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Create a scenario of an adolescent of either gender in which you describe the person, the physical changes he or she experiences, and the effect of those changes on his/her sexuality and relationships.

• Describe the culture of the individual in the scenario.
• Explain the influences of culture on the development of adolescence.

Journal of Adolescence 45 (2015) 160e170 Contents lists available at ScienceDirect Journal of Adolescence journal homepage: www.elsevier.com/locate/jado The effects of pubertal timing on externalizing behaviors in adolescence and early adulthood: A meta-analytic review Laura M. Dimler*, Misaki N. Natsuaki University of California, Riverside, CA, United States a r t i c l e i n f o a b s t r a c t Article history: Available online 3 October 2015 Using a meta-analytic approach, this investigation examines the association between early pubertal timing and externalizing behaviors in adolescence and early adulthood. The findings showed that the effect size of early pubertal maturation on externalizing behaviors was r ¼ 0.180. This small, yet significant effect size is consistent with the models of early pubertal maturation in that early maturation is associated with higher levels of externalizing behaviors. Using contrast analyses, we examined three potential moderators of this association: sex, the concurrent versus long-term effect of early puberty, and types of puberty assessments. Neither sex nor type of pubertal timing assessment moderated the effect significantly. However, results indicated that the effect was stronger for studies that measured pubertal timing and externalizing behaviors concurrently rather than longitudinally (i.e., examining prospective effect of pubertal timing on later externalizing behaviors). The findings are discussed in terms of implications for future research. © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved. Keywords: Meta-analysis Pubertal timing Externalizing Moderator Adolescence Early puberty is a risk factor for the development of adolescent psychopathologies, including externalizing behaviors such as classroom disruptions, aggression, delinquency, and social deviancy. Although there have been many literature reviews on this topic (e.g., Ge & Natsuaki, 2009; Graber, 2013; Mendle & Ferrero, 2012; Mendle, Turkheimer, & Emery, 2007; Negriff & Susman, 2011; Rudolph, 2014), no meta-analysis has been conducted to date. Meta-analysis on pubertal timing and externalizing behaviors would help further advance the field for the following reasons. First, while there are many studies that do report a positive association between early puberty and externalizing problems, there are also many studies that do not find early puberty to predict adolescent externalizing behaviors (e.g., Carter, Caldwell, Matusko, Antonucci, & Jackson, 2011; Obeidallah, Brennan, Brooks-Gunn, & Earls, 2004; Stattin, Kerr, & Skoog, 2011). Therefore, quantification of the pubertal timing effect using a systematic meta-analysis would further the literature by providing a general overview of the statistical associations between early pubertal maturation and externalizing behaviors. Second, quantification of the effect size can inform applied science. It can provide clues to the question of whether targeting early maturing youths is an effective and efficient strategy for interventions and prevention of externalizing behaviors. If the effect of early pubertal maturation is found to be robust in the meta-analysis, it is especially alarming because in the context of secular trend of puberty, the age of pubertal onset has been steadily decreasing in both sexes in the last 25 years (Anderson & Must, 2005; Golub et al., 2008; Sørenson et al., 2012). For these reasons, the overarching aim of this study is to fill this critical gap in the literature by conducting a meta-analytic review to further our understanding of the strength of the associations between timing of * Corresponding author. E-mail address: laura.dimler@email.ucr.edu (L.M. Dimler). http://dx.doi.org/10.1016/j.adolescence.2015.07.021 0140-1971/© 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved. L.M. Dimler, M.N. Natsuaki / Journal of Adolescence 45 (2015) 160e170 161 pubertal maturation and externalizing behavior. We do this by analyzing effect sizes and multiple moderators on more than 36,000 adolescents. Although previous studies have shown the association between early pubertal maturation and externalizing behaviors, the strength of this link