Exploring adolescent wellbeing: A scoping review

Exploring adolescent wellbeing: A scoping review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring adolescent wellbeing: A scoping review Genevieve McSporran, Laura Perry, Madeline Burgess, Xiaofang (Sarah) Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7506445/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract PISA is the only international large-scale assessment to specifically examine adolescent wellbeing alongside academic achievement. Wellbeing in PISA is a multidimensional construct comprising many indicators or factors for each of five main dimensions. An overall wellbeing score, like there is for academic achievement, does not exist at the student-level. Many secondary analyses of wellbeing in PISA have been conducted but the field is fragmented due to the large number of factors that are associated with the different dimensions of wellbeing. A further complexity is that various dimensions and indicators of wellbeing have been studied as both predictor and outcome variables. Our aim with this scoping review is to bring order to the field by mapping the various factors that are associated with the various dimensions of wellbeing. Through the systematic selection process, 46 secondary analyses of PISA 2015 or PISA 2018, the two cycles that examined wellbeing in depth, were identified for inclusion. Analysis revealed the existence of 170 individual factors or indicators categorised into five core dimensions of wellbeing (psychological, cognitive, social, physical and material), plus a sixth dimension for control and other variables. Overall, the most common individual factors studied were gender, economic social and cultural status, life satisfaction, positive affect and sense of belonging. A series of systematic reviews, about individual indicators and dimensions, is recommended to further extend the field. Systematic reviews about group differences based on individual or school-level characteristics would be especially fruitful. adolescent wellbeing Programme of International Student Assessment (PISA) scoping review predictors life satisfaction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1.0 Introduction Interest in wellbeing is growing worldwide due to declining levels of wellbeing across all age groups, and among children and adolescents in particular. Previous studies have shown that wellbeing fluctuates throughout childhood and is often at its lowest during early adolescence (McClelland & Steward, 2015; NASEM, 2021; Suldo, 2016). This drop in wellbeing coincides with the onset of puberty, broadening face-to-face and online peer groups, along with experimentation with alcohol, other drugs and sexual behaviours (WHO & UNICEF, 2024). In addition, the wellbeing of children and adolescents has been identified as an important contributor to the educational outcomes of young people whilst they are at school, and wellbeing outcomes across the lifespan (Aldridge et al., 2016). In 2021, the WHO and UNICEF (2024) estimated that 15% of 10-19 year olds experienced mental illnesses such as anxiety, depression, conduct disorder and attention deficit hyperactivity disorder. Furthermore, the authors identified suicide as the third leading cause of death for 15-29 year olds in the same report. Failing to address declining levels of childhood wellbeing has been projected to have broad health, social and criminal justice implications (WHO & UNICEF, 2024). Promoting good health and wellbeing is enshrined as the United Nations’ Sustainable Development Goal 3 (United Nations, nd). International large-scale assessments (ILSA) have become increasingly important sources of data for education policy and reform, with the Organisation for Economic Co-operation and Development (OECD) becoming particularly powerful through its Programme for International Student Assessment (PISA). Since 2000, PISA has been administered every three years to 15-year olds, near the end of their compulsory education, across OECD countries and OECD partner countries or economies. PISA has traditionally focused on academic achievement in mathematics, science and reading, plus one other contemporary focus area such as problem solving, financial literacy or global competence. Since 2015, PISA has become unique as the first ILSA to examine specific elements of student wellbeing. While a universal definition of wellbeing has not emerged (Simons & Baldwin, 2021), there is general agreement that wellbeing is a multi-faceted construct (Borgonovi & Pál, 2016). The multi-faceted nature of wellbeing and its impact on school and life outcomes was highlighted by the OECD (2019, p. 223) in the below statement used to frame the development of its PISA questionnaire. Success in school – and in life – also depends on being committed to learning, respecting and understanding others, being motivated to learn and being able to regulate one’s own behaviour. These constructs can be perceived as prerequisites to learning, but they may themselves also be judged as goals of education and important for success in life and overall wellbeing. Consistent with the literature, PISA’s operationalisation of wellbeing is similarly multi-faceted, comprising five dimensions. Each of these five dimensions of wellbeing comprise multiple wellbeing indicators. Unlike its academic achievement measure, there is no one single measure of wellbeing in PISA. In addition, PISA collects substantial information about students’ characteristics and school environments, all of which can be used to examine relationships with wellbeing. The richness of data collected that can be used to examine wellbeing in PISA is one of its greatest strengths. At the same time, however, it presents tremendous complexity. For example, the field includes studies that examine predictors of a wide range of wellbeing indicators, studies that examine how various indicators of wellbeing predict academic achievement, as well as how some wellbeing indicators (e.g., sense of belonging) are related to other wellbeing indicators (e.g., positive affect). The aim of this scoping review is to bring some order to the field by providing an overview of studies that have utilised PISA to understand student wellbeing. Which dimensions of wellbeing have been most studied, which factors have been examined, and what areas have not received as much attention? We see this study as a first step for enabling a comprehensive understanding of the various factors that are associated with the various dimensions of wellbeing. As noted by Borgonovi (2022), ILSAs have enabled researchers to map factors impacting cognitive achievement or the cognitive dimension of wellbeing across countries and world regions, and that it would also be beneficial to map the psychological, social, physical and material dimensions of wellbeing in the same way. Such mapping could facilitate the adoption of policies and practices that promote achievement and wellbeing without compromising one over the other (Hopfenbeck et al., 2018). In the remainder of this paper, we will overview the theoretical framework for wellbeing used in this study, our data collection and analysis methods, our results and conclusions before implications, limitations and recommendations for future studies. 2.0 Theoretical framework: Dimensions of wellbeing Wellbeing is a ubiquitous term that can mean both everything and nothing at the same time (Powell et al., 2018 ). As a concept, wellbeing can be dated to the ancient Greek philosophers. Aristotle was credited with identifying eudaemonic elements of wellbeing such as leading a good life, flourishing and self-actualisation. On the other hand, Aristippus’ contribution related to hedonism or the seeking of pleasure and happiness, which has been associated with contemporary understandings of subjective wellbeing. Perry et al. ( 2023 ) continued by stating themes relating to eudaemonia, hedonism and life satisfaction can be readily seen through the work of influential figures in psychology such as Maslow and Rogers in relation to humanist theory, Deci and Ryan regarding self-determination theory, Diener as an early researcher of subjective wellbeing, Csikszentmihalyi for his contribution of ‘flow’, and Seligman’s PERMA model (positive emotions, engagement, relationships, meaning and accomplishment) for flourishing as a key feature of positive psychology. In addition, Fattore et al. ( 2009 ) postulated wellbeing manifests itself as both a process and outcome that fluctuates and is negotiated over time. With reference to the wellbeing of children, two broad perspectives have been proposed. First, as a developmental approach which incorporates the different environments children experience based on Bronfenbrenner’s work (1981) and, secondly that children’s rights are just as important as adult’s rights (Borgonovi, 2022 ). With children’s wellbeing identified as an important determinant of educational outcomes whilst at school, and broader wellbeing outcomes as adults (Aldridge et al., 2016 ), there has been increased interest in how countries fare both academically and in the promotion of student wellbeing (OECD, 2017 ). As there is no universal definition of wellbeing (Simons & Baldwin, 2021 ) or agreed upon tool to measure adolescent wellbeing, this scoping review, as recommended by Mak and Thomas ( 2022 ) and Tricco et al. ( 2018 ), aims to map existing evidence to identify the range, extent and nature of factors reported in the literature relating to the research questions. As such, this scoping review constitutes a first step in elucidating important dimensions and factors or indicators used to define, measure and predict adolescent wellbeing. As this scoping review was focused on research in relation to the PISA 2015 and 2018 data sets, we started with the OECD’s definition of wellbeing for children as the “psychological, cognitive, social and physical functioning and capabilities that students need to live a happy and fulfilling life” (OECD, 2017 , p. 35). We chose to adopt a definition that also included the material dimension of wellbeing as this was done by Borgonovi ( 2022 ), Borgonovi and Pal (2016) and Resino et al. ( 2024 ). An additional rationale is that material conditions have formed one of two major headings in the OECD’s How’s Life? framework to evaluate adult wellbeing since 2015. Thus, the cognitive, psychological, social, physical and material dimensions of wellbeing form the framework for this scoping review and are overviewed in Figs. 1 and 2 , following. Overall student wellbeing is multi-faceted and the result of interactions among the five dimensions as shown in Fig. 1 . As described by the OECD ( 2017 ), each dimension has been positioned as both an outcome and enabling condition with respect to the other dimensions and students’ overall wellbeing. Notably, overall wellbeing, centred in the middle of the figure, is not measured in PISA. Unlike the cognitive/academic outcomes of reading, mathematics and science literacy, students do not receive a score that captures their wellbeing. Rather, wellbeing can be measured using a large range of indicators, either singly or in combination. More detail about this complexity is provided later. Another aspect of student wellbeing is that for educators, the rationale for evaluations of wellbeing has typically been to promote academic achievement (Borgonovi, 2022 ). Thus, most ILSA focus on the interaction between the cognitive dimension, which includes subject-specific achievement, and the other four dimensions of wellbeing as overviewed in Fig. 2 , following. To date, the relationship between overall wellbeing (which, again, is not measured in PISA) and the different dimensions of wellbeing (including multiple individual factors or indicators within each dimension) remains unclear. Courtney et al. ( 2023 ) identified challenges associated with managing the large number of individual wellbeing indicators and multiple wellbeing dimensions represented in the PISA questionnaires. They went on to describe diverse approaches to measure student wellbeing identified in the literature and concluded that there was no consensus as to the best way to measure student wellbeing. For example, some studies use a single PISA question to determine life satisfaction using a 0–10 Likert scale, whereas other studies combined scores from up to ten questions using 4-point or 6-point Likert scales to measure life satisfaction relating to health, life and school. Furthermore, some indicators within dimensions appear to be related, for example meaning in life and purpose in life , whilst others are empirically and conceptually distinguishable, for example eudaemonia and hedonia (Courtney et al., 2023 ). Some indicators and dimensions appear to have stronger predictive potential than others, routinely appearing as dependent variables in the literature, for example sense of belonging . Other variables appear as covariate, independent and/or control variables, for example gender . However, gender was not identified in the five dimensions presented by Borgonovi ( 2022 ). Thus, we added a sixth dimension to capture commonly reported control and other variables presented in the literature. Therefore, this scoping review aims to overview of the depth and breadth of the available research on factors exploring wellbeing using the PISA 2015 and 2018 datasets. Table 1 Summary of the dimensions of wellbeing measured in PISA 2015 and/or 2018 datasets Dimension Indicators Psychological Student’s self-reported psychological functioning, including: • Overall life satisfaction (0–10 point Likert scale) • Combined life satisfaction (combines multiple satisfaction item scores) • Goals and ambitions • Test and learning anxiety • Eudaemonia (meaning/purpose in life) • Affect Social The quality of student’s social lives within and beyond school, including: • Sense of belonging at school • Social learning experiences (cooperative learning spirit) • Relationship with teachers (perceptions of teachers’ attitudes) • Relationship with peers (engagement, bullying) • Relationship with parents (support, engagement) • School climate and support Cognitive Objective measures of students’ achievement in specific subjects: • reading • maths • science • focus area In addition, self-reported measures including: • General feelings of competence • Fear of failure • Mindset Physical Student’s self-reported perception of their physical health, including: • Amount of physical activity (at school and outside of school) • Eating habits (eating breakfast/dinner, parent and student eat together) • Physical health conditions (headache, stomach pain, back pain) • Mental health conditions (depression, irritability, anxiety) Material Student’s self-reported responses indicating availability of education, cultural and home durables, such as: • Parental occupation and education attainment • ESCS (economic social and cultural status) • Work in and beyond the household, with and without pay • Resources at school (human resources, physical resources) • Born in country of test, parents born in country of test taken • Language spoken at home • Worry about finances Control and Other Variables • Individual-level (age, gender, grade, grade repetition) • School-level (school type, school location, school sector) • Country/society-level (GDP, gender inequality) Adapted from Borgonovi ( 2022 ), Borgonovi and Pal (2016) and OECD ( 2019 ). Finally, subjective wellbeing is measured in PISA along the three dimensions of life satisfaction , purpose in life , and positive affect (OECD, 2013 ). All three measures are included in the psychological dimension as shown in Table 1 . These subjective measures of wellbeing are probably the closest to an overall wellbeing indicator that exists. This is because they undoubtedly reflect the presence of many other indicators. Sense of belonging - at school , in the social dimension, is likely to be an umbrella construct as well in the sense that it captures other indicators, for example, relationships with peers and teachers. 