UNASSIGNED: The present study aimed to further examine the factor structure and measurement invariance of the UDRQ among a sample of Hungarian university students.
UNASSIGNED: Firstly, the factor structure of the UDRQ was examined among 837 Hungarian university students. Specifically, two measurement models (first-order model and second-order model) were constructed and compared. Secondly, the internal consistency reliability of the UDRQ was examined. Thirdly, measurement invariance of the UDRQ was evaluated across genders. Finally, measurement invariance of the UDRQ was evaluated across two different samples.
UNASSIGNED: It was found that the first-order model outperformed the second-order model and better represented the factor structure of the UDRQ subscales. Results of Cronbach\'s alpha and Composite Reliability suggested that the internal consistency reliabilities of the two UDRQ subscales were satisfactory. Measurement invariance analysis revealed that the UDRQ measurement model was strict invariant across genders and samples.
UNASSIGNED: The findings of the present study indicated that the UDRQ displayed satisfactory reliability and validity and could be used to assess demands and resources of Hungarian university students.

Both the Psychopathy Checklist-Revised (PCL-R) and the Psychopathy Checklist: Youth Version (PCL:YV), respectively, are established instruments for assessment of psychopathy and development of psychopathic propensity. To reliably compare scores from both instruments, measurement invariance must be established. The current study involved a combined sample of 1091 male participants (adults = 813; adolescents = 278) from correctional facilities in New Mexico. An exploratory structural equation modeling (ESEM) framework was used to test for measurement invariance. The four-factor ESEM model demonstrated good fit for the combined and individual samples. Results from the multiple group ESEM provide evidence for generally strong invariance, with equivalent factor loadings and thresholds. Adolescents exhibited decreased latent interpersonal traits but increased latent features on other PCL factors (affective, lifestyle, and antisocial) compared to adults. Findings suggest that the four-factor model and the measurement of psychopathic traits remain consistent across age groups. Implications of the findings within research and clinical contexts are discussed.

Psychometricians have argued that measurement invariance (MI) testing is needed to know if the same psychological constructs are measured in different groups. Data from five experiments allowed that position to be tested. In the first, participants answered questionnaires on belief in free will and either the meaning of life or the meaning of a nonsense concept called \"gavagai.\" Since the meaning of life and the meaning of gavagai conceptually differ, MI should have been violated when groups were treated like their measurements were identical. MI was severely violated, indicating the questionnaires were interpreted differently. In the second and third experiments, participants were randomized to watch treatment videos explaining figural matrices rules or task-irrelevant control videos. Participants then took intelligence and figural matrices tests. The intervention worked and the experimental group had an additional influence on figural matrix performance in the form of knowing matrix rules, so their performance on the matrices tests violated MI and was anomalously high for their intelligence levels. In both experiments, MI was severely violated. In the fourth and fifth experiments, individuals were exposed to growth mindset interventions that a twin study revealed changed the amount of genetic variance in the target mindset measure without affecting other variables. When comparing treatment and control groups, MI was attainable before but not after treatment. Moreover, the control group showed longitudinal invariance, but the same was untrue for the treatment group. MI testing is likely able to show if the same things are measured in different groups.

UNASSIGNED: Chronic back pain is a frequent and disabling health problem. There is evidence that ignorance and erroneous beliefs about chronic low back pain among health professionals interfere in the treatment of people who suffer from it. The Health Care Providers\' Pain and Impairment Relationship Scale (HC-PAIRS) has been one of the most used scale to assess these misbeliefs, but no studies have been reported in Latin America. Method: We studied the factorial structure of the HC-PAIRS in health personnel and health sciences university students in two Latin American countries: Colombia (n = 930) and Chile (n = 190). Spain\'s data was taken of the original study of the Spanish version of the HC-PAIRS (171 Physiotherapy students). Additionally, the measurement invariance of this scale among Chile, Colombia and Spain was evaluated by calculating three nested models: configural, metric and scalar. We used a Confirmatory Factor Analysis (CFA) in both Latin American samples, with Maximum Likelihood Robust (MLR) estimation to estimate the parameters. For the final model in each sample, reliability was assessed with the Composite Reliability (CR) index, and to obtain the proportion of variance explained by the scale the Average Variance Extracted (AVE) was calculated.
UNASSIGNED: The one-factor solution shows an acceptable fit in both countries after deleting items 1, 6, and 14. For the resulting scale, the CR value is adequate, but the AVE is low. There is scalar invariance between Chile and Colombia, but not between these two countries and Spain.
UNASSIGNED: HC-PAIRS is useful for detecting misconceptions about the relationship between chronic low back pain that would cause health personnel to give wrong recommendations to patients. However, it has psychometric weaknesses, and it is advisable to obtain other evidence of validity.

