Socio-economic status, mastery-approach goals and learning-related outcomes: Mediation and moderation.

BACKGROUND: Socio-economic status is one of the most important factors shaping students' motivation and achievement but has seldom been explored in relation to achievement goals. AIMS: This study aimed to investigate whether mastery-approach goals explain the link between SES and key learning-related outcomes (mediation) and whether SES modifies the relationship between mastery-approach goals and these outcomes (moderation). SAMPLE: Data came from 595,444 students nested in 21,322 schools across 77 countries. METHODS: Data were analysed using multilevel-moderated mediation analyses. RESULTS: We found significant mediation and moderation. In terms of mediation, mastery-approach goals mediated the association between family SES and learning-related outcomes. However, a different pattern emerged for school SES, as students in higher SES schools had lower mastery-approach goals. In terms of moderation, we found that family SES strengthened the association between mastery-approach goals and learning-related outcomes. However, the association between mastery-approach goals and learning-related outcomes was weaker in higher SES schools. CONCLUSION: Theoretical and practical implications for the achievement goal approach to achievement motivation are discussed.

Biclustering of Log Data: Insights from a Computer-Based Complex Problem Solving Assessment.

Computer-based assessments provide the opportunity to collect a new source of behavioral data related to the problem-solving process, known as log file data. To understand the behavioral patterns that can be uncovered from these process data, many studies have employed clustering methods. In contrast to one-mode clustering algorithms, this study utilized biclustering methods, enabling simultaneous classification of test takers and features extracted from log files. By applying the biclustering algorithms to the "Ticket" task in the PISA 2012 CPS assessment, we evaluated the potential of biclustering algorithms in identifying and interpreting homogeneous biclusters from the process data. Compared with one-mode clustering algorithms, the biclustering methods could uncover clusters of individuals who are homogeneous on a subset of feature variables, holding promise for gaining fine-grained insights into students' problem-solving behavior patterns. Empirical results revealed that specific subsets of features played a crucial role in identifying biclusters. Additionally, the study explored the utilization of biclustering on both the action sequence data and timing data, and the inclusion of time-based features enhanced the understanding of students' action sequences and scores in the context of the analysis.

Analysis of applying a patient safety taxonomy to patient and clinician-reported incident reports during the COVID-19 pandemic: a mixed methods study.

BACKGROUND: The COVID-19 pandemic resulted in major disruption to healthcare delivery worldwide causing medical services to adapt their standard practices. Learning how these adaptations result in unintended patient harm is essential to mitigate against future incidents. Incident reporting and learning system data can be used to identify areas to improve patient safety. A classification system is required to make sense of such data to identify learning and priorities for further in-depth investigation. The Patient Safety (PISA) classification system was created for this purpose, but it is not known if classification systems are sufficient to capture novel safety concepts arising from crises like the pandemic. We aimed to review the application of the PISA classification system during the COVID-19 pandemic to appraise whether modifications were required to maintain its meaningful use for the pandemic context. METHODS: We conducted a mixed-methods study integrating two phases in an exploratory, sequential design. This included a comparative secondary analysis of patient safety incident reports from two studies conducted during the first wave of the pandemic, where we coded patient-reported incidents from the UK and clinician-reported incidents from France. The findings were presented to a focus group of experts in classification systems and patient safety, and a thematic analysis was conducted on the resultant transcript. RESULTS: We identified five key themes derived from the data analysis and expert group discussion. These included capitalising on the unique perspective of safety concerns from different groups, that existing frameworks do identify priority areas to investigate further, the objectives of a study shape the data interpretation, the pandemic spotlighted long-standing patient concerns, and the time period in which data are collected offers valuable context to aid explanation. The group consensus was that no COVID-19-specific codes were warranted, and the PISA classification system was fit for purpose. CONCLUSIONS: We have scrutinised the meaningful use of the PISA classification system's application during a period of systemic healthcare constraint, the COVID-19 pandemic. Despite these constraints, we found the framework can be successfully applied to incident reports to enable deductive analysis, identify areas for further enquiry and thus support organisational learning. No new or amended codes were warranted. Organisations and investigators can use our findings when reviewing their own classification systems.

Longitudinal Assessment of Botulinum Toxin Treatment for Lateral Trunk Flexion and Pisa Syndrome in Parkinson's Disease: Real-life, Long-Term Study.