varies greatly among studies (Ge & Natsuaki, 2009; Ge, Natsuaki, Jin, & Biehl, 2011). In this report, we sought to examine whether the following potential moderators contribute to the mixed results in the literature: sex of the adolescent (Graber, Lewinsohn, Seeley, & Brooks-Gunn, 1997; Najman et al., 2009); whether the researchers assessed a concurrent or long-term effect of pubertal timing (Graber et al., 1997); and types of pubertal timing measurement (BrooksGunn, Warren, Rosso, & Gargiulo, 1987; Dorn & Biro, 2011; Shirtcliff, Dahl, & Pollak, 2009). Thus, an additional aim of this study is to examine whether these potential moderators alter the effect size of pubertal timing on externalizing behaviors. Early puberty and externalizing behaviors It is well documented that adolescents who experience pubertal maturation earlier than their same-age, same-sex peers are more likely to have negative developmental outcomes, including externalizing behaviors and affiliation with deviant peers, especially in adolescence (e.g., Caspi, Lynam, Moffitt, & Silva, 1993; Felson & Haynie, 2002; Ge, Brody, Conger, Simons, & Murry, 2002; Lynne, Graber, Nichols, Brooks-Gunn, & Botvin, 2007; Mensah et al., 2013; Stattin & Magnusson, 1990). For instance, in a longitudinal study with more than 500 young adults, early maturers tended to have significantly higher rates of disruptive behavior disorders (i.e., conduct disorder and oppositional defiant disorder) and antisocial personality traits in early adulthood compared with on-time maturers (Graber, Seeley, Brooks-Gunn, & Lewinsohn, 2004). More recently, Mrug et al. (2014) echo similar results, but add that early pubertal timing, compared to on-time or late pubertal timing, is related to a wide range of externalizing behaviors including delinquency, physical aggression, relational aggression, and nonphysical aggression. Several hypotheses have been put forth to explain this association between early pubertal maturation and externalizing behaviors (see Ge & Natsuaki, 2009 for a review). One possible explanation is that the hormonal changes associated with puberty increases the risk for developing externalizing problems by heightening an adolescent’s novelty-seeking behaviors and other biological systems such as stress reactivity and brain development (Rudolph, 2014). Another hypothesis suggests that the gap between physical and psychological (i.e., cognitive and emotional) maturities places early physical maturers at risk for developing externalizing behaviors. This maturation disparity model asserts that early maturers’ externalizing behaviors are reflections of misalignment of their slow-developing neural and cognitive development and their body’s fastpaced development, lending to a host of social and emotional demands for which the adolescent is not yet cognitively or emotionally equipped (Ge & Natsuaki, 2009; Moffitt, 1993). Another hypothesis proposes that early puberty places an adolescent into a demanding transition that is novel, uncertain, and ambiguous, which may exacerbate pre-existing vulnerabilities including pre-pubertal behavioral problems (Caspi & Moffitt, 1991; Giletta et al., 2015; Graber, 2013; Hamilton et al., 2014; Rudolph, 2014). Lastly, Ge and Natsuaki (2009) outline the contextual amplification hypothesis, which states that an adverse situation (e.g., family conflict, peer challenges) amplifies the effects of the rapid hormonal and biological changes occurring in an adolescent’s body, exacerbating developing psychopathologies. Despite the theoretical elaboration of the aforementioned mechanisms, the empirical literature has not demonstrated the consistent effects of early pubertal maturation. Some studies report significant effect sizes that are rather small (e.g., r ¼ 0.09, Burt, McGue, DeMarte, Krueger, & Iacono, 2006), while other studies have reported larger effects (e.g., r ¼ 0.55, Storvoll & Wichstrøm, 2002). Therefore, because of the theoretical implications and the statistical inconsistencies in the literature, it is important to compute the aggregated effect size across studies, and the variation in effect sizes, if any, that needs to be explained. Moderators of the pubertal timing effect To explain the potential heterogeneity in effect sizes, we focused on three possible moderators: sex of the adolescent, short- vs. long-term effects of pubertal timing, and assessments of pubertal maturation. Sex Sex differences in the effect of pubertal timing is discussed extensively in the domain of internalizing psychopathology; early maturing