Assessment of the Effects of Physiotherapy on Back Care and Prevention of Non-Specific Low Back Pain in Children and Adolescents: A Systematic Review and Meta-Analysis.

Non-specific low back pain (NSLBP) in children and adolescents has increased in recent years, and the evidence of the physiotherapy interventions in back care needs to be updated. Our main goal was to quantify the effects of preventive physiotherapy interventions on improving behavior and knowledge related to back care and prevention of NSLBP in children and adolescents. Based on two previous meta-analyses, Cochrane Library, MEDLINE, PEDro, Web of Science, LILACS, IBECS, PsycINFO, and IME databases and several journals were searched. Two researchers independently extracted data and assessed the risk of bias in the studies using the RoB2 tool. Data were described according to PRISMA guidelines. A total of 24 studies (28 reports) were included. In the posttest, the behavior variable obtained an overall effect size of d+ = 1.48 (95%CI: 0.40 to 2.56), and the knowledge variable obtained an effect size of d+ = 1.41 (95%CI: 1.05 to 1.76). Physiotherapy has demonstrated beneficial impacts on behavior and knowledge concerning back care and to prevent NSLBP in children and adolescents. Interventions focusing on postural hygiene and exercise should be preferred, especially those that are shorter in number of weeks, more intense, and incorporate as many intervention hours as possible.

A systematic review and network meta-analysis on the effectiveness of exercise-based interventions for reducing the injury incidence in youth team-sport players. Part 2: an analysis by movement patterns.

The objectives of this network meta-analysis were: (a) to estimate and compare the pooled effects of some injury prevention programs (IPPs) whose exercise-based components were categorized using a movement pattern-specific taxonomy on reducing overall and some specific body regions (lower extremity, thigh, knee, and ankle) injury incidences in youth team sport athletes and (b) to explore the individual effects of these components on the injury incidence rates (IIRs) previously mentioned. Searches were performed in PubMed, Web of Science, SPORTDiscus, and Cochrane Library. Eligible criteria were: exercise-based interventions comprised of exercises involving athletic motor skill competencies and evaluated against a control group, overall IIRs were reported, and youth (≤19 years old) team sport players. For the current analysis, a taxonomy based on movement patterns was employed for exercise component identification (upper body pushing and pulling; lower body concentric and eccentric; core; mechanics; acceleration; and lower body stability). Pooled effects were calculated by frequentist random effects pairwise and network meta-analyses. Nineteen studies were included. Most of the IPPs exhibit risk reduction when compared to their control groups on overall, lower extremity, and ankle injuries. Interventions comprised of lower body concentric and eccentric, core, mechanics, and lower body stability exercises were the most effective measures for reducing these injuries. None of the IPPs demonstrated to be effective for reducing thigh injuries, and contradictory results were found for knee injuries. Individual analysis at component level revealed that the lower body (bilateral and unilateral, concentric, and eccentric) component was the only one associated with a significant reduction on overall injuries. Indirect evidence suggests that interventions incorporating lower body concentric and eccentric, core, mechanics, and lower body stability exercises might be the most effective for reducing overall, lower extremity, and ankle injuries in youth team sports.

The categorization of exercise components based on the movement patterns might, a priori, be considered a criterion more closely associated with the injury phenomenon.Lower body concentric and eccentric, core, mechanics, and lower body stability exercises should be incorporated to any training program aimed at minimizing the risk of injury in youth.The ineffectiveness of interventions on the reduction of thigh injuries reveals the need for reconsideration of injury prevention strategies.

Transparency in Cognitive Training Meta-analyses: A Meta-review.

