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ORIGINAL RESEARCH article

Front. Psychol., 01 September 2020
Sec. Educational Psychology

The Impact of Positive Youth Development Attributes and Life Satisfaction on Academic Well-Being: A Longitudinal Mediation Study

  • Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China

While research studies revealed that positive youth development (PYD) attributes have beneficial impact on adolescent developmental outcomes, whether and how PYD qualities are related to academic well-being (such as academic stress and academic satisfaction) are unclear. Based on a longitudinal study (N = 2,312 secondary school students; Mage = 12.54 ± 0.68; 51% female) in Hong Kong, the present study tested a longitudinal mediation model in which it was hypothesized that PYD qualities predicted life satisfaction, academic stress, and academic satisfaction, with satisfaction with life mediating the influence of PYD qualities on academic well-being. Results showed that PYD qualities positively predicted academic satisfaction but negatively predicted academic stress over time. While life satisfaction partially mediated the influence of PYD attributes on academic satisfaction, it fully mediated the influence of PYD attributes on academic stress. The present study supports the proposed conceptual model and underscores the role of PYD qualities in academic well-being through the mediation of life satisfaction.

Introduction

During the past two decades, there has been a change in the paradigm of adolescent research. Rather than viewing adolescents as “problems,” the “positive youth development” (PYD) perspective highlights resources, potentials, and strengths in adolescents (Damon, 2004; Shek et al., 2019). For example, Lerner (2005) theorized that PYD qualities could be indicated by “Five Cs,” including “competence, confidence, connection, character, and caring” (p. 31). The “Five Cs” could enable an adolescent to function as “an active agent in one’s own development,” which would increase his/her well-being but decrease his/her problem behavior (Lerner, 2005, p.32). Catalano et al. (2004) put forward 15 indicators of PYD based on an evaluation of positive youth development programs in the United States. The 15 indicators include “bonding,” “resilience,” “social competence,” “emotional competence,” “cognitive competence,” “behavioral competence,” “moral competence,” “self-determination,” “spirituality,” “self-efficacy,” “clear and positive identity,” “belief in the future,” “recognition for positive behavior,” “prosocial involvement,” and “prosocial norms” (Catalano et al., 2004, p.101–102). Benson et al. (2006) argued that PYD could be shaped by both external and internal assets, which contributes to adolescent well-being and later success. Consistent with the PYD theories, research findings showed that PYD qualities were linked to a broad range of adolescent developmental outcomes including internalizing and externalizing behaviors, psychological adjustment as well as prosocial behavior (Eichas et al., 2010; Schwartz et al., 2010; Ciocanel et al., 2017; Shek and Zhu, 2018; Zhou et al., 2020). However, few studies have addressed the mediating role of life satisfaction in the influence of PYD qualities on adolescent developmental outcomes, particularly in different Chinese societies (Sun and Shek, 2010, 2012). Studies on the effect of PYD qualities on academic well-being (such as academic stress and academic satisfaction) are also scarce in the international literature (Shek and Wu, 2016).

As a commonly used index of subjective well-being, life satisfaction is defined as a person’s overall cognitive evaluation of the quality of own life (Gilman and Huebner, 2003). Studies showed that life satisfaction was influenced by both environmental and individual factors (e.g., McKnight et al., 2002), including PYD qualities such as emotional intelligence, self-esteem, self-efficacy, social competence, spirituality, and character strengths (Huebner et al., 2004; Proctor et al., 2009; Rey et al., 2011; Howell et al., 2013; Chen et al., 2017). In addition, cross-sectional and longitudinal studies also revealed that PYD qualities positively predicted satisfaction with life among adolescents (Sun and Shek, 2010, 2013; Mohamad et al., 2014). Theoretically, PYD qualities such as self-efficacy, self-worth, and good social relationships (Lerner et al., 2009) would lead to one’s positive appraisal of one’s life (i.e., higher life satisfaction). As a result, it is commonly hypothesized that PYD qualities are a positive predictor of satisfaction with life (Sun and Shek, 2010, 2012).

Although studies suggest that PYD qualities and related intervention could promote academic performance of students (Durlak et al., 2010; Yu et al., 2018), it is not clear about the relationships between PYD qualities and academic well-being such as academic satisfaction and academic stress. According to Marchiondo et al. (2010), academic satisfaction was defined as “the attraction or positive feelings that a student associates with the college or program in question” (p. 610). Jadidian and Duffy (2012) also proposed that academic satisfaction mainly covers one’s satisfaction with academic programs and classes. Therefore, students’ satisfaction with their curriculum is an essential component of their academic satisfaction. However, academic satisfaction is different from academic engagement with the latter referring to students’ devotion and involvement in their academic study such as participating in classes on time, preparation for classwork, and efforts in doing homework (Singh et al., 2002). Students’ academic satisfaction is a major concern of educators as it was regarded as one important “subjective indicator” of an individual’s success in the academic domain (Wach et al., 2016, p.1). Academic satisfaction also reflects how successfully a program is conducted (Albarrak et al., 2013), which is closely related to student retention (Wilkins-Yel et al., 2018). A few studies revealed that PYD qualities positively predicted academic satisfaction, including self-efficacy, emotional competence, and conscientiousness (Lent et al., 2007; van Schaick et al., 2007; Sheu et al., 2016). Also, research studies revealed that PYD attributes such as hope and optimism predicted school satisfaction (Wilkins et al., 2014; Sun, 2016). The common conjecture generated from the scientific literature is that PYD qualities are a positive predictor of academic satisfaction.

Besides academic satisfaction, academic stress is also an important factor influencing adolescents’ psychosocial development, including school adjustment. While there are different views on academic stress, one common conception is that academic stress is students’ “subjective experience of distress” under certain academic-related stimulus or stressors (Putwain, 2007). Perceived academic stress might come from different stressors produced by one’s academic study such as high workload, meeting tight deadlines, and handling multiple tasks (Rayle and Chung, 2007; Bedewy and Gabriel, 2015). Particularly, research suggests that “academic work and its related assessments” are major stressors for students in secondary schools (Putwain, 2007). Therefore, highly pressured academic study and academic programs could be the major stressors or stimuli leading to academic stress. While a similar concept related to academic stress is academic burnout, the two concepts are different. Scholars conceptualized academic burnout to be a psychological reaction or syndrome that is shaped by academic stress (Shin et al., 2012; Charkhabi et al., 2013). Empirical research also showed that academic stress was an important predictor of academic burnout (Lin and Huang, 2013). Academic stress is important to students because it is related to a wide range of physical, mental, and academically related problems such as depression, low motivation to learn, and physical illness (Ang and Huan, 2006; Hystad et al., 2009; Liu, 2015). Unfortunately, the extant literature mainly focuses on environmental predictors and outcomes of academic stress, with few studies examining personal predictors of perceived academic stress. Some limited studies revealed that perceived academic stress was negatively predicted by psychological strengths such as grit, optimism, and emotional intelligence (Huan et al., 2006; Bao et al., 2015; Lee, 2017) as well as cognitive abilities (Giota and Gustafsson, 2017). Taking together, the literature suggests a negative influence of PYD attributes on perceived academic stress.

Considering the relationship between life satisfaction and academic satisfaction, the proposal that life satisfaction influences academic satisfaction is supported by the “top-down model” of life satisfaction. In the “top-down model,” global satisfaction with life is regarded as “a global propensity to experience things in positive ways” which “influences the momentary interactions an individual has with the world” (Diener, 1984, p.565). In other words, life satisfaction is not the sum of satisfaction with different aspects of life, but more a relatively stable psychological characteristic that influences individuals’ perceptions of, and reaction to, their environment (Diener, 1984; Schimmack et al., 2002). On the basis of the “top-down model,” it is hypothesized that life satisfaction would positively contribute to academic satisfaction. Some studies showed that higher life satisfaction predicted higher job and career satisfaction among adolescents (Judge and Watanabe, 1993; Diener and Tay, 2017). In addition, research showed that life satisfaction led to higher student motivation and school engagement (Lewis et al., 2011; Dilling, 2016), which predicted increased academic satisfaction (Wach et al., 2016; Johnson et al., 2017). However, few studies have further explored such findings using longitudinal research designs.

While perceived stress is commonly conceived as a precursor of life satisfaction, some research studies suggest that life satisfaction might also be an antecedent of perceived stress. For example, two studies showed that global life satisfaction was an important predictor of perceived stress in university students (Sheets et al., 1993; Saleh et al., 2017). Besides, recent longitudinal research on young ex-offenders showed that life satisfaction negatively predicted later perceived stress, but early perceived stress did not predict later life satisfaction (Tang and Chan, 2017). Another study also found that perceived stress was a mediator on the influence of global life satisfaction on post-trauma physical and psychological health (Tremblay et al., 2006). Taken together, these studies indicate that as a psychological strength, life satisfaction could also help an individual to reduce his or her perceived level of stress. Therefore, it can be asserted that life satisfaction predicts perceived academic stress over time.