3.0 Methods The focus of this scoping review was to map the extent and range of literature exploring factors relating to wellbeing using the 2015 and 2018 PISA data sets. We used the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach (Page et al., 2021 ) and PRISMA Extension for Scoping Reviews (PRISMA-ScR) (Tricco et al., 2018 ) to systematically identify and include literature required to address the research questions. The four key phases relevant to this review based on the PRISMA and PRISMA-ScR are briefly described below. 3.1 Data Collection 3.1.1 Phase One: Literature identification. This phase involved a search for all literature published on student wellbeing using the 2015 or 2018 PISA data sets, or both. The search terms were developed through discussion and collaboration among the authors. The final list of search terms included ‘PISA systematic review’, ‘PISA wellbeing index’, ‘PISA and wellbeing’, and ‘student wellbeing PISA assessment’ across all the selected databases. The search terms were applied to the fields of ‘title’, ‘abstract’ and ‘keywords’, and the initial search date range spanned from 2015 to 2022. (In addition, a second screening of the literature was conducted to cover the period from December 2022 until July 2024). Keywords from the initial search results were scanned to determine if additional terms should be added. No new search terms were added. Alternative spellings (wellbeing, well-being and well being) were included in the literature search to ensure that articles were not missed due to spelling variations. The search terms were applied to key education databases, including ERIC (the Education Resources Information Centre), Scopus, ProQuest, Web of Science, our university library catalogue and Google Scholar. These databases were selected due to their coverage of the education research literature. The electronic search was limited to peer-reviewed publications in the English language. This initial search yielded a total of 69 items. The publication records were saved and managed in EndNote. We then used a ‘snowball’ method to search for additional articles by searching for studies that were referenced within the papers identified from the initial search. The reference lists of the initial 69 studies were reviewed by the authors to identify additional potential studies that contained PISA or wellbeing in their title, abstract or keywords list. An additional ten studies were located using this snowball method and were also added to the sample giving a new total of 79. 3.1.2 Phase Two: Screening and Eligibility . This phase involved the elimination of duplicate records and articles not meeting the eligibility criteria. One duplicate record was identified and eliminated from the sample. The remaining 78 articles were then screened using the eligibility criteria with none being removed. 3.1.3 Phase Three: Eligibility Criteria. The eligibility criteria used to screen the articles follows: Published in the English language Peer reviewed PISA and wellbeing appeared in the title, abstract or keywords Data were from PISA 2015, PISA 2018 or both Published after 2015 and before December 2022 (for the initial screening of literature). A total of 30 articles were eliminated from the initial sample of 78 for not meeting the inclusion criteria. Next, the full text of the remaining 48 articles were reviewed for eligibility. During this process, another six papers were excluded from the sample. 3.1.4 Phase Four: Inclusion . After the two-stage screening process, a total of 42 studies were included in this scoping review. The process of including articles involved the first and third authors reading the titles, abstracts and keywords of the articles independently, and then excluding studies that did not meet the inclusion criteria. The rate of agreement for inclusion of articles amongst the first and third authors was 91%. For contested articles a discussion amongst the first three authors continued until agreement was achieved. Before the final data synthesis, we conducted a second screening of the literature, limiting the search time frame from December 2022 to July 2024. We applied the same search strategies and elimination strategies, which yielded an additional four articles that were included in the sample, bringing the total to 46. The search methodology procedure is summarised in Fig. 3 , following. 3.2 Data extraction and synthesis All 46 eligible articles were exported from EndNote into NVivo for data extraction and synthesis (see Appendix 1 for summary of reviewed articles). The coding process involved the first author initially reading the title and abstract of each article to identify individual factors or indicators likely to appear in the results section. The methods section was then previewed with attention being paid to the definitions of factors which assisted in categorising each factor to one of the dimensions as shown in Table 1 . It also allowed decisions to be made about combining some terms that multiple authors used interchangeably in their respective papers, for example, purpose in life and meaning in life (e.g., Govorova et al., 2020 ; Marquez et al., 2022 ), as well as resilience and self-efficacy (e.g., Rodriguez et al., 2020). In addition, definitions provided in the method section allowed for more nuanced coding, for example in the method, sense of belonging may have been defined as “combining connectedness scores to family, peers, school and/or neighbourhood”, or only “relating to sense of belonging at school”, both were then referred to simply as sense of belonging in the results section of articles. Data from reported findings were assigned a level one, level two or level three code associated with one of the dimensions of wellbeing identified in the framework used for this scoping review. After the first 20 papers were analysed, the coding scheme was set by consolidating duplicates and adjusting the alignment of first, second and third level codes where necessary. At this point, the sixth dimension of control and other variables was added to capture factors commonly reported in the literature, that were not part of the five dimensions overviewed by Borgonovi ( 2022 ), for example, gender . 3.3 Interrater reliability Two interrater reliability tests were conducted. The first test related to the screening of articles identified for inclusion. As recommended by Multon ( 2010 ) at least two raters were involved in each test of interrater reliability. Articles initially identified by the third author were created as ‘cases’ within NVivo by the first author to verify the inclusion criteria had been met. Four articles were excluded at this stage, after consultation between the first three authors. The overall percentage agreement was 91% and well above the 70% recommended (Multon, 2010 ). The second test for interrater reliability related to the level of agreement for the codes allocated by authors one and four. After author one coded all 46 articles, author four independently coded 10% of the total number of articles (selected by a randomised number generating process). The consensus between the two coders was 92%. In addition, no new codes were identified during this second interrater reliability test. Non-agreement was resolved after discussion between the authors until consensus was achieved. 4.0 Results 4.1 Overview of study characteristics Of the included publications, a total of 63% drew on PISA 2018 data, 24% used PISA 2015 data, and 13% used both 2015 and 2018 data sets. The percentage of publications with wellbeing in their titles was 48. If wellbeing was not included in the title, wellbeing appeared in the abstract for 46% of articles. If not mentioned in the title or abstract, wellbeing appeared in the keywords for the remaining 6% of articles. All 46 articles reported quantitative findings. Most studies focused on a small number of countries (1–4) at 46%, followed by 43% for studies focused on many countries (11 or more), with 11% of studies including a medium number of countries (5–10). Where studies focused on less than 11 countries, 24 different countries were evaluated. The country that was studied most frequently was Spain, which appeared in nine of the 46 articles. The countries involved in the 2018 PISA optional wellbeing survey (Hong Kong, Bulgaria, Mexico, Serbia, Georgia, Ireland, United Arab Emirates, Spain and Panama) were studied more frequently than other countries along with the four Chinese economies of Beijing, Shanghai, Jiangsu and Zhejiang. See Fig. 4 following for a summary of all countries studied in included articles for this scoping review. The studies in our scoping review examined a range of dependent variables related to wellbeing. As wellbeing in PISA is conceptualised as a multidimensional construct with five dimensions, each of which includes several indicators, the number of possible dependent variables is extensive. The most commonly studied wellbeing variables were life satisfaction , positive affect and sense of belonging . Wellbeing variables were used both as predictor and outcome variables. For example, some studies examined the extent to which a psychological wellbeing indicator (e.g., life satisfaction ) predicted a social wellbeing indicator (e.g., sense of belonging - at school ). Some studies examined cognitive wellbeing (PISA achievement scores) as a predictor variable, while others examined how psychological or social wellbeing indicators predicted cognitive wellbeing. All studies included control variables related to student demographic and/or socio-cultural dimensions, and many included school-level and even societal-level variables as well. Table 2 illustrates the range of ways that various wellbeing variables were examined. Table 2 Wellbeing as predictive and outcome variables Control variables /covariates Wellbeing independent variables Wellbeing dependent variables Example Various None Social wellbeing (sense of belonging to school; victimisation) Psychological wellbeing (eudaemonia – sense of meaning or purpose; life satisfaction; positive affect) Basarkod et al. (2024) Various None Cognitive wellbeing (fear of failure) Borgonovi & Han (2021) Various None Psychological wellbeing (eudaemonia – sense of meaning or purpose; life satisfaction; positive affect) Liang et al. (2022) Various Social wellbeing (relationships) Psychological wellbeing (eudaemonia – sense of meaning or purpose) Chue & Yeo (2023) Various Social wellbeing (victimisation) Psychological wellbeing (life satisfaction; positive affect) Katsantonis et al. (2024) Various Psychological wellbeing (eudaemonia; affect; goal orientation) Cognitive wellbeing (resilience; fear of failure) Social wellbeing (parental support; sense of belonging) Cognitive wellbeing (reading, math and science literacy scores) Erdem & Kaya (2021) Various Cognitive wellbeing (reading and maths achievement) Social wellbeing (sense of belonging to school) Högberg & Lindgren (2023) The studies differed in the number of dependent variables measured. The percentage of studies that included 1–4 dependent variables was 80%, whereas articles examining 5–10 dependent variables was 15%, and only 5% studied 11 or more dependent variables. For other variables (independent, co-variate and control variables), for the categories of 5–10 variables and 11 or more variables, the percentage was 48% for each, and the remaining 4% of articles focused on between one and four other variables. The variety in number of dependent variables and number of countries studied included in this scoping review is summarised in Table 3 . Table 3 Summary of the number of dependent variables and countries included in studies Number of dependent variables Number of countries Number of articles Example 1–4 dependent variables 1–4 countries 16 Ambrosetti, A., Crotta, F., & Zampieri, S. (2017). PISA 2015: Expectations about future education and life satisfaction of Swiss students. In J. Marcionetti, L. Castelli, & A. Crescentini (Eds.), Well-being in education systems: Conference abstract book, Locarno, 2017 (pp. 129–133). Hogrete Editore. 