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Literature screening is the process of identifying all relevant records from a pool of candidate paper records in systematic review, meta-analysis, and other research synthesis tasks. This process is time consuming, expensive, and prone to human error. Screening prioritization methods attempt to help reviewers identify most relevant records while only screening a proportion of candidate records with high priority. In previous studies, screening prioritization is often referred to as automatic literature screening or automatic literature identification. Numerous screening prioritization methods have been proposed in recent years. However, there is a lack of screening prioritization methods with reliable performance. Our objective is to develop a screening prioritization algorithm with reliable performance for practical use, for example, an algorithm that guarantees an 80% chance of identifying at least 80 % of the relevant records. Based on a target-based method proposed in Cormack and Grossman, we propose a screening prioritization algorithm using sampling with replacement. The algorithm is a wrapper algorithm that can work with any current screening prioritization algorithm to guarantee the performance. We prove, with mathematics and probability theory, that the algorithm guarantees the performance. We also run numeric experiments to test the performance of our algorithm when applied in practice. The numeric experiment results show this algorithm achieve reliable performance under different circumstances. The proposed screening prioritization algorithm can be reliably used in real world research synthesis tasks., (© 2024 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.)

Despite many dogs living in homes in the UK, there is still more to know about the welfare of those individual animals. Past research has shown that owners' thoughts and behaviours have a substantial impact on their dog's welfare. This study aimed to better understand owners' pre-purchase behaviours, knowledge and understanding, and ownership practices, and explore any associations between these factors and their dog's welfare. We conducted further analysis of the data collected by People's Dispensary for Sick Animals (PDSA) for their 2017 PDSA Animal Welfare (PAW) Report ( n = 1814). We extracted variables to describe owner demographics (7), pre-purchase behaviours (1), knowledge and understanding (4), welfare indicators, (2) and ownership practices (4), and we tested for an association between these variables. We found more pre-purchase research was carried out by younger respondents and those with a higher education level. Also, more research was associated with feeling more informed about the five welfare needs and knowing to seek help for behaviour from appropriate sources. Overall, the study found several novel and significant results worthy of note and further exploration but did not find any strong connections between the variables.

It is common practice in both randomized and quasi-experiments to adjust for baseline characteristics when estimating the average effect of an intervention. The inclusion of a pre-test, for example, can reduce both the standard error of this estimate and-in non-randomized designs-its bias. At the same time, it is also standard to report the effect of an intervention in standardized effect size units, thereby making it comparable to other interventions and studies. Curiously, the estimation of this effect size, including covariate adjustment, has received little attention. In this article, we provide a framework for defining effect sizes in designs with a pre-test (e.g., difference-in-differences and analysis of covariance) and propose estimators of those effect sizes. The estimators and approximations to their sampling distributions are evaluated using a simulation study and then demonstrated using an example from published data., (© 2023 British Psychological Society.)

Meta-analysts often ask a yes-or-no question: Is there an intervention effect or not? This traditional, all-or-nothing thinking stands in contrast with current best practice in meta-analysis, which calls for a heterogeneity-attuned approach (i.e., focused on the extent to which effects vary across procedures, participant groups, or contexts). This heterogeneity-attuned approach allows researchers to understand where effects are weaker or stronger and reveals mechanisms. The current article builds on a rare opportunity to compare two recent meta-analyses that examined the same literature (growth mindset interventions) but used different methods and reached different conclusions. One meta-analysis used a traditional approach (Macnamara and Burgoyne, in press), which aggregated effect sizes for each study before combining them and examined moderators one-by-one by splitting the data into small subgroups. The second meta-analysis (Burnette et al., in press) modeled the variation of effects within studies-across subgroups and outcomes-and applied modern, multi-level meta-regression methods. The former concluded that growth mindset effects are biased, but the latter yielded nuanced conclusions consistent with theoretical predictions. We explain why the practices followed by the latter meta-analysis were more in line with best practices for analyzing large and heterogeneous literatures. Further, an exploratory re-analysis of the data showed that applying the modern, heterogeneity-attuned methods from Burnette et al. (in press) to the dataset employed by Macnamara and Burgoyne (in press) confirmed Burnette et al.'s conclusions; namely, that there was a meaningful, significant effect of growth mindset in focal (at-risk) groups. This article concludes that heterogeneity-attuned meta-analysis is important both for advancing theory and for avoiding the boom-or-bust cycle that plagues too much of psychological science., Competing Interests: Conflict of Interest: We mention a book Mark McDaniel co-authored (Make It Stick) in Table 2. This mention does not promote the book and includes very minimal discussion. We are countering a claim in the article that is the focus of our Commentary.