girls tend to have higher rates of depression, anxiety, and other internalizing symptoms during adolescence and adulthood while the evidence on adolescent boys’ internalizing symptoms and pubertal maturation are mixed €, 2003; Mendle & Ferrero, (Fernandez-Castelao & Kroner-Herwig, 2014; Kaltiala-Heino, Marttunen, Rantanen, & Rimpela 2012; Natsuaki, Biehl, & Ge, 2009). Stronger effects of early maturation in female internalizing symptoms are theorized that features of female pubertal development (e.g., curvy body, breast development, menarche) can elicit social and emotional challenges, and the stress associated with these challenges deplete yet-developed early maturing girls’ coping and resources to deal with the pressures, which in turn can contribute to depression and anxiety (Natsuaki, Samuels, & Leve, 2014). For males, on the other hand, earlier work suggests that features associated with male puberty such as voice change, facial hair, and growth spurt bring social advantages, such that early maturing boys can enjoy potential dominance, power, and leadership in peer relationships (McCabe & Ricciardelli, 2004; Simmons & Blyth, 1987). However, recent empirical research 162 L.M. Dimler, M.N. Natsuaki / Journal of Adolescence 45 (2015) 160e170 advises that this thinking ought to be revised because this early pubertal transition is associated with elevated levels of internalizing psychopathology for young males (Ge, Brody, Conger, & Simons, 2006; Graber, 2013; Mendle & Ferrero, 2012). While existing reviews note that the effect of early maturation on externalizing psychopathology also depends on sex of the child, the literature is not as clear-cut as it is for internalizing symptoms. Although a fairly consistent finding is that early maturing boys have higher levels of externalizing behaviors than late maturing counterparts (Felson & Haynie, 2002; Mendle & Ferrero, 2012; Susman et al., 2007), the results are rather mixed for girls. For example, multiple recent studies on females suggest early menarche does not have an impact on externalizing behaviors in females (e.g., Boden, Fergusson, & Horwood, 2011; Carter et al., 2011), while there seem to be just as many recent studies suggesting that entering into puberty earlier than most peers is a risk factor for future delinquency for girls (e.g., Mendle et al., 2007; Mrug et al., 2014). In attempt to resolve this confusion, the present meta-analysis includes sex as a moderator of the association between early pubertal maturation and externalizing psychopathology. Concurrent vs. longitudinal effect of pubertal timing Another potential moderator of the association between early pubertal timing and externalizing behaviors is the shortversus long-term effect of early puberty. Pubertal timing is associated with externalizing behaviors concurrently, as evidenced by a number of cross-sectional studies (e.g., Flannery, Rowe, & Gulley, 1993; Graber et al., 1997; Sontag, Graber, & Clemans, 2011). However, we have limited knowledge regarding the long-term effect of early puberty. Although there are a comparatively small number of studies that have investigated the long-term effects of early pubertal timing, available evidence suggests that the adverse effect of early maturation is rather short-lived and is contained within the bounds of adolescence (Boden et al., 2011; Natsuaki et al., 2009; Obeidallah et al., 2004). Among studies that have examined this longitudinal effect, there is evidence that early pubertal timing in boys, who were measured once a year for four years, consistently resulted in more externalized hostile feeling in late adolescence than on-time or late-maturing boys (Ge, Conger, & Elder, 2001), but did not result in major psychopathology in adulthood (Graber et al., 2004). Similarly, adult females who were formerly early maturers in adolescence were more likely than formerly on-time maturers to have antisocial behavior and conduct behavior disorders in early adulthood, but not after the age of 21 (Boden et al., 2011; Graber et al., 2004). As such, this quantitative review aims to combine the results of cross-sectional as well as longitudinal studies to examine whether the concurrent vs. longitudinal effect of puberty moderates the strength of the association between early puberty and externalizing behaviors. Pubertal timing assessment The third potential moderator that may explain mixed findings in this area of research concerns the type of pubertal maturation assessments used in each study. Although there are many different and