Longitudinal development of adolescent academic engagement following the Wenchuan earthquake: Domain-specific trajectories

Abstract

Recent studies have examined academic engagement trajectories, but many focused on the overall academic engagement of adolescents, and few assessed specific engagement dimensions of adolescents with trauma experiences. The current study recruited 342 adolescents who had experienced an earthquake to examine their behavioral and psychological engagement trajectories. Participants were asked to complete self-report questionnaires at 3.5, 4.5, and 5.5 years after the Wenchuan earthquake in China. The results identified two types of behavioral engagement trajectories (high–stable and decreasing), and two types of psychological engagement trajectories (high–stable and increasing). The behavioral engagement trajectories showed strong agreement with the psychological engagement trajectories. We also found that gratitude could prevent behavioral engagement from decreasing over time, and that social support facilitated increase of psychological engagement. The findings suggested that the developmental paths of behavioral and psychological engagement were both heterogeneous among adolescents following an earthquake, and gratitude and social support played different roles in predicting engagement trajectories.

Keywords

academic engagement trajectories gratitude social support adolescents

Introduction

Research shows that mass trauma events not only negatively affect adolescents’ mental health (e.g. Kolaitis, 2017; Ponnamperuma & Nicolson, 2016) but also deprive them of the necessary resources for learning (e.g. Ying, Wang, Lin, & Chen, 2016), thereby having a negative impact on their academic activities (e.g. Ying et al., 2016; Zhou, Zhen, & Wu, 2017). Academic engagement is an important aspect of academic and learning activities that has attracted the attention of a growing number of researchers (e.g. Font & Maguire-Jack, 2013; Kagei, Takashima, Sakata, & Yamada, 2013; Pan, Zaff, & Donlan, 2017). Academic engagement refers to a sense of belongingness and perceived worth of schooling, as well as positive participation in the school curriculum and other school activities (e.g. Finn, 1989; Glanville & Wildhagen, 2007). Academic engagement is closely associated with adolescent academic performance (e.g. Furrer & Skinner, 2003; Vizoso, Rodríguez, & Arias-Gundín, 2018), academic achievement (e.g. Hershberger & Jones, 2018; Skinner, Zimmer-Gembeck, & Connell, 1998), and mental health (e.g. Leonard, Stiles, & Gudiño, 2016).

Although the importance of academic engagement has been emphasized, not all adolescents show high levels of engagement (e.g. Estell & Perdue, 2013; Salmela-Aro, Moeller, Schneider, Spicer, & Lavonen, 2016; Wang & Peck, 2013). Recent studies indicate that academic engagement is not homogeneous or stable in adolescent samples (e.g. Li & Lerner, 2011), but is heterogeneous across individuals and tends to change over time (e.g. Wang, Chow, Hofkens, & Salmela-Aro, 2015). Correspondingly, trajectories of academic engagement among adolescents are also heterogeneous (e.g. Janosz, Archambault, Morizot, & Pagani, 2008). However, most studies on this topic have focused on the general population of adolescents; few studies have specifically assessed traumatized adolescents.

Mass trauma experiences disrupt individuals’ cognitive and emotional regulation (e.g. Calhoun & Tedeschi, 2006; Janoff-Bulman, 2010) and thus have a negative effect on their cognitive or emotional developmental processes (e.g. Zhou, Wu, An, & Chen, 2014a). The academic engagement trajectories of adolescents with trauma experiences may therefore differ from those of adolescents without trauma experiences. To investigate this possibility, this study examined adolescent academic engagement trajectories following an earthquake to identify factors that can differentiate adolescent academic engagement trajectories. We hoped that the study findings would inform a targeted education or intervention to improve adolescents’ post-traumatic adjustment and thereby improve their academic achievement.