Meta-analyses often present flexibility regarding their inclusion criteria, outcomes of interest, statistical analyses, and assessments of the primary studies. For this reason, it is necessary to transparently report all the information that could impact the results. In this meta-review, we aimed to assess the transparency of meta-analyses that examined the benefits of cognitive training, given the ongoing controversy that exists in this field. Ninety-seven meta-analytic reviews were included, which examined a wide range of populations with different clinical conditions and ages. Regarding the reporting, information about the search of the studies, screening procedure, or data collection was detailed by most reviews. However, authors usually failed to report other aspects such as the specific meta-analytic parameters, the formula used to compute the effect sizes, or the data from primary studies that were used to compute the effect sizes. Although some of these practices have improved over the years, others remained the same. Moreover, examining the eligibility criteria of the reviews revealed a great heterogeneity in aspects such as the training duration, age cut-offs, or study designs that were considered. Preregistered meta-analyses often specified poorly how they would deal with the multiplicity of data or assess publication bias in their protocols, and some contained non-disclosed deviations in their eligibility criteria or outcomes of interests. The findings shown here, although they do not question the benefits of cognitive training, illustrate important aspects that future reviews must consider.

Obesity and overweight as risk factors for low back pain in children and adolescents: a meta-analysis.

BACKGROUND: Childhood obesity and overweight are associated with musculoskeletal pain, but the association between low back pain (LBP) and overweight/obesity in this population needs clarification. The objective of this meta-analysis is to ascertain the relationship between LBP and obesity/overweight in children and adolescents. METHODS: Various databases and specialized journals were queried from inception to October 2022. Encompassed were all studies examining the association between overweight or obesity and LBP among participants aged 6 to 18 years. The ROBINS-E tool was employed to assess bias. Random-effects models were used to pool results across studies, with location-scale models used to search for moderator variables where evidence of heterogeneity was found. RESULTS: In total, 34 studies were incorporated. Four studies had a low risk of bias, while the remaining studies had some concerns. Nine studies evinced an association between overweight and LBP, in contrast to normal weight, yielding an OR of 1.13 (95% CI 1.10-1.16) and no heterogeneity. Eight studies demonstrated a similar association between obesity and LBP compared to normal weight, with an OR of 1.27 (95% CI 1.20-1.34) and no heterogeneity. Ten studies established an association between overweight/obesity and LBP compared to normal weight, yielding an OR of 1.18 (95% CI 1.14-1.23) and no heterogeneity. Finally, nineteen studies showcased an association between body mass index (BMI) and LBP, with an OR of 1.19 (95% CI 1.03-1.39) with evidence of heterogeneity. For this last analysis, we compared the mean BMI in groups and transformed results to log OR, and then retransformed to OR. CONCLUSION: Overweight and obesity may be risk factors for LBP in children and adolescents. The association between LBP and obesity appears to be stronger than with overweight. However, the analysis revealed considerable heterogeneity and risk of bias across studies.

Florida Obsessive-Compulsive Inventory and Children's Florida Obsessive Compulsive Inventory: A reliability generalization meta-analysis.

BACKGROUND: The Florida Obsessive Compulsive Inventory (FOCI) and its pediatric version, the Children's Florida Obsessive Compulsive Inventory (C-FOCI), are instruments for evaluating obsessive-compulsive symptomatology. METHOD: A reliability generalization meta-analysis was conducted to estimate an average reliability of the scores and to identify study characteristics that explained the heterogeneity among scores. Using Kuder-Richardson 20 (KR-20) and Cronbach's α, a total of 23 and 20 independent samples were included in the meta-analysis for the FOCI and C-FOCI. RESULTS: We found an average KR-20 of 0.826 for the FOCI's Symptom Checklist and an α of 0.882 FOCI's Symptom Severity. An average KR-20 of 0.740 was found for the C-FOCI's Symptom Checklist, while an average α of 0.794 was found for the C-FOCI's Symptom Severity. Moderator analyses showed that the source of the coefficients (i.e., whether they were reported by the authors of the primary study or estimated by the meta-analysts) was an important variable for the FOCI Symptom Severity, and that the focus of the study (i.e., whether it was psychometric or applied) and the sample size were relevant for the C-FOCI Symptom Checklist. CONCLUSIONS: Considering that the FOCI and C-FOCI are scales characterized by their brevity and ease of use, and the reliabilities obtained here, both scales are well suited for screening purposes.

Effectiveness of healthy lifestyle-based interventions in lung cancer survivors: a systematic review and meta-analysis.