nuanced ways to measure the complex phenomenon of puberty than are outlined in this meta-analysis (e.g., hormone concentrations, bone age, and gonadal ultrasound), we discuss the five most common forms of assessing pubertal timing that are found within the literature of externalizing behaviors (see Dorn & Biro, 2011; Dorn, Dahl, Woodward, & Biro, 2006 for comprehensive reviews on puberty assessment). Conventional measures of puberty in psychological research include the Pubertal Development Scale (PDS; Petersen, Crockett, Richards, & Boxer, 1988), the Tanner Stages (i.e., self-report and/or clinician-report; Marshall & Tanner, 1969, 1970), perceived pubertal timing (i.e., subjective assessment of whether one feels mature earlier than their peers; see Mendle, 2014a), and self-reported age of menarche in females. The PDS is a subjective, noninvasive five-item questionnaire that assesses the status of puberty-related physical development (breast development and menarche for girls; voice change and facial hair for boys; skin change, body hair, and growth spurt for both sexes) at the time of questionnaire administration. Adolescents, parents, and clinicians respond to a four-point scale, indicating how far along the adolescent’s physical maturation has advanced. The Tanner Stages assessment uses an illustrated scale of primary and secondary sex characteristics in which the adolescent, parent, and/or clinician select one of the five pictures that describes the adolescent’s current physical development. Research demonstrates that both the PDS and the Tanner Stages are highly correlated with puberty-related hormones (i.e., dehydroepiandrosterone, testosterone, and estradiol; Shirtcliff et al., 2009), indicating that the subjective measures are valid and practical when hormonal profiling and other biological or objective measures of pubertal timing are unfeasible to attain. The clinician-reported Tanner Stages are known to be more accurate when purposefully isolating an off-time puberty sample (Brooks-Gunn et al., 1987; Dorn et al., 2006; Shirtcliff et al., 2009). To compute pubertal timing scores from the pubertal status scores based on the PDS and/or Tanner Stages, researchers typically either 1) standardize the scores within age and sex to create a continuous measure of pubertal timing; and/or 2) classify the sample into three groups of early, on-time, and late-maturers using the score distribution generated from the given sample (peer-normative comparison). Perceived pubertal timing is another method that assesses an adolescent’s perception of pubertal timing synchrony with peers, usually by asking adolescents if they feel their physical changes are occurring before, at the same time, or after the rest of their peers (Mendle, 2014a). Recently, studies have indicated that adolescents’ subjective assessment of their timing status among their peers may be an important factor that uniquely contributes to externalizing behaviors (Lynne et al., 2007; Storvoll & Wichstrøm, 2002). Mendle (2014a) calls for greater awareness of the importance of the subjective synchrony of pubertal timing within peers as these self-perceptions of feeling ‘different’ from peers may result from thoughts and actions that correspond with the adolescents’ impression of their physical appearance. For example, in the context of externalizing L.M. Dimler, M.N. Natsuaki / Journal of Adolescence 45 (2015) 160e170 163 behaviors, feeling physically ‘different’ from peers may accentuate the desire to be accepted by peers, resulting in adolescents associating with older peers and engaging in “adult-like” behaviors that are not age-appropriate for them (i.e., driving a car at age 14). Lastly, self-reported recall of age at menarche is the most frequently used measure of female pubertal timing because of its ease of accessibility and the fact that menarche is a clearly timed event in a female’s life (Dorn & Biro, 2011). However, this type of measurement has its limitations: menarche occurs late in the pubertal process and is not the most accurate measure of pubertal timing in terms of reliability of self-reported recall, as the reported age of menarche has been shown to vary within longitudinal studies (Dorn et al., 2006). Given the heterogeneity in the assessment of pubertal timing across studies, it may be the case that the strength of observed associations between early pubertal maturation and externalizing behaviors in previous work may depend on the types of pubertal timing measures and the reporter of pubertal timing, but this