What do meta-analysts need in primary studies? Guidelines and the SEMI checklist for facilitating cumulative knowledge.

Meta-analysis is often recognized as the highest level of evidence due to its notable advantages. Therefore, ensuring the precision of its findings is of utmost importance. Insufficient reporting in primary studies poses challenges for meta-analysts, hindering study identification, effect size estimation, and meta-regression analyses. This manuscript provides concise guidelines for the comprehensive reporting of qualitative and quantitative aspects in primary studies. Adhering to these guidelines may help researchers enhance the quality of their studies and increase their eligibility for inclusion in future research syntheses, thereby enhancing research synthesis quality. Recommendations include incorporating relevant terms in titles and abstracts to facilitate study retrieval and reporting sufficient data for effect size calculation. Additionally, a new checklist is introduced to help applied researchers thoroughly report various aspects of their studies.

Exploring the role of OXTR gene methylation in attachment development: A longitudinal study.

The current study explored longitudinally whether oxytocin receptor gene methylation (OXTRm) changes moderated the association between parental sensitivity changes and children's attachment changes over three waves. Six hundred six Flemish children (10-12 years, 42.8%-44.8% boys) completed attachment measures and provided salivary OXTRm data on seven CpG sites. Their parents reported their sensitive parenting. Results suggest that OXTRm changes hardly link to attachment (in)security changes after the age of 10. Some support was found for interaction effects between parental sensitivity changes and OXTRm changes on attachment changes over time. Effects suggest that for children with increased OXTRm in the promotor region and decreased methylation in the inhibitor region over time, increased parental sensitivity was associated with increased secure attachment and decreased insecure attachment over time.

The effect of unpredictability on the perception of pain: a systematic review and meta-analysis.

ABSTRACT: Despite being widely assumed, the worsening impact of unpredictability on pain perception remains unclear because of conflicting empirical evidence, and a lack of systematic integration of past research findings. To fill this gap, we conducted a systematic review and meta-analysis focusing on the effect of unpredictability on pain perception. We also conducted meta-regression analyses to examine the moderating effect of several moderators associated with pain and unpredictability: stimulus duration, calibrated stimulus pain intensity, pain intensity expectation, controllability, anticipation delay, state and trait negative affectivity, sex/gender and age of the participants, type of unpredictability (intensity, onset, duration, location), and method of pain induction (thermal, electrical, mechanical pressure, mechanical distention). We included 73 experimental studies with adult volunteers manipulating the (un)predictability of painful stimuli and measuring perceived pain intensity and pain unpleasantness in predictable and unpredictable contexts. Because there are insufficient studies with patients, we focused on healthy volunteers. Our results did not reveal any effect of unpredictability on pain perception. However, several significant moderators were found, ie, targeted stimulus pain intensity, expected pain intensity, and state negative affectivity. Trait negative affectivity and uncontrollability showed no significant effect, presumably because of the low number of included studies. Thus, further investigation is necessary to clearly determine their role in unpredictable pain perception.

Exploring burnout among preschool teachers in rural China: a job demands-resources model perspective.

Rural preschool teachers are increasingly experiencing job burnout, which could lead to their intention to leave and negatively impact education quality. This research explored the prevalence of job burnout among preschool teachers in rural China. It further investigated the potential influence of job-related characteristics on their levels of burnout. This study surveyed 10,581 preschool teachers across 34 counties in 18 provinces in China, utilizing multilevel structural equation models to analyze the situation and factors influencing job burnout. The findings indicate that the situation regarding job burnout among preschool teachers is not encouraging, particularly in the western areas and independent public kindergartens. Job resources were found to be associated with a reduction in burnout, while job demands had the opposite effect. The findings also revealed that job demands served as a mediating variable between job resources and job burnout. Moreover, the results also showed that reduced job burnout among preschool teachers was related to teacher cooperation, decision making, kindergarten resources and salary. On the other hand, role commitments, business issues, and classroom management were associated with increased burnout among preschool teachers. Furthermore, the impact of demands and resources on burnout was found to be intensified by kindergarten variables. To address the issue of burnout, it is essential to recognize the diversity and heterogeneity of kindergartens and take specific measures to reduce work demands while providing adequate and specific resources. Attention should be given to diversity and integration to ensure a positive work environment that can effectively prevent job burnout among preschool teachers.

Perceived Parental Support and Psychological Control, DNA Methylation, and Loneliness: Longitudinal Associations Across Early Adolescence.