Trajectories of academic engagement

There are three main viewpoints on adolescent academic engagement trajectories. One viewpoint is that academic engagement remains stable over time (e.g. Skinner & Belmont, 1993), and it can be considered as a personality characteristic (e.g. Skinner & Pitzer, 2012). In contrast, most theories and studies suggest that academic engagement is changeable, because it is often affected by interpersonal, social, and academic factors (e.g. Deci & Ryan, 2000; Eccles, 2004; Mahatmya, Lohman, Matjasko, & Farb, 2012; Marks, 2000). For example, compared with younger students, older adolescents must handle more complex learning problems and are confronted with more academic evaluation and competition. This environment will have a substantial negative effect on adolescents’ intrinsic motivation (e.g. Gottfried, Fleming, & Gottfried, 2001; Marks, 2000; Otis, Grouzet, & Pelletier, 2005), which leads to a decrease in their involvement in learning activities over time (e.g. Eccles, Wigfield, Harold, & Blumenfeld, 1993; Wigfield, Eccles, Davis-Kean, Roeser, & Scheifele, 2006). In contrast, some researchers have suggested that academic engagement increases as adolescent cognitive capability increases (e.g. Sharkey, 2009; Welsh, Miller, Kooken, Chafouleas, & Mccoach, 2016).

The differing viewpoints on academic engagement trajectories share a common limitation. These relevant studies relied on variable-focused analytic methods, which use an average trajectory to indicate trajectories of all the participants. This approach has neglected student heterogeneity and led to contradictory interpretations. In fact, adolescent academic engagement trajectories are characterized by heterogeneity (e.g. Janosz et al., 2008) owing to the complex influence of social, school, and individual factors (e.g. Estell & Perdue, 2013). Therefore, some researchers have used person-centered methods to examine the heterogeneity of adolescent engagement trajectories (e.g. Archambault & Dupéré, 2017; Archambault, Janosz, Fallu, & Pagani, 2009; Janosz et al., 2008; Li & Lerner, 2011; Wylie & Hodgen, 2012). Their findings indicate several common academic engagement trajectories, such as a normal group (in which engagement slightly decreases over time), a moderately stable group and a high–stable group (characterized by stable moderate and high-level engagement), a transient increasing group with an inverted U-shaped change curve, a transient decreasing group with a U-shaped change curve, an increasing group characterized by a constant ascending tendency, and a decreasing group with a constant descending tendency (e.g. Archambault et al., 2009; Janosz et al., 2008; Wylie & Hodgen, 2012).

However, these person-centered studies focused on general academic engagement, which limited our understanding of developmental differences in specific engagement dimensions (e.g. psychological and behavioral engagement; Li & Lerner, 2011). To address this issue, a few researchers examined specific trajectories of different dimensions of academic engagement (e.g. Archambault & Dupéré, 2017; Engels et al., 2017; Li & Lerner, 2011). Their findings show that behavioral engagement is characterized by four trajectory patterns: high–stable, moderate–stable, temporarily decreasing, and constantly decreasing; and that emotional engagement also has four patterns: highest engagement, fast decreasing, moderate, and constantly decreasing (e.g. Li & Lerner, 2011). However, no studies have examined how the different trajectory patterns of the different engagement dimensions coexist for an individual, so it is unclear whether the trajectory of one dimension correlates with changes in another dimension. To address this gap, the current study focused on the developmental paths of psychological and behavioral engagement among adolescents after an earthquake. Behavioral and emotional, or psychological, engagement may influence students’ motivation to cognitively engage with their academic work (Li & Lerner, 2013; Wang & Eccles, 2012), which may affect their overall academic engagement and performance.

The role of gratitude and social support in academic engagement

It is important to identify factors that affect academic engagement trajectories. Both individual and social factors may affect students’ academic engagement (e.g. Wang & Eccles, 2013), such as positive emotions and social support (e.g. Liu et al., 2018; Zhen et al., 2017). For example, the relationship between the positive emotion of gratitude and academic engagement has begun to attract researchers’ attention (e.g. Chao, Zhang, Li, Yu, & Dai, 2010; Li & Gao, 2015; Ma, Kibler, & Sly, 2013; Zhou, Wu, & Chen, 2014c). Gratitude is an emotion that occurs after receiving aid from others that one perceives as costly, valuable, and altruistic (Wood, Maltby, Stewart, & Joseph, 2008). The broaden-and-build theory of positive emotion posits that gratitude as a positive emotion can broaden individuals’ momentary thought–action repertoires and widen the range of thoughts and actions that come to mind (e.g. Fredrickson, 1998, 2004). In students, gratitude may increase levels of brain dopamine, which enlarges their cognitive scope (e.g. Ashby & Isen, 1999) and inspires more creative thoughts (e.g. Fredrickson, 2004), in turn promoting deeper engagement in learning tasks.