Existing literature suggests that life satisfaction is not only a predictor of adolescent outcomes, but also a mediator of the influence of other personal and environmental factors on adolescent outcomes (e.g., Otero-López et al., 2011; Yamawaki et al., 2011). Particularly, three research studies revealed that satisfaction with life functioned as a mediator in the impact of PYD qualities on problem behaviors among Chinese youth in Hong Kong (Sun and Shek, 2010, 2012, 2013). Another research also revealed that life satisfaction mediated the influence of recognition for positive behavior (an indicator of PYD) on personal growth initiatives among university students (Stevic and Ward, 2008). Furthermore, Lambert et al. (2009) revealed that satisfaction with life mediated the predictive effect of gratitude on materialism. These studies suggest the mediating role of life satisfaction in the influence of PYD qualities on other adolescent developmental outcomes, such as academic satisfaction and perceived academic stress.

The existing literature in this field shows several limitations. First, while there are studies on PYD qualities and adolescent outcomes such as problem behavior, the predictive role of PYD qualities in adolescent academic well-being indexed by academic satisfaction and academic stress has not been systematically investigated. Second, while studies revealed that both PYD qualities and life satisfaction were linked to adolescent outcomes, whether satisfaction with life has a mediating effect on the influence of PYD qualities on adolescent outcomes is unclear. As studies showed the mediating effect of life satisfaction on the influence of PYD qualities on other adolescent outcomes such as problem behavior (Sun and Shek, 2010, 2012), it is interesting to investigate the mediating effect of life satisfaction on the impact of PYD qualities on academic well-being. Third, while adolescents’ academic development is an important research area, most of the extant studies mainly focused on academic performance and achievement, with few studies investigating academic satisfaction and stress (i.e., academic well-being) as outcomes. Fourth, the existing studies on PYD qualities and life satisfaction mainly adopted cross-sectional research designs, with very few longitudinal studies. Finally, as most of the existing PYD studies were performed in Western contexts, research on PYD qualities and adolescent outcomes in non-Western contexts such as Chinese cultures is strongly needed.

Research in this area would be particularly meaningful in the context of Hong Kong, which inherits the Chinese cultural tradition of morbid emphasis on academic excellence. At the same time, Hong Kong has also experienced a significant and systematic educational reform in the past decade. Under strong Chinese cultural influence, Hong Kong families and parents still strongly emphasize academic excellence in their children, which might cause high academic stress among Hong Kong adolescents. Adding to this situation is a structural change of the secondary school curriculum in Hong Kong since 2009. A “New Secondary School Curriculum” has been implemented that aims at building a more flexible learning system, promoting all-around development of students and developing their life-long skills for the 21st century (Wong, 2011; Cheung and Jhaveri, 2016). The new curriculum has brought about significant change in secondary school students’ study: it shortens students’ senior secondary study from four years to three years, changes students’ examination requirements, and incorporates a compulsory new interdisciplinary subject named “Liberal Studies” (Shek and Leung, 2014; Tan, 2019). Although the intention is good, the new curriculum might increase students’ academic stress. Not only do the shortened study years cause stress for students in their preparation for university entrance examinations, but they also increase pressure for students who are not familiar with the subject and how it is taught (Shek and Li, 2016; Tan, 2019). Therefore, it is important and meaningful to identify personal strengths such as PYD qualities and satisfaction with life that protect Hong Kong students from the development of higher academic stress and promote students’ academic satisfaction under the context of educational transformation.

Adopting a longitudinal research design, the present study attempted to investigate the influence of PYD qualities and life satisfaction on academic satisfaction and academic stress, with life satisfaction hypothesized to be a mediator of the influence of PYD qualities on academic satisfaction and academic stress. This study utilized data from a six-year longitudinal project on the “positive youth development” of Hong Kong adolescents. Three waves of data, i.e., Wave 1, 3, and 6, were used in this study to test the longitudinal mediating effect as the three waves have relatively equal time span. Figure 1 shows the hypothesized mediation model. Based on the above discussion, the following seven hypotheses were formed:

FIGURE 1
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Figure 1. The hypothesized model (life satisfication is hypothesized as a mediator on the relationship between positive youth development qualities to academic satisfication and academic stress). “+” sign indicates positive direction; “-“indicates negative direction.

• PYD qualities at Wave 1 would positively predict academic satisfaction at Wave 6 (hypothesis 1a) but negatively predict academic stress at Wave 6 (hypothesis 1b).

• PYD qualities at Wave 1 would positively predict life satisfaction at Wave 3 (hypothesis 2a) and life satisfaction at Wave 3 would positively predict academic satisfaction at Wave 6 (hypothesis 2b) but negatively predict academic stress at Wave 6 (hypothesis 2c).

• Life satisfaction at Wave 3 would mediate the influence of PYD qualities at Wave 1 on academic satisfaction (hypothesis 3a) and academic stress at Wave 6 (hypothesis 3b).

Materials and Methods

Participants and Procedure

The data of this study were derived from in a large-scale project on adolescents’ positive development and its precursors as well as outcomes. The project was conducted from the 2009/2010 to 2015/2016 school years, which involved 28 randomly selected Hong Kong secondary schools. Since the 2009/2010 school year, seventh-grade students in these schools had been invited to fill out a paper and pencil questionnaire each year. Before the start of the study, formal written consent was obtained from all participating schools, students, and parents. The participating students were fully informed about the purpose of the study and principles of confidentiality.

The present study used the data collected in Waves 1, 3, and 6. The time span between Wave 1 and Wave 3 is two years (i.e., 24 months), and the time span between Wave 3 and Wave 6 is two years and 10 months (i.e., 34 months). The number of students who completed the three waves of the questionnaire was 2,312. The mean age and educational level of the participants in different waves are shown in Table 1. At Wave 1, the participants reported a mean age of 12.54 ± 0.68 years old and 51% of the participants were female students.

TABLE 1
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Table 1. Mean age and grade of the participants in different waves.

Measures

Positive Youth Development (PYD) Attributes

Positive Youth Development was assessed using a shortened version of the “Chinese Positive Youth Development Scale” (CPYDS) (Shek et al., 2007). The original version of the scale contains 90 items assessing 15 attributes of positive development: “Bonding,” “Resilience,” “Social Competence,” “Recognition for Positive Behavior,” “Emotional Competence,” “Cognitive Competence,” “Behavioral Competence,” “Moral Competence,” “Self-Determination,” “Self-Efficacy,” “Clear and Positive Identity,” “Beliefs in the Future,” “Prosocial Norms,” and “Spirituality.” In a validation study based on 5,649 Hong Kong secondary school students (Shek and Ma, 2010), the CPYDS showed stable factor structure. In another validation study based on 322 adolescents in Hong Kong (Shek et al., 2007), the scale showed acceptable reliability and criterion-related validity.

The trimmed CPYDS was based on selecting the items with higher factor loadings from each subscale. It contains 44 items measuring the 15 attributes. Some sample items are (1) “When I need help, I believe my father/mother (or guardian) will definitely help me” (“Bonding”); (2) “When facing difficulties, I do not give up easily” (“Resilience”); (3) “I can get along with other people” (“Social Competence”); and (4) “If I’m not happy, I can express my emotions properly” (“Emotional Competence”). Except for “Spiritualty,” all items were rated on a six-point scale (1 = “Strongly Disagree” and 6 = “Strongly Agree”). The items in the subscale of “Spirituality” were rated on a seven-point scale (1 = “my life is very boring/empty” and 7 = “my life is full of energy/excitement”). A higher level of positive development is represented by a higher composite score. To test the internal structure of the trimmed CPYDS, confirmatory factor analyses (CFA) were performed. The resulting global model fit indices are: χ2(795, N = 2,312) = 4137.106, p < 0.001, CFI = 0.91; TLI = 0.89; SRMR = 0.04; RMSEA = 0.043 with 90% CI [0.041, 0.044]. We also tested the local fit of the model by examining the correlation residuals. Based on Kline’s (2016) suggestion, with reference to the 1,034 correlation residuals, only 39 (4%) had absolute values greater than 0.10. The Cronbach alpha for all subscales of the trimmed CPYDS in Wave 1 ranged from 0.70 to 0.88, except for the “Self-Efficacy” subscale with a value of 0.62. The omega coefficients of all subscales also ranged from 0.70 to 0.88, except for the “Self-Efficacy” subscale which cannot yield an omega coefficient because there are only two items. All the subscales also showed acceptable mean inter-item and item-total coefficients (Table 2).

