Toward Advancing Precision Environmental Health: Developing a Customized Exposure Burden Score to PFAS Mixtures to Enable Equitable Comparisons Across Population Subgroups, Using Mixture Item Response Theory.

Quantifying a person's cumulative exposure burden to per- and polyfluoroalkyl substances (PFAS) mixtures is important for risk assessment, biomonitoring, and reporting of results to participants. However, different people may be exposed to different sets of PFASs due to heterogeneity in the exposure sources and patterns. Applying a single measurement model for the entire population (e.g., by summing concentrations of all PFAS analytes) assumes that each PFAS analyte is equally informative to PFAS exposure burden for all individuals. This assumption may not hold if PFAS exposure sources systematically differ within the population. However, the sociodemographic, dietary, and behavioral characteristics that underlie systematic exposure differences may not be known, or may be due to a combination of these factors. Therefore, we used mixture item response theory, an unsupervised psychometrics and data science method, to develop a customized PFAS exposure burden scoring algorithm. This scoring algorithm ensures that PFAS burden scores can be equitably compared across population subgroups. We applied our methods to PFAS biomonitoring data from the United States National Health and Nutrition Examination Survey (2013-2018). Using mixture item response theory, we found that participants with higher household incomes had higher PFAS burden scores. Asian Americans had significantly higher PFAS burden compared with non-Hispanic Whites and other race/ethnicity groups. However, some disparities were masked when using summed PFAS concentrations as the exposure metric. This work demonstrates that our summary PFAS burden metric, accounting for sources of exposure variation, may be a more fair and informative estimate of PFAS exposure.

Development and validation of the food availability and related eating behaviors questionnaire: A stage 1 registered report.

OBJECTIVE: Historically, eating disorder research has excluded marginalized and underserved populations, such as those with food insecurity (which also impacts higher numbers of Black/African American and Latinx communities). However, burgeoning research suggests an association between food insecurity and the development of eating disorder pathology. Examining patterns of food availability and related eating behaviors may elucidate the association between food insecurity and eating disorder pathology. However, to date, there are no comprehensive measures that accurately capture food availability patterns and related eating behaviors. METHOD: In Study 1, 40 participants (20 adolescents, 20 adults) will respond to and provide qualitative feedback on the Food Availability and Related Eating Behaviors Questionnaire (FAREB-Q). In study 2, 50 participants (approximately 25 with and without food insecurity) will complete the FAREB-Q at two time-points, and respond to questions about food insecurity, disordered eating, and every day stress to assess the FAREB-Q's reliability and validity. RESULTS: Results will clarify whether the FAREB-Q is a reliable and valid instrument that measures food availability and related eating behavior patterns. DISCUSSION: The present study aims to develop, pilot, and examine the psychometric properties of the FAREB-Q, a self-report measure examining food availability and related eating behaviors in community populations. PUBLIC SIGNIFICANCE: The novel FAREB-Q assesses food availability and related eating patterns in the general community. The FAREB-Q will be reviewed by experts in disordered eating, food insecurity, psychometric statisticians and piloted in the general public before being psychometrically evaluated in a larger sample. The FAREB-Q is anticipated to help elucidate the mechanisms linking food availability, food (in)security, disordered eating behaviors, and eating pathology.

Comparison of ad libitum snack consumption and acquisition between adolescents living with food security and food insecurity: A stage 1 registered report.

OBJECTIVE: Approximately 11% of the U.S. population experiences food insecurity (FI; insufficient access to healthy food due to financial constraints). FI is associated with detrimental health outcomes, including the development of eating disorders (EDs). However, additional studies are needed, particularly in adolescence when EDs are likely to emerge. The current study will utilize an experimental ad libitum snack paradigm to investigate snack consumption, acquisition (i.e., taking snacks home), and associated disordered eating behaviors among racially, ethnically, and financially diverse adolescents living with FI and food security (FS). METHOD: Sixty-four adolescents will be recruited and randomized into one of two conditions: prior knowledge condition (i.e., participants will know prior to snacking that they can take any remaining food home) and no prior knowledge condition (i.e., participants will not know ahead of time that they can take snacks home). RESULTS: We expect youth with FI to show increased eating and acquisition behaviors compared to youth with FS across both conditions. DISCUSSION: This study, utilizing a novel experimental design, is an important step in understanding how FI impacts adolescent eating behaviors among youth from marginalized backgrounds, who have historically been excluded from research.

