The effects of psychological maladjustments on predicting developmental trajectories of academic burnout

Abstract

We identified developmental trajectories of academic burnout related to psychological maladjustments (i.e., compulsion and depression) in 7th and 8th grade Korean adolescents.

This is vital because it facilitates early awareness of burnout trends and related psychological maladjustments, which might influence mental health problems, thus promoting proactive prevention and intervention before deterioration. We utilized four-wave longitudinal data from 415 adolescents who completed the Maslach Burnout Inventory-Student Survey and Symptom Check List-47. Data were analysed using growth mixture modeling. The results indicated that developmental trajectories of academic burnout can be characterized by three linear trajectories, ‘moderate-maintain’ (N = 213, 51.33%) which is related to depression, ‘low-deteriorated’ (N = 15, 3.61%) which is related to compulsion, and ‘well-adjusted’ (N = 158, 38.07%) which is related to no maladjustment symptoms. This longitudinal study promotes understanding of middle school students who may experience academic burnout and can facilitate early interventions for academic burnout.

Keywords

academic burnout compulsion depression growth mixture modeling longitudinal analysis

Academic issues are a major concern for students around the world. In particular, a number of studies (Huan et al., 2006; Sadler-Smith & Tsang, 1998) point out the serious academic pressures and stress in the Asian countries (e.g. Hong Kong, Singapore, and South Korea). According to a national report (Kim, 2015), the proportion of Korean adolescents who are experiencing academic stress is 50.5%, which is significantly higher than the OEDC average (33.3%). Additionally, the proportion of respondents who said they are ‘very satisfied’ with their school life was 18.5%, compared to the overall average of 26.7%, which is 4th lowest among 30 countries. Furthermore, the life satisfaction of Korean adolescents ranked the lowest among OECD countries. This implies that the prominent level of academic stress experienced by Korean students not only can have a negative impact on their school life but is also related to their overall quality of life. These consequences may be attributed to the unique culture and atmosphere of Korean education.

Because most Koreans believe that higher education is an essential process for social recognition and success, the drive for academic achievement and fierce competition for entrance examinations are common. Mo (2010, p. 51) interpreted this as ‘social utility of education’. Consequently, most Korean parents are over solicitous toward their children's education and children are expected to display high academic achievement. Korean middle school students feel the burden of academic achievement because of the pressure concerning high school and college entrance examinations. Many previous studies reported several negative academic problems due to this academic burden among Korean middle school students, and emphasized the importance of the middle-school years concerning psychological maladjustment related to academic problems.

In a previous study (Kim, 2008), the academic efficacy and autonomous motivation of Korean middle school students was significantly lower than that of elementary school students. Furthermore, the academic stress experienced by middle school students is evident. According to the Korean National Youth Policy Institute (Kim & Yu, 2016), 56.3% of elementary school students said they do not experience academic stress, whereas 68.9% of middle school students and 80.0% of high school students reported that they do. Additionally, those experiencing ‘extreme’ academic stresses increased with grade level: Elementary school = 11.2%, middle school = 22.5%, and high school = 33.0%. In many international studies (Larson & Ham, 1993; Tepper et al., 2008) it has been reported that various maladaptive psychological symptoms as well as stress worsened as grade increased. Thus, these findings suggest that middle school students may experience various psychological maladjustments and psychological distress due to academic problems, suggesting the need for appropriate interventions during middle school before the problems worsen.

