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

Objective We describe the development of a new computer adaptive vocabulary test, Mobile Toolbox (MTB) Word Meaning, and validity evidence from 3 studies. Method Word Meaning was designed to be a multiple-choice synonym test optimized for self-administration on a personal smartphone. The items were first calibrated online in a sample of 7,525 participants to create the computer-adaptive test algorithm for the Word Meaning measure within the MTB app. In Study 1, 92 participants self-administered Word Meaning on study-provided smartphones in the lab and were administered external measures by trained examiners. In Study 2, 1,021 participants completed the external measures in the lab and Word Meaning was self-administered remotely on their personal smartphones. In Study 3, 141 participants self-administered Word Meaning remotely twice with a 2-week delay on personal iPhones. Results The final bank included 1363 items. Internal consistency was adequate to good across samples (ρxx = 0.78 to 0.81, p  < .001). Test–retest reliability was good (ICC = 0.65, p  < .001), and the mean theta score was not significantly different upon the second administration. Correlations were moderate to large with measures of similar constructs (ρ = 0.67–0.75, p  < .001) and non-significant with measures of dissimilar constructs. Scores demonstrated small to moderate correlations with age (ρ = 0.35 to 0.45, p  < .001) and education (ρ = 0.26, p  < .001). Conclusion The MTB Word Meaning measure demonstrated evidence of reliability and validity in three samples. Further validation studies in clinical samples are necessary. [ABSTRACT FROM AUTHOR]

The research aims to compare anxiety of non -native (Iraqi) Persian language learners in computer adaptive placement test of Persian grammar and vocabulary with its linear computerized test counterpart. The main concern of this study was to scrutinize the probable relationship between linear and adaptive vocabulary and grammar placement tests and testees’ anxiety (in case there is any)?" Explanatory mixed -method approach was used in the present study. The procedure for data collection was field research via the application of questionnaire and tests. The designed test was given to 48 Iraqi male and female students with the age range of 25 -40 years from Persian language center of Tarbiat Modares University, with different language levels and in two forms of adaptive and linear computerized tests. According to positive upper and lower limits of average variance, the researcher came up to the conclusion that the average of anxiety component in linear computer test is more than the average 3. The findings revealed that test anxiety level of Iraqi students in adaptive test was lower than the linear computer test. These results help to encourage teachers and educational centers to design more computer adaptive tests. [ABSTRACT FROM AUTHOR]

Educators and researchers have been interested in supporting sentence-level language comprehension for struggling readers, but it has been challenging to research. To investigate the properties of sentences that might be useful targets for future research in instruction and assessment, we coded several features of the items in a computer-adaptive scale of sentence comprehension. The Syntactic Knowledge Task is designed for students in Grades 3–10. We then explored how the features of the sentences were related to the item's difficulty value to determine which aspects of sentence-level language made sentences more and less challenging for students across a range of development. We found that genre, words that represent a logical connection, number of idea units, long words, and words on the Academic Word List were significantly associated with item difficulty. Implications for understanding students' sentence-level language development are discussed. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) is a set of problem-solving skills with high relevance in education and work contexts. The present paper explores the role of key cognitive factors underlying CT performance in non-programming university students. We collected data from 97 non-programming adults in higher education in a supervised setting. Fluid intelligence, crystallized intelligence, and visuospatial ability were assessed using computerized adaptive tests; CT was measured using the Computational Thinking test. The direct and indirect effects of gender and visuospatial ability through fluid intelligence on CT were tested in a serial multiple mediator model. Fluid intelligence predicted CT when controlling for the effects of gender, age, and visuospatial ability, while crystallized intelligence did not predict CT. Men had a small advantage in CT performance when holding the effects of cognitive abilities constant. Despite its large correlation with gender and CT, visuospatial ability did not directly influence CT performance. Overall, we found that programming-naive computational thinkers draw on their reasoning ability that does not rely on previously acquired knowledge to solve CT problems. Visuospatial ability and CT were spuriously associated. Drawing on the process overlap theory we propose that tests of fluid intelligence and CT sample an overlapping set of underlying visuospatial processes. [ABSTRACT FROM AUTHOR]

This document is a compilation of various research articles and papers related to the assessment of performance validity in neuropsychological testing. The articles cover topics such as the use of computerized assessments, the detection of feigned cognitive impairment, the development of performance validity tests, and the use of embedded validity indicators. The research explores different methods and measures for assessing performance validity and highlights the importance of accurate and reliable testing in various populations, including individuals with traumatic brain injury and children with neurological conditions. The references provide a range of perspectives and approaches to performance validity testing, and may be useful for researchers and practitioners in the field of neuropsychology. [Extracted from the article]

Background: Automated test assembly (ATA) represents a modern methodology that employs data science optimization on computer platforms to automatically create test form, thereby significantly improving the efficiency and accuracy of test assembly procedures. In the realm of medical education, large-scale high-stakes assessments often necessitate lengthy tests, leading to elevated costs in various dimensions (such as examinee fatigue and expenses associated with item development). This study aims to augment the design of the medical education assessments by leveraging modern ATA approaches. Methods: To achieve the objective, a four-step process employing psychometric methodologies was used to calibrate and analyze the item pool of the Standardized Competence Test for Clinical Medicine Undergraduates (SCTCMU), a nationwide summative test comprising 300 multiple-choice questions (MCQ) in China. Subsequently, two modern ATA approaches were employed to determine the optimal item combination, accounting for both statistical and content requirements specified in the test blueprint. The qualities of the assembled test form, generated using modern ATA approaches, underwent meticulous evaluation. Results: Through an exploration of the psychometric properties of the SCTCMU as a foundational step, the evaluation revealed commendable quality in the item properties. Furthermore, the evaluation of the quality of assembled test form using modern ATA approaches indicated the ability to ascertain the optimal test length within the predefined measurement precision. Specifically, this investigation demonstrates that the application of modern ATA approaches can substantially reduce the test length of assembled test form, while simultaneously maintaining the required statistical and content standards specified in the test blueprint. Conclusions: This study harnessed modern ATA approaches to facilitate the automatic construction of test form, thereby significantly enhancing the efficiency and precision of test assembly procedures. The utilization of modern ATA approaches offers medical educators a valuable tool to enhance the efficiency and cost-effectiveness of medical education assessment. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) contamination in agricultural soils and its accumulation in plant organs have become a global issue due to its harmful effects on human health. The in-situ stabilizing technique, which involves using organic amendments, is commonly employed for removing Cd from agricultural soils. Thus, the current study investigated the effect of vermicompost (VC) on soil properties and plant physio-biochemical attributes, leaf ultrastructure analysis, antioxidant defense mechanisms, and grain yields of two different fragrant rice cultivars, Xiangyaxiangzhan (XGZ) and Meixiangzhan-2 (MXZ-2), under Cdstress conditions. The results showed that Cd toxicity deteriorates soil quality, the plant's photosynthetic apparatus, and the plant's antioxidant defense mechanism. Moreover, under Cd stress, both cultivars produced significantly lower (p < 0.05) rice grain yields compared to non-Cd stress conditions. However, the VC application alleviated the Cd toxicity and improved soil qualitative traits, such as soil organic carbon, available nitrogen, total nitrogen, phosphorus, and potassium. Similarly, VC amendments improved leaf physiological activity, photosynthetic apparatus function, antioxidant enzyme activities and its related gene expression under Cd stress These enhancements led to increased grain yields of both fragrant under Cd toxicity. The addition of VC mitigated the adverse effects of Cd on the leaf chloroplast structure by reducing Cd uptake and accumulation in tissues. This helped prevent Cd-induced peroxidation damage to leaf membrane lipids by increasing the activities of antioxidant enzymes such as ascorbate peroxidase (APX), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD). On average across the growth stages, the Pos-Cd + VC3 treatment increased SOD, APX, CAT, and POD activities by122.2 and 112.5%, 118.6, and 120.6%, 44.6 and 40.6%, and 38.6 and 33.2% in MXZ-2 and XGZ, respectively, compared to the plants treated with Pos-Cd treated alone. Enhancements in leaf physiological activity and plant antioxidant enzyme activity strengthen the plant's antioxidant defense mechanism against Cd toxicity. In addition, correlation analysis showed a strong relationship between the leaf net photosynthetic rate and soil chemical attributes, suggesting that improved soil fertility enhances leaf physiological activity and boosts rice grain yields. Of the treatments, Pos-Cd + VC3 proved to be the most effective treatment in terms of enhancing soil health and achieving high fragrant rice yields. Thus, the outcomes of this study show that the addition of VC in Cd-contaminated soils could be useful for sustainable rice production and safe utilization of Cdpolluted soil. [ABSTRACT FROM AUTHOR]