Metric Stability in Item Response Models.

In item response theory, uncertainty associated with estimated item parameters can lead to greater uncertainty in subsequent analyses, such as estimating trait scores for individual examinees. Most existing methods to characterize or correct for item parameter uncertainty implicitly assume that the latent trait continuum is fixed across the posterior distribution of item parameters. However, the latent trait continuum can also be understood as an artifact of the fitted model, such that the location of this continuum is determined with error. In other words, item parameter estimation error implies uncertainty about the location of the metric. This article uses Ramsay's (1996) geometry of the latent trait metric to develop a quantitative measure of metric stability, that is, the sampling variability of the latent trait continuum implied by errors in item parameter estimation. Through a series of illustrations, it is clarified how metric stability is related to other item response model evaluation outcomes (e.g., test information, model fit), and how metric stability can be useful in identifying well-determined regions of the latent trait continuum, making sample size recommendations, and selecting a model. Overall, the proposed measure of metric stability provides meaningful and highly interpretable information to aid in item response model evaluation.

Competence to Consent to Oral and Injectable PrEP Trials Among Adolescent Males Who Have Sex with Males.

Adherence to oral pre-exposure prophylaxis (PrEP) is challenging for adolescent males who have sex with males (AMSM). Once adult trials comparing oral to longer lasting injectable PrEP are completed, there will be a need for adolescent studies. However, lack of data on adolescent consent capacity may sustain guardian permission requirements identified as a barrier to AMSM participation in prior PrEP trials. This online study assessed AMSM's (14-17 years) consent capacity for these trials, comparing performance to MSM (18-19 years) for whom guardian permission is not required. Applying the MacCAT-CR, participants (N = 214) viewed a video and mock consent form followed by open-ended and yes/no items. Cognitive diagnostic models and means testing analyses supported AMSM capacity to consent to these trials: 16-17 and most 14-15 year-olds, demonstrated consent understanding, appreciation and reasoning at 18-19 year-old levels. Data also identified vulnerabilities requiring attention during informed consent.

A note on the identification of change detection task models to measure storage capacity and attention in visual working memory.

The change detection task is a common method for assessing the storage capacity of working memory, but estimates of memory capacity from this task can be distorted by lapses of attention. When combined with appropriate mathematical models, some versions of the change detection task make it possible to separately estimate working memory and the probability of attentional lapses. In principle, these models should allow researchers to isolate the effects of experimental manipulations, group differences, and individual differences on working memory capacity and on the rate of attentional lapses. However, the present research found that two variants of a widely accepted model of the change detection task are not mathematically identified.

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

Longitudinal measurement invariance in prospective oral health-related quality of life assessment.

BACKGROUND: Prospective assessments of oral health-related quality of life (OHRQoL) changes are prone to response shift effects when patients reconceptualize, reprioritize, or recalibrate the perceived meanings of OHRQoL test items. If this occurs, OHRQoL measurements are not "invariant" and may reflect changes in problem profiles or perceptions of OHRQoL test items. This suggests that response shift effects must be measured and controlled to achieve valid prospective OHRQoL measurement. The aim of this study was to quantify response shift effects of Oral Health Impact Profile (OHIP) scores in prospective studies of prosthodontic patients. METHODS: Data came from the Dimensions of Oral Health-Related Quality of Life Project. The final sample included 554 patients who completed the OHIP questionnaire on two occasions: pre- and post-treatment. Only items that compose the 14-item OHIP were analyzed. Structural equation models that included pre- and post-treatment latent factors of OHRQoL with different across-occasion constraints for factor loadings, intercepts, and residual variances were fit to the data using confirmatory factor analysis. RESULTS: Data fit both the unconstrained model (RMSEA = .038, SRMR = .051, CFI = .92, TLI = .91) and the partially constrained model with freed residual variances (RMSEA = .037, SRMR = .064, CFI = .92, TLI = .92) well, meaning that the data are well approximated by a one-factor model at each occasion, and suggesting strong factorial across-occasion measurement invariance. CONCLUSIONS: The results provided cogent evidence for the absence of response shift in single factor OHIP models, indicating that longitudinal OHIP assessments of OHRQoL measure similar constructs across occasions.

