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Insomnia is associated with adverse outcomes in women in the perinatal period; thus, the assessment of insomnia is important for pregnant women. The Insomnia Severity Index (ISI) is an instrument used globally to assess the severity of insomnia. However, its factor structure and structural invariance for pregnant women have not been studied. Therefore, we aimed to conduct factor analyses to search for the best model to fit its structural invariance. A cross-sectional study with the ISI was conducted at one hospital and five clinics in Japan from January 2017 to May 2019. A set of questionnaires was administered on two occasions with a one-week interval. The study included 382 pregnant women ranging in gestational age from 10 to 13 weeks. One week later, 129 participants answered the retest. After exploratory and confirmatory factor analyses, the measurement and structural invariance between parity and two time points was tested. The two-factor structure model showed an acceptable fit for the ISI in pregnant women (χ2 (12) = 28.516, CFI = 0.971, RMSEA = 0.089). The model also showed satisfactory measurement and structure invariance between parity and time points. The findings indicate that the ISI’s use would be appropriate for pregnant women as a two-factor subscale of “severity” and “impact”, regardless of the parity or time point. The ISI’s factor structure may vary by subject; hence, it is necessary to confirm the measurement and structural invariance of the subject for whom the ISI will be used. Furthermore, interventions that focus not only on total scores and cutoff points but also on the phenomenon of subscales should be considered.

Background: Many pregnant women experience impairments in social, occupational, or other important functioning. Aim: This study aimed to confirm measurement and structural invariance of the Sheehan Disability Scale (SDS) and its validity during early pregnancy. Design: Longitudinal study with two observations. Methods: Questionnaires were distributed to pregnant women attending antenatal clinics at gestational weeks 10–13. Of 382 respondents, 129 responded to the SDS again 1 week later. Results: Confirmatory factor analysis shows good fit with the data: χ2/df = 0, comparative fit index (CFI) = 1.000, standardized root mean square residual (SRMR) = 0, and root mean square error of approximation (RMSEA) = 0.718. There is acceptable configural, measurement, and structural invariance of the factor structure between primiparas and multiparas as well as between two observation occasions. The Pregnancy–Unique Quantification of Emesis and Nausea, Patient Health Questionnaire-9, and Insomnia Severity Index subscales explain 47% of the variance in SDS scores. Conclusion: Perinatal health care professionals should pay more attention to the difficulties and disabilities that pregnant women face.

Background: Stigma towards COVID-19 may negatively impact people who suffer from it and those supporting and treating them. Objective: To develop and validate a scale to assess 11-item COVID-19–related stigma. Methods: A total of 696 pregnant women at a gestational age of 12 to 15 weeks were surveyed using an online survey with a newly developed scale for COVID-19 stigma and other variables. The internal consistency of the scale was calculated using omega indices. We also examined the measurement invariance of the scale. Results: Exploratory factor analyses (EFAs) of the scale items were conducted using a halved sample (n = 350). Confirmatory factor analyses (CFAs) among the other halved sample (n = 346) compared the single-, two-, three-, and four-factor structure models derived from the EFAs. The best model included the following three-factor structure (χ2/df = 2.718, CFI = 0.960, RMSEA = 0.071): Omnidirectional Avoidance, Attributional Avoidance, and Hostility. Its internal consistency was excellent (all omega indices > 0.70). The three-factor structure model showed configuration, measurement, and structural invariances between primiparas and multiparas, and between younger (less than 32 years) and older women (32 years or older). Fear of childbirth, mother–fetal bonding, obsessive compulsive symptoms, depression, adult attachment self-model, and borderline personality traits were not significantly correlated with the Omnidirectional Avoidance subscale but correlated with the Attributional Avoidance and Hostility subscales (p < 0.001). Conclusion: The findings suggested that our scale for COVID-19 stigma was robust in its factor structure, as well as in construct validity.

