses (DIF) for age, gender and language were calculated. RESULTS: As part of the three one-factor models, we found support that each item bank measures a unidimensional construct. No monotonicity or local dependence were found. We found that 11 items had significant lack of fit in the item response theory (IRT) analyses. The result also showed DIF for age (seven items) and language (nine items). However, the differences on item fits and effect sizes of McFadden were negligible. After considering the analytic results, graphical illustration, item content and clinical relevance we decided to keep all items in the item banks. CONCLUSIONS: We translated and validated the U.S. PROMIS item banks pain interference, fatigue and physical activity into Swedish by applying CFA, IRT and DIF analyses. The results suggest adequacy of the translations in terms of their psychometrics. The questionnaires can be used in school health and other pediatric care. Future studies can be to use Computerized Adaptive Testing (CAT), which provide fewer but reliable items to the test person compared to classical testing.

Heterogeneity in Association Between Cognitive Function and Gait Speed Among Older Adults: An Integrative Data Analysis Study.

BACKGROUND: Increasing evidence shows that cognition and gait speed are associated and are important measures of health among older adults. However, previous studies have used different methods to assess these 2 outcomes and lack sufficient sample size to examine heterogeneity among subgroups. This study examined how the relationship between global cognitive function and gait speed are influenced by age, gender, and race utilizing an integrated data analysis approach. METHOD: Data on cognition (Montreal Cognitive Assessment [MoCA], Mini-Mental Status Examination [MMSE], and Modified Mini-Mental State Examination [3MSE]) and gait speed (range: 4-400 m) were acquired and harmonized from 25 research studies (n = 2802) of adults aged 50+ from the Wake Forest Older American Independence Center. Multilevel regression models examined the relationship between predicted values of global cognitive function (MoCA) and gait speed (4-m walk), including heterogeneity by age, race, and gender. RESULTS: Global cognitive function and gait speed exhibited a consistent positive relationship among whites with increasing age, while this was less consistent for African Americans. That is, there was a low correlation between global cognitive function and gait speed among African Americans aged 50-59, a positive correlation in their 60s and 70s, then a negative correlation thereafter. CONCLUSION: Global cognition and gait speed exhibited a curvilinear U-shaped relationship among whites; however, the association becomes inverse in African Americans. More research is needed to understand this racial divergence and could aid in identifying interventions to maintain cognitive and gait abilities across subgroups.

Linking With External Covariates: Examining Accuracy by Anchor Type, Test Length, Ability Difference, and Sample Size.

Research has recently demonstrated the use of multiple anchor tests and external covariates to supplement or substitute for common anchor items when linking and equating with nonequivalent groups. This study examines the conditions under which external covariates improve linking and equating accuracy, with internal and external anchor tests of varying lengths and groups of differing abilities. Pseudo forms of a state science test were equated within a resampling study where sample size ranged from 1,000 to 10,000 examinees and anchor tests ranged in length from eight to 20 items, with reading and math scores included as covariates. Frequency estimation linking with an anchor test and external covariate was found to produce the most accurate results under the majority of conditions studied. Practical applications of linking with anchor tests and covariates are discussed.

Optimal Scores: An Alternative to Parametric Item Response Theory and Sum Scores.

The aim of this paper is to discuss nonparametric item response theory scores in terms of optimal scores as an alternative to parametric item response theory scores and sum scores. Optimal scores take advantage of the interaction between performance and item impact that is evident in most testing data. The theoretical arguments in favor of optimal scoring are supplemented with the results from simulation experiments, and the analysis of test data suggests that sum-scored tests would need to be longer than an optimally scored test in order to attain the same level of accuracy. Because optimal scoring is built on a nonparametric procedure, it also offers a flexible alternative for estimating item characteristic curves that can fit items that do not show good fit to item response theory models.

Item Response Theory Observed-Score Kernel Equating.

Item response theory (IRT) observed-score kernel equating is introduced for the non-equivalent groups with anchor test equating design using either chain equating or post-stratification equating. The equating function is treated in a multivariate setting and the asymptotic covariance matrices of IRT observed-score kernel equating functions are derived. Equating is conducted using the two-parameter and three-parameter logistic models with simulated data and data from a standardized achievement test. The results show that IRT observed-score kernel equating offers small standard errors and low equating bias under most settings considered.

Alternative Linear Item Response Theory Observed-Score Equating Methods.

