The “hot hand” reconsidered: A meta-analytic approach

Despite evidence supporting the effectiveness of diabetic retinopathy screening (DRS) in reducing the risk of sight loss, attendance for screening is consistently below recommended levels. The primary objective of the review was to assess the effectiveness of quality improvement (QI) interventions that seek to increase attendance for DRS in people with type 1 and type 2 diabetes.Secondary objectives were:To use validated taxonomies of QI intervention strategies and behaviour change techniques (BCTs) to code the description of interventions in the included studies and determine whether interventions that include particular QI strategies or component BCTs are more effective in increasing screening attendance;To explore heterogeneity in effect size within and between studies to identify potential explanatory factors for variability in effect size;To explore differential effects in subgroups to provide information on how equity of screening attendance could be improved;To critically appraise and summarise current evidence on the resource use, costs and cost effectiveness. We searched the Cochrane Library, MEDLINE, Embase, PsycINFO, Web of Science, ProQuest Family Health, OpenGrey, the ISRCTN, ClinicalTrials.gov, and the WHO ICTRP to identify randomised controlled trials (RCTs) that were designed to improve attendance for DRS or were evaluating general quality improvement (QI) strategies for diabetes care and reported the effect of the intervention on DRS attendance. We searched the resources on 13 February 2017. We did not use any date or language restrictions in the searches. We included RCTs that compared any QI intervention to usual care or a more intensive (stepped) intervention versus a less intensive intervention. We coded the QI strategy using a modification of the taxonomy developed by Cochrane Effective Practice and Organisation of Care (EPOC) and BCTs using the BCT Taxonomy version 1 (BCTTv1). We used Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital (PROGRESS) elements to describe the characteristics of participants in the included studies that could have an impact on equity of access to health services.Two review authors independently extracted data. One review author entered the data into Review Manager 5 and a second review author checked them. Two review authors independently assessed risks of bias in the included studies and extracted data. We rated certainty of evidence using GRADE. We included 66 RCTs conducted predominantly (62%) in the USA. Overall we judged the trials to be at low or unclear risk of bias. QI strategies were multifaceted and targeted patients, healthcare professionals or healthcare systems. Fifty-six studies (329,164 participants) compared intervention versus usual care (median duration of follow-up 12 months). Overall, DRS attendance increased by 12% (risk difference (RD) 0.12, 95% confidence interval (CI) 0.10 to 0.14; low-certainty evidence) compared with usual care, with substantial heterogeneity in effect size. Both DRS-targeted (RD 0.17, 95% CI 0.11 to 0.22) and general QI interventions (RD 0.12, 95% CI 0.09 to 0.15) were effective, particularly where baseline DRS attendance was low. All BCT combinations were associated with significant improvements, particularly in those with poor attendance. We found higher effect estimates in subgroup analyses for the BCTs 'goal setting (outcome)' (RD 0.26, 95% CI 0.16 to 0.36) and 'feedback on outcomes of behaviour' (RD 0.22, 95% CI 0.15 to 0.29) in interventions targeting patients, and 'restructuring the social environment' (RD 0.19, 95% CI 0.12 to 0.26) and 'credible source' (RD 0.16, 95% CI 0.08 to 0.24) in interventions targeting healthcare professionals.Ten studies (23,715 participants) compared a more intensive (stepped) intervention versus a less intensive intervention. In these studies DRS attendance increased by 5% (RD 0.05, 95% CI 0.02 to 0.09; moderate-certainty evidence).Fourteen studies reporting any QI intervention compared to usual care included economic outcomes. However, only five of these were full economic evaluations. Overall, we found that there is insufficient evidence to draw robust conclusions about the relative cost effectiveness of the interventions compared to each other or against usual care.With the exception of gender and ethnicity, the characteristics of participants were poorly described in terms of PROGRESS elements. Seventeen studies (25.8%) were conducted in disadvantaged populations. No studies were carried out in low- or middle-income countries. The results of this review provide evidence that QI interventions targeting patients, healthcare professionals or the healthcare system are associated with meaningful improvements in DRS attendance compared to usual care. There was no statistically significant difference between interventions specifically aimed at DRS and those which were part of a general QI strategy for improving diabetes care. This is a significant finding, due to the additional benefits of general QI interventions in terms of improving glycaemic control, vascular risk management and screening for other microvascular complications. It is likely that further (but smaller) improvements in DRS attendance can also be achieved by increasing the intensity of a particular QI component or adding further components.

