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Assessment literacy's vital role in faculty effectiveness within higher education lacks sufficient tools for measuring faculty attitudes on this matter. Employing a sequential mixed-methods approach, this study utilized the theory of planned behavior to develop the Assessment Literacy Attitude Scale (ALAS) and evaluate its psychometric properties within the U.S. higher education context. The qualitative phase involved a literature review of relevant studies and existing self-report measures, interviews with stakeholders, and panel reviews to shape initial item development. Following the establishment of a conceptual foundation and a comprehensive overview of the scale's construction, our study advanced to the quantitative stage that involves factor analytical and item response theory approaches using data from 260 faculty across three public universities in the U.S. Exploratory factor analysis (EFA) was employed initially to obtain preliminary insights into the scale's factorial structure and dimensionality. Confirmatory factor analysis (CFA) was subsequently applied with separate data and the findings largely supported the conclusions from the EFA. Exploratory and confirmatory factor analyses resulted in 15 items loading across two factors in a good model fit range. Finally, we used nonparametric item response theory (IRT) techniques based on Mokken Scale Analysis (MSA) to evaluate individual items for evidence of effective psychometric properties to support the interpretation of ALAS scores, including monotonicity, scalability, and invariant item ordering. The newly-developed scale shows promise in assessing faculty attitudes toward enhancing their assessment literacy.

This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational competencies in educational measurement, illustrate how educational measurement programs can help learners develop these competencies, and demonstrate how foundational competencies continue to develop in educational measurement professions. The framework introduces three foundational competency domains: Communication and Collaboration Competencies; Technical, Statistical, and Computational Competencies; and Educational Measurement Competencies. Within the Educational Measurement Competency domain, the authors identify five subdomains: Social, Cultural, Historical, and Political Context; Validity, Validation, and Fairness; Theory and Instrumentation; Precision and Generalization; and Psychometric Modeling.

Abstract Background Microglial activation is one hallmark of Alzheimer disease (AD) neuropathology but the impact of the regional interplay of microglia cells in the brain is poorly understood. We hypothesized that microglial activation is regionally synchronized in the healthy brain but experiences regional desynchronization with ongoing neurodegenerative disease. We addressed the existence of a microglia connectome and investigated microglial desynchronization as an AD biomarker. Methods To validate the concept, we performed microglia depletion in mice to test whether interregional correlation coefficients (ICCs) of 18 kDa translocator protein (TSPO)-PET change when microglia are cleared. Next, we evaluated the influence of dysfunctional microglia and AD pathophysiology on TSPO-PET ICCs in the mouse brain, followed by translation to a human AD-continuum dataset. We correlated a personalized microglia desynchronization index with cognitive performance. Finally, we performed single-cell radiotracing (scRadiotracing) in mice to ensure the microglial source of the measured desynchronization. Results Microglia-depleted mice showed a strong ICC reduction in all brain compartments, indicating microglia-specific desynchronization. AD mouse models demonstrated significant reductions of microglial synchronicity, associated with increasing variability of cellular radiotracer uptake in pathologically altered brain regions. Humans within the AD-continuum indicated a stage-depended reduction of microglia synchronicity associated with cognitive decline. scRadiotracing in mice showed that the increased TSPO signal was attributed to microglia. Conclusion Using TSPO-PET imaging of mice with depleted microglia and scRadiotracing in an amyloid model, we provide first evidence that a microglia connectome can be assessed in the mouse brain. Microglia synchronicity is closely associated with cognitive decline in AD and could serve as an independent personalized biomarker for disease progression.

We explored three approaches to resolving or re-scoring constructed-response items in mixed-format assessments: rater agreement, person fit, and targeted double scoring (TDS). We used a simulation study to consider how the three approaches impact the psychometric properties of student achievement estimates, with an emphasis on person fit. We found that although TDS is not specifically designed to identify discrepant or misfitting score profiles, this approach can improve person fit for students who are also within a critical range of achievement. Our findings also suggest that TDS alone is not sufficient to provide a comprehensive picture of measurement quality because it does not directly consider person fit. We suggest that researchers and practitioners consider combining TDS with other approaches to score resolution. We consider the implications of our findings for research and practice.