This article explores the support needed for early-career measurement professionals in research and testing companies. It emphasizes the importance of lifelong learning and the development of technical, statistical, and computational competencies, as well as understanding social and cultural contexts in educational measurement. The authors suggest strengthening partnerships between graduate training programs and research/testing organizations and highlight the significance of intellectual humility, interdisciplinary knowledge, and ethics in the field. The article also emphasizes the need for employers to create conditions that foster the development of critical thinking, creativity, and flexibility, and stresses the importance of modeling, mentorship, advocacy, and a sense of belonging in the field. Overall, the article calls for continued collaboration and support for early-career professionals in educational measurement. [Extracted from the article]

Background: Social risk such as housing instability, trouble affording medical care and food insecurity are a downstream effect of social determinants of health (SDOHs) and are frequently associated with worse health. SDOHs include experiences of racism, sexism and other discrimination as well as differences in income and education. The collective effects of each social risk a person reports are called cumulative social risk. Cumulative social risk has traditionally been measured through counts or sum scores that treat each social risk as equivalent. We have proposed to use item response theory (IRT) as an alternative measure of person-reported cumulative social risk as IRT accounts for the severity in each risk and allows for more efficient screening with computerized adaptive testing. Methods: We conducted a differential item functioning (DIF) analysis comparing IRT-based person-reported cumulative social risk scores by income and education in a population-based sample (n = 2122). Six social risk items were analyzed using the two-parameter logistic model and graded response model. Results: Analyses showed no DIF on an IRT-based cumulative social risk score by education level for the six items examined. Statistically significant DIF was found on three items by income level but the ultimate effect on the scores was negligible. Conclusions: Results suggest an IRT-based cumulative social risk score is not biased by education and income level and can be used for comparisons between groups. An IRT-based cumulative social risk score will be useful for combining datasets to examine policy factors affecting social risk and for more efficient screening of patients for social risk using computerized adaptive testing. [ABSTRACT FROM AUTHOR]

Background and purpose: At 12 months in the phase 2 TOPAZ study, treatment with apitegromab was associated with both an improved motor function in patients with Type 2 or 3 spinal muscular atrophy (SMA) and with a favorable safety profile. This manuscript reports the extended efficacy and safety in the nonambulatory group of the TOPAZ study at 36 months. Methods: Patients who completed the primary study (NCT03921528) could enroll in an open-label extension, during which patients received apitegromab 20 mg/kg by intravenous infusion every 4 weeks. Patients were assessed periodically via the Hammersmith Functional Motor Scale-Expanded (HFMSE), Revised Upper Limb Module (RULM), World Health Organization (WHO) motor development milestones, Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT) Daily Activities and Mobility domains, and Patient-Reported Outcomes Measurement Information System (PROMIS) Fatigue questionnaire. Results: Of the 58 patients enrolled in TOPAZ, 35 were nonambulatory (mean age 7.3 years). The mean change at 36 months in HFMSE score from baseline was +4.0 (standard deviation [SD]: 7.54), and + 2.4 (3.24) for RULM score (excluding n = 7 after scoliosis surgery). Caregiver-reported outcomes (PEDI-CAT and PROMIS Fatigue) showed improvements from baseline over 36 months. In addition, most patients (28/32) improved or maintained WHO motor milestones achieved at baseline. The most frequently reported treatment-emergent adverse events were pyrexia (48.6%), nasopharyngitis (45.7%), COVID-19 infection (40.0%), vomiting (40.0%), and upper respiratory tract infection (31.4%). Conclusion: The benefit of apitegromab treatment observed at 12 months was sustained at 36 months with no new safety findings. [ABSTRACT FROM AUTHOR]

Purpose: This article describes DigiSpan, a new computer-controlled auditory test of forward and reverse digit span, designed to be administered by clinicians, and presents normative and test-retest reliability data for adults. Method: DigiSpan mimics conventional live-voice tests in that it commences with trials that ascend in length until a stopping criterion is met, giving rise to a conventional scaled score. It then administers five additional adaptive trials, the length of which depends on the correctness of the response to the previous trial. Each of these two segments of the measurement gives rise to a scaled score. The ascending and adaptive scores are averaged to give an overall score and subtracted to produce an internal measure of consistency, and hence reliability. Young adults with an Mage of 25 years (N = 163) were tested, of whom 65 were retested on a separate day. Results: The scaled scores from the conventional ascending trials were highly consistent with existing normative data based on live-voice tests. Combination of the conventional scaled score with a scaled score based on the adaptive trials led to 44% reduction in error variance for forward memory span and 20% reduction for reverse memory span. The average of these (32%) is similar to but (insignificantly) less than the 42% reduction in error variance that can be predicted based on adding the five adaptive trials. Conclusions: Replacing live-voice production of digits by a clinician with recorded, computer-controlled production has not affected the difficulty of the test. Adding five additional trials around the sequence length that a test participant can just remember has produced a decrease in measurement error. In addition, the availability of separate scaled scores for the ascending and adaptive phases enables the reliability of the combined score to be checked, for both forward and reverse measurements. The combination of standardized delivery, increased accuracy, internal reliability check, and fast automated scoring makes the test highly suitable for clinical use. [ABSTRACT FROM AUTHOR]