PURPOSE: To assess the effectiveness of healthy lifestyle-based interventions in lung cancer survivors. METHODS: We performed a literature search using PubMed, Web of Science, and Science Direct (last search March 2022). Quality assessment and risk of bias were assessed using the Downs and Black scale and the Cochrane tool. A systematic review and meta-analysis of randomized controlled trials were performed. We included controlled trials testing the effect of healthy lifestyle-based interventions in lung cancer survivors versus a control intervention where lung cancer patients had no treatment, were receiving the usual care, or had not an active role in the intervention. The data were pooled and a meta-analysis was completed for quality of life, psychological distress, and cancer-related symptoms. RESULTS: We selected 14 studies, which included 1519 patients with lung cancer. The treatment status of these patients was heterogeneous. Healthy lifestyle programs were applied isolated or in combination with usual care in most of the studies. The components of the healthy lifestyle programs were also heterogeneous. Results showed significant differences in favor of healthy lifestyle-based interventions in comparison to the control group for quality of life (p = 0.01), psychological distress (p = 0.05), and cancer-related symptoms (p = 0.03). CONCLUSIONS: The findings indicated a beneficial effect of healthy lifestyle-based interventions for improving quality of life, psychological distress, and cancer-related symptoms in lung cancer patients. However, this review could not show any conclusion about the better treatment moment to apply healthy lifestyle-based interventions. REVIEW REGISTRATION: PROSPERO Identifier: CRD42021292152. REVIEW REGISTRATION DATE: 19/12/2021.

Location-scale models for meta-analysis.

Heterogeneity is commonplace in meta-analysis. When heterogeneity is found, researchers often aim to identify predictors that account for at least part of such heterogeneity by using mixed-effects meta-regression models. Another potentially relevant goal is to focus on the amount of heterogeneity as a function of one or more predictors, but this cannot be examined with standard random- and mixed-effects models, which assume a constant (i.e., homoscedastic) value for the heterogeneity variance component across studies. In this paper, we describe a location-scale model for meta-analysis as an extension of the standard random- and mixed-effects models that not only allows an examination of whether predictors are related to the size of the outcomes (i.e., their location), but also the amount of heterogeneity (i.e., their scale). We present estimation methods for such a location-scale model through maximum and restricted maximum likelihood approaches, as well as methods for inference and suggestions for visualization. We also provide an implementation via the metafor package for R that makes this model readily available to researchers. Location-scale models can provide a useful tool to researchers interested in heterogeneity in meta-analysis, with the potential to enhance the scope of research questions in the field of evidence synthesis.

Effectiveness of physiotherapy interventions for back care and the prevention of non-specific low back pain in children and adolescents: a systematic review and meta-analysis.

BACKGROUND: Non-specific low back pain in children and adolescents has increased in recent years. The purpose of this study was to upgrade the evidence of the most effective preventive physiotherapy interventions to improve back care in children and adolescents. METHODS: The study settings were children or adolescents aged 18 years or younger. Data were obtained from the Cochrane Library, MEDLINE, PEDro, Web of Science, LILACS, IBECS, and PsycINFO databases and the specialized journals BMJ and Spine. The included studies were published between May 2012 and May 2020. Controlled trials on children and adolescents who received preventive physiotherapy for back care were considered. Data on all the variables gathered in each individual study were extracted by two authors separately. Two authors assessed risk of bias of included studies using the RoB2 and quality of the body of evidence using the GRADE methodology. Data were described according to PRISMA guidelines. To calculate the effect size, a standardized mean difference "d" was used and a random-effects model was applied for the following outcome variables: behaviour, knowledge, trunk flexion muscle endurance, trunk extension muscle endurance, hamstring flexibility and posture. RESULTS: Twenty studies were finally included. The most common physiotherapy interventions were exercise, postural hygiene and physical activity. The mean age of the total sample was 11.79 years. When comparing the change from baseline to end of intervention in treatment and control groups, the following overall effect estimates were obtained: behaviour d+ = 1.19 (95% CI: 0.62 and 1.76), knowledge d+ = 1.84 (0.58 and 3.09), trunk flexion endurance d+ = 0.65 (-0.02 and 1.33), trunk extension endurance d+ = 0.71 (0.38 and 1.03), posture d+ = 0.65 (0.24 and 1.07) and hamstrings flexibility d+ = 0.46 (0.36 and 0.56). At follow-up, the measurement of the behaviour variable was between 1 and 12 months, with an effect size of d+ = 1.00 (0.37 and 1.63), whereas the knowledge variable obtained an effect size of d+ = 2.08 (-0.85 and 5.02) at 3 months of follow-up. CONCLUSIONS: Recent studies provide strong support for the use of physiotherapy in the improvement of back care and prevention of non-specific low back pain in children and adolescents. Based on GRADE methodology, we found that the evidence was from very low to moderate quality and interventions involving physical exercise, postural hygiene and physical activity should be preferred.