TABLE 2
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Table 2. Cronbach’s alpha, omega coefficient, mean inter-item correlation, and mean item-total correlation of different scales and subscales.

Life Satisfaction (LS)

We used the “Satisfaction with Life Scale” (SWLS) (Diener et al., 1985) to assess the participants’ global evaluation of life satisfaction. The scale comprises five items gauging global life satisfaction of individuals, applicable in different age groups. One sample item is “In most ways my life is close to my ideal.” The five items were answered on a six-point scale (1 = “Strongly Disagree” and 6 = “Strongly Agree”). A higher level of LS is represented by a higher total score. In several studies, Cronbach’s alpha of SWLS ranged from 0.77 to 0.90 (Gouveia et al., 2009; Rosengren et al., 2015). Also, in several validation studies, SWLS showed convergent validity, criterion-based validity, and test-retest reliability (Pavot et al., 1991; Gouveia et al., 2009; Rosengren et al., 2015). The present study used data of LS in Wave 3 as the mediator. Both Cronbach’s alpha and omega coefficients of SWLS in Wave 3 were 0.86 (“mean inter-item correlation” = 0.58; “mean item-total correlation” = 0.69).

Academic Stress (AS)

Two items were developed to measure students’ perceived academic stress. One item is “Do you feel pressure in your current studies?” Another item is “Do you feel pressure under the new senior secondary school curriculum?” The first item assesses the students’ subjective experience of distress in their general academic studies as a whole based on the literature on academic stress (Putwain, 2007). The second item assesses students’ subjective experience of pressure or distress specifically toward the new secondary school curriculum which is perceived as a major stressor in students’ academic study. The items were rated on a four-point scale (1 = “Not at all” and 4 = “Very much”). Higher levels of perceived academic stress are indicated by higher scores. The present study used AS in Wave 6 as one outcome variable. Cronbach’s alpha of AS for Wave 6 was 0.92 in the present study.

Academic Satisfaction

As literature suggests students’ satisfaction with their academic program is an important aspect of academic satisfaction (Marchiondo et al., 2010; Jadidian and Duffy, 2012) and because the implementation of the “New Secondary School Curriculum” in Hong Kong would have great impact on students’ satisfaction with academics, a measure was developed to gauge students’ academic satisfaction as a function of their positive feelings and perspectives on the whole new secondary school curriculum (PNSC). Originally, PNSC contained a total of 24 items among which six were reverse-coded. Answers to all items were on a six-point scale (1 = “Strongly Disagree” and 6 = “Strongly Agree”), with higher levels of satisfaction indicated by higher scores. As a reliability test showed that the six reverse-coded items had low item-total correlations with other items, the six reverse-coded items were removed from the scale. The removal of reverse-coded items was also based on the argument that negatively worded items would have negative influence on the reliability and validity of the scale, and they may not measure the same construct as positively worded items (Pilotte and Gable, 1990; Dalal and Carter, 2014). The refined PNSC contained 18 items. Conceptually, the 18 items were generated to measure four dimensions: (1) students’ fondness for, and interest in, the junior secondary school curriculum (4 items); (2) students’ perceptions of the benefits of the junior secondary curriculum in promoting positive and holistic development (5 items); (3) students’ fondness for, and interest in, the senior secondary school curriculum (4 items); and (4) students’ perceptions of the benefits of the senior secondary school curriculum in promoting personal development (5 items). The sample items are “I like the new junior/senior high school curriculum” and “The curriculum can enhance my interest in learning.”

On the basis of the new “standards for educational and psychological testing” (American Educational Research Association, 2014), we performed exploratory factor analyses (EFA) and confirmatory factor analyses (CFA) on PNSC to provide evidence for the internal structure of the scale (Kelloway, 1995; Worthington and Whittaker, 2006). The current dataset (N = 2,312, Wave 6) was randomly split into two sub-datasets: dataset A (N = 1,141) and dataset B (N = 1,171). First, we conducted EFA based on dataset A. In the initial round of EFA, “principal axis factors” (PAF) were used as the data did not meet the assumption of a multivariate normal distribution (Costello and Osborne, 2005; Goretzko et al., 2019). Promax rotation was adopted as the rotation method since the hypothesized factors were assumed to be correlated (Brown, 2009). The analyses suggested three factors based on Eigenvalues > 1. However, there were four items highly loaded on two factors, which could not generate a “simple structure,” an important criterion of EFA (Brown, 2009; Watson, 2017). As parallel analyses (PA) (Humphreys and Montanelli, 1975) and “Velicer’s Minimum Average Partial Test” (MAP) (Velicer, 1976) are two other important methods for determining factor numbers, we conducted PA and MAP using SPSS 25 to detect factor numbers. Both analyses suggested four factors should be extracted. Therefore, another round of PAF with Promax rotation was performed by fixing the factor number at four. The analyses yielded a clear and simple four primary factor structure with each item highly loaded on one factor (ranging from 0.55 to 0.99) but not on other factors according to the original conceptual model. The factor loadings are shown in Table 3. The factor correlation matrix showed that the four factors were correlated with each other (r = 0.55 to 0.77), justifying the use of Promax rotation. The four factors explained 81.563% of the item total variance. The findings also matched the conceptual model of the scale. Therefore, the four-factor structure of PNSC was adopted for CFA.

TABLE 3
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Table 3. Factor loadings of the four factors of PNSC in exploratory factor analyses based on Dataset A (N = 1141).

CFA was conducted on the four-factor model of PNSC based on dataset B. The resulting global model fit indices were: χ2(129, N = 1,171) = 840.008, p < 0.001, CFI = 0.94; TLI = 0.93; SRMR = 0.04; RMSEA = 0.069 with 90% CI [0.064, 0.073]. Based on Hu and Bentler (1999) and Kline (2011, 2016), the CFI value and TLI value were greater than or equal to 0.90, and the RMSEA value below 0.08 suggests adequate model fit. While the chi-square test rejected the model (p < 0.001), the SRMR value = 0.04 (<0.08) suggests the approximate fit of the model (Asparouhov and Muthen, 2018). In addition, among 189 correlation residuals, only 5 (3%) had an absolute value > 0.10, thus providing support for the model fit. The factor loadings ranged from 0.84 to 0.96 with the four factors all significantly positively correlated with each other (Table 4). As the four-factor model of PNSC was supported, it was adopted for further analyses in this study. Both Cronbach’s alpha and omega coefficients for the four subscales ranged from 0.94 to 0.95 (“mean inter-item correlation” ranged from 0.78 to 0.83; “mean item-total correlation” ranged from 0.86 to 0.88).

TABLE 4
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Table 4. Table 4 Factor loadings of the four factors of PNSC in confirmatory factor analyses based on Dataset B (N = 1171).

Data Analyses

Means, standard deviations, and correlations among different variables were computed first. Second, two steps (Anderson and Gerbing, 1988) were followed to examine the hypothesized mediation model by using Structural Equation Modeling (SEM) and MPLUS 8.1. First, a measurement model was tested for four inter-correlated latent variables, including Positive Youth Development (PYD, indicated by its 15 dimensions), Life Satisfaction (LS, indicated by its five items), Academic Stress (AS, indicated by its two items), and Perspective on the New Secondary School Curriculum (PNSC, indicated by its four factors as sub-latent variables, which were further indicated by their respective items). Second, on the condition of satisfactory model fit of the measurement model, the mediation model was then examined, with LS being hypothesized as the mediator on the relationship between PYD and the two indexes of academic well-being (AS and PNSC).

One assumption of SEM was the multivariate normal distribution of the data (Kaplan, 2008). This assumption was tested by MPLUS. The results showed that p < 0.001 for both multivariate skew and kurtosis tests. Therefore, MLR (“robust maximum likelihood method”) was used as the model estimation method as it is a “robust full information ML estimator” which “is not dependent on the assumption of normality,” and it “yields a robust chi-square test of model fit” (Kaplan, 2008, p.88). The MLR estimation was also adopted based on the following justifications. First, although the data of the outcome variables were collected based on a Likert scale, which is ordinal in nature, studies suggested that MLR could be used for ordinal data with five or more response categories (Byrne, 2012; Raykov, 2012; Li, 2016). Second, although there are other estimation methods suitable for ordinal data such as WLSMV, research has shown that the estimations of MLR and WLSMV are quite similar when the sample size is large (Hansson and Gustafsson, 2013) and although MLR is not “specifically developed for use with categorized data, performed surprisingly well” (Bandalos, 2014, p. 116). As the present study had a sample size of over 2,000, we used MLR as the estimation method.

