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Item response tree (IRTree) models form a family of psychometric models that allow researchers to control for multiple response processes, such as different sorts of response styles, in the measurement of latent traits. While IRTree models can capture quantitative individual differences in both the latent traits of interest and the use of response categories, they maintain the basic assumption that the nature and weighting of latent response processes are homogeneous across the entire population of respondents. In the present research, we therefore propose a novel approach for detecting heterogeneity in the parameters of IRTree models across subgroups that engage in different response behavior. The approach uses score‐based tests to reveal violations of parameter heterogeneity along extraneous person covariates, and it can be employed as a model‐based partitioning algorithm to identify sources of differences in the strength of trait‐based responding or other response processes. Simulation studies demonstrate generally accurate Type I error rates and sufficient power for metric, ordinal, and categorical person covariates and for different types of test statistics, with the potential to differentiate between different types of parameter heterogeneity. An empirical application illustrates the use of score‐based partitioning in the analysis of latent response processes with real data. [ABSTRACT FROM AUTHOR]

Recent research at the intersection of psychology and economics sheds light on the influence of hope on economic decisions. A body of that work concentrates on the economics of hope in developing country contexts. We identify two notable gaps: lack of attention to the measurement of hope as a latent psychological construct, and consequently, the lack of description and characterization of hope as a variable that can be measured and targeted. This study addresses these gaps by assessing the effectiveness of a novel hope measurement instrument, utilizing a large primary dataset collected in rural Tanzania. We estimate hope distributions across over 5,000 individuals and conditionally within subgroups defined by gender, region, recent shock, age, food security, income source, and religiosity. A positively-worded question about faith had the greatest information content among all questions, negatively worded questions were more effective in distinguishing people with relatively high hope. Employing generalized structural equation models, we observe significant variations in hope across sub-groups. Correcting for measurement distortions, we find significant heterogeneity in hope distributions across individuals and subgroups. The presence of an income-earning household member and religiosity yield the most pronounced shifts in hope distributions. [ABSTRACT FROM AUTHOR]

Recent years have seen a growing interest in the development of person‐fit statistics for tests with polytomous items. Some of the most popular person‐fit statistics for such tests belong to the class of standardized person‐fit statistics, T, that is assumed to have a standard normal null distribution. However, this distribution only holds when (a) the true ability parameter is known and (b) an infinite number of items are available. In practice, both conditions are violated, and the quality of person‐fit results is expected to deteriorate. In this paper, we propose three new corrections for T that simultaneously account for the use of an estimated ability parameter and the use of a finite number of items. The three new corrections are direct extensions of those that were developed by Gorney et al. (Psychometrika, 2024, https://doi.org/10.1007/s11336‐024‐09960‐x) for tests with only dichotomous items. Our simulation study reveals that the three new corrections tend to outperform not only the original statistic T but also an existing correction for T proposed by Sinharay (Psychometrika, 2016, 81, 992). Therefore, the new corrections appear to be promising tools for assessing person fit in tests with polytomous items. [ABSTRACT FROM AUTHOR]

Computerized adaptive testing (CAT) is a widely embraced approach for delivering personalized educational assessments, tailoring each test to the real‐time performance of individual examinees. Despite its potential advantages, CAT�s application in small‐scale assessments has been limited due to the complexities associated with calibrating the item bank using sparse response data and small sample sizes. This study addresses these challenges by developing a two‐step item bank calibration strategy that leverages the 1‐bit matrix completion method in conjunction with two distinct incomplete pretesting designs. We introduce two novel 1‐bit matrix completion‐based imputation methods specifically designed to tackle the issues associated with item calibration in the presence of sparse response data and limited sample sizes. To demonstrate the effectiveness of these approaches, we conduct a comparative assessment against several established item parameter estimation methods capable of handling missing data. This evaluation is carried out through two sets of simulation studies, each featuring different pretesting designs, item bank structures, and sample sizes. Furthermore, we illustrate the practical application of the methods investigated, using empirical data collected from small‐scale assessments. [ABSTRACT FROM AUTHOR]

Several new models based on item response theory have recently been suggested to analyse intensive longitudinal data. One of these new models is the time‐varying dynamic partial credit model (TV‐DPCM; Castro‐Alvarez et al., Multivariate Behavioral Research, 2023, 1), which is a combination of the partial credit model and the time‐varying autoregressive model. The model allows the study of the psychometric properties of the items and the modelling of nonlinear trends at the latent state level. However, there is a severe lack of tools to assess the fit of the TV‐DPCM. In this paper, we propose and develop several test statistics and discrepancy measures based on the posterior predictive model checking (PPMC) method (PPMC; Rubin, The Annals of Statistics, 1984, 12, 1151) to assess the fit of the TV‐DPCM. Simulated and empirical data are used to study the performance of and illustrate the effectiveness of the PPMC method. [ABSTRACT FROM AUTHOR]

To understand why some individuals who develop alcohol use disorders (AUD) first begin to drink heavily, a number of scales have been developed that index aspects of alcohol craving and restraint from drinking. We developed a new measure called the Alcohol Consumption Questionnaire (ACQ), based in part on items modified from scales used to index binge eating, because there are data to suggest that binge eating and binge drinking may share common antecedents. We present an initial validity study using data from a sample of Mexican Americans. Data were from 699 Mexican American young adults in San Diego County, CA. A subsample (n = 60) had short-term test-retest data. Factor analysis and reliability assessment guided item reduction. Item response theory (IRT) analyses quantified item severity and identified questions with differential item functioning (DIF). Logistic regression assessed associations of mean scale scores with AUD, adjusting for key demographics, alcohol expectancies and subjective response to alcohol. We also examined associations with a protective genetic variant downstream from the alcohol dehydrogenase 7 (ADH7) gene. The scale was reduced from 20 to 14 questions, which can be summarized by a single overall score (Cronbach's alpha = 0.896) or by two sub-scores (Consumption: 12 items, Cronbach's alpha = 0.896; Enjoyment: 2 items, Cronbach's alpha = 0.780). Test-retest reliability was very high (0.80–0.98) in this sample. The overall ACQ score and each subdomain score were strongly associated with AUD (ORs = 5.95 mild; 11.41 moderate; 48.56 severe) and family history of AUD. Respondents with the protective genetic variant had significantly lower overall ACQ scores (p < 0.001). The ACQ is a novel measure of alcohol consumption with strong relationships with both the AUD phenotype and ADH7 gene variants in a sample of Mexican American young adults. [Display omitted] • The Alcohol Consumption Questionnaire (ACQ) was developed from binge eating measures. • We present initial validity data from a sample of Mexican Americans (N = 699). • ACQ has strong relationships with AUD phenotype and ADH7 variants in this sample. [ABSTRACT FROM AUTHOR]

