Demands and stress before and during the COVID-19 pandemic of parents to children with autism spectrum disorder.

Introduction: Parents to children with Autism Spectrum Disorder (ASD) face diverse daily demands that can lead to stress. The aim of this study was to examine to which extent stress in parents to children with ASD can be explained by daily demands before and during the COVID-19 pandemic (after lockdowns; first half of 2022), and whether there are differences between the two time periods in this regard. Methods: Data from parents to children with ASD living in Germany from two independent questionnaire studies (before the pandemic: N = 168, during the pandemic: N = 105) were matched for comparability. Simple and multiple linear regression analyses were used to answer the research question. Results: Parental stress as well as all demands examined showed higher levels during the COVID-19 pandemic than before. Significant predictors of parental stress before and during the COVID-19 pandemic were (1) the daily demands to deal with the child's problem behavior, (2) the restriction of one's personal way of life, and (3) the challenge to cooperate with the partner. During the COVID-19 pandemic, the child's problem behavior was particularly relevant. It was also found that the demand to deal with stigmatizing reactions did not explain parental stress during the COVID-19 pandemic whereas before the pandemic it had been a significant predictor. Discussion: Although parental stress and the demands of daily life increased during the pandemic, most of the stress can be explained by the same demands. It is suggested that the increased levels may be due to an increase in the child's ASD symptomatology, which is why it is advisable to install therapeutic and care structures that prepare children with ASD for future crises.

Coping resources and stress due to demands in parents to children with autism spectrum disorder.

Introduction: Parents to children with autism spectrum disorder (ASD) are exposed to numerous demands in their daily lives and exhibit high levels of stress. The present study aims to find out which coping resources are mediators that help parents cope with these demands and which of those coping resources amplify or reduce stress arising from the demands. Studies often only focus on the connection between coping resources and stress without taking the demands into account at the same time. Methods: For this reason, a mediation model was set up to answer the research question. Data from a German questionnaire survey with N = 266 parents who have children with ASD (two to 23 years old) were used. Subjectively perceived demands in everyday life (scale "Parental demands in everyday life"), parental stress ("Parental Stress Inventory", based on Abidin's parenting stress model) and the following coping resources were collected: parental self-efficacy beliefs ("Parents' sense of competence questionnaire"), available social support of parents (scale "Availability of social support") and parental coping strategies (German version of the Brief COPE). Results: An exploratory factor analysis revealed four mediators: dysfunctional coping, functional coping, social support, and self-efficacy. The use of dysfunctional behavior and parental self-efficacy were found to be significant mediators that mediated between daily demands and parental stress. A direct effect of demands on parental stress was also found, implying partial mediation. The two factors of functional coping and support were not found to be significant mediators. Discussion: Key findings indicate that parental stress resulting from the daily demands of parenting children with ASD can be reduced by high parental self-efficacy and increased by dysfunctional coping. For practice, it can be deduced that dysfunctional coping strategies of parents to children with ASD should be reduced and parental self-efficacy should be strengthened in order to reduce stress which arises from the multiple demands in everyday life.

Delayed development of basic numerical skills in children with developmental dyscalculia.

Research suggests that children with developmental dyscalculia (DD) have deficits in basic numerical skills. However, there is conflicting evidence on whether basic numerical skills in children with DD are qualitatively different from those in typically developing children (TD) or whether basic numerical skills development in children with DD is simply delayed. In addition, there are also competing hypotheses about deficits in basic numerical skills, assuming (1) a general deficit in representing numerosities (Approximate Number System, ANS), (2) specific deficits in an object-based attentional system (Object Tracking System, OTS), or (3) deficits in accessing numerosities from symbols (Access Deficit, AD). Hence, the purpose of this study was to investigate whether deficits in basic numerical skills in children with DD are more indicative of a developmental delay or a dyscalculia-specific qualitative deviation and whether these deficits result from (selective) impairment of core cognitive systems involved in numerical processing. To address this, we tested 480 children (68 DD and 412 TD) in the 2nd, 3rd, and 4th grades with different paradigms for basic numerical skills (subitizing, counting, magnitude comparison tasks, number sets, and number line estimation tasks). The results revealed that DD children's impairments did not indicate qualitatively different basic numerical skills but instead pointed to a specific developmental delay, with the exception of dot enumeration. This result was corroborated when comparing mathematical profiles of DD children in 4th grade and TD children in 2nd grade, suggesting that DD children were developmentally delayed and not qualitatively different. In addition, specific deficits in core markers of numeracy in children with DD supported the ANS deficit rather than the AD and OTS deficit hypothesis.