A 7-day recall period for a clinical application of the oral health impact profile questionnaire.

OBJECTIVES: Aims were to investigate and compare the validity and reliability of Oral Health Impact Profile (OHIP) scores referencing 7-day and 1-month recall periods in international prosthodontic patients. MATERIAL AND METHODS: A sample of 267 patients (mean age = 54.0 years, SD = 17.2 years, 58 % women) with stable oral health-related quality of life was recruited from prosthodontic treatment centers in Croatia, Germany, Hungary, Japan, Slovenia, and Sweden. These patients completed the OHIP on two occasions using a new 7-day recall period and the traditional 1-month recall period. OHIP score validity and reliability were investigated with structural equation models (SEMs) that included OHIP(past 7 days) and OHIP(1 month) latent factors and single indicator measures of global oral health status. The SEMs assessed measurement invariance and the relative validities of the two OHIP latent factors (representing the two recall periods). RESULTS: The SEMs provided cogent evidence for recall period measurement invariance for the two OHIP forms and equal validities (r = .48) with external measures of global oral health status. CONCLUSION: When assessed in international prosthodontic patients, OHIP scores using the new 7-day recall period were as reliable and valid as the scores using the 1-month recall period. CLINICAL RELEVANCE: Conceptual advantages make a 7-day recall period a preferred frame of reference in clinical applications of the OHIP questionnaire.

Applying Latent Variable Models to Estimate Cumulative Exposure Burden to Chemical Mixtures and Identify Latent Exposure Subgroups: A Critical Review and Future Directions.

Environmental mixtures, which reflect joint exposure to multiple environmental agents, are a major focus of environmental health and risk assessment research. Advancements in latent variable modeling and psychometrics can be used to address contemporary questions in environmental mixtures research. In particular, latent variable models can quantify an individual's cumulative exposure burden to mixtures and identify hidden subpopulations with distinct exposure patterns. Here, we first provide a review of measurement approaches from the psychometrics field, including structural equation modeling and latent class/profile analysis, and discuss their prior environmental epidemiologic applications. Then, we discuss additional, underutilized opportunities to leverage the strengths of psychometric approaches. This includes using item response theory to create a common scale for comparing exposure burden scores across studies; facilitating data harmonization through the use of anchors. We also discuss studying fairness or appropriateness of measurement models to quantify exposure burden across diverse populations, through the use of mixture item response theory and through evaluation of measurement invariance and differential item functioning. Multi-dimensional models to quantify correlated exposure burden sub-scores, and methods to adjust for imprecision of chemical exposure data, are also discussed. We show that there is great potential to address pressing environmental epidemiology and exposure science questions using latent variable methods.

Linking patient-reported oral and general health-related quality of life.