This Campbell systematic review examines the effect of interventions on school attendance to inform policy, practice and research. The review summarise findings from 28 studies conducted in the US, Canada, UK and Australia. Overall, truancy intervention programs are effective. There is a significant overall positive and moderate mean effect of intervention on attendance, which increases attendance by 4.7 days per student by the end of the intervention. Studies did not measure longer‐term outcomes, so we do not know if these gains in attendance continue after the intervention ends. There was no significant difference in the effectiveness of different delivery channels (e.g. school, court or community‐based), different modalities (e.g., individual, family, group, or multimodal), or different lengths of time (e.g., one day versus a school year). Contrary to popular belief and recommendations for best practices in truancy reduction found in the existing literature, collaborative programs and multimodal interventions do not produce greater effects on attendance than other types of programs. However, small sample sizes and substantial variation between studies suggest caution is needed in interpreting and applying these findings. There are shortcomings in the literature, notably the lack of inclusion of minority students. Executive summary/Abstract BACKGROUND Truancy is a significant problem in the U.S. and in other countries around the world. Truancy has been linked to serious immediate and far‐reaching consequences for youth, families, and schools and communities, leading researchers, practitioners, and policy makers to try to understand and to address the problem. Although numerous and significant steps have been taken at the local, state, and national levels to reduce truancy, the rates of truancy have at best remained stable or at worst been on the rise, depending on the indicator utilized to assess truancy rates. The costs and impact of chronic truancy are significant, with both short‐ and long‐term implications for the truant youth as well as for the family, school, and community. Although several narrative reviews and one meta‐analysis of attendance and truancy interventions have attempted to summarize the extant research, there are a number of limitations to these reviews. It is imperative that we systematically synthesize and examine the evidence base to provide a comprehensive picture of interventions that are being utilized to intervene with chronic truants, to identify interventions that are effective and ineffective, and to identify gaps and areas in which more research needs to be conducted to better inform practice and policy. OBJECTIVES The main objective of this systematic review was to examine the effects of interventions on school attendance to inform policy, practice, and research. The questions guiding this study were: Do truancy programs with a goal of increasing student attendance for truant youth affect school attendance behaviors of elementary and secondary students with chronic attendance problems? Are there differences in the effects of school‐based, clinic/community‐based, and court‐based programs? Are some modalities (i.e., family, group, multimodal) more effective than others in increasing student attendance? SEARCH STRATEGY A systematic and comprehensive search process was employed to locate all possible studies between 1990 and 2009, with every effort made to include both published and unpublished studies to minimize publication bias. A wide range of electronic bibliographic databases and research registers was searched, websites of relevant research centers and groups were mined for possible reports, over 200 e‐mails and letters were sent to programs listed in large databases of truancy programs compiled by the National Center for School Engagement and the National Dropout Prevention Center, and contact with researchers in the field of truancy and absenteeism was attempted. In addition, we examined reference lists of all previous reviews as well as citations in research reports for potential studies. SELECTION CRITERIA Studies eligible for this review were required to meet several eligibility criteria. Studies must have utilized a randomized, quasi‐experimental, or single‐group pre‐posttest design with the aim of evaluating the effectiveness of interventions with a stated primary goal of increasing student attendance (or decreasing absenteeism) among chronic truant students. Studies must have measured an attendance outcome and reported sufficient