**Abstract**

In the present research, the relationship between mental health and academic achievement in adolescents was investigated. The research adopted meta-analysis model to investigate the relationship between these two phenomena. In the metaanalysis, 13 independent studies were included, and their data were combined to display effect sizes. According to the result of the research, it was indicated that there was a positive relationship between mental health and academic achievement. Also, it was revealed that there was no significant relationship within sub-group variation in the relationship between mental health and academic achievement in terms of year of publication, publication type, community, and sample size, but not the setting.

**Keywords:** mental health, academic achievement, mental health in adolescents, meta-analysis

## **1. Introduction**

In recent years, mental health of adolescents has taken considerable attention worldwide, because of a dramatic upward trend in suicide [1]. More than twenty percent of adolescents in the U.S. have a mental health disorder [2], and one in five of them are affected by a mental health problem [3], which is estimated to account for a larger burden of disease than any other class of health conditions [4].

The mental health field has traditionally focused on psychological ill-health, such as symptoms of anxiety or depression [5]. The most common mental health disorders among adolescents include obsessive–compulsive disorder, attention deficit hyperactive disorder, bi-polar disorder, impulse disorders, and oppositional defiance disorder [6]. Often, adolescents experience mental health problems, with fewer than half of them [7], in other words nearly one third of them need receiving treatment [8]. The situation is much more severe in adolescents living in racial and ethnic communities, who are more likely to have mental health problems [9]. Moreover, evidence suggests that adolescents coming from such communities are less likely to use mental health services, compared adolescents living in non-racial and ethnic communities [10]. Thus, when adolescents struggle with mental health problems, they often have attendance problems, difficulty completing assignments, increased conflicts with adults and peers [11]. Also, mental health problems adolescents have negatively impact their academic productivity and interpersonal relationships [12], and as a result of such problems, one million of adolescents – which is deemed to be very high – drop out of school annually in the U.S., for example [13].

Mental health issues among adolescents not only cause such problems, but they also negatively influence schooling [14]. Adolescents with mental health problems are at risk for schooling [15], and they may have increased difficulties primarily with academic achievement in school [16]. Frequent feelings of mental health problems exhibit school difficulties, including poor academic achievement [17]. Adolescents displaying strong mental health are likely to have better academic achievement, compared to adolescents displaying weak mental health [18]. Adolescents showing strong mental health have good social skills with both adults and peers [19], and their enhanced social and emotional behaviors have a strong impact on academic achievement [20]. Therefore, mental health problems in adolescents may have an important influence on academic achievement, which in turn have lifelong consequences for employment, income, and other outcomes [21]. Mental health issues may become problematic for adolescents in that they negatively influence academic achievement [22], which also might affect their future employment, health, and socioeconomic status [23].

Mental health problems of adolescents have an important influence on their schooling, particularly their academic achievement, which in turn may create important lifelong consequences. Due to a growing interest in mental health of adolescents in recent years, a meta-analysis seems timely, not only to demonstrate the association between mental health and academic achievement, but also to identify moderators that should be articulated in more depth in future research. Although there is a body of research on the relationship between mental health and academic achievement across the world, the literature is missing a meta-analysis of this relationship. To date, no meta-analytic research has examined the potential relationship between mental health and academic achievement, and the present research aims to fill this gap in the scope. Thus, the present research attempts to synthesize this association between mental health and academic achievement of adolescents. This meta-analysis aimed to answer the following research questions: (a) What is the relationship between mental health and academic achievement? (b) Does this relationship depend on year of publication? (c) Does this relationship depend on setting? (d) Does this relationship depend on community? (e) Does this relationship depend on sample size?

## **2. Methodology**

#### **2.1 Model**

The present research adopted meta-analysis model [24] to combine data from independent studies to draw a single conclusion with greater statistical power [25]. Meta-analysis is a model that reviews the research results and combines the data obtained from independent studies in statistical ways [26].

#### **2.2 Data sources**

Research examining the relationship between mental health and academic achievement was identified through a search of reference databases. To identify relevant empirical research on the relationship between mental health and academic achievement, a systematic literature review was conducted over a

*Relation between Student Mental Health and Academic Achievement Revisited: A Meta-Analysis DOI: http://dx.doi.org/10.5772/intechopen.95766*

two-month time for the period 2000 to 2020, using such databases as Education Resources Information Center (ERIC), PsycINFO, Web of Science, EBSCOhost, Science Direct, Scopus, ProQuest®, and Google Scholar, with the following queries: [("mental health" OR "mental health disorders") AND ("mental health and academic achievement" OR "mental health disorders and academic achievement"], ["academic achievement" AND "academic success"], [("adolescents mental disorders" OR "adolescents mental health") AND ("adolescents mental health academic achievement" OR "adolescents mental health disorders academic success")]. As a result of such review, a total of 52 studies including 34 journal articles and 18 postgraduate dissertations were reached. Thus, over 50 potential independent studies were generated for preliminary review as a result of the literature search.

#### **2.3 Inclusion criteria**

To be eligible for inclusion in the present meta-analysis, a study had to (a) investigate the relationship between mental health and academic achievement; (b) include studies conducted on adolescents; (c) have taken place from 2000 to the present; (d) be reported to be available in English; and (e) include sample size and correlation coefficients.

The first four criteria were used in an initial screening of the abstracts of the studies. If the study had no abstract available, the full publication was collected and examined thoroughly. For the last criterion, the full publication was examined, and it was checked whether it included sample size as well as correlation coefficients. For the studies with insufficient statistical information, the corresponding author was contacted and the relevant information for the missing data was requested. If the author did not respond or could not provide the missing data, the study was excluded from the meta-analysis. After checking each study in the light of the inclusion criteria, the author agreed that 13 studies met all the five criteria of the research (see **Table 1**).