Aim Method Results Interpretation To refine the Gross Motor Family Report (GM‐FR) using parents' input and to evaluate its psychometric properties.In this measurement study, 12 parents of children and adolescents with cerebral palsy (CP), aged 2 to 18 years, classified in all levels of the Gross Motor Function Classification System (GMFCS), were interviewed about their experience completing the GM‐FR (content validity). Parents' feedback was used to refine the measure which was then completed by 146 families to evaluate internal consistency, and discriminative and concurrent validity. Forty‐six parents completed the GM‐FR again, 7 to 30 days later, to evaluate test–retest reliability.GM‐FR scoring, pictures, descriptions, and the total number of items were revised based on parents' feedback. The GM‐FR version 2.0 demonstrated high internal consistency (Cronbach's α = 0.99), no floor/ceiling effects, and excellent test–retest reliability (intraclass correlation coefficient = 0.99). GM‐FR scores discriminated between GMFCS levels (p < 0.05) and were strongly negatively correlated with GMFCS level (r = −0.92; p < 0.001). GM‐FR scores correlated positively and strongly with the Gross Motor Function Measure‐66 (r = 0.94; p < 0.001) and the Pediatric Evaluation of Disability Inventory – Computer Adaptive Test mobility domain (r = 0.93; p < 0.001).Active participation of families in the GM‐FR's development facilitated creation of a family‐friendly instrument. This study provides strong evidence of reliability and validity to support GM‐FR use in clinical practice and research for assessing gross motor performance of children and adolescents with CP. [ABSTRACT FROM AUTHOR]

We administered a computerized adaptive test of vocabulary three times to assess the verbal intelligence of chatGPT (GPT 3.5) and Bing (based on GPT 4). There was no difference between their performance; both performed at a high level, outperforming approximately 95% of humans and scoring above the level of native speakers with a doctoral degree. In 42% of test items that were administered more than once these large language models provided different answers to the same question in different sessions. They never engaged in guessing, but provided hallucinations: answers that were not among the options. Such hallucinations were not triggered by the inability to answer correctly as the same questions evoked correct answers in other sessions. The results implicate that psychometric tools developed for humans have limitations when assessing AI, but they also imply that computerised adaptive testing of verbal ability is an appropriate tool to critically evaluate the performance of large language models. [ABSTRACT FROM AUTHOR]

Increasingly over the past decade, there has been a demand of more thorough documentation of the quality of reading assessments. Yet, available documentation of high-quality measures are often restricted to general framework descriptions providing psychometric information as a token of test quality. In a modern view of validity, understanding what is being measured and how scores are calculated is a prerequisite for good interpretation and use of test scores. The present article aims to document the research and development process of a national adaptive screening test for reading difficulties, in which the envisioned interpretation and use of test scores is guiding the work. Given the mandatory nature of this test the sample consist of 49,828 third grade students aged 8. Significant outcomes from this design process involve detailed information on: (a) choice of sub-tests and item formats, (b) selection of high quality items, (c) choice and design of adaptive model, and finally, a statement on the challenges that are still to bemet for such a test to function optimally. The present paper is among the first to, in an open and detailedmanner, describe the development process as well as qualities and challenges of an adaptive reading screening test for students of this young age. [ABSTRACT FROM AUTHOR]

An item bank is key to applying computerized adaptive testing (CAT). The traditional approach to developing an item bank requires content experts to design each item individually, which is a time-consuming and costly process. The cognitive design system (CDS) approach offers a solution by automating item generation. However, the CDS approach has a specific way of calibrating or predicting item difficulty that affects the measurement efficiency of CAT A simulation study was conducted to compare the efficiency of CAT using both calibration and prediction models. The results show that, although the predictive model (linear logistic trait model; LLTM) shows a higher root mean square error (RMSE) than the baseline model (Rasch), it requires only a few additional items to achieve comparable RMSE. Importantly, the number of additional items needed decreases as the explanatory rate of the model increases. These results indicate that the slight reduction in measurement efficiency due to prediction item difficulty is acceptable. Moreover, the use of prediction item difficulty can significantly reduce or even eliminate the need for item pretesting, thereby reducing the costs associated with item calibration. [ABSTRACT FROM AUTHOR]

This article examines whether the relationship between the members of the United Nations' Treaty Bodies' (TB) home countries and the countries reviewed by these bodies is significant to the amount and style of criticism the reviewed country receives. This article explains why the source–target relationship is significant to shaming. It defines two shaming styles – Socializing shaming and Disciplining shaming and defines elements that enable the identification of shaming styles. Utilizing data on CAT shaming from 2001 to 2022 and on TB members' country of origin it shows through regression analysis that the existence of a trade partnership between TB members' home countries and reviewed countries results in more criticism. This article qualitatively identifies elements of Socializing versus Disciplining shaming in the communications with countries that are trade partners of the TB members' home countries. It finds that Socializing shaming elements are more prevalent. This article draws theoretical, empirical and policy conclusions. [ABSTRACT FROM AUTHOR]

Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and principled assessment design. The generalized nature of the algorithm permits a wide array of test requirements allowing experts to define what to measure and how to measure it and the algorithm is simply a means to an end to support better construct representation. This work also emphasizes the computational algorithm and its ability to scale to support faster computing and better cost‐containment in real‐world applications than other CAT algorithms. We make a significant effort to consolidate all information needed to build and scale the algorithm so that expert psychometricians and software developers can use this document as a self‐contained resource and specification document to build and deploy an operational CAT platform. [ABSTRACT FROM AUTHOR]

The article focuses on the evolution and impact of large-scale assessments of adult skills over the past six decades, highlighting innovations and methodologies introduced by the Programme for the International Assessment of Adult Competencies (PIAAC). Topics include the historical development and growth of adult skill assessments, technological advancements in survey design and administration, and the influence of these assessments on policy and educational practices globally.

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Computational Thinking (CT) skill was a part of the global framework of reference on Digital Literacy for Indicator 4.4.2, widely developed in mathematics and science learning. This study aimed to promote an assessment tool using a two-tier Computerized Adaptive Test (CAT). The study used the Design and Development Research (DDR) method with four stages of data collection: expert judgment, usability test, simulation study, and student feedback. The two-tier questions have been tested empirically and fit with the Generalized Partial Credit Model (GPCM) or 2 Parameter Logistic (2PL). This study proved that the CAT could be used to estimate students' CT with a minimum different Standard Error of Measurement (different SEM) or close to zero (⁓0.001). According to the expert judgment, CAT was proper for measurement with a feasibility of 90.23%. The usability test proved that CAT was feasible to use, with satisfaction of 79.51%. Furthermore, the simulation study or empirical measurement explained that students' CT at the high school level were greater than at the middle and lower school levels. Thus, CAT were empirically proven to estimate students' CT accurately. Finally, students' feedback showed that the acceptance from students' feedback is 74.40% with a very satisfactory category. [ABSTRACT FROM AUTHOR]

The ability to rapidly provide examinees with detailed and effective diagnostic information is a critical topic in psychology. Knowing what diagnostic criteria the examinees have met enables the practitioner to seek the solution to help them in a timely manner, and this can be achieved by cognitive diagnostic computerized adaptive testing (CD-CAT). However, the pervasive challenge of replenishing items in the CD-CAT item bank limits its practical application. Online calibration is a means to address item replenishment, but in CD-CAT, most existing online calibration methods that jointly calibrate the Q-matrix and item parameters of the new items are developed only for dichotomous responses and are time-consuming. Notably, previous studies pay no attention to polytomously scored items that are frequently observed in testing, even though they can offer additional evidence for the examinees' diagnosis. To fill this gap, we propose a SCAD-based method (SCAD-EM) to calibrate the Q-matrix and item parameters of the new items with polytomous response data in order to promote the application of CD-CAT in practice. The performance of the SCAD-EM was investigated in two comprehensive simulation studies and compared against the revised single-item estimation method (SIE-BIC). Results indicated that the SCAD-EM produces a higher calibration accuracy for the category-level Q-matrix and is computationally more efficient across all conditions, but it produces a lower calibration accuracy for the item-level Q-matrix. An empirical study further demonstrated the utility of the SCAD-EM and the SIE-BIC methods in calibrating new items with a real dataset. The advantages of the proposed method, its limitations, and possible future research directions are offered at the end. [ABSTRACT FROM AUTHOR]

