Discrimination Parameters Research Articles

A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms

BackgroundAplastic anemia (AA) and myelodysplastic neoplasms (MDS) have similar peripheral blood manifestations and are clinically characterized by reduced hematological triad. It is challenging to distinguish and diagnose these two diseases. Hence, utilizing machine learning methods, we employed and validated an algorithm that used cell population data (CPD) parameters to diagnose AA and MDS.MethodsIn this study, CPD parameters were obtained from the Beckman Coulter DxH800 analyzer for 160 individuals diagnosed with AA or MDS through a comprehensive retrospective analysis. The individuals were unselectively assigned to a training cohort (77%) and a testing cohort (23%). Additionally, an external validation cohort consisting of eighty-six elderly patients with AA and MDS from two additional centers was established. The discriminative parameters were carefully analyzed through univariate analysis, and the most predictive variables were selected using least absolute shrinkage and selection operator (LASSO) regression. Six machine learning algorithms were utilized to compare the performance of forecasting AA and MDS patients. The area under the curves (AUCs), calibration curves, decision curves analysis (DCA), and shapley additive explanations (SHAP) plots were employed to interpret and assess the model’s predictive accuracy, clinical utility, and stability.ResultsAfter the comparative evaluation of various models, the logistic regression model emerged as the most suitable machine learning model for predicting the probability of AA and MDS, which utilized five principal variables (age, MNVLY, SDVLY, MNLALSEGC, and MNCEGC) to accurately estimate the risk of these diseases. The best model delivered an AUC of 0.791 in the testing cohort and had a high specificity (0.850) and positive predictive value (0.818). Furthermore, the calibration curve indicated excellent agreement between actual and predicted probabilities. The DCA curve further supported the clinical utility of our model and offered significant clinical advantages in guiding treatment decisions. Moreover, the model’s performance was consistent in an external validation group, with an AUC of 0.719.ConclusionsWe developed a novel model that effectively distinguished elderly patients with AA and MDS, which had the potential to provide physicians assistance in early diagnosis and the proper treatment for the elderly.

Breast myopathy co-occurrence and its impact on carcass and meat quality attributes in broiler chickens

Wooden breast (WB), spaghetti meat (SM) and white striping (WS) are significant research focuses due to their impact on meat quality. This study examines the relationship between different myopathies in chickens from a commercial slaughterhouse and compares physicochemical traits between breasts with single and multiple myopathies and control (CO-no apparent myopathy). A total of 240 breasts were evaluated for myopathy presence, severity and location, and physicochemical parameters (i.e. carcass weight and color; breast color, pH, electrical conductivity, drip, thaw and cooking loss, Warner-Brazler texture, moisture, protein, fat and collagen content). A 54.8 % of the affected breasts presented multiple myopathies, and within them, a correlation between WB and WS was found (Kendall's tau = 0.24; P < 0.01). Additionally, myopathies were more prevalent in the breast cranial region (P < 0.05). Most physicochemical parameters varied significantly across myopathy classes. Breasts presenting WB, alone or in combination, were the most altered, showing: heavier carcasses with higher breast yield and redder and yellower skin; breasts with higher L*, b* and Hue, higher moisture, fat and collagen and lower protein content, and with higher cooking loss and lower resistance to shear (P < 0.05). SM, WS and their combination often had intermediate values between CO and WB breasts, with a few exceptions in carcass color and breast fat content. The principal component discriminant analysis revealed a proximity of CO to WS, SM, and their combinations, and a clear separation to WB and WB-SM. Breast yield, pH, cooking and thaw loss, and protein and fat content were the most discriminative parameters between categories. The partial least squares discriminant analysis could not differentiate between single, multiple myopathies and CO (accuracy = 42.6 %), but showed 80.63 % balanced accuracy for WB-SM, 74.26 % for SM and 74.61 % for CO. These findings confirm most previously reported data on meat quality, and provide a thorough analysis that can help industries to improve breast myopathies postmortem classification and identification.