Background Objective Methods Results Conclusions Progressive supranuclear palsy (PSP) is a rare and fatal neurodegenerative disorder for which there are currently no disease‐modifying treatments. Recent trials of potential therapies had durations of 12 months, which may be insufficient because of nonrandom missingness due to death. Longer durations, incorporating PSP Rating Scale and survival, can reduce the potential for type II error. Selecting efficacy measures more sensitive to disease modification may facilitate identification of treatment effect.The objective of this study was to evaluate the simulated phase 3 PSP trial assessing the effect of disease‐modifying intervention on a novel combined primary endpoint comprising function (PSP Rating Scale) and survival, the Combined Assessment of Function and Survival (CAFS), and to determine operating characteristics of the CAFS.To simulate PSP progression in the trial population, we developed models of PSP Rating Scale and survival using data from published clinical studies. These models were used to define operating characteristics of the CAFS for use in a phase 3 trial.The sample size determined (N = 384; 1:1 randomization) would provide >80% power to detect significant treatment effects on the CAFS compared with placebo. The CAFS provides good operating characteristics and increased power to detect moderate treatment effects on the PSP Rating Scale. We propose a trial design allowing potential detection of treatment effects at a preplanned interim analysis after participants complete 12 months of treatment, with assessment of effects of treatment (≤24 months) on survival.Use of the CAFS could provide a comprehensive and robust estimate of the clinical benefit of future therapies. © 2024 UCB. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item Response Theory (IRT)’s item parameter invariance assumption, which facilitates applications of IRT in various psychometric tasks such as computerized adaptive testing (CAT). Ignoring IPE might lead to issues such as inaccurate ability estimation in CAT. This article extends research on IPE by proposing and evaluating approaches to controlling position effects under an item‐level computerized adaptive test via a simulation study. The results show that adjusting IPE via a pretesting design (approach 3) or a pool design (approach 4) results in better ability estimation accuracy compared to no adjustment (baseline approach) and item‐level adjustment (approach 2). Practical implications of each approach as well as future research directions are discussed as well. [ABSTRACT FROM AUTHOR]

Recently Variational Autoencoders (VAEs) have been proposed as a method to estimate high dimensional Item Response Theory (IRT) models on large datasets. Although these improve the efficiency of estimation drastically compared to traditional methods, they have no natural way to deal with missing values. In this paper, we adapt three existing methods from the VAE literature to the IRT setting and propose one new method. We compare the performance of the different VAE‐based methods to each other and to marginal maximum likelihood estimation for increasing levels of missing data in a simulation study for both three‐ and ten‐dimensional IRT models. Additionally, we demonstrate the use of the VAE‐based models on an existing algebra test dataset. Results confirm that VAE‐based methods are a time‐efficient alternative to marginal maximum likelihood, but that a larger number of importance‐weighted samples are needed when the proportion of missing values is large. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethodResultsConclusionThis study aimed to validate the Cultural Humility and Enactment Scale - Supervision (CHES-S).The sample included a total of 201 post-masters counselors who were currently engaged in clinical supervision across 11 U.S. states, who were recruited from the state licensing board email lists. Analyses included confirmatory factor analysis (CFA) and item response theory (IRT) analysis based on a multidimensional adaptation of the partial credit model.We found evidence to support the three-factor structure of the CHES-S. We also found that the CHES-S can be used to distinguish participants scores from low to high CH, and that the thresholds of each item could capture participants responses in the expected order.Evidencing reliability and validity with a sample of post-master’s practitioners engaged in supervision for licensure, the CHES-S can be effectively utilized as a tool to monitor supervisory process and outcome in clinical supervision. [ABSTRACT FROM AUTHOR]

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample size. These efforts unveil new questions about how to integrate data across distinct sources and instruments. The goal of this study was to link scores across common auditory verbal learning tasks (AVLTs). This international secondary analysis aggregated multisite raw data for AVLTs across 53 studies totaling 10,505 individuals. Using the ComBat-GAM algorithm, we isolated and removed the component of memory scores associated with site effects while preserving instrumental effects. After adjustment, a continuous item response theory model used multiple memory items of varying difficulty to estimate each individual's latent verbal learning ability on a single scale. Equivalent raw scores across AVLTs were then found by linking individuals through the ability scale. Harmonization reduced total cross-site score variance by 37% while preserving meaningful memory effects. Age had the largest impact on scores overall (− 11.4%), while race/ethnicity variable was not significant (p > 0.05). The resulting tools were validated on dually administered tests. The conversion tool is available online so researchers and clinicians can convert memory scores across instruments. This work demonstrates that global harmonization initiatives can address reproducibility challenges across the behavioral sciences. [ABSTRACT FROM AUTHOR]

Background Objective Methods Results Conclusions The MDS‐UPDRS Parts IB and II are self‐reported items providing a direct patient voice to the experiences of PD.To determine the most sensitive combination of MDS‐UPDRS Parts IB and II items that accurately predicted the clinically relevant target of dopaminergic therapy initiation.Utilizing a longitudinal cohort of de novo non‐treated PD patients, we applied item response theory (IRT) and survival analysis to assess the relationship between baseline patient‐reported symptoms and the later initiation of dopaminergic therapy. The 20 MDS‐UPDRS Parts IB and II items were analyzed for their relationship to PD severity (discrimination) and the amount of information they provided in this determination (information). These parameters were used to develop models of predictive accuracy for initiation of dopaminergic therapy.A six‐item version showed a significantly higher C‐index as compared to the full 20 item model (P = 0.001). This shortened version of the MDS‐UPDRS contained only Part II items and provided a predictive accuracy for initiation of dopaminergic therapy better than the total combined scale score or any other combination.A six‐item “Baseline Outcome Voice” version of patient‐reported MDS‐UPDRS items significantly increases the sensitivity of predicting the key future clinical outcome of starting dopaminergic treatment in early PD. This study also demonstrates how IRT modeling can provide information useful to refining existing measures to identify the most sensitive combination of items honoring the voice of the patient in determining key clinically pertinent decisions. Further research is needed to validate these findings in underrepresented populations. [ABSTRACT FROM AUTHOR]

This study presents a generalized version of the residual differential item functioning (RDIF) detection framework in item response theory, named GRDIF, to analyze differential item functioning (DIF) in multiple groups. The GRDIF framework retains the advantages of the original RDIF framework, such as computational efficiency and ease of implementation. The performance of GRDIF was assessed through a simulation study and compared with existing DIF detection methods, including the generalized Mantel‐Haenszel, Lasso‐DIF, and alignment methods. Results showed that the GRDIF framework demonstrated well‐controlled Type I error rates close to the nominal level of .05 and satisfactory power in detecting uniform, nonuniform, and mixed DIF across different simulated conditions. Each of the three GRDIF statistics, GRDIFR$GRDI{{F}_R}$, GRDIFS$GRDI{{F}_S}$, and GRDIFRS$GRDI{{F}_{RS}}$, effectively detected the specific type of DIF for which it was designed, with GRDIFRS$GRDI{{F}_{RS}}$ exhibiting the most robust performance across all types of DIF. The GRDIF framework outperformed other DIF detection methods under various conditions, suggesting its potential for practical applications, particularly in large‐scale assessments involving multiple groups. Additionally, an empirical study demonstrated the efficacy and utility of the GRDIF framework in conducting DIF analysis with a high‐stakes assessment data set. [ABSTRACT FROM AUTHOR]

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample size. These efforts unveil new questions about how to integrate data across distinct sources and instruments. The goal of this study was to link scores across common auditory verbal learning tasks (AVLTs). This international secondary analysis aggregated multisite raw data for AVLTs across 53 studies totaling 10,505 individuals. Using the ComBat-GAM algorithm, we isolated and removed the component of memory scores associated with site effects while preserving instrumental effects. After adjustment, a continuous item response theory model used multiple memory items of varying difficulty to estimate each individual's latent verbal learning ability on a single scale. Equivalent raw scores across AVLTs were then found by linking individuals through the ability scale. Harmonization reduced total cross-site score variance by 37% while preserving meaningful memory effects. Age had the largest impact on scores overall (− 11.4%), while race/ethnicity variable was not significant (p > 0.05). The resulting tools were validated on dually administered tests. The conversion tool is available online so researchers and clinicians can convert memory scores across instruments. This work demonstrates that global harmonization initiatives can address reproducibility challenges across the behavioral sciences. [ABSTRACT FROM AUTHOR]