5–10 dependent variables 1–4 countries 5 Huang, L. (2021). Bullying victimization, self-efficacy, fear of failure, and adolescents’ subjective well-being in China. Children and Youth Services Review , 127 (106084). https://doi.org/10.1016/j.childyouth.2021.106084 11 + dependent variables 1–4 countries 0 NA 1–4 dependent variables 5–10 counties 5 Chue, K. L., & Yeo, A. (2023). Exploring associations of positive relationships and adolescent well-being across cultures. Youth & Society , 55 (5), 873–894. https://doi.org/10.1177/0044118X221109305 5–10 dependent variables 5–10 counties 1 Meng, J., & Liu, S. (2022). Effects of culture on the balance between mathematics achievement and subjective wellbeing. Frontiers in Psychology , 13 (13:894774). https://doi.org/10.3389/fpsyg.2022.894774 11 + dependent variables 5–10 counties 0 NA 1–4 dependent variables 11 + countries 16 Högberg, B. (2023). Is there a trade-off between achievement and wellbeing in education systems? New cross-country evidence. Child Indicators Research , 16 , 2165–2186. https://doi.org/10.1007/s12187-023-10047-9 5–10 dependent variables 11 + countries 2 Basarkod, G., Dicke, T., Allen, K., Parker, P. D., Ryan, M., Marsh, H. W., Carrick, Z. T., & Guo, J. (2024). Do intercultural education and attitudes promote student wellbeing and social outcomes? An examination across PISA countries. Learning and Instruction , 91 (101879). https://doi.org/10.1016/j.learninstruc.2024.101879 11 + dependent variables 11 + countries 1 Guo, J., Basarkod, G., Perales, F., Parker, P. D., Marsh, H. W., Donald, J., Dicke, T., Sahdra, B. K., Ciarrochi, J., & Hu, X. (2022). The equality paradox: Gender equality intensifies male advantages in high school students’ subjective well-being. Personality and Social Psychology Bulletin , 1–18. https://doi.org/10.1177/01461672221125619 The most common range of dependent variables studied was 1–4, which covered a total of 80% of articles. Broken down further, for articles with 1–4 dependent variables the majority focused on 1–4 countries or 11 + countries, at 16 times for each, representing 70%, overall. An additional 2% of articles across the whole sample studied 1–4 dependent variables across 5–10 countries. 4.2 Emerging categories A total of 170 individual factors or indicators emerged from the data. Codes were categorised into the five core dimensions of the wellbeing framework used for this scoping review, as overviewed in Figs. 1 and 2 , and a sixth dimension for control and other variables as outlined in Table 1 . The number of factors or indicators identified in each dimension are presented in Fig. 5 following. The number of factors identified in each dimension, in descending order, were material (65), social (27), cognitive (25), psychological (23), control and other variables (20), and physical (10). Within the material dimension of wellbeing 19 factors or indicators were reported three or more times as overviewed in Fig. 6 following. The most common indicator studied in the material dimension, was family economic social and cultural status (ESCS) which appeared in 29 articles. Immigrant background (13), differences at the country level (11), school economic social and cultural status (6) and parents’ educational attainment (5) were the next four most prevalent factors studied within the material dimension of wellbeing. For the social dimension 15 factors or indicators were identified three or more times in the literature. These factors have been overviewed in Fig. 7 following. Sense of belonging – at school was the most prominent factor to emerge from the data appearing in 22 articles. Sense of belonging - at school was followed by being bullied (20), parent support (14) and teacher support (14). Sense of belonging - combined items and cooperation were the equal fifth in frequency with each being reported ten times in the literature reviewed. For the cognitive dimension 14 factors or indicators were identified three of more times in the literature. These factors have been presented in Fig. 8 following. For the cognitive dimension the most common factors identified three or more times in the literature were science achievement (14), mathematics achievement (13), fear of failure (12), reading achievement (10) and goal mastery orientation (8). For the psychological dimension, 10 factors or indicators were identified three or more times in the literature. These factors are presented in Fig. 9 following. The most common indicators studied in the psychological dimension were life satisfaction – single item (27), positive affect (23), eudaemonia (20). self-efficacy (13) and negative affect (11). The control and other predictor variables category emerged from the data as the dimension with the fifth greatest number of factors or indicators studied (n = 20). Seven factors were studied three or more times with the most frequent being gender , which was studied 30 times, followed by school type (9), age (8), grade repetition (7), gross domestic product (GDP) (5) and school location (5). For the physical dimension, six of the ten factors or indicators were studied three or more times, and these were body image (6), nutrition (3), perception of overall health (3) moderate physical activity (3), physical activity at school (3) and physical activity outside of school (3). Most factors (133) appeared in the literature reviewed between one and four times, with 21 factors appearing between five and ten times, and 16 factors appearing in the literature 11 or more times. Overall, the most common indicators studied were gender (30), family ESCS (29), life satisfaction - single item (27), positive affect (23) and sense of belonging - at school (22). However, if family ESCS (29) and school ESCS (6) were collated to give 35, sense of belonging - at school (22) and sense of belonging – combined items (10) were collated to give 32, and life satisfaction – single item (27) and life satisfaction – combined items (5) were collated to give 32, the five most studied factors in descending order were ESCS (35), sense of belonging (32), life satisfaction (32) gender (30) and positive affect (23). Further, if GDP was added to family ESCS and school ESCS, factors relating to social economic status remain the most studied factor, overall. 5.0 Discussion Our scoping review found the most commonly studied indicator of wellbeing was family ESCS from the material dimension, followed by the subjective measures of life satisfaction and positive affect from the psychological domain, and sense of belonging from the social domain. The wellbeing indicators have been studied both as outcomes as well as predictors of other outcomes. As would be expected, the common control variables of gender , economic, social and cultural status (ESCS) , and immigrant status were widely used as such in the studies included in our review. Many studies examined associations with cognitive wellbeing, usually defined as PISA scores in reading, mathematics and science achievement. Many studies also examined how specific wellbeing indicators (e.g., relationships with peers ) are related to the more general subjective wellbeing indicators, such as life satisfaction or positive affect . Some factors/indicators were studied less than others, for example those in the physical dimension relating to nutrition and physical activities outside of school , perhaps because these have traditionally been seen as the responsibility of families and therefore less likely to be positively impacted by education policies. In summary, one of the key messages from this scoping review is that there is immense complexity in the PISA student wellbeing literature, which is not surprising given its framing as a multidimensional construct. Although OECD reports overview individual factors from PISA cycles for individual countries, researchers have found it challenging to gain a clear picture of factors that predict overall levels of student wellbeing across countries and PISA cycles. It would appear different factors have different relevance for specific groups of students depending on the interaction between indicators at the individual, family, school, community, education system or society levels. For example, Borgonovi and Han (2021) found that fear of failure was higher for adolescents with higher reading scores who lacked a growth mindset . In addition, the authors reported a gender gap relating to fear of failure that was more pronounced amongst high achieving students and students with high achieving peers . The size of the gender gap for fear of failure also varied across countries, it was higher in countries with greater Gross Domestic Product ( GDP ) with low societal-level gender inequalities and comprehensive education systems . In a similar vein, Marquez and Main ( 2021 ) found student life satisfaction varied from country to country, for example the impact of education policy accounts for 36% of student life satisfaction in Iceland compared to 15% in Bulgaria. Furthermore, schools play a more important role in some societies than others in relation to life satisfaction . Such variation was explained by differences in responses to bullying and grade repetition , along with how students with different characteristics were concentrated in particular types of schools, study programmes and/or classrooms. In summary, the authors posited that a complex association exists between education policy and life satisfaction and called for more nuanced approaches to research that consider school-level characteristics, cross-society differences and factors at other levels of the child’s environment (individual, family, community), and the interconnections between them (Marquez & Main, 2021 ). Having identified 170 factors or indicators relating to wellbeing, further research is needed to identify the predictive power of different individual indicators, clusters of individual factors, the main predictors of each of the five dimensions of wellbeing (cognitive, psychological, social, physical and material) as well as more general subjective measures of wellbeing such as life satisfaction , and the impact of demographic, control and/or other variables. Such research could provide baseline measures useful at the individual, family, school, community, education system, province/state/region, education system or national level to inform policy and practice. Being able to identify strengths, weaknesses and opportunities at each of these levels could support the development of universal and targeted interventions to support the development of overall wellbeing and/or specific dimensions of wellbeing for school aged individuals. With declining levels of wellbeing worldwide, improving wellbeing outcomes during schooling has the potential to improve adulthood wellbeing with implications for workplaces and society. 5.1 Limitations The PISA assessment itself has both strengths and challenges, with scholars having called for caution when using data sets to make comparisons between countries and/or to inform policy (Hopfenbeck et al., 2018 ; Odell et al., 2020 ). Identified challenges relate to test constructs, assessment design, data collection and analysis, translation and language effects, curriculum and cultural fairness, bias and reliability. These are further complicated for wellbeing due to complications associated with not having a universal definition. In addition, whilst there is agreement that wellbeing is multidimensional there is no agreement about how many or which dimensions ought to be included. Furthermore, some factors identified within a particular dimension of the framework used for this study are more routinely reported in the educational research literature as control variables, for example, economic, social and cultural status (ESCS) , language spoken at home and immigrant background . Additional challenges arise around the sheer number of factors or indicators in each dimension. This has implications for the number of variables that researchers can control in any single study. In some instances, a single PISA question/item has been used to represent and measure one particular factor, for example the single question relating to overall life satisfaction (Likert scale 0–10). In other studies, to make the volume of data more manageable, authors have combined a small number of PISA questions/items to represent a single factor, for example combining eating breakfast , eating dinner , physical activity , physical education classes and test anxiety into the heading health behaviour and stress as done by Cho (2019). Although these strategies help to manage the large quantities of data, they limit the ability of researchers to make reliable evaluations regarding the impact that individual factors have on a particular dimension of wellbeing or indeed overall levels of wellbeing as measured by general subjective wellbeing measures such as life satisfaction . Finally, our study was limited by our search strategy and inclusion criteria. Our selection criteria required mention of wellbeing and PISA in either the title, abstract or keywords. These criteria were essential for maintaining focus and being systematic, but a disadvantage is that some articles that were clearly focused on an aspect of wellbeing as defined by PISA were excluded. This was typically done because the authors mentioned a specific indicator (for example, life satisfaction ) in the title, abstract or keywords but not wellbeing; Campbell et al. ( 2021 ) is an example of this. Fortunately, the number of studies excluded for this reason were small (n = 6). 