Lateral trunk flexion (LTF) and its severe form, called Pisa syndrome (PS), are highly invalidating axial postural abnormalities associated with Parkinson's disease (PD). Management strategies for LTF lack strong scientific evidence. We present a real-life, longitudinal study evaluating long-term efficacy of botulinum toxin (BoNT) injections in axial muscles to reduce LTF and PS in PD. A total of 13 PD patients with LTF > 5° received ultrasound- and electromyography-guided BoNT injections every 4 months. Seven untreated matched PD patients with LTF served as controls and their changes in posture after 18 months were compared with those of seven patients continuing BoNT over 12 months. 53.8% of patients continued the BoNT injections for at least 12 months. Various individual LTF responses were observed. Overall, BoNT-treated patients obtained a not statistically significant improvement of LTF of 17 ± 41% (p = 0.237). In comparison, the seven untreated PD patients suffered a deterioration in LTF over 12 months by 36 ± 45% (p = 0.116), showing a significantly different trajectory of posture change (p = 0.026). In conclusion, repeated BoNT injections in axial muscles showed varying effects in managing PD-associated LTF, suggesting that: (a) a relevant number of patients with LTF can benefit from BoNT; (b) long-term treatment could prevent LTF worsening; (c) an instrumented, personalized approach is important; and (d) there is a need for prospective, long-term studies.

What cultural values determine student self-efficacy? An empirical study for 42 countries and economies.

Self-efficacy is a vital personal characteristic for student success. However, the challenge of cross-cultural comparisons remains as scalar invariance is hard to be satisfied. Also, it is unclear how to contextually understand student self-efficacy in light of cultural values in different countries. This study implements a novel alignment optimization method to rank the latent means of student self-efficacy of 308,849 students in 11,574 schools across 42 countries and economies that participated in the 2018 Program in International Student Assessment. We then used classification and regression trees to classified countries with differential latent means of student self-efficacy into groups according to Hofstede's six cultural dimensions theory. The results of the alignment method recovered that Albania, Colombia, and Peru had students with the highest mean self-efficacy, while Slovak Republic, Moscow Region (RUS), and Lebanon had the lowest. Moreover, the CART analysis indicated a low student self-efficacy for countries presenting three features: (1) extremely high power distance; (2) restraint; and (3) collectivism. These findings theoretically highlighted the significance of cultural values in shaping student self-efficacy across countries and practically provided concrete suggestions to educators on which countries to emulate such that student self-efficacy could be promoted and informed educators in secondary education institutes on the international expansion of academic exchanges.

Do women's empowerment and self-expression values change adolescents' gendered occupational expectations? Longitudinal evidence against the gender-equality paradox from 26 European countries.

Despite the increases in women's educational attainment in recent decades, female labor market participation and labor market returns are still lower than those of their male counterparts. Among the main factors explaining this persistence of economic inequality is the persistently gendered nature of occupational expectations, which results in gender segregation of labor. In this paper, we describe how gender-specific adolescents' occupational expectations change over time (2006-2018) and how women's empowerment and cultural norms might influence gender-specific occupational expectations. Against the backdrop of the research on the gender-equality paradox and from a comparative perspective, we focus on national and institutional characteristics to investigate how individual and national factors explain gendered occupational expectations. We answer our research questions by applying a two-step multilevel model with fixed effects. For this, we used PISA data and merged them with state-level information from 26 European countries. We add to existing research by making three contributions. First, we describe the changes in occupational expectations over time within European countries by looking at the gender composition of the desired occupation and distinguishing three categories (gender-typical, gender-balanced, and gender-atypical). Second, we investigate the relationship between national characteristics and the evolution of gendered occupational expectations separately by gender to reveal gender-specific mechanisms. Third, by using data from two-time points, we explore which national-level changes lead to changes in students' occupational expectations. Our first descriptive results show that the patterns of how students' occupational expectations change over time differ remarkably between countries. In 2018 in some countries, students' occupational expectations became more segregated while in others the number of students with gender-balanced or gender-atypical expectations increased. Our fixed effects models show that women's empowerment and self-expression value explained variance over time. For example, women's empowerment measured via an increase in women's employment and participation in parliament led to less gender-typical occupational expectations among girls and boys. Similarly, a rise in self-expression values led to less gender-typical occupational expectations, again for both boys and girls. Remarkably, our results do not verify the gender-equality paradox for occupational expectations, as is the case in previous cross-sectional analyses.

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software.