Background: Assessment is necessary to ensure both attainment and maintenance of competency in gastrointestinal (GI) endoscopy, and this can be accomplished through self-assessment. We conducted a systematic review with meta-analysis to evaluate the accuracy of self-assessment among GI endoscopists., Methods: This was an individual participant data meta-analysis of studies that investigated self-assessment of endoscopic competency. We performed a systematic search of the following databases: Ovid MEDLINE, Ovid EMBASE, Wiley Cochrane CENTRAL, and ProQuest Education Resources Information Center. We included studies if they were primary investigations of self-assessment accuracy in GI endoscopy that used statistical analyses to determine accuracy. We conducted a meta-analysis of studies using a limits of agreement (LoA) approach to meta-analysis of Bland-Altman studies., Results: After removing duplicate entries, we screened 7138 records. After full-text review, we included 16 studies for qualitative analysis and three for meta-analysis. In the meta-analysis, we found that the LoA were wide (-41.0 % to 34.0 %) and beyond the clinically acceptable difference. Subgroup analyses found that both novice and intermediate endoscopists had wide LoA (-45.0 % to 35.1 % and -54.7 % to 46.5 %, respectively) and expert endoscopists had narrow LoA (-14.2 % to 21.4 %)., Conclusions: GI endoscopists are inaccurate in self-assessment of their endoscopic competency. Subgroup analyses demonstrated that novice and intermediate endoscopists were inaccurate, while expert endoscopists have accurate self-assessment. While we advise against the sole use of self-assessment among novice and intermediate endoscopists, expert endoscopists may wish to integrate it into their practice., Competing Interests: S. C. Grover has received research grants and personal fees from AbbVie and Ferring Pharmaceuticals, personal fees from Takeda, education grants from Janssen, and has equity in Volo Healthcare. R. Khan has received research grants from AbbVie and Ferring Pharmaceuticals and research funding from Pendopharm. G. Bradley-Ridout, S. Genis, N. Gimpaya, J. Li, C. Pattni, M. A. Scaffidi, E. Tipton, and C. M. Walsh declare that they have no conflict of interest., (Thieme. All rights reserved.)

Regular exercise at the intensity matching maximal fat oxidation (FAT max ) has been proposed as a key element in both athletes and clinical populations when aiming to enhance the body's ability to oxidize fat. In order to allow a more standardized and tailored training approach, the connection between FAT max and the individual aerobic thresholds (AerT) has been examined. Although recent findings strongly suggest that a relationship exists between these two intensities, correlation alone is not sufficient to confirm that the intensities necessarily coincide and that the error between the two measures is small. Thus, this systematic review and meta-analysis aim to examine the agreement levels between the exercise intensities matching FAT max and AerT by pooling limits of agreement in a function of three parameters: (i) the average difference, (ii) the average within-study variation, and (iii) the variation in bias across studies, and to examine the influence of clinical and methodological inter- and intra-study differences on agreement levels. This study was registered with PROSPERO (CRD42021239351) and ClinicalTrials (NCT03789045). PubMed and Google Scholar were searched for studies examining FAT max and AerT connection. Overall, 12 studies with forty-five effect sizes and a total of 774 subjects fulfilled the inclusion criteria. The ROBIS tool for risk of bias assessment was used to determine the quality of included studies. In conclusion, the overall 95% limits of agreement of the differences between FAT max and AerT exercise intensities were larger than the a priori determined acceptable agreement due to the large variance caused by clinical and methodological differences among the studies. Therefore, we recommend that future studies follow a strict standardization of data collection and analysis of FAT max - and AerT-related outcomes.

Background: Rabbits are popular pets, but research into their welfare is limited. This study analysed the potential association(s) between the provision of suitable housing and owner demographic factors., Methods: Data from 2017, 2018 and 2019 PDSA Animal Wellbeing (PAW) report surveys gave a sample of 1333 UK rabbit owners. Whether the rabbit housing was adequate or inadequate was ascertained by asking owners to indicate images of hutch and run size or indoor environment type that were similar to their own. The owner demographic factors collected included gender, education, household income and deprivation. Chi-squared tests and binary logistic regression (univariable and multivariable) were used to investigate factors associated with adequate/inadequate housing., Results: One-third (31.2%) of rabbits lived in inadequate housing and half were housed alone (51.4%). Male owners were more likely to report providing inadequate housing than females (odds ratio [OR] = 1.795, 95% confidence interval [CI] 1.319-2.441, p < 0.001). Compared to owners over 55 years old, those aged 25-34 years were more likely to house their rabbits inadequately (OR = 2.050, 95% CI 1.286-3.267, p = 0.003). Owners with a household income below average were more likely to report providing inadequate housing compared to those with a household income above average (OR = 1.406, 95% CI 1.025-1.928, p = 0.035)., Conclusion: The findings identify that inadequate rabbit housing is provided by owners of all ages, genders and deprivation levels but highlight some particular owner demographics that could be useful to target if resources are limited., (© 2022 The Authors. Veterinary Record published by John Wiley & Sons Ltd on behalf of British Veterinary Association.)

Background: Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge., Objective: The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits., Methods: We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps., Results: A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively)., Conclusions: Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes., (©Guillaume Chevance, Natalie M Golaszewski, Elizabeth Tipton, Eric B Hekler, Matthew Buman, Gregory J Welk, Kevin Patrick, Job G Godino. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 13.04.2022.)

In prevention science and related fields, large meta-analyses are common, and these analyses often involve dependent effect size estimates. Robust variance estimation (RVE) methods provide a way to include all dependent effect sizes in a single meta-regression model, even when the exact form of the dependence is unknown. RVE uses a working model of the dependence structure, but the two currently available working models are limited to each describing a single type of dependence. Drawing on flexible tools from multilevel and multivariate meta-analysis, this paper describes an expanded range of working models, along with accompanying estimation methods, which offer potential benefits in terms of better capturing the types of data structures that occur in practice and, under some circumstances, improving the efficiency of meta-regression estimates. We describe how the methods can be implemented using existing software (the "metafor" and "clubSandwich" packages for R), illustrate the proposed approach in a meta-analysis of randomized trials on the effects of brief alcohol interventions for adolescents and young adults, and report findings from a simulation study evaluating the performance of the new methods., (© 2021. Society for Prevention Research.)