5.2 Recommendations This scoping review examined factors included in studies exploring wellbeing using PISA 2015 and/or 2018 data sets. Based on our findings and limitations we make the following recommendations for future research as well as policy and practice. For future research, we recommend a series of systematic reviews of secondary analyses of PISA, as follows: Conduct systematic reviews for each of the other dimension of wellbeing (psychological, social, physical and material) as has been done for the academic achievement aspect of the cognitive dimension of wellbeing. Similarly, systematic reviews of other aspects of cognitive wellbeing, such as fear of failure and growth mindset , would be useful for the field. Conduct systematic reviews of the most prevalent wellbeing indicators uncovered in our study, namely life satisfaction , positive affect and sense of belonging . Conduct systematic reviews to identify factors/indicators with the greatest predictive power at the individual, family, school, sector, region/state/province or national level. Conduct systematic reviews of group differences in various dimensions of wellbeing, and the factors that predict them. These group differences could include student-level characteristics, for example, immigrant status , gender , social and cultural status (ESCS) or rural/urban locations . Examining how wellbeing varies between different groups of students could uncover inequalities that should be addressed. Group differences based on school factors (e.g., private versus public schools, socially mixed versus socially homogenous school contexts, socially advantaged versus socially disadvantaged school contexts, vocational versus academic tracks/institutions) would highlight policies and structures that could be promoted. Finally, cross-national differences are always useful for highlighting contextual features and configurations of educational policies and structures that may influence student wellbeing. For policy and practice, we recommend the following: Compare localised definitions of wellbeing with those in the literature before developing policy and practice aimed at improving overall wellbeing outcomes, outcomes for one or more individual dimensions of wellbeing, or one particular wellbeing factor/indicator. Encourage nuanced interventions at the state/region/province and/or national level that support overall wellbeing by acknowledging the power of broader political, cultural and economic societal conditions. 6.0 Conclusion This scoping review aimed to identify factors included in studies exploring wellbeing using PISA 2015 and 2018 data sets. Analysis revealed the existence of 170 individual factors or indicators categorised into five core dimensions, and a sixth dimension for control and other variables. The number of factors identified in each dimension were material (65), social (27), cognitive (25), psychological (23), physical (10) and control and other variables (20). Overall, the most common indicator studied was gender as independent or control variables associated with wellbeing. The second most studied factor was family ESCS , often as an independent or control variable, although classified as a material wellbeing factor in the framework used for this study. The next most studied factors were life satisfaction , positive affect and sense of belonging at school as indicators of wellbeing, either as independent or dependent variables. This scoping review constitutes a first step in elucidating important dimensions and indicators of wellbeing as reported in the literature. Due to its multidimensional nature, there is much complexity in the literature about wellbeing as measured in PISA. Future systematic reviews will go a long way towards identifying patterns and creating order in this rich but possibly overwhelming body of research. 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C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., . . . Straus, S. E. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine , 467-473. https://doi.org/10.7326/M18-0850 United Nations (nd). Department of Economic and Social Affairs, Sustainable Development. https://sdgs.un.org/goals World Health Organization [WHO], & the United Nations Children’s Fund [UNICEF]. (2024). Mental health of children and young people: Service guidance. Licence: CC BY-NC-SA 3.0 IGO. https://www.who.int/publications/i/item/9789240100374 Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":25253,"visible":true,"origin":"","legend":"\u003cp\u003eInter-relationships between the five dimensions of wellbeing\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/277886c47b04c84b30ce97e2.png"},{"id":94189393,"identity":"0143f58a-ef83-4e32-bb24-91e2147f4823","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":204563,"visible":true,"origin":"","legend":"\u003cp\u003eInteractions of dimensions affecting cognitive wellbeing\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/d23d932bbdc257d917215943.png"},{"id":94189390,"identity":"b7450a4d-d0f2-4df6-9c46-2f0bb2638d79","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56597,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of four phases to identify literature for inclusion based on PRISMA\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/84c3dd0a87ea93a1d99f7be3.png"},{"id":94189389,"identity":"3f25d644-063d-4d3e-9914-61b37629bfe0","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56714,"visible":true,"origin":"","legend":"\u003cp\u003eCountries/economies studied in articles focusing on less than 10 countries\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/eb457082d429f6caeb2ed45f.png"},{"id":94189404,"identity":"d9f95e1a-1cfc-45d3-9ce4-20e2046d5bce","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":21729,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of number of factors or indicators identified for each dimension of wellbeing\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/86d0afa2ea8ac980f1993659.png"},{"id":94189398,"identity":"95acb998-945e-4d5f-992e-415f9a073597","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":45283,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of material factors reported in articles three or more times\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/9b5f4fd81840ee75582537d4.png"},{"id":94189410,"identity":"23a94357-cde7-440d-b554-37c87f6f686a","added_by":"auto","created_at":"2025-10-23 11:39:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":54872,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of social factors reported in articles three or more times\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/d7715883465fb7cc5e64799b.png"},{"id":94189691,"identity":"edb1dcbf-9de7-415d-90a1-1ed3ebec4074","added_by":"auto","created_at":"2025-10-23 11:47:55","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":51000,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of cognitive factors reported in articles three or more times\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/8adef22b935cac5c424a372f.png"},{"id":94189689,"identity":"07ffd347-ac7d-4a3c-bc75-87781e56212e","added_by":"auto","created_at":"2025-10-23 11:47:55","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":40010,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of psychological factors reported in articles three or more times\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/be001b638f6e9cf5d66b28c4.png"},{"id":96243443,"identity":"392387a3-74ec-4a20-8e47-bad53764d37e","added_by":"auto","created_at":"2025-11-19 07:16:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1360218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/3a3cae77-5c77-4826-9974-0adcbe0f7e09.pdf"},{"id":94189388,"identity":"88268097-b54d-4d17-b345-c9ac9a9fec31","added_by":"auto","created_at":"2025-10-23 11:39:55","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29595,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1Summaryofincludedarticles.docx","url":"https://assets-eu.researchsquare.com/files/rs-7506445/v1/c31f0d4379c18f872198529e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring adolescent wellbeing: A scoping review","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eInterest in wellbeing is growing worldwide due to declining levels of wellbeing across all age groups, and among children and adolescents in particular. Previous studies have shown that wellbeing fluctuates throughout childhood and is often at its lowest during early adolescence (McClelland \u0026amp; Steward, 2015; NASEM, 2021; Suldo, 2016). This drop in wellbeing coincides with the onset of puberty, broadening face-to-face and online peer groups, along with experimentation with alcohol, other drugs and sexual behaviours (WHO \u0026amp; UNICEF, 2024). In addition, the wellbeing of children and adolescents has been identified as an important contributor to the educational outcomes of young people whilst they are at school, and wellbeing outcomes across the lifespan (Aldridge et al., 2016). In 2021, the WHO and UNICEF (2024) estimated that 15% of 10-19 year olds experienced mental illnesses such as anxiety, depression, conduct disorder and attention deficit hyperactivity disorder. Furthermore, the authors identified suicide as the third leading cause of death for 15-29 year olds in the same report. Failing to address declining levels of childhood wellbeing has been projected to have broad health, social and criminal justice implications (WHO \u0026amp; UNICEF, 2024). Promoting good health and wellbeing is enshrined as the United Nations\u0026rsquo; Sustainable Development Goal 3 (United Nations, nd).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInternational large-scale assessments (ILSA) have become increasingly important sources of data for education policy and reform, with the Organisation for Economic Co-operation and Development (OECD) becoming particularly powerful through its Programme for International Student Assessment (PISA). Since 2000, PISA has been administered every three years to 15-year olds, near the end of their compulsory education, across OECD countries and OECD partner countries or economies. PISA has traditionally focused on academic achievement in mathematics, science and reading, plus one other contemporary focus area such as problem solving, financial literacy or global competence. Since 2015, PISA has become unique as the first ILSA to examine specific elements of student wellbeing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile a universal definition of wellbeing has not emerged (Simons \u0026amp; Baldwin, 2021), there is\u0026nbsp;general agreement that wellbeing is a multi-faceted construct (Borgonovi \u0026amp; P\u0026aacute;l, 2016). The multi-faceted nature of wellbeing and its impact on school and life outcomes was highlighted by the OECD (2019, p. 223) in the below statement used to frame the development of its PISA questionnaire.\u003c/p\u003e\n\u003cp\u003eSuccess in school \u0026ndash; and in life \u0026ndash; also depends on being committed to learning, respecting and understanding others, being motivated to learn and being able to regulate one\u0026rsquo;s own behaviour. These constructs can be perceived as prerequisites to learning, but they may themselves also be judged as goals of education and important for success in life and overall wellbeing.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsistent with the literature, PISA\u0026rsquo;s operationalisation of wellbeing is similarly multi-faceted, comprising five dimensions. Each of these five dimensions of wellbeing comprise multiple wellbeing indicators. Unlike its academic achievement measure, there is no one single measure of wellbeing in PISA. In addition, PISA collects substantial information about students\u0026rsquo; characteristics and school environments, all of which can be used to examine relationships with wellbeing. The richness of data collected that can be used to examine wellbeing in PISA is one of its greatest strengths. At the same time, however, it presents tremendous complexity. For example, the field includes studies that examine predictors of a wide range of wellbeing indicators, studies that examine how various indicators of wellbeing predict academic achievement, as well as how some wellbeing indicators (e.g., sense of belonging) are related to other wellbeing indicators (e.g., positive affect).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe aim of this scoping review is to bring some order to the field by providing an overview of studies that have utilised PISA to understand student wellbeing. Which dimensions of wellbeing have been most studied, which factors have been examined, and what areas have not received as much attention? We see this study as a first step for enabling a comprehensive understanding of the various factors that are associated with the various dimensions of wellbeing. As noted by Borgonovi (2022), ILSAs have enabled researchers to map factors impacting cognitive achievement or the cognitive dimension of wellbeing across countries and world regions, and that it would also be beneficial to map the psychological, social, physical and material dimensions of wellbeing in the same way. Such mapping could facilitate the adoption of policies and practices that promote achievement and wellbeing without compromising one over the other (Hopfenbeck et al., 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the remainder of this paper, we will overview the theoretical framework for wellbeing used in this study, our data collection and analysis methods, our results and conclusions before implications, limitations and recommendations for future studies.\u003c/p\u003e"},{"header":"2.0 Theoretical framework: Dimensions of wellbeing","content":"\u003cp\u003eWellbeing is a ubiquitous term that can mean both everything and nothing at the same time (Powell et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a concept, wellbeing can be dated to the ancient Greek philosophers. Aristotle was credited with identifying eudaemonic elements of wellbeing such as leading a good life, flourishing and self-actualisation. On the other hand, Aristippus\u0026rsquo; contribution related to hedonism or the seeking of pleasure and happiness, which has been associated with contemporary understandings of subjective wellbeing. Perry et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) continued by stating themes relating to eudaemonia, hedonism and life satisfaction can be readily seen through the work of influential figures in psychology such as Maslow and Rogers in relation to humanist theory, Deci and Ryan regarding self-determination theory, Diener as an early researcher of subjective wellbeing, Csikszentmihalyi for his contribution of \u0026lsquo;flow\u0026rsquo;, and Seligman\u0026rsquo;s PERMA model (positive emotions, engagement, relationships, meaning and accomplishment) for flourishing as a key feature of positive psychology. In addition, Fattore et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) postulated wellbeing manifests itself as both a process and outcome that fluctuates and is negotiated over time.