The current study presents the development process and initial validation of the Engagement in Athletic Training Scale (EATS), which was designed to evaluate athletes\' engagement in athletic training. In study 1, item generation and initial content validity of the EATS were achieved. In study 2, the factor structure of the EATS was examined using exploratory factor analysis (EFA) and exploratory structural equation modeling (ESEM). Internal consistency reliabilities of the subscales were examined (N = 460). In study 3, factor structure, discriminant validity, internal consistency reliability, and nomological validity of the EATS were further examined in an independent sample (N = 513). Meanwhile, measurement invariance of the EATS across samples (study 2 and study 3) and genders was evaluated. Overall, results from the 3 rigorous studies provided initial psychometric evidence for the 19-item EATS and suggested that the EATS could be used as a valid and reliable measure to evaluate athletes\' engagement in athletic training.

(1) Background: Parents of children with autism spectrum disorders often experience psychological distress, which can affect the quality of childcare they provide. It is crucial to screen for psychiatric symptoms among these parents. The core symptom index (CSI) is a widely recognized tool used to assess general symptoms, including depression, anxiety, and somatic issues. It has proven validity and reliability across diverse Thai populations. Given the cultural similarities between Thai and Chinese populations, the CSI has been successfully implemented within the Chinese population. Nevertheless, it is crucial to research its validity and reliability in the general Chinese population. This study aimed to investigate the psychometric properties of the Chinese version of the CSI among parents of children with autism spectrum disorders using confirmatory factor analysis (CFA). (2) Methods: A total of 794 Chinese parents raising children with autism participated in this study. All completed the CSI, along with the social inhibition subscale of the Interpersonal Problems Inventory and the Couple Satisfaction Index. Factorial validity was assessed using CFA to determine how well the bifactor three-factor model fits the data. Various structural models were compared using model fit indices. Convergent and discriminant validity were examined by exploring correlations with the social inhibition subscale and the Couple Satisfaction Index. Invariance testing of the CSI was conducted across multiple groups based on gender, age, and education using CFA. The reliability of the CSI was evaluated using McDonald\'s omega coefficients. (3) Results: The bifactor model emerged as the best-fitting model for the data, suggesting that the total score of the CSI adequately represents overall psychiatric symptoms. The CSI exhibited significant correlations with the social inhibition subscale (r = 0.41, p < 0.01) and smaller correlation coefficients with the Couple Satisfaction Index (r = -0.16, p < 0.05), indicating both convergent and discriminant validity. The invariant test results support scalar invariance levels based on gender and age but only partial invariance for education. The Chinese version of the CSI demonstrated high consistency, with McDonald\'s omega coefficients ranging between 0.86 and 0.95. (4) Conclusions: The bifactor model of the Chinese version of the CSI is validated, making it a suitable tool for measuring depression, anxiety, and somatization symptoms among parent(s) of children with autism spectrum disorders. Further research on other Chinese populations is encouraged.

Fit indices are descriptive measures that can help evaluate how well a confirmatory factor analysis (CFA) model fits a researcher\'s data. In multigroup models, before between-group comparisons are made, fit indices may be used to evaluate measurement invariance by assessing the degree to which multiple groups\' data are consistent with increasingly constrained nested models. One such fit index is an adaptation of the root mean square error of approximation (RMSEA) called RMSEAD. This index embeds the chi-square and degree-of-freedom differences into a modified RMSEA formula. The present study comprehensively compared RMSEAD to ΔRMSEA, the difference between two RMSEA values associated with a comparison of nested models. The comparison consisted of both derivations as well as a population analysis using one-factor CFA models with features common to those found in practical research. The findings demonstrated that for the same model, RMSEAD will always have increased sensitivity relative to ΔRMSEA with an increasing number of indicator variables. The study also indicated that RMSEAD had increased ability to detect noninvariance relative to ΔRMSEA in one-factor models. For these reasons, when evaluating measurement invariance, RMSEAD is recommended instead of ΔRMSEA.