Two Dyscalculia Subtypes With Similar, Low Comorbidity Profiles: A Mixture Model Analysis.

Several studies have aimed to identify subtypes of dyscalculia. In many of these studies, either pre-defined groups (e.g., children with reading and mathematical difficulties vs. children with isolated mathematical difficulties) were analyzed regarding their cognitive profiles (top-down approach), or clusters of children with dyscalculia (CwD) were identified based on a narrow range of cognitive and mathematical skills (data-driven or bottom-up approach). However, it has remained difficult to establish robust subtypes of dyscalculia across studies. Against this background, we conducted a mixture model analysis in order to explore and identify subtypes of dyscalculia based on a broad range of variables (intelligence, reading fluency, working memory, attention, and various mathematical skills). The total sample comprised 174 elementary school CwD (IQ > 70; mathematical abilities: percentile rank <10), which consisted of two subsamples. The first subsample was based on a diagnostic test focusing on calculation (HRT 1-4; n = 71; 46 girls, 25 boys; age: M = 9.28 years, SD = 0.94) whereas the second subsample was based on a diagnostic test with a strong focus on basic numerical capacities (ZAREKI-R; n = 103; 78 girls, 25 boys; age: M = 8.94 years, SD = 1.05). Results provided convincing evidence for the existence of two subtypes in CwD: A slightly impaired subtype and a strongly impaired subtype. Subtypes differed most strongly regarding mathematical abilities, but the analyses suggest that differences in attention could also be a key factor. Therefore, comorbid attention difficulties seem to be a relevant factor that needs to be considered when establishing subtypes. Substantial intelligence differences between dyscalculia subtypes could not be found. Differences in working memory and reading fluency were negligible. Overall, the results seemed to be robust regardless of the diagnostic test used for assessing dyscalculia. When planning interventions for CwD, the existence of a subtype with substantial attention problems should be kept in mind.

The co-occurrence of Attention-Deficit/Hyperactivity Disorder and mathematical difficulties: An investigation of the role of basic numerical skills.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) and dyscalculia, also called mathematics disorder, frequently co-occur, yet the etiology of this comorbidity is poorly understood. AIMS: This study investigated whether impairments in the understanding of numbers and magnitudes (basic numerical skills) are a unique risk factor for mathematical difficulties (MD) or a shared risk factor that could help to explain the association between ADHD and MD. METHODS AND PROCEDURES: Basic numerical skills were assessed with eight subtests in children (age 6-10 years, N = 86) with clinically significant ADHD symptoms and/or MD and typically developing children (control group). This double dissociation design allowed to test for main and interaction effects of ADHD and MD using both classical and Bayesian analysis of variance (ANOVA). OUTCOMES AND RESULTS: Children with MD were impaired in transcoding, complex number and magnitude comparison, and arithmetic fact retrieval. They were not impaired in tasks assessing core markers of numeracy, which might be explained by the sample including children with mathematical difficulties instead of a diagnosed dyscalculia. ADHD was not associated with deficits in any of the tasks. The evidence for an additive combination of cognitive profiles was weak. CONCLUSIONS AND IMPLICATIONS: Impairments in basic numerical skills are uniquely associated with MD and do not represent a shared risk factor for ADHD symptoms and MD.

Modeling Responses and Response Times in Tests With the Hierarchical Model and the Three-Parameter Lognormal Distribution.

The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels-one for the responses and one for the response times-that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a skew distribution with a support from zero to infinity. Such a support is unrealistic as the solution process demands a minimal processing time that sets a response time threshold. Ignoring this response time threshold misspecifies the model and threatens the validity of model-based inferences. In this article, the response time model of van der Linden is replaced by a model that is based on the three-parameter lognormal distribution. The three-parameter lognormal distribution extends the lognormal distribution by an additional location parameter that bounds the support away from zero. Two different approaches to model fitting are proposed and evaluated with regard to parameter recovery in a simulation study. The extended model is applied to two data sets. In both data sets, the extension improves the fit of the hierarchical model.

Minimum Distance Estimation of Multidimensional Diffusion-Based Item Response Theory Models.

Diffusion-based item response theory models are models for responses and response times on psychological tests, which can be used as measurement models in the same way as standard item response theory models (Tuerlinckx, Molenaar, & van der Maas, 2016). Their range of application, however, is narrowed by the fact that multidimensional versions of the model are not easy to fit. Marginal maximum likelihood estimation (e.g., Molenaar, Tuerlinckx, & van der Maas, 2015a) is computationally intensive and infeasible for multidimensional versions. The weighted least squares estimator of Ranger, Kuhn, and Szardenings (2016) is inefficient. Here, we propose an alternative estimator that is more efficient than the least squares estimator and less demanding than the maximum likelihood estimator. The estimator is based on minimum distance estimation and consists in modeling the sample quantiles and sample covariances. The performance of the estimator is investigated in a simulation study. The simulation study corroborates that the estimator performs well. The application of the estimator is demonstrated with real data.