Abstract Background There is no gold standard patient-reported outcome measure (PROM) in hand surgery. As a result, a diverse array of PROM instruments have been utilized across centers over time. Lack of score interchangeability limits the ability to compare or conglomerate scores when new instruments are introduced. Our aim was to develop a linkage for the PROMIS UE CAT v1.2 and PROMIS PF CAT scores and develop crosswalk tables for interconversion between these PROMs. Methods Retrospective review was conducted to identify adult (≥ 18y) patients seen by orthopaedic hand surgeons at a single academic tertiary care hospital who had completed PROMIS UE CAT v1.2 and PROMIS PF CAT score at the same visit. For those with multiple visits, only one randomly selected visit was included in the analyses. Pearson’s correlation was calculated to determine the linear relationship between the scores. Linkage from PF to UE was performed utilizing several commonly utilized equating models (identity, mean, linear, equipercentile and circle-arc methods). The performance of the models was assessed using intraclass correlation (ICC) between observed PROMIS UE CAT v1.2 and estimated PROMIS UE CAT v1.2 scores generated using the model as well as Root Mean Square Error (RMSE). The model chosen as the ‘best’ was further assessed for population invariance using root expected mean squared difference (REMSD) where

Background: The Forgotten Joint Score (FJS), a commonly used patient-reported outcome measure, was developed without fully confirming assumptions such as unidimensionality (all items reflect 1 underlying factor), appropriate weighting of each item in scoring, absence of differential item functioning (in which different groups, e.g., men and women, respond differently), local dependence (pairs of items are measuring only 1 underlying factor), and monotonicity (persons with higher function have a higher score). We applied item response theory (IRT) to perform validation of the FJS according to contemporary standards, and thus support its ongoing use. We aimed to confirm that the FJS reflects a single latent trait. In addition, we aimed to determine whether an IRT model could be fitted to the FJS. Methods: Participants undergoing primary total knee replacement provided responses to the FJS items preoperatively and at 6 and 12 months postoperatively. An exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Mokken analysis were conducted. A graded response model (GRM) was fitted to the data. Results: A total of 1,774 patient responses were analyzed. EFA indicated a 1-factor model (all 12 items reflecting 1 underlying trait). CFA demonstrated an excellent model fit. Items did not have equal weighting. The FJS demonstrated good monotonicity and no differential item functioning by sex, age, or body mass index. GRM parameters are reported in this paper. Conclusions: The FJS meets key validity assumptions, supporting its use in clinical practice and research. The IRT-adapted FJS has potential advantages over the traditional FJS: it provides continuous measurements with finer granularity between health states, includes individual measurement error, and can compute scores despite more missing data (with only 1 response required to estimate a score). It can be applied retrospectively to existing data sets or used to deliver individualized computerized adaptive tests. Level of Evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

AbstractFeedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students’ current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished. Latent trait models identify ability as a continuous uni- or multi-dimensional construct, with unidimensional item response theoretic (IRT) models presumably the most popular type of latent trait models. They report a single ability score that allows for locating examinees relative to their peers on the latent ability dimension targeted by the test. Latent trait models have been criticized for lacking diagnostic information on students’ specific skills, their strengths and weaknesses in a knowledge domain. Cognitive diagnosis (CD) models, in contrast, describe ability as a combination of discrete skills (called “attributes”) that constitute (partially) ordered latent classes of proficiency. The focus of CD is on collecting information about the learning progress for immediate feedback to students in terms of skills they have mastered and those needing study. CD has been underused in education; performance assessment still mostly relies on latent-trait-based methods. The motivation for the study reported here arose from the desire to conduct a side-by-side evaluation of the two seemingly disparate psychometric frameworks, CD and IRT. Data from a biochemistry end-of-term exam were used for illustration. They were fitted with multiple CD and IRT models, among them also HO-GDINA models that permit for a close approximation to several unidimensional IRT models. [ABSTRACT FROM AUTHOR]

Purpose: The present study aimed to test the relationship between the components of the Cognitive Load Theory (CLT) including memory, intrinsic and extraneous cognitive load in workplace-based learning in a clinical setting, and decision-making skills of nursing students. Methods: This study was conducted at Shahid Sadoughi University of Medical Sciences in 2021–2023. The participants were 151 nursing students who studied their apprenticeship courses in the teaching hospitals. The three basic components of the cognitive load model, including working memory, cognitive load, and decision-making as the outcome of learning, were investigated in this study. Wechsler's computerized working memory test was used to evaluate working memory. Cognitive Load Inventory for Handoffs including nine questions in three categories of intrinsic cognitive load, extraneous cognitive load, and germane cognitive load was used. The clinical decision-making skills of the participants were evaluated using a 24-question inventory by Lowry et al. based on a 5-point scale. The path analysis of AMOS 22 software was used to examine the relationships between components and test the model. Findings: In this study, the goodness of fit of the model based on the cognitive load theory was reported (GIF = 0.99, CFI = 0.99, RMSEA = 0.03). The results of regression analysis showed that the scores of decision-making skills in nursing students were significantly related to extraneous cognitive load scores (p-value = 0.0001). Intrinsic cognitive load was significantly different from the point of view of nursing students in different academic years (p = 0.0001). Conclusion: The present results showed that the CLT in workplace-based learning has a goodness of fit with the components of memory, intrinsic cognitive load, extraneous cognitive load, and clinical decision-making skill as the key learning outcomes in nursing education. The results showed that the relationship between nursing students' decision-making skills and extraneous cognitive load is stronger than its relationship with intrinsic cognitive load and memory Workplace-based learning programs in nursing that aim to improve students' decision-making skills are suggested to manage extraneous cognitive load by incorporating cognitive load principles into the instructional design of clinical education. [ABSTRACT FROM AUTHOR]

This study presents a novel method to investigate test fairness and differential item functioning combining psychometrics and machine learning. Test unfairness manifests itself in systematic and demographically imbalanced influences of confounding constructs on residual variances in psychometric modeling. Our method aims to account for resulting complex relationships between response patterns and demographic attributes. Specifically, it measures the importance of individual test items, and latent ability scores in comparison to a random baseline variable when predicting demographic characteristics. We conducted a simulation study to examine the functionality of our method under various conditions such as linear and complex impact, unfairness and varying number of factors, unfair items, and varying test length. We found that our method detects unfair items as reliably as Mantel–Haenszel statistics or logistic regression analyses but generalizes to multidimensional scales in a straight forward manner. To apply the method, we used random forests to predict migration backgrounds from ability scores and single items of an elementary school reading comprehension test. One item was found to be unfair according to all proposed decision criteria. Further analysis of the item's content provided plausible explanations for this finding. Analysis code is available at: https://osf.io/s57rw/?view_only=47a3564028d64758982730c6d9c6c547. [ABSTRACT FROM AUTHOR]