The purpose of this article is to discuss reliability and precision through the lens of a modern measurement approach, item response theory (IRT). Reliability evidence in the field of counseling is primarily generated using Classical Test Theory (CTT) approaches, although recent studies in the field of counseling have shown the benefits of using IRT approaches to explore measurement precision. We discuss the theoretical foundations and assumptions of CTT and IRT, and examine how modern measurement theory (i.e. IRT) poses advantages for capturing measurement precision. We use an example analysis to demonstrate the indices of measurement precision in IRT approaches (e.g. standard errors, person-fit, item-fit, targeting, residual-based fit statistics). Finally, we discuss practical and clinical implications for counseling researchers for using IRT approaches to measure precision, including insights into precision for persons, items, and measurement invariance as well as the utility of brief and adaptive scales.

Mixed-format assessments made up of multiple-choice (MC) items and constructed response (CR) items that are scored using rater judgments include unique psychometric considerations. When these item types are combined to estimate examinee achievement, information about the psychometric quality of each component can depend on that of the other. For example, the presence of differential item functioning (DIF) in MC items could compromise the sensitivity of rater effect indicators, such as differential rater functioning (DRF) indices. Likewise, the presence of DRF could compromise the sensitivity of DIF indices. We used real data and a simulation study to consider the impact of DIF on DRF indices, and the impact of DRF on DIF indices. Results indicate some interaction between DIF and DRF that varies across data collection designs. We consider the implications of these results for research and practice.

We evaluated the psychometric properties of the Trauma Informed Practice Scales -- School Counseling Programs Version scores using item response theory with a sample of 270 school counselors. Participants ranged in age from 24 to 69 years (M = 42.82, SD = 9.96). Participants identified as female (81.5%), male (14.1%) or unreported (4.4%,). Participants' racial and ethnic backgrounds were: White (79.3%), African American or Black (5.6%), Multiracial (5.2%), Latino/Hispanic/Spanish (4.8%), American Indian/Alaskan Native (0.4%), Other (0.4%), or unreported (4.4%). Participants from 14 states completed an online survey, which included demographics questions and the TIPS-SCP. After removing the poorly performing items, partial credit model estimates explained 58.63% of the variance in participant responses. We found psychometric evidence to support its ability to capture trauma informed practices in schools and school counseling programs.

Children's fears have received scholarly attention for well over 50 years. A considerable amount of literature has focused on such fear variables as fear intensity and fear prevalence scores and age and gender differences. We used meta-analysis to systematically review the findings related to gender differences in children's fear intensity scores and fear prevalence scores and to examine the moderator effect of sample, year of study, and type of instrument on gender differences. Research studies that used the Fear Survey Schedule for Children (FSSC) or an updated version of the FSSC, were included in this meta-analysis. The findings from 58 intensity and 17 prevalence studies suggest that females have 11.4% higher total fear scores than males and females have 7.2% more fears than males. Results of sub-group analyses indicate that moderator variables of sample, year of publication, and type/version of FSSC cause significant variability in gender differences.

Researchers who use measurement models for evaluation purposes often select models with stringent requirements, such as Rasch models, which are parametric. Mokken Scale Analysis (MSA) offers a theory-driven nonparametric modeling approach that may be more appropriate for some measurement applications. Researchers have discussed using MSA as a preliminary procedure with which to evaluate data quality before applying a parametric model. However, the literature includes only a few examples in which researchers have integrated MSA techniques with parametric models throughout the analytic procedure. We consider a systematic approach for integrating results from nonparametric MSA techniques with parametric measurement models to evaluate measurement quality and construct scales with useful measurement properties. We use real-data illustrations and a simulation study to demonstrate and systematically explore our approach. We discuss implications for research and practice.

Abstract Background Returning to work after long-term sick leave can be challenging, particularly in small- and medium-sized enterprises (SMEs) where support may be limited. Recognizing the responsibilities and challenges of SME employers, a web-based intervention (hereafter the SME tool) has been developed. The SME tool aims to enhance the employer’s intention and ability to support the sick-listed employee. Based on the Self-Determination Theory, it is hypothesized that this intention is enhanced by intervening in the employer’s autonomy, competences, and relatedness targeted at, e.g., communication with sick-listed employee, involvement of other stakeholders, and practical support. This is achieved by means of providing templates, communication videos, and information on legislation. This article describes the design of an effect and process evaluation of the SME tool. Methods A randomized controlled trial (RCT) with a 6-month follow-up will be conducted with a parallel-group design with two arms: an intervention group and a control group. Sick-listed employees (≤ 8 weeks) of SMEs (≤ 250 employees) at risk of long-term sick leave and their employers will be recruited and randomly allocated as a dyad (1:1). Employers randomized to the intervention group receive unlimited access to the SME tool, while those in the control group will receive care as usual. The primary outcome is the satisfaction of the employee with the return to work (RTW) support provided by their employer. Secondary outcomes include social support, work performance, and quality of work life at the employee level and self-efficacy in providing RTW support at the employer level. Outcomes will be assessed using questionnaires at baseline and 1, 3, and 6 months of follow-up. Process evaluation measures include, e.g., recruitment and use of and perceived usefulness of the SME tool. Additionally, semi-structured interviews with employers, employees, and occupational physicians will explore the interpretation of the RCT results and strategies for the national implementation of the SME tool. Discussion The SME tool is hypothesized to be valuable in addition to usual care helping employers to effectively support the RTW of their long-term sick-listed employees, by improving the employers’ intention and ability to support. Trial registration ClinicalTrials.gov, NCT06330415. Registered on February 14, 2024.

