Next Article in Journal
Ascertaining the Online Learning Behaviors and Formative Assessments Affecting Students’ Academic Performance during the COVID-19 Pandemic: A Case Study of a Computer Science Course
Previous Article in Journal
Examination of the Effect of Career Barriers and Presenteeism Behaviors on Teacher Professionalism through Structural Equation Model
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

School Adjustment and Academic Success in Qatari Secondary School Students: Associations with Well-Being and Emotional and Behavioral Problems

1
Department of Psychological Sciences, College of Education, Qatar University, Doha P.O. Box 2713, Qatar
2
Department of Psychology, College of Humanities and Sciences, Virginia Commonwealth University, Richmond, VA 23284-2018, USA
*
Author to whom correspondence should be addressed.
Educ. Sci. 2022, 12(12), 934; https://doi.org/10.3390/educsci12120934
Submission received: 26 October 2022 / Revised: 8 December 2022 / Accepted: 8 December 2022 / Published: 17 December 2022

Abstract

:
Although the Qatari government has invested significantly in education over the past two decades, little research has comprehensively assessed factors associated with high school adjustment and academic success in the country. The present study addressed this gap with a sample of 576 students attending high school in Qatar (M age = 16.32, SD = 1.09; 63.7% male). Students self-reported their school adjustment and perceived academic performance as well as positive and negative indicators of health, including well-being and emotional and behavioral problems. Path models revealed that both well-being and problems contributed to school adjustment. Well-being and problems also contributed to academic performance, but these paths differed for males and females. For females, but not males, well-being was directly related to better performance; for males, but not females, problems contributed directly to worse performance and also operated through school adjustment to affect performance. Implications for promoting optimal school adjustment are discussed.

1. Introduction

Qatari education follows a pattern similar to that of many systems around the world. Children attend school for a total of 12 years, divided into primary, middle, and secondary school. In secondary school, which extends from the 10th to the 12th grade, students can choose between attending public schools that provide general education and specialized schools that provide a variety of options based on the student’s interests and academic priorities, such as science, technology, and business [1]. The social, economic, and cultural transformations that Qatar has experienced over the last two decades have resulted in a significant government investment in education. Further, the youth Qatar is educating now differs from previous generations; they are wealthier, which has increased their material living standards and given them more options for meeting their material needs and aspirations [2]. Despite this investment in education, a paucity of research has comprehensively evaluated factors that contribute to school adjustment and performance among Qatari secondary school students—including assessments of strengths and protective factors in addition to weaknesses and risk factors. Such an evaluation is important, as it can identify factors to address in prevention or intervention programs that are aimed at enhancing adjustment and success in academic settings.
There is ample evidence to suggest that emotional and behavioral problems, as well as assessments of well-being, contribute to school adjustment and academic performance [3,4,5,6,7,8]. For example, two recent systematic reviews that evaluated data primarily from western nations documented positive associations between psychological well-being and academic achievement [3,5]. Among the studies conducted in Asia, Arslan and Coşkun [4] found that Turkish high school students’ subjective well-being was significantly associated with youth school functioning and adjustment outcomes. Mustafa et al. [8] demonstrated a positive association between psychological well-being and academic achievement among university students in Malaysia. Among urban secondary school students in Bangladesh, Hossain [6] found negative associations between emotional and behavioral problems and academic achievement. While emotional and behavioral problems, in general, are associated with low academic performance, research indicates that externalizing behaviors negatively affect academic performance much more than internalizing behaviors [9,10,11]. For instance, Esch and colleagues [12] reported that externalizing problems predicted school dropout, whereas internalizing problems were often a consequence of school dropout. However, most previous work, including studies in the Middle East, have not considered the contributions of emotional and behavioral problems along with well-being with school adjustment and achievement.
Studies conducted in the Middle East have been limited to descriptions of behavioral problems and have not addressed the relations between behavioral problems and well-being or associations with school achievement [13,14,15,16]. Because a comprehensive understanding of mental health should take both psychological problems and well-being into account [17], both emotional and behavioral problems and well-being should be considered when investigating contributions to school adjustment and academic performance. To this end, and consistent with an emphasis on the strengths and protective factors in concert with weaknesses and risk factors, the current study considered Qatar students’ psychological well-being as well as emotional and behavioral problems as contributors to school adjustment and academic performance.