Background: Software-based measurements of axial postural abnormalities in Parkinson's disease (PD) are the gold standard but may be time-consuming and not always feasible in clinical practice. An automatic and reliable software to accurately obtain real-time spine flexion angles according to the recently proposed consensus-based criteria would be a useful tool for both research and clinical practice. Objective: We aimed to develop and validate a new software based on Deep Neural Networks to perform automatic measures of PD axial postural abnormalities. Methods: A total of 76 pictures from 55 PD patients with different degrees of anterior and lateral trunk flexion were used for the development and pilot validation of a new software called AutoPosturePD (APP); postural abnormalities were measured in lateral and posterior view using the freeware NeuroPostureApp (gold standard) and compared with the automatic measurement provided by the APP. Sensitivity and specificity for the diagnosis of camptocormia and Pisa syndrome were assessed. Results: We found an excellent agreement between the new APP and the gold standard for lateral trunk flexion (intraclass correlation coefficient [ICC] 0.960, IC95% 0.913-0.982, P < 0.001), anterior trunk flexion with thoracic fulcrum (ICC 0.929, IC95% 0.846-0.968, P < 0.001) and anterior trunk flexion with lumbar fulcrum (ICC 0.991, IC95% 0.962-0.997, P < 0.001). Sensitivity and specificity were 100% and 100% for detecting Pisa syndrome, 100% and 95.5% for camptocormia with thoracic fulcrum, 100% and 80.9% for camptocormia with lumbar fulcrum. Conclusions: AutoPosturePD is a valid tool for spine flexion measurement in PD, accurately supporting the diagnosis of Pisa syndrome and camptocormia.

Beyond the Covid-19 pandemic: remote learning and education inequalities.

Is remote learning associated with education inequalities? We use PISA 2018 data from five European countries-France, Germany, Italy, Spain and the United Kingdom-to investigate whether education outcomes are related to the possession of the resources needed for distance learning. After controlling for a wide set of covariates, fixed effects, different specifications and testing the stability of coefficients, we find that remote learning is positively associated with average education outcomes, but also with strong and significant education inequalities. Our results show that negative gaps are larger where online schooling is more widespread, across countries, locations, and school types. More generally, remote learning inequalities appear to be associated with technological network externalities: they increase as digital education spreads. Policy makers must guarantee to all students and schools the possession of the resources needed for remote learning, but to reach this goal efficiently they must adapt their actions to the characteristics of countries, areas and school systems. Supplementary Information: The online version contains supplementary material available at 10.1007/s10663-022-09556-7.

Establishing Pandemic Influenza Severity Assessment (PISA) parameters and thresholds for Canada's FluWatch program.

Background: The World Health Organization (WHO) developed a structured framework to enable countries to rapidly assess the severity of an influenza pandemic. This framework, the Pandemic Influenza Severity Assessment (PISA), is intended to be performed weekly during seasonal epidemics so that assessing influenza severity during a pandemic can be done with greater ease and efficiency. Objective: Using influenza surveillance indicators within Canada's FluWatch program from seasons 2014-2015 to 2018-2019, national PISA thresholds were developed and assessed against seasonal data for seasons 2019-2020 to June of 2022-2023. Outcomes: Canada developed thresholds for each required indicator (transmissibility, seriousness of disease and impact) for multiple WHO-recommended parameters. The thresholds were assessed against four seasons, and it was determined that there was a good agreement between the PISA assessments and the characterization of the season by FluWatch epidemiologists. Conclusion: With confidence in the validity of the PISA thresholds, the FluWatch program will begin to share PISA assessments weekly through the FluWatch report in the 2023-2024 seasons to help characterize influenza activity in Canada and inform responses to the seasonal influenza epidemic.

Exploring the Multiverse of Analytical Decisions in Scaling Educational Large-Scale Assessment Data: A Specification Curve Analysis for PISA 2018 Mathematics Data.

In educational large-scale assessment (LSA) studies such as PISA, item response theory (IRT) scaling models summarize students' performance on cognitive test items across countries. This article investigates the impact of different factors in model specifications for the PISA 2018 mathematics study. The diverse options of the model specification also firm under the labels multiverse analysis or specification curve analysis in the social sciences. In this article, we investigate the following five factors of model specification in the PISA scaling model for obtaining the two country distribution parameters; country means and country standard deviations: (1) the choice of the functional form of the IRT model, (2) the treatment of differential item functioning at the country level, (3) the treatment of missing item responses, (4) the impact of item selection in the PISA test, and (5) the impact of test position effects. In our multiverse analysis, it turned out that model uncertainty had almost the same impact on variability in the country means as sampling errors due to the sampling of students. Model uncertainty had an even larger impact than standard errors for country standard deviations. Overall, each of the five specification factors in the multiverse analysis had at least a moderate effect on either country means or standard deviations. In the discussion section, we critically evaluate the current practice of model specification decisions in LSA studies. It is argued that we would either prefer reporting the variability in model uncertainty or choosing a particular model specification that might provide the strategy that is most valid. It is emphasized that model fit should not play a role in selecting a scaling strategy for LSA applications.