Background: The relationship between oral and overall health is of interest to health care professionals and patients alike. This study investigated the correlation between oral health-related quality of life (OHRQoL) and health-related quality of life (HRQoL) in a general adult population. Methods: This cross-sectional study used a convenience sample of adult participants (N = 607) attending the 2022 Minnesota County and State fairs in USA, the 5-item Oral Health Impact Profile (OHIP-5) assessed OHRQoL, and the 10-item PROMIS v.1.2 Global Health Instrument assessed HRQoL. Spearman and Pearson correlations were used to summarize the bivariable relationship between OHRQoL and HRQoL (both physical and mental health dimensions). A structural equation model determined OHRQoL-HRQoL correlations (r). Correlations' magnitude was interpreted according to Cohen's guidelines (r = 0.10, 0.30, and 0.50 to demarcate "small," "medium," and "large" effects, respectively). Results: OHRQoL and HRQoL correlated with r = 0.52 (95% confidence interval, CI: [0.50-0.55]), indicating that the two constructs shared 27% of their information. According to Cohen, this was a "large" effect. OHRQoL, and the physical and mental HRQoL dimensions correlated with r = 0.55 (95% CI: [0.50-0.59]) and r = 0.43 (95% CI: [0.40-0.46]), respectively, indicating a "large" and a "medium" effect. OHRQoL and HRQoL were substantially correlated in an adult population. Conclusion: Using OHIP-5 to assess their dental patients' oral health impact allows dental professionals to gain insights into patients' overall health-related wellbeing.

The U.S. PFAS exposure burden calculator for 2017-2018: Application to the HOME Study, with comparison of epidemiological findings from NHANES.

BACKGROUND: The 2017-2018 U.S. PFAS exposure burden calculator was designed to provide a summary exposure score for per- and polyfluoroalkyl substances (PFAS) mixtures using targeted PFAS analyte data. Its aim was to place PFAS burden score estimates onto a common scale based on nationally representative U.S. reference ranges from 2017 to 2018, enabling comparisons of overall PFAS burden scores across studies even if they did not measure the same set of PFAS analytes. OBJECTIVE: To use the U.S. PFAS exposure burden calculator for comparing the same mixture of PFAS compounds in similarly aged adolescents and their associations with cardiometabolic outcomes in the HOME Study and NHANES between 2015 and 2018. METHODS: We applied the PFAS burden calculator to 8 PFAS analytes measured in the serum of adolescents from the HOME Study (Cincinnati, Ohio; age range 11-14 years; years: 2016-2019; n = 207) and NHANES (US; age range 12-14 years; years 2015-2018; n = 245). We used the non-parametric Mann-Whitney U test and chi-squared test to compare the two study samples. In both studies, we examined associations of PFAS burden scores with the same cardiometabolic outcomes, adjusted for the same core set of covariates using regression analyses. We conducted sensitivity analyses to verify robustness of exposure-outcome associations, by accounting for measurement error of PFAS burden scores. RESULTS: PFAS burden scores were significantly different (p = 0.004) between the HOME Study (median: 0.00, interquartile range - 0.37, 0.34) and the NHANES samples (median: 0.04, IQR -0.11, 0.54), while no significant difference was found for PFAS summed concentrations (p = 0.661). In the HOME Study, an interquartile (IQR) increase in PFAS burden score was associated with higher total cholesterol [7.0 mg/dL, 95% CI: 0.6, 13.4]; HDL [2.8 mg/dL, 95% CI: 0.4, 5.2]; LDL [5.9 mg/dL, 95% CI: 0.5, 11.3], insulin [0.1 log(mIU/L), 95% CI: 0.01, 0.2], and HOMA-IR [0.1, 95% CI: 0.01, 0.2]. In NHANES, an IQR increase in PFAS burden score was associated with higher diastolic blood pressure [2.4 mmHg, 95% CI: 0.4, 4.4] but not with other outcomes. Sensitivity analyses in the HOME Study and NHANES were consistent with the main findings. CONCLUSIONS: Performance of the U.S. PFAS exposure burden calculator was similar in a local versus national sample of adolescents, and may be a useful tool for the assessment of PFAS mixtures across studies.

Measuring hopelessness in advanced cancer: a secondary analysis of the Hopelessness Assessment in Illness questionnaire (HAI).