PurposeThis study responded to the call to empirically reconcile conflicting findings in unethical pro-organizational behavior (UPB) literature. It did so by examining the influence of organizational culture on the relationship between affective organizational commitment and UPB.Design/methodology/approachUsing a sample of 710 U.S. service sector employees based on a three-wave data collection design, structural invariance assessment was utilized to evaluate the relationship between affective organizational commitment and UPB across organizational cultures with opposing effectiveness criteria (i.e. focused on stability vs flexibility).FindingsThe result indicated a statistically significant positive direct effect between affective organizational commitment and UPB for the stability-focused cultures, while finding a statistically insignificant effect for the flexibility-focused cultures. These results support organizational culture research, which shows that organizational cultures with opposing effectiveness criteria (i.e. stability vs flexibility) can either encourage or discourage ethical behavior.Practical implicationsWhile leaders and managers encourage employee commitment to the organization, it is important to understand that increased organizational commitment is not limited to positive outcomes. Cultivating elements of flexibility-oriented cultures, like promoting teamwork (as in clan cultures) or fostering innovation and adaptability (as in adhocracy cultures), can be a strategic approach to minimize the chances of UPB among committed employees.Originality/valueBy integrating insights from social exchange theory, Trevino’s interactionist model and the competing values framework, we have contributed to a nuanced understanding of how different organizational cultures can suppress or stimulate UPB.

Stress represents a significant risk factor for several psychophysical diseases among college students, such as depression and anxiety, which may undermine their academic functioning, resulting in high drop rates from college. Nevertheless, university services for mental health promotion are typically underutilized. As a result, professionals and authorities strive to find new ways to address students' mental health needs. In this view, mobile apps seem appropriate for well-being promotion interventions. Drawing on the Technology Acceptance Model (TAM), which is the most widely used theory on users' intention to use technologies, we assumed that perceived usefulness (PU) and perceived ease of use (PEOU) would be positively related to intention to use (INT), and PEOU would be positively related to PU among both Italian and German university students. To test our hypotheses, we replicated the same cross-sectional study in Italy ( n  = 255) and Germany ( n  = 228) with university students. Although we found partial scalar invariance of the TAM dimensions across the two nations, our predictions were only partially confirmed: PEOU was positively related to PU in the Italian sample only. Overall, this study is one of the first empirical attempts to compare TAM cross-nationally within the European context and it contributes to the small but increasing body of research investigating students’ acceptance of smartphone-based interventions for stress management and well-being promotion. Understanding mobile health acceptance could help universities increase students’ chances of adopting the proposed services, considering the factors influencing this choice.

OrientationStudent burnout has become increasingly evident among university students. However, to measure student burnout accurately in the South African context, it is essential to use validated, fair and unbiased instruments.Research purposeThis study investigates the psychometric properties of the Maslach Burnout Inventory Student Survey (MBI-SS) in a sample of university students, focussing on factorial validity, measurement invariance, item bias and internal consistency.Motivation for the studyInternational guidelines on psychometric assessments emphasise the importance of validation to ensure reliable, valid and unbiased measurement across diverse groups.Research approach/design and methodA quantitative cross-sectional research design was used to validate the psychometric properties of the MBI-SS in a sample of university students (N = 2434) across three campuses of a South African university.Main findingsThe findings support the MBI-SS’s three-factor structure and show measurement invariance across participating language and campus groups. While some items exhibited bias, the effects were negligible. The MBI-SS showed high internal consistency, demonstrating its reliability.Practical/managerial implicationsThese findings support the reliable, valid and unbiased application of the MBI-SS among South African university students. Universities can use this instrument to measure student burnout, identify causal factors and enhance student well-being and academic success.Contribution/value-addThis study contributes to the limited literature on the psychometric properties of the MBI-SS among university students in South Africa and could enable comparative analysis across different contexts within the country.

PurposeThe purpose of this paper is to validate the conceptual model that presents the determinants of Tier 2 consumer’s online shopping attitude and the interrelationships among the constructs across the three Tier 2 cities in India.Design/methodology/approachThe paper uses survey-based data from three Tier 2 cities of North India – Kota, Agra and Jalandhar and uses a combination of statistical techniques to assess psychometric properties of the scales and conduct the measurement and structural invariance.FindingsThe findings of the paper reveals that technology readiness, consumer innovativeness, fondness for branded products and perceived brand unavailability act as determinants of online shopping attitude and there is a positive relationship between online shopping attitude and online purchase intention among Tier 2 consumers in India while perceived offline hedonic value do not have any significant impact.Research limitations/implicationsFuture researchers can use this model with additional confidence given its cross-segment robustness.Practical implicationsOnline marketers can use the antecedents identified in this study to develop and encourage positive online shopping attitude in small town India.Originality/valueThis research paper is the first one that investigated online shopping attitudes of Indian Tier 2 consumers. Importantly, it validated the determinants of online shopping attitude among Tier 2 consumers. National and international e-tailers aiming to develop and expand their operations to India now have the critical empirical verification concerned with the determinants of online shopping attitude and behaviour in India which would be meaningful to develop a sound marketing strategy.