Bayesian analysis relies heavily on the Markov chain Monte Carlo (MCMC) algorithm to obtain random samples from posterior distributions. In this study, we compare the performance of MCMC stopping rules and provide a guideline for determining the termination point of the MCMC algorithm in latent variable models. In simulation studies, we examine the performance of four different MCMC stopping rules: potential scale reduction factor (PSRF), fixed‐width stopping rule, Geweke's diagnostic, and effective sample size. Specifically, we evaluate these stopping rules in the context of the DINA model and the bifactor item response theory model, two commonly used latent variable models in educational and psychological measurement. Our simulation study findings suggest that single‐chain approaches outperform multiple‐chain approaches in terms of item parameter accuracy. However, when it comes to person parameter estimates, the effect of stopping rules diminishes. We caution against relying solely on the univariate PSRF, which is the most popular method, as it may terminate the algorithm prematurely and produce biased item parameter estimates if the cut‐off value is not chosen carefully. Our research offers guidance to practitioners on choosing suitable stopping rules to improve the precision of the MCMC algorithm in models involving latent variables. [ABSTRACT FROM AUTHOR]

Normal ogive (NO) models have contributed substantially to the advancement of item response theory (IRT) and have become popular educational and psychological measurement models. However, estimating NO models remains computationally challenging. The purpose of this paper is to propose an efficient and reliable computational method for fitting NO models. Specifically, we introduce a novel and unified expectation‐maximization (EM) algorithm for estimating NO models, including two‐parameter, three‐parameter, and four‐parameter NO models. A key improvement in our EM algorithm lies in augmenting the NO model to be a complete data model within the exponential family, thereby substantially streamlining the implementation of the EM iteration and avoiding the numerical optimization computation in the M‐step. Additionally, we propose a two‐step expectation procedure for implementing the E‐step, which reduces the dimensionality of the integration and effectively enables numerical integration. Moreover, we develop a computing procedure for estimating the standard errors (SEs) of the estimated parameters. Simulation results demonstrate the superior performance of our algorithm in terms of its recovery accuracy, robustness, and computational efficiency. To further validate our methods, we apply them to real data from the Programme for International Student Assessment (PISA). The results affirm the reliability of the parameter estimates obtained using our method. [ABSTRACT FROM AUTHOR]

Background: Robust tools to assess self-reported adolescent functional health literacy are lacking. In Portugal, the only available tool is the Newest Vital Sign for Portuguese adolescents (NVS-PTeen), though presenting modest validity and reliability properties. A new instrument–the Functional Literacy Questionnaire (FLiQ)–was developed, inspired by the NVS-PTeen, but following the European Regulation for food labeling and targeting a balanced assessment of numeracy and verbal comprehension skills. This study aimed to evaluate several psychometric properties of the FLiQ when administered to Portuguese adolescents. Methods: We conducted a longitudinal observational study with three phases: (1) Delphi panel with health literacy experts; (2) self-administration of FLiQ and NVS-PTeen to adolescents in 7th to 9th grades; and (3) re-administration of FLiQ four weeks after baseline, to the same group of participants. Results: FLiQ's content validity was excellent, with an Average-Content Validity Index of.95. Overall, 372 adolescents (50.3% girls) aged between 12–17 years (median age: 13) participated in the study. Of these, 150 completed the test-retest assessment. Internal consistency was good (Kuder-Richardson Fornula-20 =.70), as well as test-retest reliability (Intraclass Coefficient Correlation =.82). FLiQ total score was weakly correlated with the school year (rho =.174), and moderately with Portuguese (rho =.348) and Mathematics grades (rho =.333). Factor analysis indicated a two-dimension structure, reflecting numeracy and verbal comprehension skills. Item response theory analysis revealed differences in difficulty and discrimination capacity among items, all with adequate fit values. Conclusion: FLiQ is a valid and reliable tool. It can be used to monitor functional health literacy levels in Portuguese adolescents. [ABSTRACT FROM AUTHOR]

Instruments used to assess the mental well-being of young athletes in Brazil are scarce. Therefore, the present study aimed to translate, cross-culturally adapt for young athletes, and gather evidence of validity for the Sport Mental Health—Short Form (S-MHC) for use in Brazilian Portuguese. The research was conducted in five stages: translation, synthesis, back-translation, expert review, and validation of the psychometric properties. For validation, 246 young athletes of both genders (88 females, 35.8%), aged between 12 and 18 years (14.5 ± 1.9 years), were recruited. Psychometric methods were employed to confirm and validate the translated and adapted versions of the S-MHC for young athletes, including internal consistency using Cronbach's alpha and McDonald's omega, composite reliability, Item Characteristic Curve (ICC) using Item Response Theory (IRT), and Confirmatory Factor Analysis (CFA). Two structures were tested, with Model 1 loading the 14 items of the translated version of the S-MHC into a single latent factor and Model 2 loading the items into three factors related to emotional, social, and psychological sport well-being. Both models showed good validity, consistency, and reliability measures and can be used to investigate the sport well-being of young athletes. It was concluded that the translated version of the S-MHC in Brazilian Portuguese can be used to assess the sport well-being of young athletes in Brazil. Model 2 structure is recommended to observe the different nuances of emotional, social, and psychological well-being. [ABSTRACT FROM AUTHOR]

Figural matrices tests are frequently used to measure fluid intelligence. The HeiQ—an operation-oriented figural matrices test—was developed to tackle limitations of previous matrices tests, mainly the possibility of excluding distractors based on superficial features instead of actively solving the items. However, allowing for a total administration time of 60 min for the assessment of one construct is not feasible in many study designs. Thus, the goal of this study was to develop three short forms of the existing HeiQ. Two parallel 20-item short forms (the HeiQ-S A and HeiQ-S B) that are comparable in content as well as on a psychometric basis and a 6-item short form (the HeiQ-XS) were generated. All tests showed good internal consistency (Cronbach's Alpha ranging from α = 0.82 to α = 0.86) and good criterion-related validity (correlations with high school grade (Abitur) ranging from r = −0.34 to r = −0.38); construct validity (correlations with the global intelligence scores of the Intelligence Structure Test 2000R were between r = 0.58 and r = 0.71). Further, all test versions showed to be Rasch-scalable, implying a uniform underlying ability. Thus, we conclude that all three newly developed short versions are valid tools for assessing fluid intelligence. [ABSTRACT FROM AUTHOR]

Linear logistic test models (LLTMs), leveraging item response theory and linear regression, offer an elegant method for learning about item characteristics in complex content areas. This study used LLTMs to model single-best-answer, multiple-choice-question response data from two medical subspecialty certification examinations in multiple years and found that word count, proportion of complex words, number of options (3- vs. 4-option), whether including an image, nature of the question task (identifying risks, diagnostic test, management), and whether including application context significantly predicted item difficulty in one or both of the Critical Care Medicine and Pediatric Anesthesiology exams. The differences in the item characteristics that were significant predictors of item difficulty and their associated coefficient estimates between the two exams suggest possible domain differences. This study highlights the possibilities and challenges of using LLTMs to identify item characteristics for complex assessments. The results may help inform or expedite item writing and reviewing processes. [ABSTRACT FROM AUTHOR]