A broad range of factors have been associated with the development of adolescent loneliness. In the family context, a lack of parental support and high levels of parental psychological control have systematically been linked to loneliness. On the biological level, DNA methylation (which is an epigenetic process that suppresses gene expression) is believed to play a role in the development of loneliness. Specifically, high levels of DNA methylation in genes that play an important role in the functioning of the human stress response system are believed to elevate the risk of loneliness. Moreover, DNA methylation levels in these stress-related genes can be influenced by stressful environmental factors, suggesting a potential mediating role of DNA methylation in the association between parenting behaviors and loneliness. The current 3-year longitudinal study is the first study to examine the potential bidirectional longitudinal associations between loneliness, DNA methylation in stress-related genes, and both perceived parental support and psychological control. Furthermore, we explored the potential mediating role of DNA methylation in stress-related genes in the associations between perceived parenting and loneliness. The sample comprised 622 early adolescents (55% girls, Mage T1 = 10.77 years, SDage T1 = 0.48) who were followed from Grade 5 to 7. Parental support, psychological control, and loneliness were assessed annually by adolescent self-report questionnaires and DNA methylation was determined from saliva samples. Cross-Lagged Panel Models (CLPM) revealed that higher levels of loneliness predicted lower perceived parental support and higher perceived psychological control over time, as well as higher DNA methylation in some stress-related genes, that is, the glucocorticoid receptor gene (NR3C1) and the brain-derived neurotrophic factor (BDNF). In addition, higher NR3C1 methylation was predictive of lower perceived parental support and higher psychological control over time. No evidence was found for a mediating role of DNA methylation. Overall, our longitudinal findings challenge the current focus on DNA methylation and parenting behaviors as risk factors for adolescent loneliness. Instead, they suggest that the less considered direction of effects, which implies that loneliness predicts DNA methylation and aspects of parenting such as support and psychological control, should receive greater attention in future research.

A Multilevel Meta-analysis of Single-Case Research on Interventions for Internalizing Disorders in Children and Adolescents.

The effectiveness of interventions for internalizing disorders in children and adolescents was studied using a review and meta-analysis of published single-case research. Databases and other resources were searched for quantitative single-case studies in youth with anxiety, depressive, and posttraumatic stress disorders. Raw data from individual cases were aggregated and analyzed by means of multilevel meta-analytic models. Outcome variables were symptom severity assessed across baseline and treatment phases of the studies, and diagnostic status at post- and follow-up treatment. Single-case studies were rated for quality. We identified 71 studies including 321 cases (Mage = 10.66 years; 55% female). The mean quality of the studies was rated as below average, although there were considerable differences between the studies. Overall, positive within-person changes during the treatment phase in comparison to the baseline phase were found. In addition, positive changes in the diagnostic status were observed at post- and follow-up treatment. Yet high variability in treatment effects was found between cases and studies. This meta-analysis harvests the knowledge from published single-case research in youth-internalizing disorders and illustrates how within-person information from single-case studies can be summarized to explore the generalizability of the results from this type of research. The results emphasize the importance of keeping account of individual variability in providing and investigating youth interventions.

Cumulative family stress and externalizing problems: Secure base script knowledge as a protective factor.

The current study examined whether secure base script knowledge can buffer against higher concurrent externalizing problems and against relative increases in externalizing problems associated with cumulative family stress. We conducted a one-year longitudinal study with two waves between 2017 and 2019 in which 272 Dutch-speaking Western European children from Flanders (47.8% boys, M age = 10.20 , SD age = 0.60 ) participated. Secure base script knowledge was associated with lower concurrent externalizing problems (f2  = 0.03). High levels of secure base script knowledge also buffered against relative increases in externalizing problems associated with cumulative family risk (f2  = 0.02). These findings suggest that secure base script knowledge can mitigate the negative effects of a stressful family environment on externalizing problems.

Comparing the prediction performance of item response theory and machine learning methods on item responses for educational assessments.

To obtain more accurate and robust feedback information from the students' assessment outcomes and to communicate it to students and optimize teaching and learning strategies, educational researchers and practitioners must critically reflect on whether the existing methods of data analytics are capable of retrieving the information provided in the database. This study compared and contrasted the prediction performance of an item response theory method, particularly the use of an explanatory item response model (EIRM), and six supervised machine learning (ML) methods for predicting students' item responses in educational assessments, considering student- and item-related background information. Each of seven prediction methods was evaluated through cross-validation approaches under three prediction scenarios: (a) unrealized responses of new students to existing items, (b) unrealized responses of existing students to new items, and (c) missing responses of existing students to existing items. The results of a simulation study and two real-life assessment data examples showed that employing student- and item-related background information in addition to the item response data substantially increases the prediction accuracy for new students or items. We also found that the EIRM is as competitive as the best performing ML methods in predicting the student performance outcomes for the educational assessment datasets.