data to calculate an effect size. Finally, studies must have been published between 1990 and 2009 in the United States, United Kingdom, Australia, or Canada. DATA COLLECTION AND ANALYSIS A total of 28 studies, reported in 26 reports, met final eligibility criteria and were included in this review and meta‐analysis. Of the studies that were included, 5 utilized a randomized design (RCT), 11 utilized a quasi‐experimental design (QED), and 12 utilized a single group pre‐posttest design (SGPP). All eligible studies were coded using a structured coding instrument, with 20% of studies coded by a second coder. Descriptive analysis was conducted to examine and describe data related to the characteristics of the included studies. Analysis of the mean effect size, the heterogeneity of effect sizes, and the relationship between effect size and methodological and substantive characteristics of the interventions was also conducted separately for the RCT/QED studies and the SGPP studies. The effect sizes were calculated using the standardized mean difference effect size statistic, correcting for small sample size using Hedges' g (Hedges, 1992). Assuming a mixed effects model, the analog to the ANOVA and bivariate meta‐regression frameworks were used to examine potential moderating variables related to study, participant, and intervention characteristics. RESULTS The meta‐analytic findings demonstrated a significant overall positive and moderate mean effect of interventions on attendance outcomes. The mean effect size for interventions examined in the included RCT studies was .57 and the mean effect size for the QED studies was .43. No significant differences were observed between the RCT and QED studies in the magnitude of the treatment effect (Q b = .28, p >.05). The mean effect size of interventions examined using an SGPP design was .95. A moderate effect on attendance outcomes is encouraging; however, the overall mean effect size is masked by a large amount of heterogeneity, indicating significant variance in effect sizes between studies. Moderator analyses found no significant differences in mean effects between studies on any moderating variable tested. No differences were found between school‐, court‐, or community‐based programs or between different modalities of programs. The duration of the intervention also did not demonstrate any association with effect size. Collaborative programs and multimodal interventions produced statistically similar effects on attendance as non‐collaborative and single‐modality programs, which runs counter to the prevailing beliefs and recommendations for best practices in truancy reduction found in the literature. Other significant findings from this study relate to methodological shortcomings, the absence of important variables as well as gaps in the evidence base. These findings include the lack of inclusion of minority students and a lack of reporting and statistical analysis of demographic variables, particularly race/ethnicity and socioeconomic status (SES). Given that race and SES have been linked to absenteeism, the absence of this data was surprising. The majority of studies also lacked adequate descriptions of the interventions, making replication of the intervention difficult, and failed to measure and report long‐term outcomes. AUTHORS' CONCLUSIONS Overall, the findings from this study suggest that chronic truant students benefit from interventions targeting attendance behaviors; thus it is important and worthwhile to intervene with chronic truant youth. Given the minimal differences in effects across program types and modalities, no one program type or modality stands out as being more effective than any other. Although no statistically significant differences in effects were found between types and modalities of interventions included in this review, there was a lack of available evidence to support the general belief (and popular “best‐practice” recommendations) that collaborative and multimodal interventions are more effective than programs that are not collaborative and single modal interventions. Due to the small sample size and large heterogeneity between studies and within groups of studies, caution must be used when interpreting and applying the findings from this meta‐analysis. Overall, the studies included in the review improved attendance by an average of 4.69 days, almost a full school week. However, although the interventions included in this study were, overall, found to be effective, the mean rates of absenteeism at postte