Several studies have consistently noted that if adolescents continue to experience high levels of academic stress, they are likely to experience academic burnout (Kim, Lee, Shin, Park, & Lee, 2010; Shin et al., 2011). Burnout is a psychological syndrome that is defined as a sustained response to chronic job stressors (Maslach, Schaufeli, & Leiter, 2001). Since burnout was introduced by Freudenberger in 1974, it has been expanded into school contexts (Kim, Lee, Kim, Choi, & Lee, 2015; Lin & Huang, 2014), although it has been generally regarded as a work-related disorder. This is because their studies encompass structured activities, such as attending classes and submitting assignments, which can be considered ‘work’ (Lin & Huang, 2014), and school is a place where students work. Thus, academic burnout is a students’ response to continuing difficulties in coping with complex achievement pressures. Academic burnout is a multidimensional construct consisting of emotional exhaustion, cynicism and inefficacy. According to Kim et al. (2015, p. 282), ‘exhausted’ students feel emotionally drained by their studies. Students who experience ‘cynicism’ have become less enthusiastic about their studies. Students who believe ‘I make an effective contribution to the classes’ experience less ‘inefficacy’. Academic burnout is significant for several reasons (Charkhabi, Abarghuei, & Hayati, 2013; Lin & Huang, 2014). First, academic burnout may be a key for understanding different behaviors in students during their studies. Second, academic burnout may also influence students’ relationships, present and future, with their peers, teachers, parents, and others. Ultimately, academic burnout can affect students’ beliefs and attitudes toward studying.

Burnout is closely related to psychological maladjustment, which is indicated by various symptoms such as depression, anxiety, somatization, compulsion, withdrawal, etc. (Shin et al, 2011; Taris, Van Horn, Schaufeli, & Schreurs, 2004). This relationship is noteworthy among other internal variables associated with burnout because psychological maladjustment can affect adolescents' lives in areas such as academic performance, adaptation to school life, and life satisfaction. Shin and colleagues (2011) studied the relationship between mental health problems caused by psychological maladaptation and academic burnout among Korean middle school students. They revealed that depression, compulsion, anxiety, and hostility were very closely associated with exhaustion and cynicism. In other words, Korean middle school students most frequently experienced these symptoms, and compulsion and depression are the most powerful variables explaining academic burnout among these students. Consequently, more intensive, progressive research on the relationship between academic burnout and these two central indicators of psychological maladjustment— compulsion and depression—is required.

First, depression has been frequently shown to be related to academic burnout (Salmela-Aro, Savolainen, & Holopainen, 2009; Shin et al., 2011). Depression can affect individuals' thoughts, behavior, feelings, and physical well-being (Salmans, 1995). Dysphoric symptoms of burnout including fatigue, distancing, irritability, difficulty relaxing on days off work, and diminished enthusiasm may be typical for depression as well (Bakker et. al., 2000). The overlap between symptoms of burnout and depression is a controversial topic since the introduction of the burnout construct in the 1970s (Bianchi, Schonfeld, & Laurent, 2015). Bianchi and colleagues (2015) point out that the distinction between burnout and depression is conceptually fragile. In addition, among the three components of burnout, emotional exhaustion shows the most powerful link to depression with moderate to higher correlations. In previous studies (Leiter & Durup, 1994; Shirom & Ezrachi, 2003), emotional exhaustion overlaps with decreased energy and chronic fatigue symptoms to promote depression, and the depersonalization or cynicism implies that social withdrawal and learned helplessness influence depressive states. This ambiguity, therefore, has led to different results in previous studies (Leiter & Durup, 1994, Schaufeli, Martinez, Pinto, Salanova, & Bakker, 2002) on how correlated burnout and depression are and how the two symptoms can predict each other.

Compulsion is a means of proving oneself (Gandi, Wai, Karick, & Dagona, 2011). In the work place, those who are over-committed display excessive striving in combination with an ardent desire for approval (Bakker & Demerouti, 2007). This excessive desire is expressed in two forms of determination: a fighting spirit and compulsion (Gandi et. al., 2011). Some studies have revealed that compulsion in the form of ‘workaholism’ can be problematic (Schaufeli, Taris, & Bakker, 2006; Schaufeli, Taris, & Bakker, 2008). Scott, Moore, and Miceli (1997) defined that workaholics work beyond what is reasonably expected to meet organizational or economic requirements. Burnout has been known as a potential consequence of workaholism (Scott et. al., 1997; Taris, Schaufeli, & Verhoeven, 2005). Generally, compulsive work is believed to weaken employees’ well-being (Ng, Sorensen, & Feldman, 2007). Previous studies have certainly reported that workaholics who work compulsively, relative to non-workaholics, show more ill-health and lower levels of well-being as indexed by job stress, burnout, and negative affect (Burke, 2000; Schaufeli, Taris, & Van Rhenen, 2007). These results, ironically, imply that people with passion for satisfactory performance may obtain negative results.