Measuring Spatial Ability: Analysis of Spatial Ability Test for Gulf State Students Using Item Response Theory

This study evaluates the psychometric properties of the spatial ability test using the three-parameter logistic model within item response theory. The final version of the scale comprised 29 dichotomous items, administered to a sample of 2,694 male and female students from grades 5 and 6 across schools in the Arab Gulf region. The test adhered to the three-parameter model, satisfying the assumptions of unidimensionality and local independence. The item difficulty parameters ranged from -1.541 to 1.735, discrimination parameters spanned from 0.419 to 5.252, and guessing parameters varied between 0.00 and 0.346. With a marginal reliability coefficient of 0.86, the scale demonstrated strong stability. These findings indicate that the test items align with established measurement principles, supporting the spatial ability test as a valid and reliable assessment tool for measuring spatial abilities in the Gulf region. The results have important implications for educational assessment in the Arab Gulf and could guide the development of similar assessments in other educational contexts. Further research is recommended to improve the test’s precision and explore its application in diverse educational settings.

Quantitative assessment of pulmonary blood flow redistribution in the classification of group 1 and group 4 pulmonary hypertension.

All patients with pulmonary hypertension (PH), without left heart disease or lung diseases, need further distinguishing between pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH). This study aimed to investigate the value of quantitative assessment of pulmonary blood flow redistribution in further classification. Forty-six patients who underwent echocardiography and computed tomography pulmonary angiography at The First Affiliated Hospital of Xi'an Jiaotong University were included in this cross-sectional study, and all patients were categorized into a non-PH group (18 cases), a PAH group (12 cases), and a CTEPH group (16 cases). The diameter of the left ventricle and right ventricle were measured. The volumes of the main, right, and left pulmonary arteries were calculated. The total blood volume (TBV), the blood volume of vessels at the cross-section with an area <5 mm2 (BV5), between 5 and 10 mm2 (BV5-10), and >10 mm2 (BV10), and the blood volume of the pulmonary arteries and veins, were quantitatively assessed. TBV, BV5, BV5-10 and BV10 were all normalized to the volume of the corresponding lung or lobe. The diameter of the right ventricular, and the volumes of the main pulmonary artery, right pulmonary artery, and left pulmonary artery were not significantly different between the PAH and CTEPH group (P>0.05). The BV10 of CTEPH were significantly lower than those of the PAH group for the whole lung (32.69‰±13.53‰ vs. 18.73‰±6.10‰; t=6.234; P=0.004), right lung (29.06‰±15.01‰ vs. 9.99‰±4.26‰; t=10.819; P<0.001), left lung (32.41‰±15.83‰ vs. 18.32‰±6.43‰; t=4.322; P=0.020), right upper lobe (RUL) (22.26‰±12.07‰ vs. 7.90‰±2.92‰; t=8.991; P=0.001), right middle lobe (20.72‰±9.95‰ vs. 7.54‰±5.32‰; t=7.117; P=0.002), right lower lobe (RLL) (31.55‰±18.22‰ vs. 12.40‰±5.99‰; t=8.098; P=0.001), left upper lobe (28.23‰±14.82‰ vs. 14.95‰±5.24‰; t=5.630; P=0.007) and left lower lobe (31.04‰±14.85‰ vs. 20.04‰±8.58‰; t=2.477; P=0.096). The arterial TBV (42.18‰±13.67‰ vs. 27.76‰±7.96‰; t=6.544; P=0.003), arterial BV10 (18.19‰±7.29‰ vs. 9.36‰±3.83‰; t=7.758; P=0.001), venous TBV (35.58‰±16.35‰ vs. 25.01‰±4.79‰; t=3.727; P=0.033), and venous BV10 (14.50‰±7.09‰ vs. 9.36‰±2.76‰; t=3.676; P=0.034) were also significantly lower in the CTEPH group than those of the PAH group. Age [95% confidence interval (CI): 0.011 to 0.082; P=0.013] and BV10 of the RUL (95% CI: -0.102 to -0.004; P=0.034) were the most discriminative parameters, with an area under the curve of 0.950 in distinguishing PAH and CTEPH (P<0.05). Pulmonary vessel volume increased in PAH, particularly in larger-caliber vessels and the pulmonary artery, while it decreased in CTEPH, especially in larger-caliber vessels and the RLL.