possibility has never been systematically examined. Previous studies have shown that the potential effect of pubertal timing measurement on an adolescent’s psychopathology differ by continuous and categorical forms of measurement (Negriff, Fung, & Trickett, 2008) and stagenormative and peer-normative forms of measurement (i.e., Cance, Ennett, Morgan-Lopez, & Foshee, 2012), thus, this metaanalysis further expands these studies by examining five types of pubertal timing measures in the context of externalizing psychopathology. Present study The goal of the present study was two-fold: (1) to conduct a meta-analysis on pubertal timing and externalizing behaviors to quantify the magnitude of the pubertal timing effect; and (2) to explore factors that potentially moderate the link between pubertal timing and externalizing psychopathology. Based on the previous literature outlined above, we hypothesized that: (1) early pubertal timing would lead to more externalizing behaviors; (2) the link between pubertal timing and externalizing behaviors would be stronger for boys than for girls; and (3) this association would be stronger when pubertal timing and externalizing behaviors are measured concurrently, as opposed to longitudinally. We did not form specific hypotheses regarding the pubertal timing assessments. This meta-analytic review advances previous literature reviews in two ways. First, meta-analyses compliment theoretical reviews by focusing on effect sizes, providing a statistical tool for describing average effect sizes, and allowing for more powerful methods of evaluating variability of findings across studies and its sources (Rosenthal, 1991). Second, this metaanalysis allows for testing for moderation via contrast analysis. Methods Selection of studies In this study, the operationalization of externalizing behaviors was based on the Diagnostic and Statistical Manual, Fifth Edition (DSM-5) (American Psychiatric Association, 2013). According to the DSM-5, disruptive, impulse control, and conduct disorders include symptoms that involve problems in the self-control of emotions and behaviors. While other disorders in DSM-5 may also involve problems in emotional and/or behavioral regulation (i.e., substance use and risky sexual behaviors), the disorders in this cluster are unique in that these problems are manifested in behaviors that violate the rights of others (e.g. aggression, destruction of property) and/or bring the individual into significant conflict with societal norms or authority figures (American Psychiatric Association, 2013). Peer-reviewed studies were obtained through (a) searching computerized literature in the PsycINFO and Academic Search Complete databases using all combinations of the keywords: adolescent, externalizing, antisocial, aggression, delinquency, conduct disorder, conduct problems, behavior problems, behavior disorder, puberty, pubertal timing, adolescence, menarche, spermarche, and oigarche; (b) going through the authors’ personal collection of pertinent studies on puberty; (c) using the ancestry method by examining references cited in prior reviews and empirical articles; and (d) communicating with those in the field who have conducted research in this specific area. Studies were included in this quantitative review if they met the following criteria: (a) they used a correlational model to assess an association between pubertal timing and externalizing behaviors; (b) they used externalizing behaviors as an outcome variable, predicted from pubertal timing; (c) the studies were available in peer-reviewed English language journals; and (d) the studies reported effect size r or enough statistical information to reconstruct this effect size (i.e., means and standard deviations). The following studies were not included in the meta-analysis: (a) Studies that focus exclusively on risky sexual behaviors (n ¼ 50); (b) studies that assessed only substance/alcohol use (n ¼ 23); and (c) studies that reported odds ratios or relative risk ratios (n ¼ 3), as there is no process of which to reconstitute a reliable effect size r (Rosenthal & Rosnow, 2008; Rosenthal, Rosnow, & Rubin, 2000). Studies with exclusive focus on sexual behaviors and substance use were excluded because these behaviors tend to be measured as their own constructs and have their own validity, as opposed to being nested under externalizing behaviors (e.g., American Psychiatric Association, 2013; Timmermans, van Lier, & Koot, 2008; Winters, Stinchfield, Latimer, & Stone, 2008). Readers who are specifically interested in the effect of pubertal timing and risky sexual behaviors should refer to a recent meta-analysis by Baams, Dubas, Overbeek, and van Aken (2015). 