Several researchers (Rudman & Gustavsson, 2011; Salmela-Aro, Kiuru, Nurmi, 2008) found that psychological symptoms have differential effects on varied levels of performance, engagement, and burnout. Consequently, it can be posited that academic burnout might have diverse trajectories due to the relations with varied levels of psychological symptoms. Considering that burnout is a developmental process and it has individual differences, it is necessary to investigate the developmental trajectories of academic burnout and examine its' relevant factors longitudinally. However, although a large body of research has addressed academic burnout, little is known about how academic burnout symptoms change during the middle-school years. Furthermore, even less is known about the heterogeneity of academic burnout that individuals show during this period. Consequently, we examined the developmental trajectories of academic burnout using longitudinal data from 7th and 8th grade students at four measurement points. Another aim was to identify the extent that psychological maladaptive symptoms (i.e. depression and compulsion) predict trajectories of academic burnout. An effort was also made to emphasize the importance of identifying the risk factors early, which can support interventions for school psychologists to prevent academic burnout.

Methods

Participants

Participants were middle school students from Seoul, South Korea and 415 students were collected every six months over four waves: Just before final examinations, which is expected to be a time of elevated academic stress. All participants were in the same year at school. The data were collected during grades 7 and 8. Among participants, 42.9% (N = 178) were boys, 55.2% (N = 229) were girls, and 1.9% (N = 8) did not provide their sex.

Measures

MBI-Student Survey (MBI-SS)

To measure academic burnout, the Korean version of the MBI-SS was used. In a previous study (Jung, Lee, & Choi, 2016), this instrument showed high internal consistency for all 15 items (α = 0.84) and each subscale (five items measured Emotional Exhaustion, α = 0.87; four items measured Cynicism, α = 0.87; six items measured Academic Efficacy, α = 0.83). In this study, internal consistency for all 15 items were $α_{t 1}$ = 0.89, $α_{t 2}$ = 0.91, $α_{t 3}$ = 0.90, $α_{t 4}$ = 0.88; for the Emotional Exhaustion subscale were $α_{t 1}$ = 0.83, $α_{t 2}$ = 0.87, $α_{t 3}$ = 0.87, $α_{t 4}$ = 0.89; for the Cynicism subscale were $α_{t 1}$ = 0.82, $α_{t 2}$ = 0.83, $α_{t 3}$ = 0.83, $α_{t 4}$ = 0.85; and for the Academic Efficacy subscale were $α_{t 1}$ = 0.83, $α_{t 2}$ = 0.84, $α_{t 3}$ = 0.83, $α_{t 4}$ = 0.85. The MBI-SS uses a five-point Likert design and responses range from 1 (strongly disagree) to 5 (strongly agree). High scores on Emotional Exhaustion, Cynicism, and low scores on Efficacy are indicative of greater burnout. All Academic Efficacy items were reversed coded to assess academic inefficacy.

Symptom Check List-47 (SCL-47)

To measure depression and compulsion, the SCL-47 was used. This instrument was modified by factor analysis on the SCL-90 tailored to the Korean context (Lee, 1986). The SCL-47 uses a five-point Likert design and responses range from 1 (not at all) to 5 (strongly severe) according to the degree to which a respondent agrees with their behavior or thoughts during the current or past six months. A higher score in each item means worse mental health. In previous research, Chong (1994) reported that the Cronbach's α for all 47 items was 0.95, somatization was 0.77, compulsion was 0.63, interpersonal sensitivity was 0.78, depression was 0.82, anxiety was 0.80, hostility was 0.82, phobic anxiety was 0.66, paranoid ideation was 0.75, and psychoticism was 0.65. In our study, we include only two subscales out of nine domains: Compulsion (five items, $α_{t 1}$ = 0.73, $α_{t 2}$ = 0.72, $α_{t 3}$ = 0.70, $α_{t 4}$ = 0.75) and depression (five items, $α_{t 1}$ = 0.86, $α_{t 2}$ = 0.87, $α_{t 3}$ = 0.85, $α_{t 4}$ = 0.87). Cronbach's α for ten items were $α_{t 1}$ = 0.97, $α_{t 2}$ = 0.97, $α_{t 3}$ = 0.97, $α_{t 4}$ = 0.97.