Social support is one of the most important social factors predicting academic engagement (e.g. Pan et al., 2017; Quin, Heerde, & Toumbourou, 2018; Xerri, Radford, & Shacklock, 2018). The expanded social-cognitive processing model (Lepore & Kernan, 2003) suggests that a supportive environment encourages greater disclosure of feelings and ideas and provides positive feedback for adolescents, which may increase their motivation to participate in learning activities and to engage in learning behaviors (e.g. Gill, Ashton, & Algina, 2004; Zhou et al., 2014c). Moreover, social support from others, particularly from teachers, helps to build better teacher–student relationships, and such support also increases the closeness between students and teachers or between students and the school (e.g. Patrick, Ryan, & Kaplan, 2007; Wang & Holcombe, 2010). Therefore, students who feel more supported and cared for are likely to adapt better to school life (e.g. Birch & Ladd, 1997) and to develop a positive attitude and sense of belongingness toward school (e.g. Zou, Qu, & Ye, 2007), in turn engaging more in learning activities.

Although previous studies have demonstrated the role of gratitude and social support in academic engagement (e.g. Ma et al., 2013; Quin et al., 2018; Xerri et al., 2018; Zhou et al., 2014c), their ability to predict different trajectories of different dimensions of academic engagement (i.e. behavioral and psychological engagement) is still unknown. Furthermore, social support consists of both emotional and material support, but research has rarely examined whether these aspects of social support have different effects on academic engagement among traumatized adolescents. To explore these issues, the study aim was to examine the psychological and behavioral engagement trajectories among adolescents following an earthquake, and then to assess the roles of gratitude and social support in behavioral and psychological engagement trajectories. Based on the research described above, it was predicted that behavioral and psychological engagement had heterogeneous trajectories in adolescents, and that social support and gratitude were associated with increasing behavioral and psychological engagement.

Methods

Participants and procedures

This study was part of a longitudinal study of psychological adjustment among child and adolescent survivors of the Wenchuan earthquake in China. We first investigated adolescents living in Wenchuan County 3.5 years after the earthquake (Time 1; T1); these adolescents were assessed again longitudinally at 4.5 years (T2) and 5.5 years (T3) after the earthquake. After approval was obtained from the local education authorities, two secondary schools volunteered to participate. With the help of the principals and school psychologists, four classes in each school were randomly selected (approximately 40 students per class). The age range of students in one school was 12–14 years for the two 7th grade classes and 15–17 years for the two 10th grade classes. In the other school, the age range was 13–15 years for the two 8th grade classes and 15–18 years for the two 11th grade classes. All students in the selected classes attended school on the assessment date, and all agreed to participate in this investigation and complete self-report questionnaires. At 3.5 years after the earthquake (T1), 342 adolescents participated in the first assessment, 339 adolescents participated in the second assessment (T2), and 161 adolescents participated in the third assessment (T3). The mean age was 15.06 (standard deviation = 1.69) years at the first measurement wave, ranging from 12.0 to 18.0 years. Of the 342 participants, 181 were female.

As some students had dropped out of school (or transferred to another school from their original school) at each wave after the first wave, it was difficult to conduct a longitudinal investigation with these students. Particularly at the last measurement wave, many students had graduated from their original schools and went to other provinces or cities to attend high school or university or to work. Thus, there was a high attrition rate. This project was approved by the research ethics committee of School of Psychology, Beijing Normal University and the local education authorities (in this case, county departments of education), and by the participating school principals. Written informed consent was obtained from school principals, classroom teachers, and participants. In China, research projects that are approved by local education authorities and school administrators and are deemed to provide services for students do not require parental consent. The study purpose and the autonomy of students were highlighted before the survey. The same set of questionnaires was distributed at three time points under the supervision of trained psychology post-graduate students. No compensation was provided for students’ participation other than counseling services if needed.

Measures

Academic engagement

Adolescents’ academic engagement was assessed using a revised school engagement scale developed by Zhou et al. (2014c). The original 25-item scale was developed by Glanville and Wildhagen (2007) and comprised behavioral and psychological engagement items. All items were scored on 3- or 4-point Likert scales. Zhou et al. (2014c) have translated the scale and modified the scoring so that responders rate all items on a 5-point Likert scale (1 = “completely disagree” and 5 = “completely agree”). In this study, the revised scale had acceptable Cronbach’s alpha coefficients (0.70, 0.67, and 0.69 for the behavioral engagement subscale at T1, T2, and T3, respectively; 0.77, 0.71, and 0.73 for the psychological engagement subscale at T1, T2, and T3, respectively).