Network meta-analysis in psychology and educational sciences: A systematic review of their characteristics.

Network meta-analysis (NMA) allows the combination of evidence on the effectiveness of several interventions. NMA has mainly been applied in the medical science field, whereas in the domain of psychology and educational sciences its use is less frequent. Consequently, systematic reviews that describe the characteristics of published NMAs are limited to the field of medicine, and nothing is known about the characteristics of NMAs published in the psychology and educational sciences field. However, this information is still relevant for the design of future simulation studies and for detecting good and bad research practices. Thus, this study describes the features of the meta-analytic datasets of NMAs published in the field of psychology and educational sciences, as well as their methodological characteristics, and compares them to those observed in the medical domain. Results show that the number of studies included is larger in NMAs from psychology and educational sciences, the most commonly used effect size is the standardized mean difference (unlike the odds ratio in medicine), the sample size is smaller, more intervention groups are included, and inconsistent effects are observed more often. These results can be used in future simulation studies to generate realistic datasets. Finally, we warn about the poor quality of reporting of some technical aspects of the NMA, such as the statistical model used.

Consistency in Single-Case ABAB Phase Designs: A Systematic Review.

The current article presents a systematic review of consistency in single-case ABAB phase designs. We applied the CONsistency of DAta Patterns (CONDAP) measure to a sample of 460 data sets retrieved from 119 applied studies published over the past 50 years. The main purpose was to (a) identify typical CONDAP values found in published ABAB designs and (b) develop interpretational guidelines for CONDAP to be used for future studies to assess the consistency of data patterns from similar phases. The overall distribution of CONDAP values is right-skewed with several extreme values to the right of the center of the distribution. The B-phase CONDAP values fall within a narrower range than the A-phase CONDAP values. Based on the cumulative distribution of CONDAP values, we offer the following interpretational guidelines in terms of consistency: very high, 0 ≤ CONDAP ≤ 0.5; high, 0.5 < CONDAP ≤ 1; medium, 1 < CONDAP < 1.5; low, 1.5 < CONDAP ≤ 2; very low, CONDAP > 2. We give examples of combining CONDAP benchmarks with visual analysis of single-case ABAB phase designs and conclude that the majority of data patterns (41.2%) in published ABAB phase designs is medium consistent.

Modeling the effect of postgraduate courses on soft skills: a practical approach.

Over the last decade, Higher Education has focused more of its attention toward soft skills compared to traditional technical skills. Nevertheless, there are not many studies concerning the relation between the courses followed within an academic program and the development of soft skills. This work presents a practical approach to model the effects of courses on soft skills proficiency. Multiple Membership Ordinal Logistic Regression models are trained with real data from students of the 2021, 2022, and 2023 cohorts from the general engineering program in a French Higher Education institution. The results show that attending a postgraduate course in average increases the odds of being more proficient in terms of soft skills. Nonetheless, there is considerable variability in the individual effect of courses, which suggest there can be huge differences between courses. Moreover, the data also suggest great dispersion in the students' initial soft skill proficiency.

The effect of a school-based creative expression program on immigrant and refugee children's mental health and classroom social relationships: A cluster randomized trial in elementary school.

This study evaluated the effects of a school-based creative expression program on mental health and classroom social relationships in elementary school children with refugee and nonrefugee migration backgrounds. It was hypothesized that children receiving the intervention would report less externalizing and internalizing problem behaviors, less posttraumatic functioning, and more positive classroom social relationships at posttest than children receiving education as usual, particularly for refugee children. Classes in three multiethnic Belgian elementary schools were randomly assigned to a creative intervention (7 classes, 68 students) or control condition (6 classes, 52 students). All participants (8-12 years old) had a migration background. Almost half (47%) were refugees, 53% were first- to third-generation nonrefugee immigrants. Data collection included pre- and posttest assessment with children, parents, and teachers. Multilevel analysis was used to assess outcomes. Children in the intervention condition rated the classroom climate at posttest more positive than their control peers (d = .33). Children who received the intervention did not show less symptomatic functioning than children in the education-as-usual condition. However, post hoc analysis by baseline severity showed that students with high baseline levels of posttraumatic stress reported less trauma symptoms at posttest in the intervention group than in the control group (d = -.97). This effect was moderated by children's refugee background, indicating a differential effect in which refugee children show more reduction of trauma symptoms as compared to nonrefugee immigrant children. The intervention supported classroom climate and alleviated posttraumatic stress in children with increased posttraumatic symptomatology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Mental health problems in refugee and immigrant primary school children in Flanders, Belgium.