Data analyses

Growth Mixture Modeling (GMM)

GMM (Muthén & Muthén, 2000) was used to identify meaningful subpopulations within the larger population to examine the mean trajectories and individual variation across and within the subpopulations (Espy, Fang, Charak, Minich, & Taylor, 2009). These subpopulations are not known a priori, but are empirically determined as latent classes, where every class corresponds to a qualitatively distinct type of trajectory (Hodis, Meyer, McClure, Weir, & Walkey, 2011). In this study, GMM was applied to examine whether heterogeneity existed in the developmental trajectories of participants' academic burnout symptoms across Time 1–4, and what kind of psychological maladjustment was related to this heterogeneity in the level and growth rate of academic burnout across this period. Consequently, application of GMM is useful for developing intervention protocols as well as identifying specific psychological problems related to development of academic burnout.

The goodness-of-fit for the GMM analysis was evaluated for four indicators, as recommended by Muthén and Muthén (2000) and Nagin (2005). First, Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample-size adjusted BIC (SSA-BIC), which are known as the excellent criteria among information indices, were used to identify the optimal number of latent classes. For AIC, BIC, and SSA-BIC, the lower and the sharpest decreased score indicates a better fit of the model. Second, the quality of classification was estimated by entropy. The values of entropy rage from 0–1, and scores closer to 1 indicate clear classifications. Third, the minimum ratio for the latent classes based on the participants was applied. It is possible to compare the latent classes if the ratio is more than 1% (Jung & Wickrama, 2008). Additionally, along with statistical criteria, the substantive meaningfulness of the latent class results is also considerable in deciding on the number of classes. Figure 1 shows the GMM for this study.

Figure 1.

Research model.

Results

Descriptive statistics

The number of participants, mean scores, standard deviations, and correlations for all the involved variables are shown in Table 1. Mean academic burnout increased over the study period. There were moderate to relatively high correlations between academic burnout measured at distinct times, and low to relatively moderate, but significant correlations, between academic burnout and psychological maladjustment symptoms during middle school.

Table 1.

Correlations and descriptive information of study variables

Variable	1	2	3	4	5	6
1. Time 1. Academic burnout	1	0.48**	0.41**	0.35**	0.28**	0.31**
2. Time 2.	0.48**	1	0.44**	0.30**	0.30**	0.32**
3. Time 3.	0.41**	0.44**	1	0.50**	0.25**	0.29**
4. Time 4.	0.35**	0.30**	0.50**	1	0.25**	0.26**
5. Compulsion	0.28**	0.30**	0.25**	0.25**	1	0.78**
6. Depression	0.31**	0.32**	0.29**	0.26**	0.78**	1
n	367	381	375	388	415	415
Mean	2.75	2.78	2.86	2.85	50.07	50.08
Standard deviation	0.39	0.40	0.40	0.41	8.43	8.84

Note. **p < 0.01.

Determining the optimal number of classes

The optimal number of latent classes was identified, and the best possible model was selected.The models were compared using relative fit information criteria: AIC, BIC, SSA-BIC, entropy, minimum ratio for the latent classes based on total participants, and substantive meaningfulness of the latent class results. Those indicators were tested as classes added, two-, three-, four-, and five-class solutions.