OBJECTIVE: Hopelessness, or a sense of despair about the future, has been a growing focus of psychological research among patients with serious medical illnesses. This study evaluated the psychometric properties of the Hopelessness Assessment in Illness (HAI) questionnaire, developed specifically for those facing a life-threatening illness. Participants were 344 advanced cancer patients (e.g. lung, breast, gastrointestinal, etc.) participating in two psychotherapy research trials. DESIGN: Descriptive statistics characterised participants in regard to both demographic (age, gender, race, ethnicity, religiosity) and clinical characteristics (cancer type). Scale properties were assessed for internal consistency using Cronbach's coefficient alpha, item-total correlations, Principle Axis factor analysis, and its correlation to relevant psychological constructs. Nonlinear confirmatory factor analysis (CFA) assessed for latent construct variance by gender. MAIN OUTCOME MEASURES: Psychometric properties of the Hopelessness Assessment in Illness questionnaire. RESULTS: Results indicated strong internal consistency and temporal stability of the HAI, with significant correlations between the HAI and several theoretically related psychological constructs. CFA suggested the same single underlying factor for males and females. CONCLUSIONS: The HAI demonstrated strong psychometric properties in the context of advanced cancer. Future research is needed to assess the utility of the HAI in more medically and geographically diverse populations.

Validation of the HeLD-14 functional oral health literacy instrument in a general population.

Background: Oral health literacy (OHL) is recognized as an important determinant of oral outcomes. Measuring OHL with a valid and reliable instrument that accurately captures the functional nature of this construct across cultures is needed. The short version of the Health Literacy in Dentistry scale (HeLD-14) shows promise as an appropriate instrument due to its inclusion of comprehensive domains hypothesized to comprise OHL. While studies validating the instrument in several languages have occurred, the number of dimensions in the various analyses range from one to seven. Validation of the HeLD-14 in a general English-speaking population is also lacking. The purpose of this study was to explore and confirm the dimensionality of the HeLD-14 in a general US English-speaking population. Methods: The psychometric properties of HeLD-14 were evaluated in a sample of 631 participants attending the Minnesota State Fair. Construct validity was assessed using exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA) on the data set split into two groups. Internal consistency reliability was assessed using the Cronbach's alpha coefficient. Concurrent validity was established between the HeLD-14 and the Oral Health Inventory Profile (OHIP-5) using Pearson's correlation. Results: EFA found, and CFA reinforced, a unidimensional structure of the HeLD-14. Cronbach's alpha was acceptable at 0.92. Fit assessment also supported a unidimensional structure, comparative fit index = 0.992, Tucker-Lewis index = 0.991, root mean square error of approximation = 0.065, and standardized root mean square residual = 0.074. Concurrent validity analyses showed that the HeLD-14 correlated with the OHIP-5. Conclusions: The HeLD-14 is a unidimensional reliable and valid instrument for measuring the oral health literacy in the general US English-speaking adult population.

Phthalate mixtures and insulin resistance: an item response theory approach to quantify exposure burden to phthalate mixtures.

BACKGROUND: Molar sums are often used to quantify total phthalate exposure, but they do not capture patterns of exposure to multiple phthalates. OBJECTIVE: To introduce an exposure burden score method for quantifying exposure to phthalate metabolites and examine the association between phthalate burden scores and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). METHODS: We applied item response theory (IRT) to data from 3474 adults aged 20-60 years in the 2013-2018 National Health and Examination Survey (NHANES) to quantify latent phthalate exposure burden from 12 phthalate metabolites. We compared model fits of three IRT models that used different a priori groupings (general phthalate burden; low molecular weight (LMW) and high molecular weight (HMW) burdens; and LMW, HMW and DEHP burden), and used the best fitting model to estimate phthalate exposure burden scores. Regression models assessed the covariate-adjusted association between phthalate burden scores and HOMA-IR. We compared findings to those using molar sums. In secondary analyses, we examined how the IRT model could be used for data harmonization when a subset of participants are missing some phthalate metabolites, and accounted for measurement error of the phthalate burden scores in estimating associations with HOMA-IR through a resampling approach using plausible value imputation. RESULTS: A three correlated factors model (LMW, HMW and DEHP burdens) provided the best fit. One interquartile range (IQR) increase in DEHP burden score was associated with 0.094 (95% CI: 0.022, 0.164, p = 0.010) increase in log HOMA-IR, co-adjusted for LMW and HMW burden scores. Findings were consistent when using log molar sums. Associations of phthalate burden and insulin resistance were also consistent when participants were simulated to be missing some phthalate metabolites, and when we accounted for measurement error in estimating burden scores. CONCLUSION: Both phthalate molar sums and burden scores are sensitive to associations with insulin resistance. Phthalate burden scores may be useful for data harmonization.