1.1. Gender Differences

Consistent with findings around the world, research conducted in the Middle East has revealed gender differences in students’ mean levels of psychological distress [13,14,16,18], indicators of well-being (e.g., self-efficacy [13]), and academic motivation and performance [19]. In Qatar, despite extensive investment in education, boys, in particular, are underperforming compared to international standards and to expectations based on the nation’s wealth. Male students who perceive economic entitlement and wasta (social status) as a venue to success are especially unmotivated to perform well [19,20]. Although researchers have focused on these gender differences and the potential consequences of academic disengagements, such as dropping out of the educational system before receiving the training that would allow them to contribute to Qatari economy [19,20], few studies have evaluated how emotional and behavioral problems and well-being are associated in different ways or to different degrees with school adjustment and academic success for males versus females. For instance, research has also shown that boys are more likely to exhibit problem behaviors of an externalizing nature, while girls tend to have internalizing behaviors [21]. This is important because different prevention or intervention strategies to improve school adjustment and academic success may be indicated for male versus female students based on such research findings. Thus, a second focus of the current study was to evaluate gender differences in patterns of association between emotional and behavioral problems, well-being, school adjustment, and academic performance.

1.2. Current Study

The current study assessed Qatari high school students regarding their emotional and behavioral problems, well-being, school adjustment, and academic performance. We tested a path model linking problems and well-being to school adjustment, which in turn, was hypothesized to affect academic performance. We anticipated that emotional and behavioral problems would be negatively associated, and well-being would be positively associated with better school adjustment, which in turn would be associated with higher perceived academic achievement. Gender differences in these patterns of association were exploratory, given the paucity of available data to inform this question.

2. Method

2.1. Participants and Sampling

High school students (N = 576; 63.7% male; Mage = 16.32, SD = 1.09, Range = 15 to 19 years old; 61.3% non-Qatari) participated. Data were collected from the municipality of Doha, which has more than 80% of the nation’s population [22]. Schools are segregated by gender in Qatar. Four schools—two all-female and two all-male—were invited to participate in the study. Schools were invited to participate if their student scores on the National Comprehensive Educational Exam for the school were average (versus extremely high or low) and had a distribution of both Qatari and non-Qatari nationalities. Students were fairly evenly distributed across grades, with 34.4%, 32.8%, and 32.8% enrolled in the 10th, 11th, and 12th grades, respectively. Students reported paternal educational attainment as either below university (43.2%), university degree (43.2%), or post-graduate work (13.5%), and maternal educational attainment as below university (47.9%), university degree (45.1%), or post graduate work (6.9%). Family socioeconomic status (SES) was rated as below average (19.1%), average (62.5%), or above average (18.4%).

2.2. Measures

All measures were self-reported by students in Arabic. Other than the Strengths and Difficulties Questionnaire (SDQ), which is available in Arabic, all measures were obtained from Abu-rayya and Sam [23] and have previously been used with Arab populations. In translating the measures, Abu-rayya and Sam [23] followed a parallel approach [24], which involved several translators working independently to translate the measures from English into standard Arabic. The draft translated version was back-translated from Arabic into English and then analyzed during two review meetings between the committee members. A copy of the translated questionnaires was shared with faculty in the field and also with high school students. Reviews by teachers and students revealed no difficulties in comprehending the measures.

2.2.1. Emotional and Behavioral Problems

The 25-item Strengths and Difficulties Questionnaire (SDQ; [25]) was used to assess a range of emotional and behavioral functioning, including emotional problems, conduct problems, hyperactivity, peer problems, and prosocial behavior. Each 5-item subscale is rated on a 3-point Likert scale with the options 0 (not true), 1 (somewhat true), and 2 (certainly true). Items were reverse-coded as needed so that higher scores on each subscale reflected more problematic functioning. The items were summed to create total subscale scores. The Arabic version of the SDQ has been used previously in Arab countries, including Qatar [26]. The SDQ has excellent validity and reliability and can be used to assess and diagnose general emotional and behavioral problems within an educational context [27,28]. In the present study, only the emotional problems scale (Cronbach’s alpha = 0.77) and hyperactivity (Cronbach’s alpha = 0.66) had acceptable reliability, and thus, these were used in the analyses.

