Disablement in the Physically Active Scale Short Form-8: psychometric evaluation

Background Patient-centered care and evidence-based practice (EBP) are core competencies for health care professionals. The importance of EBP has led to an increase in research involving clinical outcomes; current recommendations emphasize collecting patient focused measures, thus increasing the need for psychometrically sound patient reported outcome measures (PROMs) of health. Disablement has been identified as a valuable multi-dimensional construct for patient care. The Disablement in the Physically Active Scale Short Form-8 (DPA SF-8) has been proposed as a tool to be used in the physically active population that assesses a physical summary component of health and a quality of life component however, further analysis is necessary to ensure the instrument is psychometrically sound. Methods Confirmatory factor analyses (CFAs) were conducted on the DPA SF-8 at each time point to ensure factor structure. Reliability of the scale and internal consistency of the subscales were assessed, and a minimal detectable change (MDC) calculated. Additionally, a minimal clinically important difference (MCID) was also established, and invariance testing across three time points and groups was conducted. Results The CFAs at all three visits exceeded recommended model fit indices. The interclass correlation coefficient value (.924) calculated indicated excellent scale reliability and Cronbach’s alpha for subscales PHY and QOL were within recommend values. The MDC value calculated was 5.83 and the MCID for persistent injuries were 2 points and for acute injuries, 3 points. The DPA SF-8 was invariant across time and across subgroups. Conclusions The DPA SF-8 met CFA recommendations and criteria for multi-group and longitudinal invariance testing, which indicates the scale may be used to assess for differences between the groups or across time. Our overall analysis indicates the DPA SF-8 is a valid, reliable, and responsive instrument to assess patient improvement in the physically active population.

Confirmatory Factor Analysis of the Athlete Sleep Behavior Questionnaire

Context: Sleep has long been understood as an essential component for overall well-being, significantly impacting physical health, cognitive functioning, mental health, and quality of life. Currently, the Athlete Sleep Behavior Questionnaire (ASBQ) is the only known instrument designed to measure sleep behaviors in the athletic population. However, the psychometric properties of the scale in a collegiate student-athlete and dance population have not been established. Objective: To assess model fit of the ASBQ using a sample of collegiate student-athletes and competitive dancers. Design: Observational study. Setting: Twelve colleges and universities. Patients or Other Participants: Student-athletes and dancers competing at the collegiate level. Main Outcome Measure(s): A confirmatory factor analysis (CFA) was conducted to assess the factor structure of the ASBQ. Principal component analysis (PCA) extraction and covariance modeling analyses were performed to identify an alternate model. Multi-group invariance testing was performed on the alternate model to identify if group differences existed between sex, athletic activity, injury status, and division of competition. Results: The CFA on the ASBQ indicated the model did not meet recommended model fit indices. An alternate three-factor, nine-item model with improved fit was identified; however, the scale structure was not consistently supported during multi-group invariance testing procedures. Conclusions: The original three factor, 18-item ASBQ was not supported for use with collegiate athletes in our study. The alternate ASBQ was substantially improved; however, more research should be completed to ensure the nine-item instrument accurately captures all dimensions of sleep behavior relevant for collegiate athletes.

The Relationship Between (sub)national Identity, Citizenship Conceptions, and Perceived Ethnic Threat in Flanders and Wallonia for the Period 1995–2020: A Measurement Invariance Testing Strategy

This article examines the relationship between (sub)national identity and attitudes towards immigrants in the multinational context of Belgium. We extend our previous studies by analysing a longer time period (1995–2020) and by making a strong case for the idea that measurement invariance testing and theoretical meaningfulness are closely intertwined. To examine whether and how the relationship between (sub)national identity and perceived ethnic threat has changed over time and between regions, we first test for metric invariance of the latent concepts. Using data from the Belgian National Election Studies, we illustrate that evaluating invariance of measurements is a necessary condition for comparative research, but also that measurement equivalence testing should be considered as an empirical guide showing researchers where substantial conclusions should potentially be revisited and theoretical validity rethought. Next, we verify whether the relationship between (sub)national identity and perceptions of ethnic threat across subnational units can be attributed to different conceptions of community membership -in terms of ethnic and/or civic citizenship conceptions- in Flanders and Wallonia. While we expected that a strong identification with Flanders would primarily be related to an ethnic citizenship representation, and as a result, stronger feelings of threat towards immigrants; we expected that a strong identification with Wallonia would primarily be related to a civic representation of the nation and therefore lower feelings of threat. Thanks to our thorough invariance testing strategy, the conceptualisation and measurement of (sub)national identity had to be adjusted in Wallonia, and the hypotheses had to be qualified.