We examined the longitudinal psychometric properties of the Perceived Stress Scale – 4 items version (PSS‐4) using item response theory with a sample of 361 mental health counsellors. Participants completed the PSS‐4 at three timepoints at six‐month intervals in a one‐year period. There were 290 participants who (80.3%) identified as female, 51 (14.1%) identified as male, eight (2.2%) identified as gender variant/non‐conforming, seven (1.9%) wrote in their own gender identity (e.g., genderqueer, gender expansive), three (0.8%) identified as Transgender male, and two (0.6%) did not respond to the item. The racial and ethnic backgrounds were as follows: White (87.3%), Multiracial (5.5%), Latino or Hispanic or Spanish (2.8%), Black or African American (1.4%), Asian (0.8%), Middle Eastern (0.8%), and five did not respond to the item (1.4%). We found unidimensionality evidence of the PSS‐4 across all three timepoints and response categories were monotonically ordered. We also found that across all timepoints, the average person location was lower than the average item location, suggesting that the PSS‐4 may not be well‐targeted for this sample of mental health counsellors. We observed no significant interactions between timepoints, hours worked per week, and length of employment. Implications of the findings, including a discussion of the utility of the PSS‐4 as a global measure of stress and with mental health counsellors. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the psychometric properties of the Utrecht Work Engagement Scale-9 (UWES-9) using both Classical Test Theory (CTT) and Item Response Theory (IRT) approaches, with a sample of practicing school counselors (N = 356). The results of analyzing the UWES-9 included information on item-level statistics, internal consistency, structural validity, and concurrent validity. IRT findings based on the Graded Response Model (GRM) indicated the usefulness of the UWES-9 in measuring school counselors' work engagement. Significance Statement: This study provides information on the usefulness of the UWES-9 as a measure of school counselors' work engagement. Given the increasing academic attention to school counselors' work-related attitudes and job performances, having a better understanding of the construct of work engagement and its measure can contribute to further relevant studies. [ABSTRACT FROM AUTHOR]

Peggy McIntosh's (White privilege and male privilege: A personal account of coming to see correspondences through work in women's studies, Working Paper 189, Wellesley Center for Research on Women, 1988) list of 50 racial privileges, which purportedly benefit persons of white skin colour, has had enormous impact on social science research and educational curriculum and pedagogy. Surprisingly, to date, no attempt has been made to empirically explore the validity and reliability of her list of racial privileges. To address this issue, we conducted a psychometric analysis on McIntosh's list of racial privileges with 204 adult Australian university students. Using a combination of factor analyses and Rasch modelling on McIntosh's list of racial privileges we identified a 27‐item multidimensional scale consisting of three well‐functioning and reliable subscales (i.e. a 15‐item Racial Representation, a six‐item Social Interaction and a six‐item Culture and Politics subscale). Moreover, the derived multi‐dimensional white privilege instrument was found to have good criterion validity in that persons' experiences of racism significantly predicted white privilege (i.e. the more racism experienced the less white privilege experienced and vice versa). Finally, analysis of variance comparisons indicated that persons with white skin colour had significantly more white privilege than persons with black skin colour and Asians, while Asians had more white privilege than persons with black skin colour. Overall, this study presents evidence of a psychometrically valid and reliable 27‐item multi‐dimensional white privilege instrument and lends empirical support to the theoretical underpinnings of McIntosh's contentions. [ABSTRACT FROM AUTHOR]

As Korea is rapidly becoming an aging society, people are increasingly interested in the life satisfaction of the older adults. Therefore, the need for a tool that can precisely measure the life satisfaction of the older adults in Korea is also increasing. In this study, SWLS, which has been widely used to measure life satisfaction, was applied to Korean older adults. This study analyzed the life satisfaction of the older adults using item response theory that can supplement the limitations of existing research methods. Data from 3543 older adults who responded to the 2021 Korean Happiness Survey. As a result of the analysis, it was found that the goodness of fit of item 5 exceeded the standard value, and item 4 functioned differentially between the young-old and old-old. Based on the results of this study, it presented an empirical basis for the application of SWLS to the older adults. [ABSTRACT FROM AUTHOR]

To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about choosing the middle category or extreme categories are largely determined by midpoint RS (MRS) and extreme RS (ERS). One limitation of traditional IRTree models is the assumption that all respondents utilize the same set of RS in their response strategies, whereas it can be assumed that the nature and the strength of RS effects can differ between individuals. To address this limitation, we propose a mixture multidimensional IRTree (MM-IRTree) model that detects heterogeneity in response strategies. The MM-IRTree model comprises four latent classes of respondents, each associated with a different set of RS traits in addition to the substantive trait. More specifically, the class-specific response strategies involve (1) only ERS in the "ERS only" class, (2) only MRS in the "MRS only" class, (3) both ERS and MRS in the "2RS" class, and (4) neither ERS nor MRS in the "0RS" class. In a simulation study, we showed that the MM-IRTree model performed well in recovering model parameters and class memberships, whereas the traditional IRTree approach showed poor performance if the population includes a mixture of response strategies. In an application to empirical data, the MM-IRTree model revealed distinct classes with noticeable class sizes, suggesting that respondents indeed utilize different response strategies. [ABSTRACT FROM AUTHOR]

Many universities use diagnostic tests to assess incoming students' preparedness for mathematics courses. Diagnostic test results can help students to identify topics where they need more practice and give lecturers a summary of strengths and weaknesses in their class. We demonstrate a process that can be used to make improvements to a mathematics diagnostic test, so that it provides better information about students' abilities. To identify questions that could be improved, our process uses item response theory to analyse student data. We provide an accessible introduction to the key ideas of item response theory, and we describe how we applied the process of improvement of diagnostic tests at two universities. Our method provides a model for others wishing to make improvements to mathematics diagnostic tests. [ABSTRACT FROM AUTHOR]

Background: The birthweight of a newborn is critical to their health, development, and well‐being. Previous studies that used maternal characteristics to predict birthweight did not employ a harmonised scale to assess the risk of low birthweight (LBW). Objective: The goal of this study was to develop a new instrument that uses items on a uniform scale to assess the risk of an LBW in a pregnant woman. Methods: Item response theory was employed to evaluate a similar existing scale, and some weaknesses were identified. Results: Based on the observed weaknesses of the existing scale, a new uniform scale was developed, which is a 3‐point Likert scale consisting of seven items. Conclusion: The scale, termed birthweight questionnaire, is a valuable tool for collecting data that could assist in assessing the risk of an LBW at every stage of pregnancy. [ABSTRACT FROM AUTHOR]

Many Indo-European languages refer to meaning in life with three groups of terms (e.g. vocation/significance/Bezeichnung, meaning/purpose/Meinung, sense/Sinn). These etymologies seem to refer to traditional, functionalistic and critical-intuitive/phenomenological approaches to life. This study aimed to develop and validate a psychometric instrument measuring traditional, functionalistic and critical-intuitive/phenomenological approaches to meaning in life. Eight experts developed consensus definitions and generated items for the Meaning Approach Scale (MAS) in a Delphi-study. A Three-Step-Test-Interview with eight participants, Confirmatory Factor Analysis and Item Response Theory in an informal survey of 108 participants, reduced the initial 56-item MAS-56 to MAS-45, with sub-scales for traditional, functionalistic and critical-intuitive/phenomenological approaches. The MAS-45 was validated in a survey of 1281 participants in 49 countries, with reliability, factor structure and correlations with other questionnaires as hypothesized. Traditional and functionalistic approaches correlated with negative affects, low quality-of-life and life satisfaction, whereas critical-intuitive/phenomenological approaches correlated with positive affects, quality-of-life and life satisfaction. Functionalistic approaches were reported more frequently in Western countries and traditional and critical-intuitive approaches in less Western countries. This study indicates the MAS-45 to be valid and reliable, differentiating three approaches to life. Individuals benefit most from a critical-intuitive/phenomenological approach, which therapists may consider exploring with clients. [ABSTRACT FROM AUTHOR]