A meta-review of transparency and reproducibility-related reporting practices in published meta-analyses on clinical psychological interventions (2000-2020).

Meta-analysis is a powerful and important tool to synthesize the literature about a research topic. Like other kinds of research, meta-analyses must be reproducible to be compliant with the principles of the scientific method. Furthermore, reproducible meta-analyses can be easily updated with new data and reanalysed applying new and more refined analysis techniques. We attempted to empirically assess the prevalence of transparency and reproducibility-related reporting practices in published meta-analyses from clinical psychology by examining a random sample of 100 meta-analyses. Our purpose was to identify the key points that could be improved, with the aim of providing some recommendations for carrying out reproducible meta-analyses. We conducted a meta-review of meta-analyses of psychological interventions published between 2000 and 2020. We searched PubMed, PsycInfo and Web of Science databases. A structured coding form to assess transparency indicators was created based on previous studies and existing meta-analysis guidelines. We found major issues concerning: completely reproducible search procedures report, specification of the exact method to compute effect sizes, choice of weighting factors and estimators, lack of availability of the raw statistics used to compute the effect size and of interoperability of available data, and practically total absence of analysis script code sharing. Based on our findings, we conclude with recommendations intended to improve the transparency, openness, and reproducibility-related reporting practices of meta-analyses in clinical psychology and related areas.

A Reliability Generalization Meta-analysis of the Padua Inventory-Revised (PI-R).

Background/Objective: The Padua Inventory-Revised (PI-R) is a widely applied instrument to measure obsessive-compulsive symptoms in clinical and nonclinical samples. We conducted a reliability generalization meta-analysis on the PI-R. Method: An exhaustive literature search yielded 118 empirical studies that had applied the PI-R, from which 30 studies (33 samples) reported an original reliability estimate. Results: Assuming a random-effects model, the average internal consistency reliability (Cronbach's alpha) was .92 (95% CI [.91, .93]) for the total scores, and ranged from .74 to .89 for the subscales. Assuming mixed-effects models, moderator analyses showed a positive statistically significant association between the standard deviation of the total scores and the reliability coefficients (p = .002; R2  = .38). Conclusions: In terms of reliability, the PI-R scale was found to be adequate for both research and clinical purposes, although exhibiting large heterogeneity across studies. Future empirical studies using the PI-R should be required to provide at least one reliability estimate based on their own data.

Antecedentes/Objetivo: El Padua Inventory-Revised (PI-R) es un instrumento ampliamente utilizado para medir los síntomas obsesivo-compulsivos en muestras clínicas y no clínicas. Llevamos a cabo un meta-análisis de generalización de la fiabilidad del PI-R. Método: Una búsqueda exhaustiva de la literatura arrojó 118 estudios empíricos que habían aplicado el PI-R, de los cuales 30 estudios (33 muestras) reportaron una estimación propia de la fiabilidad. Resultados: Asumiendo un modelo de efectos aleatorios, la fiabilidad en términos de consistencia interna promedio (alfa de Cronbach) fue de 0,92 (IC del 95% [0,91, 0,93]) para las puntuaciones totales, y osciló entre 0,74 y 0,89 para las subescalas. Asumiendo modelos de efectos mixtos, los análisis de moderadores mostraron una relación positiva estadísticamente significativa entre la desviación típica de las puntuaciones totales y los coeficientes de fiabilidad (p = 0,002; R2  = 0,38). Conclusiones: En términos de fiabilidad, se encontró que el PI-R es adecuado tanto para fines clínicos como de investigación, aunque con una alta heterogeneidad entre los estudios. Es necesario que los estudios empíricos futuros que apliquen el PI-R proporcionen al menos una estimación de la fiabilidad basada en sus propios datos.