2.2.2. Well-Being

Two measures were used to indicate well-being. First, the PERMA [29] was used to assess well-being in the five domains of positive emotion, engagement, relationships, meaning, and accomplishment. Each domain is assessed with three items on an 11-item scale from 0 (not at all) to 10 (completely), with higher scores indicating more positive well-being. Across eight studies with a combined sample size of 31,966, the PERMA-Profiler demonstrated an acceptable model fit, internal and cross-time consistency, and evidence for content, convergent, and divergent validity. Validity has been established in a variety of countries and languages [30,31,32]. In the present study, internal consistency and reliability assessed with Cronbach’s alpha were: positive emotion (0.91), engagement (0.57), relationships (0.78), meaning (0.89), and accomplishment (0.88). Our analysis revealed that dropping one item from the engagement subscale yielded a correlation of 0.79 with the remaining two items, and engagement was recomputed using two items. Item averages for each domain were used in the current study.
The second indicator of well-being was self-esteem, assessed with the 10-item Rosenberg [33] Self-Esteem scale. This measure has strong validity and reliability [34] and has been used in thousands of studies worldwide. Items are rated on a 4-point Likert scale ranging from 0 (strongly disagree) to 3 (strongly agree). Negatively worded items are reverse-coded so that higher scores indicate greater levels of self-esteem. Cronbach’s alpha in the current study was 0.80.

2.2.3. School Adjustment

Adjustment to school was assessed with the 7-item School Adjustment Scale [35]. Items were rated on a scale from 1 (strongly agree) to 7 (strongly disagree). One item was reverse coded, and higher scores indicated more positive school adjustment. A sample item is “I find it difficult to go to school in the morning”. The School Adjustment Scale has been proven to provide good validity and reliability in several international studies [23,35]. Cronbach’s alpha in the current study was 0.70.

2.2.4. School Performance

Students rated their perceived school performance on a 4-point scale adapted from Achenbach and Rescorla [36]. The response options were: 1 (below average), 2 (average), 3 (good), or 4 (excellent). This scale has been used in previous studies in Qatar [37].

2.2.5. Procedure

The project was approved by the ethical review board at Qatar University as well as the Ministry of Education and Higher Education in Qatar. Once schools agreed to participate, parents were sent forms requesting their consent for their children to participate. All participating students had parental approval and agreed to participate themselves. After agreeing to participate, students were sent a link to a survey which they completed online. Data were collected in October 2021 for one week while schools in Qatar were held virtually.

3. Data Analysis

First, the latent structure of a well-being factor and an emotional and behavioral problems factor were confirmed using MPlus Version 8.1 [38]. Manifest variables were then created by standardizing each of the indicators of well-being and of emotional and behavioral problems and multiplying them by their respective factor loadings. Next, descriptive information on all the study variables was calculated. Univariate analyses, including correlations among the constructs and t-tests, and Chi-squares assessing differences across males and females were computed. A path model then was tested, linking well-being and emotional and behavioral problems with school adjustment and school performance. The fit for the model was assessed using the χ2 value, the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). Values of 0.90 or above for the CFI [39], 0.08 or below for the RMSEA [40], and 0.05 or below for the SRMR indicated that the model adequately fit the data. Gender differences in the association between the variables in the model were tested using multiple group analyses. An unconstrained model where the path coefficients were allowed to vary by gender was compared with a constrained model where path coefficients were set to be equal across gender. The fit for the unconstrained and constrained models was compared using the Bayesian information criterion (BIC), RMSEA, CFI, and SRMR. In comparing the unconstrained and constrained models, if the BIC was lower by at least 10 points for the constrained model, this suggests that there was an improvement in the fit of the model, suggesting that the constrained model is more parsimonious and should be favored over the unconstrained model [41], and would indicate no gender differences in the model fit. Finally, bias-corrected bootstrapping procedures, outlined by Shrout and Bolger [42], were used to test the significance of indirect effects. In the current study, 3000 bootstrap samples were created through random sampling with replacements. Analyses were run to examine the indirect effects of well-being and emotional and behavioral problems on school performance through school adjustment.

4. Results

4.1. Latent Structure of Well-Being and Problems Factors

A latent factor of well-being with six indicators and a latent factor of emotional and behavioral problems with two indicators revealed adequate fit, χ2 (31) = 185.26, p < 0.001; CFI = 0.951; RMSEA = 0.093; SRMR = 0.032. Although the RMSEA was slightly higher than 0.08, the other indicators of the model fit were good, and the factor loading for each latent variable was similar.

4.2. Descriptive Information and Univariate Analyses

The means, SDs, and range of the study variables and their intercorrelations are presented in Table 1.
As seen in the table, the key study constructs were all correlated in the expected directions. Age was negatively associated with school adjustment and school performance, but not with well-being or emotional and behavioral problems. The t-tests assessing gender differences revealed no differences in well-being, t(574) = −0.06, p = 0.95 or school adjustment, t(574) = 0.52, p = 0.61. However, there were significant gender differences in emotional and behavioral problems, t(574) = 3.23, p < 0.001 and school performance, t(574) = 4.57, p < 0.001, as well as age, t(574) = −2.59, p = 0.01. Females reported more emotional and behavioral problems than males (M = 0.23, SD = 1.41 for females; M = −0.14, SD = 1.27 for males), but higher school performance than males (M = 3.37, SD = 0.72 for females; M = 3.05, SD = 0.86 for males). Males were older than females (M = 16.17, SD = 1.09 for females; M = 16.41, SD = 1.09 for males).