Schizotypy involves schizophrenia-like traits and symptoms, with the Wisconsin Schizotypy Scales (WSS) being frequently used in previous research. There is some evidence that schizophrenia-spectrum symptom levels, including when using the WSS, might vary both by gender and by race and ethnicity. However, previous research has rarely examined to what extent the WSS show gender and racial bias. Further, this has not been previously examined for the Cognitive Slippage Scale, a measure of disorganized schizotypy. In this study, we examined biases for a subset of items from the WSS in a large sample of undergraduate students (n = 21,829). Using item response theory to test for levels of differential item functioning (DIF), we found some evidence of problematic DIF for all scales, including for negative, positive, and disorganized schizotypy scales. There was evidence of problematic DIF especially by gender and for Black and Multiracial participants. Overall, the current results suggest that gender and/or racial bias on these scales should be an important consideration in using these scales and our results could have implications for assessment of schizophrenia-spectrum symptoms. [ABSTRACT FROM AUTHOR]

The Kessler psychological distress scale is a useful tool for identifying possible psychological problems and has been widely used in research and health services. Unfortunately, its application in various populations has not always been psychometrically supported. For this reason, the present study investigated the psychometric properties of its Spanish version in adolescents, verifying its factorial structure, measurement invariance by gender, internal consistency and the discrimination and difficulty parameters of its items according to the Item Response Theory (IRT). A sample of 5132 Ecuadorian adolescents was evaluated. The sample is equally distributed between male and female participants (50%) and basic and higher education (51% the former). All participants were between 11 and 20 years old. The results show that a 9-item version with correlated intercepts presents the best fit. In addition, it is invariant by gender at a strict level and has adequate internal consistency. IRT analyses indicated that all the items, except for item eight, present adequate discrimination and difficulty. Based on these results, we conclude that the 9-item version of the Psychological Distress Scale is the most appropriate for this population. [ABSTRACT FROM AUTHOR]

The tendency for individuals to mind wander is often measured using experience sampling methods in which probe questions embedded within computerized cognitive tasks attempt to catch episodes of off-task thought at random intervals during task performance. However, mind-wandering probe questions and response options are often chosen ad hoc and vary between studies with extant little guidance as to the psychometric consequences of these methodological decisions. In the present study, we examined the psychometric properties of several common approaches for assessing mind wandering using methods from item response theory (IRT). IRT latent modeling demonstrated that measurement information was generally distributed across the range of trait estimates according to when probes were presented in time. Probes presented earlier in time provided more information about individuals with greater tendency to mind wandering than probes presented later. Furthermore, mind-wandering ratings made on a continuous scale or using multiple categorical rating options provided more information about individuals' latent mind-wandering tendency – across a broader range of the trait continuum – than ratings dichotomized into on-task and off-task categories. In addition, IRT provided evidence that reports of "task-related thoughts" contribute to the task-focused dimension of the construct continuum, providing justification for studies conceptualizing these responses as a kind of task-related focus. Together, we hope these findings will help guide researchers hoping to maximize the measurement precision of their mind wandering assessment procedures. [ABSTRACT FROM AUTHOR]

The assessment of creativity as an individual difference has historically focused on divergent thinking, which is increasingly viewed as involving the associative processes that are also understood to be a key component of creative potential. Research on associative processes has proliferated in many sub-fields, often using Compound Remote Associates (CRA) tasks with an open response format and relatively small participant samples. In the present work, we introduce a new format that is more amenable to large-scale data collection in survey designs, and present evidence for the reliability and validity of CRA measures in general using multiple large samples. Study 1 uses a large, representative dataset (N = 1,323,480) to demonstrate strong unidimensionality and internal consistency (α =.97; ωt =.87), as well as links to individual differences in temperament, cognitive ability, occupation, and job characteristics. Study 2 uses an undergraduate sample (N = 685) to validate the use of a multiple-choice format relative to the traditional approach. Study 3 uses a crowdsourced sample (N = 357) to demonstrate high test–retest reliability of the items (r =.74). Finally, Study 4 uses a sample that overlaps with Study 1 (N = 1,502,922) to provide item response theory (IRT) parameters for a large set of high-quality CRA items that use a multiple-choice response mode, thus facilitating their use in future research on creativity, insight, and related topics. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach known as the cross estimation network (CEN) for fitting the datasets obtained from psychological or educational tests and estimating the parameters of item response theory (IRT) models. The CEN is comprised of two subnetworks: the person network (PN) and the item network (IN). The PN processes the response pattern of individual respondent and generates an estimate of the underlying ability, while the IN takes in the response pattern of individual item and outputs the estimates of the item parameters. Four simulation studies and an empirical study were comprehensively and rigorously conducted to investigate the performance of CEN on parameter estimation of the two-parameter logistic model under various testing scenarios. Results showed that CEN effectively fit the training data and produced accurate estimates of both person and item parameters. The trained PN and IN adhered to AI principles and acted as intelligent agents, delivering commendable evaluations for even unseen patterns of new respondents and items. [ABSTRACT FROM AUTHOR]

Questionnaires are ever present in survey research. In this study, we examined whether an indirect indicator of general cognitive ability could be developed based on response patterns in questionnaires. We drew on two established phenomena characterizing connections between cognitive ability and people's performance on basic cognitive tasks, and examined whether they apply to questionnaires responses. (1) The worst performance rule (WPR) states that people's worst performance on multiple sequential tasks is more indicative of their cognitive ability than their average or best performance. (2) The task complexity hypothesis (TCH) suggests that relationships between cognitive ability and performance increase with task complexity. We conceptualized items of a questionnaire as a series of cognitively demanding tasks. A graded response model was used to estimate respondents' performance for each item based on the difference between the observed and model-predicted response ("response error" scores). Analyzing data from 102 items (21 questionnaires) collected from a large-scale nationally representative sample of people aged 50+ years, we found robust associations of cognitive ability with a person's largest but not with their smallest response error scores (supporting the WPR), and stronger associations of cognitive ability with response errors for more complex than for less complex questions (supporting the TCH). Results replicated across two independent samples and six assessment waves. A latent variable of response errors estimated for the most complex items correlated.50 with a latent cognitive ability factor, suggesting that response patterns can be utilized to extract a rough indicator of general cognitive ability in survey research. [ABSTRACT FROM AUTHOR]