Multidimensional achievement tests are recently gaining more importance in educational and psychological measurements. For example, multidimensional diagnostic tests can help students to determine which particular domain of knowledge they need to improve for better performance. To estimate the characteristics of candidate items (calibration) for future multidimensional achievement tests, we use optimal design theory. We generalize a previously developed exchange algorithm for optimal design computation to the multidimensional setting. We also develop an asymptotic theorem saying which item should be calibrated by examinees with extreme abilities. For several examples, we compute the optimal design numerically with the exchange algorithm. We see clear structures in these results and explain them using the asymptotic theorem. Moreover, we investigate the performance of the optimal design in a simulation study. [ABSTRACT FROM AUTHOR]

This study aimed to examine the performances of item selection algorithms in terms of measurement accuracy and computational time, using factors such as test length, number of attributes, and item quality in fixed-length CDCAT and average test lengths and computational time, using factors such as number of attributes and item quality in variable-length CD-CAT. In the research, two different simulation studies were conducted for the fixed and variable-length tests. Item responses were generated according to the DINA model. Two item banks, which consisted of 480 items for 5 and 6 attributes, were generated, and the item banks were used for both the fixed and variable-length tests. Q-matrix was generated item by item and attribute by attribute. In the study, 3000 examinees were generated in such a way that each examinee had a 50% chance of achieving each attribute. The cognitive patterns of the examinees were estimated by usingMAP. In the variable-length CD-CAT, the first-highest posterior probability threshold is 0.80, and the second-highest posterior probability threshold is 0.10. The CD-CAT administration and other analyses were conducted using R 3.6.1.At the end of the study in which the fixed-length CD-CAT was used, it was concluded that an increase in the number of attributes resulted in a decrease in the pattern recovery rates of item selection algorithms. Conversely, these rates improved with higher item quality and longer test lengths. The highest values in terms of pattern recovery rate were obtained from JSD and MPWKL algorithms. In the variable-length CD-CAT, it was concluded that the average test length increased with the number of attributes and decreased with higher item quality. Across all conditions, the JSD algorithm yielded the shortest average test length. Additionally, It has been determined that GDI algorithm had the shortest computation time in all scenarios, whereas the MPWKL algorithm exhibited the longest computation time. [ABSTRACT FROM AUTHOR]

Objectives: Following a user‐centred redesign and refinement process of an electronic delirium screening tool (eDIS‐MED), further accuracy assessment was performed prior to anticipated testing in the clinical setting. Methods: Content validity of each of the existing questions was evaluated by an expert group in the domains of clarity, relevance and importance. Questions with a Content Validity Index (CVI) <0.80 were reviewed by the development group for potential revision. Items with CVI <0.70 were discarded. Next, face validity of the entirety of the tests was conducted and readability measured. Results: A panel of five clinical experts evaluated the test battery comprising eDIS‐MED. The content validity process endorsed 61 items. The overall scale CVI was 0.92. Eighty‐eight per cent of the responses with regard to question relevancy, usefulness and appropriateness were positive. The questions were deemed fifth grade level and very easy to read. Conclusions: A revised electronic screening tool was shown to be accurate according to an expert group. A clinical validation study is planned. [ABSTRACT FROM AUTHOR]

'Single Session Therapy' (SST) is a service delivery model that seeks to provide an evidence-based, solution-focused, brief intervention within a single therapy session. The stand-alone session affords the opportunity to provide brief psychological interventions while clients await access to longer-term services. The COVID-19 pandemic has adversely impacted individuals' mental health. However, the majority of research has investigated patient mental health within hospital settings and community organizations that offer long-term services, whereas minimal research has focused on mental health concerns during COVID-19 within an SST model. The primary aim of the study was to measure client experiences of a brief mental health service. The nature of client mental health concerns who access such services at various points during a pandemic was also investigated. The current study utilized client feedback forms and the Computerized Adaptive Testing—Mental Health (CAT-MH) to measure client experiences and mental health concerns. Qualitative analysis of client feedback forms revealed themes of emotional (e.g., safe space) and informational support (e.g., referrals). Clients also reported reduced barriers to accessing services (e.g., no appointment necessary, no cost), as well as limitations (e.g., not enough sessions) of the Walk-in clinic. Profile analysis of the CAT-MH data indicated that clients had higher rates of depression before COVID-19 (M = 64.2, SD = 13.07) as compared to during the pandemic (M = 59.78, SD = 16.87). In contrast, higher rates of positive suicidality flags were reported during the pandemic (n = 54) as compared to before (n = 29). The lower reported rates of depression but higher rate of suicidality during the pandemic was an unanticipated finding that contradicted prior research, to which possible explanations are explored. Taken together, the results demonstrate the positive experiences of clients who access a single session therapy. [ABSTRACT FROM AUTHOR]

Background: There is no gold standard patient-reported outcome measure (PROM) in hand surgery. As a result, a diverse array of PROM instruments have been utilized across centers over time. Lack of score interchangeability limits the ability to compare or conglomerate scores when new instruments are introduced. Our aim was to develop a linkage for the PROMIS UE CAT v1.2 and PROMIS PF CAT scores and develop crosswalk tables for interconversion between these PROMs. Methods: Retrospective review was conducted to identify adult (≥ 18y) patients seen by orthopaedic hand surgeons at a single academic tertiary care hospital who had completed PROMIS UE CAT v1.2 and PROMIS PF CAT score at the same visit. For those with multiple visits, only one randomly selected visit was included in the analyses. Pearson's correlation was calculated to determine the linear relationship between the scores. Linkage from PF to UE was performed utilizing several commonly utilized equating models (identity, mean, linear, equipercentile and circle-arc methods). The performance of the models was assessed using intraclass correlation (ICC) between observed PROMIS UE CAT v1.2 and estimated PROMIS UE CAT v1.2 scores generated using the model as well as Root Mean Square Error (RMSE). The model chosen as the 'best' was further assessed for population invariance using root expected mean squared difference (REMSD) where < 0.08 were considered good. Results: Of 10,081 included patients, mean age was 48.3 (SD = 17.0), and 54% were female (5,477/10,081). Mean UE CAT v1.2 and PF CAT scores were 37 (SD = 9.8) and 46 (SD = 10.0), respectively. There was a strong correlation between the scores (Pearson correlation r = 0.70). All methods performed acceptably (ICC ≥ 0.66 and RMSE < = 7.52 for all). The equipercentile method had the highest ICC (ICC = 0.70 (95% CI 0.69–0.71)) while the mean and circle arc methods had the lowest RMSE. The circle arc method is the most reliable with the smallest standard error and has satisfactory population invariance across age group (REMSD 0.065) and sex (REMSD 0.036). Conclusions: Crosswalk tables to be used for bidirectional conversion between scores were created. Level of evidence: : III. [ABSTRACT FROM AUTHOR]