4.3. Path Analysis Predicting School Adjustment and School Performance

Figure 1 depicts the path model that was tested for linking well-being, emotional and behavioral problems, school adjustment, and school performance. The model was a good fit to the data, χ2 (4) = 18.52, p < 0.001; RMSEA = 0.079 CI (0.045, 0.118); CFI = 0.961; TLI = 0.912; SRMR = 0.037.
Although the BIC for the unconstrained model was larger than the constrained model (10276 vs. 10239), the multiple group analyses overall favored the unconstrained model, indicating gender differences in the model paths. Specifically, the Akaike (AIC) was similar for the unconstrained and constrained models (10137 vs. 10134), as was the sample-size adjusted BIC (10174 vs. 10163). The RMSEA was slightly lower for the unconstrained versus the constrained model (0.047 vs. 0.049); the CFI was slightly higher (0.993 vs. 0.977), and the SRMR was lower (0.032 vs. 0.075). Figure 1 presents the standardized beta weights for the model paths of males and females.
As seen in Figure 1, for both male and female secondary students living in Qatar, well-being was positively associated with school adjustment, while emotional and behavioral problems were negatively associated with adjustment. Likewise, older students reported poorer school adjustment across gender. However, for school performance, well-being was positively associated with this outcome for females but not for males, and emotional and behavioral problems were negatively related to school performance for males but not females. Additionally, school adjustment negatively predicted school performance in males but not females.
Analyses of indirect effects of well-being and emotional and behavioral problems on school performance via school adjustment revealed significant indirect effects for males but not for females. For males, the indirect effect of well-being on school performance via school adjustment was 0.07 (p = 0.004). The indirect effect of emotional and behavioral problems on school performance via school adjustment was −0.12 (p < 0.001).

5. Discussion

Little research has examined positive and negative indicators of health, including psychological well-being and emotional and behavioral problems, for high school students in Middle Eastern countries, including Qatar, as well as their relations with positive educational outcomes. Our study fills this gap and confirms both theory and observation that both psychological well-being and emotional and behavioral problems matter. Notably, although correlated, psychological well-being and emotional and behavioral problems made independent contributions to school adjustment. These findings were consistent with our expectations and also with previous research [43,44,45].
Interestingly, contributions to self-rated school performance differed by gender. For males, school performance—whether they believed they were below average, average, good, or excellent—was positively associated with school adjustment and directly negatively related to emotional and behavioral problems. In contrast, although females reported more emotional and behavioral problems than males, their school performance was directly and positively associated with well-being, not problems. If both male and female emotional and behavioral problems present differently, this could explain part of this finding. For example, a more overt expression of emotional and behavioral problems by males versus females may evoke a more negative response by peers, teachers, and others at school, leading to both poorer school adjustment and performance. Our results may be understood in light of findings that girls are prone to internalizing behaviors, and those behaviors have less of an effect on their academic performance, while boys are more likely to exhibit externalizing behaviors, which are more likely to adversely affect academic performance [9,10,11,21].
Additionally, Qatari female students, compared to their male peers, tend to prioritize their education. Male Qatari students, on the other hand, are more likely than females to view economic entitlement and social status, not educational attainment, as key to success [19]. In addition, male students appear to have fewer positive attitudes toward going to school and value education less compared to females [20]. Because of the country’s wealth, male students tend to do less and have higher expectations compared to females. Students expect that the government and their families will provide for them regardless of their individual effort and performance [20]. Gender differences in the freedoms afforded to Qatari high school students may have also contributed to these patterns. Males at this age are more independent due to the fact that they are allowed to spend more time outside the home without supervision, engaging in leisure or sports activities. These options are not available for most female high school students. Overall, age differences in the study were mixed. At the univariate level, there were no age differences in well-being or emotional and behavioral problems; however, younger students reported better school adjustment and school performance than older students: a finding consistent with other research [46,47,48]. In contrast in the path models that accounted for co-variation among the study constructs, there were no age differences in school performance. Further, younger males, but not younger females, reported better school adjustment. These findings again may reflect differences in freedoms across both age and gender in Qatari culture.