On the Performance of Semi- and Nonparametric Item Response Functions in Computer Adaptive Tests.

Large-scale assessments often use a computer adaptive test (CAT) for selection of items and for scoring respondents. Such tests often assume a parametric form for the relationship between item responses and the underlying construct. Although semi- and nonparametric response functions could be used, there is scant research on their performance in a CAT. In this work, we compare parametric response functions versus those estimated using kernel smoothing and a logistic function of a monotonic polynomial. Monotonic polynomial items can be used with traditional CAT item selection algorithms that use analytical derivatives. We compared these approaches in CAT simulations with a variety of item selection algorithms. Our simulations also varied the features of the calibration and item pool: sample size, the presence of missing data, and the percentage of nonstandard items. In general, the results support the use of semi- and nonparametric item response functions in a CAT.

Developing an Exposure Burden Score for Chemical Mixtures Using Item Response Theory, with Applications to PFAS Mixtures.

BACKGROUND: There are few existing methods to quantify total exposure burden to chemical mixtures, independent of a health outcome. A summary metric could be advantageous for use in biomonitoring, risk assessment, health risk calculators, and mediation models. OBJECTIVE: We developed a novel exposure burden score method for chemical mixtures, applied it to estimate exposure burden to per- and polyfluoroalkyl substances (PFAS) mixtures, and estimated associations of PFAS burden scores with cardio-metabolic outcomes in the general U.S. METHODS: We applied item response theory (IRT) to biomonitoring data from 1,915 children and adults 12-80 years of age in the 2017-2018 National Health and Examination Survey to quantify a latent PFAS burden score, using serum concentrations of eight measured PFAS biomarkers, each considered an "item." The premise of IRT is that through using both information about a participant's concentration of an individual PFAS biomarker, as well as their exposure patterns for the PFAS mixture, we can estimate the participant's latent PFAS exposure burden, independent of a health outcome. We used linear regression to estimate associations of the PFAS burden score with cardio-metabolic outcomes and compared our findings to results using summed PFAS concentrations as the exposure metric. RESULTS: PFAS burden scores and summed PFAS concentrations had moderate-high correlation (ρ=0.75). Isomers of PFOS [n-perfluorooctane sulfonic acid (n-PFOS) and perfluoromethylheptane sulfonic acid isomers (Sm-PFOS)] were the most informative to the PFAS burden scores. PFAS burden scores and summed PFAS concentrations were both significantly associated with cardio-metabolic outcomes, but associations were generally closer to the null for summed PFAS concentrations vs. the PFAS burden score. Adjusted associations (95% CIs) with total cholesterol (in milligrams per deciliter) were 8.6 (95% CI: 5.2, 11.9) and 2.4 (95% CI: 0.5, 4.2) per interquartile range increase in the PFAS burden score and summed concentrations, respectively. Sensitivity analyses showed similar associations with cardio-metabolic outcomes when only a subset of PFAS biomarkers was used to estimate PFAS burden. In a validation study, associations between PFAS burden scores and cholesterol were consistent with primary analyses but null when using summed PFAS concentrations. DISCUSSION: IRT offers a straightforward way to include exposure biomarkers with low detection frequencies and can reduce exposure measurement error. Further, IRT enables comparisons of exposure burden to chemical mixtures across studies even if they did not measure the exact same set of chemicals, which supports harmonization across studies and consortia. We provide an accompanying PFAS burden calculator (https://pfasburden.shinyapps.io/app_pfas_burden/), enabling researchers to calculate PFAS burden scores based on U.S. population exposure reference ranges. https://doi.org/10.1289/EHP10125.