Objectives: At present, there are many limitations in the evaluation of lymph node metastasis of lung adenocarcinoma. Currently, there is a demand for a safe and accurate method to predict lymph node metastasis of lung cancer. In this study, radiomics was used to accurately predict the lymph node status of lung adenocarcinoma patients based on contrast-enhanced CT. Methods: A total of 503 cases that fulfilled the analysis requirements were gathered from two distinct hospitals. Among these, 287 patients exhibited lymph node metastasis (LNM +) while 216 patients were confirmed to be without lymph node metastasis (LNM-). Using both traditional and deep learning methods, 22,318 features were extracted from the segmented images of each patient's enhanced CT. Then, the spearman test and the least absolute shrinkage and selection operator were used to effectively reduce the dimension of the feature data, enabling us to focus on the most pertinent features and enhance the overall analysis. Finally, the classification model of lung adenocarcinoma lymph node metastasis was constructed by machine learning algorithm. The Accuracy, AUC, Specificity, Precision, Recall and F1 were used to evaluate the efficiency of the model. Results: By incorporating a comprehensively selected set of features, the extreme gradient boosting method (XGBoost) effectively distinguished the status of lymph nodes in patients with lung adenocarcinoma. The Accuracy, AUC, Specificity, Precision, Recall and F1 of the prediction model performance on the external test set were 0.765, 0.845, 0.705, 0.784, 0.811 and 0.797, respectively. Moreover, the decision curve analysis, calibration curve and confusion matrix of the model on the external test set all indicated the stability and accuracy of the model. Conclusions: Leveraging enhanced CT images, our study introduces a noninvasive classification prediction model based on the extreme gradient boosting method. This approach exhibits remarkable precision in identifying the lymph node status of lung adenocarcinoma patients, offering a safe and accurate alternative to invasive procedures. By providing clinicians with a reliable tool for diagnosing and assessing disease progression, our method holds the potential to significantly improve patient outcomes and enhance the overall quality of clinical practice. [ABSTRACT FROM AUTHOR]

In the social sciences, accurately identifying the dimensionality of measurement scales is crucial for understanding latent constructs such as anxiety, happiness, and self-efficacy. This study presents a rigorous comparison between Parallel Analysis (PA) and Exploratory Graph Analysis (EGA) for assessing the dimensionality of scales, particularly focusing on ordinal data. Through an extensive simulation study, we evaluated the effectiveness of these methods under various conditions, including varying sample size, number of factors and their association, patterns of loading magnitudes, and symmetrical or skewed item distributions with assumed underlying normality or non-normality. Results show that the performance of each method varies across different scenarios, depending on the context. EGA consistently outperforms PA in correctly identifying the number of factors, particularly in complex scenarios characterized by more than a single factor, high inter-factor correlations and low to medium primary loadings. However, for datasets with simpler and stronger factor structures, specifically those with a single factor, high primary loadings, low cross-loadings, and low to moderate interfactor correlations, PA is suggested as the method of choice. Skewed item distributions with assumed underlying normality or non-normality were found to noticeably impact the performance of both methods, particularly in complex scenarios. The results provide valuable insights for researchers utilizing these methods in scale development and validation, ensuring that measurement instruments accurately reflect theoretical constructs. [ABSTRACT FROM AUTHOR]

The relationship between confidence and accuracy and the reliability of eyewitness identifications has attracted a lot of attention. In contrast, relatively little is known about the relationship between eyewitness confidence and the accuracy of recall memory in interview contexts. Here, we manipulated questioning approaches to investigate the impact of Free‐Recall and Cued‐Recall questions, whereby the latter were witness‐compatible (questions concerning details reported in the preceding Free‐Recall) or witness‐incompatible questions. We also manipulated the order these questions were asked. A sample of 124 mock witness participants watched a crime‐video and subsequently recalled the event to understand the impact of question type and order on confidence‐accuracy calibration. Our results show that a Free‐Recall invitation and compatible (compared to incompatible) questions promoted more stable confidence. Compatible questions yielded fewer errors, more accurate details, and promoted more reliable confidence‐accuracy calibration and discrimination, especially when they preceded the incompatible questions. Implications are discussed. [ABSTRACT FROM AUTHOR]

Computerized adaptive tests (CATs) are highly efficient assessment tools that couple low patient and clinician time burden with high diagnostic accuracy. A CAT for substance use disorders (CAT-SUD-E) has been validated in adult populations but has yet to be tested in adolescents. The purpose of this study was to perform initial evaluation of the K-CAT-SUD-E (i.e., Kiddy-CAT-SUD-E) in an adolescent sample compared to a gold-standard diagnostic interview. Adolescents (N = 156; aged 11–17) with diverse substance use histories completed the K-CAT-SUD-E electronically and the substance related disorders portion of a clinician-conducted diagnostic interview (K-SADS) via tele-videoconferencing platform. The K-CAT-SUD-E assessed both current and lifetime overall SUD and substance-specific diagnoses for nine substance classes. Using the K-CAT-SUD-E continuous severity score and diagnoses to predict the presence of any K-SADS SUD diagnosis, the classification accuracy ranged from excellent for current SUD (AUC = 0.89, 95% CI = 0.81, 0.95) to outstanding (AUC = 0.93, 95% CI = 0.82, 0.97) for lifetime SUD. Regarding current substance-specific diagnoses, the classification accuracy was excellent for alcohol (AUC = 0.82), cannabis (AUC = 0.83) and nicotine/tobacco (AUC = 0.90). For lifetime substance-specific diagnoses, the classification accuracy ranged from excellent (e.g., opioids, AUC = 0.84) to outstanding (e.g., stimulants, AUC = 0.96). K-CAT-SUD-E median completion time was 4 min 22 s compared to 45 min for the K-SADS. This study provides initial support for the K-CAT-SUD-E as a feasible accurate diagnostic tool for assessing SUDs in adolescents. Future studies should further validate the K-CAT-SUD-E in a larger sample of adolescents and examine its acceptability, feasibility, and scalability in youth-serving settings. [ABSTRACT FROM AUTHOR]

This evaluation study explored a two-year literacy reform effort in a school district with 10 of its 13 elementary schools in the improvement process. Schools were placed in three groups. Group 1 (four schools, 80 teachers) implemented new instructional practices in Year 1 and then added a new curriculum. Group 2 (four schools, 102 teachers) changed both the pedagogy and curriculum for both years. Group 3 (five schools, 107 teachers) did not make any changes in Year 1 and then implemented both components. After propensity score matching students, reading scores were analyzed with three-level change score models. Results suggested that two years of the combined reforms generally were effective at improving students' oral reading fluency, and two years of the pedagogical changes were effective at improving students' performance on a computer-adaptive test of overall reading ability. However, improvements on the computer-adaptive test as well as the state reading test were small, which might reflect the stability in reading comprehension found in other studies. [ABSTRACT FROM AUTHOR]