Introduction: This study evaluated the psychometric properties of the Subjective Memory Complaints Questionnaire (SMCQ) in a non-Hispanic White (NHW) and Mexican American (MA) sample from Texas in the USA. Methods: Data were obtained from the Health and Aging Brain Study – Health Disparities (HABS-HD; N = 1,691, age = 66.5 ± 8.7, education = 12.4 ± 4.8, 60.6% female, 33.2% MA Spanish speaking). Unidimensionality of the SMCQ was evaluated with confirmatory factor analysis. Differential item functioning (DIF) of the SMCQ was assessed across age, sex, education, and ethnicity/language using item response theory/logistic ordinal regression. Associations of the SMCQ in relation to cognitive status, Alzheimer’s disease (AD) blood-based biomarkers, and psychological distress were examined. Results: The SMCQ showed excellent fit in a single-factor model (CFI = 0.97, TLI = 0.97, RMSEA [95% CI] = 0.05 [0.04, 0.05], SRMR = 0.07). Significant item-level DIF was detected by education level and ethnicity/language, but not by age or sex; when detected, DIF was not salient (i.e., adverse). The SMCQ was associated with greater psychological distress, worse Clinical Dementia Rating scores, and greater disease burden as measured by total tau and neurofilament light. Conclusions: Practically negligible item-level bias was identified across education and ethnicity/language. Detected DIF can be described as benign, indicating that some items manifested differently between groups but had minimal impact on measurement properties. These results demonstrate that the SMCQ performs appropriately across demographic variables. Our findings also provide support for the associations of SMCQ scores with self-reported mood, cognitive status, and AD blood-based biomarkers. [ABSTRACT FROM AUTHOR]

AbstractThe aim of the study was to understand the role of transdiagnostic vulnerabilities, namely intolerance of uncertainty (IU) and neuroticism, in initiating safety-seeking preparatory behaviors under the threat of an imminent war. A sample of N = 1460 adults were recruited via convenience sampling in March 2022, after the outbreak of the Russia-Ukraine war from nearing countries. Due to the lack of suitable measures in the literature to cover the phenomenon, first a short inventory for measuring these safety actions, the War-Related Preparatory Safety-Seeking Inventory (W-PRESS) was elaborated and validated via Item Response Theory. Next, a transdiagnostic cognitive behavioral framework was proposed for the determinants of W-PRESS: IU (IUS-12), fear of war (FoW), neuroticism (Big-Five), and anxiety (DASS). The SEM results confirmed the proposed model. A strong positive relationship was found of both IU and neuroticism with anxiety, FoW, and W-PRESS. Higher neuroticism was associated with higher W-PRESS, fully mediated by IU. IU also partially mediated the relationship of neuroticism with anxiety and FoW, respectively. In contextual uncertainty evoked by the outbreak of the nearby war, dispositional vulnerabilities, like IU and neuroticism may enhance the individual level of crisis management in the sense of preparing for and dealing with emerging risks. [ABSTRACT FROM AUTHOR]

Recent studies suggest that cognateness boosts bilingual lexical acquisition. This study proposes an account in which language co‐activation accelerates accumulation of word‐learning instances across languages. This account predicts a larger cognate facilitation for words in the lower‐exposure language than in the higher‐exposure language, as the former receive co‐activation from their translations more frequently. Bayesian Item Response Theory was used to model acquisition trajectories for 604 Catalan‐Spanish translations from a dataset of 366 12–32 month‐old bilinguals (M = 22.23 months, 175 female, mainly White, collected 2020–2022). Results show a larger cognate facilitation for words in the lower‐exposure language (d = .276), than for words in the higher‐exposure language (d = .022), supporting a language exposure‐moderated account for the effect of cognateness on lexical acquisition. [ABSTRACT FROM AUTHOR]

AbstractAsymptotic goodness-of-fit methods in contingency table analysis can struggle with sparse data, especially in multi-way tables where it can be infeasible to meet sample size requirements for a robust application of distributional assumptions. However, algebraic statistics provides exact alternatives to these classical asymptotic methods that remain viable even with sparse data. We apply these methods to a context in psychometrics and education research that leads naturally to multi-way contingency tables: the analysis of differential item functioning (DIF). We explain concretely how to apply the exact methods of algebraic statistics to DIF analysis using the R package algstat, and we compare their performance to that of classical asymptotic methods. [ABSTRACT FROM AUTHOR]

The assessment of hopelessness plays a significant role in preventing various psychological disorders and major life events within the general population. However, the psychometric properties of the Beck Hopelessness Scale (BHS) have been a subject of controversy, primarily studied in clinical groups. The aim of the present study was to gain new psychometric insights and propose a new short version of the BHS for the general population using the Item Response Theory (IRT) approach. A total of 2164 Argentinean individuals completed the BHS alongside the Inventory of Suicide Orientation-30. We compared IRT models with two and three parameters for the original BHS version, exploring the removal of redundant and less informative items. Convergent and discriminant validity was also examined. Our results support the 2PL model for the BHS-19. In addition, the BHS-10 short version adequately depicted the same range of the measured trait as the original version, showing reasonable measurement accuracy in the middle-high levels of the trait (marginal reliability = 0.70, Cronbach's α = 0.86). Notably, a positive correlation was found between the factorial score of BHS-10, BHS-19, and suicide orientation. In conclusion, our findings support the use of a simplified version as a practical and valuable tool for both research and clinical practice in the future. • The Beck Hopelessness Scale is the most frequently utilized instrument for assessing hopelessness. • A 2PL model was the most suitable using the Item Response Theory Approach. • The BHS-10 short version showed reasonable measurement accuracy in the middle-high levels of trait. • Our findings extend the BHS application also to non-psychiatric groups. • A positive correlation was found between BHS-10 and suicide orientation. [ABSTRACT FROM AUTHOR]

Although Item Response Theory (IRT) has been recommended for helping advance interprofessional education (IPE) research, its use remains limited. This may be partly explained by potential misconceptions regarding IRT`s “limitation” to cross-sectional data. The aim of this study is to demonstrate how Item Response Theory (IRT) can be applied effectively in before-and-after designs in IPE research. Specifically, a two-week before-after design with survey methodology using the Extended Professional Identity Scale (EPIS), an interprofessional identity measure, was conducted among n = 146 mixed health-science students. Results indicated that EPIS increased significantly before-after intervention by .74 standardised mean differences, t146 = 7.73, p < .05. The before-after IRT model also gave a test–retest reliability estimate of .60 which was considered acceptable. Comparison of the IRT model with a conventional paired-t-test indicated similar effect size estimates of Cohen’s d = .56 and .54, respectively. We demonstrate IRT`s flexibility to before-after studies in IPE. Application of this model can yield accurate changes in target IPE constructs, and it is advantageous to classical test theory vis-à-vis baseline differences. [ABSTRACT FROM AUTHOR]