"Clinical prediction model for masked hypertension diagnosed by 24-h ambulatory blood pressure measurements in a sample from specialized hospital."

The conventional assessment of the relationship between arterial hypertension (AH) and cardiovascular damage has predominantly relied on office measurements. However, the diagnostic significance of ambulatory and home measurements has gained prominence, particularly in identifying distinct AH phenotypes like masked hypertension (MH), characterized by normal office values but elevated readings outside the clinical setting, carrying comparable risks to sustained AH. Current guidelines advocate for Ambulatory Blood Pressure Monitoring (ABPM) in individuals with office values exceeding 130/85 mmHg. This study aims to develop a clinical prediction model to identify masked hypertension in individuals with normal office blood pressure and to create a clinical score.A cross-sectional study was conducted in a secondary level hospital, including patients aged 18-85 years with average office blood pressure <140/90 mmHg who underwent a valid ABPM on the same day. Pregnant and postpartum women were excluded. A multivariable logistic regression model with calibration, discrimination, and stability parameters was applied to predict masked hypertension. 506 individuals with valid ABPM were analysed. The prevalence of masked hypertension was 30.8%. The selected variables were: diastolic blood pressure, pulse pressure, waist diameter and sex. The model calibrated adequately (Hosmer-Lemeshow test p = 0.35), with an AUC of 0.72 (95% CI, 0.67-0.77). Significant differences existed between the traditional and the new models (p < 0.001). A user-friendly clinical model was developed, with a clinical score achieving 90% specificity using an estimated probability of 0.4 with a 10-point score.A novel model, performed with easily collectable clinical variables, showed robust calibration, stability, and discrimination. It outperforms sole reliance on office blood pressure, exhibiting high specificity (~90%) for masked hypertension detection. Its internal validity suggests a potential for enhanced masked hypertension identification.

Validation of the Rosenberg Self-Esteem Scale in Military Personnel of the Spanish Army (RSES-JGA).

Self-esteem is a psychological term that, since its emergence in 1890 with William James, has been widely studied. Furthermore, this construct has been examined in different areas of psychology, including the clinical field, where its relationship with mental health and low levels of depression has been demonstrated. In the realm of positive psychology, its connection to resilience and life satisfaction has also been established. Evaluating self-esteem in military personnel is essential, as healthy self-esteem can enhance resilience, improve performance, and promote emotional well-being. To evaluate validity based on internal structure from the perspective of Classical Test Theory (CTT) and Item Response Theory (IRT), to obtain evidence of validity based on the relationship with other variables, and to estimate the reliability of the Rosenberg Self-Esteem Scale (RSES). To this end, 584 military personnel from the three ranks of the Spanish Army (officers, non-commissioned officers, and professional soldiers and sailors) were evaluated, of which 511 were men (87.70%) and 72 were women (12.30%), with an age range of 18 to 66 years (M = 33.17, SD = 7.38). The results indicate that the unidimensional structure of the RSES shows adequate fit indices (CFI = 0.94, TLI = 0.91, SRMR = 0.05), while the difficulty and discrimination parameters exhibited favorable values. Additionally, an acceptable reliability value was found (ɷ = 0.81; α = 0.80). Therefore, it is concluded that the RSES-JGA presents adequate psychometric properties of validity and reliability, making it a useful and relevant instrument for measuring self-esteem in military personnel of the Spanish Army. This will make it possible to measure the level of self-esteem in military personnel, i.e., the set of perceptions, thoughts, evaluations, feelings, and behavioral tendencies directed towards oneself, one's own way of being, and towards one's own body and character traits.

On the local convergence of ADAM-DPGAN with simultaneous and alternating gradient decent training methods