Gratitude

Gratitude was assessed using a modified version of the Gratitude Questionnaire-6 (GQ-6) (Wei, Hu, Kong, & Wang, 2011). The original 6-item GQ-6 was developed by McCullough, Emmons, and Tsang (2002). Each item is scored on a 7-point scale ranging from 0 (completely disagree) to 6 (completely agree). To address cultural and language differences, Wei et al. (2011) revised the GQ-6; this revised version has shown good reliability and validity. To make the revised GQ-6 suitable to assess adolescents after an earthquake, Zhou, Wu, An, Chen, and Long (2014b) further reworded the items to be more applicable to such participants; this new version also shows good reliability and validity (e.g. Zhou & Wu, 2016; Zhou et al., 2014b). Gratitude was assessed across three different time points. According to the needs of this study, we only used data from the T1 gratitude assessment. In the present study, the revised GQ-6 at T1 showed acceptable internal consistency (alpha coefficient: 0.71).

Social support

Social support was assessed using the modified social net questionnaire (Zhou et al., 2014b, 2014c). This is a 16-item instrument that measures perceived social support. The questionnaire has two subscales: support and encouragement, and intimacy and companionship. All items are rated on a 5-point Likert scale ranging from 0 (completely disagree) to 4 (completely agree). Social support was assessed across three measurement waves. Based on the hypotheses, only data from the T1 assessment were included. In the current study, the scale at T1 showed good reliability (alpha coefficients: 0.94 for the support and encouragement subscale; 0.85 for the intimacy and companionship subscale).

Data analysis procedures

Missing data were first estimated and the percentage was equal to or lower than 3.2% at T1, 3.8% at T2, and 4.3% at T3. Then, Little’s missing completely at random test was used to analyze missing values across the three time points. The results revealed that the data were missing in a non-random way, χ² (63) = 83.281, p = 0.044. Therefore, the robust maximum likelihood estimate was used to handle missing data.

Mplus 7.0 software (Muthén & Muthén, 2012) was used for analysis. First, linear unconditional latent growth mixture modeling (LGMM) was conducted to identify the trajectory patterns of two dimensions of academic engagement (behavioral and psychological engagement) over time. Because the three measurement waves were conducted at 3.5, 4.5, and 5.5 years after the earthquake, the time scores of 0, 1, and 2, respectively, in the linear unconditional model were used to determine the academic engagement slope. Consistent with previous longitudinal studies (e.g. Fan, Long, Zhou, Zheng, & Liu, 2015; Guyon-Harris, Ahlfs-Dunn, & Huth-Bocks, 2017), we used participants in the first measurement wave as the original sample to examine the trajectories of academic engagement over time, in order to fully mine data information when the attrition rate is acceptable. More importantly, to determine the optimal number of latent classes, all solutions were evaluated and compared based on fit statistics, interpretability, and theoretical considerations. A good model fit is indicated by a lower Bayesian information criterion (BIC), Akaike information criterion, and sample size-adjusted Bayesian information criterion (adj BIC); higher entropy; a significant Lo–Mendell–Rubin adjusted likelihood ratio test (ALMR-LRT) result; and a significant bootstrap likelihood ratio test result (e.g. Akaike, 1987; Lo, Mendell, & Rubin, 2001; Nylund, Asparouhov, & Muthén, 2007).

Second, the most likely class membership variables for behavioral and psychological engagement trajectories were exported to SPSS, and we ensured that the LGMM results matched participants one by one. A Kappa test was then used to assess the concordance style of behavioral and psychological engagement trajectories. Subsequently, to assess the ability of gratitude and social support to differentiate academic engagement trajectories, the most likely class membership variable in the multinomial logistic regression analyses was used. Gratitude and social support were not included as covariates when conducting the latent growth mixture model to avoid their interference with the mixture solution.

Results

Trajectories of behavioral and psychological engagement

Table 1 shows fit indices of 1- to 6-class solutions for adolescent trajectories of behavioral and psychological engagement. As the table shows, only the 2-class solution for both behavioral and psychological engagement showed significant LMR-LRT and ALMR-LRT; thus, the 2-class solution for behavioral and psychological engagement was selected as optimal.

Table 1.

Linear changes in behavioral and psychological engagement over time.