164 L.M. Dimler, M.N. Natsuaki / Journal of Adolescence 45 (2015) 160e170 Because we assessed sex as a potential moderator, we extracted two effect sizes from a study if it reported separate statistical analyses for males and females. Under these criteria, 34 publications consisting of over 36,000 adolescents (N ¼ 36,641) and 40 effect sizes were included in the current investigation. Extraction of information from studies The following information was extracted from each study: sample size, correlation (or regression coefficient), sex of the sample, the type of pubertal timing measurement, the ages of the participants when the pubertal timing and externalizing measures were completed, and the duration of the study. It is important to note that when multiple time points were used to assess for externalizing symptoms (e.g., pubertal timing’s effects on externalizing behavior in the seventh grade, tenth grade, and twelfth grade), the furthest time point from the pubertal timing assessment was used (e.g., in a four-year longitudinal study, the ninth grade puberty assessment and the twelfth grade externalizing assessment would be used). This was done so that the longitudinal effect would be as long-term as possible, within each article’s confines. Coding of moderators This study focused on three moderators: participants’ sex, concurrent vs. long-term effect of pubertal timing, and the type of pubertal timing assessment. Sex was dummy coded with males as the reference group. For concurrent vs. long-term effect of pubertal timing, we dummy coded with concurrent ¼ 1 and long-term ¼ 0. Long-term was defined by a longitudinal design with at least one year between the times at which puberty and externalizing psychopathology were assessed. We identified 16 effect sizes that corresponded with longitudinal studies that met the aforementioned criterion, with an average time interval of 4.6 years (SD ¼ 4.5) between puberty and externalizing behavior assessments. Lastly, pubertal timing measurement was divided into five subgroups: (a) PDS; (b) medical professional-reported Tanner Stages; (c) parent- or self-reported Tanner Stages; (d) perceived pubertal timing; and (e) age of menarche (for female-only samples). Each type of pubertal timing assessment was dummy coded (1 ¼ the measure of interest, 0 ¼ all others). Statistical analyses Effect size calculations The effect size r was the statistical basis for this meta-analysis because r illustrates both the strength and direction of the association between variables (Durlak, 2009; Ozer, 1985; Rosenthal & DiMatteo, 2001; Rosenthal & Rubin, 1982). As noted earlier, studies reporting only odds ratios or relative risk ratios (and did not report descriptive statistics on the dataset) were omitted from the meta-analysis due to difficulty in the reconstituted effect size (Rosenthal & Rosnow, 2008; Rosenthal et al., 2000), unless the corresponding author was available and willing to release the data needed to compute r. For studies reporting effect sizes other than r, the information in the published article was computed into the desired effect size through other information within the article such as group means and standard deviations, Hedge’s g, Cohen’s d, an exact p-value, chi-square, or an F-test with one degree of freedom in the numerator (Rosenthal, 1991; Rosenthal & Rosnow, 2008; Rosenthal et al., 2000). If a study did not report an exact p-value for a significant result, the one-tailed p-value was conservatively assumed to be 0.025. Effect sizes were transformed via Fisher’s Zr transformation, and back-transformed to r’s for intuitive interpretability. Four effect sizes from the same sample in separate papers (Negriff et al., 2008; Negriff, Ji, & Trickett, 2011; Negriff, Susman, & Trickett, 2011; Negriff & Trickett, 2010) were ensemble adjusted into one overall effect size (thus, using a fixed effects approach since all effect sizes were drawn from the same population; Borenstein, Hedges, Higgins, & Rothstein, 2009; Rosenthal & Rubin, 1983). In such cases, we transformed each r into Fisher’s Zr, averaged the effect sizes, transformed back to an r, and gave the one averaged effect size (Achenbach, McConaughy, & Howell, 1987; Borenstein et al., 2009; Rosenthal, 1991; Rosenthal & DiMatteo, 2001; Rosenthal & Rubin, 1983; Smith & Glass, 1977; see Appendix A). By doing so, we avoided violations of independence