Amanda Jean Neitzel

Background: Compared with other forms of online mental health interventions, programs delivered through social media apps may require less training and be more acceptable and accessible to various populations. During and after the pandemic, both the number of social media users and the prevalence of social-media-based mental health interventions increased significantly. However, to the best of the authors’ knowledge, no meta-analysis so far has focused on rigorous social-media-based mental health interventions for general populations. Objective: This preregistered meta-analysis synthesized findings from rigorously designed randomized controlled trials (RCTs) (ie, decent sample size, low attrition, and comparable baseline conditions) to understand whether social-media-based mental health RCTs work as expected in reducing mental health issues. Methods: We searched for articles through database queries, hand searching, and forward and backward citation tracking, which yielded 11,658 studies. We only included social-media-based RCTs with a decent sample size (n≥30 for each experimental condition at baseline assessment), low differential attrition between treatments and controls (P<.001, N_ES=61, 95% CI 0.24-0.45, I²=88.10, τ²=0.13) for the general population (range of mean age: 15.27~59.65). In other words, social-media-based interventions were effective at reducing anxiety (ES=0.33, P=.04, n=27), depression (ES=0.31, P<.001, n=31), and stress (ES=0.69, P=.02, n=12). Moderator analysis showed that social-media-based interventions are more effective when the participants are more than 70% female, when the programs are human-guided, social-oriented, and when control groups are care as usual. Furthermore, we conducted a risk of bias analysis, publication bias analysis, and sensitivity analysis, which show low risks of bias and robust findings. The biggest limitation of this review is the small sample size of 17 included studies, which restricts the power of our models. Conclusions: While technology can be a double-edged sword, this meta-analysis highlighted social media’s benefits and future potential in the treatment of mental health symptoms.

The issue of students dropping out before completing secondary education is a global concern with significant individual and societal consequences. Various terms, such as Early School Leaving (ESL), Early Leaving from Education and Training (ELET), and school dropout, reflect different policy perspectives on this phenomenon. Despite international efforts to address school dropout, a comprehensive review identifying areas with strong evidence and research gaps is lacking. This Evidence and Gap Map (EGM) systematically reviews the evidence on programs aimed at reducing school dropout and improving intermediate outcomes (e.g., educational performance, attendance). Following the 2011 European Council Recommendations, interventions are categorized into three domains: prevention, intervention, and compensation. The EGM will provide school and policy decision-makers, as well as program developers, with an overview of research evidence useful for guiding efforts to reduce school dropout and design effective programs. By pinpointing research gaps, the EGM will help identify critical areas where further investigation is needed to better understand and address the impact of school dropout programs.

This systematic review and meta-analysis examined the effectiveness of Spanish reading programs in grades K–6. The research designs included were experimental and quasi-experimental. Effect sizes were analyzed using a multivariate meta-regression model with robust variance estimation. To assess the degree of heterogeneity in the effect sizes, a 95% prediction interval was calculated. A total of 11 studies and 51 effect sizes met the inclusion criteria. The full meta-regression model controlling for grade level and outcome type showed a large positive effect across all studies (effect size = 0.49, p < 0.05), with a large, positive effect on reading outcomes, and significant impacts on phonological awareness, phonics, fluency, and reading comprehension in K–2. Results suggest that effective instructional programs for K–6 Spanish reading exist. However, there is a need for more rigorous research on reading instructional programs for Spanish-speaking children.

This meta-analysis synthesized recent research on promoting learner autonomy through strategy instruction in tertiary English classrooms in China for two main purposes: (a) to estimate the effects of strategy instruction on English achievement and outcomes related to learner autonomy; and (b) to examine the moderating effects of a set of intervention and contextual characteristics. A total of 49 studies contributed to 111 effect sizes for this meta-analysis. Using a random-effects model, this study finds that the overall effect size of strategy instruction was 0.92 (p < 0.001). The type of outcome measure significantly moderated the impact of strategy instruction. Interventions that assessed multiple aspects of learner autonomy (cognitive, metacognitive, motivational, and social) had a significantly higher mean effect size than those assessing a single aspect. The results suggest strategy instruction is a viable instructional tool for promoting learner autonomy among college students in English-as-a-foreign-language classrooms. The results emphasize that fully understanding the impact of a strategy instruction intervention on learner autonomy requires an examination of its various dimensions.