5.1. Study Strengths and Limitations

The strengths of this study include the inclusion of both positive and negative dimensions of health, a relatively large sample size, and sophisticated tests of our model. Limitations include the cross-sectional design, which precludes forming conclusions about the temporal ordering of constructs, and the sole reliance on adolescents for the data. Utilizing a longitudinal design and augmenting these data with official school reports of performance and/or parent or teacher reports of emotional and behavioral problems or well-being could increase confidence in the findings. Additionally, although schools were invited to participate if students’ scores on the National Comprehensive Educational Exam were neither extremely high nor extremely low, and the schools included both Qatari and non-Qatari nationalities, the sample was based on a specific set of four schools. Thus, the findings may not generalize to the entire population of secondary school students in Qatar. Finally, no study can include all possible factors that might affect an outcome of interest. Thus, this study may have missed key variables that could have influenced school performance in this context.

5.2. Implications for Practice and Research

Data from this study might be used by teachers and other school personnel to improve student school adjustment and performance. For example, school-based interventions might focus on increasing social-emotional competencies, especially for males, and fostering well-being [49]. Programs such as Social and Emotional Learning (SEL) that help adolescents with emotion management have been successful at improving academic outcomes, adaptive coping strategies, and skills and mindsets [50]. In addition, future research should target interventions for externalizing problems as they tend to place adolescents at increased risk for poor academic performance. Further research should also examine the bidirectional pathways between problem behavior and academic performance.

Author Contributions

Conceptualization, M.A.-H.; Methodology, M.A.-H. and W.K.; Validation, M.A.-H. and W.K.; Formal analysis, M.A.-H. and W.K.; Investigation, M.A.-H. and E.H.; Data curation, M.A.-H. and E.H.; Writing—original draft, M.A.-H.; Writing—review & editing, M.A.-H. and W.K.; Project administration, M.A.-H.; Funding acquisition, M.A.-H. All authors have read and agreed to the published version of the manuscript.

Funding

This publication was jointly supported by Qatar University [QUCP-CED-2021-2]. The findings achieved herein are solely the responsibility of the authors.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Qatar University (approval code QU-IRB QU-IRB 1591-EA/21, approved on 22 September 2021) for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study and those are relevant.