Robust estimation of the hierarchical model for responses and response times.

Van der Linden's (2007, Psychometrika, 72, 287) hierarchical model for responses and response times in tests has numerous applications in psychological assessment. The success of these applications requires the parameters of the model to have been estimated without bias. The data used for model fitting, however, are often contaminated, for example, by rapid guesses or lapses of attention. This distorts the parameter estimates. In the present paper, a novel estimation approach is proposed that is robust against contamination. The approach consists of two steps. In the first step, the response time model is fitted on the basis of a robust estimate of the covariance matrix. In the second step, the item response model is extended to a mixture model, which allows for a proportion of irregular responses in the data. The parameters of the mixture model are then estimated with a modified marginal maximum likelihood estimator. The modified marginal maximum likelihood estimator downweights responses of test-takers with unusual response time patterns. As a result, the estimator is resistant to several forms of data contamination. The robustness of the approach is investigated in a simulation study. An application of the estimator is demonstrated with real data.

Analysing model fit of psychometric process models: An overview, a new test and an application to the diffusion model.

Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. MODEL: , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions.

(Non-)symbolic magnitude processing in children with mathematical difficulties: A meta-analysis.

Symbolic and non-symbolic magnitude representations, measured by digit or dot comparison tasks, are assumed to underlie the development of arithmetic skills. The comparison distance effect (CDE) has been suggested as a hallmark of the preciseness of mental magnitude representations. It implies that two magnitudes are harder to discriminate when the numerical distance between them is small, and may therefore differ in children with mathematical difficulties (MD), i.e. low mathematical achievement or dyscalculia. However, empirical findings on the CDE in children with MD are heterogeneous, and only few studies assess both symbolic and non-symbolic skills. This meta-analysis therefore integrates 44 symbolic and 48 non-symbolic response time (RT) outcomes reported in nineteen studies (N=1630 subjects, aged 6-14 years). Independent of age, children with MD show significantly longer mean RTs than typically achieving controls, particularly on symbolic (Hedges' g=0.75; 95% CI [0.51; 0.99]), but to a significantly lower extent also on non-symbolic (g=0.24; 95% CI [0.13; 0.36]) tasks. However, no group differences were found for the CDE. Extending recent work, these meta-analytical findings on children with MD corroborate the diagnostic importance of magnitude comparison speed in symbolic tasks. By contrast, the validity of CDE measures in assessing MD is questioned.

Comorbidity of Arithmetic and Reading Disorder.

The aim of the present study was to investigate the cognitive profiles of primary school children (age 82-133 months) on a battery of basic number processing and calculation tasks. The sample consisted of four groups matched for age and IQ: arithmetic disorder only (AD; n = 20), reading disorder only (RD; n = 40), a comorbid group ( n = 27), and an unimpaired control group ( n = 40). Multiple 2 (RD vs. No RD) × 2 (AD vs. No AD) factorial ANCOVAs showed that children with RD had selective impairments in counting and number transcoding efficiency. In contrast, children with AD performed poorly in most tasks, including symbolic and nonsymbolic magnitude comparisons, subitizing, number line estimation, number sets, number transcoding accuracy, and calculation. These findings provide further support that AD is characterized by multiple, heterogeneous underlying deficits. In contrast, RD is associated with specific number processing impairments only if tasks require verbal processing. Taken together, the results fully support the assumption of comorbid additivity of AD and RD.

A Diffusion Model Analysis of Magnitude Comparison in Children with and without Dyscalculia: Care of Response and Ability Are Related to Both Mathematical Achievement and Stimuli.

The respective roles of the approximate number system (ANS) and an access deficit (AD) in developmental dyscalculia (DD) are not well-known. Most studies rely on response times (RTs) or accuracy (error rates) separately. We analyzed the results of two samples of elementary school children in symbolic magnitude comparison (MC) and non-symbolic MC using a diffusion model. This approach uses the joint distribution of both RTs and accuracy in order to synthesize measures closer to ability and response caution or response conservatism. The latter can be understood in the context of the speed-accuracy tradeoff: It expresses how much a subject trades in speed for improved accuracy. We found significant effects of DD on both ability (negative) and response caution (positive) in MC tasks and a negative interaction of DD with symbolic task material on ability. These results support that DD subjects suffer from both an impaired ANS and an AD and in particular support that slower RTs of children with DD are indeed related to impaired processing of numerical information. An interaction effect of symbolic task material and DD (low mathematical ability) on response caution could not be refuted. However, in a sample more representative of the general population we found a negative association of mathematical ability and response caution in symbolic but not in non-symbolic task material. The observed differences in response behavior highlight the importance of accounting for response caution in the analysis of MC tasks. The results as a whole present a good example of the benefits of a diffusion model analysis.