	Model	AIC	BIC	adj BIC	Entropy	LMR-LRT	ALMR-LRT
Behavioral engagement	1-class	5054.19	5084.86	5059.49	–	–	–
Behavioral engagement	2-class	4989.57	5031.75	4996.86	0.93	70.62**	66.80**
	3-class	4953.16	5006.84	4962.43	0.91	42.41	40.12
	4-class	4933.28	4998.47	4944.55	0.85	25.87	24.48
	5-class	4917.38	4994.07	4930.63	0.84	20.54	19.43
	6-class	4907.47	4995.67	4922.71	0.83	14.04	13.28
Psychological engagement	1-class	5002.57	5033.22	5007.84	–	–	–
Psychological engagement	2-class	4971.04	5013.19	4978.30	0.87	37.53***	35.50**
	3-class	4969.77	5023.42	4979.01	0.74	7.27	6.87
	4-class	4973.13	5038.28	4984.35	0.70	2.64	2.50
	5-class	4977.36	5053.99	4990.55	0.73	1.78	1.68
	6-class	4982.46	5070.59	4997.63	0.73	0.90	0.85

Note: **p < 0.01, ***p < 0.001.

For the two latent trajectories of behavioral engagement, the intercept was 55.26 (standard error (SE) = 0.32) and 45.79 (SE = 2.50) for groups 1 and 2, respectively. The slope was 0.31 (SE = 0.24, p > 0.05) and −4.60 (SE = 1.65, p < 0.001) for groups 1 and 2, respectively. Figure 1 shows the two adolescent behavioral engagement trajectory patterns. Group 1 was named the high–stable group (n = 322, 94.2%), characterized by an initial high level of engagement and stable tendency across the three measurement waves. Group 2 was labeled the decreasing group (n = 20, 5.8%), characterized by an initial high level of engagement followed by a decreasing tendency at T2 and T3.

Figure 1.

Two latent trajectories of behavioral engagement.

For the two latent trajectories of psychological engagement, the intercept and slope of group 1 were 21.65 (SE = 1.96) and 6.22 (SE = 1.59, p < 0.001), respectively. The intercept and slope of group 2 were 34.30 (SE = 0.42) and−0.80 (SE = 0.26, p > 0.05), respectively. Figure 2 shows the two adolescent psychological engagement trajectory patterns. Group 1 was considered the increasing group (n = 26, 7.6%), characterized by an initial low level of engagement followed by an increasing tendency from T2 to T3. Group 2 was named the high–stable group (n = 315, 92.4%), characterized by an initial high level of engagement and stable tendency across the three measurement waves.

Figure 2.

Two latent trajectories of psychological engagement.

Concordance between behavioral and psychological engagement trajectories

We used the Kappa test and agreement rates to assess the concordance style of behavioral and psychological engagement trajectories (see Table 2). The trajectories of behavioral and psychological engagement showed relatively high agreement in 301 (88.3%) subjects. Table 2 shows the prevalence rates and their concordance style expressed by Kappa coefficients (Kappa value = 0.21, p < 0.001). The concordance between behavioral and psychological engagement trajectories varied but had a high rate of agreement.

Table 2.

Participant distribution for different trajectories of behavioral and psychological engagement.

		Behavioral engagement		Total
		High–stable group	Increasing group	Total
Psychological engagement	High–stable group	301 (88.3%)	14 (4.1%)	315 (92.4%)
Psychological engagement	Decreasing group	20 (5.9%)	6 (1.8%)	26 (7.6%)
Total		321 (94.1%)	20 (5.9%)	341 (100.0%)

Association of gratitude and social support with distinct engagement trajectories

Multivariate logistic regressions were used to examine the roles of gratitude and social support in predicting behavioral and psychological engagement trajectory patterns (see Table 3). Gratitude significantly differentiated behavioral engagement trajectories (OR = 0.85, 95% confidence interval (CI) = 0.75–0.96), but support and encouragement, and intimacy and companionship, had non-significant relationships to behavioral engagement trajectories (OR = 0.99, 95% CI = 0.93–1.05; OR = 1.04, 95% CI = 0.94–1.16). Gratitude was less likely to be associated with decreasing behavioral engagement than with high–stable behavioral engagement.

Table 3.

The relation of gratitude and social support to trajectories of behavioral and psychological engagement.