\u003c/p\u003e\u003cp\u003eWith reference to the wellbeing of children, two broad perspectives have been proposed. First, as a developmental approach which incorporates the different environments children experience based on Bronfenbrenner\u0026rsquo;s work (1981) and, secondly that children\u0026rsquo;s rights are just as important as adult\u0026rsquo;s rights (Borgonovi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). With children\u0026rsquo;s wellbeing identified as an important determinant of educational outcomes whilst at school, and broader wellbeing outcomes as adults (Aldridge et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), there has been increased interest in how countries fare both academically and in the promotion of student wellbeing (OECD, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As there is no universal definition of wellbeing (Simons \u0026amp; Baldwin, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) or agreed upon tool to measure adolescent wellbeing, this scoping review, as recommended by Mak and Thomas (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Tricco et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), aims to map existing evidence to identify the range, extent and nature of factors reported in the literature relating to the research questions. As such, this scoping review constitutes a first step in elucidating important dimensions and factors or indicators used to define, measure and predict adolescent wellbeing.\u003c/p\u003e\u003cp\u003eAs this scoping review was focused on research in relation to the PISA 2015 and 2018 data sets, we started with the OECD\u0026rsquo;s definition of wellbeing for children as the \u0026ldquo;psychological, cognitive, social and physical functioning and capabilities that students need to live a happy and fulfilling life\u0026rdquo; (OECD, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, p. 35). We chose to adopt a definition that also included the material dimension of wellbeing as this was done by Borgonovi (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Borgonovi and Pal (2016) and Resino et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). An additional rationale is that material conditions have formed one of two major headings in the OECD\u0026rsquo;s \u003cem\u003eHow\u0026rsquo;s Life?\u003c/em\u003e framework to evaluate adult wellbeing since 2015. Thus, the cognitive, psychological, social, physical and material dimensions of wellbeing form the framework for this scoping review and are overviewed in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, following.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOverall student wellbeing is multi-faceted and the result of interactions among the five dimensions as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. As described by the OECD (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), each dimension has been positioned as both an outcome and enabling condition with respect to the other dimensions and students\u0026rsquo; overall wellbeing. Notably, overall wellbeing, centred in the middle of the figure, is not measured in PISA. Unlike the cognitive/academic outcomes of reading, mathematics and science literacy, students do not receive a score that captures their wellbeing. Rather, wellbeing can be measured using a large range of indicators, either singly or in combination. More detail about this complexity is provided later.\u003c/p\u003e\u003cp\u003eAnother aspect of student wellbeing is that for educators, the rationale for evaluations of wellbeing has typically been to promote academic achievement (Borgonovi, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, most ILSA focus on the interaction between the cognitive dimension, which includes subject-specific achievement, and the other four dimensions of wellbeing as overviewed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, following.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo date, the relationship between overall wellbeing (which, again, is not measured in PISA) and the different dimensions of wellbeing (including multiple individual factors or indicators within each dimension) remains unclear. Courtney et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) identified challenges associated with managing the large number of individual wellbeing indicators and multiple wellbeing dimensions represented in the PISA questionnaires. They went on to describe diverse approaches to measure student wellbeing identified in the literature and concluded that there was no consensus as to the best way to measure student wellbeing. For example, some studies use a single PISA question to determine \u003cem\u003elife satisfaction\u003c/em\u003e using a 0\u0026ndash;10 Likert scale, whereas other studies combined scores from up to ten questions using 4-point or 6-point Likert scales to measure \u003cem\u003elife satisfaction\u003c/em\u003e relating to health, life and school. Furthermore, some indicators within dimensions appear to be related, for example \u003cem\u003emeaning in life\u003c/em\u003e and \u003cem\u003epurpose in life\u003c/em\u003e, whilst others are empirically and conceptually distinguishable, for example \u003cem\u003eeudaemonia\u003c/em\u003e and \u003cem\u003ehedonia\u003c/em\u003e (Courtney et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Some indicators and dimensions appear to have stronger predictive potential than others, routinely appearing as dependent variables in the literature, for example \u003cem\u003esense of belonging\u003c/em\u003e. Other variables appear as covariate, independent and/or control variables, for example \u003cem\u003egender\u003c/em\u003e. However, gender was not identified in the five dimensions presented by Borgonovi (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, we added a sixth dimension to capture commonly reported control and other variables presented in the literature. Therefore, this scoping review aims to overview of the depth and breadth of the available research on factors exploring wellbeing using the PISA 2015 and 2018 datasets.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of the dimensions of wellbeing measured in PISA 2015 and/or 2018 datasets\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndicators\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u0026rsquo;s self-reported psychological functioning, including:\u003c/p\u003e\u003cp\u003e\u0026bull; Overall life satisfaction (0\u0026ndash;10 point Likert scale)\u003c/p\u003e\u003cp\u003e\u0026bull; Combined life satisfaction (combines multiple satisfaction item scores)\u003c/p\u003e\u003cp\u003e\u0026bull; Goals and ambitions\u003c/p\u003e\u003cp\u003e\u0026bull; Test and learning anxiety\u003c/p\u003e\u003cp\u003e\u0026bull; Eudaemonia (meaning/purpose in life)\u003c/p\u003e\u003cp\u003e\u0026bull; Affect\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe quality of student\u0026rsquo;s social lives within and beyond school, including:\u003c/p\u003e\u003cp\u003e\u0026bull; Sense of belonging at school\u003c/p\u003e\u003cp\u003e\u0026bull; Social learning experiences (cooperative learning spirit)\u003c/p\u003e\u003cp\u003e\u0026bull; Relationship with teachers (perceptions of teachers\u0026rsquo; attitudes)\u003c/p\u003e\u003cp\u003e\u0026bull; Relationship with peers (engagement, bullying)\u003c/p\u003e\u003cp\u003e\u0026bull; Relationship with parents (support, engagement)\u003c/p\u003e\u003cp\u003e\u0026bull; School climate and support\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObjective measures of students\u0026rsquo; achievement in specific subjects:\u003c/p\u003e\u003cp\u003e\u0026bull; reading\u003c/p\u003e\u003cp\u003e\u0026bull; maths\u003c/p\u003e\u003cp\u003e\u0026bull; science\u003c/p\u003e\u003cp\u003e\u0026bull; focus area\u003c/p\u003e\u003cp\u003eIn addition, self-reported measures including:\u003c/p\u003e\u003cp\u003e\u0026bull; General feelings of competence\u003c/p\u003e\u003cp\u003e\u0026bull; Fear of failure\u003c/p\u003e\u003cp\u003e\u0026bull; Mindset\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u0026rsquo;s self-reported perception of their physical health, including:\u003c/p\u003e\u003cp\u003e\u0026bull; Amount of physical activity (at school and outside of school)\u003c/p\u003e\u003cp\u003e\u0026bull; Eating habits (eating breakfast/dinner, parent and student eat together)\u003c/p\u003e\u003cp\u003e\u0026bull; Physical health conditions (headache, stomach pain, back pain)\u003c/p\u003e\u003cp\u003e\u0026bull; Mental health conditions (depression, irritability, anxiety)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaterial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudent\u0026rsquo;s self-reported responses indicating availability of education, cultural and home durables, such as:\u003c/p\u003e\u003cp\u003e\u0026bull; Parental occupation and education attainment\u003c/p\u003e\u003cp\u003e\u0026bull; ESCS (economic social and cultural status)\u003c/p\u003e\u003cp\u003e\u0026bull; Work in and beyond the household, with and without pay\u003c/p\u003e\u003cp\u003e\u0026bull; Resources at school (human resources, physical resources)\u003c/p\u003e\u003cp\u003e\u0026bull; Born in country of test, parents born in country of test taken\u003c/p\u003e\u003cp\u003e\u0026bull; Language spoken at home\u003c/p\u003e\u003cp\u003e\u0026bull; Worry about finances\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControl and Other Variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026bull; Individual-level (age, gender, grade, grade repetition)\u003c/p\u003e\u003cp\u003e\u0026bull; School-level (school type, school location, school sector)\u003c/p\u003e\u003cp\u003e\u0026bull; Country/society-level (GDP, gender inequality)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAdapted from Borgonovi (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Borgonovi and Pal (2016) and OECD (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, subjective wellbeing is measured in PISA along the three dimensions of \u003cem\u003elife satisfaction\u003c/em\u003e, \u003cem\u003epurpose in life\u003c/em\u003e, and \u003cem\u003epositive affect\u003c/em\u003e (OECD, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). All three measures are included in the psychological dimension as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These subjective measures of wellbeing are probably the closest to an overall wellbeing indicator that exists. This is because they undoubtedly reflect the presence of many other indicators. \u003cem\u003eSense of belonging\u003c/em\u003e - \u003cem\u003eat school\u003c/em\u003e, in the social dimension, is likely to be an umbrella construct as well in the sense that it captures other indicators, for example, relationships with peers and teachers.\u003c/p\u003e"},{"header":"3.0 Methods","content":"\u003cp\u003eThe focus of this scoping review was to map the extent and range of literature exploring factors relating to wellbeing using the 2015 and 2018 PISA data sets. We used the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach (Page et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and PRISMA Extension for Scoping Reviews (PRISMA-ScR) (Tricco et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) to systematically identify and include literature required to address the research questions. The four key phases relevant to this review based on the PRISMA and PRISMA-ScR are briefly described below.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Data Collection\u003c/h2\u003e\u003cp\u003e\u003cb\u003e3.1.1 Phase One: Literature identification.\u003c/b\u003e This phase involved a search for all literature published on student wellbeing using the 2015 or 2018 PISA data sets, or both. The search terms were developed through discussion and collaboration among the authors. The final list of search terms included \u0026lsquo;PISA systematic review\u0026rsquo;, \u0026lsquo;PISA wellbeing index\u0026rsquo;, \u0026lsquo;PISA and wellbeing\u0026rsquo;, and \u0026lsquo;student wellbeing PISA assessment\u0026rsquo; across all the selected databases. The search terms were applied to the fields of \u0026lsquo;title\u0026rsquo;, \u0026lsquo;abstract\u0026rsquo; and \u0026lsquo;keywords\u0026rsquo;, and the initial search date range spanned from 2015 to 2022. (In addition, a second screening of the literature was conducted to cover the period from December 2022 until July 2024). Keywords from the initial search results were scanned to determine if additional terms should be added. No new search terms were added. Alternative spellings (wellbeing, well-being and well being) were included in the literature search to ensure that articles were not missed due to spelling variations.\u003c/p\u003e\u003cp\u003eThe search terms were applied to key education databases, including ERIC (the Education Resources Information Centre), Scopus, ProQuest, Web of Science, our university library catalogue and Google Scholar. These databases were selected due to their coverage of the education research literature. The electronic search was limited to peer-reviewed publications in the English language. This initial search yielded a total of 69 items. The publication records were saved and managed in EndNote. We then used a \u0026lsquo;snowball\u0026rsquo; method to search for additional articles by searching for studies that were referenced within the papers identified from the initial search. The reference lists of the initial 69 studies were reviewed by the authors to identify additional potential studies that contained PISA or wellbeing in their title, abstract or keywords list. An additional ten studies were located using this snowball method and were also added to the sample giving a new total of 79.