Basic numerical processing, calculation, and working memory in children with dyscalculia and/or ADHD symptoms.

Objective: Deficits in basic numerical skills, calculation, and working memory have been found in children with developmental dyscalculia (DD) as well as children with attention-deficit/hyperactivity disorder (ADHD). This paper investigates cognitive profiles of children with DD and/or ADHD symptoms (AS) in a double dissociation design to obtain a better understanding of the comorbidity of DD and ADHD. Method: Children with DD-only (N = 33), AS-only (N = 16), comorbid DD+AS (N = 20), and typically developing controls (TD, N = 40) were assessed on measures of basic numerical processing, calculation, working memory, processing speed, and neurocognitive measures of attention. Results: Children with DD (DD, DD+AS) showed deficits in all basic numerical skills, calculation, working memory, and sustained attention. Children with AS (AS, DD+AS) displayed more selective difficulties in dot enumeration, subtraction, verbal working memory, and processing speed. Also, they generally performed more poorly in neurocognitive measures of attention, especially alertness. Children with DD+AS mostly showed an additive combination of the deficits associated with DD-only and A_Sonly, except for subtraction tasks, in which they were less impaired than expected. Conclusions: DD and AS appear to be related to largely distinct patterns of cognitive deficits, which are present in combination in children with DD+AS.

Clinical trial on tonal tinnitus with tailor-made notched music training.

BACKGROUND: Tinnitus is a result of hyper-activity/hyper-synchrony of auditory neurons coding the tinnitus frequency, which has developed due to synchronous mass activity owing to the lack of inhibition. We assume that removal of exactly these frequencies from a complex auditory stimulus will cause the brain to reorganize around tonotopic regions coding the tinnitus frequency through inhibition-induced plasticity. Based on this assumption, a novel treatment for tonal tinnitus--tailor-made notched music training (TMNMT)--has been introduced and was tested in this clinical trial. METHODS: A randomized controlled trial in parallel group design was performed in a double-blinded manner. We included 100 participants with chronic, tonal tinnitus who listened to tailor-made notched music for two hours a day for three consecutive months. Our primary outcome measures were the Tinnitus Handicap Questionnaire and Visual Analog Scales measuring perceived tinnitus loudness, awareness, distress and handicap. Participants rated their tinnitus before and after the training as well as one month after cessation of the training. RESULTS: While no effect was found for the primary outcome measures, tinnitus distress, as measured by the Tinnitus Questionnaire, a secondary outcome measure, developed differently in the two groups. The treatment group showed higher distress scores while the placebo group revealed lower distress scores after the training. However, this effect did not reach significance in post-hoc analysis and disappeared at follow-up measurements. At follow-up, tinnitus loudness in the treatment group was significantly reduced as compared to the control group. Post hoc analysis, accounting for low reliability scores in the Visual Analog Scales, showed a significant reduction of the overall Visual Analog Scale mean score in the treatment group even at the post measurement. CONCLUSION: This is the first study on TMNMT that was planned and conducted following the CONSORT statement standards for clinical trials. The current work is one more step towards a final evaluation of TMNMT. Already after three months the effect of training with tailor-made notched music is observable in the most direct rating of tinnitus perception - the tinnitus loudness, while more global measures of tinnitus distress do not show relevant changes. TRIAL REGISTRATION: Current Controlled Trials ISRCTN04840953; Trial registration date: 17.07.2013.

Limited information estimation of the diffusion-based item response theory model for responses and response times.

Psychological tests are usually analysed with item response models. Recently, some alternative measurement models have been proposed that were derived from cognitive process models developed in experimental psychology. These models consider the responses but also the response times of the test takers. Two such models are the Q-diffusion model and the D-diffusion model. Both models can be calibrated with the diffIRT package of the R statistical environment via marginal maximum likelihood (MML) estimation. In this manuscript, an alternative approach to model calibration is proposed. The approach is based on weighted least squares estimation and parallels the standard estimation approach in structural equation modelling. Estimates are determined by minimizing the discrepancy between the observed and the implied covariance matrix. The estimator is simple to implement, consistent, and asymptotically normally distributed. Least squares estimation also provides a test of model fit by comparing the observed and implied covariance matrix. The estimator and the test of model fit are evaluated in a simulation study. Although parameter recovery is good, the estimator is less efficient than the MML estimator.