BACKGROUND: European countries face the challenge of promoting refugee and immigrant children's well-being within their host communities, invoking the necessity of adequate mental health assessment. This study aims to contribute to document the psychosocial well-being of primary school refugee and non-refugee immigrant children in Flanders, Belgium. METHOD: A total of 120 children (8-12 years old) with migration backgrounds participated in the study. Through self-report, parent and teacher questionnaires we scrutinized externalizing and internalizing behavioral problems, post-traumatic stress problems, and classroom relationships. RESULTS: Thirty percent of the participants reported high levels of post-traumatic stress; around 25% reported a high or very high prevalence of internalizing and externalizing behavioral problems. Self-reported mental health problems are elevated in comparison to the general population. Refugee children did not report more difficulties than their immigrant peers. In the perception of parents and teachers, respectively 20% and 5% of children showed high or very high amounts of internalizing and externalizing behavioral difficulties. Almost 70% of the participants perceived the class climate as unsafe. CONCLUSIONS: Refugee and immigrant children are at risk for mental health difficulties, and experience classroom dynamics as markedly distressful. School-based intervention might be particularly suited to support these children's psychosocial well-being in resettlement.

Individual differences in environmental sensitivity at physiological and phenotypic level: Two sides of the same coin?

Young adolescents are hypothesized to differ in their environmental sensitivity, at both phenotypic (i.e., Sensory Processing Sensitivity [SPS]) and physiological (i.e., biological stress response) level. This is the first study that investigated whether individual differences in environmental sensitivity at physiological level could be predicted by individual differences at phenotypic level, as measured with the HSC scale. A total of 101 adolescents (Mage = 11.61, SDage = 0.64) participated in a standardized social stress task (i.e., Trier Social Stress Task-Modified version for children and adolescents (TSST-M)). From baseline to the end of recovery, eight cortisol samples were collected, as well as a continuous measure of Autonomic Nervous System activity. Adolescents reported on SPS and on perceived stress before, during, and after TSST-M. As a follow-up analysis, the quality of the environment, the possible overlap with Neuroticism, and several covariates were considered. Multilevel models were used to investigate within- and between-person differences in stress reactivity across different systems. Results indicate significant individual differences in heart rate, heart rate variability, skin conductance, cortisol, and perceived stress in response to the TSST-M. Only for perceived stress significant differences in SPS were observed, with more sensitive individuals perceiving more negative and less positive affect. For environmental quality and the interaction between SPS and Neuroticism results showed higher recovery rates of heart rate in high quality environments and stronger cortisol responses for adolescents scoring high on both SPS and Neuroticism. Potential explanations for these findings and implications for current theorizing on environmental sensitivity are discussed.

Network Meta-Analysis for Single-Case Design Studies: An Illustration.

Single-case designs (SCDs) are used to evaluate the effects of interventions on individual participants. By repeatedly measuring participants under different conditions, SCD studies focus on individual effects rather than on group summaries. The main limitation of SCDs remains its generalisability to wider populations, reducing the relevance of their findings for practice and policy making. With this limitation in mind, methodological developments for synthesising SCD data from different studies that investigate the same research question have intensified in the past decades (e.g. multilevel modelling). However, these techniques are restricted to comparing two interventions at a time and can only incorporate evidence from studies that directly compare the two treatments of interest. These limitations could be addressed by using network meta-analysis that incorporates both direct and indirect evidence to simultaneously compare multiple interventions. Despite its potential, network meta-analytical techniques have yet to be applied to SCD data. Thus, in this paper, we argue that network meta-analysis can be a valuable tool to synthesise SCD data. We demonstrate the use of network meta-analysis in SCD data using a real dataset, and we conclude by reflecting on the challenges that SCD researchers might face when applying network meta-analysis methods to their data.

Multilevel Meta-Analysis of Individual Participant Data of Single-Case Experimental Designs: One-Stage versus Two-Stage Methods.