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.1.2 Phase Two: Screening and Eligibility\u003c/b\u003e. This phase involved the elimination of duplicate records and articles not meeting the eligibility criteria. One duplicate record was identified and eliminated from the sample. The remaining 78 articles were then screened using the eligibility criteria with none being removed.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e\u003cb\u003e3.1.3 Phase Three: Eligibility Criteria.\u003c/b\u003e The eligibility criteria used to screen the articles follows:\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ePublished in the English language\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePeer reviewed\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePISA and wellbeing appeared in the title, abstract or keywords\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eData were from PISA 2015, PISA 2018 or both\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePublished after 2015 and before December 2022 (for the initial screening of literature).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eA total of 30 articles were eliminated from the initial sample of 78 for not meeting the inclusion criteria. Next, the full text of the remaining 48 articles were reviewed for eligibility. During this process, another six papers were excluded from the sample.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.1.4 Phase Four: Inclusion\u003c/b\u003e. After the two-stage screening process, a total of 42 studies were included in this scoping review. The process of including articles involved the first and third authors reading the titles, abstracts and keywords of the articles independently, and then excluding studies that did not meet the inclusion criteria. The rate of agreement for inclusion of articles amongst the first and third authors was 91%. For contested articles a discussion amongst the first three authors continued until agreement was achieved. Before the final data synthesis, we conducted a second screening of the literature, limiting the search time frame from December 2022 to July 2024. We applied the same search strategies and elimination strategies, which yielded an additional four articles that were included in the sample, bringing the total to 46. The search methodology procedure is summarised in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, following.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Data extraction and synthesis\u003c/h2\u003e\u003cp\u003eAll 46 eligible articles were exported from EndNote into NVivo for data extraction and synthesis (see Appendix 1 for summary of reviewed articles). The coding process involved the first author initially reading the title and abstract of each article to identify individual factors or indicators likely to appear in the results section. The methods section was then previewed with attention being paid to the definitions of factors which assisted in categorising each factor to one of the dimensions as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. It also allowed decisions to be made about combining some terms that multiple authors used interchangeably in their respective papers, for example, \u003cem\u003epurpose in life\u003c/em\u003e and \u003cem\u003emeaning in life\u003c/em\u003e (e.g., Govorova et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Marquez et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), as well as \u003cem\u003eresilience\u003c/em\u003e and \u003cem\u003eself-efficacy\u003c/em\u003e (e.g., Rodriguez et al., 2020). In addition, definitions provided in the method section allowed for more nuanced coding, for example in the method, \u003cem\u003esense of belonging\u003c/em\u003e may have been defined as \u0026ldquo;combining connectedness scores to family, peers, school and/or neighbourhood\u0026rdquo;, or only \u0026ldquo;relating to sense of belonging at school\u0026rdquo;, both were then referred to simply as \u003cem\u003esense of belonging\u003c/em\u003e in the results section of articles. Data from reported findings were assigned a level one, level two or level three code associated with one of the dimensions of wellbeing identified in the framework used for this scoping review. After the first 20 papers were analysed, the coding scheme was set by consolidating duplicates and adjusting the alignment of first, second and third level codes where necessary. At this point, the sixth dimension of control and other variables was added to capture factors commonly reported in the literature, that were not part of the five dimensions overviewed by Borgonovi (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), for example, \u003cem\u003egender\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Interrater reliability\u003c/h2\u003e\u003cp\u003eTwo interrater reliability tests were conducted. The first test related to the screening of articles identified for inclusion. As recommended by Multon (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) at least two raters were involved in each test of interrater reliability. Articles initially identified by the third author were created as \u0026lsquo;cases\u0026rsquo; within NVivo by the first author to verify the inclusion criteria had been met. Four articles were excluded at this stage, after consultation between the first three authors. The overall percentage agreement was 91% and well above the 70% recommended (Multon, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The second test for interrater reliability related to the level of agreement for the codes allocated by authors one and four. After author one coded all 46 articles, author four independently coded 10% of the total number of articles (selected by a randomised number generating process). The consensus between the two coders was 92%. In addition, no new codes were identified during this second interrater reliability test. Non-agreement was resolved after discussion between the authors until consensus was achieved.\u003c/p\u003e\u003c/div\u003e"},{"header":"4.0 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Overview of study characteristics\u003c/h2\u003e\n \u003cp\u003eOf the included publications, a total of 63% drew on PISA 2018 data, 24% used PISA 2015 data, and 13% used both 2015 and 2018 data sets. The percentage of publications with wellbeing in their titles was 48. If wellbeing was not included in the title, wellbeing appeared in the abstract for 46% of articles. If not mentioned in the title or abstract, wellbeing appeared in the keywords for the remaining 6% of articles. All 46 articles reported quantitative findings. Most studies focused on a small number of countries (1\u0026ndash;4) at 46%, followed by 43% for studies focused on many countries (11 or more), with 11% of studies including a medium number of countries (5\u0026ndash;10). Where studies focused on less than 11 countries, 24 different countries were evaluated. The country that was studied most frequently was Spain, which appeared in nine of the 46 articles. The countries involved in the 2018 PISA optional wellbeing survey (Hong Kong, Bulgaria, Mexico, Serbia, Georgia, Ireland, United Arab Emirates, Spain and Panama) were studied more frequently than other countries along with the four Chinese economies of Beijing, Shanghai, Jiangsu and Zhejiang. See Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e following for a summary of all countries studied in included articles for this scoping review.\u003c/p\u003e\n \u003cp\u003eThe studies in our scoping review examined a range of dependent variables related to wellbeing. As wellbeing in PISA is conceptualised as a multidimensional construct with five dimensions, each of which includes several indicators, the number of possible dependent variables is extensive. The most commonly studied wellbeing variables were \u003cem\u003elife satisfaction\u003c/em\u003e, \u003cem\u003epositive affect\u003c/em\u003e and \u003cem\u003esense of belonging\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003eWellbeing variables were used both as predictor and outcome variables. For example, some studies examined the extent to which a psychological wellbeing indicator (e.g., \u003cem\u003elife satisfaction\u003c/em\u003e) predicted a social wellbeing indicator (e.g., \u003cem\u003esense of belonging - at school\u003c/em\u003e). Some studies examined cognitive wellbeing (PISA achievement scores) as a predictor variable, while others examined how psychological or social wellbeing indicators predicted cognitive wellbeing. All studies included control variables related to student demographic and/or socio-cultural dimensions, and many included school-level and even societal-level variables as well. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the range of ways that various wellbeing variables were examined.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eWellbeing as predictive and outcome variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl variables /covariates\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWellbeing independent variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWellbeing dependent variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExample\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial wellbeing (sense of belonging to school; victimisation)\u003c/p\u003e\n \u003cp\u003ePsychological wellbeing (eudaemonia \u0026ndash; sense of meaning or purpose; life satisfaction; positive affect)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasarkod et al. (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCognitive wellbeing (fear of failure)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBorgonovi \u0026amp; Han (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological wellbeing (eudaemonia \u0026ndash; sense of meaning or purpose; life satisfaction; positive affect)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiang et al. (2022)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial wellbeing (relationships)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological wellbeing (eudaemonia \u0026ndash; sense of meaning or purpose)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChue \u0026amp; Yeo (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial wellbeing (victimisation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological wellbeing (life satisfaction; positive affect)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKatsantonis et al. (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsychological wellbeing (eudaemonia; affect; goal orientation)\u003c/p\u003e\n \u003cp\u003eCognitive wellbeing (resilience; fear of failure)\u003c/p\u003e\n \u003cp\u003eSocial wellbeing (parental support; sense of belonging)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCognitive wellbeing (reading, math and science literacy scores)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eErdem \u0026amp; Kaya (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCognitive wellbeing (reading and maths achievement)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial wellbeing (sense of belonging to school)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH\u0026ouml;gberg \u0026amp; Lindgren (2023)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe studies differed in the number of dependent variables measured. The percentage of studies that included 1\u0026ndash;4 dependent variables was 80%, whereas articles examining 5\u0026ndash;10 dependent variables was 15%, and only 5% studied 11 or more dependent variables.\u003c/p\u003e\n \u003cp\u003eFor other variables (independent, co-variate and control variables), for the categories of 5\u0026ndash;10 variables and 11 or more variables, the percentage was 48% for each, and the remaining 4% of articles focused on between one and four other variables. The variety in number of dependent variables and number of countries studied included in this scoping review is summarised in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary of the number of dependent variables and countries included in studies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of dependent variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of countries\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of articles\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExample\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmbrosetti, A., Crotta, F., \u0026amp; Zampieri, S. (2017). PISA 2015: Expectations about future education and life satisfaction of Swiss students. In J. Marcionetti, L. Castelli, \u0026amp; A. Crescentini (Eds.), \u003cem\u003eWell-being in education systems: Conference abstract book, Locarno, 2017\u003c/em\u003e (pp. 129\u0026ndash;133). Hogrete Editore.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuang, L. (2021). Bullying victimization, self-efficacy, fear of failure, and adolescents\u0026rsquo; subjective well-being in China. \u003cem\u003eChildren and Youth Services Review\u003c/em\u003e, \u003cem\u003e127\u003c/em\u003e(106084). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.childyouth.2021.106084\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 counties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChue, K. L., \u0026amp; Yeo, A. (2023). Exploring associations of positive relationships and adolescent well-being across cultures. \u003cem\u003eYouth \u0026amp; Society\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(5), 873\u0026ndash;894. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0044118X221109305\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 counties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeng, J., \u0026amp; Liu, S. (2022). Effects of culture on the balance between mathematics achievement and subjective wellbeing. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(13:894774). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2022.894774\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 counties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;4 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eH\u0026ouml;gberg, B. (2023). Is there a trade-off between achievement and wellbeing in education systems? New cross-country evidence. \u003cem\u003eChild Indicators Research\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e, 2165\u0026ndash;2186. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12187-023-10047-9\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;10 dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBasarkod, G., Dicke, T., Allen, K., Parker, P. D., Ryan, M., Marsh, H. W., Carrick, Z. T., \u0026amp; Guo, J. (2024). Do intercultural education and attitudes promote student wellbeing and social outcomes? An examination across PISA countries. \u003cem\u003eLearning and Instruction\u003c/em\u003e, \u003cem\u003e91\u003c/em\u003e(101879). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.learninstruc.2024.101879\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;dependent variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026thinsp;+\u0026thinsp;countries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGuo, J., Basarkod, G., Perales, F., Parker, P. D., Marsh, H. W., Donald, J., Dicke, T., Sahdra, B. K., Ciarrochi, J., \u0026amp; Hu, X. (2022). The equality paradox: Gender equality intensifies male advantages in high school students\u0026rsquo; subjective well-being. \u003cem\u003ePersonality and Social Psychology Bulletin\u003c/em\u003e, 1\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/01461672221125619\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe most common range of dependent variables studied was 1\u0026ndash;4, which covered a total of 80% of articles. Broken down further, for articles with 1\u0026ndash;4 dependent variables the majority focused on 1\u0026ndash;4 countries or 11\u0026thinsp;+\u0026thinsp;countries, at 16 times for each, representing 70%, overall. An additional 2% of articles across the whole sample studied 1\u0026ndash;4 dependent variables across 5\u0026ndash;10 countries.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2 Emerging categories\u003c/h2\u003e\n \u003cp\u003eA total of 170 individual factors or indicators emerged from the data. Codes were categorised into the five core dimensions of the wellbeing framework used for this scoping review, as overviewed in Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, and a sixth dimension for control and other variables as outlined in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The number of factors or indicators identified in each dimension are presented in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e following.\u003c/p\u003e\n \u003cp\u003eThe number of factors identified in each dimension, in descending order, were material (65), social (27), cognitive (25), psychological (23), control and other variables (20), and physical (10). Within the material dimension of wellbeing 19 factors or indicators were reported three or more times as overviewed in Fig. 6 following.\u003c/p\u003e\n \u003cp\u003eThe most common indicator studied in the material dimension, was \u003cem\u003efamily economic social and cultural status\u003c/em\u003e (ESCS) which appeared in 29 articles. \u003cem\u003eImmigrant background\u003c/em\u003e (13), \u003cem\u003edifferences at the country level\u003c/em\u003e (11), \u003cem\u003eschool economic social and cultural status\u003c/em\u003e (6) and \u003cem\u003eparents\u0026rsquo; educational attainment\u003c/em\u003e (5) were the next four most prevalent factors studied within the material dimension of wellbeing.\u003c/p\u003e\n \u003cp\u003eFor the social dimension 15 factors or indicators were identified three or more times in the literature. These factors have been overviewed in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e following.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eSense of belonging \u0026ndash; at school\u003c/em\u003e was the most prominent factor to emerge from the data appearing in 22 articles. \u003cem\u003eSense of belonging - at school\u003c/em\u003e was followed by \u003cem\u003ebeing bullied\u003c/em\u003e (20), \u003cem\u003eparent support\u003c/em\u003e (14) and \u003cem\u003eteacher support\u003c/em\u003e (14). \u003cem\u003eSense of belonging - combined items\u003c/em\u003e and \u003cem\u003ecooperation\u003c/em\u003e were the equal fifth in frequency with each being reported ten times in the literature reviewed.\u003c/p\u003e\n \u003cp\u003eFor the cognitive dimension 14 factors or indicators were identified three of more times in the literature. These factors have been presented in Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e following.\u003c/p\u003e\n \u003cp\u003eFor the cognitive dimension the most common factors identified three or more times in the literature were \u003cem\u003escience achievement\u003c/em\u003e (14), \u003cem\u003emathematics achievement\u003c/em\u003e (13), \u003cem\u003efear of failure\u003c/em\u003e (12), \u003cem\u003ereading achievement\u003c/em\u003e (10) and \u003cem\u003egoal mastery orientation\u003c/em\u003e (8).\u003c/p\u003e\n \u003cp\u003eFor the psychological dimension, 10 factors or indicators were identified three or more times in the literature. These factors are presented in Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e following.\u003c/p\u003e\n \u003cp\u003eThe most common indicators studied in the psychological dimension were \u003cem\u003elife satisfaction \u0026ndash; single item\u003c/em\u003e (27), \u003cem\u003epositive affect\u003c/em\u003e (23), \u003cem\u003eeudaemonia\u003c/em\u003e (20). \u003cem\u003eself-efficacy\u003c/em\u003e (13) and \u003cem\u003enegative affect\u003c/em\u003e (11).\u003c/p\u003e\n \u003cp\u003eThe control and other predictor variables category emerged from the data as the dimension with the fifth greatest number of factors or indicators studied (n\u0026thinsp;=\u0026thinsp;20). Seven factors were studied three or more times with the most frequent being \u003cem\u003egender\u003c/em\u003e, which was studied 30 times, followed by \u003cem\u003eschool type\u003c/em\u003e (9), \u003cem\u003eage\u003c/em\u003e (8), \u003cem\u003egrade repetition\u003c/em\u003e (7), \u003cem\u003egross domestic product (GDP)\u003c/em\u003e (5) and \u003cem\u003eschool location\u003c/em\u003e (5).\u003c/p\u003e\n \u003cp\u003eFor the physical dimension, six of the ten factors or indicators were studied three or more times, and these were \u003cem\u003ebody image\u003c/em\u003e (6), \u003cem\u003enutrition\u003c/em\u003e (3), \u003cem\u003eperception of overall health\u003c/em\u003e (3) \u003cem\u003emoderate physical activity\u003c/em\u003e (3), \u003cem\u003ephysical activity at school\u003c/em\u003e (3) and \u003cem\u003ephysical activity outside of school\u003c/em\u003e (3).\u003c/p\u003e\n \u003cp\u003eMost factors (133) appeared in the literature reviewed between one and four times, with 21 factors appearing between five and ten times, and 16 factors appearing in the literature 11 or more times. Overall, the most common indicators studied were \u003cem\u003egender\u003c/em\u003e (30), \u003cem\u003efamily ESCS\u003c/em\u003e (29), \u003cem\u003elife satisfaction - single item\u003c/em\u003e (27), \u003cem\u003epositive affect\u003c/em\u003e (23) and \u003cem\u003esense of belonging - at school\u003c/em\u003e (22). However, if \u003cem\u003efamily ESCS\u003c/em\u003e (29) and \u003cem\u003eschool ESCS\u003c/em\u003e (6) were collated to give 35, \u003cem\u003esense of belonging - at school\u003c/em\u003e (22) and \u003cem\u003esense of belonging \u0026ndash; combined items\u003c/em\u003e (10) were collated to give 32, and \u003cem\u003elife satisfaction \u0026ndash; single item\u003c/em\u003e (27) and \u003cem\u003elife satisfaction \u0026ndash; combined items\u003c/em\u003e (5) were collated to give 32, the five most studied factors in descending order were \u003cem\u003eESCS\u003c/em\u003e (35), \u003cem\u003esense of belonging\u003c/em\u003e (32), \u003cem\u003elife satisfaction\u003c/em\u003e (32) \u003cem\u003egender\u003c/em\u003e (30) and \u003cem\u003epositive affect\u003c/em\u003e (23). Further, if GDP was added to family ESCS and school ESCS, factors relating to social economic status remain the most studied factor, overall.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5.0 Discussion","content":"\u003cp\u003eOur scoping review found the most commonly studied indicator of wellbeing was \u003cem\u003efamily ESCS\u003c/em\u003e from the material dimension, followed by the subjective measures of \u003cem\u003elife satisfaction\u003c/em\u003e and \u003cem\u003epositive affect\u003c/em\u003e from the psychological domain, and \u003cem\u003esense of belonging\u003c/em\u003e from the social domain. The wellbeing indicators have been studied both as outcomes as well as predictors of other outcomes. As would be expected, the common control variables of \u003cem\u003egender\u003c/em\u003e, \u003cem\u003eeconomic, social and cultural status (ESCS)\u003c/em\u003e, and \u003cem\u003eimmigrant status\u003c/em\u003e were widely used as such in the studies included in our review. Many studies examined associations with cognitive wellbeing, usually defined as PISA scores in reading, mathematics and science achievement. Many studies also examined how specific wellbeing indicators (e.g., \u003cem\u003erelationships with peers\u003c/em\u003e) are related to the more general subjective wellbeing indicators, such as \u003cem\u003elife satisfaction\u003c/em\u003e or \u003cem\u003epositive affect\u003c/em\u003e. Some factors/indicators were studied less than others, for example those in the physical dimension relating to \u003cem\u003enutrition\u003c/em\u003e and \u003cem\u003ephysical activities outside of school\u003c/em\u003e, perhaps because these have traditionally been seen as the responsibility of families and therefore less likely to be positively impacted by education policies. In summary, one of the key messages from this scoping review is that there is immense complexity in the PISA student wellbeing literature, which is not surprising given its framing as a multidimensional construct.\u003c/p\u003e\n\u003cp\u003eAlthough OECD reports overview individual factors from PISA cycles for individual countries, researchers have found it challenging to gain a clear picture of factors that predict overall levels of student wellbeing across countries and PISA cycles. It would appear different factors have different relevance for specific groups of students depending on the interaction between indicators at the individual, family, school, community, education system or society levels. For example, Borgonovi and Han (2021) found that \u003cem\u003efear of failure\u003c/em\u003e was higher for adolescents with higher \u003cem\u003ereading scores\u003c/em\u003e who lacked a \u003cem\u003egrowth mindset\u003c/em\u003e. In addition, the authors reported a gender gap relating to \u003cem\u003efear of failure\u003c/em\u003e that was more pronounced amongst \u003cem\u003ehigh achieving students\u003c/em\u003e and students with \u003cem\u003ehigh achieving peers\u003c/em\u003e. The size of the gender gap for \u003cem\u003efear of failure\u003c/em\u003e also varied across countries, it was higher in countries with greater \u003cem\u003eGross Domestic Product\u003c/em\u003e (\u003cem\u003eGDP\u003c/em\u003e) with low societal-level \u003cem\u003egender inequalities\u003c/em\u003e and \u003cem\u003ecomprehensive education systems\u003c/em\u003e. In a similar vein, Marquez and Main (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) found student \u003cem\u003elife satisfaction\u003c/em\u003e varied from country to country, for example the impact of education policy accounts for 36% of student \u003cem\u003elife satisfaction\u003c/em\u003e in Iceland compared to 15% in Bulgaria. Furthermore, schools play a more important role in some societies than others in relation to \u003cem\u003elife satisfaction\u003c/em\u003e. Such variation was explained by differences in responses to \u003cem\u003ebullying\u003c/em\u003e and \u003cem\u003egrade repetition\u003c/em\u003e, along with how students with different characteristics were concentrated in particular types of schools, study programmes and/or classrooms. In summary, the authors posited that a complex association exists between education policy and \u003cem\u003elife satisfaction\u003c/em\u003e and called for more nuanced approaches to research that consider school-level characteristics, cross-society differences and factors at other levels of the child\u0026rsquo;s environment (individual, family, community), and the interconnections between them (Marquez \u0026amp; Main, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eHaving identified 170 factors or indicators relating to wellbeing, further research is needed to identify the predictive power of different individual indicators, clusters of individual factors, the main predictors of each of the five dimensions of wellbeing (cognitive, psychological, social, physical and material) as well as more general subjective measures of wellbeing such as \u003cem\u003elife satisfaction\u003c/em\u003e, and the impact of demographic, control and/or other variables. Such research could provide baseline measures useful at the individual, family, school, community, education system, province/state/region, education system or national level to inform policy and practice. Being able to identify strengths, weaknesses and opportunities at each of these levels could support the development of universal and targeted interventions to support the development of overall wellbeing and/or specific dimensions of wellbeing for school aged individuals. With declining levels of wellbeing worldwide, improving wellbeing outcomes during schooling has the potential to improve adulthood wellbeing with implications for workplaces and society.