	Behavioral engagement		Psychological engagement
	Decreasing group versus high–stable group		Increasing group versus high–stable group
	OR	95% CI	OR	95% CI
Gratitude	0.85**	(0.75–0.96)	0.92	(0.84–1.02)
Support and encouragement	0.99	(0.93–1.05)	0.92**	(0.87–0.97)
Intimacy and companion	1.04	(0.94–1.16)	1.10^#	(0.99–1.21)

Note: ^#p = 0.064, **p < 0.01.

In contrast, gratitude had a non-significant relationship with psychological engagement trajectories (OR = 0.92, 95% CI = 0.84–1.02), but two dimensions of social support had significant relationships with distinct psychological engagement trajectories (OR = 0.92, 95% CI = 0.87–0.97; OR = 1.10, 95% CI = 0.99–1.21). Specifically, support and encouragement were less likely to be associated with increasing psychological engagement than with high–stable psychological engagement, whereas intimacy and companionship were more likely to be related to increasing psychological engagement. The findings indicated that gratitude was more effective in maintaining a high level of behavioral engagement than psychological engagement over time, whereas social support had a stronger effect on psychological engagement trajectories than on behavioral engagement trajectories. These results suggest that support and encouragement help to maintain high–stable psychological engagement, and intimacy and companionship help to promote psychological engagement over time.

Discussion

To our knowledge, this study is among the first to examine developmental paths of behavioral and psychological engagement over time among adolescents with mass trauma experiences, and among the first to assess the concordance style of different trajectories of behavioral and psychological engagement. The results indicated two different trajectories of behavioral engagement in adolescents: a high–stable tendency and a decreasing tendency. Psychological engagement also showed two trajectories: a high–stable tendency and an increasing tendency. These findings support those of previous studies demonstrating the heterogeneity of academic engagement trajectories in adolescents (e.g. Archambault & Dupéré, 2017; Archambault et al., 2009; Janosz et al., 2008; Li & Lerner, 2011; Wylie & Hodgen, 2012). In addition, we found that the concordance styles of behavioral and psychological engagement trajectories varied but had a high rate of agreement. This finding is consistent with previous studies (e.g. Li & Lerner, 2013; Pietarinen, Soini, & Pyhältö, 2014) and suggests a close relationship between different dimensions of academic engagement. Furthermore, we found that gratitude was only associated with behavioral engagement trajectories, and social support was only associated with psychological engagement trajectories, indicating the distinct roles of individual and social factors in predicting engagement trajectories.

Specifically, behavioral engagement was characterized by high–stable and decreasing trajectories, and most adolescents (94.2%) were in the high–stable group. This finding is consistent with previous findings (e.g. Archambault & Dupéré, 2017; Li & Lerner, 2011) and suggests that most adolescents positively and constantly engage in academic or school activities. The demand–resources model (e.g. Bakker & Demerouti, 2007; Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) provides a possible explanation for these findings. According to the model, academic activities depend on the satisfaction of an individual’s demand for resources. When resources can meet the demand for learning, the individual will engage in learning activities (e.g. Demerouti et al., 2001). At 3.5 years post-earthquake, post-disaster reconstruction had gradually replaced the resources lost in the earthquake and the necessary resources were available to meet the learning demands of most adolescents. At 4.5 and 5.5 years post-earthquake, the school infrastructure had been further improved, and there were more school resources to meet adolescents’ learning requirements, which made it possible for most students to engage in learning. The strict requirements and high expectations of Chinese parents and teachers may also explain the high and stable level of adolescent behavioral engagement (e.g. Lin, Wang, Zhang, & Ji, 2009; Liu, 2015; Ouyang, 2005). Moreover, parents and teachers can provide learning supervision and guidance for adolescents (e.g. Liu, 2015; Ouyang, 2005), increasing their behavioral engagement in learning activities.

However, not all adolescents in our study showed high and stable levels of behavioral engagement; 5.8% showed a decreasing tendency, which is similar to Li and Lerner’s (2011) results and supports previous related findings (e.g. De et al., 2015; Fredricks, Blumenfeld, & Paris, 2004; Wang & Eccles, 2012). A potential reason for this is that these adolescents experienced high stress from academic tasks and competition over time (e.g. Gottfried et al., 2001; Marks, 2000; Otis et al., 2005). Once they could no longer appropriately tackle such stress, their feelings of self-denial increased (e.g. Archambault, Eccles, & Vida, 2010), and they may have avoided behavioral engagement in learning and experienced a decreasing tendency to behavioral engagement over time.