Teacher turnover influences students’ performance in a negative way. Among all reasons, unsatisfying salary could be a main factor contributing to teachers leaving their profession. Yet, little is known about how contextual moderators affect this relationship and most past research focuses on the US context. This meta-analysis seeks to compare the relationship between turnover and salary in the US and China while differentiating turnover intention from real turnover rate. Applying a set of screening criteria, we identified 21 studies (five in China and 16 in the US), which produced a statistically significant relationship (OR = 0.99, p < .05). This result means that salary had a negative relationship with turnover - where more salary is related with a lower chance of teacher turnover. As for moderator analysis, we found a significant difference between urban schools as compared to rural and combined school types (p = 0.01). There was no statistically significant difference in the relationship between salary and turnover in studies conducted in the US and China, or studies in public and private schools or studies in middle and primary schools. Our findings contribute to the field of research around teacher turnover by reinforcing the significant role that salary continues to play in teachers’ decisions to stay in the classroom or leave. Additionally, this study expands the geographical scope of the research on teacher turnover and salary beyond the United States to include studies of Chinese teachers as well.

Given the importance of conversation practice in language learning, chatbots, especially ChatGPT, have attracted considerable attention for their ability to converse with learners using natural language. This review contributes to the literature by examining the currently unclear overall effect of using chatbots on language learning performance and comprehensively identifying important study characteristics that affect the overall effectiveness. We meta-analyzed 70 effect sizes from 28 studies, using robust variance estimation. The effects were assessed based on 18 study characteristics about learners, chatbots, learning objectives, context, communication/interaction, and methodological and pedagogical designs. Results indicated that using chatbots produced a positive overall effect on language learning performance ( g = 0.484), compared to nonchatbot conditions. Moreover, four characteristics (i.e., educational level, language level, interface design, and interaction capability) affected the overall effectiveness. In an in-depth discussion on how the 18 characteristics are related to the effectiveness, future implications for practice and research are presented.

The Every Student Succeeds Act has made the use of evidence even more relevant to policymakers and practitioners. The What Works Clearinghouse (WWC) serves a role as reviewer of evidence as policymakers and practitioners attempt to navigate the broad expanse of educational research. For this reason, it is of vital interest to understand whether WWC policies lead to fair estimates of effect sizes. Previous research (e.g. Cheung & Slavin, 2016) has indicated that small studies are associated with greatly inflated effect sizes. This study examined whether this could be explained by methodological and program factors of studies in the WWC database. Using the outcomes from all accepted studies in the reading and mathematics areas, we found a non-linear trend of effect size decreasing as the sample size increases. Even controlling for research design, level of assignment, type of intervention, and type of outcome, there was still an effect of sample size. While publication bias, intervention strength, methodological rigor, and superrealization may each contribute partially to this sample size effect, neither individually nor together do they explain the full impact of sample size on effect size. We suggest the WWC institute a policy of weighting studies by inverse variance before averaging effect sizes, and setting minimum sample criteria to reduce the inflationary effect of small study bias.

This study evaluates the efficacy of the "Tutoring with the Lightning Squad" (TwLS) model, developed by the Success for All Foundation, which uses trained college graduates to provide structured, cooperative learning-based tutoring to small groups of elementary students. The randomized controlled trial, conducted during the 2021-2022 school year across 23 elementary schools in a diverse Southern California district, aimed to determine the impact of TwLS on reading achievement for students at risk of reading failure, comparing small-group and one-to-one tutoring formats. Students were randomly assigned to receive TwLS tutoring in small groups or one-to-one. Reading achievement was measured using the Woodcock-Johnson III Tests of Achievement and NWEA MAP scores. The study assessed the fidelity of implementation, overall impact, and effects on subgroups, including gender, ethnicity, English Learner status, grade level, and baseline reading achievement. Results showed a significant positive impact on the Word Attack subtest of the Woodcock-Johnson for students receiving small-group tutoring, with an effect size of +0.18. No significant differences were found for other reading measures. Comparisons between small-group and one-to-one tutoring revealed no significant differences in outcomes. The study highlights the potential of TwLS as a cost-effective approach to improving reading skills in early grades, particularly in economically challenged and diverse school districts. Despite disruptions from the COVID-19 pandemic, which affected consistent implementation, the findings suggest that TwLS can enhance reading achievement for struggling readers. Further research is recommended to replicate these findings and explore the program's impact across different populations and settings.