To conduct a multilevel meta-analysis of multiple single-case experimental design (SCED) studies, the individual participant data (IPD) can be analyzed in one or two stages. In the one-stage approach, a multilevel model is estimated based on the raw data. In the two-stage approach, an effect size is calculated for each participant and these effect sizes and their sampling variances are subsequently combined to estimate a meta-analytic multilevel model. The multilevel model in the two-stage approach has fewer parameters to estimate, in exchange for the reduction of information of the raw data to effect sizes. In this paper we explore how the one-stage and two-stage IPD approaches can be applied in the context of meta-analysis of single-case designs. Both approaches are compared for several single-case designs of increasing complexity. Through a simulation study we show that the two-stage approach obtains better convergence rates for more complex models, but that model estimation does not necessarily converge at a faster speed. The point estimates of the fixed effects are unbiased for both approaches across all models, as such confirming results from methodological research on IPD meta-analysis of group-comparison designs. In light of these results, we discuss the implementation of both methods in R.

Improving the Measurement of Environmental Sensitivity in Children and Adolescents: The Highly Sensitive Child Scale-21 Item Version.

Children differ in their sensitivity to positive and negative environmental influences, which can be measured with the Highly Sensitive Child (HSC) scale. The present study introduces the HSC-21, an adaptation of the original 12 item scale with new items and factor structure that are meant to be more informative than the original ones. The psychometric properties of the HSC-21 were investigated in 1,088 children across Belgium and the Netherlands, including child and mother reports. Results showed evidence for (a) bifactor model with a general sensitivity factor and two specific factors (i.e., Ease of Excitation-Low Sensory Threshold and Aesthetic Sensitivity); (b) (partial) measurement invariance across gender, developmental stage, country, and informants; (c) moderate child-mother agreement; (d) good reliability; (e) normally distributed item scores; and (f) meaningful associations with personality and temperament across both samples. No evidence was found for HSC-21 as a moderator in the relationship between parenting and problem behaviors.

Epigenetics in Families: Covariance between Mother and Child Methylation Patterns.

Theory and research both point at epigenetic processes affecting both parenting behavior and child functioning. However, little is known about the convergence of mother and child's epigenetic patterns in families. Therefore, the current study investigated epigenetic covariance in mother-child dyads' methylation levels regarding four stress-regulation related genes (5HTT, NR3C1, FKBP5, and BDNF). Covariance was tested in a general population sample, consisting of early adolescents (Mage = 11.63, SDage = 2.3) and mothers (N = 160 dyads). Results showed that mother and offspring 5HTT and NR3C1 methylation patterns correlated. Furthermore, when averaged across genes, methylation levels strongly correlated. These findings partially supported that child and parent methylation levels covary. It might be important to consider this covariance to understand maladaptive parent-child relationships.

Who is teaching in Chinese primary schools? A profile of the primary education workforce in Chinese county areas.

A teaching workforce with good quality is a key factor in the process of China's rapid development. Although 76% of Chinese pupils are studying at schools within county areas, a general portray of the corresponding teaching workforce is still not clear. This study presents data from a nationally representative survey of primary education teachers in 35 counties of 18 provinces in China. Findings presented include demographic and professional characteristics, living conditions as well as attitudes towards work. Besides, variations among school locations and geographical regions are also examined. The key findings are the followings: 1) Quality of primary school teachers in county areas has been improved regarding education background; 2) Teaching force in village primary schools has an unbalanced age and gender composition; 3) Out-of-field teaching practice is widespread, especially for minor subjects. 4) Primary school teachers perceived relative low salary and low social status.

Estimating outcome-specific effects in meta-analyses of multiple outcomes: A simulation study.

In meta-analysis, primary studies often include multiple, dependent effect sizes. Several methods address this dependency, such as the multivariate approach, three-level models, and the robust variance estimation (RVE) method. As for today, most simulation studies that explore the performance of these methods have focused on the estimation of the overall effect size. However, researchers are sometimes interested in obtaining separate effect size estimates for different types of outcomes. A recent simulation study (Park & Beretvas, 2019) has compared the performance of the three-level approach and the RVE method in estimating outcome-specific effects when several effect sizes are reported for different types of outcomes within studies. The goal of this paper is to extend that study by incorporating additional simulation conditions and by exploring the performance of additional models, such as the multivariate model, a three-level model that specifies different study-effects for each type of outcome, a three-level model that specifies a common study-effect for all outcomes, and separate three-level models for each type of outcome. Additionally, we also tested whether the a posteriori application of the RV correction improves the standard error estimates and the 95% confidence intervals. Results show that the application of separate three-level models for each type of outcome is the only approach that consistently gives adequate standard error estimates. Also, the a posteriori application of the RV correction results in correct 95% confidence intervals in all models, even if they are misspecified, meaning that Type I error rate is adequate when the RV correction is implemented.