Background: When collecting data from human participants, it is often important to minimise the length of questionnaire-based measures. This makes it possible to ensure that the data collection is as engaging as possible, while it also reduces response burden, which may protect data quality. Brevity is especially important when assessing eating disorders and related phenomena, as minimising questions pertaining to shame-ridden, unpleasant experiences may in turn minimise any negative affect experienced whilst responding. Methods: We relied on item response theory to shorten three eating disorder and body dysmorphia measures, while aiming to ensure that the information assessed by the scales remained as close to that assessed by the original scales as possible. We further tested measurement invariance, correlations among different versions of the same scales as well as different measures, and explored additional properties of each scale, including their internal consistency. Additionally, we explored the performance of the 3-item version of the modified Weight Bias Internalisation Scale and compared it to that of the 11-item version of the scale. Results: We introduce a 5-item version of the Eating Disorder Examination Questionnaire, a 3-item version of the SCOFF questionnaire, and a 3-item version of the Dysmorphic Concern Questionnaire. The results revealed that, across a sample of UK adults (N = 987, ages 18–86, M = 45.21), the short scales had a reasonably good fit. Significant positive correlations between the longer and shorter versions of the scales and their significant positive, albeit somewhat weaker correlations to other, related measures support their convergent and discriminant validity. The results followed a similar pattern across the young adult subsample (N = 375, ages 18–39, M = 28.56). Conclusions: These results indicate that the short forms of the tested scales may perform similarly to the full versions. Plain English summary: This manuscript introduces short versions of existing measures of eating disorders and body dysmorphia, specifically the Eating Disorder Examination Questionnaire, the SCOFF Questionnaire, and the Dysmorphic Concern Questionnaire. We further investigate the properties of the recently introduced 3-item short version of the modified Weight Bias Internalisation Scale. Across analyses including measurement invariance testing and bivariate correlations aiming to assess convergent and discriminant validity, we find support that the short scales may perform similarly to their longer versions. These short scales may contribute in meaningful ways to research where the brevity of questionnaire-type measures may make a difference by contributing to data quality. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions So What? Systems change approaches are increasingly adopted in public health to address complex problems. It is important that measures of systems change be developed so that the effects of systems change on health outcomes can be evaluated. Organisational practices are potential levers for systems change. However, robust measures of organisational capacity to engage in these practices are lacking. Informed by the Theory of Systems Change, we developed and tested the Capacity of Organisations for System Practices (COSP) scale. The COSP scale comprises four inter‐related system practices within organisations—adaptation, alignment, collaboration and evidence‐driven action and learning.We applied a three‐stage process: (1) Item generation; (2) Scale pre‐testing; and (3) Structural analyses. Item response theory tests and semantic review, together with factor analytic techniques, were applied to refine the item set and determine the scale structure.An initial pool of 97 items was generated and pre‐tested with six content experts and four target audience representatives. Modifications resulted in 60 items. In total, 126 participants provided data for the structural analysis. A second‐order hierarchical four‐factor model fit the data better than the more basic correlated factor model (Δχ2 = 1.758, p = .415). The fit indices for the final 31‐item model were acceptable (RMSEA = .084, TLI = .819).The COSP scale is ready for further testing to ensure construct validity, stability and utility.Once validated, the Capacity of Organisations for System Practices (COSP) scale has the potential to advance the theory and practice of systems change approaches. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Attention deficit hyperactivity disorder (ADHD) is often present in people with intellectual disability (ID) and autism. However, few ADHD measures have been developed specifically for individuals with these conditions. There is little literature exploring how well ADHD measures are performing at picking up specific symptoms at the item level.Analyses were conducted on data from 122 children aged 7–15 years old with diagnoses of both ADHD and ID enrolled in the Hyperactivity and Special Educational Needs trial. Parents and teachers completed ratings of ADHD symptoms on the Aberrant Behavior Checklist (ABC) hyperactivity subscale and the revised Conners' Rating Scales hyperactivity scale and ADHD index. Cronbach's alpha was used to examine the reliability of these measures. Item response theory explores the performance of individual items. Multiple indicators, multiple causes models were used to test for measurement invariance by ID severity, co‐occurring autism traits and child age.The reliability of parent and teacher reports of ADHD symptoms on the Conners' and ABC was acceptable across the range of ID. Item performance was generally good, and information was provided across the continuum of ADHD traits. Few items on either measure were non‐invariant (i.e., item endorsement generally did not differ based on other child characteristics). When non‐invariance was found, the effect was small.Both the parent‐reported and teacher‐reported versions of the Conners' hyperactivity scale and ADHD index and the ABC hyperactivity subscale appear to function well in the current sample of children with co‐occurring ADHD and ID. [ABSTRACT FROM AUTHOR]

Background: Neurodevelopmental performance tasks are often separately analyzed, even when they tap into a similar construct. This may yield mixed findings for associations of an exposure-neurobehavioral outcome. We develop an item response theory (IRT) approach to integrate multiple task variables together to improve measurement precision of the underlying construct. We apply this approach to create an integrative measure of childhood inhibitory control, and study impacts of pre/post-natal lead exposure. Methods: Using data from a prospective cohort based in Mexico (N = 533), we created an inhibitory control scale that integrates accuracy and reaction time information from four inhibitory control tasks (Go/NoGo Letter, Go/NoGo Neutral, Go/NoGo Happy, Delis-Kaplan Executive Function System (D-KEFS) Color-Word Interference Test, Condition 3). Using a generalized partial credit item response theory model, we estimated an inhibitory control index for each participant. We then assessed adjusted associations between umbilical cord blood and 4-year lead and childhood inhibitory control. We developed a resampling approach to incorporate error estimates from the inhibitory control variable to confirm the consistency of the lead-inhibitory control associations. We modeled time-varying associations of lead with each inhibitory control measure separately. Results: Participants had a median age of 9 years; 51.4% were males. Umbilical cord blood [-0.06 (95% CI: -0.11, -0.01)] and 4-year lead [-0.07 (95% CI: -0.12, -0.02)] were associated with inhibitory control index at 8–10 years. A resampling approach confirmed that 4-year lead was consistently associated with childhood inhibitory control index. Umbilical cord blood and 4-year lead were each associated with 3 out of 8 measures in separate models. Conclusion: This is the first application of IRT in environmental epidemiology to create a latent variable for inhibitory control that integrates accuracy and reaction time information from multiple, related tasks. This framework can be applied to other correlated neurobehavioral assessments or other phenotype data. Key messages: We are among the first to use item response theory to create an integrative measure of childhood inhibitory control, using multiple performance-tasks to improve measurement precision and construct validity. We combined information about speed and accuracy on each inhibitory control performance-task using theory driven considerations. We developed a resampling approach using plausible value imputation to account for measurement error of inhibitory control factor scores in estimating associations between lead exposures and inhibitory control. Higher lead exposure at birth, and during preschool age, were both associated with worse childhood inhibitory control. In boys, lead exposure at birth was associated with worse childhood inhibitory control, while in girls, lead exposure during preschool age was associated with worse childhood inhibitory control. [ABSTRACT FROM AUTHOR]

Objective structured clinical examinations (OSCEs) are a widely used performance assessment for medical and dental students. A common limitation of OSCEs is that the evaluation results depend on the characteristics of raters and a scoring rubric. To overcome this limitation, item response theory (IRT) models such as the many-facet Rasch model have been proposed to estimate examinee abilities while taking into account the characteristics of raters and evaluation items in a rubric. However, conventional IRT models have two impractical assumptions: constant rater severity across all evaluation items in a rubric and an equal interval rating scale among evaluation items, which can decrease model fitting and ability measurement accuracy. To resolve this problem, we propose a new IRT model that introduces two parameters: (1) a rater–item interaction parameter representing the rater severity for each evaluation item and (2) an item-specific step-difficulty parameter representing the difference in rating scales among evaluation items. We demonstrate the effectiveness of the proposed model by applying it to actual data collected from a medical interview test conducted at Tokyo Medical and Dental University as part of a post-clinical clerkship OSCE. The experimental results showed that the proposed model was well-fitted to our OSCE data and measured ability accurately. Furthermore, it provided abundant information on rater and item characteristics that conventional models cannot, helping us to better understand rater and item properties. [ABSTRACT FROM AUTHOR]