Generative Adversarial Networks (GANs) do not ensure the privacy of the training datasets and may memorize sensitive details. To maintain privacy of data during inference, various privacy-preserving GAN mechanisms have been proposed. Despite the different approaches and their characteristics, advantages, and disadvantages, there is a lack of a systematic review on them. This paper first presents a comprehensive survey on privacy-preserving mechanisms and offers a taxonomy based on their characteristics. The survey reveals that many of these mechanisms modify the GAN learning algorithm to enhance privacy, highlighting the need for theoretical and empirical analysis of the impact of these modifications on GAN convergence. Among the surveyed methods, ADAM-DPGAN is a promising approach that ensures differential privacy in GANs for both the discriminator and the generator networks when using the ADAM optimizer, by introducing appropriate noise based on the global sensitivity of discriminator parameters. Therefore, this paper conducts a theoretical and empirical analysis of the convergence of ADAM-DPGAN. In the presented theoretical analysis, assuming that simultaneous/alternating gradient descent method with ADAM optimizer converges locally to a fixed point and its operator is L-Lipschitz with L < 1, the effect of ADAM-DPGAN-based noise disturbance on local convergence is investigated and an upper bound for the convergence rate is provided. The analysis highlights the significant impact of differential privacy parameters, the number of training iterations, the discriminator’s learning rate, and the ADAM hyper-parameters on the convergence rate. The theoretical analysis is further validated through empirical analysis. Both theoretical and empirical analyses reveal that a stronger privacy guarantee leads to a slower convergence, highlighting the trade-off between privacy and performance. The findings also indicate that there exists an optimal value for the number of training iterations regarding the privacy needs. The optimal settings for each parameter are calculated and outlined in the paper.

Age-related differences in psychometric properties of World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0): a retrospective analysis.

The aim of this study was to detect a possible age-related differential item functioning (DIF) of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) among people with musculoskeletal disorders. This was a cross-sectional study of 1739 consecutive patients with chronic musculoskeletal pain at a university clinic. Difficulty and discrimination parameters were calculated for each of 12 items of the WHODAS 2.0 using item response theory. The presence of DIF was assessed both numerically and graphically. When considering differences in both difficulty and discrimination, a statistically significant DIF was observed for all the items except for the item 'washing' (P values <0.001). The DIF was mostly uniform. Items 'standing', 'household responsibilities', 'learning a new task', 'emotional affectedness', 'concentrating', 'washing' and 'dressing' showed better precision among older patients. Items 'walking', 'dealing with strangers', 'maintaining a friendship' and 'day-to-day work' were more informative among younger patients. Difficulty and discrimination parameters were alike for all 12 items. The DIF was mostly uniform. These results can be taken into account when applying the WHODAS 2.0 to people with musculoskeletal complaints, especially when the studied groups are predominated by people of certain age.

Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis.

Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), incomparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs. In total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student's t-test or the Mann-Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves. Isotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p < 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897). Advanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment.

Psychometric Properties of the Saudi Version of the Mathematics Confidence Scale using the Modern Test Theory

The aim of the study was to analyze the psychometric properties of the Arabic version of the Math Confidence Rating Scale (MCS), using Item Response Theory (IRT) and Exploratory Factor Analysis (EFA). The participants were (315) from Imam Mouhammad Ibn Saud Islamic University; They are distributed into (92) female and (223) male, selected through a convenience sampling. The EFA models indicated that the one-dimensional structure better represents the data, and the pairs of items were considered locally independent, IRT findings indicate that all items had a very high discrimination parameter and all items had acceptable threshold parameters, And that MCS is more informative for mid-level ability of Math confidence. The MCS in Arabic has adequate psychometric properties to be used as a short measure of Math confidence.

Psychometric properties of Parenting Sense of Competence Scale using item-response theory

Parental competence is one of the essential components of raising ethical and healthy children. The mother's satisfaction with her maternal role significantly influences her cognitive responses and parenting behaviors. Having appropriate instruments to measure maternal satisfaction and identify and solve potential problems after childbirth can substantially contribute to maintaining and improving mother and infant health. This study aimed to evaluate the psychometric properties of the Parenting Sense of Competence (PSOC) Scale in mothers referring to the healthcare centers affiliated with Qazvin University of Medical Sciences. This cross-sectional psychometric study collected data from 254 mothers with 1.5-month-old infants referred to the healthcare centers in Qazvin Province. Data were analyzed using the item response theory (IRT) in SPSS 26 and Stata 17 software. The mean age (±standard deviation) of participants was 30.05 ± 5.7, and the overall Cronbach's alpha for the scale was 0.931. We used the graded response model (GRM) appropriate for Likert-type rating scales to fit the IRT. The discrimination parameter estimates showed that item 5 had a discrimination level <0.65, leading to its exclusion from the final analysis. In addition, the total information index confirmed that the scale was suitable in the trait range of −2.1 to 1.8. Compared with other common models for ordered responses based on general model fit indices, the GRM showed a better fit. The study results recommend applying the IRT models to improve and enhance the quality of questionnaires in various measurement fields.