Unequal expectations? Testing decisional mechanisms for secondary effects of social origin.

It is a common research practice to decompose the effect of social origin on an educational expectation into a primary effect, via academic performance, and a secondary effect, computed as the inequality that survives the control of performance. In this paper, I examine how specific decisional mechanisms described in the Cultural Capital and Rational Action theories contribute to explain the inequalities that survive the control of performance in the configuration of educational expectations. Cultural Capital Theory argues that participation in the dominant culture at schools, the endowment of educational resources and the development of skill-generating habits contribute to holding ambitious expectations over and above performance. In Rational Action Theory, students form expectations at each level of performance by gathering information, pondering benefits and costs, and evaluating the risk of academic failure and social demotion, which in turn might account for the secondary effect of social origin. Relying on Spanish data from 2018 PISA, I observe that Cultural Capital and Rational Action mechanisms are compatible in the explanation of the secondary effects of social origin, although two-thirds of that inequality remain unexplained. Nonetheless, I find differences in how those mechanisms perform in vertical (whether to enrol an educational level) and horizontal expectations (what alternative is preferred in that educational level).

On the Treatment of Missing Item Responses in Educational Large-Scale Assessment Data: An Illustrative Simulation Study and a Case Study Using PISA 2018 Mathematics Data.

Missing item responses are prevalent in educational large-scale assessment studies such as the programme for international student assessment (PISA). The current operational practice scores missing item responses as wrong, but several psychometricians have advocated for a model-based treatment based on latent ignorability assumption. In this approach, item responses and response indicators are jointly modeled conditional on a latent ability and a latent response propensity variable. Alternatively, imputation-based approaches can be used. The latent ignorability assumption is weakened in the Mislevy-Wu model that characterizes a nonignorable missingness mechanism and allows the missingness of an item to depend on the item itself. The scoring of missing item responses as wrong and the latent ignorable model are submodels of the Mislevy-Wu model. In an illustrative simulation study, it is shown that the Mislevy-Wu model provides unbiased model parameters. Moreover, the simulation replicates the finding from various simulation studies from the literature that scoring missing item responses as wrong provides biased estimates if the latent ignorability assumption holds in the data-generating model. However, if missing item responses are generated such that they can only be generated from incorrect item responses, applying an item response model that relies on latent ignorability results in biased estimates. The Mislevy-Wu model guarantees unbiased parameter estimates if the more general Mislevy-Wu model holds in the data-generating model. In addition, this article uses the PISA 2018 mathematics dataset as a case study to investigate the consequences of different missing data treatments on country means and country standard deviations. Obtained country means and country standard deviations can substantially differ for the different scaling models. In contrast to previous statements in the literature, the scoring of missing item responses as incorrect provided a better model fit than a latent ignorable model for most countries. Furthermore, the dependence of the missingness of an item from the item itself after conditioning on the latent response propensity was much more pronounced for constructed-response items than for multiple-choice items. As a consequence, scaling models that presuppose latent ignorability should be refused from two perspectives. First, the Mislevy-Wu model is preferred over the latent ignorable model for reasons of model fit. Second, in the discussion section, we argue that model fit should only play a minor role in choosing psychometric models in large-scale assessment studies because validity aspects are most relevant. Missing data treatments that countries can simply manipulate (and, hence, their students) result in unfair country comparisons.

Factors Related with Underperformance in Reading Proficiency, the Case of the Programme for International Student Assessment 2018.

Almost 217 million secondary school students (60% of the world's adolescents) do not reach minimum levels in reading proficiency at the end of secondary school, according to objective 4.1 of the UN's Sustainable Development Goals. Therefore, the early and efficient identification of this disadvantage and implementation of remedial strategies is critical for economies. In 2018, the Programme for International Student Assessment (PISA) assessed the reading skills of 15-year-old students in 80 countries and economies. This work introduces a methodology that uses PISA's data to build logistic regression models to identify the main factors contributing to students' underperforming reading skills. Results showed that socioeconomic status (SES), metacognition strategies, Information and Communication Technology (ICT) skills, and student-teacher relationships are the most important contributors to low reading abilities.