ABSTRACT The cost of living in the United Kingdom has risen to unprecedented levels, leaving people experiencing intensifying hardship. However, there is a tension between the ways in which the cost‐of‐living crisis has been framed in public discourse and the experiences of the public, who focus less on coping with short‐term shocks and more on the erosion of personal resilience over the long term. To explore how resilience has been practised during the crisis and the types of policy change people want to see, this article draws on findings from a mixed‐methods study, taking in a longitudinal survey fielded in Britain in 2022–2023, alongside findings from deliberative workshops and peer research conducted in three London boroughs. Our contribution is both theoretical, connecting lived experience to the existing literature on resilience, and empirical, through the application of novel methods to policy responses to hardship. Using Item Response Theory, supported by insights from peer research and deliberative workshops, we identify the differential nature of the strategies people are taking to cope with rising costs. We then consider the types of policy changes people would like to see, finding far greater appetite for long‐term, ambitious systemic reform to rebuild resilience, not short‐term measures to weather the peaks of inflation. Our findings suggest a distrust in those with the power to enact change as well as stigma around accessing support, while also highlighting the need for engaging the most vulnerable in the process. [ABSTRACT FROM AUTHOR]

Background: Computerized adaptive testing (CAT) is an effective way to reduce time, repetitious redundancy, and respond burden, and has been used to measure outcomes in many diseases. This study aimed to develop and validate a comprehensive disease-specific CAT for chronic obstructive pulmonary disease (COPD) patient-reported outcome measurement. Methods: The discrimination and difficulty of the items from the modified patient-reported outcome scale for COPD (mCOPD-PRO) were analyzed using item response theory. Then the initial item, item selection method, ability estimation method, and stopping criteria were further set based on Concerto platform to form the CAT. Finally, the reliability and validity were validated. Results: The item discrimination ranged from 1.05 to 2.71, and the item difficulty ranged from − 3.08 to 3.65. The measurement reliability of the CAT ranged from 0.910 to 0.922 using random method, while that ranged from 0.910 to 0.924 using maximum Fisher information (MFI) method. The content validity was good. The correlation coefficient between theta of the CAT and COPD assessment test and modified Medical Research Council dyspnea scale scores using random method was 0.628 and 0.540 (P < 0.001; P < 0.001) respectively, while that using MFI method was 0.347 and 0.328 (P = 0.007; P = 0.010) respectively. About 11 items (reducing by 59.3%) on average were tested using random method, while about seven items (reducing by 74.1%) on average using MFI method. The correlation coefficient between theta of the CAT and mCOPD-PRO total scores using random method was 0.919 (P < 0.001), while that using MFI method was 0.760 (P < 0.001). Conclusions: The comprehensive disease-specific CAT for COPD patient-reported outcome measurement is well developed with good psychometric properties, which can provide an efficient, accurate, and user-friendly measurement for patient-reported outcome of COPD. [ABSTRACT FROM AUTHOR]

Background: Neurodevelopmental performance tasks are often separately analyzed, even when they tap into a similar construct. This may yield mixed findings for associations of an exposure-neurobehavioral outcome. We develop an item response theory (IRT) approach to integrate multiple task variables together to improve measurement precision of the underlying construct. We apply this approach to create an integrative measure of childhood inhibitory control, and study impacts of pre/post-natal lead exposure. Methods: Using data from a prospective cohort based in Mexico (N = 533), we created an inhibitory control scale that integrates accuracy and reaction time information from four inhibitory control tasks (Go/NoGo Letter, Go/NoGo Neutral, Go/NoGo Happy, Delis-Kaplan Executive Function System (D-KEFS) Color-Word Interference Test, Condition 3). Using a generalized partial credit item response theory model, we estimated an inhibitory control index for each participant. We then assessed adjusted associations between umbilical cord blood and 4-year lead and childhood inhibitory control. We developed a resampling approach to incorporate error estimates from the inhibitory control variable to confirm the consistency of the lead-inhibitory control associations. We modeled time-varying associations of lead with each inhibitory control measure separately. Results: Participants had a median age of 9 years; 51.4% were males. Umbilical cord blood [-0.06 (95% CI: -0.11, -0.01)] and 4-year lead [-0.07 (95% CI: -0.12, -0.02)] were associated with inhibitory control index at 8–10 years. A resampling approach confirmed that 4-year lead was consistently associated with childhood inhibitory control index. Umbilical cord blood and 4-year lead were each associated with 3 out of 8 measures in separate models. Conclusion: This is the first application of IRT in environmental epidemiology to create a latent variable for inhibitory control that integrates accuracy and reaction time information from multiple, related tasks. This framework can be applied to other correlated neurobehavioral assessments or other phenotype data. Key messages: We are among the first to use item response theory to create an integrative measure of childhood inhibitory control, using multiple performance-tasks to improve measurement precision and construct validity. We combined information about speed and accuracy on each inhibitory control performance-task using theory driven considerations. We developed a resampling approach using plausible value imputation to account for measurement error of inhibitory control factor scores in estimating associations between lead exposures and inhibitory control. Higher lead exposure at birth, and during preschool age, were both associated with worse childhood inhibitory control. In boys, lead exposure at birth was associated with worse childhood inhibitory control, while in girls, lead exposure during preschool age was associated with worse childhood inhibitory control. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Method Result and Discussion Conclusion Few psychosis screening instruments have been tested for use in Africa, yet appropriate tools can increase the detection of self‐reported psychotic symptoms, improve the detection of psychosis and impact its prognosis.The construct validity and factor structure of Psychosis Screening Questionnaire (PSQ) were tested with confirmatory factor analysis (CFA) and item response theory (IRT) in a sample of 1928 Ethiopian adults without any history of psychosis. We tested a unidimensional model with and without an item on mania. For IRT, unidimensional latent structure one‐parameter logistic (1PL) and two‐parameter (2PL) logistic models were tested and compared for relative fit using a likelihood‐ratio test.The prevalence of lifetime positive screens was 2.8% in an Ethiopian sample of adults from a general medical setting. A unidimensional model demonstrated good fit for the PSQ, (CFI = 0.993, TLI = 0.986 and RMSEA = 0.025). For IRT, a 2PL model was the best fitting one. IRT tests of item difficulty and discrimination parameters showed that paranoia had the highest discrimination α=4.59$$ \left(\alpha =4.59\right) $$ and lowest difficulty (β=2.53$$ \beta =2.53 $$), likely to be endorsed at low levels of psychotic features. Thought insertion had the highest item difficulty (β=2.98$$ \beta =2.98 $$). Overall, the measure captures the psychosis construct at higher levels of the latent trait and may be suited for detecting moderate to severe levels of psychosis.The PSQ is found to have good construct validity in screening for psychosis among Ethiopian adults. Future studies may focus on the diagnostic validity of the PSQ comparing it with a structured clinical interview. [ABSTRACT FROM AUTHOR]

In education testing, the items that examinees receive may be selected for a variety of reasons, resulting in missing data for items that were not selected. Item selection is internal when based on prior performance on the test, such as in adaptive testing designs or for branching items. Item selection is external when based on an auxiliary variable collected independently to performance on the test, such as education level in a targeting testing design or geographical location in a nonequivalent anchor test equating design. This paper describes the implications of this distinction for Item Response Theory (IRT) estimation, drawing upon missing-data theory (e.g., Mislevy & Sheehan, 1989, https://doi.org/10.1007/BF02296402; Rubin, 1976, https://doi.org/10.1093/biomet/63.3.581), and selection theory (Meredith, 1993, https://doi.org/10.1007/BF02294825). Through mathematical analyses and simulations, we demonstrate that this internal versus external item selection framework provides a general guide in applying missing-data and selection theory to choose a valid analysis model for datasets with missing data. [ABSTRACT FROM AUTHOR]