Cardiac vagal control and children's adaptive functioning: a meta-analysis.
TL;DR: A meta-analysis of 44 studies revealed small effect sizes such that greater levels of RSA-W were related to fewer externalizing, internalizing, and cognitive/academic problems, and theoretical/practical implications for the study of cardiac vagal control are discussed.
About: This article is published in Biological Psychology.The article was published on 2013-09-01 and is currently open access. It has received 343 citations till now. The article focuses on the topics: Polyvagal Theory & Vagal tone.
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TL;DR: The historical emergence of neurobiologically-informed dimensional trait models of psychopathology are reviewed, and thinking regarding high frequency heart rate variability (HF-HRV) as a transdiagnostic biomarker of self-regulation and cognitive control is summarized.
546 citations
Cites background from "Cardiac vagal control and children'..."
...attention demanding rather than emotionally evocative (e.g., Dietrich et al., 2007; Graziano and Derefinko, 2013; Obradović et al., 2010)....
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...…sometimes correlates with greater tonic RSA, less RSA withdrawal during assorted lab tasks, or no RSA withdrawal, especially when stimulus conditions are attention demanding rather than emotionally evocative (e.g., Dietrich et al., 2007; Graziano and Derefinko, 2013; Obradović et al., 2010)....
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TL;DR: A series of recommendations for facilitating cross-study comparisons and leveraging multifaceted approaches to studying emotion regulation processes within a developmental psychopathology framework are provided.
Abstract: In response to rapidly growing rates of comorbidity among psychiatric disorders, clinical scientists have become interested in identifying transdiagnostic processes that can help explain dysfunction across diagnostic categories (e.g., Kring & Sloan, 2009). One factor that has received a great deal of attention is that of emotion regulation, namely, the ability to modulate the intensity and/or duration of emotional states (e.g., Cicchetti, Ackerman, & Izard, 1995; Gross, 1998). Recent theoretical and empirical work has begun to emphasize the role that emotion regulation plays in the temporal comorbidity between internalizing and externalizing conditions (e.g., Aldao & De Los Reyes, 2015; De Los Reyes & Aldao, 2015; Drabick & Kendall, 2010; Jarrett & Ollendick, 2008; Patrick & Hajcak, 2016). However, close inspection of this work reveals two very pertinent areas of growth: (a) this literature is characterized by mixed findings that are likely explained, in part, by methodological heterogeneity; and (b) emotion regulation tends to be studied in relatively narrow terms. To address these issues, we provide a series of recommendations for facilitating cross-study comparisons and leveraging multifaceted approaches to studying emotion regulation processes within a developmental psychopathology framework. We hope that our perspective can enhance the organization and growth of this very important area of inquiry, and ultimately result in more effective prevention and treatment programs.
282 citations
Cites background from "Cardiac vagal control and children'..."
...…some studies have shown that reductions in RSA (i.e., vagal withdrawal) in response to stressors reflects an adaptive response (as reviewed in Graziano & Derefinko, 2013), whereas others have found that it is linked to internalizing psychopathology (e.g., Boyce et al., 2001) and that…...
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TL;DR: Central nervous system substrates and autonomic correlates of emotion dysregulation are reviewed and several suggestions for future research are offered.
Abstract: This article reviews central nervous system substrates and autonomic correlates of emotion dysregulation and offers several suggestions for future research. Studies conducted in the last two decades indicate that effective emotion regulation requires efficient top-down, cortically mediated regulation of bottom-up, subcortically mediated individual differences in trait impulsivity and trait anxiety. Without making critical distinctions between highly heritable individual differences in trait impulsivity and trait anxiety, versus less heritable and more socialized deficiencies in emotion regulation, progress in understanding the development of psychopathology among children and adolescents will be hampered. Future research can also be improved by measuring emotion dysregulation across multiple level of analysis, specifying physiological mechanisms through which operant reinforcement shapes emotional lability, improving the internal and external validity of psychophysiological measures, integrating emotion dysregulation into factor analytic and behavioral genetic models of psychopathology, identifying molecular genetic risk for emotion dysregulation, and expanding neuroimaging research on emotion dysregulation among children and adolescents.
251 citations
Cites background from "Cardiac vagal control and children'..."
...…correlated with greater tonic RSA, less RSA withdrawal during lab tasks, or no RSA withdrawal, especially when stimulus conditions are attention demanding and not emotionally evocative (e.g., Dietrich et al., 2007; Graziano & Derefinko, 2013; Obradović, Bush, Stamperdahl, Adler, & Boyce, 2010)....