The study used multiple indices to assess the fitness of the models, including CFI (“comparative fit index”), TLI (“Tucker-Lewis index”), RMSEA (“root mean square error of approximation”), and SRMR (“standardized root mean square residual”). Based on Hu and Bentler (1999) and Kline (2011, 2016), a model would be acceptable if the CFI value and TLI value are above 0.90, and the RMSEA value is below 0.08. These criteria have been widely used in many research studies not only for ML but also for MLR estimation (e.g., Boelen et al., 2010; Hill et al., 2015). Also, a model would be approximately well fit with a SRMR value below 0.08 when the chi-square test rejects the model (Asparouhov and Muthen, 2018). In addition, R software (version 3.6.3 with Lavaan) was used to test the local fit of the CFA and SEM models by examining the correlation residuals. According to Kline (2016), the local fit can be established if few (<5%) correlation residuals were smaller than 0.10. Furthermore, bias-corrected bootstrap estimation (95% confidence interval for significance testing) based on 5,000 bootstrap samples was conducted to examine the mediation effects.

Results

Descriptive Analyses

Table 5 presents the mean scores and standard deviations of different variables, and mean score correlations between different variables. As predicted, there were significant positive correlations amongst PYD, LS, and PNSC, and these variables were significantly and negatively correlated with AS.

TABLE 5
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Table 5. Means, standard deviations, and mean score correlations between different variables.

Measurement Model

The measurement model comprised four interrelated latent variables (PYD, LS, AS, and PNSC). Results showed adequate model fit: χ2(730, N = 2,312) = 5666.991, p < 0.001, CFI = 0.91; TLI = 0.91; SRMR = 0.05; RMSEA = 0.054 with 90% CI [0.053, 0.055]. The factor loadings ranged from 0.57 to 0.96 (p < 0.001), suggesting that the indicators well represented their respective latent variables.

Analyses of the Mediation Model

As the measurement model is acceptable, the mediation model (SEM model) was then examined in which PYD at Wave 1 was hypothesized to predict the two academic well-being variables (PNSC and AS) at Wave 6, with LS at Wave 3 mediating the relationships. Considering that the participants came from 28 schools, we used Type = complex option in MPLUS to control the school influence. Meanwhile, we controlled the age and gender effects in the model. The resulting global model fit indices were: χ2(804, N = 2,312) = 6058.749, p < 0.001, CFI = 0.91; TLI = 0.90, SRMR = 0.05, RMSEA = 0.054 with 90% CI [0.052, 0.055]. Figure 2 shows the model. For local fit, results showed that among the 945 pairs of correlation residuals, 48 (5%) had absolute values over 0.10, which gave marginal support for the local fit of the model. However, when the global fit and local fit findings were taken into account, the evidence provided reasonable support for the proposed model. The estimates of the relationships between different latent variables are presented in Table 6. As shown in Table 6, Wave 1 PYD positively predicted Wave 6 PNSC (total effect: ß = 0.288, p < 0.001) but negatively predicted Wave 6 AS (total effect: ß = -0.063, p = 0.01). Therefore, Hypotheses 1a and 1b were supported.

FIGURE 2
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Figure 2. The structural equation model on the mediating effects of life satisfication on the influence of youth development qualities on academic satisfication and academic strees. ***p < 0.001;**p < 0.01;*p < 0.05. pyd = positive youth development qualities at Wave 1; Is = life satisfication at Wave 3; as = academic strees at Wave 6; pnsc = satisfication with new secondary school curriculam at Wave 6; pnjscf1, pnjscf2, pnsscf1, and pnsscf2 are four factors of pnsc; m1 and m2 are two convariates: m1 = age, m2 = gender. The factors loadings for each latent variable were estimated by fixing one factor loading (unstandardized) to 1.0. The factor loadings shown in figure are standardized factor loadings. The R-square values for the two endogenous variables: as and pnsc are 0.024 and 0 147, respectively.

TABLE 6
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Table 6. Estimated predicting effects of PYD on AS and PNSC with the mediating effect of LS in SEM.

In addition, Wave 1 PYD positively predicted Wave 3 LS (ß = 0.409, p < 0.001) and Wave 3 LS positively predicted Wave 6 PNSC (ß = 0.271, p < 0.001) but negatively predicted Wave 6 AS (ß = -0.113, p < 0.001). Therefore, Hypotheses 2a–2c were supported. Furthermore, Wave 3 LS partially mediated the association between PYD (Wave 1) and PNSC (Wave 6) due to the both significant indirect effect (ß = 0.111, p < 0.001) and direct effect (ß = 0.177, p < 0.001), which supported Hypothesis 3a. LS (Wave 3) fully mediated the effect of PYD (Wave 1) on AS (Wave 6) based on the significant indirect effect (ß = -0.046, p < 0.001) but insignificant direct effect (ß = -0.017, p > 0.05). Therefore, Hypothesis 3b was supported. Besides, the estimated correlations among different latent variables were shown in Table 7 where PYD, LS, and PNSC were positively correlated with each other but they were negatively correlated with AS.

TABLE 7
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Table 7. Estimated correlations between different latent variables.

To examine the mediating effects further, “bias-corrected bootstrap” estimation based on 5,000 bootstrap samples was also conducted on the mediation model. As shown in Table 8, the 95% confidence intervals for all the two indirect effects with LS as mediator did not cross zero, indicating the significance of these mediation effects.

TABLE 8
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Table 8. Results of bias-corrected bootstrap estimation for the mediation model.

Discussion

This study investigated the predictive effects of PYD qualities and life satisfaction on academic well-being indicated by academic satisfaction and academic stress among Hong Kong adolescents. The study is significant for two reasons. First, as few studies have examined the mediating effect of global life satisfaction on the influence of PYD qualities on adolescent developmental outcomes, this study is an interesting addition to the literature. Second, we examined academic satisfaction and academic stress, which are two important aspects of adolescents’ academic well-being (Trógolo and Medrano, 2012; Wach et al., 2016). As existing research on academic satisfaction and stress focused more on the environmental influences (e.g., Tessema et al., 2012) with relative negligence of the role of personal factors (particularly PYD attributes), studies on the role of PYD qualities in these two areas of adolescent academic well-being are very important. Besides, the related findings would shed light not only on research but also on intervention programs that may promote academic well-being among high school students.

The findings support Hypothesis 1a, showing that PYD qualities at Wave 1 positively predicted the participants’ satisfaction with their academic study curriculum at Wave 6. Theoretically, as a positively developed adolescent would possess high competence in different domains and develop a high self-efficacy (Catalano et al., 2004; Lerner, 2005), he or she would feel more capable and have better planning, self-management, and self-regulation in academic study. A positively developing adolescent would also gain more social support from peers and teachers in their academic study, and they would have higher spirituality and resilience in facing difficulties. The present study is pioneering in that it provides direct evidence of the positive influence of PYD on adolescents’ academic satisfaction. The findings are consistent with some isolated research findings that PYD indicators positively predicted academic satisfaction and school satisfaction (Lent et al., 2007; Sun, 2016; Urquijo and Extremera, 2017). This study expanded the empirical evidence of the value of PYD development, showing that PYD qualities would provide positive influence on adolescents in different aspects, including their satisfaction with their academic studies.

The results also support Hypothesis 1b, revealing that PYD at Wave 1 negatively predicted perceived academic stress at Wave 6. The finding is consistent with a few studies showing that some personal strength factors negatively predicted perceived academic stress. For example, a study showed that perceived stress was predicted by the ability of emotional regulation and management (Bao et al., 2015), which is one important indicator of PYD. Another study revealed that character strength such as grit negatively predicted perceived stress level among college students (Lee, 2017), which strongly suggests that stress could be interpreted as “the subjective psychological appraisal of an event as threatening or not” and “psychological resources may influence one’s appraisal of an event” (Lee, 2017, 148–149). Positive youth development qualities such as psychosocial competence, confidence, character strengths, and important connections (Catalano et al., 2004; Lerner, 2005) are essential psychological resources for adolescents. Adolescents with higher levels of PYD qualities would possess more psychological resilience to appraise a negative or threatening event more positively, which leads to reduced stress in different domains, including academic stress.

The results support Hypothesis 2a, showing that PYD (Wave 1) positively predicted LS (Wave 3). This is in line with the literature that psychological well-being and different indicators of PYD positively predicted their life satisfaction: one study showed that social support and self-esteem were important antecedents of satisfaction with life (Chen et al., 2017); Howell et al. (2013) found that meaning in life (a PYD quality) positively predicted satisfaction with life; Rey et al. (2011) revealed that both emotional intelligence and self-esteem (PYD qualities) positively predicted satisfaction with life. As existing studies commonly focused on one to two PYD qualities in a single study, the present study’s focus on different dimensions of PYD qualities and adoption of longitudinal research method contributes to the existing literature by suggesting that PYD qualities are important precursor of satisfaction with life.

The results also support Hypothesis 2b, showing that satisfaction with life at Wave 3 positively predicted students’ satisfaction with their academic study programs at Wave 6. The findings support the “top-down model” that global life satisfaction is a relatively stable psychological strength which would influence an individual’s perceptions of specific aspects of life or experiences (Diener, 1984; Scherpenzeel and Saris, 1996). While no study has been done to examine the relationship between global satisfaction with life and specific satisfaction with academic study, the results are consistent with some existing studies supporting the “top-down model” that global satisfaction with life would influence satisfaction with specific life aspects such as job satisfaction, career satisfaction, and relationship satisfaction (Judge and Watanabe, 1993; Diener and Tay, 2017). Hence, the present study constitutes a theoretical advance in this area.

Hypothesis 2c was also supported by the present study which showed that life satisfaction (Wave 3) negatively predicted academic stress (Wave 6). This finding strengthens the existing literature suggesting that life satisfaction could be a precursor or antecedent of perceived stress (e.g., Saleh et al., 2017; Tang and Chan, 2017). Theoretically, as “a global propensity to experience things in positive ways” (Diener, 1984, p.565), higher life satisfaction would enable an individual to appraise an environmental stressor, such as that of academic studies, as less negative and devastating as well as to cope more positively, which would eventually lead to a lower level of stress. This conjecture constitutes an exciting area for future research.

Finally, the results of the present study support Hypotheses 3a and 3b, showing that life satisfaction partially mediated the positive influence of PYD on academic satisfaction but fully mediated the negative influence of PYD on academic stress. The findings suggest that global life satisfaction is an important mechanism underlying the relationship between PYD and academic well-being, where a higher level of PYD would lead to a higher level of satisfaction with academic study but a lower level of perceived stress. The results are significant as very few studies have investigated the mediating function of global satisfaction with life on the relationship between psychological well-being such as PYD qualities and adolescent academic well-being. Particularly, the extant literature on the mediation role of satisfaction with life focused mainly on satisfaction with life being an underlying mechanism in the relationship between environmental antecedents (e.g., stressful life events and authoritative parenting) and adolescents’ problem behaviors such as internalizing problems (e.g., McKnight et al., 2002; Suldo and Huebner, 2004). Only few studies revealed that life satisfaction mediated the impact of PYD on adolescent problem behavior (Sun and Shek, 2010, 2012, 2013). Therefore, the results of this study expand the existing literature by highlighting the important role of satisfaction with life in the relationship between PYD and adolescents’ academic well-being.

This study has important practical implications. It provides school educators with important knowledge about the important role of PYD and life satisfaction in adolescent academic well-being. Therefore, school educators and administrators could try to promote their students’ PYD and life satisfaction through different measures or interventions. One possibility is to implement PYD programs to promote life satisfaction of the program participants. In the Chinese context, the Project P.A.T.H.S. has been shown to promote life satisfaction in Chinese high school students in Hong Kong (Ma et al., 2019a,b) and China (Zhu and Shek, 2020). The development and implementation of educational and intervention programs to promote students’ PYD qualities and life satisfaction would be very meaningful for helping educators and school administrators to reduce the academic stress of students and elevate their academic satisfaction.

Despite the pioneering nature of the study in the field of adolescent life satisfaction and academic well-being, this study has limitations. First, this study only tested the predictive role of PYD qualities in adolescent academic well-being indexed by academic satisfaction and academic stress, and the mediating effect of life satisfaction on the relationship. Because the literature also suggests the predictive role of stress and domain-specific satisfaction in life satisfaction, alternative models should be tested in future research to further advance the understanding of the relationships among the factors under study. Second, despite having a large sample size, this study was mainly based on Hong Kong secondary school students. Studies on adolescents in other Chinese cultures and non-Chinese cultures should also be conducted to replicate the results. Third, it is also interesting to examine whether the mediation effects and the relationships among variables are the same for boys and girls. Future research is needed in this direction. Fourth, some subscales of CPYDS had relatively lower reliability, which might be due to the fewer item numbers, although the “mean inter-item correlation” and “mean item-total correlation” values are acceptable. Future research could be conducted by using the original version of CPYDS to retest the mediation model. Despite these limitations, this study is pioneering in that it examines the longitudinal predictive role of PYD qualities in academic satisfaction and stress and in uncovering the underlying mechanism played by life satisfaction.

Data Availability Statement

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

This study was approved by the Human Subjects Ethics Sub-Committee (HSESC) (or its Delegate) of The Hong Kong Polytechnic University. Formal written consent was obtained from all participating schools, students, and their parents.

Author Contributions

DS conceived of the research, contributed to all stages of the research work, and critically revised the different versions of the manuscript drafted by WC. WC conducted data analyses, drafted the manuscript, and revised the manuscript based on the comments provided by DS.

Funding

The Project P.A.T.H.S. and this manuscript are financially supported by the Hong Kong Jockey Club Charities Trust.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Albarrak, A., Mohammed, R., Abalhassan, M. F., and Almutairi, N. K. (2013). Academic satisfaction among traditional and problem based learning medical students. A comparative study. Saudi Med. J. 34, 1179–1188.

Google Scholar

American Educational Research Association (2014). Standards for Educational and Psychological Testing, 3rd Edn, Washington, DC: American Educational Research Association.

Google Scholar

Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychol. Bull. 103, 411–423. doi: 10.1037/0033-2909.103.3.411

CrossRef Full Text | Google Scholar

Ang, R. P., and Huan, V. S. (2006). Relationship between academic stress and suicidal ideation: testing for depression as a mediator using multiple regression. Child. Psychiatry Hum. Dev. 37, 133–143. doi: 10.1007/s10578-006-0023-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Asparouhov, T., and Muthen, B. (2018). SRMR in MPLUS. Available online at: http://www.statmodel.com/download/SRMR2.pdf (accessed June 18, 2020).

Google Scholar

Bandalos, D. L. (2014). Relative performance of categorical diagonally weighted least squares and robust maximum likelihood estimation. Struct. Equ. Model. 21, 102–116. doi: 10.1080/10705511.2014.859510

CrossRef Full Text | Google Scholar

Bao, X., Xue, S., and Kong, F. (2015). Dispositional mindfulness and perceived stress: the role of emotional intelligence. Pers. Indiv. Differ. 78, 48–52. doi: 10.1016/j.paid.2015.01.007

CrossRef Full Text | Google Scholar

Bedewy, D., and Gabriel, A. (2015). Examining perceptions of academic stress and its sources among university students: the perception of academic stress scale. Health. Psychol. Open 2, 1–9. doi: 10.1177/2055102915596714

PubMed Abstract | CrossRef Full Text | Google Scholar

Benson, P. L., Scales, P. C., Hamilton, S. F., and Sesma, J. R. A. (2006). “Positive youth development: theory, research, and applications,” in Handbook of Child Psychology. Volume I: Theoretical Models of Human Development, eds D. William and R. M. Lerner (Hoboken, NJ: John Wiley & Sons), 894–941.

Google Scholar

Boelen, P. A., van de Schoot, R., van den Hout, M. A., de Keijser, J., and van den Bout, J. (2010). Prolonged grief disorder, depression, and posttraumatic stress disorder are distinguishable syndromes. J. Affect Disord. 125, 374–378. doi: 10.1016/j.jad.2010.01.076

PubMed Abstract | CrossRef Full Text | Google Scholar

Brown, J. D. (2009). Choosing the right type of rotation in PCA and EFA. JALT Test. Eval. SIG Newslett. 13, 20–25.

Google Scholar

Byrne, B. M. (2012). Structural Equation Modeling With Mplus: Basic Concepts, Applications, and Programming. New York, NY: Taylor & Francis Group.

Google Scholar

Catalano, R. F., Berglund, M. L., Ryan, J. A. M., Lonczak, H. S., and Hawkins, J. D. (2004). Positive youth development in the United States: research findings on evaluations of positive youth development programs. Ann. Am. Acad. Pol. Soc. Sci. 591, 98–124. doi: 10.1177/0002716203260102

CrossRef Full Text | Google Scholar

Charkhabi, M., Azizi Abarghuei, A., and Hayati, D. (2013). The association of academic burnout with self-efficacy and quality of learning experience among Iranian students. Springerplus 2, 1–5. doi: 10.1186/2193-1801-2-677

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, W., Zhang, D., Pan, Y., Hu, T., Liu, G., and Luo, S. (2017). Perceived social support and self-esteem as mediators of the relationship between parental attachment and life satisfaction among Chinese adolescents. Pers. Indiv. Differ. 108, 98–102. doi: 10.1016/j.paid.2016.12.009

CrossRef Full Text | Google Scholar

Cheung, C., and Jhaveri, A. D. (2016). Developing students’ critical thinking skills through visual literacy in the New Secondary School Curriculum in Hong Kong. Asia. Pac. J. Educ. 36, 379–389. doi: 10.1080/02188791.2014.959470

CrossRef Full Text | Google Scholar

Ciocanel, O., Power, K., Eriksen, A., and Gillings, K. (2017). Effectiveness of positive youth development interventions: a meta-analysis of randomized controlled trials. J. Youth. Adolesc. 46, 483–504. doi: 10.1007/s10964-016-0555-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Costello, A. B., and Osborne, J. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Pract. Assess. Res. Eval. 10:7. doi: 10.7285/jyj1-4868

CrossRef Full Text | Google Scholar

Dalal, D. K., and Carter, N. T. (2014). “Negatively worded items negatively impact survey research,” in More Statistical and Methodological Myths and Urban Legends: Doctrine, Verity and Fable in Organizational and Social Sciences, eds C. E. Lance and R. J. Vandenberg (London: Routledge), 112–132.

Google Scholar

Damon, W. (2004). What is positive youth development? Ann. Am. Acad. Pol. Soc. Sci. 591, 13–24. doi: 10.1177/0002716203260092

CrossRef Full Text | Google Scholar

Diener, E. (1984). Subjective well-being. Psychol. Bull. 95, 542–575. doi: 10.1037/0033-2909.95.3.542

CrossRef Full Text | Google Scholar

Diener, E., Emmons, R. A., Larsen, R. J., and Griffin, S. (1985). The satisfaction with life scale. J. Pers. Assess. 49, 71–75. doi: 10.1207/s15327752jpa4901_13

PubMed Abstract | CrossRef Full Text | Google Scholar

Diener, E., and Tay, L. (2017). “A scientific review of the remarkable benefits of happiness for successful and healthy living,” in Happiness: Transforming the Development Landscape, eds E. Diener and L. Tay (Thimphu, BT: Center for Bhutan Studies and GNH), 90–117.

Google Scholar

Dilling, R. L. (2016). Life Satisfaction: A Study of Engagement and the Academic Progress of High School Students With Specific Learning Disabilities. Ph. D thesis, Liberty University, Lynchburg, VA.

Google Scholar

Durlak, J. A., Weissberg, R. P., and Pachan, M. (2010). A meta-analysis of after-school programs that seek to promote personal and social skills in children and adolescents. Am. J. Commun. Psychol. 45, 294–309. doi: 10.1007/s10464-010-9300-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Eichas, K., Albrecht, R. E., Garcia, A. J., Ritchie, R. A., Varela, A., Garcia, A., et al. (2010). Mediators of positive youth development intervention change: promoting change in positive and problem outcomes? Child. Youth Care Forum. 39, 211–237. doi: 10.1007/s10566-010-9103-9

CrossRef Full Text | Google Scholar

Gilman, R., and Huebner, S. (2003). A review of life satisfaction research with children and adolescents. Sch. Psychol. Q. 18, 192–205. doi: 10.1521/scpq.18.2.192.21858

CrossRef Full Text | Google Scholar

Giota, J., and Gustafsson, J. E. (2017). Perceived demands of schooling, stress and mental health: changes from Grade 6 to Grade 9 as a function of gender and cognitive ability. Stress Health 33, 253–266. doi: 10.1002/smi.2693

PubMed Abstract | CrossRef Full Text | Google Scholar

Goretzko, D., Pham, T. T. H., and Bühner, M. (2019). Exploratory factor analysis: current use, methodological developments and recommendations for good practice. Curr. Psychol. doi: 10.1007/s12144-019-00300-2

CrossRef Full Text | Google Scholar

Gouveia, V. V., Milfont, T. L., da Fonseca, P. N., and Coelho, J. A. P. (2009). Life satisfaction in Brazil: testing the psychometric properties of the Satisfaction with Life Scale (SWLS) in five Brazilian samples. Soc. Indic. Res. 90, 267–277. doi: 10.1007/s11205-008-9257-0

CrossRef Full Text | Google Scholar

Hansson, A., and Gustafsson, J. E. (2013). Measurement invariance of socioeconomic status across migrational background. Scand. J. Educ. Res. 57, 148–166. doi: 10.1080/00313831.2011.625570

CrossRef Full Text | Google Scholar

Hill, R. M., Rey, Y., Marin, C. E., Sharp, C., Green, K. L., and Pettit, J. W. (2015). Evaluating the interpersonal needs questionnaire: comparison of the reliability, factor structure, and predictive validity across five versions. Suicide Life Threat Behav. 45, 302–314. doi: 10.1111/sltb.12129

PubMed Abstract | CrossRef Full Text | Google Scholar

Howell, A., Passmore, H., and Buro, K. (2013). Meaning in nature: meaning in life as a mediator of the relationship between nature connectedness and wellbeing. J. Happiness Stud. 14, 1681–1696. doi: 10.1007/s10902-012-9403-x

CrossRef Full Text | Google Scholar

Hu, L., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criterial versus new alternatives. Struct. Equ. Model. 6, 1–55. doi: 10.1080/10705519909540118

CrossRef Full Text | Google Scholar

Huan, V. S., Yeo, L. S., Ang, R. P., and Chong, W. H. (2006). The influence of dispositional optimism and gender on adolescents’ perception of academic stress. Adolescence 41, 533–546.

Google Scholar

Huebner, E. S., Suldo, S. M., Smith, L. C., and McKnight, C. G. (2004). Life satisfaction in children and youth: empirical foundations and implications for school psychologists. Psychol. Sch. 41, 81–93. doi: 10.1002/pits.10140

CrossRef Full Text | Google Scholar

Humphreys, L. G., and Montanelli, R. G. Jr. (1975). An investigation of the parallel analysis criterion for determining the number of common factors. Multivar. Behav. Res. 10, 193–205. doi: 10.1207/s15327906mbr1002_5

CrossRef Full Text | Google Scholar

Hystad, S. W., Eid, J., Laberg, J. C., Johnsen, B. H., and Bartone, P. T. (2009). Academic stress and health: exploring the moderating role of personality hardiness. Scand. J. Educ. Res. 53, 421–429. doi: 10.1080/00313830903180349

CrossRef Full Text | Google Scholar

Jadidian, A., and Duffy, R. D. (2012). Work volition, career decision, self-efficacy, and academic satisfaction: an examination of mediators and moderators. J. Career Assess. 20, 154–165. doi: 10.1177/1069072711420851

CrossRef Full Text | Google Scholar

Johnson, D. M., Edgar, L. D., Shoulders, C. W., Graham, D. L., and Rucker, J. K. (2017). Relationship between engagement and satisfaction among seniors at a mid-south land grant university. Coll. Stud. J. 50, 335–346.

Google Scholar

Judge, T. A., and Watanabe, S. (1993). Another look at the job satisfaction-life satisfaction relationship. J. Appl. 78, 939–948. doi: 10.1037/0021-9010.78.6.939

CrossRef Full Text | Google Scholar

Kaplan, D. (2008). Structural Equation Modeling: Foundations and Extensions. Thousand Oaks, CA: SAGE Publications.

Google Scholar

Kelloway, E. K. (1995). Structural equation modelling in perspective. J. Organ. Behav. 16, 215–224. doi: 10.1002/job.4030160304

CrossRef Full Text | Google Scholar

Kline, R. B. (2011). “Convergence of structural equation modeling and multilevel modeling,” in Handbook of Methodological Innovation, ed. M. Williams (Thousand Oaks, CA: Sage), 562–589. doi: 10.4135/9781446268261.n31

CrossRef Full Text | Google Scholar

Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling. New York, NY: Guilford.

Google Scholar

Lambert, N. M., Fincham, F. D., Stillman, T. F., and Dean, L. R. (2009). More gratitude, less materialism: the mediating role of life satisfaction. J. Posit. Psychol. 4, 32–42. doi: 10.1080/17439760802216311

CrossRef Full Text | Google Scholar

Lee, W. W. S. (2017). Relationships among grit, academic performance, perceived academic failure, and stress in associate degree students. J. Adolesc. 60, 148–152. doi: 10.1016/j.adolescence.2017.08.006

PubMed Abstract | CrossRef Full Text | Google Scholar

Lent, R. W., Singley, D., Sheu, H., Schmidt, J. A., and Schmidt, L. C. (2007). Relation of social-cognitive factors to academic satisfaction in engineering students. J. Career. Assess. 15, 87–97. doi: 10.1177/1069072706294518

CrossRef Full Text | Google Scholar

Lerner, J. V., Phelps, E., Forman, Y., and Bowers, E. (2009). “Positive youth development,” in Handbook of Adolescent Psychology, eds R. M. Lerner and L. Steinberg (Hoboken, NJ: John Wiley & Sons), 524–558.

Google Scholar

Lerner, R. M. (2005). Promoting positive youth development: theoretical and empirical bases. Paper Presented at the White Paper Prepared for Workshop on the Science of Adolescent Health and Development, National Research Council, Washington, DC.

Google Scholar

Lewis, A. D., Huebner, E. S., Malone, P. S., and Valois, R. F. (2011). Life satisfaction and student engagement in adolescents. J. Youth. Adolesc. 40, 249–262. doi: 10.1007/s10964-010-9517-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, C. (2016). Confirmatory factor analysis with ordinal data: comparing robust maximum likelihood and diagonally weighted least squares. Behav. Res. 48, 936–949. doi: 10.3758/s13428-015-0619-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Lin, S., and Huang, Y. (2013). Life stress and academic burnout. Act. Learn. High. Educ. 15, 77–90. doi: 10.1177/1469787413514651

CrossRef Full Text | Google Scholar

Liu, Y. (2015). The longitudinal relationship between Chinese high school students’ academic stress and academic motivation. Learn. Individ. Differ. 38, 123–126. doi: 10.1016/j.lindif.2015.02.002

CrossRef Full Text | Google Scholar

Ma, C. M. S., Shek, D. T. L., and Chen, J. M. T. (2019a). Changed in the participants in a community-based positive youth development program in Hong Kong: objective outcome evaluation using a one-group pretest-posttest design. App. Res. Qual. Life 14, 961–979. doi: 10.1007/s11482-018-9632-1

CrossRef Full Text | Google Scholar

Ma, C. M. S., Shek, D. T. L., and Leung, H. (2019b). Evaluation of a positive youth development program in Hong Kong: a replication. Res. Soc. Work Pract. 29, 808–819. doi: 10.1177/1049731518806579

CrossRef Full Text | Google Scholar

Marchiondo, K., Marchiondo, L. A., and Lasiter, S. (2010). Faculty incivility: effects on program satisfaction of BSN students. J. Nurs. Educ. 49, 608–614. doi: 10.3928/01484834-20100524-05

PubMed Abstract | CrossRef Full Text | Google Scholar

McKnight, C. G., Huebner, E. S., and Suldo, S. (2002). Relationships among stressful life events, temperament, problem behavior, and global life satisfaction in adolescents. Psychol. Sch. 39, 677–687. doi: 10.1002/pits.10062

CrossRef Full Text | Google Scholar

Mohamad, M., Mohammad, M., Mamat, I., and Mamat, M. (2014). Modelling positive development, life satisfaction, and problem behavior among youths in Malaysia. World Appl. Sci. J. 32, 231–238.

Google Scholar

Otero-López, J. M., Pol, E. V., Bolaño, C. C., and Mariño, M. J. S. (2011). Materialism, life-satisfaction and addictive buying: examining the causal relationships. Pers. Indiv. Differ. 50, 772–776. doi: 10.1016/j.paid.2010.12.027

CrossRef Full Text | Google Scholar

Pavot, W., Diener, E., Colvin, R., and Sandvik, E. (1991). Further validation of the satisfaction with life scale: evidence for the cross-method convergence of well-being measures. J. Pers. Assess. 57, 149–161. doi: 10.1207/s15327752jpa5701_17

PubMed Abstract | CrossRef Full Text | Google Scholar

Pilotte, W. J., and Gable, R. K. (1990). The impact of positive and negative item stems on the validity of a computer anxiety scale. Educ. Psychol. Meas. 50, 603–610. doi: 10.1177/0013164490503016

CrossRef Full Text | Google Scholar

Proctor, C. L., Linley, P. A., and Maltby, J. (2009). Youth life satisfaction: a review of the literature. J. Happiness. Stud. 10, 583–630. doi: 10.1007/s10902-008-9110-9

CrossRef Full Text | Google Scholar

Putwain, D. (2007). Researching academic stress and anxiety in students: some methodological considerations. Br. Educ. Res. J. 33, 207–219. doi: 10.1080/01411920701208258

CrossRef Full Text | Google Scholar

Raykov, T. (2012). “Scale construction and development using structural equation modeling,” in Handbook of Structural Equation Modeling, ed. R. H. Hoyle (New York, NY: Guildford Press), 472–492.

Google Scholar

Rayle, A. D., and Chung, K. (2007). Revisiting first-year college students’ mattering: social support, academic stress, and the mattering experience. J. Coll. Stud. Ret. 9, 21–37. doi: 10.2190/x126-5606-4g36-8132

PubMed Abstract | CrossRef Full Text | Google Scholar

Rey, L., Extremera, N., and Pena, M. (2011). Perceived emotional intelligence, self-esteem and life satisfaction in adolescents. Interv. Psicosoc. 20, 227–234. doi: 10.5093/in2011v20n2a10

CrossRef Full Text | Google Scholar

Rosengren, L., Jonasson, S. B., Brogardh, C., and Lexell, J. (2015). Psychometric properties of the Satisfaction With Life Scale in Parkinson’s disease. Acta. Neurol. Scand. 132, 164–170. doi: 10.1111/ane.12380

PubMed Abstract | CrossRef Full Text | Google Scholar

Saleh, D., Camart, N., and Romo, L. (2017). Predictors of stress in college students. Front. Psychol. 8:19. doi: 10.3389/fpsyg.2017.00019

PubMed Abstract | CrossRef Full Text | Google Scholar

Scherpenzeel, A., and Saris, W. (1996). Causal direction in a model of life satisfaction: the top-down/bottom-up controversy. Soc. Indic. Res. 38, 161–180. doi: 10.1007/BF00300457

CrossRef Full Text | Google Scholar

Schimmack, U., Diener, E., and Oishi, S. (2002). Life-satisfaction is a momentary judgement and a stable personality characteristic: the use of chronically accessible and stable resources. J. Pers. 70, 345–384. doi: 10.1111/1467-6494.05008

PubMed Abstract | CrossRef Full Text | Google Scholar

Schwartz, S. J., Phelps, E., Lerner, J. V., Huang, S., Brown, H., Lewin-Bizan, S., et al. (2010). Promotion as prevention: positive youth development as protective against tobacco, alcohol, illicit drug, and sex initiation. Appl. Dev. Sci. 14, 197–211. doi: 10.1080/10888691.2010.516186

CrossRef Full Text | Google Scholar

Sheets, K. J., Gorenflo, D. W., and Forney, M. A. (1993). Personal and behavioral variables related to perceived stress of second-year medical students. Teach. Learn. Med. 5, 90–95. doi: 10.1080/10401339309539598

CrossRef Full Text | Google Scholar

Shek, D. T. L., Dou, D., Zhu, X., and Chai, W. Y. (2019). Positive youth development: current perspectives. Adolesc. Health Med. 10, 131–141. doi: 10.2147/AHMT.S179946

PubMed Abstract | CrossRef Full Text | Google Scholar

Shek, D. T. L., and Leung, H. (2014). “Perceived family quality of life, school competence, and academic adjustment among early adolescents in Hong Kong,” in Chinese Adolescents in Hong Kong. Quality of Life in Asia, eds D. Shek, R. Sun, and C. Ma (Cham: Springer), 71–91. doi: 10.1007/978-981-287-143-5_5

CrossRef Full Text | Google Scholar

Shek, D. T. L., and Li, X. (2016). Perceived school performance, life satisfaction, and hopelessness: a 4-year longitudinal study of adolescents in Hong Kong. Soc. Indic. Res. 126, 921–934. doi: 10.1007/s11205-015-0904-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Shek, D. T. L., and Ma, C. M. S. (2010). Dimensionality of the Chinese Positive Youth Development Scale: confirmatory factor analyses. Soc. Indic. Res. 98, 41–59. doi: 10.1007/s11205-009-9515-9

CrossRef Full Text | Google Scholar

Shek, D. T. L., Siu, A. M. H., and Lee, T. Y. (2007). The chinese positive youth development scale: a validation study. Res. Soc. Work. Pract. 17, 380–391. doi: 10.1177/1049731506296196

CrossRef Full Text | Google Scholar

Shek, D. T. L., and Wu, F. K. Y. (2016). Positive youth development and academic behavior in Chinese secondary school students in Hong Kong. Int. J. Disabil. Hum. Dev. 15, 455–459. doi: 10.1515/ijdhd-2017-5012