Similarly, we found that 92.4% of adolescents showed a high and stable level of psychological engagement, consistent with previous studies (e.g. Archambault & Dupéré, 2017; Li & Lerner, 2011), suggesting that most adolescents in our study experienced a high level of belongingness at school. In contrast to behavioral engagement, and inconsistent with previous findings on decreasing emotional engagement (e.g. Haapasalo, Välimaa, & Kannas, 2010; Wang et al., 2015; Wang & Eccles, 2012), our results indicated that the psychological engagement of a few adolescents showed an increasing trajectory. Studies on adolescents without traumatic experiences indicate that younger adolescents tend to have a more optimistic attitude to school and learning (e.g. Archambault et al., 2010) and have a high level of psychological engagement. Over time, they will experience increasing stress and academic burnout and show decreasing emotional engagement (e.g. Haapasalo et al., 2010; Wang & Eccles, 2012). In contrast, the adolescents in our study had received targeted interventions to relieve negative reactions and improve positive adjustment after the earthquake (e.g. Lin, Wu, Hou, Fang, & Zang, 2009). These interventions were mainly carried out in schools, and helped to build a closer connectedness between adolescents and schools. Thus, in addition to those with a high and stable psychological engagement level, a few students also experienced an increasing trend of psychological engagement over time.

Our examination of the concordance of trajectories of both behavioral and psychological engagement showed that two behavioral engagement trajectories and two psychological engagement trajectories varied but had a high rate of agreement, which is consistent with previous studies (e.g. Li & Lerner, 2013; Pietarinen et al., 2014). Specifically, 88.3% of the adolescents with high–stable psychological engagement also showed high–stable behavioral engagement, indicating that most of these students displayed consistency in psychological and behavioral engagement. Psychological engagement reflects adolescents’ attitudes and emotions toward school and learning activities, and behavioral engagement reflects behavioral participation in school and learning activities (e.g. Glanville & Wildhagen, 2007). The broaden-and-build theory of positive emotion (Fredrickson, 2001) suggests that positive emotions can broaden individuals’ momentary thought–action repertoires and widen the scope of attention, cognition, and action, thereby encouraging approach behaviors or continued action (Fredrickson, 2001). Therefore, students who enjoy learning or feel attached to school are more likely to invest time and effort in academic-related activities, suggesting that positive emotional involvement serves as an important impetus for academic behavioral activities throughout an individual’s learning career (e.g. Ladd, Buhs, & Seid, 2000). This phenomenon can explain the positive association between psychological engagement and behavioral engagement (e.g. Li & Lerner, 2013; Skinner, Furrer, Marchand, & Kindermann, 2008) and the high level of agreement between high–stable psychological engagement and high–stable behavioral engagement. However, the relationship between psychological engagement and behavioral engagement may also be affected by academic tasks, classroom environment, teachers’ teaching style, and other factors (e.g. Archambault, Janosz, & Chouinard, 2012; Rubie-Davies, Flint, & Mcdonald, 2012). Hence, a few adolescents displayed divergent pathways in psychological and behavioral engagement over time, such as a decreasing trend of behavioral engagement together with an increasing trend of psychological engagement.

Finally, we examined the role of gratitude and social support in predicting engagement trajectories and found that gratitude was significantly associated with behavioral rather than psychological engagement trajectories. This may be because after the Wenchuan earthquake, adolescents with a high gratitude level were more likely to give positive feedback to others and to have an adaptive worldview (e.g. Zhou & Wu, 2015), thus behaving in accordance with their parents’ and teachers’ requirements and investing more effort in school activities. That is, gratitude facilitates adolescents’ participation in academic activities (e.g. Chao et al., 2010; Li & Gao, 2015; Ma et al., 2013; Zhou et al., 2014c). Furthermore, the results indicated that, compared with high–stable behavioral engagement, gratitude was less likely to be related to decreasing behavioral engagement. In fact, gratitude can help to inspire adolescents’ intrinsic motivation for learning (e.g. Froh, Bono, & Emmons, 2010; McCullough, Kilpatrick, Emmons, & Larson, 2001), which can further activate persistent learning-related behaviors (e.g. Graham, 2007); this may explain why adolescents with high gratitude were less likely to show a tendency for decreasing behavioral engagement.