Abstract Left ventricular hypertrophy (LVH) is often used as an indicator to assess hypertension‐mediated organ damage (HMOD), alongside hypertensive retinopathy (HR) and nephropathy. Assessment of HMOD is crucial when making decisions about treatment optimization. Despite longstanding debate over its reliability to detect LVH, it is common practice to perform an electrocardiogram (ECG) instead of directly assessing left ventricular mass with echocardiography. In this study, the presence of LVH was evaluated using both ECG and echocardiography among consecutive patients suspected of therapy‐resistant hypertension or secondary hypertension in the outpatient clinic of the Department of Internal Medicine at the Diakonessen Hospital, Utrecht, the Netherlands, between July 15, 2017, and July 31, 2020. The primary endpoints were the specificity and sensitivity of ECG as a diagnostic tool for LVH, with echocardiography serving as the reference method. Among the 329 participants, we identified 70 individuals (21.3%) with true LVH based on echocardiography. The ECG displayed a sensitivity of 47.9% and a specificity of 75.3%. Moreover, the area under the receiver operating characteristics curve was 0.604. In conclusion, ECG demonstrates limited value in identifying LVH. Considering the importance of accurately assessing HMOD for treatment optimization of hypertension, the role of ECG as a diagnostic tool for LVH is, therefore, questionable. Instead, we recommend employing standard echocardiography as a more reliable diagnostic.

Rating scale analysis techniques provide researchers with practical tools for examining the degree to which ordinal rating scales (e.g., Likert-type scales or performance assessment rating scales) function in psychometrically useful ways. When rating scales function as expected, researchers can interpret ratings in the intended direction (i.e., lower ratings mean "less" of a construct than higher ratings), distinguish between categories in the scale (i.e., each category reflects a unique level of the construct), and compare ratings across elements of the measurement instrument, such as individual items. Although researchers have used these techniques in a variety of contexts, studies are limited that systematically explore their sensitivity to problematic rating scale characteristics (i.e., "rating scale malfunctioning"). I used a real data analysis and a simulation study to systematically explore the sensitivity of rating scale analysis techniques based on two popular polytomous item response theory (IRT) models: the partial credit model (PCM) and the generalized partial credit model (GPCM). Overall, results indicated that both models provide valuable information about rating scale threshold ordering and precision that can help researchers understand how their rating scales are functioning and identify areas for further investigation or revision. However, there were some differences between models in their sensitivity to rating scale malfunctioning in certain conditions. Implications for research and practice are discussed.

Western media are not equipped to handle right-wing populists like Donald Trump, Orbán, or the AfD. Moreover, constitutional theorists who argue that democracy should be purely procedural are joining the populist chorus. In our current age of populism we keep telling ourselves that everyone’s voice is always equally valid – also when based on lies and disinformation. It’s just another “point of view”. What populism has undermined is the right but also the courage to call out those who deliberately spread lies as well as those who in doing so openly use democratic institutions to destroy democracy.

Purpose: 2-Fluorodeoxyglucose-PET (FDG-PET) is a powerful tool to study glucose metabolism in mammalian brains, but cellular sources of glucose uptake and metabolic connectivity during aging are not yet understood. Methods: Healthy wild-type mice of both sexes (2–21 months of age) received FDG-PET and cell sorting after in vivo tracer injection (scRadiotracing). FDG uptake per cell was quantified in isolated microglia, astrocytes and neurons. Cerebral FDG uptake and metabolic connectivity were determined by PET. A subset of mice received measurement of blood glucose levels to study associations with cellular FDG uptake during aging. Results: Cerebral FDG-PET signals in healthy mice increased linearly with age. Cellular FDG uptake of neurons increased between 2 and 12 months of age, followed by a strong decrease towards late ages. Contrarily, FDG uptake in microglia and astrocytes exhibited a U-shaped function with respect to age, comprising the predominant cellular source of higher cerebral FDG uptake in the later stages. Metabolic connectivity was closely associated with the ratio of glucose uptake in astroglial cells relative to neurons. Cellular FDG uptake was not associated with blood glucose levels and increasing FDG brain uptake as a function of age was still observed after adjusting for blood glucose levels. Conclusion: Trajectories of astroglial glucose uptake drive brain FDG-PET alterations and metabolic connectivity during aging.

Abstract Background The current report investigates fusion rates and patient-reported outcomes following lumbar spinal surgery using cellular bone allograft (CBA) in patients with risk factors for non-union. Methods A prospective, open label study was conducted in subjects undergoing lumbar spinal fusion with CBA (NCT 02969616) to assess fusion success rates and patient-reported outcomes in subjects with risk factors for non-union. Subjects were categorized into low-risk (≤ 1 risk factors) and high-risk (> 1 risk factors) groups. Radiographic fusion status was evaluated by an independent review of dynamic radiographs and CT scans. Patient-reported outcome measures included quality of life (EQ-5D), Oswestry Disability Index (ODI) and Visual Analog Scales (VAS) for back and leg pain. Adverse event reporting was conducted throughout 24-months of follow-up. Results A total of 274 subjects were enrolled: 140 subjects (51.1%) were categorized into the high-risk group (> 1 risk factor) and 134 subjects (48.9%) into the low-risk group (≤ 1 risk factors). The overall mean age at screening was 58.8 years (SD 12.5) with a higher distribution of females (63.1%) than males (36.9%). No statistical difference in fusion rates were observed between the low-risk (90.0%) and high-risk (93.9%) groups (p > 0.05). A statistically significant improvement in patient-reported outcomes (EQ-5D, ODI and VAS) was observed at all time points (p

Abstract Charge-transfer excitations are of paramount importance for understanding the electronic structure of copper-oxide based high-temperature superconductors. In this study, we investigate the response of a Bi $$_2$$ 2 Sr $$_2$$ 2 CaCu $$_2$$ 2 O $$_{\textrm{8}+ \delta }$$ 8 + δ crystal to the charge redistribution induced by an infrared ultrashort pulse. Element-selective time-resolved core-level photoelectron spectroscopy with a high energy resolution allows disentangling the dynamics of oxygen ions with different coordination and bonds thanks to their different chemical shifts. Our experiment shows that the O 1s component arising from the Cu–O planes is significantly perturbed by the infrared light pulse. Conversely, the apical oxygen, also coordinated with Sr ions in the Sr-O planes, remains unaffected. This result highlights the peculiar behavior of the electronic structure of the Cu–O planes. It also unlocks the way to study the out-of-equilibrium electronic structure of copper-oxide-based high-temperature superconductors by identifying the O 1s core-level emission originating from the oxygen ions in the Cu–O planes. This ability could be critical to gain information about the strongly-correlated electron ultrafast dynamical mechanisms in the Cu–O plane in the normal and superconducting phases.

AbstractObjective To analyse the mechanisms at play in the adjudications made by professionals and socially vulnerable patients with type 2 diabetes about their eligibility for care.Design, setting and subjects The study included 14 patients and 10 health professionals in seven general practice surgeries in deprived areas in Greater Copenhagen. The study data consist of 17 semi-structured interviews with patients and 22 with health professionals immediately after observation of 23 consultations. Our analytical approach was inspired by Systematic Text Condensation and the concept of ‘candidacy’ for access to health care.Results Adjudications of patients not being candidates for services were common, but we also found that both patients and health professionals worked to align the services to the needs of the patients. This could include using services differently than was intended by the providers or by changing routines to make it easier for patients to use the services. We discuss these processes as ‘tinkering’. This usually implies that the best individual solution for the patient is aimed for, and in this study, the best solution sometimes meant not focusing on diabetes.Conclusion The study adds to existing knowledge about access to services for socially vulnerable patients by demonstrating that both patients and professionals in general practice engage in tinkering processes to make services work.

Background: The attention of leprosy management has shifted to reduce the burden of leprosy complications, including leprosy reactions. Leprosy reaction is the predominant cause of nerve impairment that leads to disability and lowers the quality of life of the affected. Purpose: The aim of this study was to provide primary data about leprosy reaction epidemiology, risk factor, and outcomes in the post-elimination era. Methods: A cross-sectional study was held in a general hospital in Gresik City, Indonesia, to give clinical demography, risk factors, and outcomes of leprosy reaction. Result: New leprosy reaction cases remain detected each year. There were 57 (58.8%) out of 97 leprosy patients who had a reactional episode. The incidence of leprosy reactions has been increasing in the last three years. The multibacillary (MB) group and type 2 reactions dominated leprosy reactions, which mostly occurred in the young adult population. Some of the leprosy reaction patients had developed a complication due to prolonged steroid usage. Conclusion: Leprosy cases in a young population with a high risk of developing reaction episodes need collaboration in the management to prevent deformity in youth.

Abstract Background In the last decade, interest in working life expectancy (WLE) and socioeconomic differences in WLE has grown considerably. However, a comprehensive overview of the socioeconomic differences in WLE is lacking. The aim of this review is to systematically map the research literature to improve the insight on differences in WLE and healthy WLE (HWLE) by education, occupational class and income while using different ways of measuring and estimating WLE and to define future research needs. Methods A systematic search was carried out in Web of Science, PubMed and EMBASE and complemented by relevant publications derived through screening of reference lists of the identified publications and expert knowledge. Reports on differences in WLE or HWLE by education, occupational class or income, published until November 2022, were included. Information on socioeconomic differences in WLE and HWLE was synthesized in absolute and relative terms. Results A total of 26 reports from 21 studies on educational and occupational class differences in WLE or HWLE were included. No reports on income differences were found. On average, WLE in persons with low education is 30% (men) and 27% (women) shorter than in those with high education. The corresponding numbers for occupational class difference were 21% (men) and 27% (women). Low-educated persons were expected to lose more working years due to unemployment and disability retirement than high-educated persons. Conclusions The identified socioeconomic inequalities are highly relevant for policy makers and pose serious challenges for equitable pension policies. Many policy interventions aimed at increasing the length of working life follow a one-size-fits-all approach which does not take these inequalities into account. More research is needed on socioeconomic differences in HWLE and potential influences of income on working life duration.

Functional analyses are the main method to classify mismatch repair (MMR) gene variants of uncertain significance (VUSs). However, the pathogenicity remains unclear for many variants because of conflicting results between clinical, molecular, and functional data. In this study, we evaluated whether whole exome sequencing (WES) could add another layer of evidence to elucidate the pathogenicity of MMR variants with conflicting interpretations. WES was performed on formalin-fixed paraffin-embedded tumor tissue of eight patients with a constitutional MMR VUS (seven families), including eight colorectal and two endometrial carcinomas and one ovarian carcinoma. Cell-free CIMRA assays were performed to assign Odds of Pathogenicity to these VUSs. In four families, seven tumors showed MMR deficiency-associated mutational signatures, supporting the pathogenicity of the VUS. Moreover, somatic (second) MMR hits identified in the WES data were found to explain MMR staining patterns when the MMR staining was discordant with the reported germline MMR gene variant. In conclusion, WES did not significantly reclassify VUS in these cases but clarified some phenotypic aspects such as age of onset and explanations in case of discordant MMR stainings.

BackgroundGenetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain.MethodsWe engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-β pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aβ content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays.ResultsLeveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aβ content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged.DiscussionOur findings demonstrate that fibrillar Aβ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.

Researchers frequently evaluate rater judgments in performance assessments for evidence of differential rater functioning (DRF), which occurs when rater severity is systematically related to construct-irrelevant student characteristics after controlling for student achievement levels. However, researchers have observed that methods for detecting DRF may be limited in sparse rating designs, where it is not possible for every rater to score every student. In these designs, there is limited information with which to detect DRF. Sparse designs can also exacerbate the impact of artificial DRF, which occurs when raters are inaccurately flagged for DRF due to statistical artifacts. In this study, a sequential method is adapted from previous research on differential item functioning (DIF) that allows researchers to detect DRF more accurately and distinguish between true and artificial DRF. Analyses of data from a rater-mediated writing assessment and a simulation study demonstrate that the sequential approach results in different conclusions about which raters exhibit DRF. Moreover, the simulation study results suggest that the sequential procedure results in improved accuracy in DRF detection across a variety of rating design conditions. Practical implications for language testing research are discussed.