\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e5.1 Limitations\u003c/h2\u003e\n \u003cp\u003eThe PISA assessment itself has both strengths and challenges, with scholars having called for caution when using data sets to make comparisons between countries and/or to inform policy (Hopfenbeck et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Odell et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Identified challenges relate to test constructs, assessment design, data collection and analysis, translation and language effects, curriculum and cultural fairness, bias and reliability. These are further complicated for wellbeing due to complications associated with not having a universal definition. In addition, whilst there is agreement that wellbeing is multidimensional there is no agreement about how many or which dimensions ought to be included. Furthermore, some factors identified within a particular dimension of the framework used for this study are more routinely reported in the educational research literature as control variables, for example, \u003cem\u003eeconomic, social and cultural status (ESCS)\u003c/em\u003e, \u003cem\u003elanguage spoken at home\u003c/em\u003e and \u003cem\u003eimmigrant background\u003c/em\u003e. Additional challenges arise around the sheer number of factors or indicators in each dimension. This has implications for the number of variables that researchers can control in any single study. In some instances, a single PISA question/item has been used to represent and measure one particular factor, for example the single question relating to overall life satisfaction (Likert scale 0\u0026ndash;10). In other studies, to make the volume of data more manageable, authors have combined a small number of PISA questions/items to represent a single factor, for example combining \u003cem\u003eeating breakfast\u003c/em\u003e, \u003cem\u003eeating dinner\u003c/em\u003e, \u003cem\u003ephysical activity\u003c/em\u003e, \u003cem\u003ephysical education classes\u003c/em\u003e and \u003cem\u003etest anxiety\u003c/em\u003e into the heading \u003cem\u003ehealth behaviour and stress\u003c/em\u003e as done by Cho (2019). Although these strategies help to manage the large quantities of data, they limit the ability of researchers to make reliable evaluations regarding the impact that individual factors have on a particular dimension of wellbeing or indeed overall levels of wellbeing as measured by general subjective wellbeing measures such as \u003cem\u003elife satisfaction\u003c/em\u003e.\u003c/p\u003e\n \u003cp\u003eFinally, our study was limited by our search strategy and inclusion criteria. Our selection criteria required mention of wellbeing and PISA in either the title, abstract or keywords. These criteria were essential for maintaining focus and being systematic, but a disadvantage is that some articles that were clearly focused on an aspect of wellbeing as defined by PISA were excluded. This was typically done because the authors mentioned a specific indicator (for example, \u003cem\u003elife satisfaction\u003c/em\u003e) in the title, abstract or keywords but not wellbeing; Campbell et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) is an example of this. Fortunately, the number of studies excluded for this reason were small (n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e5.2 Recommendations\u003c/h2\u003e\n\u003c/div\u003e\n\u003cp\u003eThis scoping review examined factors included in studies exploring wellbeing using PISA 2015 and/or 2018 data sets. Based on our findings and limitations we make the following recommendations for future research as well as policy and practice. For future research, we recommend a series of systematic reviews of secondary analyses of PISA, as follows:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eConduct systematic reviews for each of the other dimension of wellbeing (psychological, social, physical and material) as has been done for the academic achievement aspect of the cognitive dimension of wellbeing. Similarly, systematic reviews of other aspects of cognitive wellbeing, such as \u003cem\u003efear of failure\u003c/em\u003e and \u003cem\u003egrowth mindset\u003c/em\u003e, would be useful for the field.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eConduct systematic reviews of the most prevalent wellbeing indicators uncovered in our study, namely \u003cem\u003elife satisfaction\u003c/em\u003e, \u003cem\u003epositive affect and sense of belonging\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eConduct systematic reviews to identify factors/indicators with the greatest predictive power at the individual, family, school, sector, region/state/province or national level.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eConduct systematic reviews of group differences in various dimensions of wellbeing, and the factors that predict them. These group differences could include student-level characteristics, for example, \u003cem\u003eimmigrant status\u003c/em\u003e, \u003cem\u003egender\u003c/em\u003e, \u003cem\u003esocial and cultural status (ESCS)\u003c/em\u003e or \u003cem\u003erural/urban locations\u003c/em\u003e. Examining how wellbeing varies between different groups of students could uncover inequalities that should be addressed. Group differences based on school factors (e.g., private versus public schools, socially mixed versus socially homogenous school contexts, socially advantaged versus socially disadvantaged school contexts, vocational versus academic tracks/institutions) would highlight policies and structures that could be promoted. Finally, cross-national differences are always useful for highlighting contextual features and configurations of educational policies and structures that may influence student wellbeing.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFor policy and practice, we recommend the following:\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003eCompare localised definitions of wellbeing with those in the literature before developing policy and practice aimed at improving overall wellbeing outcomes, outcomes for one or more individual dimensions of wellbeing, or one particular wellbeing factor/indicator.\u003c/li\u003e\n \u003cli\u003eEncourage nuanced interventions at the state/region/province and/or national level that support overall wellbeing by acknowledging the power of broader political, cultural and economic societal conditions.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"6.0 Conclusion","content":"\u003cp\u003eThis scoping review aimed to identify factors included in studies exploring wellbeing using PISA 2015 and 2018 data sets. Analysis revealed the existence of 170 individual factors or indicators categorised into five core dimensions, and a sixth dimension for control and other variables. The number of factors identified in each dimension were material (65), social (27), cognitive (25), psychological (23), physical (10) and control and other variables (20). Overall, the most common indicator studied was \u003cem\u003egender\u003c/em\u003e as independent or control variables associated with wellbeing. The second most studied factor was \u003cem\u003efamily ESCS\u003c/em\u003e, often as an independent or control variable, although classified as a material wellbeing factor in the framework used for this study. The next most studied factors were \u003cem\u003elife satisfaction\u003c/em\u003e, \u003cem\u003epositive affect\u003c/em\u003e and \u003cem\u003esense of belonging at school\u003c/em\u003e as indicators of wellbeing, either as independent or dependent variables. This scoping review constitutes a first step in elucidating important dimensions and indicators of wellbeing as reported in the literature. Due to its multidimensional nature, there is much complexity in the literature about wellbeing as measured in PISA. Future systematic reviews will go a long way towards identifying patterns and creating order in this rich but possibly overwhelming body of research.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eGM led the entire project and was a major contributor to data collection and analysis, and writing the manuscript. LP conceptualised the project, interpreted the findings, and contributed to writing the manuscript. MB performed data collection and analysis. XW provided guidance about the PRISMA framework, analysed data and created figures and tables. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAldridge, J. M., Fraser, B. J., Fozdar, F., Ala\u0026rsquo;i, K., Earnest, J., \u0026amp; Afari, E. (2016). Students\u0026rsquo; perceptions of school climate as determinants of wellbeing, resilience and identity. \u003cem\u003eImproving Schools\u003c/em\u003e,\u003cem\u003e 19\u003c/em\u003e(1), 5-26. https://doi.org/10.1177/1365480215612616 \u003c/li\u003e\n\u003cli\u003eBorgonovi, F. (2022). Well-being in international large-scale assessments. In T. Nilsen, A. Stancel-Piątak, \u0026amp; J.-E. Gustafsson (Eds.), \u003cem\u003eInternational handbook of comparative large-scale studies in education: Perspectives, methods and findings\u003c/em\u003e (pp. 1-26). Springer. https://doi.org/10.1007/978-3-030-38298-8_45-1 \u003c/li\u003e\n\u003cli\u003eBorgonovi, F., \u0026amp; P\u0026aacute;l, J. 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Sage. https://doi.org/10.4135/9781529783506.n23 \u003c/li\u003e\n\u003cli\u003ePowell, M. A., Graham, A., Fitzgerald, R., Thomas, N., \u0026amp; White, N. E. (2018). Wellbeing in schools: What do students tell us? \u003cem\u003eAustralian Educational Researcher\u003c/em\u003e,\u003cem\u003e 45\u003c/em\u003e, 515-531. https://doi.org/10.1007/s13384-018-0273-z\u003c/li\u003e\n\u003cli\u003eResino, D. A., Constante-Amores, A., Madrona, P. G., \u0026amp; L\u0026oacute;pez, P. J. C. (2024). Student well-being and mathematical literacy performance in PISA 2018: A machine-learning approach. \u003cem\u003eEducational Psychology\u003c/em\u003e,\u003cem\u003e 44\u003c/em\u003e(3), 340-357. https://doi.org/10.1080/01443410.2024.2359104 \u003c/li\u003e\n\u003cli\u003eSimons, G., \u0026amp; Baldwin, D. S. (2021). A critical review of the definition of \u0026lsquo;wellbeing\u0026rsquo; for doctors and their patients in a post Covid-19 era. \u003cem\u003eInternational Journal of Social Psychiatry\u003c/em\u003e, 984-999. https://doi.org/10.1177/00207640211032259 \u003c/li\u003e\n\u003cli\u003eSuldo, S. (2016). Factors associated with youth subjective well-being. In \u003cem\u003ePromoting student happiness : Positive psychology interventions in schools\u003c/em\u003e (pp. 28-36). Guilford. https://ebookcentral.proquest.com/lib/murdoch/detail.action?docID=4439757 \u003c/li\u003e\n\u003cli\u003eThe National Academies of Science Engineering Medicine [NASEM]. (2019). \u003cem\u003ePromoting positive adolescent health behaviors and outcomes: Thriving in the 21\u003csup\u003est\u003c/sup\u003e Century\u003c/em\u003e. The National Academies Press. https://doi.org/10.17226/25552\u003c/li\u003e\n\u003cli\u003eTricco, A. C., Lillie, E., Zarin, W., O\u0026apos;Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., . . . Straus, S. E. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. \u003cem\u003eAnnals of Internal Medicine\u003c/em\u003e, 467-473. https://doi.org/10.7326/M18-0850 \u003c/li\u003e\n\u003cli\u003eUnited Nations (nd). Department of Economic and Social Affairs, Sustainable Development. https://sdgs.un.org/goals\u003c/li\u003e\n\u003cli\u003eWorld Health Organization [WHO], \u0026amp; the United Nations Children\u0026rsquo;s Fund [UNICEF]. (2024). \u003cem\u003eMental health of children and young people: Service guidance.\u003c/em\u003e Licence: CC BY-NC-SA 3.0 IGO. https://www.who.int/publications/i/item/9789240100374\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"adolescent wellbeing, Programme of International Student Assessment (PISA), scoping review, predictors, life satisfaction","lastPublishedDoi":"10.21203/rs.3.rs-7506445/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7506445/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePISA is the only international large-scale assessment to specifically examine adolescent wellbeing alongside academic achievement. Wellbeing in PISA is a multidimensional construct comprising many indicators or factors for each of five main dimensions. An overall wellbeing score, like there is for academic achievement, does not exist at the student-level. Many secondary analyses of wellbeing in PISA have been conducted but the field is fragmented due to the large number of factors that are associated with the different dimensions of wellbeing. A further complexity is that various dimensions and indicators of wellbeing have been studied as both predictor and outcome variables. Our aim with this scoping review is to bring order to the field by mapping the various factors that are associated with the various dimensions of wellbeing. Through the systematic selection process, 46 secondary analyses of PISA 2015 or PISA 2018, the two cycles that examined wellbeing in depth, were identified for inclusion. Analysis revealed the existence of 170 individual factors or indicators categorised into five core dimensions of wellbeing (psychological, cognitive, social, physical and material), plus a sixth dimension for control and other variables. Overall, the most common individual factors studied were gender, economic social and cultural status, life satisfaction, positive affect\u003cem\u003e \u003c/em\u003eand sense of belonging. A series of systematic reviews, about individual indicators and dimensions, is recommended to further extend the field. Systematic reviews about group differences based on individual or school-level characteristics would be especially fruitful.\u003c/p\u003e","manuscriptTitle":"Exploring adolescent wellbeing: A scoping review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 11:39:50","doi":"10.21203/rs.3.rs-7506445/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e95a632-c7ab-477b-aca9-7760f65cebf2","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-14T07:38:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 11:39:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7506445","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7506445","identity":"rs-7506445","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}