Compositional and structural analysis of engineered stones and inorganic particles in silicotic nodules of exposed workers.

BACKGROUND: Engineered stone silicosis is an emerging disease in many countries worldwide produced by the inhalation of respirable dust of engineered stone. This silicosis has a high incidence among young workers, with a short latency period and greater aggressiveness than silicosis caused by natural materials. Although the silica content is very high and this is the key factor, it has been postulated that other constituents in engineered stones can influence the aggressiveness of the disease. Different samples of engineered stone countertops (fabricated by workers during the years prior to their diagnoses), as well as seven lung samples from exposed patients, were analyzed by multiple techniques. RESULTS: The different countertops were composed of SiO2 in percentages between 87.9 and 99.6%, with variable relationships of quartz and cristobalite depending on the sample. The most abundant metals were Al, Na, Fe, Ca and Ti. The most frequent volatile organic compounds were styrene, toluene and m-xylene, and among the polycyclic aromatic hydrocarbons, phenanthrene and naphthalene were detected in all samples. Patients were all males, between 26 and 46 years-old (average age: 36) at the moment of the diagnosis. They were exposed to the engineered stone an average time of 14 years. At diagnosis, only one patient had progressive massive fibrosis. After a follow-up period of 8 ± 3 years, four patients presented progressive massive fibrosis. Samples obtained from lung biopsies most frequently showed well or ill-defined nodules, composed of histiocytic cells and fibroblasts without central hyalinization. All tissue samples showed high proportion of Si and Al at the center of the nodules, becoming sparser at the periphery. Al to Si content ratios turned out to be higher than 1 in two of the studied cases. Correlation between Si and Al was very high (r = 0.93). CONCLUSION: Some of the volatile organic compounds, polycyclic aromatic hydrocarbons and metals detected in the studied countertop samples have been described as causative of lung inflammation and respiratory disease. Among inorganic constituents, aluminum has been a relevant component within the silicotic nodule, reaching atomic concentrations even higher than silicon in some cases. Such concentrations, both for silicon and aluminum showed a decreasing tendency from the center of the nodule towards its frontier.

Improving the reporting quality of reliability generalization meta-analyses: The REGEMA checklist.

Reliability generalization (RG) is a meta-analytic approach that aims to characterize how reliability estimates from the same test vary across different applications of the instrument. With this purpose RG meta-analyses typically focus on a particular test and intend to obtain an overall reliability of test scores and to investigate how the composition and variability of the samples affect reliability. Although several guidelines have been proposed in the meta-analytic literature to help authors improve the reporting quality of meta-analyses, none of them were devised for RG meta-analyses. The purpose of this investigation was to develop REGEMA (REliability GEneralization Meta-Analysis), a 30-item checklist (plus a flow chart) adapted to the specific issues that the reporting of an RG meta-analysis must take into account. Based on previous checklists and guidelines proposed in the meta-analytic arena, a first version was elaborated by applying the nominal group methodology. The resulting instrument was submitted to a list of independent meta-analysis experts and, after discussion, the final version of the REGEMA checklist was reached. In a pilot study, four pairs of coders applied REGEMA to a random sample of 40 RG meta-analyses in Psychology, and results showed satisfactory inter-coder reliability. REGEMA can be used by: (a) meta-analysts conducting or reporting an RG meta-analysis and aiming to improve its reporting quality; (b) consumers of RG meta-analyses who want to make informed critical appraisals of their reporting quality, and (c) reviewers and editors of journals who are considering submissions where an RG meta-analysis was reported for potential publication.