Community correction institutions in China frequently employ the Symptom Checklist-90 (SCL-90) and the health survey brief (SF-12) as primary tools for psychological assessment of community correctional prisoners. However, in practical application, the SCL-90 Checklist faces issues such as complex item numbers, overall low cultural level of the subjects, and insufficient professional level of the administrators. The SF-12 health survey brief, as a preliminary screening tool, although only has 12 questions, to some extent simplifies the evaluation process and improves work efficiency, it is prone to missed screening. The research team collected 17-dimensional basic characteristic data and corresponding SCL-90 and SF-12 data from 25,480 samples of community correctional prisoners in Zhejiang Province, China. This study explored the application of multi-label multi-classification algorithms and oversampling techniques in building machine learning models to delve into the correlation between the psychological health risks of community correctional prisoners and their characteristic data. Inspired by computerized adaptive testing (CAT), we constructed an adaptive and efficient screening model for community correctional prisoners through experimental comparisons, based on the binary relevance algorithm with sample oversampling. This screening model personalize the assessment process by dynamically matching participants with the most relevant subset (s) of the nine dimensions of the SCL-90 based on their individual characteristics. Thus, adaptive dynamic simplification and personalized recommendation of the SCL-90 scale between question groups were achieved for the specific group of community correctional prisoners. As a screening tool for psychological symptoms of community correctional prisoners, this model significantly simplifies the number of questions compared to SCL-90, with a simplification rate of up to 65%. However, it achieves this simplification while maintaining excellent performance. The accuracy reached 0.66, with a sensitivity of 0.754, and an F1 score of 0.649. This innovation simplified the assessment process, reduced the assessment time, improved work efficiency, and enhanced the ability to judge the specificity of community correctional prisoners population. Compared to the SF-12, although the simplification rate and accuracy of the model are slightly lower than those of the SF-12, the sensitivity increased by 42.26%, and the F1 score improved by 15.28%. This means the model greatly reduces the possibility of missed screening, effectively preventing prisoners with abnormal psychological or mental states from losing control due to missed screening, and even committing suicide, self injury, or injuring others. [ABSTRACT FROM AUTHOR]

The number of mobile phone users worldwide has increased in recent years. As people spend more time on their phones, negative effects such as problematic mobile phone use (PMPU) have become more pronounced. Many researchers have dedicated their efforts to developing the questionnaires and revising the tools to more accurately evaluate PMPU. Previous studies had demonstrated that CAT-PMPU for adults could significantly enhance measurement accuracy and efficiency. However, most of the items in this scenario was developed for adults, and there were notable differences between adults and adolescents, making some items potentially unsuitable for the latter. Thus, this study aimed to generalize the CAT-PMPU adult version to make it suitable for both adult and adolescent populations. A total of 740 Chinese adolescents and 980 Chinese adults participated in this study, completing online or paper-pencil questionnaires. Empirical data was then used to simulate CAT-PMPU, and the measurement efficiency, accuracy and reliability were compared between adults and adolescents in different stopping rules. The results showed that generalized CAT-PMPU in this study had promising measurement efficiency and accuracy, which was consistent with adult version. In conclusion, the CAT-PMPU developed in this study not only exhibited satisfactory test reliability but also emerged as a novel technical support for evaluation of PMPU in both adolescent and adult populations, which demonstrated the potential applicability in practice. [ABSTRACT FROM AUTHOR]

Educational tests often combine text and images in items. Research shows that including images in test items can influence response accuracy, termed the Multimedia Effect in Testing. This effect suggests that using pictures in tests can enhance student performance and reduce the perception of item difficulty. As such, the Multimedia Effect in Testing could influence test validity. However, research in this area has produced varied and conflicting results, which may be partly attributed to the functionality of the images used. Besides, many studies only offer test-level data, making it challenging to determine whether the outcomes represent a generic phenomenon or result from averaging mixed outcomes in individual test items. This present study examined whether coherency of pictures in tests influences response accuracy, mental effort and time-on-task at the test level and item level. Item-level analysis showed that the Multimedia Effect in Testing is not universal; only a small subset of items showed significant differences between text-only and text-picture items. The degree of coherence also did not give unambiguous results. In summary, the study highlights the complexity of the Multimedia Effect in Testing, suggesting it is context-dependent, with not all test items benefiting equally from multimedia elements. The findings emphasize the need for a nuanced understanding of how multimedia affects educational testing. [ABSTRACT FROM AUTHOR]

The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end‐of‐year proficiency in reading and math. Participants included 13,009 students in Grades 3–8 who had at least one fall screening score and end‐of‐year state test score in reading and math. First, diagnostic accuracy statistics were evaluated for a single screening measure to predict proficiency on end‐of‐year tests. Second, a gated screening framework was simulated to examine the diagnostic accuracy of a combination of screening measures (i.e., scores from the CATs and the end‐of‐year test). The diagnostic accuracy of each screening method was compared. Results suggest that diagnostic accuracy did not improve for the gated screening method when compared to the single screening method. The gated screening method tended to yield low sensitivity values (M = 0.42, range = 0.35–0.48) and high specificity values (M = 0.97, range = 0.95–0.99). The only condition to reach acceptable sensitivity and specificity (>0.70) was a single reading screener predicting reading outcomes. Sample specific cut‐scores from receiver operating curve (ROC) analyses led to improved diagnostic accuracy outcomes relative to all other methods. Practitioner Points: The diagnostic accuracy did not improve for the gated screening method when compared to the single screening method.Across the screening conditions, the only method to yield acceptable diagnostic accuracy was when a single reading screener predicted reading outcomes.Utilizing multiple assessment measures cannot be justified according to the results of the study. [ABSTRACT FROM AUTHOR]

Stroke survivors frequently experience difficulties in daily activities, such as bathing, feeding, and mobility. This study aimed to evaluate the reliability and validity of a computer-adaptive test-Longshi scale (CAT-LS) for assessing activities of daily living (ADL) in stroke survivors. This cross-sectional study collected data using an electronic application. The ADL function of stroke survivors in rehabilitation departments of hospitals was assessed using both the CAT-LS and BI. Correlations between the CAT-LS and Barthel index (BI) and concurrent validity were evaluated using Pearson's correlation test and multiple linear regression. Interrater reliability was evaluated using the intraclass correlation coefficient based on a two-way random effect. The internal consistency of the CAT-LS was assessed using Cronbach's coefficient (α) and corrected item-total correlations. Overall, 103 medical institutions in China were used in this study. In total, 7151 patients with stroke were included in this study. The CAT-LS classified patients into three ADL groups (bedridden, domestic, and community) with significantly different BI scores (P < 0.05). The CAT-LS results obtained using the decision-tree scoring model were consistent with the scores for each BI item. A strong correlation was observed between CAT-LS and BI (Pearson's r: 0.6–0.894, P < 0.001). The CAT-LS demonstrated good internal consistency (Cronbach's α, 0.803–0.894) and interrater reliability (ICC, 0.928–0.979). CAT-LS is time-efficient and requires < 1 min to administer. The CAT-LS is a reliable and valid tool for assessing ADL function in stroke survivors and can provide rapid and accurate assessments that reduce the burden on healthcare professionals. Further validation of this tool in other populations and settings is necessary. Study registration number: No.: ChiCTR2000034067; http://www.chictr.org.cn/showproj.aspx?proj=54770. [ABSTRACT FROM AUTHOR]

U.S. elementary schools administer reading screeners to identify students in need of remedial instruction. However, the administration of additional assessments comes with a cost. It is unclear the extent to which multiple types of reading screeners warrant the increase in resources that could be used for instruction. This study compared cost–accuracy ratios for three types of reading screeners in Grade 3: curriculum-based measurement (Acadience), computer adaptive assessment (Star), informal reading inventory (Fountas and Pinnell Benchmark Assessment System), and the cost–accuracy of using all three in conjunction. We used classification and regression tree analysis to identify local cut-scores and identify how measures could be combined to maximize classification accuracy. Results suggested that oral reading fluency score (Acadience) yielded the best cost–accuracy ratio, but the combination of Star and oral reading fluency identified important instructional groups. Cost tables provide additional insight to schools on critical decision points for choosing and implementing reading screeners. [ABSTRACT FROM AUTHOR]

The questionnaire method has always been an important research method in psychology. The increasing prevalence of multidimensional trait measures in psychological research has led researchers to use longer questionnaires. However, questionnaires that are too long will inevitably reduce the quality of the completed questionnaires and the efficiency of collection. Computer adaptive testing (CAT) can be used to reduce the test length while preserving the measurement accuracy. However, it is more often used in aptitude testing and involves a large number of parametric assumptions. Applying CAT to psychological questionnaires often requires question-specific model design and preexperimentation. The present article proposes a nonparametric and item response theory (IRT)-independent CAT algorithm. The new algorithm is simple and highly generalizable. It can be quickly used in a variety of questionnaires and tests without being limited by theoretical assumptions in different research areas. Simulation and empirical studies were conducted to demonstrate the validity of the new algorithm in aptitude tests and personality measures. [ABSTRACT FROM AUTHOR]

Questionnaires to detect emotional and behavioral (EB) problems in preventive child healthcare (PCH) should be short; this potentially affects their validity and reliability. Computerized adaptive testing (CAT) could overcome this weakness. The aim of this study was to (1) develop a CAT to measure EB problems among pre-school children and (2) assess the efficiency and validity of this CAT. We used a Dutch national dataset obtained from parents of pre-school children undergoing a well-child care assessment by PCH (n = 2192, response 70%). Data regarded 197 items on EB problems, based on four questionnaires, the Strengths and Difficulties Questionnaire (SDQ), the Child Behavior Checklist (CBCL), the Ages and Stages Questionnaire: Social Emotional (ASQ:SE), and the Brief Infant–Toddler Social and Emotional Assessment (BITSEA). Using 80% of the sample, we calculated item parameters necessary for a CAT and defined a cutoff for EB problems. With the remaining part of the sample, we used simulation techniques to determine the validity and efficiency of this CAT, using as criterion a total clinical score on the CBCL. Item criteria were met by 193 items. This CAT needed, on average, 16 items to identify children with EB problems. Sensitivity and specificity compared to a clinical score on the CBCL were 0.89 and 0.91, respectively, for total problems; 0.80 and 0.93 for emotional problems; and 0.94 and 0.91 for behavioral problems. Conclusion: A CAT is very promising for the identification of EB problems in pre-school children, as it seems to yield an efficient, yet high-quality identification. This conclusion should be confirmed by real-life administration of this CAT. What is Known: • Studies indicate the validity of using computerized adaptive test (CAT) applications to identify emotional and behavioral problems in school-aged children. • Evidence is as yet limited on whether CAT applications can also be used with pre-school children. What is New: • The results of this study show that a computerized adaptive test is very promising for the identification of emotional and behavior problems in pre-school children, as it appears to yield an efficient and high-quality identification. [ABSTRACT FROM AUTHOR]

The computerized adaptive form of cognitive diagnostic testing, CD-CAT, has gained increasing attention in the domain of personalized measurements for its ability to categorize individual mastery status of fine-grained attributes more accurately and efficiently through administering items tailored to one's ability progressively. How to select the next item based on previous response(s) is crucial for the success of CD-CAT. Previous item selection strategies for CD-CAT have often followed a greedy or semi-greedy approach, which makes it difficult to strike a balance between diagnostic performance and item bank utilization. To address this issue, this study takes a graph perspective and transforms the item selection problem in CD-CAT into a path-searching problem, in which paths refer to possible test construction and nodes refer to individual items. A heuristic function is defined to predict the prospect of a path, indicating how well the corresponding test can diagnose the current examinee. Two search mechanisms with different biases towards item exposure control are proposed to approximate the optimal path with the best prospect. The first unused item on the resulting path is selected as the next item. The above components compose a novel CD-CAT item selection framework based on heuristic search. Simulation studies are conducted under a variety of conditions regarding bank designs, bank-quality conditions, and testing scenarios. The results are compared with different types of classic item selection strategies in CD-CAT, showing that the proposed framework can enhance bank utilization at a smaller cost of diagnostic performance. [ABSTRACT FROM AUTHOR]

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Translation technology is a fundamental aspect of the translation profession. Cloud-based computer-assisted translation (CAT) tools are becoming popular among translators because of their simplicity and usability. However, studies on the factors affecting the use of cloud-based CAT tools by translators and translation students are scarce. Therefore, this study explores the factors that influence the acceptance and use of such tools among translation students using the technology acceptance model (TAM). The hypothesized model is empirically validated using a survey of 181 participants. Using structural equation modeling, data analysis suggests that translation students' intention to use cloud-based CAT tools and their perceived usefulness are key adoption factors, while actual use is less significant. The simplicity of cloud-based CAT tools is also an important consideration, particularly for translation students with limited information technology experience. The implications for tool developers and translation instructors are discussed considering these findings. [ABSTRACT FROM AUTHOR]

Despite the growing prevalence of Bismuth (Bi), very little research has been carried to assess its potential toxic effects on aquatic organisms. This study aimed to address this gap by investigating the interactive effects of Bi exposure and elevated temperature on freshwater snails of the genus Lymnaea, specifically on their fatty acid (FA) profiles, oxidative stress markers (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione S-transferase (GST)) and lipid peroxidation (malondialdehyde (MDA) content). Bismuth exposure was introduced through two distinct routes: i) food via Bi-exposed biofilm (grown under 2 µM Bi), and ii) water (2 µM Bi). Exposed snails were maintained at two temperatures, 19°C and 25°C, over a duration of 14 days. Bismuth bioaccumulation occurred in Bi-exposed biofilm concurrently with a pronounced increase in polyunsaturated fatty acids (PUFA), likely as a protective mechanism to preserve cell structure and integrity. Bismuth bioaccumulation also occurred in snails with their FA composition largely reflecting the composition of their dietary source highlighting the direct link between diet and snail FA profiles. Additionally, the antioxidant enzymes studied exhibited diverse responses under Bi exposure and thermal stress, suggesting the induction of oxidative stress in snails. SOD activity increased at 25°C, suggesting a thermal stress. CAT activity remained high under all conditions, unaffected by temperature or Bi exposure. GPx levels increased in snails fed with Bi-laden biofilm, particularly at 19°C. GST activity showed great variability with a significant three-way interaction. The observed elevation in MDA levels among Bi-exposed snails suggested a potential deficiency in their antioxidant enzyme systems, leading to an increased susceptibility to lipid peroxidation. This research highlights the complex interaction between Bi contamination, temperature, and the physiological responses of aquatic organisms, and reveals the need for future research into the environmental impact of Bi in aquatic ecosystems. We further highlight the importance of food for Bi transfer to higher consumers and the importance of considering dietborne exposures in ecotoxicological studies. [ABSTRACT FROM AUTHOR]