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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].
\nThe 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].
\nMental 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].
\nMental 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?
\nThe 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].
\nResearch 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 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.
\nTo 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.
\nThe 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).
\nAuthor(s) | \nPublication type | \nSetting | \nCommunity | \nSample size | \n
---|---|---|---|---|
White [27] | \nDissertation | \nU.S. | \nUrban | \n780 | \n
Sathiyaraj and Babu [28] | \nJournal article | \nNon-U.S. (India) | \nCombination | \n750 | \n
Chung [29] | \nDissertation | \nNon-U.S. (Australia) | \nUrban | \n261 | \n
Eisenberg et al. [30] | \nJournal article | \nU.S. | \nUrban | \n2.798 | \n
Gilavand and Shooriabi [31] | \nJournal article | \nNon-U.S. (Iran) | \nCombination | \n200 | \n
Mundia [32] | \nJournal article | \nNon-U.S. (Brunei) | \nUrban | \n6 | \n
Geetha [33] | \nDissertation | \nNon-U.S. (India) | \nCombination | \n1.088 | \n
Jenkins [34] | \nDissertation | \nU.S. | \nUrban | \n331 | \n
Singh [35] | \nJournal article | \nNon-U.S. (India) | \nUrban | \n200 | \n
Sheykhjan et al. [36] | \nJournal article | \nNon-U.S. (Iran) | \nUrban | \n314 | \n
Murphy et al. [37] | \nJournal article | \nNon-U.S. (Chile) | \nUrban | \n37.397 | \n
Talawar and Das [38] | \nJournal article | \nNon-U.S. (India) | \nCombination | \n200 | \n
Manchri et al. [39] | \nJournal article | \nNon-U.S. (India) | \nUrban | \n270 | \n
Studies included in the meta-analysis.
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.
\nStandard 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 meta-analysis 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 (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.
\nThere 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.
\nIn 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.
\nPublication 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].
\nA 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 fail-safe 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.
\nFunnel plot for the effect size of the relationship between mental health and academic achievement.
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].
\nAlso, 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.
\nLastly, 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 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.
\nA total of 13 studies were included in the meta-analysis with a sample size of 44.595 adolescents. As a result of the comparisons, the Q value indicated that the distribution of effect size of the studies was heterogeneous, Q(12) = 1002.815, p < .001, so that a random effects model was adopted in the meta-analysis (see Table 2).
\nModel | \n\nk\n | \n\nd\n | \n\nSE\n | \n\n95% CI | \n\nQb\n\n | \n\ndfq\n\n | \n\npq\n\n | \n\nI2\n\n | \n|
---|---|---|---|---|---|---|---|---|---|
Lower | \nUpper | \n||||||||
Overall | \n13 | \n.334 | \n.155 | \n[.187 | \n.467] | \n\n | \n | \n | 98.803 | \n
Year of publication 2009–2014 2015–2020 Publication type Journal article Dissertation | \n4 9 9 4 | \n.256 .267 .256 .430 | \n.034 .010 .010 .047 | \n[.227 [.258 [.247 [.397 | \n.285] .276} .265] .462] | \n.004 .005 | \n1 1 | \n.949 .942 | \n.00 .00 | \n
Setting\na\n\n U.S. Non-U.S. | \n3 10 | \n.107 .399 | \n.232 .206 | \n[−.126 [.212 | \n.329] .557] | \n3.899 | \n1 | \n.048 | \n.00 | \n
Community\nb\n\n Urban Combination Sample size 1 ≤ N ≤ 500 501 ≤ N | \n9 4 8 5 | \n.250 .532 .408 .260 | \n.010 .051 .053 .010 | \n[.241 [.502 [.369 [.251 | \n.259] .562] .447] .268] | \n.990 .796 | \n1 1 | \n.320 .360 | \n.00 .00 | \n
Results related to overall effect sizes of the studies.
Due to that they did not report in English, other studies coming from diverse settings across the world were not included.
Because there was no study only conducted in rural settings, the community included urban and combination (urban, suburban and rural).
\nTable 2 demonstrated the relationship between mental health and academic achievement of adolescents. The effect size of the relationship between mental health and academic achievement computed by random effects model was r = .334 (95% CI = .187–.467). The confidence interval showed that the true effect size was likely to fall in the .187 to .467, which indicated a low to medium effect [65]. The computed effect size revealed that there is a moderate level of positive correlation between mental health and academic achievement. The forest plot of the relationship between mental health and academic achievement was displayed in Figure 2.