Cost-Effectiveness of Different Formats for Delivery of Cognitive Behavioral Therapy for Depression: A Systematic Review Based Economic Model.

OBJECTIVES: Cognitive behavioral therapy (CBT) is an effective treatment for depression. Different CBT delivery formats (face-to-face [F2F], multimedia, and hybrid) and intensities have been used to expand access to the treatment. The aim of this study is to estimate the long-term cost-effectiveness of different CBT delivery modes. METHODS: A decision-analytic model was developed to evaluate the cost-effectiveness of different CBT delivery modes and variations in intensity in comparison with treatment as usual (TAU). The model covered an average treatment period of 4 months with a 5-year follow-up period. The model was populated using a systematic review of randomized controlled trials and various sources from the literature. RESULTS: Incremental cost-effectiveness ratios of treatments compared with the next best option after excluding all the dominated and extended dominated options are: £209/quality-adjusted life year (QALY) for 6 (sessions) × 30 (minutes) F2F-CBT versus TAU; £4 453/QALY for 8 × 30 F2F versus 6 × 30 F2F; £12 216/QALY for 8 × 60 F2F versus 8 × 30 F2F; and £43 072/QALY for 16 × 60 F2F versus 8 × 60 F2F. The treatment with the highest net monetary benefit for thresholds of £20 000 to £30 000/QALY was 8 × 30 F2F-CBT. Probabilistic sensitivity analysis illustrated 6 × 30 F2F-CBT had the highest probability (32.8%) of being cost-effective at £20 000/QALY; 16 × 60 F2F-CBT had the highest probability (31.0%) at £30 000/QALY. CONCLUSIONS: All CBT delivery modes on top of TAU were found to be more cost-effective than TAU alone. Four F2F-CBT options (6 × 30, 8 × 30, 8 × 60, 16 × 60) are on the cost-effectiveness frontier. F2F-CBT with intensities of 6 × 30 and 16 × 60 had the highest probabilities of being cost-effective. The results, however, should be interpreted with caution owing to the high level of uncertainty.

The Padua Inventory-Washington State University Revision of Obsessions and Compulsions: A Reliability Generalization Meta-Analysis.

The Padua Inventory-Washington State University Revision (PI-WSUR) is a frequently used test to assess obsessive-compulsive symptoms in screening and clinical contexts. A reliability generalization meta-analysis was carried out to estimate the average reliability of the PI-WSUR scores and its subscales and to search for characteristics of the studies that can explain the heterogeneity among reliability coefficients. A total of 124 independent samples reported some coefficient alpha or test-retest correlation with the data at hand for the PI-WSUR scores. The average internal consistency reliability of the PI-WSUR total scores was .929 (95% CI [.922, .936]), and for the subscales, the means ranged from .792 to .900. The test-retest reliability for PI-WSUR total scores was .767 (95% CI [.700, .820]), with the subscales ranging from .540 to .790. Moderator analyses revealed a positive relationship between the standard deviation of PI-WSUR total scores and alpha coefficients, as well as higher reliability estimates for the original version of the test and for studies from North America. The reliability induction rate for the PI-WSUR was 53.7%. Regarding reliability, the PI-WSUR ranks among the best scales for assessing obsessive-compulsive symptoms. Internal consistency reliability was excellent for the PI-WSUR total score and good for the subscales.

Estimation of an overall standardized mean difference in random-effects meta-analysis if the distribution of random effects departs from normal.

The random-effects model, applied in most meta-analyses nowadays, typically assumes normality of the distribution of the effect parameters. The purpose of this study was to examine the performance of various random-effects methods (standard method, Hartung's method, profile likelihood method, and bootstrapping) for computing an average effect size estimate and a confidence interval (CI) around it, when the normality assumption is not met. For comparison purposes, we also included the fixed-effect model. We manipulated a wide range of conditions, including conditions with some degree of departure from the normality assumption, using Monte Carlo simulation. To simulate realistic scenarios, we chose the manipulated conditions from a systematic review of meta-analyses on the effectiveness of psychological treatments. We compared the performance of the different methods in terms of bias and mean squared error of the average effect estimators, empirical coverage probability and width of the CIs, and variability of the standard errors. Our results suggest that random-effects methods are largely robust to departures from normality, with Hartung's profile likelihood methods yielding the best performance under suboptimal conditions.