Parental Factors That Confer Risk and Resilience for Remote Learning Outcomes During the COVID-19 Pandemic Among Children With and Without Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: To test whether parental factors including internalizing symptoms, parenting style, and confidence in assisting with remote learning conferred risk/resilience for children with/without ADHD's learning and emotional outcomes during the COVID-19 pandemic. METHOD: 291 parents of children (ages 6-13; n = 180 males) with (n = 148) and without ADHD completed questionnaires online (April-July 2020). RESULTS: Structural equation modeling identified parental risk/resilience factors. Across groups, risk predicted greater difficulties with learning, internalizing and externalizing symptoms, while parent confidence in educating their child predicted better outcomes. A positive association was observed between parental involvement and child difficulties, which was stronger in families of children with ADHD. Children with/without ADHD did not differ in remote learning difficulties. CONCLUSION: Parent factors impacted child emotional and learning outcomes during the pandemic. With increases in remote learning practices, there is a need for improved understanding of how parent factors impact outcomes of children with/without ADHD.

Measuring Emotion Dysregulation in Children With Attention-Deficit/Hyperactivity Disorder: Revisiting the Factor Structure of the Emotion Regulation Checklist.

Emotion dysregulation (ED) is prevalent among youth with Attention-Deficit/Hyperactivity Disorder (ADHD) and significantly impacts functioning. Nuanced measurement of ED is central to understanding its role in this disorder and informing treatment approaches. The present study examined the factor structure of the Emotion Regulation Checklist (ERC) among children with ADHD with and without Oppositional Defiant Disorder (ODD). Exploratory factor analysis (EFA) conducted in a sample of 328 youth (mean age = 6.08) with ADHD indicated a four-factor solution, comprised of the following factors: Negative Emotion Lability, Positive Emotion Lability, Socially Appropriate Affect, and Socially Incongruent Affect. The Negative and Positive Emotion Lability subscales assess the reactivity of negatively and positively valenced emotions, respectively. The Socially Appropriate and Socially Incongruent Affect subscales provide an assessment of social-emotional functioning. All subscales discriminated between children with ADHD only and ADHD with co-morbid ODD, such that children with ODD had greater emotional lability and social-emotional difficulties. This revised factor structure of the ERC facilitates a uniquely brief, yet multifaceted and specific, assessment of emotional difficulties in children with ADHD that can inform treatment planning and operationalize emotional reactivity and social-emotional functioning in future research efforts.

Scale Alignment in the Between-Item Multidimensional Partial Credit Model.

In between-item multidimensional item response models, it is often desirable to compare individual latent trait estimates across dimensions. These comparisons are only justified if the model dimensions are scaled relative to each other. Traditionally, this scaling is done using approaches such as standardization-fixing the latent mean and standard deviation to 0 and 1 for all dimensions. However, approaches such as standardization do not guarantee that Rasch model properties hold across dimensions. Specifically, for between-item multidimensional Rasch family models, the unique ordering of items holds within dimensions, but not across dimensions. Previously, Feuerstahler and Wilson described the concept of scale alignment, which aims to enforce the unique ordering of items across dimensions by linearly transforming item parameters within dimensions. In this article, we extend the concept of scale alignment to the between-item multidimensional partial credit model and to models fit using incomplete data. We illustrate this method in the context of the Kindergarten Individual Development Survey (KIDS), a multidimensional survey of kindergarten readiness used in the state of Illinois. We also present simulation results that demonstrate the effectiveness of scale alignment in the context of polytomous item response models and missing data.