CrossRef Full Text | Google Scholar

Shek, D. T. L., and Zhu, X. (2018). Self-reported risk and delinquent behavior and problem behavioral intention in Hong Kong adolescents: the role of moral competence and spirituality. Front. Psychol. 9:430. doi: 10.3389/fpsyg.2018.00430

PubMed Abstract | CrossRef Full Text | Google Scholar

Sheu, H., Mejia, A., Rigali-Oiler, M., Prime, D. R., and Chong, S. S. (2016). Social cognitive predictors of academic and life satisfaction: measurement and structural equivalence across three racial/ethnic groups. J. Couns. Psychol. 63, 460–474. doi: 10.1037/cou0000158

PubMed Abstract | CrossRef Full Text | Google Scholar

Shin, H., Lee, J., Kim, B., and Lee, S. M. (2012). Students’ perceptions of parental bonding styles and their academic burnout. Asia Pacific Educ. Rev. 13, 509–517. doi: 10.1007/s12564-012-9218-9

CrossRef Full Text | Google Scholar

Singh, K., Granville, M., and Dika, S. (2002). Mathematics and science achievement: effects of motivation, interest, and academic engagement. J. Educ. Res. 95, 323–332. doi: 10.1080/00220670209596607

CrossRef Full Text | Google Scholar

Stevic, C. R., and Ward, R. M. (2008). Initiating personal growth: the role of recognition and life satisfaction on the development of college students. Soc. Indic. Res. 89, 523–534. doi: 10.1007/s11205-008-9247-2

CrossRef Full Text | Google Scholar

Suldo, S. M., and Huebner, E. S. (2004). The role of life satisfaction in the relationship between authoritative parenting dimensions and adolescent problem behavior. Soc. Indic. Res. 66, 165–195. doi: 10.1023/B:SOCI.0000007498.62080.1e

CrossRef Full Text | Google Scholar

Sun, R. C. F. (2016). Student misbehavior in Hong Kong: the predictive role of positive youth development and school satisfaction. Appl. Res. Qual. Life 11, 773–789. doi: 10.1007/s11482-015-9395-x

CrossRef Full Text | Google Scholar

Sun, R. C. F., and Shek, D. T. L. (2010). Life satisfaction, positive youth development, and problem behavior among Chinese adolescents in Hong Kong. Soc. Indic. Res. 95, 455–474. doi: 10.1007/s11205-009-9531-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Sun, R. C. F., and Shek, D. T. L. (2012). Positive youth development, life satisfaction and problem behavior among Chinese adolescents in Hong Kong: a replication. Soc. Indic. Res. 105, 541–559. doi: 10.1007/s11205-011-9786-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Sun, R. C. F., and Shek, D. T. L. (2013). Longitudinal influences of positive youth development and life satisfaction on problem behavior among adolescents in Hong Kong. Soc. Indic. Res. 114, 1171–1197. doi: 10.1007/s11205-012-0196-4

CrossRef Full Text | Google Scholar

Tan, C. (2019). Parental responses to educational reform in Singapore, Shanghai and Hong Kong. Asia Pacific Educ. Rev. 20, 91–99. doi: 10.1007/s12564-018-9571-4

CrossRef Full Text | Google Scholar

Tang, K. N. S., and Chan, C. S. (2017). Life satisfaction and perceived stress among young offenders in a residential therapeutic community: latent change score analysis. J. Adolesc. 57, 42–53. doi: 10.1016/j.adolescence.2017.03.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Tessema, M. T., Ready, K., and Yu, W. (2012). Factors affecting college students’ satisfaction with major curriculum: evidence from nine years of data. Int. J. Humanit. Soc. Sci. 2, 34–44.

Google Scholar

Tremblay, M. A., Blanchard, C. M., Pelletier, L. G., and Vallerand, R. J. (2006). A dual route in explaining health outcomes in natural disaster. J. Appl. Soc. Psychol. 36, 1502–1522. doi: 10.1111/j.0021-9029.2006.00069.x

CrossRef Full Text | Google Scholar

Trógolo, M., and Medrano, L. A. (2012). Personality traits, difficulties in emotion regulation and academic satisfaction in a sample of argentine college students. Int. J. Psychol. Res. 5, 30–39. doi: 10.21500/20112084.734

CrossRef Full Text | Google Scholar

Urquijo, I., and Extremera, N. (2017). Academic satisfaction at university: the relationship between emotional intelligence and academic engagement. Rev. Electron. Investig. Psicoeduc. Psigopedag. 15, 553–573. doi: 10.14204/ejrep.43.16064

CrossRef Full Text | Google Scholar

van Schaick, L., Kovacik, K., Hallman, K., Diaz, M., and Morrison, S. (2007). Personality as a potential predictor of academic satisfaction. Psi. Chin. J. Undergrad. Res. 12, 46–50. doi: 10.24839/1089-4136.jn12.2.46

CrossRef Full Text | Google Scholar

Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika 41, 321–327. doi: 10.1007/bf02293557

CrossRef Full Text | Google Scholar

Wach, F., Karbach, J., Ruffing, S., Brunken, R., and Spinath, F. M. (2016). University students’ satisfaction with their academic studies: personality and motivation matter. Front. Psychol. 7:55. doi: 10.3389/fpsyg.2016.00055

PubMed Abstract | CrossRef Full Text | Google Scholar

Watson, J. C. (2017). Establishing evidence for internal structure using exploratory factor analysis. Meas. Eval. Couns. Dev. 50, 232–238. doi: 10.1080/07481756.2017.1336931

CrossRef Full Text | Google Scholar

Wilkins, K. G., Santilli, S., Ferrari, L., Nota, L., Tracey, T. J. G., and Soresi, S. (2014). The relationship among positive emotional dispositions, career adaptability, and satisfaction in Italian high school students. J. Vocat. Behav. 85, 329–338. doi: 10.1016/j.jvb.2014.08.004

CrossRef Full Text | Google Scholar

Wilkins-Yel, K. G., Roach, C. M., Tracey, T. J. G., and Yel, N. (2018). The effects of career adaptability on intended academic persistence: the mediating role of academic satisfaction. J. Vocat. Behav. 108, 67–77. doi: 10.1016/j.jvb.2018.06.006

CrossRef Full Text | Google Scholar

Wong, P. W. (2011). Textbook Evaluation: A Framework for Evaluating the Fitness of the Hong Kong New Secondary School (NSS) Curriculum. Master thesis, City University of Hong Kong, Hong Kong.

Google Scholar

Worthington, R. L., and Whittaker, T. A. (2006). Scale development research: a content analysis and recommendations for best practices. Couns. Psychol. 34, 806–838. doi: 10.1177/0011000006288127

CrossRef Full Text | Google Scholar

Yamawaki, N., Nelson, J. A. P., and Omori, M. (2011). Self-esteem and life satisfaction as mediators between parental bonding and psychological well-being in Japanese young adults. Int. J. Psychol. Couns. 3, 1–8.

Google Scholar

Yu, L., Shek, D. T. L., and Zhu, X. (2018). The influence of personal well-being on learning achievement in university students over time: mediating or moderating effects of internal and external university engagement. Front. Psychol. 8:2287. doi: 10.3389/fpsyg.2017.02287

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, Z., Shek, D. T. L., Zhu, X., and Dou, D. (2020). Positive youth development and adolescent depression: a longitudinal study based on mainland Chinese high school students. Int. J. Environ. Res. Pub. Health 17, 1–15. doi: 10.3390/ijerph17124457

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhu, X., and Shek, D. T. L. (2020). Impact of a positive youth development program on junior high school students in mainland China: a pioneer study. Child Youth Serv. Rev. 114:1. doi: 10.1016/j.childyouth.2020.105022

CrossRef Full Text | Google Scholar

Keywords: positive youth development, life satisfaction, academic stress, academic satisfaction, longitudinal study

Citation: Shek DTL and Chai W (2020) The Impact of Positive Youth Development Attributes and Life Satisfaction on Academic Well-Being: A Longitudinal Mediation Study. Front. Psychol. 11:2126. doi: 10.3389/fpsyg.2020.02126

Received: 26 February 2020; Accepted: 30 July 2020;
Published: 01 September 2020.

Edited by:

María Carmen Martínez Monteagudo, University of Alicante, Spain

Reviewed by:

Michael D. Toland, The University of Toledo, United States
Luciano Romano, Libera Università Maria SS. Assunta, Italy
Rodrigo J. Carcedo, University of Salamanca, Spain

Copyright © 2020 Shek and Chai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Daniel T. L. Shek, ZGFuaWVsLnNoZWtAcG9seXUuZWR1Lmhr

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