Economic complexity highlights the relationship between interdependence (a positional characteristic of elements belonging to a given network or structure) and connectivity (a functional characteristic of elements belonging to a given field of interaction). Positional interdependence (as the one between pieces in a jigsaw puzzle) is central to studies investigating the architecture of a complex system (Simon) while connectivity is central to the analysis of responsiveness patterns in social networks and strategic action fields. This paper discusses the fundamentals of a structural approach to economic and spatial complexity by highlighting the hierarchical arrangement of network elements as a distinctive feature of system identity. The positional distribution of network elements is a fundamental characteristic of complex networks and a central condition constraining the dynamics of those networks through the principle of relative structural invariance. The paper investigates the role of this principle by connecting it with the aggregation criterion followed in assigning network elements to specific subsystems. The type of aggregation is essential in determining the resilience properties of the network with respect to specific dynamic impulses. The paper concludes highlighting the need to combine the investigation of positional interdependence with the analysis of connectivity since positional interdependence is fundamental in determining which patterns of connection are more likely to arise (and which ones are excluded), due to the role of alternative properties of relative invariance constraining the feasible transformations in the positions of network elements.

This study presents a comprehensive evaluation of the quick invariant signature (QIS), dynamic time warping (DTW), and a novel hybrid QIS + DTW approach for time series analysis. QIS, a translation and rotation invariant shape descriptor, and DTW, a widely used alignment technique, were tested individually and in combination across various datasets, including ECG5000, seismic data, and synthetic signals. Our hybrid method was designed to embed the structural representation of the QIS with the temporal alignment capabilities of DTW. This hybrid method achieved a performance of up to 93% classification accuracy on ECG5000, outperforming DTW alone (86%) and a standard MLP classifier in noisy or low-data conditions. These findings confirm that integrating structural invariance (QIS) with temporal alignment (DTW) yields superior robustness to noise and time compression artifacts. We recommend adopting hybrid QIS + DTW, particularly for applications in biomedical signal monitoring and earthquake detection, where real-time analysis and minimal labeled data are critical. The proposed hybrid approach does not require extensive training, making it suitable for resource-constrained scenarios.

There are many measures of student perceptions of school climate; accordingly, there is a staggering amount of research examining those perceptions and related outcomes. There is a comparatively small number of measures examining school personnel perceptions. Of those found, only some had evidence of measurement invariance/equivalence (MI/E). None found with evidence of MI/E had evidence of structural invariance/equivalence (SI/E). This article explores these psychometric properties of The Georgia School Personnel Survey (GSPS) of school climate. We analyzed a representative sample of Georgia school personnel (N = 166,887) through exploratory, confirmatory, and multigroup confirmatory factor analysis. Results indicated that the GSPS has a second-order model containing six first-order subscales loading onto a second-order scale (acting as a measure of whole-school climate). Assessment of MI/E and SI/E suggested that the GSPS is an appropriate measure for comparisons based on gender, racial/ethnic identity, grade level, and job classification. Implications for research and practice will be discussed referencing the Cultural-Ecological Model of School Climate (CEMSC). Impact Statement This research provides psychometric properties for the Georgia School Personnel Survey (GSPS) of school climate, giving school personnel, lawmakers, and researchers information necessary to justify the use of the GSPS as a valid tool to assess and confidently compare staff perceptions of school climate. Specifically, this research provides evidence that the GSPS may be used to compare perceptions of school climate between school staff based on demographic characteristics (gender, racial/ethnic identity, job classification, and grade level). This research may be of special interest to a range of stakeholders, including school psychologists, district- and school-level administrators, and policymakers who are interested in comparing perceptions within schools or systems. School psychologists, who are trained as data-based decision-makers, play an important role as advocates to administrators and other school personnel. Specifically, school psychologists can help teams to analyze and interpret data as part of an empirically-based intervention to address the needs of school personnel. Supplemental data for this article is available online at https://doi.org/10.1080/2372966X.2021.1958645 .