In contrast, social support was significantly related to psychological rather than behavioral engagement trajectories. Specifically, support and encouragement were more associated with high–stable psychological engagement, but intimacy and companionship were more associated with increasing psychological engagement. After the earthquake, social support from others in schools focused on the relief of negative psychological outcomes (e.g. Du et al., 2018; Guo, Liu, Kong, Solomon, & Fu, 2018; Wu, Xu, & Yan, 2016), which promoted adolescents’ positive psychological responses (e.g. Jia, Liu, Ying, & Lin, 2017; Zhou et al., 2014a, 2014b). Thus, social support helped adolescents to identify and develop a sense of attachment and belonging to their schools, and to experience a high level of psychological engagement. Specifically, support and encouragement, particularly from friends or teachers, can help adolescents to cope with stress (e.g. Zhou et al., 2014b) and expand their positive emotional school-related experiences. This helps them to maintain highly stable psychological academic engagement. Intimacy and companionship from interpersonal relationships provide emotional support, which can offset the noxious effects of trauma (e.g. Krause, 2004). As individuals age, they become increasingly oriented toward relationships that are emotionally supportive (e.g. Carstensen, 1992), so intimacy and companionship are increasingly important to psychological outcomes.

There were several study limitations. First, we did not assess adolescents’ academic engagement before our first assessment time point (3.5 years after the earthquake), so our findings only indicate engagement trajectories from 3.5 years to 5.5 years post-earthquake. Second, participants may have experienced other traumatic events during the lengthy study period, which might have affected the development of academic engagement; however, traumatic events other than the Wenchuan earthquake were not investigated. Third, gratitude and social support were the only academic engagement predictors examined; other potential predictors were not assessed. Moreover, owing to the small sample size at T3, it was difficult to analyze a breakdown of academic engagement trajectories by class or age; future studies are needed with larger samples to examine the effect of class and age on trajectories.

Despite these limitations, the current study is among the first to examine the trajectories of behavioral and psychological engagement among adolescents following an earthquake, extending relevant research on the general population of adolescents to those with trauma experiences. The findings suggest that both the behavioral and psychological academic engagement of traumatic adolescents show heterogeneous trajectories. In addition, the strong agreement between the trajectories of behavioral and psychological engagement, from a longitudinal research perspective, further supports previous findings on the relationship between engagement dimensions (e.g. Li & Lerner, 2013; Skinner et al., 2008).

Our findings also provide practical implications. First, since adolescents may show different levels in different dimensions of academic engagement, it is necessary to consider the features of dimensions rather than overall academic engagement. Second, due to the nature of rapid change of adolescence, educators need to take a developmental and heterogeneous perspective to assess adolescents’ distinct trajectories of engagement in learning-related activities, in order to carry out more targeted education or intervention. Third, although most adolescents kept high levels in behavioral and psychological engagement across time, some presented downward tendency in behavioral engagement. This suggests that teachers and parents should pay attention to these adolescents’ problems in learning behaviors. Besides, the findings highlight the role of gratitude in hindering their decline in behavioral engagement since earthquake. School psychologists can enhance adolescents’ satisfaction with school and impede their behavioral disengagement by deepening their gratitude, such as keeping a diary on gratitude or giving thanks and appreciation to others every day. Moreover, providing social support and encouragement for adolescents following natural disasters, parents and teachers can help them to boost emotional connectedness to school and school-related activities, and to maintain a high psychological engagement level.

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 study was supported by the General Research Program of Education Department of Zhejiang, China (Grant No. Y201840094).

Rui Zhen is an Associate Researcher in Institute of Psychological Sciences, College of Education, Hangzhou Normal University. Her research focuses on academic motivation in adolescents. She achieved her PhD in educational psychology from Faculty of Psychology, Beijing Normal University.

Xinchun Wu is a Professor in Faculty of Psychology, Beijing Normal University. His interest focuses on trauma psychology and educational psychology. He achieved his PhD in educational psychology from Faculty of Psychology, Beijing Normal University.

Xiao Zhou is a Researcher in Department of Psychological and Behavioral Sciences, Zhejiang University. His research focuses on post-traumatic reactions among adolescents following earthquake and cancer patients. He achieved his PhD in educational psychology from Faculty of Psychology, Beijing Normal University.

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