Table 2 shows that three-class solution had the sharpest decreased and the lowest score in AIC and SSA-BIC, and the second lowest BIC, which is not significantly different from the lowest value. The entropy was above 0.60 for the all the solutions except the two-class solution, and the three-class solutions provided the highest value. Furthermore, Jung and Wickrama (2008) asserted that no classes should contain less than 1% of the total participants and the smallest class should contain 3.61% of the population. In this study, the three-class solution fits this criterion. The final key criterion in selecting a model is whether it makes theoretical sense and shows the classes to have qualitatively distinct trajectories. Because the trajectories of three classes did indeed differ (moderate-maintain, well-adjusted, low-deteriorated), the model was in accordance with this criterion. Consequently, the three-class solution was selected as the best-fit model. Figure 2 shows the developmental trajectories of academic burnout in the three-class solution.

Table 2.

Goodness-of-fit for models based on the number of classes

Class No.	AIC	BIC	SSA-BIC	Entropy	Classification of individuals
Class No.	AIC	BIC	SSA-BIC	Entropy	C	n	%
2	1189.22	1261.73	1204.61	0.00	1	213	51.33
2	1189.22	1261.73	1204.61	0.00	2	202	48.68
3	1175.60	1264.22	1194.41	0.88	1	242	58.31
					2	158	38.07
					3	15	3.61
4	1172.80	1285.593	1196.74	0.73	1	5	1.21
					2	62	14.94
					3	60	14.46
					4	288	69.40
5	1176.26	1297.11	1201.92	0.60	1	19	0.05
					2	119	0.29
					3	57	0.14
					4	195	0.46
					5	25	0.06

Note. *p < 0.05; **p < 0.01; ***p < 0.001.

AIC = Akaike's information criterion; BIC = Bayesian information criterion; SSA–BIC = sample-size-adjusted Bayesian information criteria.

Figure 2.

Developmental trajectories of academic burnout by the three-class solution

Estimation of the developmental trajectories of academic burnout as related to compulsion and depression

As shown Figure 2 and Table 3, Class 1, 2, and 3 were named ‘moderate-maintain’, ‘well-adjusted’, and ‘low-deteriorated’, respectively. The former two classes showed stable academic burnout states in their quite different primary stage. On the other hand, Class 3 had an upward trajectory signifying academic burnout deterioration. Furthermore, it also showed elevated levels of compulsion and moderate levels of depression.

Table 3.

Estimates derived from the model for latent classes

No. Latent Class	Intercept	Slope	Compulsion	Depression
1	2.90	0.02	53.51	55.27
2	2.58	0.05	43.80	42.21
3	2.44	0.14	58.76	50.34

Comparing the outcomes of the three academic burnout trajectory classes

The results presented in Table 4 show that all variables entered into the equation predicted academic burnout trajectory. The Korean adolescents in the ‘moderate-maintain’ class reported more severe levels of depressive symptom compared with those in the ‘low-deteriorated’ class. Additionally, Korean adolescents in the ‘low-deteriorated’ class reported more serious level of compulsive symptom compared with those in the ‘well-adjusted’ class. Psychological maladaptive symptoms predicting the ‘well-adjusted’ class were not found in this study.

Table 4.

Means and Standard Deviations for psychological maladaptive symptoms across three trajectory classes

Reference class	Comparative class	Personality Factor	M	SD
Moderate-maintain	Well-adjusted	Com	−0.16	0.20	0.83
	Well-adjusted	Dep	−2.55	1.89	1.35
	Low-deteriorated	Com	0.31	0.17	1.85
	Low-deteriorated	Dep	−0.38	0.17	2.26*
Well-adjusted	Moderate-maintain	Com	0.16	0.20	0.83
	Moderate-maintain	Dep	2.55	1.89	1.35
	Low-deteriorated	Com	0.47	0.22	2.12*
	Low-deteriorated	Dep	2.18	1.82	1.20

Note. *p < 0.05.

Com = compulsion; Dep = depression; SD = standard deviation.