In order to investigate possible relationship between mental health and academic achievement, five moderators were extracted from the studies [40]. The first moderator concerned with the year of publication. The year of the publications were classified as 2009–2014 and 2015–2020, with a range of five years. The second moderator, publication type, referred to whether a study appeared as a journal article or a postgraduate dissertation. The third moderator, setting, referred to the country in which the research was conducted. Because the studies included in the meta-analysis were not from diverse settings – they were mainly coming from the U.S. and some Asian countries including India and Iran – the setting was classified as U.S. and non-U.S. The fourth moderator of the research, community, referred to the society people are living in. Because there was no study only conducted in rural settings, the community included urban and combination (urban, suburban, and rural). The last moderator, sample size, was classified as 1–500 and 501 above.

#### **2.4 Computation of effect sizes**

Standard procedures for conducting meta-analyses were followed [41], and the correlation between mental health and academic achievement were examined though effect sizes of independent studies. The effect size obtained in metaanalysis is a standard measure value used to determine the strength and direction of the relationship in the research [42]. In meta-analytic research, the variance depends strongly on correlation coefficient [43]. Pearson's correlation coefficient


#### **Table 1.**

*Studies included in the meta-analysis.*

(*r*) was calculated as effect size in the present research. For this reason, correlation coefficients were transformed into Fisher's z coefficient for computing the effect sizes, and analyses were conducted through the transformed coefficients [44]. In meta-analysis research, when the variable consists of more than one factor and when more than one correlation value is given, there are two different approaches about which one of them can be used [45]. In this research, if the correlations were independent, all relevant correlations were included in the analysis and accepted as independent studies. When dependent correlations were given, the correlations were averaged.

There are two basic models in meta-analysis research; they are fixed effects and random effects models. When deciding which model to use, it is necessary to look at which model's prerequisites are met by the features of the studies included in meta-analysis [46]. The fixed effect model is based on the assumption that when the data obtained are homogeneous, all the collected studies estimate exactly the same effect [47]. In this model, it is thought that the variance among the study results is caused by the data related to each other [48]. According to the fixed effect model, there is one effect size shared by the studies showing the same effect size for all studies [49]. In cases where the studies included in the meta-analysis show heterogeneous characteristics, it is more appropriate to use the random effect model [50]. This model is used in cases where the data obtained are not homogeneous [51]. As a result, while deciding which statistical model to use during meta-analysis, it should be tested whether the effect sizes show a homogeneous distribution.

In addition, the coefficient classification is taken into account in the interpretation of the effect sizes obtained as a result of meta-analysis [52]. In this research, Cohen's [53] effect size classification was taken into account in the interpretation of effect sizes. According to this classification, values between .20 and .50 correspond to small effect size; values between .50 and .80 correspond to medium effect size; and values above .80 correspond to large effect size.

*Relation between Student Mental Health and Academic Achievement Revisited: A Meta-Analysis DOI: http://dx.doi.org/10.5772/intechopen.95766*

#### **2.5 Publication bias**

Publication bias refers to the possibility that all studies performed on a particular subject will not be representative of the reported studies [54]. Since the studies where statistically significant relationships are not determined or studies with low level relationships are not deemed worthy to be published, this affects the total effect size negatively and increases the average effect size bias [55]. So, effect sizes seem to be higher than what they normally are [56].

A number of calculations are used to reveal publication bias in meta-analysis research, including methods such as funnel plot, classical fail-safe *N*, Orwin's failsafe *N*, and Duval and Tweedie's trim and fill. The first method used to determine whether studies have publication bias is funnel plot [57]. The funnel plot, which displays the possibility of a publication bias in meta-analysis research [58], created for the relationships between mental health and academic achievement was shown in **Figure 1**.

The funnel plot is expected to be significantly asymmetrical in publication bias. In cases where publication bias is not observed on the funnel plot, the effect sizes are symmetrically scattered around the vertical line. The line in the middle of the funnel plot shows the overall effect, and individual studies are expected to cluster around this line [59]. Studies which are asymmetrically scattered around the funnel plot refer to a possible publication bias in meta-analysis [60].

Also, classical fail-safe *N* was performed to reduce the average effect size to insignificant levels which is needed to increase the *p*-value for the meta-analysis to above .05 [61]. Classical fail-safe *N* showed that a total of 1699 studies with null results would be required to bring the overall effect size to trivial level at .01. Besides, Orwin's fail-safe *N* was performed to decide the values of criterion for a trivial log odd's ratio and mean log odds ratio in missing studies [62]. As a result of it, the number of missing null studies to bring the existing overall average effect sizes to trivial level at .01 was found to be .243.

Lastly, to assess the possibility of publication bias in the studies the trim and fill method, which is a nonparametric method of data augmentation used to estimate

**Figure 1.** *Funnel plot for the effect size of the relationship between mental health and academic achievement.*

the number of studies absent from a meta-analysis due to the exclusion on one side of the funnel plot of the most extreme findings [63], was performed. With the help of this statistic, small studies at the far end on the positive side of the funnel plot are removed. The effect size is recalculated until the funnel plot is symmetrical [64]. When there is publication bias in the studies, the effect sizes are distributed asymmetrical on the funnel plot. In the research, the funnel plot provided evidence that there is no publication bias in the meta-analysis.