Interpreting Cross-Cultural Bias in Psychological Assessments: An Empirical Example

Cockcroft et al. (2015) fit a multigroup confirmatory factor model to Wechsler Adult Intelligence Scale III (WAIS-III) data from South Africa and the United Kingdom. They found evidence for measurement bias and suggested that bias was greatest in those subtests of the WAIS-III that showcased the largest mean group differences. They went on to state that the "[i]dentification of tests that do not favor individuals from Eurocentric and favorable SES circumstances with advantaged educational backgrounds is valuable in providing direction for the development of culture fair tests", in effect suggesting that the results confirmed the test was biased towards culturally European groups. However, a reanalysis that included estimation of the effect sizes and directions of bias showed that, far from their conclusions, bias operated in different directions, but primarily in favor of the lower-scoring South African population examined in their study. The need for greater qualification in measurement invariance testing is shown and recommended.

Factor Analysis of the Short-Form Cohen-Mansfield Agitation Inventory (CMAI) and the Measurement Invariance by Gender

Background and PurposeThe Cohen-Mansfield Agitation Inventory (CMAI) is a widely used measure of agitation. The purpose of this study was to test the internal consistency, reliability, and validity of short-form CMAI in a sample of nursing home residents with cognitive impairment and examine if it is invariant across gender.MethodsThis study utilized baseline data from a randomized trial including 553 residents from 55 nursing homes. Data was analyzed using structural equation modeling.ResultsConfirmatory factory analysis supported the three-factor structure including aggressive (α = .794), physically nonaggressive (α = .617), and verbally agitated (α = .718) behaviors. Invariance testing confirmed that the shortened measure is invariant across gender.ConclusionsFindings provide validity evidence of short-form CMAI to assess agitation and gender differences in agitation in nursing home population.

Measurement Invariance Testing Using Confirmatory Factor Analysis and Alignment Optimization: A Tutorial for Transparent Analysis Planning and Reporting

Measurement invariance—the notion that the measurement properties of a scale are equalacross groups, contexts, or time—is an important assumption underlying much of psychology research. The traditional approach for evaluating measurement invariance is to fit a series of nested measurement models using multiple-group confirmatory factor analyses. However, traditional approaches are strict, vary across the field in implementation, and present multiplicity challenges, even in the simplest case of two groups under study. The alignment method was recently proposed as an alternative approach. This method is more automated, requires fewer decisions from researchers, and accommodates two or more groups. However, it has different assumptions, estimation techniques, and limitations from traditional approaches. To address the lack of accessible resources that explain the methodological differences and complexities between the two approaches, we introduce and illustrate both, comparing them side by side. First, we overview the concepts, assumptions, advantages, and limitations of each approach. Based on this overview, we propose a list of four key considerations to help researchers decide which approach to choose and how to document their analytical decisions in a preregistration or analysis plan. We then demonstrate our key considerations on an illustrative research question using an open dataset and provide an example of a completed preregistration. Our illustrative example is accompanied by an annotated analysis report that shows readers, step-by-step, how to conduct measurement invariance tests using R and Mplus. Finally, we provide recommendations for how to decide between and use each approach and next steps for methodological research.

Nový přístup v testování ekvivalence na příkladu měření subjektivního blahobytu

Survey-based measures of subjective well-being are more and more often analyzed cross-culturally. However, international comparison of these measures requires measurement invariance. Therefore, the major goal of this study was to investigate the cross-country comparability of the five-item subjective well-being scales used in the International Social Survey Programme (2011, 2017). This study applied both the traditional exact and the more recent Bayesian approximate approach to assess whether the subjective well-being scales were measurement invariant. The Bayesian approach detected several non‑invariant items that were problematic for cross-national comparison and could be dropped from the scales. Consequently, measurement invariance was established in all countries for the reduced scales, allowing researchers to meaningfully compare their latent mean scores and the relationships with other theoretical constructs of interest. Thus, the study highlighted the advantages of using multiple indicators and the necessity of measurement invariance testing in subjective well-being research.