\nForest plot of the relationship between mental health and academic achievement.
Moderator analyses were performed to examine whether the effect sizes were attributable to the basic research sub-groups. Results indicated that this was not the case, as neither sub-group, excluding the setting, moderated the research findings. There was no significant relationship within sub-group variation in the relationship between mental health and academic achievement in terms of year of publication Qb\n(1) = .004, p = ns, publication type Qb\n(1) = .005, p = ns, community Qb\n(1) = .990, p = ns, and sample size Qb\n(1) = .796, p = ns, but not the setting Qb\n(1) = 3.899, p = .048. In other words, no significant moderation effect was found, which means that the relationship between mental health and academic achievement does not depend on the basic sub-groups, excluding the setting.
\nThe present research quantitatively synthesized the results of 13 independent studies, conducted over the past two decades, which examined the relationship between mental health and academic achievement in adolescents. The results of the research confirmed that there is a significant positive relationship between mental health and academic achievement. These results are consistent with the recent research investigating the relationship between mental health and academic achievement [27, 34]. Mental health problems may create many obstacles to adolescents, not just in their daily life routines, but also in their schooling academically. Mental health risks have long term and complex interactions with academic outcomes [27]. Mental health issues among adolescents not only cause pain and distress, but they also influence negatively their potential for success in school [14]. More and more adolescents – for example in the U.S. – face with mental health problems annually [1], and their behaviors lead to feelings of anxiety or depression [66]. The effects of mental health problems negatively influence the academic performance primarily [22], and as a result of it, more than one million adolescents drop out of school every year in the U. S. [23]. Mental health problems make adolescents face with a decline in academic achievement [67], which in turn results in school absence, poor grades, and even repeating a grade in school [68]. Those adolescents reporting high level of mental health problems are more likely to perceive themselves as less academically competent [69], and they display low academic achievement in school [70]. When schools identify problem behaviors with programs of intervention, it is likely to improve academic achievement of adolescents [71]. Well planned and well-implemented programs to foster mental health [72] can make adolescents achieve better academically in school [20]. However, in the U.S. – for example – 70 percent of adolescents who need mental health intervention cannot receive services [22], and nearly one third of them who need help receive treatment [8], which in turn negatively influences their academic achievement. Therefore, early detection of mental health problems of adolescents can have access to appropriate services which lead to improvement in both mental disorder symptoms and academic performance [73].
\nIn addition to these overall findings, this meta-analysis also looked at the influence of some moderators in the association between mental health and academic achievement. It was revealed that no variables moderated the relationship between mental health and academic achievement, but not the setting. 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.
\nFirst, year of publication did not appear to be a moderator in the association between mental health and academic achievement, indicating that the effect sizes of all studies included in the meta-analysis were similar. Second, the publications included in this meta-analysis were dissertations and journal articles. Although dissertations had a higher effect size compared to journal articles, publication type did not appear to be a moderator in the relationship between mental health and academic achievement. This showed that in spite of the fact that journal articles are selective to display significant results [74], they produced similar effect sizes as with dissertations which keep relatively minor results unpublished. Third, community did not appear to be a moderator in the association between mental health and academic achievement, which indicated that studies conducted both in urban and combination societies had similar effect sizes. This result revealed that mental health of adolescents living in both urban and combination communities is associated positively with academic achievement. Also, sample size did not appear to be a moderator in the relationship between mental health and academic achievement. Studies including more than 500 adolescents did not contribute significantly to the effect sizes, which indicated that the association between mental health and academic achievement was not affected by sample size.
\nHowever, it was indicated that setting appeared to be a significant moderator in the association between mental health and academic achievement. This result showed that studies conducted in the U.S. and countries out of the U.S. impacted differently to overall effect size. According to this result, countries out of the U.S., which are mainly Asian contexts, had a high effect size in the relationship between mental health and academic achievement. It may be due that the U.S. has relatively more racial and ethnic communities, or immigrants, compared to other countries, and such diversity of the U.S. may have an influence on the result obtained in the research. In the U.S. 70 percent of the adolescents need mental health interventions [22]; however, the situation is much more severe in minority communities [9]. Adolescents living in racial and ethnic communities in the U.S. are less likely to use mental health services due to poverty in particular [10]. Poverty has a disproportionate effect on racial and ethnic minorities, and adolescents who live in such condition are more likely to have a mental disorder [9]. As a result, almost half of the adolescents living in ethnic and racial communities in the U.S. fail to graduate due to the low level of academic achievement in school [75].
\nLastly, although the meta-analysis included the studies which took place from 2000 to the present, no study could be reached in 2020 probably due to the Covid-19 pandemic. Since the outbreak in Wuhan, China, nearly all countries across the world has faced with the Covid-19 pandemic in 2020. The pandemic has created severe consequences for millions of people in either losing their lives or their jobs. Many countries, including the U.S., the U.K., France, Germany, China, Italy, and Spain at the top, imposed lockdowns for several months and tried to prevent the fast spread of the virus. The pandemic not only affected general health of individuals and social lives of people, but it also impacted the schooling of many students. Most educational institutions around the world canceled in-person instruction and moved to distant teaching in an attempt to contain the spread of Covid-19 [76], and they are still pursuing this kind of teaching through digital platforms, such as Zoom, Skype, Google Meet, Microsoft Teams, and so on. Owing to the closure of schools, researchers have faced with considerable difficulty in reaching participants to conduct empirical studies; so this may have influenced the future research on the relationship between mental health and academic achievement in 2020.
\nOn the other hand, the Covid-19 pandemic might have affected the mental health of adolescents worldwide because they were imposed curfew for several months at home. During the lockdown, millions of adolescents had to stay home, and they were in social isolation both from their peers and the society. Many countries implemented isolation policies for adolescents in particular, due to the fact that these individuals have the potential to spread the virus easily to relatively older people which may result in higher fatalities. Affected by the long months in lockdown, many adolescents had to spend their time at home and pursue their education through digital platforms. Many adolescents faced with severe difficulties in pursuing their education at home, as well as they had problems in access to treatment as a result of losing their mental health. Many students confined at home due to Covid-19 may have felt stressed and anxious, and this may negatively have affected their mental health [76]. Many adolescents, having mental health problems, have faced with severe academic difficulties and dropped out of school [77]. During the pandemic, the dropout rates in adolescents have substantially increased across the world, and this in turn may have affected their schooling negatively, particularly their academic achievement. However, there is no empirical evidence to support the relationship between mental health and academic achievement during the Covid-19 pandemic; therefore it is timely to conduct research to investigate this potential association to prevent mental health disorders in adolescents and improve their academic achievement. Although the present meta-analysis showed that there is a positive relationship between mental health and academic achievement in adolescents, this cannot be the case during the pandemic. Months of curfew and lockdown may have influenced the mental health and academic achievement of adolescents; so future research is needed to better clarify the relationship between these two phenomena.
\nThe present meta-analysis aimed to determine the relationship between mental health and academic achievement in adolescents. This research, as expected, confirmed that there is a positive relationship between mental health and academic achievement. The research also indicated that mental health of adolescents is very important for schooling, in that it has a potential to influence academic achievement positively or negatively. Therefore, it is deemed crucial for adolescents to have a strong mental health to perform better academically in school, which in turn have lifelong consequences for employment, income, and other outcomes [21].
\nResults also indicated 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. It was indicated that setting appeared to be a significant moderator in the association between mental health and academic achievement. This result showed that studies conducted in the U.S. and countries out of the U.S. impacted differently to overall effect size. According to this result, countries out of the U.S. had a high effect size in the relationship between mental health and academic achievement. The effect size of the studies conducted in the U.S. was found to be relatively low, which implied that ethnic and racial diversity might have an impact on the result obtained in the research. This underlines the role of the school; thus, if schools identify mental health problems of adolescents with programs of intervention, it is likely to improve academic achievement [71]. Schools play an important role in determining the mental health of adolescents because they serve more than 95 percent of a country’s young people population [78].
\nA relatively small number of studies have been identified in the present meta-analysis, so more studies are needed to better clarify the relationship between mental health and academic achievement in adolescents. This research included only studies reported in English; therefore further meta-analyses might be conducted to include other reports out of English. Also, the role of school-based intervention programs in the relationship between mental health and academic achievement has not been taken into account in the present meta-analysis, so further research might be carried out to clarify the issue. The research has reported that school-based intervention programs may be effective to prevent mental health problems, and thus foster academic achievement [14]. In particular, adolescents living in ethnic and racial communities suffer from mental health problems, and academic achievement in school is influenced by such background. Because of this, mental health issues of adolescents living in ethnic and racial communities should be taken into consideration seriously.
\nThe author has no conflicts of interest to declare.
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