Pallister-Killian syndrome is an uncommon genetic disorder that has broad developmental and multisystemic effects. While medical complications are widely reported throughout the literature, research on the neurodevelopmental profile has been limited. Case reports make up the majority of the few existing studies regarding the neurodevelopmental phenotype associated with this disorder. The current case report describes a 3-year-old male with Pallister-Killian syndrome (AF), reports the neurodevelopmental evaluation of his unaffected twin brother (MF), and outlines the results of an optical imaging study on both boys. AF presents with severe developmental delays, however, he ambulates with support and engages in conversation using his communication device. Most severely impaired was AF's speech and expressive language, with childhood apraxia of speech (CAS) as a possible explanation for these severe deficits. MF, the sibling, demonstrated neurotypical abilities and often advanced scores for his age. Both subjects completed a functional near-infrared spectroscopy (fNIRS) study, revealing decreased temporal and frontal lobe function in AF and typical functioning in MF. This case report expands on the existing literature on PKS by describing variances in fraternal twin presentation and novel reporting on fNIRS findings in both boys., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Samango-Sprouse, Hamzik, Rosenbaum, Khaksari, Mitchell, Kommareddi, Brooks, Tipton, Sadeghin and Gropman.)

Knowing who to target with certain messages is the prerequisite of efficient public health campaigns during pandemics. Using the COVID-19 pandemic situation, we explored which facets of the society-defined by age, gender, income, and education levels-are the most likely to visit social gatherings and aggravate the spread of a disease. Analyzing the reported behavior of 87,169 individuals from 41 countries, we found that in the majority of the countries, the proportion of social gathering-goers was higher in male than female, younger than older, lower-educated than higher educated, and low-income than high-income subgroups of the populations. However, the data showed noteworthy heterogeneity between the countries warranting against generalizing from one country to another. The analysis also revealed that relative to other demographic factors, income was the strongest predictor of avoidance of social gatherings followed by age, education, and gender. Although the observed strength of these associations was relatively small, we argue that incorporating demographic-based segmentation into public health campaigns can increase the efficiency of campaigns with an important caveat: the exploration of these associations needs to be done on a country level before using the information to target populations in behavior change interventions., (© 2022. The Author(s).)

Wellness in the Schools (WITS) is a national non-profit organization partnering with public schools to provide healthy, scratch cooked, less processed meals (called an Alternative Menu), and active recess. This study examined the effects of WITS programming on school lunch consumption, including fruit and vegetable intake, in second and third grade students in New York City public schools serving a high proportion of students from low-income households. The intervention was evaluated with a quasi-experimental, controlled design with 14 elementary schools (7 that had initiated WITS programming in fall 2015 and were designated as intervention schools, and 7 matched Control schools). School lunch consumption was assessed by anonymous observation using the System of Observational Cafeteria Assessment of Foods Eaten (SOCAFE) tool in the fall of 2015 (Time 0, early intervention) and the spring of 2016 (Time 1) and 2017 (Time 2). There were no baseline data. Data were also collected on the types of entrées served in the months of October, January, and April during the two school years of the study. Across time points, and relative to students in the Control schools, students in WITS schools ate more fruits and vegetables (units = cups): Time 0: Control 0.18 vs. WITS 0.28; Time 1: Control 0.25 vs. WITS 0.31; and Time 2: Control 0.19 vs. WITS 0.27; p < 0.001. They also had more fruits and vegetables (cups) on their trays, which included more vegetables from the salad bar. However, students in the WITS schools ate fewer entrées (grain and protein) and drank less milk than students in the Control schools. Compared to the Control schools, WITS schools offered more homestyle entrées and fewer finger foods and sandwich entrees, i.e., less processed food. Students in WITS schools who received the Alternative menu and all of the WITS programming at all data collection time points selected and consumed more fruits and vegetables. Replication studies with randomized designs and true baseline data are needed to confirm these findings and to identify avenues for strengthening the effects of the program on other school lunch components.

In the past decade, behavioural science has gained influence in policymaking but suffered a crisis of confidence in the replicability of its findings. Here, we describe a nascent heterogeneity revolution that we believe these twin historical trends have triggered. This revolution will be defined by the recognition that most treatment effects are heterogeneous, so the variation in effect estimates across studies that defines the replication crisis is to be expected as long as heterogeneous effects are studied without a systematic approach to sampling and moderation. When studied systematically, heterogeneity can be leveraged to build more complete theories of causal mechanism that could inform nuanced and dependable guidance to policymakers. We recommend investment in shared research infrastructure to make it feasible to study behavioural interventions in heterogeneous and generalizable samples, and suggest low-cost steps researchers can take immediately to avoid being misled by heterogeneity and begin to learn from it instead., (© 2021. Springer Nature Limited.)

Background: The Five Welfare Needs in UK animal welfare legislation underpin a legal duty of care and are an animal welfare assessment framework. Health and welfare problems arise when these needs are unmet. The veterinary professions work with others to address these problems, but there is no publicly funded U.K. companion animal welfare surveillance to identify priorities, or promote and monitor change., Methods: The veterinary charity, the People's Dispensary for Sick Animals (PDSA), together with the market research organisation, YouGov, has undertaken a longitudinal nationwide survey, assessing whether the U.K's pet dogs, cats and rabbits are having their Five Welfare Needs met. Data from nationally representative samples of pet-owning adults, drawn from YouGov's online survey panel, have been used to produce the PDSA Animal Wellbeing (PAW) Report annually since 2011., Results: Examples are given of how the PAW Report has been used to monitor trends in animal welfare problems, drive collaborative behaviour change campaigns, create evidence-based funding applications and inspire innovation in veterinary practice., Conclusion: The PAW Report has contributed to closing a gap in national companion animal welfare surveillance. When governments rely on non-governmental organisations to assist with animal welfare surveillance, reliable sources such as the PAW Report can inform research, policy and legislation., (© 2021 The Authors. Veterinary Record published by John Wiley & Sons Ltd on behalf of British Veterinary Association.)