A methodological review of meta-analyses of the effectiveness of clinical psychology treatments.

This article presents a methodological review of 54 meta-analyses of the effectiveness of clinical psychological treatments, using standardized mean differences as the effect size index. We statistically analyzed the distribution of the number of studies of the meta-analyses, the distribution of the sample sizes in the studies of each meta-analysis, the distribution of the effect sizes in each of the meta-analyses, the distribution of the between-studies variance values, and the Pearson correlations between effect size and sample size in each meta-analysis. The results are presented as a function of the type of standardized mean difference: posttest standardized mean difference, standardized mean change from pretest to posttest, and standardized mean change difference between groups. These findings will help researchers design future Monte Carlo and theoretical studies on the performance of meta-analytic procedures, based on the manipulation of realistic model assumptions and parameters of the meta-analyses. Furthermore, the analysis of the distribution of the mean effect sizes through the meta-analyses provides a specific guide for the interpretation of the clinical significance of the different types of standardized mean differences within the field of the evaluation of clinical psychological interventions.

A Reliability Generalization Meta-Analysis of the Padua Inventory of Obsessions and Compulsions.

The Padua Inventory (PI) of obsessions and compulsions is one of the most usually applied tests to assess obsessive-compulsive symptomatology in research contexts as well as for clinical and screening purposes. A reliability generalization meta-analysis was accomplished to estimate the average reliability of the PI scores and to search for characteristics of the samples and studies that can explain the variability among reliability estimates. An exhaustive literature search enabled us to select 39 studies (53 independent samples) that reported alpha and/or test-retest coefficients with the data at hand for the PI total score and subscales. An excellent average coefficient alpha was found for the PI total score (M = .935; 95%CI = .922-.949) and for Impaired Mental Control subscale (M = .911; 95%CI = .897-.924), being good for Contamination (M = .861; 95%CI = .841-.882) and Checking (M = .880; 95%CI = .856-.903), and fair for Urges and Worries (M = .783; 95%CI = .745-.822). The average test-retest reliability for PI total score was also satisfactory (M = .835; 95%CI = .782-.877). Moderator analyses showed larger coefficients alpha for larger standard deviation of the PI total scores (p = .0005; R 2 = .46), for adapted versions of the test (p = .002; R 2 = .32), and for samples composed of clinical participants (p = .066; R 2 = .10). The practical implications of these results are discussed as well as the need for researchers to report reliability estimates with the data at hand.

Assessing meta-regression methods for examining moderator relationships with dependent effect sizes: A Monte Carlo simulation.

Dependent effect sizes are ubiquitous in meta-analysis. Using Monte Carlo simulation, we compared the performance of 2 methods for meta-regression with dependent effect sizes-robust variance estimation (RVE) and 3-level modeling-with the standard meta-analytic method for independent effect sizes. We further compared bias-reduced linearization and jackknife estimators as small-sample adjustments for RVE and Wald-type and likelihood ratio tests for 3-level models. The bias in the slope estimates, width of the confidence intervals around those estimates, and empirical type I error and statistical power rates of the hypothesis tests from these different methods were compared for mixed-effects meta-regression analysis with one moderator either at the study or at the effect size level. All methods yielded nearly unbiased slope estimates under most scenarios, but as expected, the standard method ignoring dependency provided inflated type I error rates when testing the significance of the moderators. Robust variance estimation methods yielded not only the best results in terms of type I error rate but also the widest confidence intervals and the lowest power rates, especially when using the jackknife adjustments. Three-level models showed a promising performance with a moderate to large number of studies, especially with the likelihood ratio test, and yielded narrower confidence intervals around the slope and higher power rates than those obtained with the RVE approach. All methods performed better when the moderator was at the effect size level, the number of studies was moderate to large, and the between-studies variance was small. Our results can help meta-analysts deal with dependency in their data.