Search

This study conducted secondary analysis of data from the National Longitudinal Transition Study-2 (NLTS2) to examine the degree to which student, family, and school constructs predicted self-determination outcomes. Multi-group structural equation modeling was used to examine predictive relationships between 5 student, 4 family, and 7 school constructs developed from NLTS2 data and self-determination outcomes (autonomy, psychological empowerment, and self-realization) across disability groups. The pattern of predictive relationship between the constructs and self-determination outcomes across disability groups was complex. Only one construct--self-concept--showed a positive predictive relationship with all three self-determination constructs across most disability groups. Implications of the complex pattern of findings for research and practice are discussed.

The purpose of this study was to use data from the National Longitudinal Transition Study-2 (NLTS2) to (a) conceptually identify and empirically establish student, family, and school constructs; (b) explore the degree to which the constructs can be measured equivalently across disability groups; and (c) examine latent differences (means, variances, and correlations) in the constructs across disability groups. Conceptual analysis of NLTS2 individual survey items yielded 21 student, family, and school constructs, and 16 were empirically supported. Partial strong metric invariance was established across disability groups, and in the latent space, a complex pattern of mean and variance differences across disability groups was found. Disability group moderated the correlational relationships between multiple predictor constructs, suggesting the key role of disability-related characteristics in understanding the experiences of youth with disabilities. Implications for future research and practice are discussed.

We examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based) measure that contains systematic measurement bias (e.g., response bias). Using simulated data on four measurement occasions, we compared the cost-efficiency and validity of longitudinal designs where the gold standard is measured at one or more measurement occasions. We manipulated the nature of the response bias over time (constant, increasing, fluctuating), the factorial structure of the response bias over time, and the constraints placed on the latent variable model. Our results showed that parameter bias is lowest when the gold standard is measured on at least two occasions. When a multifactorial structure was used to model response bias over time, it is necessary to have the "gold standard" measures included at every time point, in which case most of the parameters showed low bias. Almost all parameters in all conditions displayed high relative efficiency, suggesting that the 2-method design is an effective way to reduce costs and improve both power and accuracy in longitudinal research.

Background: Individuals with autism spectrum disorder (ASD) have social communication difficulties and restricted, repetitive, and/or sensory behaviors or interests. The prevalence of ASD is now 1 in 36 individuals. Parents of individuals with ASD face challenges that can affect their physical and psychological well-being. Objective: With the long-term goal to tailor an exercise program, the purpose of this study was 2-fold: (1) establish the baseline physical and mental health of parents of individuals with ASD and (2) estimate the relationship of physiologic variables with psychological variables of health for parents of individuals with ASD. Methods: This descriptive, cross-sectional study (N = 44) explored physical health measures and the correlation between physical and psychological health, using measures of anxiety, stress, parenting depression, and positive thinking for parents who care for individuals with ASD. Results: The common characteristics that these parents shared was high body fat and low physical activity. Body fat was negatively correlated to total step count (r = −0.428, P <.05), grip strength (r = −0.319, P <.5), and total distance walked in the week (r = −0.661, P <.01), and positively correlated to 5-times sit to stand (r = 0.337, P <.05). Low activity correlated to increased parenting stress of advocating for child's needs (r = −0.310, P =.043). Conclusions: Understanding relationships between physical and psychological health informs effective interventions and support systems for parents. Parents need supports to be able to prioritize exercise. Future studies should include a larger sample to verify these effects. [ABSTRACT FROM AUTHOR]

It is often unrealistic to assume normally distributed latent traits in the measurement of health outcomes. If normality is violated, the item response theory (IRT) models that are used to calibrate questionnaires may yield parameter estimates that are biased. Recently, IRT models were developed for dealing with specific deviations from normality, such as zero-inflation ("excess zeros") and skewness. However, these models have not yet been evaluated under conditions representative of item bank development for health outcomes, characterized by a large number of polytomous items. A simulation study was performed to compare the bias in parameter estimates of the graded response model (GRM), polytomous extensions of the zero-inflated mixture IRT (ZIM-GRM), and Davidian Curve IRT (DC-GRM). In the case of zero-inflation, the GRM showed high bias overestimating discrimination parameters and yielding estimates of threshold parameters that were too high and too close to one another, while ZIM-GRM showed no bias. In the case of skewness, the GRM and DC-GRM showed little bias with the GRM showing slightly better results. Consequences for the development of health outcome measures are discussed. [ABSTRACT FROM AUTHOR]

The process of ovarian aging is influenced by a complex and poorly understood interplay of endocrine, metabolic, and environmental factors. The purpose of this study was to explore the feasibility of using latent class analysis to identify subgroups based on cardiometabolic, psychological, and reproductive parameters of health and to describe patterns of anti-Müllerian hormone levels, a biomarker of the ovarian reserve, within these subgroups. Sixty-nine lean (body mass index [BMI] ⩽ 25 kg/m2) and severely obese (BMI ⩾ 40 kg/m2) postpartum women in Edinburgh, Scotland, were included in this exploratory study. The best fitting model included three classes: Class 1, n = 23 (33.5%); Class 2, n = 30 (42.2%); Class 3, n = 16 (24.3%). Postpartum women with lower ovarian reserve had less favorable cardiometabolic and psychological profiles. Examining the ovarian reserve within distinct subgroups based on parameters of health that affect ovarian aging may facilitate risk stratification in the context of ovarian aging. [ABSTRACT FROM AUTHOR]