Zero-heat-flux thermometers provide clinicians with the ability to continuously and non-invasively monitor body temperature. These devices are increasingly being used to substitute for more invasive core temperature measurements during surgery and in critical care. The aim of this review was to determine the accuracy and precision of zero-heat-flux temperature measurements from the 3M™ Bair Hugger™ Temperature Monitoring System. Medline and EMBASE were searched for studies that reported on a measurement of core or peripheral temperature that coincided with a measurement from the zero-heat-flux device. Study selection and quality assessment was performed independently using the Revised Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2). The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach was used to summarize the strength of the evidence. Pooled estimates of the mean bias and limits of agreement with outer 95% confidence intervals (population limits of agreement) were calculated. Sixteen studies were included. The primary meta-analysis of zero-heat-flux versus core temperature consisted of 22 comparisons from 16 individual studies. Data from 952 participants with 314,137 paired measurements were included. The pooled estimate for the mean bias was 0.03 °C. Population limits of agreement, which take into consideration the between-study heterogeneity and sampling error, were wide, spanning from - 0.93 to 0.98 °C. The GRADE evidence quality rating was downgraded to moderate due to concerns about study limitations. Population limits of agreement for the sensitivity analysis restricted to studies rated as having low risk of bias across all the domains of the QUADAS-2 were similar to the primary analysis. The range of uncertainty in the accuracy of a thermometer should be taken into account when using this device to inform clinical decision-making. Clinicians should therefore consider the potential that a temperature measurement from a 3M™ Bair Hugger™ Temperature Monitoring System could be as much as 1 °C higher or lower than core temperature. Use of this device may not be appropriate in situations where a difference in temperature of less than 1 °C is important to detect.

Background: Veterinary animal welfare advocacy can be undertaken at individual, community, national and international levels. The People's Dispensary for Sick Animals (PDSA), a veterinary charity with 48 Pet Hospitals UK-wide, created a consultative staff network to put an explicit organisational focus on animal welfare-focused veterinary practice., Methods: PDSA created a national internal committee-a Pet Wellbeing Task Force-composed of veterinary staff representatives. Together with recruited hospital-based Champions who serve as a focus for animal welfare and ethics within their clinical teams, the resulting staff network has described a vision of animal welfare and ethics within companion animal veterinary practice, with accompanying practice-level actions. These actions have formed the basis for national clinical audit, repeated three times since 2013., Results: The audit, alongside targeted interventions, has driven organisational change (eg, new policies), led to measurable improvements in pet wellbeing (eg, improved pain assessment and management) and stimulated collaborative practice-based research with universities., Conclusion: A dedicated staff network has facilitated organisation-wide communication on animal welfare and ethics; offered a safe space to raise and discuss animal welfare and ethical issues; and fostered leadership, by working towards model veterinary practice with respect to animal welfare and ethics, with benefits for pet patients, staff and the wider veterinary and veterinary nursing professions., Competing Interests: Competing interests: None declared., (© British Veterinary Association 2020. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.)

Background: Seizures are a morbid complication of intracerebral hemorrhage (ICH) and increase the risk for herniation, status epilepticus, and worse patient outcomes. Prophylactic levetiracetam is administered to approximately 40% of patients with ICH. It is unclear which patients are consciously selected for treatment by physicians. We sought to determine how patients are selected for treatment with prophylactic levetiracetam after ICH., Methods: We administered an adaptive conjoint analysis using decision making software to an NIH Stroke Trials Network Working Group. The adaptive conjoint analysis determines the most influential attributes for making a decision in an iterative, algorithm-driven process. We asked respondents which would most influence a decision to administer prophylactic levetiracetam. The attributes and their levels were taken from published phenotypes associated with prophylactic seizure medications and the likelihood of seizures after ICH: hematoma location (lobar or basal ganglia), hematoma volume (<=10 mL or >10 mL), level of consciousness (Glasgow Coma Scale 5-12 or Glasgow Coma Scale 13-15), age (<65 or ≥65 years), and race (White or Caucasian or Black/African American). The algorithm terminated when the attributes were ranked from most to least influential., Results: The study sample included 27 respondents who completed the adaptive conjoint analysis out of 42 who responded to the survey with a mean age of 43.4 ± 9.4 years. The attribute with the greatest weight was hematoma location (30%), followed by reduced level of consciousness (24%), hematoma volume (19%), race (14%), and age (13%). Ranks of attributes were different (P < .001)., Conclusions: The decision to administer prophylactic levetiracetam to patients with ICH is driven by lobar hematoma location and depressed level of consciousness. Future research on prophylactic seizure medication could focus on patients most likely to receive it., (Copyright © 2019 Elsevier Inc. All rights reserved.)

A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention-which teaches that intellectual abilities can be developed-improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. Notably, the study identified school contexts that sustained the effects of the growth mindset intervention: the intervention changed grades when peer norms aligned with the messages of the intervention. Confidence in the conclusions of this study comes from independent data collection and processing, pre-registration of analyses, and corroboration of results by a blinded Bayesian analysis.