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TL;DR: A meta-analysis of 77 studies revealed that youth with ADHD have the greatest impairment on ERNL, followed by EREG followed by ECUT, and the association between ADHD and ECUT was significantly weaker among studies that controlled for co-occurring conduct problems.
191 citations
TL;DR: In this article, the authors argue that HRV is neither uniformly nor simply a surrogate for heart period and identify knowledge gaps that remain to be satisfactorily addressed with respect to assumptions underlying existing HRV correction approaches.
Abstract: Metrics of heart period variability are widely used in the behavioral and biomedical sciences, although somewhat confusingly labeled as heart rate variability (HRV). Despite their wide use, HRV metrics are usually analyzed and interpreted without reference to prevailing levels of cardiac chronotropic state (i.e., mean heart rate or mean heart period). This isolated treatment of HRV metrics is nontrivial. All HRV metrics routinely used in the literature exhibit a known and positive relationship with the mean duration of the interval between two beats (heart period): as the heart period increases, so does its variability. This raises the question of whether HRV metrics should be "corrected" for the mean heart period (or its inverse, the heart rate). Here, we outline biological, quantitative, and interpretive issues engendered by this question. We provide arguments that HRV is neither uniformly nor simply a surrogate for heart period. We also identify knowledge gaps that remain to be satisfactorily addressed with respect to assumptions underlying existing HRV correction approaches. In doing so, we aim to stimulate further progress toward the rigorous use and disciplined interpretation of HRV. We close with provisional guidance on HRV reporting that acknowledges the complex interplay between the mean and variability of the heart period.
132 citations
References
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TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.
Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4
Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted?
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …
45,105 citations
TL;DR: It is concluded that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity, and one or both should be presented in publishedMeta-an analyses in preference to the test for heterogeneity.
Abstract: The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity.
25,460 citations
Book•
01 Jan 1985
TL;DR: In this article, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Abstract: Preface. Introduction. Data Sets. Tests of Statistical Significance of Combined Results. Vote-Counting Methods. Estimation of a Single Effect Size: Parametric and Nonparametric Methods. Parametric Estimation of Effect Size from a Series of Experiments. Fitting Parametric Fixed Effect Models to Effect Sizes: Categorical Methods. Fitting Parametric Fixed Effect Models to Effect Sizes: General Linear Models. Random Effects Models for Effect Sizes. Multivariate Models for Effect Sizes. Combining Estimates of Correlation Coefficients. Diagnostic Procedures for Research Synthesis Models. Clustering Estimates of Effect Magnitude. Estimation of Effect Size When Not All Study Outcomes Are Observed. Meta-Analysis in the Physical and Biological Sciences. Appendix. References. Index.
9,769 citations
TL;DR: In this paper, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Abstract: Preface. Introduction. Data Sets. Tests of Statistical Significance of Combined Results. Vote-Counting Methods. Estimation of a Single Effect Size: Parametric and Nonparametric Methods. Parametric Estimation of Effect Size from a Series of Experiments. Fitting Parametric Fixed Effect Models to Effect Sizes: Categorical Methods. Fitting Parametric Fixed Effect Models to Effect Sizes: General Linear Models. Random Effects Models for Effect Sizes. Multivariate Models for Effect Sizes. Combining Estimates of Correlation Coefficients. Diagnostic Procedures for Research Synthesis Models. Clustering Estimates of Effect Magnitude. Estimation of Effect Size When Not All Study Outcomes Are Observed. Meta-Analysis in the Physical and Biological Sciences. Appendix. References. Index.
7,063 citations
TL;DR: A theoretical model that links inhibition to 4 executive neuropsychological functions that appear to depend on it for their effective execution is constructed and finds it to be strongest for deficits in behavioral inhibition, working memory, regulation of motivation, and motor control in those with ADHD.
Abstract: Attention deficit hyperactivity disorder (ADHD) comprises a deficit in behavioral inhibition. A theoretical model is constructed that links inhibition to 4 executive neuropsychological functions that appear to depend on it for their effective execution: (a) working memory, (b) self-regulation of affect-motivation-arousal, (c) internalization of speech, and (d) reconstitution (behavioral analysis and synthesis). Extended to ADHD, the model predicts that ADHD should be associated with secondary impairments in these 4 executive abilities and the motor control they afford. The author reviews evidence for each of these domains of functioning and finds it to be strongest for deficits in behavioral inhibition, working memory, regulation of motivation, and motor control in those with ADHD. Although the model is promising as a potential theory of self-control and ADHD, far more research is required to evaluate its merits and the many predictions it makes about ADHD.
6,958 citations