Data Availability Statement

Data are not publicly available due to ethical restrictions, their containing information that could compromise the privacy of research participants.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ministry of Education and Higher Education Qatar (MOEHE). Public Education Sector. 2020. Available online: https://www.edu.gov.qa/en/pages/pubschoolsdefault.aspx?itemid=124 (accessed on 12 April 2022).
  2. General Secretariat for Development Planning. Expanding the Capacities of Qatari Youth. Doha Gulf Publ. Print. 2012, 1, 173. [Google Scholar]
  3. Amholt, T.T.; Dammeyer, J.; Carter, R.; Niclasen, J. Psychological Well-Being and Academic Achievement among School-Aged Children: A Systematic Review. Child Indic. Res. 2020, 13, 1523–1548. [Google Scholar] [CrossRef]
  4. Arslan, G.; Coşkun, M. Student subjective wellbeing, school functioning, and psychological adjustment in high school adolescents: A latent variable analysis. J. Posit. Sch. Psychol. 2020, 4, 153–164. [Google Scholar] [CrossRef]
  5. Kaya, M.; Erdem, C. Students’ well-being and academic achievement: A meta-analysis study. Child Indic. Res. 2021, 14, 1743–1767. [Google Scholar] [CrossRef]
  6. Hossain, S. A study of determining the relationship between academic achievement and problem behavior of urban secondary school students in Bangladesh. Int. J. Soc. Sci. 2013, 8, 1–10. [Google Scholar]
  7. Li, H.; Martin, A.J.; Armstrong, D.; Walker, R.A. Risk, protection, and resilience in Chinese adolescents: A psycho-social study: Resilience and Chinese youth. Asian J. Soc. Psychol. 2011, 14, 269–282. [Google Scholar] [CrossRef]
  8. Mustafa, M.B.; Mat Ran, N.H.; Bistaman, M.; Salim, S.; Zakaria, N.; Safian, N. The relationship between psychological well-being and university students academic achievement. Int. J. Acad. Res. Bus. Soc. Sci. 2020, 10, 518–525. [Google Scholar] [CrossRef]
  9. Barnes, T.N.; Smith, S.W.; Miller, M.D. School-based cognitive-behavioral interventions in the treatment of aggression in the United States: A meta-analysis. Aggress. Violent Behav. 2014, 19, 311–321.10. [Google Scholar] [CrossRef]
  10. Riglin, L.; Petrides, K.V.; Frederickson, N.; Rice, F. The relationship between emotional problems and subsequent school attainment: A meta-analysis. J. Adolesc. 2014, 37, 335–346. [Google Scholar] [CrossRef]
  11. Van der Ende, J.; Verhulst, F.C.; Tiemeier, H. The bidirectional pathways between internalizing and externalizing problems and academic performance from 6 to 18 years. Dev. Psychopathol. 2016, 28, 855–867. [Google Scholar] [CrossRef]
  12. Esch, P.; Bocquet, V.; Pull, C.; Couffignal, S.; Lehnert, T.; Graas, M.; Fond-Harmant, L.; Ansseau, M. The downward spiral of mental disorders and educational attainment: A systematic review on early school leaving. BMC Psychiatry 2014, 14, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Aboalshamat, K.; Hou, X.Y.; Strodl, E. Psychological well-being status among medical and dental students in Makkah, Saudi Arabia: A cross-sectional study. Med. Teach. 2015, 37, S75–S81. [Google Scholar] [CrossRef]
  14. Al-Mukhani, Z.; Bekker, H.L.; Cottrell, D. Describing psychological and behavioural problems in Omani young people: Reliability of the Self-reported Strength and Difficulties Questionnaire (SDQ) in Oman. J. Child Adolesc. Health 2018, 2, 19–23. [Google Scholar] [CrossRef] [Green Version]
  15. Lansford, J.; Brik, A.; Al Fara, H. A framework for child well-being in the Gulf countries. Child Indic. Res. 2019, 12, 1971–1987. [Google Scholar] [CrossRef]
  16. Mowafy, M.; Ahmed, D.; Halawa, E.; Emad El Din, M. Prevalence and predictors of emotional and behavioral problems among rural school Egyptian adolescents. Egypt. J. Community Med. 2015, 33, 79–93. [Google Scholar] [CrossRef]
  17. Romer, N.; von der Embse, N.; Eklund, K.; Kilgus, S.; Perales, K.; Splett, J.W.; Sudlo, S.; Wheeler, D. Best Practices in Social, Emotional, and Behavioral Screening: An Implementation Guide. Version 2.0. Available online: www.smhcollaborative.org/universalscreening (accessed on 9 March 2022).
  18. Mohammadi, M.R.; Arman, S.; Khoshhal Dastjerdi, J.; Salmanian, M.; Ahmadi, N.; Ghanizadeh, A.; Alavi, M.A.; Malek, A.; Fathzadeh Gharibeh, H.; Moharreri, F.; et al. Psychological problems in Iranian adolescents: Application of the self-report form of strengths and difficulties questionnaire. Iran. J. Psychiatry 2013, 8, 152–159. [Google Scholar]
  19. Al-Thani, H. Modernity Aspirations: The Struggle of Qatari Male Public High School Students to Become Successful Academically. Ph.D. Thesis, Columbia University, New York, NY, USA, 2017. [Google Scholar]