BACKGROUND: Given the rapid proliferation and use of online health resources, many of which may be of dubious quality, there is an increasing need to develop electronic health literacy (e-health literacy) skills among the population of internet users. E-health literacy encompasses the skills and abilities needed to access, understand, validate, evaluate, interpret, and apply online health-related information. Measuring e-health literacy has become crucial for developing targeted interventions, assessing their impact, and producing high-quality research findings that can inform health policy and clinical practice, which can lead to improved health outcomes and potentially reducing health inequalities. The scales need to be valid and reliable so that decisions are based on high-quality data. In this regard, the issue of the measurement invariance of scales across different demographic groups has been neglected. This is critical, as assessments should be valid across different sociodemographic groups to avoid bias when comparing them. The aim of this study was to validate the Extended e-health literacy scale (eHEALS-E) on general population and investigate its structural validity and internal consistency, construct validity in terms of convergent and discriminant validity, and examine its measurement invariance across gender, age, education and social status.
METHODS: The data were collected as a part of a national health literacy survey conducted by the Slovenian National Institute of Public Health. For this survey the initial eHEALS-E scale was revised in order to address its limitations and applicability to general population. Based on a nationally representative sample, the final sample for the analysis comprised 1,944 individuals who at least occasionally used one of the various internet services to obtain health-related information. Multiple group confirmatory factor analysis was used to examine the measurement invariance of the scale.
RESULTS: With some adjustments, the measurement model of the revised 6-dimensional eHEALS-E scale demonstrated a good fit to the data (χ2 = 2508, df = 282, RMSEA = 0.064, SRMR = 0.070, CFI = 0.90). The scale had good internal consistency (alpha = 0.89). Although evidence of the scale\'s convergent and discriminant validity was partially provided, the analysis revealed robust measurement invariance across sociodemographic groups.
CONCLUSIONS: With a minor limitation, the scale ensures an unbiased e-health literacy assessment across different social groups, which is crucial for interventions that aim to reduce health-related social inequalities. This ensures that the interventions derived from the assessment of reality are equally valid and effective for everyone, regardless of their sociodemographic background.

BACKGROUND: The Sleep Condition Indicator (SCI), an insomnia measurement tool based on the updated Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria with sound psychometric properties when applied in various populations, was evaluated here among healthcare students longitudinally, to demonstrate its measurement properties and invariance in this particularly high-risk population.
METHODS: Healthcare students of a Chinese university were recruited into this two-wave longitudinal study, completing the simplified Chinese version of the SCI (SCI-SC), Chinese Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration (RU_SATED-C) scale, Chinese Patient Health Questionnaire-4 (PHQ-4-C), and sociodemographic variables questionnaire (Q-SV) between September and November 2022. Structural validity, measurement invariance (MI), convergent and discriminant validity, internal consistency, and test-retest reliability of the SCI-SC were examined. Subgroups of gender, age, home location, part-time job, physical exercise, and stress-coping strategy were surveyed twice to test cross-sectional and longitudinal MI.
RESULTS: We identified 343 valid responses (62.9% female, mean age = 19.650 ± 1.414 years) with a time interval of seven days. The two-factor structure was considered satisfactory (comparative fit index = 0.953-0.989, Tucker-Lewis index = 0.931-0.984, root means square error of approximation = 0.040-0.092, standardized root mean square residual = 0.039-0.054), which mostly endorsed strict invariance except for part-time job subgroups, hence establishing longitudinal invariance. The SCI-SC presented acceptable convergent validity with the RU_SATED-C scale (r ≥ 0.500), discriminant validity with the PHQ-4-C (0.300 ≤ r < 0.500), internal consistency (Cronbach\'s alpha = 0.811-0.835, McDonald\'s omega = 0.805-0.832), and test-retest reliability (intraclass correlation coefficient = 0.829).
CONCLUSIONS: The SCI-SC is an appropriate screening instrument available for assessing insomnia symptoms among healthcare students, and the promising measurement properties provide additional evidence about validity and reliability for detecting insomnia in healthcare students.

BACKGROUND: Given the recent evidence on gender differences in the presentation of autism, there is an increasing concern that current tools for autism do not adequately capture traits more often found in women. If tools for autism measure autistic traits differently based on gender alone, their validity may be compromised as they may not be measuring the same construct across genders. Measurement invariance investigations of autism measures can help assess the validity of autism constructs for different genders. The aim of this systematic review is to identify and critically appraise the psychometric properties of all self-report tools for autism in adults that meet two criteria: (a) they have been published since or included in the NICE (2014) recommendations, and (b) they have undergone gender-related measurement invariance investigations as part of their validation process.
METHODS: A search of electronic databases will be conducted from 2014 until the present using MEDLINE, Embase, and PsycINFO using predefined search terms to identify eligible studies. The search for grey literature will include sources such as OpenGrey, APA PsycEXTRA, and Scopus. Two reviewers will independently screen titles, abstracts, and full texts for eligibility. The references of included studies will be searched for additional records. The methodological quality of the studies will be evaluated using the COSMIN Risk of Bias checklist, while psychometric quality of findings will be assessed based on criteria for good measurement properties and ConPsy checklist. The quality of the total body of evidence will be appraised using the approach outlined in the modified GRADE guidelines.
CONCLUSIONS: This systematic review will be among the first to assess the psychometric properties and gender-related measurement invariance of self-reported measures for autism in adults that were published since (or included in) NICE (2014) guidelines. The review will provide recommendations for the most suitable tool to assess for autism without gender bias. If no such measure is found, it will identify existing tools with promising psychometric properties that require further testing, or suggest developing a new measure.
BACKGROUND: The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO). The registration number is CRD42023429350.