Students from higher-socioeconomic status (SES) backgrounds show a persistent advantage in academic outcomes over lower-SES students. It is possible that students' beliefs about academic ability, or mindsets, play some role in contributing to these disparities. Data from a recent nationally representative sample of ninth-grade students in U.S. public schools provided evidence that higher SES was associated with fewer fixed beliefs about academic ability (a group difference of .22 standard deviations). Also, there was a negative association between a fixed mindset and grades that was similar regardless of a student's SES. Finally, student mindsets were a significant but small factor in explaining the existing relationship between SES and achievement. Altogether, mindsets appear to be associated with socioeconomic circumstances and academic achievement; however, the vast majority of the existing socioeconomic achievement gap in the U.S. is likely driven by the root causes of inequality.

Having surveyed the history and methods of meta-regression in a previous paper, in this paper, we review which and how meta-regression methods are applied in recent research syntheses. To do so, we reviewed studies published in 2016 across four leading research synthesis journals: Psychological Bulletin, the Journal of Applied Psychology, Review of Educational Research, and the Cochrane Library. We find that the best practices defined in the previous review are rarely carried out in practice. In light of the identified discrepancies, we consider how to move forward, first by identifying areas where further methods development is needed to address persistent problems in the field and second by discussing how to more effectively disseminate points of methodological consensus., (© 2019 John Wiley & Sons, Ltd.)

At the beginning of the development of meta-analysis, understanding the role of moderators was given the highest priority, with meta-regression provided as a method for achieving this goal. Yet in current practice, meta-regression is not as commonly used as anticipated. This paper seeks to understand this mismatch by reviewing the history of meta-regression methods over the past 40 years. We divide this time span into four periods and examine three types of methodological developments within each period: technical, conceptual, and practical. Our focus is broad and includes development of methods in the fields of education, psychology, and medicine. We conclude the paper with a discussion of five consensus points, as well as open questions and areas of research for the future., (© 2018 John Wiley & Sons, Ltd.)

Background: Transcutaneous carbon dioxide (TcCO 2 ) monitoring is a non-invasive alternative to arterial blood sampling. The aim of this review was to determine the accuracy and precision of TcCO 2 measurements., Methods: Medline and EMBASE (2000-2016) were searched for studies that reported on a measurement of PaCO 2 that coincided with a measurement of TcCO 2 . Study selection and quality assessment (using the revised Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2)) were performed independently. The Grading Quality of Evidence and Strength of Recommendation approach was used to summarise the strength of the body of evidence. Pooled estimates of the mean bias between TcCO 2 and PaCO 2 and limits of agreement with outer 95% CIs (termed population limits of agreement) were calculated., Results: The mean bias was -0.1 mm Hg and the population limits of agreement were -15 to 15 mm Hg for 7021 paired measurements taken from 2817 participants in 73 studies, which was outside of the clinically acceptable range (7.5 mm Hg). The lowest PaCO 2 reported in the studies was 18 mm Hg and the highest was 103 mm Hg. The major sources of inconsistency were sensor location and temperature. The population limits of agreement were within the clinically acceptable range across 3974 paired measurements from 1786 participants in 44 studies that applied the sensor to the earlobe using the TOSCA and Sentec devices (-6 to 6 mm Hg)., Conclusion: There are substantial differences between TcCO 2 and PaCO 2 depending on the context in which this technology is used. TcCO 2 sensors should preferentially be applied to the earlobe and users should consider setting the temperature of the sensor higher than 42°C when monitoring at other sites., Systematic Review Registration Number: PROSPERO; CRD42017057450., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Assess impact of school lunch environmental factors on fruit and vegetable (F&V) consumption in second and third grade students., Design: Cross-sectional observations in 1 school year., Participants: Students from 14 elementary schools in 4 New York City boroughs (n = 877 student-tray observations)., Main Outcome Measure(s): Dependent variables were F&V consumption collected by visual observation. Independent variables included school lunch environmental factors, and individual-level and school-level demographics., Analysis: Hierarchical linear modeling was used with F&V consumption as the outcome variable, and relevant independent variables included in each model., Results: Slicing or precutting of fruits and having lunch after recess were positively associated (P < .05) with .163- and .080-cup higher fruit consumption across all students, respectively. Preplating of vegetables on lunch trays, having 2 or more vegetable options, and having lunch after recess were positively associated (P < .05) with .024-, .009-, and .007-cup higher vegetable consumption across all students, respectively., Conclusions and Implications: Although there was a small increase in intake, results of the study support that some school lunch environmental factors affect children's F&V consumption, with some factors leading to more impactful increases than others. Slicing of fruits seems most promising in leading to greater fruit consumption and should be further tested., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

The ubiquity of video games in today's society has led to significant interest in their impact on the brain and behavior and in the possibility of harnessing games for good. The present meta-analyses focus on one specific game genre that has been of particular interest to the scientific community-action video games, and cover the period 2000-2015. To assess the long-lasting impact of action video game play on various domains of cognition, we first consider cross-sectional studies that inform us about the cognitive profile of habitual action video game players, and document a positive average effect of about half a standard deviation (g = 0.55). We then turn to long-term intervention studies that inform us about the possibility of causally inducing changes in cognition via playing action video games, and show a smaller average effect of a third of a standard deviation (g = 0.34). Because only intervention studies using other commercially available video game genres as controls were included, this latter result highlights the fact that not all games equally impact cognition. Moderator analyses indicated that action video game play robustly enhances the domains of top-down attention and spatial cognition, with encouraging signs for perception. Publication bias remains, however, a threat with average effects in the published literature estimated to be 30% larger than in the full literature. As a result, we encourage the field to conduct larger cohort studies and more intervention studies, especially those with more than 30 hours of training. (PsycINFO Database Record, ((c) 2018 APA, all rights reserved).)