  20. Lee, S. What Motivates and Engages Students in the Education Process—An Examination of Qatari Students’ Mindset and Attitudes toward Going to School, Learning, and Future Aspirations. J. Educ. Learn. 2016, 5, 220–235. [Google Scholar] [CrossRef] [Green Version]
  21. Masten, A.S.; Roisman, G.I.; Long, J.D.; Burt, K.B.; Obradović, J.; Riley, J.R.; Boelcke-Stennes, K.; Tellegen, A. Developmental cascades: Linking academic achievement and externalizing and internalizing symptoms over 20 years. Dev. Psychol. 2005, 41, 733. [Google Scholar] [CrossRef] [Green Version]
  22. The Planning Council, The General Secretariat. Annual Statistical Abstract; The Planning Council, The General Secretariat: Doha, Qatar, 2005. [Google Scholar]
  23. Abu-Rayya, H.M.; Sam, D.L. Is integration the best way to acculturate? A reexamination of the bicultural-adaptation relationship in the “ICSEY Dataset” Using the bilineal method. J. Cross-Cult. Psychol. 2017, 48, 287–293. [Google Scholar] [CrossRef]
  24. Merenda, P.F. An overview of adapting educational and psychological assessment instruments: Past and present. Psychol. Rep. 2006, 99, 307–314. [Google Scholar] [CrossRef]
  25. Goodman, R. The Strengths and Difficulties Questionnaire: A research note. Child Psychol. Psychiatry Allied Discip. 1997, 38, 581–586. [Google Scholar] [CrossRef] [PubMed]
  26. Al-Hendawi, M.; Keller, C. An exploratory study of the Strengths and Difficulties Questionnaire as a behavioral screening instrument in Qatar. In Qatar Foundation Annual Research Forum Volume 2012 Issue 1; Hamad bin Khalifa University Press: Doha, Qatar, 2021; Volume 2012, p. AHP26. [Google Scholar]
  27. Garralda, M.E.; Yates, P.; Higginson, I. Child and adolescent mental health service use. HoNOSCA as an outcome measure. Br. J. Psychiatry 2000, 177, 52–58. [Google Scholar] [CrossRef] [PubMed]
  28. Goodman, R.; Ford, T.; Simmons, H.; Gatward, R.; Meltzer, H. Using the Strengths and Difficulties Questionnaire (SDQ) to Screen for child psychiatric disorders in a community sample. Br. J. Psychiatry 2000, 177, 534–539. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Butler, J.; Kern, M.L. The PERMA-Profiler: A brief multidimensional measure of flourishing. Int. J. Wellbeing 2016, 6, 1–48. [Google Scholar] [CrossRef] [Green Version]
  30. Ayse, E.B. Adaptation of the PERMA Well-Being Scale into Turkish: Validity and Reliability Studies. Educ. Res. Rev. 2018, 13, 129–135. [Google Scholar] [CrossRef] [Green Version]
  31. Giangrasso, B. Psychometric properties of the PERMA-Profiler as hedonic and eudaimonic well-being measure in an Italian context. Curr. Psychol. 2021, 40, 1175–1184. [Google Scholar] [CrossRef]
  32. Wammerl, M.; Jaunig, J.; Mairunteregger, T.; Streit, P. The German version of the PERMA-Profiler: Evidence for construct and convergent validity of the PERMA theory of well-being in German speaking countries. J. Well-Being Assess. 2019, 3, 75–96. [Google Scholar] [CrossRef] [Green Version]
  33. Rosenberg, M. Society and the Adolescent Self-Image; Princeton University Press: Princeton, NJ, USA, 1965. [Google Scholar]
  34. Blascovich, J.; Tomaka, J. Measures of Self-Esteem. In Measures of Personality and Social Psychological Attitudes, 3rd ed.; Robinson, J.P., Shaver, P.R., Wrightsman, L.S., Eds.; Institute for Social Research: Ann Arbor, MI, USA, 1993; pp. 115–160. [Google Scholar] [CrossRef]
  35. Berry, J.; Phinney, J.S.; Sam, D.L.; Vedder, P. Immigrant Youth: Acculturation, identity, and adaptation. Appl. Psychol. 2006, 55, 303–332. [Google Scholar] [CrossRef] [Green Version]
  36. Achenbach, T.M.; Rescorla, L.A. Manual for the ASEBA School-Age Forms & Profiles; University of Vermont, Research Center for Children, Youth, & Families: Burlington, VT, USA, 2001. [Google Scholar]
  37. Al-Hendawi, M.; Keller, C.; Cloninger, L. A psychometric analysis of the Child Behavior Checklist for elementary school children in Qatar. Assess. Eff. Interv. 2016, 41, 220–229. [Google Scholar] [CrossRef]
  38. Muthén, L.K.; Muthén, B. Mplus User’s Guide, 7th ed.; Muthén & Muthén: Los Angeles, CA, USA, 2015. [Google Scholar]
  39. Bentler, P.M. On the fit of models to covariances and methodology to the Bulletin. Psychol. Bull. 1992, 112, 400–404. [Google Scholar] [CrossRef]
  40. Browne, M.W.; Cudeck, R. Alternative ways of assessing model fit. In Testing Structural Equation Models; Bollen, K.A., Long, J.S., Eds.; Sage: Newbury Park, CA, USA, 1993; pp. 136–162. [Google Scholar]
  41. Raftery, A.E. Bayesian model selection in structural equation models. In Testing Structural Equation Models; Bollen, K.A., Long, J.S., Eds.; Sage: Beverly Hills, CA, USA, 1993; pp. 163–180. [Google Scholar]
