Variable- and person-centered approaches to examining construct-relevant multidimensionality in writing self-efficacy.

Self-efficacy is an essential component of students' motivation and success in writing. There have been great advancements in our theoretical understanding of writing self-efficacy over the past 40 years; however, there is a gap in how we empirically model the multidimensionality of writing self-efficacy. The purpose of the present study was to examine the multidimensionality of writing self-efficacy, and present validity evidence for the adapted Self-Efficacy for Writing Scale (SEWS) through a series of measurement model comparisons and person-centered approaches. Using a sample of 1,466 8th-10th graders, results showed that a bifactor exploratory structural equation model best represented the data, demonstrating that the SEWS exhibits both construct-relevant multidimensionality and the presence of a global theme. Using factor scores derived from this model, we conducted latent profile analysis to further establish validity of the measurement model and examine how students disaggregate into groups based on their response trends of the SEWS. Three profiles emerged, differentiated by global writing self-efficacy, with substantively varying factor differences among the profiles. Concurrent, divergent, and discriminant validity evidence was established through a series of analyses that assessed predictors and outcomes of the profiles (e.g., demographics, standardized writing assessments, and grades). Theoretical and practical implications and avenues for future research are discussed.

Understanding afterschool engagement: Investigating developmental outcomes for adolescents.

Though student engagement is hypothesized to be a factor in explaining student level differences in afterschool programs, the measurement of student engagement in this context is inconsistent, and findings from the small number of studies about how engagement impacts developmental and academic outcomes are mixed. In this study, we tested the factor structure of Wang and colleagues' school engagement scale with a sample of middle school students (N = 197) who attended an afterschool program in an urban setting. Results suggest that a bifactor model of engagement best fits the data, meaning that engagement consists of four specific factors (affective, behavioral, cognitive, social) and a global factor. We then used structural equation modeling to examine the relationship between engagement, academic outcomes, and positive youth development (PYD). Results also showed positive associations with student mathematics achievement and PYD, but no significant associations were found between engagement and English achievement. This study provides a theoretically aligned way to measure engagement and evidence to support engagement as a key factor in predicting youth outcomes in an out-of-school context.

Reporting and Reproducibility of Meta-Analysis in Speech, Language, and Hearing Research.

Purpose The purposes of this meta-review are to (a) articulate the importance of transparency and reproducibility in meta-analysis, (b) assess the transparency and reproducibility of meta-analyses published in journals of the American Speech-Language-Hearing Association (ASHA), and (c) discuss the implications of our findings and recommendations for future research. Method We conducted a meta-review of all meta-analyses published in ASHA journals through December 31, 2020. Our systematic review yielded 47 meta-analyses for inclusion in this review. We coded all eligible reports on the core elements of transparency and reproducibility in meta-analysis. Results Our findings suggest that though reporting tendencies have improved over time, much work is needed to promote transparency and reproducibility in meta-analytic work. Key areas for future accountability include preregistering study protocol, using Preferred Reporting in Systematic Reviews and Meta-Analysis checklists, providing full data sets, and publishing analytic codes. Conclusions The state of reporting in meta-analysis is improving over time. We conclude with a discussion of specific areas that need further attention, and recommendations for researchers to consider when conducting future meta-analyses. Supplemental Material https://doi.org/10.23641/asha.14888481.