Bland-Altman method comparison studies are common in the medical sciences and are used to compare a new measure to a gold-standard (often costlier or more invasive) measure. The distribution of these differences is summarized by two statistics, the 'bias' and standard deviation, and these measures are combined to provide estimates of the limits of agreement (LoA). When these LoA are within the bounds of clinically insignificant differences, the new non-invasive measure is preferred. Very often, multiple Bland-Altman studies have been conducted comparing the same two measures, and random-effects meta-analysis provides a means to pool these estimates. We provide a framework for the meta-analysis of Bland-Altman studies, including methods for estimating the LoA and measures of uncertainty (i.e., confidence intervals). Importantly, these LoA are likely to be wider than those typically reported in Bland-Altman meta-analyses. Frequently, Bland-Altman studies report results based on repeated measures designs but do not properly adjust for this design in the analysis. Meta-analyses of Bland-Altman studies frequently exclude these studies for this reason. We provide a meta-analytic approach that allows inclusion of estimates from these studies. This includes adjustments to the estimate of the standard deviation and a method for pooling the estimates based upon robust variance estimation. An example is included based on a previously published meta-analysis. Copyright © 2017 John Wiley & Sons, Ltd., (Copyright © 2017 John Wiley & Sons, Ltd.)

Background: Policy makers and researchers are frequently interested in understanding how effective a particular intervention may be for a specific population. One approach is to assess the degree of similarity between the sample in an experiment and the population. Another approach is to combine information from the experiment and the population to estimate the population average treatment effect (PATE)., Method: Several methods for assessing the similarity between a sample and population currently exist as well as methods estimating the PATE. In this article, we investigate properties of six of these methods and statistics in the small sample sizes common in education research (i.e., 10-70 sites), evaluating the utility of rules of thumb developed from observational studies in the generalization case., Result: In small random samples, large differences between the sample and population can arise simply by chance and many of the statistics commonly used in generalization are a function of both sample size and the number of covariates being compared. The rules of thumb developed in observational studies (which are commonly applied in generalization) are much too conservative given the small sample sizes found in generalization., Conclusion: This article implies that sharp inferences to large populations from small experiments are difficult even with probability sampling. Features of random samples should be kept in mind when evaluating the extent to which results from experiments conducted on nonrandom samples might generalize.

Background: Large-scale randomized experiments are important for determining how policy interventions change average outcomes. Researchers have begun developing methods to improve the external validity of these experiments. One new approach is a balanced sampling method for site selection, which does not require random sampling and takes into account the practicalities of site recruitment including high nonresponse., Method: The goal of balanced sampling is to develop a strategic sample selection plan that results in a sample that is compositionally similar to a well-defined inference population. To do so, a population frame is created and then divided into strata, which "focuses" recruiters on specific subpopulations. Units within these strata are then ranked, thus identifying "replacements" similar to sites that can be recruited when the ideal site refuses to participate in the experiment., Result: In this article, we consider how a balanced sample strategic site selection method might be implemented in a welfare policy evaluation., Conclusion: We find that simply developing a population frame can be challenging, with three possible and reasonable options arising in the welfare policy arena. Using relevant study-specific contextual variables, we craft a recruitment plan that considers nonresponse.

Background: Results from clinical trials have shown that sugar-sweetened beverages (SSBs) lead to increased body mass index (BMI) and obesity. This relationship has yet to be explored in observational data for nonclinical populations of adults., Objective: To compare adults who drank 4+ SSBs daily to those who drank 0 in the population of adults in New York City, and to better understand adult risk factors associated with higher daily SSB consumption and BMI., Design: Secondary analysis of cross-sectional data using propensity score matching., Participants/setting: The 2009 New York City Community Health Survey (N=9,934) was used., Main Outcome Measure: BMI., Statistical Analyses: For each participant who consumed 4+ SSBs daily, propensity score matching identified matched comparisons who did not drink any SSBs. BMI in unadjusted and matched pairs was tested using t tests. A post hoc analysis compared features of those likely to drink SSBs and those not likely to drink SSBs., Results: In unmatched analyses, participants who consumed 4+ SSBs daily (n=475) had higher BMI than those who consumed 0 SSBs (n=3,818; BMI difference=1.4±0.29; t value=4.81; P<0.001); however, when compared with similar participants using nearest neighbor with replacement matching (n=1,062), the difference between those who consumed 4+ SSBs daily and those who consumed none decreased (BMI difference=0.37±0.36; t value=1.01; P=0.32). Analyses also indicated that those likely to drink SSBs and those unlikely to drink SSBs differed in several important characteristics, including sex, age, race, ethnicity, socioeconomic status, education, diet, and exercise., Conclusions: The data preclude strong causal conclusions about the role of SSB in obesity. However, our results suggest that there is a subset of participants demographically and behaviorally similar with higher BMI regardless of their self-reported SSB intake. In addition to targeting SSBs, public health policies and programs should identify and address other modifiable aspects of this profile and tailor approaches to the groups identified to be most affected by high BMI., (Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Childhood obesity is a complex, worldwide problem. Significant resources are invested in its prevention, and high-quality evaluations of these efforts are important. Conducting trials in school settings is complicated, making process evaluations useful for explaining results. Intervention fidelity has been demonstrated to influence outcomes, but others have suggested that other aspects of implementation, including participant responsiveness, should be examined more systematically. During Food, Health & Choices (FHC), a school-based childhood obesity prevention trial designed to test a curriculum and wellness policy taught by trained FHC instructors to fifth grade students in 20 schools during 2012-2013, we assessed relationships among facilitator behaviors (i.e., fidelity and teacher interest); participant behaviors (i.e., student satisfaction and recall); and program outcomes (i.e., energy balance-related behaviors) using hierarchical linear models, controlling for student, class, and school characteristics. We found positive relationships between student satisfaction and recall and program outcomes, but not fidelity and program outcomes. We also found relationships between teacher interest and fidelity when teachers participated in implementation. Finally, we found a significant interaction between fidelity and satisfaction on behavioral outcomes. These findings suggest that individual students in the same class responded differently to the same intervention. They also suggest the importance of teacher buy-in for successful intervention implementation. Future studies should examine how facilitator and participant behaviors together are related to both outcomes and implementation. Assessing multiple aspects of implementation using models that account for contextual influences on behavioral outcomes is an important step forward for prevention intervention process evaluations., Competing Interests: Compliance with Ethical Standards Disclosure of potential conflicts of interest: The authors state they have no conflict of interest.