This chapter aims to examine the relationship between service quality and customer satisfaction in the airline industry through a meta-analysis. To this end, a protocol was applied following the PRISMA 2009 guidelines, and the author analyzed 14 studies with a total sample size of 6552 eligible for analysis from the Web of Science (WoS) database. In this chapter, the “Fisher z” transformation was used to calculate the overall effect size. Due to the heterogeneity of the studies' effect sizes, the random effect model was used as the analysis model. The results revealed that publication bias does not pose a significant threat. In addition, a strong positive relationship between service quality and customer satisfaction was established (Cohen's d=0.765, 95% confidence interval [CI] 0.641, 0.888). This chapter contributes to the literature by increasing the validity of the existing studies and determining the overall effect size of the relationship between variables of interest by integrating the findings of 14 studies from the research domain.

A relevant problem in meta-analysis concerns the possible heterogeneity between trial results. If a test of heterogeneity is not significant the trials are often considered to be “homogeneous” and the...

Objective: To examine duration of efficacy of lisdexamfetamine dimesylate (LDX) in adults with attention-deficit/hyperactivity disorder (ADHD) by effect size in performance and symptom improvement in a simulated adult workplace environment (AWE). Methods: Adults (aged 18–55 years) with ADHD enrolled in the AWE study of LDX with open-label dose-optimization and randomized, placebo-controlled, double-blind, 2-way crossover phases. Efficacy measures included the Permanent Product Measure of Performance (PERMP)-Attempted (-A) and PERMP-Correct (-C) scores assessed throughout the day and the ADHD Rating Scale IV (ADHD-RS-IV) with adult prompts. Model-based least-squares (LS) mean effect size was assessed for PERMP and post-hoc ADHD-RS-IV with adult prompts. Remission was defined as an ADHD-RS-IV total scores ≤ 18. Safety assessments included treatment-emergent adverse events (TEAEs) and vital signs. Results: Least-squares mean (standard error [SE]) effect sizes were 0.9 (0.17) for PERMP-A and 0.8 (0.16) for PERMP-C for all postdose sessions. For PERMP-A, postdose LS mean (SE) effect sizes were 0.5 (0.15), 0.8 (0.16), 0.7 (0.16), 0.7 (0.16), 0.7 (0.16), and 0.6 (0.16) at 2, 4, 8, 10, 12, and 14 hours, respectively. Medium-to-large effect sizes (0.5-0.8) were generally maintained from 2 to 14 hours for all PERMP assessments. Overall LS mean (SE) ADHD-RS-IV total and subscale effect sizes were −1.2 (0.19), −1.2 (0.19), and −1.0 (0.17), respectively. Remission was achieved in 67.6% of participants receiving LDX. Treatment-emergent adverse events (≥ 5% with LDX) during the 4-week dose-optimization phase were decreased appetite, dry mouth, headache, insomnia, upper respiratory tract infection, irritability, nausea, anxiety, and feeling jittery. During the crossover week on LDX, there were no TEAEs ≥ 5%. Conclusions: In adults studied in the AWE, medium-to-large model-based effect sizes were maintained from 2 to 14 hours postdose, on a performance-based measure of productivity, suggesting participants experienced improvement in sustained attention throughout the day and into the evening hours. Lisdexamfetamine dimesylate demonstrated a safety profile consistent with long-acting stimulants.

Researchers have increasingly investigated sources of variance in reading comprehension test scores, particularly with students with reading difficulties (RD). The purpose of this meta-analysis was to determine if the achievement gap between students with RD and typically developing (TD) students varies as a function of different reading comprehension response formats (e.g., multiple choice, cloze). A systematic literature review identified 82 eligible studies. All studies administered reading comprehension assessments to students with RD and TD students in Grades K–12. Hedge’s g standardized mean difference effect sizes were calculated, and random effects robust variance estimation techniques were used to aggregate average weighted effect sizes for each response format. Results indicated that the achievement gap between students with RD and TD students was larger for some response formats (e.g., picture selection ES g = −1.80) than others (e.g., retell ES g = −0.60). Moreover, for multiple-choice, cloze, and open-ended question response formats, single-predictor metaregression models explored potential moderators of heterogeneity in effect sizes. No clear patterns, however, emerged in regard to moderators of heterogeneity in effect sizes across response formats. Findings suggest that the use of different response formats may lead to variability in the achievement gap between students with RD and TD students.