Discussion

The main purpose of this study was to examine the developmental trajectories of academic burnout and related psychological maladjustment symptoms among Korean middle school students. First, we investigated whether there was a development of academic burnout among Korean middle school students. We showed that the mean academic burnout increased from Time 1 to Time 4. Additionally, latent growth for the development of academic burnout during 7th and 8th grade was identified with a slightly increased trend. These results are consistent with some empirical studies. Previous researchers have shown how academic burnout in Korean adolescents changes progressively during stressful situations such as extreme pressure for academic achievement. Lee, Puig, Lea, & Lee (2013) reported that Korean students are inclined to burnout progressively from grade 4 to grade 12. Also, Hwang (1997) showed that academic burnout among 9th grade students is higher than that of 7th grade students, as were increased inefficacy and emotional exhaustion. These results imply that students are experiencing more academic stress as they grow up, and their academic burnout symptoms are worsening as they go to the senior years.

Second, using GMM analysis, we investigated whether there was heterogeneity in academic burnout symptoms. In this study, a model with three latent linear growth trajectory classes best captured heterogeneity in the two-year course of Korean middle school students' academic burnout. The three classes were labeled based on the tendency to grow within each group as (a) moderate-maintain, (b) well-adjusted, and (c) low-deteriorated. This finding indicates that there may be heterogeneous subgroups of Korean adolescents who follow unique trajectories of academic burnout through their middle-school years. Differences among the three classes in trajectory seemed qualitatively comparable. More than half of the first group showed a moderate level of academic burnout, while over one-third of the second group showed a low level during their middle-school years. In both groups, the academic burnout symptoms stayed at the same level over time. The third group had a small sample (N = 15) who showed a low and increasing level of academic symptoms. This is a key finding as no previous study investigated heterogeneity in academic burnout during middle-school years over an extended period.

Finally, the core aim of this study was to examine the effect of psychological maladjustment indicators on predicting developmental trajectories of academic burnout. Interestingly, the result showed that the indicators of psychological maladjustment have differential effects on the diverse patterns of academic burnout development. In other words, the results showed that compulsion predicted the trajectory of the ‘low-deteriorated’ class as compared with that of the ‘well-adjusted’ class. This result was consistent with previous research (Andreassen, Ursin, & Eriksen, 2007; Broeck et al., 2011) that reported that compulsive work was positively related to exhaustion, but not cynicism and efficacy.

Taris and Schaufeli (2010) emphasized the role of compulsion, or the uncontrollable need to work incessantly, as a mediator that influences emotional exhaustion. According to Lee and Ashforth (1993), emotional exhaustion is the beginning stage of burnout, which triggers cynicism and inefficacy. Therefore, the current results imply that compulsive, constant, recurrent intrusive thoughts and repetitive intentional behaviors or mental acts have a key effect on worsening the beginning stages of academic burnout and influencing the initial value of academic burnout. Furthermore, individuals who work compulsively with excessive vigor and enthusiasm, which makes them exert elevated levels of effort, can easily become exhausted and burned out (Maslach et al., 2001). That is, compulsion has two sides, making people work hard and, at the same time, become exhausted.

Moreover, depression predicted the trajectory of ‘moderate-maintain’ compared with that of ‘low-deteriorated’. In previous cross-sectional studies, some researchers (Bakker et al., 2000; Leiter & Durup, 1994) reported that burnout is inclinable to lead to depression; furthermore, mental health deteriorates as burnout advances (Golembiewski, Lloyd, Scherb, & Munzenrider, 1992). Contrastingly, some studies (Masten et al., 2004; Schaufeli et al., 2002) reported that depression triggers low achievement and burnout. That is, these previous cross-sectional studies disagreed on what is the cause or consequences in the relationship between burnout and depression. However, considering these previous cross-sectional studies and the results of the current longitudinal study, it is suggested that depression is not related to the beginning stages of academic burnout because it cannot predict the trajectory of deteriorated academic burnout from its initial stages over time. In other words, it is expected that depressive symptoms will present only when burnout has already progressed or developed, and vice versa. This can be supported by interesting research (Ahola & Hakanen, 2007), which showed that burnout and depression have a reciprocal relationship; burnout predicted new cases of depression and depression predicted new cases of burnout. In addition, Rudman and Gustavsson (2011) reported that changes in burnout levels were accompanied by concurrent changes in depressive indicators. This means that burnout and depression might develop in tandem (McKnight & Glass, 1995).