Objective: Sample size and statistical power calculation should consider clustering effects when schools are the unit of randomization in intervention studies. The objective of the current study was to investigate how student outcomes are clustered within schools in an obesity prevention trial., Method: Baseline data from the Food, Health & Choices project were used. Participants were 9- to 13-year-old students enrolled in 20 New York City public schools (n= 1,387). Body mass index (BMI) was calculated based on measures of height and weight, and body fat percentage was measured with a Tanita® body composition analyzer (Model SC-331s). Energy balance-related behaviors were self-reported with a frequency questionnaire. To examine the cluster effects, intraclass correlation coefficients (ICCs) were calculated as school variance over total variance for outcome variables. School-level covariates, percentage students eligible for free and reduced-price lunch, percentage Black or Hispanic, and English language learners were added in the model to examine ICC changes., Results: The ICCs for obesity indicators are: .026 for BMI-percentile, .031 for BMIz-score, .035 for percentage of overweight students, .037 for body fat percentage, and .041 for absolute BMI. The ICC range for the six energy balance-related behaviors are .008 to .044 for fruit and vegetables, .013 to .055 for physical activity, .031 to .052 for recreational screen time, .013 to .091 for sweetened beverages, .033 to .121 for processed packaged snacks, and .020 to .083 for fast food. When school-level covariates were included in the model, ICC changes varied from -95% to 85%., Conclusions: This is the first study reporting ICCs for obesity-related anthropometric and behavioral outcomes among New York City public schools. The results of the study may aid sample size estimation for future school-based cluster randomized controlled trials in similar urban setting and population. Additionally, identifying school-level covariates that can reduce cluster effects is important when analyzing data., (© 2015 Society for Public Health Education.)

The aim of this investigation was to examine the comparative effectiveness of the new Recline Exercise (RE) and the traditional Head Lift Exercise (Shaker Exercise) on submental muscle activity, tongue strength, and perceived exertion in 40 healthy young adults (mean age = 24.5 years, SD 2.6 years). Both groups participated in a 6-week exercise regimen. Outcome variables evaluated pre- and post-exercise included: duration and peak amplitude of submental muscle activity during swallowing measured via surface electromyography (sEMG); anterior and posterior isometric lingual pressures measured with the Iowa Oral Performance Instrument; and perceived exertion levels measured with the Borg category-ratio scale of perceived exertion. Results indicated no significant pre-post differences within or between groups in swallow duration and peak amplitude. In addition, the RE group demonstrated significant post-treatment increases in anterior and posterior tongue strength [p = 0.009; p < 0.001]; however, these increases were of small magnitude (d = 0.132; d = 0.319). Both groups showed marked improvements in perceived exertion levels [p < 0.001]. Our findings indicate that healthy young adults who perform the RE or the HLE do not have significant swallow duration or amplitude gains, most likely due to the reduced need for such gains in the healthy head/neck musculature for submaximal tasks. Furthermore, the significant lingual strength gains seen with the RE indicate that additional musculature is being engaged during its completion. These results are encouraging; however, future research in older adults and patients with dysphagia with examination of swallowing biomechanics is needed to determine its full potential as a rehabilitative regimen.

Although primary studies often report multiple outcomes, the covariances between these outcomes are rarely reported. This leads to difficulties when combining studies in a meta-analysis. This problem was recently addressed with the introduction of robust variance estimation. This new method enables the estimation of meta-regression models with dependent effect sizes, even when the dependence structure is unknown. Although robust variance estimation has been shown to perform well when the number of studies in the meta-analysis is large, previous simulation studies suggest that the associated tests often have Type I error rates that are much larger than nominal. In this article, I introduce 6 estimators with better small sample properties and study the effectiveness of these estimators via 2 simulation studies. The results of these simulations suggest that the best estimator involves correcting both the residuals and degrees of freedom used in the robust variance estimator. These studies also suggest that the degrees of freedom depend on not only the number of studies but also the type of covariates in the meta-regression. The fact that the degrees of freedom can be small, even when the number of studies is large, suggests that these small-sample corrections should be used more generally. I conclude with an example comparing the results of a meta-regression with robust variance estimation with the results from the corrected estimator., ((c) 2015 APA, all rights reserved).)