A Mixture Proportional Hazards Model With Random Effects for Response Times in Tests.

In this article, a new model for test response times is proposed that combines latent class analysis and the proportional hazards model with random effects in a similar vein as the mixture factor model. The model assumes the existence of different latent classes. In each latent class, the response times are distributed according to a class-specific proportional hazards model. The class-specific proportional hazards models relate the response times of each subject to his or her work pace, which is considered as a random effect. The latent class extension of the proportional hazards model allows for differences in response strategies between subjects. The differences can be captured in the hazard functions, which trace the progress individuals make over time when working on an item. The model can be calibrated with marginal maximum likelihood estimation. The fit of the model can either be assessed with information criteria or with a test of model fit. In a simulation study, the performance of the proposed approaches to model calibration and model evaluation is investigated. Finally, the model is used for a real data set.

A Race Model for Responses and Response Times in Tests.

Latent trait models for responses and response times in tests are often pure statistical models without a close connection to features of the assumed response process. In the present paper, a new model is presented that is more closely related to assumptions about the response process. The model is based on two increasing stochastic processes. Each stochastic process represents the accumulation of knowledge with respect to one of two response options, the correct and incorrect response. Both accumulators compete and the accumulator that first exceeds a critical level determines the response. General assumptions about the accumulators result in a race between two response times that follow a bivariate Birnbaum Saunders distribution. The model can be calibrated with marginal maximum likelihood estimation. Feasibility of the estimation approach is demonstrated in a simulation study. Additionally, a test of model fit is proposed. Finally, the model will be used for the analysis of an empirical data set.

Number sense or working memory? The effect of two computer-based trainings on mathematical skills in elementary school.

Research on the improvement of elementary school mathematics has shown that computer-based training of number sense (e.g., processing magnitudes or locating numbers on the number line) can lead to substantial achievement gains in arithmetic skills. Recent studies, however, have highlighted that training domain-general cognitive abilities (e.g., working memory [WM]) may also improve mathematical achievement. This study addressed the question of whether a training of domain-specific number sense skills or domain-general WM abilities is more appropriate for improving mathematical abilities in elementary school. Fifty-nine children (M age = 9 years, 32 girls and 27 boys) received either a computer-based, adaptive training of number sense (n = 20), WM skills (n = 19), or served as a control group (n = 20). The training duration was 20 min per day for 15 days. Before and after training, we measured mathematical ability using a curriculum-based math test, as well as spatial WM. For both training groups, we observed substantial increases in the math posttest compared to the control group (d = .54 for number sense skills training, d = .57 for WM training, respectively). Whereas the number sense group showed significant gains in arithmetical skills, the WM training group exhibited marginally significant gains in word problem solving. However, no training group showed significant posttest gains on the spatial WM task. Results indicate that a short training of either domain-specific or domain-general skills may result in reliable short-term training gains in math performance, although no stable training effects were found in the spatial WM task.

An accumulator model for responses and response times in tests based on the proportional hazards model.

Latent trait models for responses and response times in tests often lack a substantial interpretation in terms of a cognitive process model. This is a drawback because process models are helpful in clarifying the meaning of the latent traits. In the present paper, a new model for responses and response times in tests is presented. The model is based on the proportional hazards model for competing risks. Two processes are assumed, one reflecting the increase in knowledge and the second the tendency to discontinue. The processes can be characterized by two proportional hazards models whose baseline hazard functions correspond to the temporary increase in knowledge and discouragement. The model can be calibrated with marginal maximum likelihood estimation and an application of the ECM algorithm. Two tests of model fit are proposed. The amenability of the proposed approaches to model calibration and model evaluation is demonstrated in a simulation study. Finally, the model is used for the analysis of two empirical data sets.

Evaluating cognitive theory: a joint modeling approach using responses and response times.

In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of accuracy scores and response times of cognitive tests with a rule-based design. The model is capable of simultaneously estimating ability and speed on the person side as well as difficulty and time intensity on the task side, thus dissociating information that is often confounded in current analysis procedures. Further, by integrating design matrices on the task side, it becomes possible to assess the effects of design parameters (e.g., cognitive processes) on both task difficulty and time intensity, offering deeper insights into the task structure. A Bayesian approach, using Markov Chain Monte Carlo methods, has been developed to estimate the model. An application of the model in the context of educational assessment is illustrated using a large-scale investigation of figural reasoning ability.