Performance decline in a low-stakes test at age 15 and educational attainment at age 25: Cross-country longitudinal evidence.

INTRODUCTION: Educational attainment is associated with important life outcomes including labour market performance, health status, well-being, civic and political participation. An important question is whether it is possible to identify early those students who lack the achievement motivation that is needed to complete a higher education degree. METHODS: Longitudinal follow-ups of representative samples of participants in the 2000 and 2003 Programme for International Student Assessment (PISA) from Australia, Denmark and Switzerland (N = 3110; 1130; and 1962; age = 15 to 27; % females 51%, 51%, 49%; ethnicity/race unknown) were used to identify the association between a measure of effort on a cognitively demanding low-stake task at age 15 - performance decline during the test - and educational attainment at age 25-27. RESULTS: A one SD difference in performance decline was associated with a 5-6 percentage point difference in the probability of obtaining tertiary-level qualifications (r = -0.15 in Australia; -0.11 in Denmark and -0.11 in Switzerland). We find no evidence of differences in this relationship across genders, socio-economic status and baseline levels of ability in the three countries. The association between performance decline and educational attainment is homogeneous across these groups. Self-reported measures of achievement motivation were not predictive of educational attainment in the three countries. CONCLUSIONS: Our work contributes new longitudinal evidence to the body of research in education employing behavioural measures of motivation and engagement. It can be used to understand the potential long-term consequences of disparities in students' preparation to sustain effort over cognitively demanding tasks.

Differential Item Functioning Among English Language Learners on a Large-Scale Mathematics Assessment.

The current study research showed the nature and potential sources of the gaps in mathematics achievement between English language learners (ELLs) and non-English language learners (non-ELLs). The nature of achievement gap was examined using three DIF methodologies: including Mantel-Haenszel procedure, Rasch model, and Hierarchical Generalized Linear Model (HGLM). These were conducted at the item level in contrast to total test level. Results revealed that the three DIF approaches identified 10 common items. These 10 items demonstrated in favor of non-ELLs. Findings from this study will help educational researchers, administrators, and policymakers understand the nature of the achievement gap in mathematics at item level so that United States can be competitive in middle school mathematics education. This study also suggested that item writers and test developers should construct assessments where language is equally accessible for ELL students.

Computational Analysis of Virtual Echocardiographic Assessment of Functional Mitral Regurgitation for Validation of Proximal Isovelocity Surface Area Methods.

BACKGROUND: Mitral regurgitation (MR) quantification by the proximal isovelocity surface area (PISA) method remains challenging. Using computer models, the authors evaluated the accuracy of different PISA methods and quantified their errors. METHODS: Five functional MR computer models of different geometric and tethering abnormalities were created, validated, and treated as phantom models, from which the reference values were directly obtained. Virtual two-dimensional (2D) PISA and three-dimensional (3D) PISA (both peak and integrated values) were performed on these phantom models. By comparing virtual PISA results with reference values, the accuracy of different PISA methods was evaluated, and their sources of errors were quantified. RESULTS: Compared with reference values of regurgitant flow rate, excellent correlations were found for true PISA (r = 0.99, bias = 32.3 ± 35.3 mL/sec), 3D PISA (r = 0.97, bias = -24.4 ± 55.5 mL/sec), followed by multiplane 2D hemicylindrical PISA (r = 0.88, bias = -24.1 ± 85.4 mL/sec) and hemiellipsoidal PISA (r = 0.91, bias = -55.7 ± 96.6 mL/sec). Weaker correlations were found for single-plane 2D hemispherical PISA (parasternal long-axis: r = 0.71, bias = -77.6 ± 124.5 mL/sec; apical two-chamber: r = 0.69, bias = -52.0 ± 122.0 mL/sec; apical four-chamber: r = 0.82, bias = -65.5 ± 107.3 mL/sec). For regurgitant volume quantification, integrated PISA was more accurate than peak PISA. The bias of 3D PISA improved from -12.7 ± 7.8 mL (peak PISA) to -2.1 ± 5.3 mL (integrated PISA). CONCLUSIONS: For functional MR quantification, 2D hemispherical PISA had significant underestimation, multiplane 2D hemiellipsoidal and hemicylindrical PISA showed improved accuracy, and 3D PISA was the most accurate. The PISA method is subject to both systematic underestimation due to the Doppler angle effect and systematic overestimation when regurgitant flow is not perpendicular to PISA contour. Integrated PISA is able to capture dynamic MR and is therefore more accurate than peak PISA. The sum of regurgitant flow rates is the most feasible way to perform integrated PISA.