This report is the first case of delayed interval twin delivery in which the first infant and mother survived without major morbidity following transport to another facility. In addition, this case is only the second report of asynchronous delivery in which both twins survived and neither suffered any major morbidity. A 30-year-old G5P1031 African American female with a diamniotic/dichorionic twin pregnancy presented to U.S. Naval Hospital Okinawa, Japan, at 22 + 5 weeks due to vaginal bleeding. At 23 + 2 weeks, Twin A was born secondary to advanced cervical dilation. Twin A's birth weight was 650 g with APGAR scores of 6 (1 min) and 7 (5 min). Following delivery of Twin A, Placenta A was left in utero with high ligation of the umbilical cord. Due to a scheduled hospital move, the mother and Twin A were transported to the new facility at Camp Foster. Three weeks later, Twin B was delivered at 26 + 4 weeks. Twin B's birth weight was 930 g with APGAR scores of 3 (1 min) and 7 (5 min). Both twins were discharged without IVH, PVL, ROP, or CLD. This case demonstrates the possibility of transporting both the mother and surviving infant A to a higher level of care prior to delivery of subsequent fetuses.

Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates., (Copyright © 2013 John Wiley & Sons, Ltd.)

Dependent effect size estimates are a common problem in meta-analysis. Recently, a robust variance estimation method was introduced that can be used whenever effect sizes in a meta-analysis are not independent. This problem arises, for example, when effect sizes are nested or when multiple measures are collected on the same individuals. In this paper, we investigate the robustness of this method in small samples when the effect size of interest is the risk difference, log risk ratio, or log odds ratio. This simulation study examines the accuracy of 95% confidence intervals constructed using the robust variance estimator across a large variety of parameter values. We report results for both estimations of the mean effect (intercept) and of a slope. The results indicate that the robust variance estimator performs well even when the number of studies is as small as 10, although coverage is generally less than nominal in the slope estimation case. Throughout, an example based on a meta-analysis of cognitive behavior therapy is used for motivation. Copyright © 2013 John Wiley & Sons, Ltd., (Copyright © 2013 John Wiley & Sons, Ltd.)

Background: An important question in the design of experiments is how to ensure that the findings from the experiment are generalizable to a larger population. This concern with generalizability is particularly important when treatment effects are heterogeneous and when selecting units into the experiment using random sampling is not possible-two conditions commonly met in large-scale educational experiments., Method: This article introduces a model-based balanced-sampling framework for improving generalizations, with a focus on developing methods that are robust to model misspecification. Additionally, the article provides a new method for sample selection within this framework: First units in an inference population are divided into relatively homogenous strata using cluster analysis, and then the sample is selected using distance rankings., Result: In order to demonstrate and evaluate the method, a reanalysis of a completed experiment is conducted. This example compares samples selected using the new method with the actual sample used in the experiment. Results indicate that even under high nonresponse, balance is better on most covariates and that fewer coverage errors result., Conclusion: The article concludes with a discussion of additional benefits and limitations of the method.

Having good spatial skills strongly predicts achievement and attainment in science, technology, engineering, and mathematics fields (e.g., Shea, Lubinski, & Benbow, 2001; Wai, Lubinski, & Benbow, 2009). Improving spatial skills is therefore of both theoretical and practical importance. To determine whether and to what extent training and experience can improve these skills, we meta-analyzed 217 research studies investigating the magnitude, moderators, durability, and generalizability of training on spatial skills. After eliminating outliers, the average effect size (Hedges's g) for training relative to control was 0.47 (SE = 0.04). Training effects were stable and were not affected by delays between training and posttesting. Training also transferred to other spatial tasks that were not directly trained. We analyzed the effects of several moderators, including the presence and type of control groups, sex, age, and type of training. Additionally, we included a theoretically motivated typology of spatial skills that emphasizes 2 dimensions: intrinsic versus extrinsic and static versus dynamic (Newcombe & Shipley, in press). Finally, we consider the potential educational and policy implications of directly training spatial skills. Considered together, the results suggest that spatially enriched education could pay substantial dividends in increasing participation in mathematics, science, and engineering., (© 2013 American Psychological Association)

Conventional meta-analytic techniques rely on the assumption that effect size estimates from different studies are independent and have sampling distributions with known conditional variances. The independence assumption is violated when studies produce several estimates based on the same individuals or there are clusters of studies that are not independent (such as those carried out by the same investigator or laboratory). This paper provides an estimator of the covariance matrix of meta-regression coefficients that are applicable when there are clusters of internally correlated estimates. It makes no assumptions about the specific form of the sampling distributions of the effect sizes, nor does it require knowledge of the covariance structure of the dependent estimates. Moreover, this paper demonstrates that the meta-regression coefficients are consistent and asymptotically normally distributed and that the robust variance estimator is valid even when the covariates are random. The theory is asymptotic in the number of studies, but simulations suggest that the theory may yield accurate results with as few as 20-40 studies. Copyright © 2010 John Wiley & Sons, Ltd., (Copyright © 2010 John Wiley & Sons, Ltd.)

To obtain a better understanding of the behavior of "non-professional" costs in a medical practice, the authors analyzed the expenses of a 19-doctor practice. The analysis revealed that 80 percent of these expenses were fixed costs. Fixed costs, as opposed to variable costs, remain static in total but vary on a per unit basis as volume changes. Organizations with high fixed cost must maximize capacity to achieve profitability. Thus, the relationship among volume, capacity, cost and profit must be understood by medical practices negotiating rates for service units.