Celiac Disease and Bone Health in Children and Adolescents: A Systematic Review and Meta-Analysis

Block-based visual programming tools, such as Scratch, Alice, and MIT App Inventor, provide an intuitive and easy-to-use editing interface through which to promote programming learning for novice students of various ages. However, very little attention has been paid to investigating these tools’ overall effects on students’ academic achievement and the study features that may moderate the effects of block-based visual programming from a comprehensive perspective. Thus, the present study carried out a meta-analysis to systemically examine 29 empirical studies (extracting 34 effect sizes) using experimental or quasi-experiments involving the programming learning effects of employing block-based visual programming tools to date (until the end of 2019). The results showed a small to medium significant positive overall mean effect size (fixed-effect model g = 0.37; random-effects model g = 0.47) of the use of these block-based visual programming tools with respect to students’ academic achievement. Furthermore, the overall mean effect size was significantly affected by the educational stage, programming tool used, experimental treatment, and school location. Discussions and implications based on the findings are provided.

Current myocarditis guidelines do not advocate treatment to prevent myocardial injury and scar deposition in patients with myocarditis and normal left ventricular ejection fraction. We aimed to ascertain the utility of beta blockers, calcium channel blockers and antagonists of the renin–angiotensin system in ameliorating myocardial injury, scar formation and calcification in animal in vivo models of myocarditis. The project was prospectively registered with the PROSPERO database of systematic reviews (CRD42018089336). Primary outcomes (necrosis, fibrosis and calcification) were meta-analysed with random-effects modelling. 52 studies were systematically reviewed. Meta-analysis was performed compared with untreated controls. In each study, we identified all independent comparisons of treatment versus control groups. The pooled weighted mean difference (WMD) indicated treatment reduced necrosis by 16.9% (71 controlled analyses, 95% CI 13.2–20.7%; P < 0.001), however there was less evidence of an effect after accounting for publication bias. Treatment led to a 12.8% reduction in fibrosis (73 controlled analyses, 95% CI 7.6–18.0%; P < 0.001). After accounting for publication bias this was attenuated to 7.8% but remained significant. Treatment reduced calcification by 4.1% (28 controlled analyses, 95% CI 0.2–8.0%; P < 0.0395). We observed significant heterogeneity in effect size in all primary endpoints, which was predominantly driven by differences between drug categories. Beta blockers and angiotensin-converting enzyme (ACE) inhibitors were the only agents that were effective for both necrosis and fibrosis, while only ACE inhibitors had a significant effect on calcification. This study provides evidence for a role for ACE inhibitors and beta blockers to prevent myocardial injury and scar deposition in in vivo models of myocarditis. There is a need for further well-designed studies to assess the translational application of these treatments.

6 Background 6 Objectives 6 Selection criteria 6 Search strategy 7 Data collection and analysis 7 Main results 7 Authors’ conclusions 7

Replications are important for science, both statistically and philosophically. A plethora of empirical studies that have been done so far show that there are always variations, errors and inconclusive findings on the technical efficiency (TE) scores of wheat output in Ethiopia. In this study, we intend to contribute to these controversies by providing the first thorough investigation of the magnitude of mean-effect size and the underlying factors of mean technical efficiency variations in wheat production across studies in Ethiopia. These efficiency scores are retrieved from 31 studies, or a household size of 12,754 over the years 2011–2022. The analysis of meta-regression was done using a random effect model using Comprehensive Meta-analysis (CMA-4) software. The Begg and Mazumdar rank-correlation test, egger test, and funnel plot were used to determine publication bias across studies. Since 2022, we have utilized the classic fail-safe-N test. One issue with publication bias is the omission of some non-significant studies from the analysis, which, if they were included, would cancel out the observed effect. Further, the missing study problem or “file drawer” problem, of the study would also be computed using the “Trim and Fill” estimation approach. To evaluate heterogeneity, a forest plot is used. The effect size is also determined using the random effect model along with the I-squared statistic, the tau-squared and tau, and the Q-test. As a result, a mean effect size of 71.6% with a 95% confidence interval of 67.9%−75.3% is observed. The meta-regression demonstrates that the 31 mean technical efficiency studies included in the research had varying efficiency scores due to variations in sample size, methodologies used, publication status, and study range. It suggests that, with all other factors held constant, a 1% change in these regressors causes a 0.01%, 10.88%, 21.22%, and 6.74% change, respectively, in the mean technical efficiency scores across studies in Ethiopia. In addition, the technical efficiency score across studies is also affected by the location in which the study is conducted.

The purpose was to summarize the studies examining the contralateral protective effect on the maximal strength in the subsequent bout of muscle-damaging exercise. The literature search was conducted through CINAHL plus, SportDiscus, and PubMed. Hedge’s g effect size (ES) and 95% confidence intervals (CIs) were computed using a random effects model. From 14 papers and 25 ESs, the mean ES for contralateral repeated bout effect (CL-RBE) on 1-, 2-, and 3-day post maximal strength were −0.61 (95% CI = −0.80, −0.41), −0.50 (95% CI = −0.67, −0.33), and −0.74 (95% CI = −1.01, −0.48), respectively. For moderator analyses, the mean ESs were not influenced by type (isometric vs. isokinetic) of strength, but CL-RBE on maximal strength was influenced by duration (≤6 weeks) between bouts. Therefore, the meta-analysis demonstrated that an initial bout of exercise induces the protective effect on contralateral limb muscles regardless of the different type of strength, but can be affected by different duration (≤6 weeks) between exercise bouts.

Meta-Analysis of Catheter Directed Ultrasound-Assisted Thrombolysis in Pulmonary Embolism

School administrators’ leadership characteristics are crucial in creating a learning school. Therefore, this study aimed to examine the relationship between transformational leadership characteristics and the learning school using meta-analysis. For this purpose, individual studies suitable for inclusion criteria were determined. In this context, we examined the studies between the years 2000 and 2020 on the relationship between school administrators’ transformational leadership characteristics and learning schools. Studies including correlation coefficient, t value, and sample size were covered to calculate the effect size required for meta-analysis. A total of 20 effect sizes were included in the 19 studies. In the study, analyses of forest plots, publication bias, heterogeneity, and subgroup tests were performed. The random-effects model conducted in the study determined that the overall effect size was positive and strong. The subgroup analysis showed that the country variable was the source of heterogeneity in effect sizes, while the publication type was not. The study revealed that leadership characteristics are significant predictors of learning school and one of the most critical leadership styles to create a learning school is transformational leadership. Policymakers and practitioners have essential duties in transforming schools into learning schools. Therefore, school administrators who want to turn their schools into learning organizations should always be supported by those who produce education policies.

In high-dimensional sparse regression, would increasing the signal-to-noise ratio while fixing the sparsity level always lead to better model selection? For high-dimensional sparse regression problems, surprisingly, in this paper we answer this question in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">negative</i> in the regime of linear sparsity for the Lasso method, relying on a new concept we term <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">effect size heterogeneity</i> . Roughly speaking, a regression coefficient vector has high effect size heterogeneity if its nonzero entries have significantly different magnitudes. From the viewpoint of this new measure, we prove that the false and true positive rates achieve the optimal trade-off <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">uniformly</i> along the Lasso path when this measure is maximal in a certain sense, and the worst trade-off is achieved when it is minimal in the sense that all nonzero effect sizes are roughly equal. Moreover, we demonstrate that the first false selection occurs much earlier when effect size heterogeneity is minimal than when it is maximal. The underlying cause of these two phenomena is, metaphorically speaking, the “competition” among variables with effect sizes of the same magnitude in entering the model. Taken together, our findings suggest that effect size heterogeneity shall serve as an important complementary measure to the sparsity of regression coefficients in the analysis of high-dimensional regression problems. Our proofs use techniques from approximate message passing theory as well as a novel technique for estimating the rank of the first false variable.