  42. Shrout, P.E.; Bolger, N. Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychol. Methods 2002, 7, 422–445. [Google Scholar] [CrossRef] [PubMed]
  43. Di Fabio, A.; Kenny, M.E. Promoting well-being: The contribution of emotional intelligence. Front. Psychol. 2016, 7, 1182. [Google Scholar] [CrossRef] [PubMed]
  44. Orgilés, M.; Samper, D.; Fernández-Martínez, I.; Espada, J.P. Depresión en preadolescentes españoles: Diferencias en función de variables familiares. Rev. Psicol. Clínica Niños Adolesc. 2017, 4, 129–134. [Google Scholar]
  45. Schoeps, K.; Tamarit, A.; Montoya-Castilla, I.; Takšic, V. Factorial structure and validity of the Emotional skills and competences Questionnaire (ESCQ) in Spanish adolescents. Psicol. Conduct. 2019, 27, 275–293. [Google Scholar]
  46. Ansary, N.S.; McMahon, T.J.; Luthar, S.S. Trajectories of emotional-behavioral difficulty and academic competence: A 6-year, person-centered, prospective study of affluent suburban adolescents. Dev. Psychopathol. 2017, 29, 215–234. [Google Scholar] [CrossRef] [Green Version]
  47. Atoum, M.; Alhussami, M.; Rayan, A. Emotional and behavioral problems among Jordanian adolescents: Prevalence and associations with academic achievement. J. Child Adolesc. Psychiatr. Nurs. 2018, 31, 70–78. [Google Scholar] [CrossRef]
  48. Ortuño-Sierra, J.; Fonseca-Pedrero, E.; Paíno, M.; Aritio-Solana, R. Prevalencia de síntomas emocionales y comportamentales en adolescentes españoles [Prevalence of emotional and behavioral symptomatology in Spanish adolescents]. Rev. Psiquiatr. Salud Ment. 2014, 7, 121–130. [Google Scholar] [CrossRef]
  49. De La Barrera, U.; Schoeps, K.; Gil-Gómez, J.A.; Montoya-Castilla, I. Predicting adolescent adjustment and well-being: The interplay between socio-emotional and personal factors. Int. J. Environ. Res. Public Health 2019, 16, 4650. [Google Scholar] [CrossRef] [Green Version]
  50. Yeager, D.S. Social and emotional learning programs for adolescents. Future Child. 2017, 27, 73–94. [Google Scholar] [CrossRef]
Figure 1. Path model of the relations between well-being, emotional and behavioral problems, and school adjustment and performance. Multiple group analyses favored an unconstrained model, indicating that paths differed across males and females. N = 576. X2 (4) = 6.58, p = 0.16; RMSEA = 0.047 90% CI (0, 0.109); CFI = 0.993; TLI = 0.975; SRMR = 0.032. Beta weights for males are before the diagonal and for females are behind the diagonal. Solid lines indicate significant paths; thicker lines indicate similar findings across males and females. * p < 0.05; *** p < 0.001.
Figure 1. Path model of the relations between well-being, emotional and behavioral problems, and school adjustment and performance. Multiple group analyses favored an unconstrained model, indicating that paths differed across males and females. N = 576. X2 (4) = 6.58, p = 0.16; RMSEA = 0.047 90% CI (0, 0.109); CFI = 0.993; TLI = 0.975; SRMR = 0.032. Beta weights for males are before the diagonal and for females are behind the diagonal. Solid lines indicate significant paths; thicker lines indicate similar findings across males and females. * p < 0.05; *** p < 0.001.
Education 12 00934 g001
Table 1. Descriptive information on and correlations among study constructs (n = 576).
Table 1. Descriptive information on and correlations among study constructs (n = 576).
12345M (SD) Range
1 Well-being-−0.59 ***0.50 ***0.28 ***−0.070 (4.21)−16.70–5.69
2 Problems -−0.56 ***−0.27 ***0.040 (1.33)−1.97–4.52
3 School Adjustment -0.35 ***−0.14 ***37.98 (8.28)9.00–49.00
4 School Performance -−0.14 ***3.17 (0.83)1.00–4.00
5 Age -
Note. Problems = emotional and behavioral problems. *** p < 0.001. M = Mean; SD = Standard Deviation.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Al-Hendawi, M.; Kliewer, W.; Hussein, E. School Adjustment and Academic Success in Qatari Secondary School Students: Associations with Well-Being and Emotional and Behavioral Problems. Educ. Sci. 2022, 12, 934. https://doi.org/10.3390/educsci12120934

AMA Style

Al-Hendawi M, Kliewer W, Hussein E. School Adjustment and Academic Success in Qatari Secondary School Students: Associations with Well-Being and Emotional and Behavioral Problems. Education Sciences. 2022; 12(12):934. https://doi.org/10.3390/educsci12120934

Chicago/Turabian Style

Al-Hendawi, Maha, Wendy Kliewer, and Esraa Hussein. 2022. "School Adjustment and Academic Success in Qatari Secondary School Students: Associations with Well-Being and Emotional and Behavioral Problems" Education Sciences 12, no. 12: 934. https://doi.org/10.3390/educsci12120934

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop