Further Validation of the Persecutory Ideation Questionnaire in the Italian Context: Results From Classical and Modern Test Theory.

The Persecutory Ideation Questionnaire (PIQ) is a valuable instrument to measure persecutory ideation. The aim of this study is to validate the scale in the Italian context and to extend the study of its psychometric properties using approaches from both classical and modern test theories. The results of the study, involving 700 individuals, confirmed the one-factor structure and the good validity and reliability of the scale. Full metric invariance and partial scalar and strict invariance were also supported across gender, age, and education level groups. Rasch analysis indicated that the 5-point response scale is well-functioning and that the PIQ is most appropriate to measure high levels of persecutory ideation. The results contribute to a better understanding of the measurement properties of the PIQ. The paper discusses the advantages and contributions of each method used to explore the measurement properties of the scale.

Psychometric Evaluation of the Social Phobia Inventory (SPIN) in Algeria: A Comprehensive Approach Utilizing Network Analysis, Confirmatory Factor Analysis, and the Polytomous Rasch Model.

This study aimed to evaluate the psychometric characteristics of the Social Phobia Inventory (SPIN) by employing network analysis, confirmatory factor analysis, and the Polytomous Rasch Model. A cross-sectional data set was collected comprising 1,530 participants, with 959 being women and 571 being men. The Bootstrap Exploratory Graph Analysis unveiled the presence of two dimensions, with Items 17, 15, 5, 14, 6, and 9 exhibiting the highest strength centrality index. Notably, the Network Comparison Test indicated no differences in Network Invariance and global strength between the networks of women and men. Furthermore, the confirmatory factor analysis results demonstrated that the two extracted dimensions displayed an acceptable goodness of fit. In addition, the reliability coefficient values were acceptable, exceeding the threshold of 0.70. The Rasch analysis results suggested an overall fit, but some items exhibited overlap, suggesting their potential removal. Furthermore, it was recommended to develop new items to address gaps between existing items, particularly for measuring the lower levels of Social Anxiety Disorder. In conclusion, these findings provide robust evidence supporting the reliability and validity of the SPIN as a tool for measuring Social Anxiety Disorder in Algeria.

Italian adaptation and psychometric validation of the Fatigue Impact Scale (FIS) and its modified versions in adults with multiple sclerosis: a Rasch analysis study.

Purpose: Several outcome measures are available to assess the severity of fatigue in people with multiple sclerosis (MS). The aim of this study was to adapt the Italian version of the Fatigue Impact Scale (FIS-40) and its modified versions: a 21-item Modified scale (MFIS-21), its 5-item short version (MFIS-5), and an 8-item version for daily use (DFIS-8) and investigate their measurement properties through classical theory-test (CTT) and Rasch analysis (RA).Methods: 229 Italian-speaking adults with MS were included. Questionnaires were cross-culturally translated and subjected to CTT (i.e. internal consistency through Cronbach's alpha and unidimensionality through confirmatory factor analysis [CFA]) and RA. (i.e. internal construct validity, reliability, and targeting).Results: Internal consistency was high for all scales (>0.850). Final CFAs reported issues in the unidimensionality for all scales except for FIS-40. Baseline RA revealed a misfit for all scales. After adjusting for local dependency, FIS-40, MFIS-21, and MFIS-5 fitted the Rasch model (RM). MFIS-21 and D-FIS-8 required a structural modification, i.e. item deletions to satisfy the RM.Conclusion: The FIS-40, MFIS-21, MFIS-5, and DFIS-8 achieved the fit to the RM after statistical and structural modifications. The fit to the RM allowed for providing ordinal-to-interval measurement conversion tables for all the questionnaires.

The Fatigue Impact Scale (FIS-40), the 21-item Modified scale (MFIS-21), its 5-item short version (MFIS-5) and the 8-item version for daily use (DFIS-8) have been successfully cross-culturally validated in Italian.The FIS-40 and its versions fit the Rasch Model with minimal changes, determining that the studied outcomes represent a unidimensional construct, i.e. fatigue in multiple sclerosis.The final Rasch Model enables the transformation of scores into interval-level measurements, allowing clinicians to gauge the distance between individuals' scores on the scale continuum.Interval-level transformation allows rehabilitation professionals to better interpret clinical changes and researchers to apply parametric statistics.

Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment.

Purpose: The present paper presents developments and advanced practical applications of Rasch's theory and statistical analysis to construct questionnaires for measuring a person's traits. The flaws of questionnaires providing raw scores are well known. Scores only approximate objective, linear measures. The Rasch Analysis allows you to turn raw scores into measures with an error estimate, satisfying fundamental measurement axioms (e.g., unidimensionality, linearity, generalizability). A previous companion article illustrated the most frequent graphic and numeric representations of results obtained through Rasch Analysis. A more advanced description of the method is presented here.Conclusions: Measures obtained through Rasch Analysis may foster the advancement of the scientific assessment of behaviours, perceptions, skills, attitudes, and knowledge so frequently faced in Physical and Rehabilitation Medicine, not less than in social and educational sciences. Furthermore, suggestions are given on interpreting and managing the inevitable discrepancies between observed scores and ideal measures (data-model "misfit"). Finally, twelve practical take-home messages for appraising published results are provided.Implications for rehabilitationThe current work is the second of two papers addressed to rehabilitation clinicians looking for an in-depth introduction to the Rasch analysis.The first paper illustrates the most common results reported in published papers presenting the Rasch analysis of questionnaires.The present article illustrates more advanced applications of the Rasch analysis, also frequently found in publications.Twelve take-home messages are given for a critical appraisal of the results.

A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data.

We propose a novel nonparametric Bayesian item response theory model that estimates clusters at the question level, while simultaneously allowing for heterogeneity at the examinee level under each question cluster, characterized by a mixture of binomial distributions. The main contribution of this work is threefold. First, we present our new model and demonstrate that it is identifiable under a set of conditions. Second, we show that our model can correctly identify question-level clusters asymptotically, and the parameters of interest that measure the proficiency of examinees in solving certain questions can be estimated at a n rate (up to a log term). Third, we present a tractable sampling algorithm to obtain valid posterior samples from our proposed model. Compared to the existing methods, our model manages to reveal the multi-dimensionality of the examinees' proficiency level in handling different types of questions parsimoniously by imposing a nested clustering structure. The proposed model is evaluated via a series of simulations as well as apply it to an English proficiency assessment data set. This data analysis example nicely illustrates how our model can be used by test makers to distinguish different types of students and aid in the design of future tests.

Psychometric evaluation of the WHOQOL-BREF and its shorter versions for general Thai population: confirmatory factor analysis and Rasch analysis.

PURPOSE: Rasch analysis was employed to validate the World Health Organization Quality of Life-BREF (WHOQOL-BREF) and its existing shorter versions in the general Thai population. METHODS: 1200 respondents were randomly selected to complete the questionnaire. Confirmatory factor analysis (CFA) was employed to test the structure of the WHOQOL-BREF and its shorter versions with the random sub-sample of 900 respondents, while Rasch analysis was performed with a random sub-sample of 300 respondents. RESULTS: The CFA confirmed the factor structure of WHOQOL-BREF and its shorter versions. The Rasch analysis revealed that the WHOQOL-BREF, when a four-domain structure was tested using a subtest approach, achieved acceptable model fit to the Rasch model and met the expectations of unidimensionality with high reliability (PSI = 0.87). Individual domain models were also unidimensional, but reliability of the 3-item social domain was inadequate. While the 8-item EUROHIS-QOL-8 and 5-item WHOQOL-5 achieved an overall acceptable fit and met the expectations of unidimensionality, the reliability of the WHOQOL-5 was below the acceptable threshold (PSI = 0.66). Reliability of the EUROHIS-QOL-8 was satisfactory (PSI = 0.79). CONCLUSIONS: The WHOQOL-BREF is a valid instrument for use in the Thai general population, both as a total score as well as individual subscales. Rasch analysis also supports the use of EUROHIS-QOL-8, but the WHOQOL-5 lacks good reliability. While the reliability of the EUROHIS-QOL-8 is sufficiently high for between-group analysis, the Thai WHOQOL-BREF total score can also be used for within-participant analyses. Rasch investigation with a more varied health conditions of general Thai samples or patient groups is encouraged for future studies.

Information from Noise: Measuring Dyslexia Risk Using Rasch-like Matrix Factorization with a Procedure for Equating Instruments.

This study examines the psychometric properties of a screening protocol for dyslexia and demonstrates a special form of matrix factorization called Nous based on the Alternating Least Squares algorithm. Dyslexia presents an intrinsically multidimensional complex of cognitive loads. By building and enforcing a common 6-dimensional space, Nous extracts a multidimensional signal for each person and item from test data that increases the Shannon entropy of the dataset while at the same time being constrained to meet the special objectivity requirements of the Rasch model. The resulting Dyslexia Risk Scale (DRS) yields linear equal-interval measures that are comparable regardless of the subset of items taken by the examinee. Each measure and cell estimate is accompanied by an efficiently calculated standard error. By incorporating examinee age into the calibration process, the DRS can be generalized to all age groups to allow the tracking of individual dyslexia risk over time. The methodology was implemented using a 2019 calibration sample of 828 persons aged 7 to 82 with varying degrees of dyslexia risk. The analysis yielded high reliability (0.95) and excellent receiver operating characteristics (AUC = 0.96). The analysis is accompanied by a discussion of the information-theoretic properties of matrix factorization.

Minimal Clinically Important Difference (MCID) in Patient-Reported Outcome Measures for Neurological Conditions: Review of Concept and Methods.

The concept of the minimal clinically important difference (MCID) emerged from the recognition that statistical significance alone is not enough to determine the clinical relevance of treatment effects in clinical research. In many cases, statistically significant changes in outcomes may not be meaningful to patients or may not result in any tangible improvements in their health. This has led to a growing emphasis on the importance of measuring patient-reported outcome measures (PROMs) in clinical trials and other research studies, in order to capture the patient perspective on treatment effectiveness. MCID is defined as the smallest change in scores that is considered meaningful or important to patients. MCID is particularly important in fields such as neurology, where many of the outcomes of interest are subjective or based on patient-reported symptoms. This review discusses the challenges associated with interpreting outcomes of clinical trials based solely on statistical significance, highlighting the importance of considering clinical relevance and patient perception of change. There are two main approaches to estimating MCID: anchor-based and distribution-based. Anchor-based approaches compare change scores using an external anchor, while distribution-based approaches estimate MCID values based on statistical characteristics of scores within a sample. MCID is dynamic and context-specific, and there is no single 'gold standard' method for estimating it. A range of MCID thresholds should be defined using multiple methods for a disease under targeted intervention, rather than relying on a single absolute value. The use of MCID thresholds can be an important tool for researchers, neurophysicians and patients in evaluating the effectiveness of treatments and interventions, and in making informed decisions about care.

Using a Non-Contact Sensor to Delineate Management Zones in Vineyards and Validation with the Rasch Model.

The production of high-quality wines is one of the primary goals of modern oenology. In this regard, it is known that the potential quality of a wine begins to be determined in the vineyard, where the quality of the grape, initially, and later that of the wine, will be influenced by the soil properties. Given the spatial variability of the fundamental soil properties related to the potential grape production, such as texture, soil organic matter content, or cation exchange capacity, it seems that a uniform management of a vineyard is not the most optimal way to achieve higher grape quality. In this sense, the delineation of zones with similar soil characteristics to implement site-specific management is essential, reinforcing the interest in incorporating technologies and methods to determine these homogeneous zones. A case study was conducted in a 3.3 ha vineyard located near Évora, south of Portugal. A non-contact sensor (DUALEM 1S) was used to measure soil apparent electrical conductivity (ECa) in the vineyard, and later, a kriged ECa map was generated. ECa and elevation maps were utilised to delineate homogeneous zones (management zones, MZs) in the field through a clustering process. MZs were validated using some soil properties (texture; pH; organic matter-OM; phosphorous-P2O5; potassium-K2O; the sum of the exchange bases-SEB; and cation exchange capacity-CEC), which were determined from 20 soil samples taken in the different MZs. Validation was also performed using Rasch measures, which were defined based on the formulation of the objective and probabilistic Rasch model, integrating the information from the aforementioned soil properties at each sampling location. The comparison of the MZs was more evident with the use of the Rasch model, as only one value was to be employed in each MZ. Finally, an additional validation was conducted using a vegetation index to consider the plant response, which was different in each MZ. The use of a non-contact sensor to measure ECa constitutes an efficient technological tool for implementing site-specific management in viticulture, which allows for the improvement of decision-making processes by considering the inherent spatial variability of the soil.

Providing meaningful interpretation of performance outcome measures by co-calibration with patient-reported outcomes through the Rasch model: illustration with multiple sclerosis measures.

Performance outcome (PerfO) measures are based on tasks performed by patients in a controlled environment, making their meaningful interpretation challenging to establish. Co-calibrating PerfO and patient-reported outcome (PRO) measures of the same target concept allow for interpretation of the PerfO with the item content of the PRO. The Rasch model applied to the discretized PerfO measure together with the PRO items allows expressing parameters related to the PerfO measure in the PRO metric for it to be linked to the PRO responses. We applied this approach to two PerfO measures used in multiple sclerosis (MS) for walking and manual ability: the Timed 25-Foot Walk (T25FW) and the 9-Hole Peg Test (9HPT). To determine meaningful interpretation of these two PerfO measures, they were co-calibrated with two PRO measures of closely related concepts, the MS walking scale - 12 items (MSWS-12) and the ABILHAND, using the data of 2,043 subjects from five global clinical trials in MS. The probabilistic relationships between the PerfO measures and the PRO metrics were used to express the response pattern to the PRO items as a function of the unit of the PerfOs. This example illustrates the promises of the co-calibration approach for the interpretation of PerfO measures but also highlights the challenges associated with it, mostly related to the quality of the PRO metric in terms of coverage of the targeted concept. Co-calibration with PRO measures could also be an adequate solution for interpretation of digital sensor measures whose meaningfulness is also often questioned.

Psychometric Properties of the Perceived Collective Family Efficacy Scale in Algeria.

The Perceived Collective Family Efficacy Scale is a tool utilized to assess the effectiveness of a family as a functioning system. The scale has a single-factor structure with good validity and reliability. However, there is a shortage of psychometric evidence of the scale in an Arab context. This study aimed to assess the psychometric properties of the Perceived Collective Family Efficacy Scale among Algerian students. A cross-sectional study was conducted to recruit 300 students from Algerian universities. The students completed the 20-item Perceived Collective Family Efficacy Scale, Arabic version, to measure their beliefs regarding collective efficacy within families. Confirmatory factor analysis (CFA) and the Rasch model were employed to assess the psychometric properties and unidimensionality of the scale. Both CFA and Rasch findings supported the single-factor structure for the Perceived Collective Family Efficacy Scale. Specifically, the CFA indicated that the data aligned with a one-dimensional model. The Rasch analysis revealed favorable indicators of unidimensionality for the scale. Moreover, a thorough examination of the Principal Component Analysis of the Rasch residuals confirmed the existence of a single dimension, which is consistent with the original structure of the Perceived Collective Family Efficacy Scale. These findings provide scientific evidence for the validity and unidimensional nature of the Perceived Collective Family Efficacy Scale. Specifically, the satisfactory psychometric properties findings indicate that the Perceived Collective Family Efficacy Scale could be applied in an Arab context (i.e., in Algerian). The scale's unidimensional structure underscores its effectiveness in measuring beliefs in collective efficacy within families. These results enhance our understanding of family dynamics and provide a reliable measurement tool for assessing family efficacy in similar cultural contexts.

A phubbing scale tested in Bangladesh, Iran, and Pakistan: confirmatory factor, network, and Rasch analyses.

BACKGROUND: Phubbing, a phenomenon of ignoring others in face-to-face conversations due to mobile phone use, can be assessed using a Phubbing Scale (PS). Recently, the PS has been shortened into an eight-item version, the PS-8. However, psychometric properties of the PS-8 among Iranian, Bangladeshi and Pakistani individuals remain understudied, especially using advanced psychometric testing, such as Rasch and network analyses. METHODS: Participants residing in Iran, Bangladesh, and Pakistan (n = 1902; 50.4% females; mean age = 26.3 years) completed the PS-8 and the Internet Disorder Scale-Short Form (IDS9-SF) via an online survey. Network analysis was used to examine if PS-8 items were differentiated from IDS9-SF items; confirmatory factor analysis (CFA) was used to examine the factor structure and measurement invariance of the PS-8; Rasch modeling was used to examine the dimensionality of the PS-8 and differential item functioning (DIF). RESULTS: Network analysis showed that PS-8 items were clustered together with a distance to the IDS9-SF items. The CFA results supported a two-factor structure of the PS-8, and the two-factor structure was found to be invariant across countries and women and men. Rasch model results indicated that the two PS-8 subscales were both unidimensional and did not display DIF across countries and gender/sex. CONCLUSION: The PS-8 is a feasible and robust instrument for healthcare providers, especially mental health professionals, to quickly assess and evaluate individuals' phubbing behaviors.

Expert judgement of collaborative cloud classroom quality and its criteria using the many-facets rasch model.

Collaborative Cloud Classroom (3CR) is an educational application that provides flexibility in the learning process. This specialized tool is designed to improve analytical and teambuilding skills, as well as enable students to document ideas, which are subsequently developed into bubble diagrams and text outlines. This study aims to assess and analyze the menu qualities possessed by the 3CR application using the Many-Facet Rasch Model (MFRM) analysis using 5 raters and 6 menus. A rating assessment was applied to 5 criteria, namely usability, functionality, visual communication, learning design, and security. In this case, a total of 135 from 150 data points were coded into FACETS software. The results showed that the six menus in the 3CR application were valid and reliable, as well as met the quality standards of learning tools. Security criteria were also the most difficult standards for raters to measure in all the application menus. The study also found that Rater A was more severe, and Rater E was more lenient in rating the 3CR menu. Rater B has overfitting and detected bias between rater gender and 3CR's menu (Discussion Forum and Learning Reflection menu) based on MFRM analysis.

Comparing Person-Fit and Traditional Indices Across Careless Response Patterns in Surveys.

Methods to identify carelessness in survey research can be valuable tools in reducing bias during survey development, validation, and use. Because carelessness may take multiple forms, researchers typically use multiple indices when identifying carelessness. In the current study, we extend the literature on careless response identification by examining the usefulness of three item-response theory-based person-fit indices for both random and overconsistent careless response identification: infit MSE outfit MSE, and the polytomous lz statistic. We compared these statistics with traditional careless response indices using both empirical data and simulated data. The empirical data included 2,049 high school student surveys of teaching effectiveness from the Network for Educator Effectiveness. In the simulated data, we manipulated type of carelessness (random response or overconsistency) and percent of carelessness present (0%, 5%, 10%, 20%). Results suggest that infit and outfit MSE and the lz statistic may provide complementary information to traditional indices such as LongString, Mahalanobis Distance, Validity Items, and Completion Time. Receiver operating characteristic curves suggested that the person-fit indices showed good sensitivity and specificity for classifying both over-consistent and under-consistent careless patterns, thus functioning in a bidirectional manner. Carelessness classifications based on low fit values correlated with carelessness classifications from LongString and completion time, and classifications based on high fit values correlated with classifications from Mahalanobis Distance. We consider implications for research and practice.

Does Sparseness Matter? Examining the Use of Generalizability Theory and Many-Facet Rasch Measurement in Sparse Rating Designs.

Sparse rating designs, where each examinee's performance is scored by a small proportion of raters, are prevalent in practical performance assessments. However, relatively little research has focused on the degree to which different analytic techniques alert researchers to rater effects in such designs. We used a simulation study to compare the information provided by two popular approaches: Generalizability theory (G theory) and Many-Facet Rasch (MFR) measurement. In previous comparisons, researchers used complete data that were not simulated-thus limiting their ability to manipulate characteristics such as rater effects, and to understand the impact of incomplete data on the results. Both approaches provided information about rating quality in sparse designs, but the MFR approach highlighted rater effects related to centrality and bias more readily than G theory.

Developing a common metric using current scales for assessing functioning in patients with knee osteoarthritis.

Objectives: Various scales exist to assess different domains of functioning in knee osteoarthritis (OA). This study aimed to explore whether it is possible to develop a common metric (CM) from the frequently used scales to assess functioning in knee OA. Patients and methods: The methodological study evaluated 411 patients (81 males, 330 females; mean age: 61.8±10.5 years; range, 41 to 88 years) with knee OA. Data from the Health Assessment Questionnaire, Oxford Knee Score, Medical Outcomes Study Short Form 36, Knee Injury and Osteoarthritis Outcome Score, Western Ontario and McMaster Universities Arthritis Index, and the Nottingham Health Profile were used, and the items focusing on self-care, mobility, and domestic activity domains based on the activities and participation component of the International Classification of Functioning, Disability, and Health were included. Concurrent calibration was performed to combine the items of the scales. The CM parameters were estimated using the Rasch measurement model. Reliability was assessed using the person separation index. The CM was utilized to generate a transformation table to convert the scale scores to each other based on the reference metric score. Results: Each scale fitted the Rasch model. Item invariance was achieved for the CM (p=0.775). The CM had a person separation index of 0.827. Age, sex, and disease duration did not cause difference in item functions. The CM satisfied the assumptions of unidimensionality and local independence. Conclusion: A reliable CM was created from the commonly used scales to measure functioning in individuals with knee OA. Thus, clinicians and researchers can refer to the transformation table to directly compare scores of those scales and use them interchangeably.

Understanding professional development challenges of Chinese public health professionals: association and prediction analyses with data validity screening.

Background: Little is known about the public health professionals engaged in educating and training new or future researchers in public health. Research in this direction identifies their issues, concerns, challenges, and needs. This study focused on the professional development challenges of Chinese public health professionals. Methods: Snowball sampling was utilized. A total of 265 public health professionals participated. An instrument of 6 dimensions (burnout, sleep issue, mood issue, friends' support, exercise, and challenges) was developed, revised, and administered online. Two different approaches, the conventional and data screening approaches, were applied. The former started with item quality analyses, whereas the latter began with data quality checks. The chi-square tests of associations and logistic regressions were performed on both approaches. Results and discussion: 19.25% of the participants were detected and deleted as careless respondents. Using both approaches, six professional development challenges except one ("Multidisciplinary learning") were significantly associated with various demographic features. The two approaches produced different models though they converged sometimes. The latent variables of exercise predicted professional development challenges more frequently than other latent variables. Regarding correct classification rates, results from the data screening approach were comparable to those from the conventional approach. Conclusion: The latent variables of exercise, such as "Exercise effects," "Expectations of exercise," and "Belief in exercise," might be understudied. More research is necessary for professional development challenges using exercise as a multidimensional construct. Based on the current study, screening and deleting careless responses in survey research is necessary.

Measuring needs-based quality of life and self-perceived health inequity in patients with multimorbidity: investigating psychometric measurement properties of the MultiMorbidity Questionnaire (MMQ) using primarily Rasch models.

BACKGROUND: Multimorbidity is a burden for the individual and to the healthcare sector worldwide, leading to a rising number of intervention studies towards this patient group. To measure a possible effect of such interventions, an adequate patient-reported outcome measure (PROM) is essential. The aim of this study was to assess the draft MultiMorbidity Questionnaire (MMQ), a PROM measuring needs-based quality of life and self-perceived inequity in patients with multimorbidity, for its psychometric properties and to adjust it accordingly to create a content- and construct valid measure. METHODS: The draft MMQ was sent to 1198 eligible respondents with multimorbidity. Modern test theory and classical test theory were used to analyse data. Dimensionality of the suggested domains and invariance of the items were assessed through item analysis, examining the fit to a psychometric model. RESULTS: The psychometric analyses were based on responses from 390 patients with multimorbidity. In the MMQ1, measuring needs-based QoL, evidence of six unidimensional scales was confirmed: physical ability (6 items), worries (6 items), limitations in everyday life (10 items), my social life (6 items), self-image (6 items), and personal finances (3 items). The psychometric analyses of the MMQ2 outlined four unidimensional scales measuring the feeling of Self-perceived inequity in patients with multimorbidity: experiences of being stigmatised (4-5 items), Experiences of insufficient understanding of the burden of disease (3 items), Experiences of not being seen and heard (4 items), Experience of powerlessness (5 items). These scales are relevant for patients' with multimorbidity encounters with (1) their general pratitioner, (2) staff at their general practitioner's surgery, (3) healthcare professionals, (4) staff at the local authorities and (5) friends, family, and others. CONCLUSION: The MMQ, a QoL measure for patients living with multimorbidity has been validated: the MMQ1 is a condition-specific PROM with adequate psychometric properties designed to measure needs-based QoL. The MMQ2 measuring Self-perceived inequity, has also been found to possess adequate measurement properties; however due to the risk of type 2 error a revalidation of MMQ2 is suggested.

Dimensionality and invariance of ADL, IADL, BI-M2/WG-SS, and GALI in large surveys in France (2008-2014) and implications for measuring disability in epidemiology.

BACKGROUND: The epidemiological investigation and surveillance of disability requires well-constructed, invariant, and, if possible, exchangeable measures. However, the current or recommended measures have not been thoroughly investigated with respect to these issues. Here we examined the dimensional structure and invariance of four measures across sociodemographic groups: Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Budapest Initiative Mark 2 (BI-M2) and Washington Group on Disability Statistics Short Set (WG-SS), and Global Activity Limitation Indicator (GALI). METHODS: We used data from three large nationwide representative surveys conducted in France between 2008 and 2014. The surveys included these four measures and classical and modern approaches (correlations, principal component analysis, Rasch modeling) were used to assess their dimensional structure as well as their invariance through differential item functioning (DIF) for sociodemographic characteristics. Polytomous logistic regression models were used to assess gradients in health inequalities associated with these measures. RESULTS: For many items of ADL, IADL, and BI-M2/WG-SS, we consistently observed disordered response thresholds, rejection of unidimensionality, and DIF evidence for sociodemographic characteristics across the survey samples. Health inequality gradients were erratic. In addition, it was impossible to identify a common continuum for GALI, ADL, IADL, and BI-M2/WG-SS or their constituent items. CONCLUSION: This study warns against the current practice of investigating disability in epidemiology using measures that are unsuitable for epidemiological use, incommensurable, and inadequate regarding the basic requisites of dimensionality and invariance. Developing invariant measures and equating them along a common continuum to enlarge the common bases of measurement should therefore be a priority.

Digital competency mapping dataset of pre-service teachers in Indonesia.

This dataset used the Digital Competency Scale (DCS) to describe Indonesian pre-service teachers' perceptions. The DCS instrument consisted of five constructs/dimensions, which are: 1) data and information literacy, 2) communication and collaboration, 3) digital content creation, 4) safety, and 5) problem-solving, with a total of 36 items using five-point agreement Likert scale. The data was gathered from 23 education and teacher training faculties at Muhammadiyah Universities in 14 provinces across Indonesia in the academic year 2021/2022. A total of 1400 students (18 to 23 years old) in their first to fifth years of study were recruited using the convenience sampling technique, where they participated in filling in the survey electronically using Google Form. The dataset was analysed with the Rasch model measurement approach using WINSTEPS version 5.2.3 software for data cleaning and validation, and reliability and validity testing of the instrument. This dataset analysis can help teacher-training institutions, or higher education policymakers design effective programmes to improve pre-service teachers' digital competencies. Furthermore, researchers can compare this dataset with more rigorous data from other countries.