Crafting an ultrashort workplace incivility scale and determining cutoffs for varied risk levels through item response theory

Workplace incivility (WI), characterized by disrespectful or rude behavior in the workplace, is linked to poor mental health and overall well-being. The Workplace Incivility Scale (WIS) is a popular 7-item measure for assessing WI. There is a current need for an ultrashort conceptually clear version of the WIS. In addition, the cutoffs for varied at-risks of WI, requiring intervention, remains unknown. Using data from 426 employees across diverse organizations, we employed item response theory (IRT) to create an ultrashort WIS and establish cutoffs for high, moderate, low, and at-not risk of WI. Confirmatory factor analyses were utilized to validate WIS construct validity. In supporting convergent validity, WIS was correlated with workplace bullying and poor health-related quality of life. All items demonstrated adequate severity threshold parameters with very high discrimination and good reliability parameters except for item WIS7. We successfully developed an ultrashort and valid 3-item WIS, specifically comprising items WIS2–4, and identified cutoffs for varying levels of WI risk. This streamlined measure aims to reduce response burden and foster a healthier organizational culture. In essence, cutoff points streamline the classification process, allowing for quicker and more standardized identification of at-risk employees. This concise, valid, and reliable ultrashort WIS holds potential for use in intervention studies conducted by organizational and occupational health psychologists, ultimately promoting employee well-being and cultivating a positive workplace environment. The current study further advances the existing theoretical framework rooted in the social interactionist perspective by delineating WI as a distinct and independent construct.

An Item Response Theory Analysis of the Psychosis Screening Questionnaire in Ethiopia.

Few psychosis screening instruments have been tested for use in Africa, yet appropriate tools can increase the detection of self-reported psychotic symptoms, improve the detection of psychosis and impact its prognosis. The construct validity and factor structure of Psychosis Screening Questionnaire (PSQ) were tested with confirmatory factor analysis (CFA) and item response theory (IRT) in a sample of 1928 Ethiopian adults without any history of psychosis. We tested a unidimensional model with and without an item on mania. For IRT, unidimensional latent structure one-parameter logistic (1PL) and two-parameter (2PL) logistic models were tested and compared for relative fit using a likelihood-ratio test. The prevalence of lifetime positive screens was 2.8% in an Ethiopian sample of adults from a general medical setting. A unidimensional model demonstrated good fit for the PSQ, (CFI = 0.993, TLI = 0.986 and RMSEA = 0.025). For IRT, a 2PL model was the best fitting one. IRT tests of item difficulty and discrimination parameters showed that paranoia had the highest discrimination and lowest difficulty ( ), likely to be endorsed at low levels of psychotic features. Thought insertion had the highest item difficulty ( ). Overall, the measure captures the psychosis construct at higher levels of the latent trait and may be suited for detecting moderate to severe levels of psychosis. The PSQ is found to have good construct validity in screening for psychosis among Ethiopian adults. Future studies may focus on the diagnostic validity of the PSQ comparing it with a structured clinical interview.

Evaluating the psychometric properties of ChatGPT-generated questions

Not much is known about how LLM-generated questions compare to gold-standard, traditional formative assessments concerning their difficulty and discrimination parameters, which are valued properties in the psychometric measurement field. We follow a rigorous measurement methodology to compare a set of ChatGPT-generated questions, produced from one lesson summary in a textbook, to existing questions from a published Creative Commons textbook. To do this, we collected and analyzed responses from 207 test respondents who answered questions from both item pools and used a linking methodology to compare IRT properties between the two pools. We find that neither the difficulty nor discrimination parameters of the 15 items in each pool differ statistically significantly, with some evidence that the ChatGPT items were marginally better at differentiating different respondent abilities. The response time also does not differ significantly between the two sources of items. The ChatGPT-generated items showed evidence of unidimensionality and did not affect the unidimensionality of the original set of items when tested together. Finally, through a fine-grained learning objective labeling analysis, we found greater similarity in the learning objective distribution of ChatGPT-generated items and the items from the target OpenStax lesson (0.9666) than between ChatGPT-generated items and adjacent OpenStax lessons (0.6859 for the previous lesson and 0.6153 for the subsequent lesson). These results corroborate our conclusion that generative AI can produce algebra items of similar quality to existing textbook questions that share the same construct or constructs as those questions.