assumptions made when testing significance (Card, 2010; Rosenthal, 1991). It is important to note that when a publication separately reported male and female results, we reported two separate effect sizes from the study. Combination statistics For each analysis, the unweighted mean and median effect size were computed, along with confidence intervals. Using the unweighted means and medians allows us to have a fuller picture of the data and the psychological phenomenon at hand. The random effects model was used to compute and combine effect size statistics, using the unweighted mean r based on k (the total number of effect sizes included). This model allows the results to be generalized beyond the samples included in the meta-analysis (Borenstein et al., 2009). In order to address the file-drawer problem and the potential number of new, unpublished, or otherwise unretrieved studies that would need to show no effect at the p < 0.05 level in order to negate our results, we computed the tolerance level (N ¼ 210) and fail-safe N (N ¼ 3053.47) values (Rosenthal & Rosnow, 2008). All statistical analyses were conducted using SPSS 22.0 and Excel Professional Plus 2013. Moderator analyses A chi square test for heterogeneity was first computed to assess for heterogeneous results within the sample (Hunter & Schmidt, 2000; Rosenthal, 1991). The chi-square statistic was used because the Type I error rate is lowest when the r- L.M. Dimler, M.N. Natsuaki / Journal of Adolescence 45 (2015) 160e170 165 nchez-Meca & Maríntransformed-to-Fisher’s-Z statistic is used in conjunction with the chi-square test for heterogeneity (Sa Martínez, 1997). The moderators were tested in random effects models in order to assess significant differences between effect sizes as a function of potential moderator variables at the most generalizable level. The random effects (unweighted) approach to analyzing moderators allows for generalization to studies that are not identical to the study sample, but are others of the same ilk (Hedges & Vevea, 1998; Hunter & Schmidt, 2000; Rosenthal & DiMatteo, 2001). Following the guideline by other meta-analytic studies (e.g., Card, 2010; Connell & Goodman, 2002) that moderator analyses with less than five effect sizes in each category are considered to be less reliable, we only ran moderator analyses with groups that contained five or more effect sizes. For moderator analyses, we computed independent sample t-tests and reported r for each group for respective comparisons. Results In total, 40 effect sizes (34 publications) were examined in this investigation. The sample sizes for these effects ranged from 52 to 5700, with a median sample size of 345, mean sample size of 916, and a total sample size of 36,641 adolescents. Thirteen effect sizes did not support the association between early pubertal timing and externalizing behaviors. Fourteen effect sizes were for males, 24 for females, and two examined both sexes without reporting separate results for each sex in the original publication. Sixteen effect sizes measured the effect of early pubertal timing longitudinally. Eleven of the 40 effect sizes used the PDS as the pubertal timing measure, five used clinician-report Tanner Stages, six used parent- or self-report Tanner Stages, seven used a perceived pubertal timing assessment, and 12 effect sizes used age of menarche as the pubertal timing measure. For a more detailed and comprehensive summary of the included studies (with effect size r, the significance, conclusion, and moderators for each study), please see Appendix A. Across the 40 effect sizes, the median correlation was r ¼ 0.123, with an average correlation of r ¼ 0.180 (95% CI: 0.109, 0.250; t(39) ¼ 140.81, p < 0.0001). These results suggest that early maturing adolescents tend to engage in more externalizing behaviors than their on-time or late-time maturing peers. These findings would be disputed only if there were over 3053 (i.e., fail-safe N) studies showing that there is in fact no association between early pubertal timing and higher levels of externalizing behaviors; this well exceeds the tolerance level of N ¼ 210. The chi square test for heterogeneity was not significant at the conventional p < 0.05 level ðc2ð39Þ ¼ 47:023Þ. Although the chi-square test is not significant by the conventional alpha level of 0.05, it has been shown that it is not necessary to have significantly heterogeneous results (Borenstein et al., 2009; Hall & Rosenthal, 1991) and is still important to examine for potential moderators (Borenstein et al., 2009;