Item response theory observed-score equating (IRTOSE) is widely used in many testing programs. The aim of this study was to empirically examine three alternative linear IRTOSE methods compared with the traditional IRTOSE method and to discuss these methods in light of previously suggested alternatives. This contribution is both conceptual, by exploring three alternative methods that fit into the current observed-score equating framework, and empirical by comparing the methods through simulations and with real data. The results show that the local linear (kernel) IRTOSE methods yield low bias and low values on loss measures. However, using only a linear IRTOSE method results in excessive bias and cannot be recommended because of the ease with which IRTOSE with full distributions can be performed. An example using real data showed considerable differences in the equated scores with the alternative methods as well as in comparison with the traditional IRTOSE method. Practical considerations are given in the concluding remarks.

A Note on the Poisson's Binomial Distribution in Item Response Theory.

The Poisson's binomial (PB) is the probability distribution of the number of successes in independent but not necessarily identically distributed binary trials. The independent non-identically distributed case emerges naturally in the field of item response theory, where answers to a set of binary items are conditionally independent given the level of ability, but with different probabilities of success. In many applications, the number of successes represents the score obtained by individuals, and the compound binomial (CB) distribution has been used to obtain score probabilities. It is shown here that the PB and the CB distributions lead to equivalent probabilities. Furthermore, one of the proposed algorithms to calculate the PB probabilities coincides exactly with the well-known Lord and Wingersky (LW) algorithm for CBs. Surprisingly, we could not find any reference in the psychometric literature pointing to this equivalence. In a simulation study, different methods to calculate the PB distribution are compared with the LW algorithm. Providing an exact alternative to the traditional LW approximation for obtaining score distributions is a contribution to the field.

Kernel Equating Under the Non-Equivalent Groups With Covariates Design.

When equating two tests, the traditional approach is to use common test takers and/or common items. Here, the idea is to use variables correlated with the test scores (e.g., school grades and other test scores) as a substitute for common items in a non-equivalent groups with covariates (NEC) design. This is performed in the framework of kernel equating and with an extension of the method developed for post-stratification equating in the non-equivalent groups with anchor test design. Real data from a college admissions test were used to illustrate the use of the design. The equated scores from the NEC design were compared with equated scores from the equivalent group (EG) design, that is, equating with no covariates as well as with equated scores when a constructed anchor test was used. The results indicate that the NEC design can produce lower standard errors compared with an EG design. When covariates were used together with an anchor test, the smallest standard errors were obtained over a large range of test scores. The results obtained, that an EG design equating can be improved by adjusting for differences in test score distributions caused by differences in the distribution of covariates, are useful in practice because not all standardized tests have anchor tests.

Gender differences in the Swedish driving-license test.

INTRODUCTION: Male drivers between 18-24 years are involved in many more motor-vehicle accidents than female drivers in Sweden. Is there also a gender difference in test performance in the Swedish driving-license tests? Is it a real difference or do any of the items display differential item functioning (DIF) with respect to gender or educational background? METHOD: Two random samples of test-takers' performance on the Swedish theory driving-license test were examined with descriptive and inference statistics. RESULTS: Female test-takers performed better than male test-takers on the theory test, which is a real difference since no items displayed DIF with respect to gender. There was no gender difference in the practical test. The gender difference in the theory test could not be fully explained by differences in educational background. CONCLUSIONS: Although everyone who passes the driving-license test has fulfilled the goals stated in the curriculum, it is possible that the gender differences in the theory test are consistent over time, and therefore might be one factor that explains why male drivers are over-represented in traffic accidents. IMPACT ON INDUSTRY: Gender differences appear persistent over time. Therefore, by improving male test takers' result on the test may lead to positive effects on the male test takers future driving career.

The Swedish driver licensure examination: exploration of a two-stage model.

INTRODUCTION: Sweden, together with several countries in the world, has no compulsory educational requirement prior to the drivers license examination. Having a valid license examination (i.e., a knowledge test and a driving test) is therefore important in order to ensure competent drivers. METHOD: The aim of this paper is to explore the possibility of a two stage testing approach for the Swedish licensure examination. In order to explore the relationship between the knowledge test and the road test, a descriptive and a logistic regression approach were carried out. RESULTS: The result indicates that how the driving candidates perform on the road test depends on their performance on the knowledge test. Therefore, the Swedish drivers licensing examination is suitable for a two-stage testing model.