Measurement of bullying in the Progress in International Reading Literacy Study 2021 cohort: Evidence for model misspecification

We evaluated the use of the Rasch model in the scoring and scaling of the context questionnaire scales from the Progress in International Reading Literacy Study 2021 cohort. Focusing on the bullying scale of the Progress in International Reading Literacy Study, we contrasted polytomous item response theory models using free (two-parameter logistic modeling) and fixed (Rasch modeling) discrimination parameters. Our analyses included data from 354,074 students from 63 countries or entities. Across all countries and entities, the Rasch-based model significantly distorted levels of bullying. The rank ordering of countries was consistent between models in 32 of the cases (50.8%), while in other cases there were changes in rank of up to five places. This study provides a robust basis for evidence-based decisions on whether a country is lagging or exceeding the global norm in aberrant behaviors such as bullying.

Revisiting the English Short Measure for Adult Playfulness (SMAP): An Investigation of Reliability, Validity, and Cross-Cultural Comparisons

Adult playfulness describes the personality of the quick initiation and strong intensity of enjoyable experiences coupled with the frequency of engaging in playful behaviors. In addition to examining the reliability and validity of the Short Measure for Adult Playfulness (SMAP), we compared the psychometric properties of the SMAP across (a) 4- and 7-point answer formats; (b) German and English language versions; and (c) gender. The SMAP and criterion validity measures were distributed across three independent samples from Canada (N total = 1,177) and a German sample (N = 660). Results supported a unidimensional solution with strong factor loadings for all items (>.50 across all samples) and high test-retest reliability (r = .67, BF10>100). In item response theory analyses, high discrimination parameters were found across the latent continuum. Although both the four-point and seven-point Likert scale versions showed robust item properties, the seven-point Likert scale version yielded more precise measurement of higher playfulness (θ > 1.50). No significant differential item functioning was located across gender or language. Finally, results supported external construct validity via associations with broad personality traits, humor, and orientations to happiness. The present investigation provides support for the reliability and validity of the English SMAP for concise adult playfulness measurement.

Cross-cultural validation of the Jenkins Sleep Scale in Spanish-speaking countries.

The study aimed to validate the Jenkins Sleep Scale (JSS-4) in six Spanish-Speaking countries. A total of 1726 people participated and were distributed between men (32.4%) and women (67.6%). Confirmatory factor analysis confirmed the unidimensional structure and high reliability of the JSS-4 overall (α = 0.85, ω = 0.81) and within each country. The invariance analysis revealed that JSS-4 exhibited complete invariance across countries, thus establishing a robust foundation for inter-group comparisons. Interestingly, a comparative analysis revealed significant differences in the average levels of sleep difficulties, with particularly high rates in Spain and Chile. Item Response Theory (IRT) showed sufficient discrimination parameters for all items, and a correlation of 0.998 between Confirmatory Factor Analysis (CFA) and IRT highlighted the robustness and reliability of the results obtained. In summary, JSS-4 exhibits strong evidence of validity and consistency in measurement invariance across the six countries.

Using item response theory to identify key symptoms of insomnia in a sample of university students with probable eating disorders

PurposeResearchers have theorized that interactions between appetitive and circadian disruptions result in increased eating disorder (ED) symptoms and insomnia. However, it is unclear how specific insomnia symptoms present among people with EDs and if the latent structure of insomnia in this population is similar to that of people with insomnia disorder.MethodsWe conducted a secondary analysis of data collected on ED and insomnia symptoms using a subset of students (N = 547; 79.52% female) with probable EDs at a large Midwestern American university. Item response theory (IRT) for polytomous items was performed to identify item difficulty, discrimination, and information parameters for the Insomnia Severity Index (ISI). IRT parameters were compared to those established in a 2011 study of people diagnosed with insomnia disorder by Morin and colleagues.ResultsClinically significant insomnia symptoms were common among students with ED pathology and symptom endorsement for each ISI item ranged from 40.77 to 86.65%. ISI items assessing insomnia-related impairment and distress showed better discriminative capacities and had higher item information than items assessing sleep behavior alterations (i.e., difficulties falling asleep, difficulties maintaining sleep, waking too early). Item discrimination was largely similar among the ED sample compared to previous IRT analyses in an insomnia disorder sample.ConclusionInsomnia symptoms are common among university students with probable EDs and similar to those reported by people with insomnia disorder. When considering insomnia assessment, items assessing sleep behaviors alone are likely inadequate to provide information about insomnia severity among people with EDs.Level VEvidence obtained from a cross-sectional descriptive study.

Development of Four-Item Attitudes toward People Living with Dementia Scale for population surveys.

This study developed a short version of a scale measuring attitudes toward people living with dementia, the Four-Item Attitudes toward People Living with Dementia Scale (APDS4), that could be included in a large population survey. We used three datasets from Japan: a web panel survey, a community-based mail survey, and data from a randomised controlled trial on dementia education. The original scale used was the Attitudes toward People Living with Dementia Scale developed by Kim and Kuroda. Test-retest reliability and item response theory analyses were used to reduce the number of items. The reliability, internal consistency, validity, and responsiveness of the short version were evaluated. Six items with low test-retest reliability and four items with low discrimination parameters were removed from the 14-item scale. The APDS4, consisting of four items, had test-retest reliability and internal consistency comparable to those of the original scale. Confirmatory factor analysis indicated that the APDS4 fit a unidimensional model. The validity of the APDS4 was confirmed by significant associations between the APDS4 scores and the original scale scores, knowledge of dementia, helping behaviour intentions toward people living with dementia, helping behaviour experience, attending the Dementia Supporter Training Course, and engagement in healthcare jobs. In a randomised controlled trial dataset, the APDS4 was more responsive to educational interventions than the original scale. The shortened APDS4 was established as a reliable, validated, and responsive scale. This scale can be used efficiently in population surveys to evaluate dementia-friendly initiatives at the community level.

Methods for measuring career readiness of high school students: based on multidimensional item response theory and text mining

In contemporary society, career readiness holds paramount significance for individual life, exerting a direct influence on initial employment, job satisfaction, and the sense of career identity. Framed within multidimensional item response theory and text mining, this study embarks on exploring assessment methodologies for high school students’ career readiness by revising the “Career Readiness Questionnaire – Adolescent Version” and employing text mining techniques. Study One collected 1261 valid data points through cluster sampling. With the aid of Bayesian multivariate item response theory parameter estimation procedures and R language, the career readiness measurement tool was revised, yielding a concise scale that aligns with psychometric requirements. The research findings indicated that the concept of “career readiness” is more suitable for the multidimensional graded response model than for the bifactor model. The dataset’s discrimination parameters fell within the range of [1.59, 3.84], the difficulty parameters fell between [−2.91, 2.24], and the peak values of the maximum information functions fell within [0.24, 2.35]. After six items with the lowest peaks were removed (Items 4, 5, 6, 31, 32, and 33), the remaining 30 items composed the Chinese concise version “Career Readiness Questionnaire – Adolescent Version,” with discrimination parameters ranging from [1.45, 3.38], difficulty parameters between [−3.31, 1.76], and maximum information function peaks within [0.50, 2.64]. Building upon the effective participants from Study One, Study Two matched questionnaire data with textual information, resulting in 1012 valid participants. Leveraging text mining, a machine learning model was constructed to predict high school students’ career readiness based on essay texts. The results of Study 2 prove that the revised lexicon was more accurate in feature extraction. Building upon this, the machine learning model for essay text demonstrated excellent performance in predicting career readiness, with random forest outperforming the other algorithms. This study provides a novel approach for schools and parents to comprehend the state of career readiness among high school students, offering a convenient and effective tool for educational activities related to students’ career development.