Improving the Precision of Ability Estimates Using Time-On-Task Variables: Insights From the PISA 2012 Computer-Based Assessment of Mathematics.

Log-file data from computer-based assessments can provide useful collateral information for estimating student abilities. In turn, this can improve traditional approaches that only consider response accuracy. Based on the amounts of time students spent on 10 mathematics items from the PISA 2012, this study evaluated the overall changes in and measurement precision of ability estimates and explored country-level heterogeneity when combining item responses and time-on-task measurements using a joint framework. Our findings suggest a notable increase in precision with the incorporation of response times and indicate differences between countries in how respondents approached items as well as in their response processes. Results also showed that additional information could be captured through differences in the modeling structure when response times were included. However, such information may not reflect the testing objective.

Echocardiographic assessment of mitral regurgitation: discussion of practical and methodologic aspects of severity quantification to improve diagnostic conclusiveness.

The echocardiographic assessment of mitral valve regurgitation (MR) by characterizing specific morphological features and grading its severity is still challenging. Analysis of MR etiology is necessary to clarify the underlying pathological mechanism of the valvular defect. Severity of mitral regurgitation is often quantified based on semi-quantitative parameters. However, incongruent findings and/or interpretations of regurgitation severity are frequently observed. This proposal seeks to offer practical support to overcome these obstacles by offering a standardized workflow, an easy means to identify non-severe mitral regurgitation, and by focusing on the quantitative approach with calculation of the individual regurgitant fraction. This work also indicates main methodological problems of semi-quantitative parameters when evaluating MR severity and offers appropriateness criteria for their use. It addresses the diagnostic importance of left-ventricular wall thickness, left-ventricular and left atrial volumes in relation to disease progression, and disease-related complaints to improve interpretation of echocardiographic findings. Finally, it highlights the conditions influencing the MR dynamics during echocardiographic examination. These considerations allow a reproducible, verifiable, and transparent in-depth echocardiographic evaluation of MR patients ensuring consistent haemodynamic plausibility of echocardiographic results.

Quantitative assessment of posture in healthy controls and patients with Parkinson's disease.

INTRODUCTION: A stooped posture is a main clinical feature of Parkinson's disease (PD). The assessment of posture is important to measure treatment effects. The aim of this study was to investigate the reliability of a standardized postural rating tool, to calculate minimal detectable change scores and to assess the role of gender and age. METHODS: Two independent raters assessed total camptocormia (TCC), upper camptocormia (UCC) and Pisa angles of 192 PD patients and 78 healthy controls (HC) with the free NeuroPostureApp©(http://www.neuroimaging.uni-kiel.de/NeuroPostureApp). Reliabilities and linear models were calculated for different effects. Three subgroups were defined based on two thresholds (mean+2SD of HC and PD): A) normal, B) presumed stooped/lateral bended posture and C) postural disorder. RESULTS: Intraclass correlation coefficients ranged between 0.71 and 0.95 for the interrater and test-retest reliability of the three angles. The minimal detectable change values in the PD patients were 3.7°, 6.7° and 2.1° for the TCC, UCC and Pisa angles, respectively. Men had a more stooped posture than women (p < 0.05). Patients with PD had a worse posture than HC (p < 0.001) in all three angles. For the TCC angle, 39.1% of the patients had a normal posture (<17.4°), 47.9% a presumed stooped posture (>17.4°, <30.2°) and 6.3° had camptocormia (>30.2°). CONCLUSIONS: The NeuroPostureApp© is reliable. Our results confirmed gender differences and the progression of postural deviation in PD patients with age and empirically support the ≥30° TCC angle as a defining criterium for camptocormia. Diagnostic criteria for UCC and Pisa syndrome should be further explored in future studies.

A latent topic model with Markov transition for process data.

We propose a latent topic model with a Markov transition for process data, which consists of time-stamped events recorded in a log file. Such data are becoming more widely available in computer-based educational assessment with complex problem-solving items. The proposed model can be viewed as an extension of the hierarchical Bayesian topic model with a hidden Markov structure to accommodate the underlying evolution of an examinee's latent state. Using topic transition probabilities along with response times enables us to capture examinees' learning trajectories, making clustering/classification more efficient. A forward-backward variational expectation-maximization (FB-VEM) algorithm is developed to tackle the challenging computational problem. Useful theoretical properties are established under certain asymptotic regimes. The proposed method is applied to a complex problem-solving item in the 2012 version of the Programme for International Student Assessment (PISA).