In conclusion, it is expected that depression can be related to the slope of academic burnout as well as its initial value. Perhaps these results can be explained by the mutual developmental relationship between common elements shared by burnout and depression. Some studies provide concrete evidence for this (Ahola et al., 2005; Schaufeli & Enzmann, 1998). They reported that emotional exhaustion and depression shared 12% to 38% of their variance, while cynicism and depression shared 2% to 29% and personal accomplishment and depression shared 3% to 20%. Therefore, it is plausible that burnout and depression reinforce and develop each other.

On the other hand, the results did not show that any psychological maladjustment symptoms predicted the trajectory of ‘well-adjusted’. This means that individuals who adjusted well to their academic stress have wholesome mental health without having vulnerable psychological symptoms. We showed that academic burnout, which is caused by chronic academic stressors, has unique trajectories due to diverse relationships with varied psychological maladjustment symptoms; that is, the distinct burnout trajectories do not reflect arbitrary patterns of development, but are mirrored by relations with a crucial concomitant symptom such as compulsion and depression.

The present study has several limitations. First, few students met the clinical criteria for academic burnout, depression, and compulsion. This is because we had low to moderate correlations between academic burnout and psychological symptoms as compared with previous research (Salmela-Aro et al., 2009). Thus, the results should be interpreted as distress rather than clinical symptoms. Second, respondents were all students from a school in Seoul. The results of this study should be understood as a tendency of urban students, considering that the level of education varies depending on the region in Korea. Third, we used self-report questionnaires, and this may have led to overestimation or underestimation. Fourth, we did not consider personal resources. Thus, future studies should also consider including protective factors (e.g., resilience, self-efficacy, coping strategies) and biological indicators (e.g., blood pressure, cortisol levels) on burnout.

Despite these limitations, the results of this study have critical implications. While most adolescents reported maintained low or moderate levels of academic burnout, others have diverging trajectories. The analysis method in this study may expose non-typical trajectories that are frequently forgotten when dealing with longitudinal data. However, one should be careful when interpreting the extracted classes. This study is the first to investigate various longitudinal trajectories of academic burnout among Korean middle school students. This represents a potentially vital first step toward early identification of subgroups of individuals who follow similar trajectories of academic burnout.

Additionally, we showed that varied factors affect the trajectory membership and growth within each class, requiring the need to further improve theories and treatment programs for school psychologists. Researchers and clinicians should be aware of the possibility that individuals with academic burnout are developmentally heterogeneous. Being aware of the developmentally heterogeneous trajectories of burnout and its' relationships with psychological maladaptive symptoms, especially in the standpoint of early adolescence, could assist school psychologists to make appropriate intervention plans for specific client populations. In other words, the results provide a more dynamic view of burnout development based growth shapes, concurrent outcomes, and later outcomes. Therefore, this study presents an advanced understanding to promote prevention and intervention at the beginning of academic burnout and ongoing academic burnout through investigating developmental trajectories rather than outcomes at specific points. The findings present interesting insight for future studies that can advance the current knowledge on academic burnout trajectories. The next key step includes research addressing differential outcomes for each trajectory. Moreover, what characterizes adolescents with differing trajectories of burnout may be helpful in identifying groups of students who are more likely to be at risk of developing burnout. Therefore, another implication of this study is that it is warranted to examine adolescents' mental health and its relationship with academic stress.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014S1A5B8060944).

Note

Portions of this article are based on a Master's dissertation by Min Young Lee at Korea University.

Author biographies

Min Young Lee is a doctoral student in the Department of Education at Korea University. She is interested in human development, counseling policy, and the promotion of Psychological well-being.

Sang Min Lee is a Professor in the Department of Education at the Korea University. His research interests include student's academic burnout syndrome, counselor's burnout syndrome, and measurement issues in counseling.

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