{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T07:15:53Z","timestamp":1788419753178,"version":"build-2803163510"},"reference-count":62,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>School belonging and mathematics anxiety reflect distinct relational and motivational processes, but cross-economy comparisons can blur distinctions among psychological relationships, model-based importance, and questionnaire availability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed Program for International Student Assessment (PISA) 2022 data from 613,744 students; outcome-valid samples comprised 561,339 students in 78 economies for school belonging and 475,792 students in 76 economies for mathematics anxiety. Per-economy LightGBM models and TreeSHAP rankings estimated relative predictive salience. Secondary post-hoc analyses assessed economy-level predictor availability, excluded unadministered modules, and fitted complementary association models. Official individualism scores covered 74 economies; outcome-eligible reference sets covered 73 for belonging and 70 for anxiety.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Eight of 12 focal combinations retained stable relative predictive salience and formed two psychologically interpretable predictor patterns. Perceived school safety, exposure to bullying, and student-teacher relations formed a relational-institutional pattern for belonging, while mathematics self-efficacy, 21st-century-skills self-efficacy, achievement, growth mindset, and persistence formed an efficacy-achievement-engagement pattern for mathematics anxiety. In separate weighted economy fixed-effects samples of 241,786-476,803 students, safety (\u03b2 = 0.323) and student-teacher relations (\u03b2 = 0.282) were positively associated with belonging, exposure to bullying was negatively associated (\u03b2 = 0.253), and the five focal mathematics predictors were negatively associated with anxiety (\u03b2 = \u22120.080 to \u22120.340). Continuous individualism interactions were small (absolute \u03b2 \u2264 0.047), inconsistent, and multilevel sensitivity models retained the direction of every main association. Four combinations involving stress resistance, assertiveness, and cooperation failed the availability criterion because these indices were much less available in low-individualism economies and unevenly distributed across IDV terciles.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The evidence therefore supported stable relative predictive salience across economies more strongly than individualism-related differentiation. Together, the predictive rankings and association models provided complementary evidence for these two patterns but did not establish psychological mechanisms, causal effects, or transferable intervention benefits.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1875261","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T06:40:35Z","timestamp":1788417635000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Cross-economy stability of predictor rankings for adolescent school belonging and mathematics anxiety: an explainable machine-learning analysis of PISA 2022"],"prefix":"10.3389","volume":"17","author":[{"given":"Yuan","family":"Liao","sequence":"first","affiliation":[{"name":"School of Intelligence Technology, Geely University of China, Chengdu","place":["Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Intelligence Technology, Geely University of China, Chengdu","place":["Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runlin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Intelligence Technology, Geely University of China, Chengdu","place":["Sichuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"21201","DOI":"10.1007\/s00521-023-08901-6","article-title":"Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015-2018 data","volume":"35","author":"Ac\u0131sl\u0131-Celik","year":"2023","journal-title":"Neural Comput. Applic"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e0326121","DOI":"10.1371\/journal.pone.0326121","article-title":"Educational improvement through machine learning: strategic models for better PISA scores","volume":"20","author":"Alkan","year":"2025","journal-title":"PLoS ONE"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10648-016-9389-8","article-title":"What schools need to know about fostering school belonging: a meta-analysis","volume":"30","author":"Allen","year":"2018","journal-title":"Educ. Psychol. Rev"},{"key":"B4","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1007\/s10648-025-10055-x","article-title":"School belonging: evidence, experts, and everyday gaps","volume":"37","author":"Allen","year":"2025","journal-title":"Educ. Psychol. Rev"},{"key":"B5","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/s12310-023-09626-6","article-title":"Adolescent school belonging and mental health outcomes in young adulthood: findings from a multi-wave prospective cohort study","volume":"16","author":"Allen","year":"2024","journal-title":"School Mental Health"},{"key":"B6","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1080\/00049530.2021.1883409","article-title":"Belonging: a review of conceptual issues, an integrative framework, and directions for future research","volume":"73","author":"Allen","year":"2021","journal-title":"Austral. J. Psychol"},{"key":"B7","doi-asserted-by":"publisher","first-page":"e70290","DOI":"10.1111\/ejed.70290","article-title":"Defining school belonging: a cross-cultural investigation of student-led conceptualisations","volume":"60","author":"Allen","year":"2025","journal-title":"Eur. J. Educ"},{"key":"B8","doi-asserted-by":"publisher","first-page":"105166","DOI":"10.1016\/j.compedu.2024.105166","article-title":"Uncovering student profiles. an explainable cluster analysis approach to PISA 2022","volume":"223","author":"Alvarez-Garcia","year":"2024","journal-title":"Comput. Educ"},{"key":"B9","doi-asserted-by":"publisher","first-page":"6679","DOI":"10.1609\/aaai.v35i8.16826","article-title":"TabNet: attentive interpretable tabular learning","volume":"35","author":"Arik","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell"},{"key":"B10","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1080\/01443410.2024.2359104","article-title":"Student well-being and mathematical literacy performance in PISA 2018: a machine-learning approach","volume":"44","author":"Arroyo Resino","year":"2024","journal-title":"Educ. Psychol"},{"key":"B11","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1080\/10705511.2014.919210","article-title":"Multiple-group factor analysis alignment","volume":"21","author":"Asparouhov","year":"2014","journal-title":"Struct. Equat. Model.: Multidiscipl. J"},{"key":"B12","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1037\/0033-295X.84.2.191","article-title":"Self-efficacy: toward a unifying theory of behavioral change","volume":"84","author":"Bandura","year":"1977","journal-title":"Psychol. Rev"},{"key":"B13","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1037\/bul0000307","article-title":"A meta-analysis of the relation between math anxiety and math achievement","volume":"147","author":"Barroso","year":"2021","journal-title":"Psychol. Bull"},{"key":"B14","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1037\/0033-2909.117.3.497","article-title":"The need to belong: desire for interpersonal attachments as a fundamental human motivation","volume":"117","author":"Baumeister","year":"1995","journal-title":"Psychol. Bull"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.3390\/math11061318","article-title":"An analysis of PISA 2018 mathematics assessment for asia-pacific countries using educational data mining","volume":"11","author":"Bayirli","year":"2023","journal-title":"Mathematics"},{"key":"B16","doi-asserted-by":"publisher","first-page":"7499","DOI":"10.1109\/TNNLS.2022.3229161","article-title":"Deep neural networks and tabular data: a survey","volume":"35","author":"Borisov","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst"},{"key":"B17","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1007\/s10648-021-09618-5","article-title":"Math performance and academic anxiety forms, from sociodemographic to cognitive aspects: a meta-analysis on 906,311 participants","volume":"34","author":"Caviola","year":"2022","journal-title":"Educ. Psychol. Rev"},{"key":"B18","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1145\/2939672.2939785","article-title":"\u201cXGBoost: a scalable tree boosting system,\u201d","author":"Chen","year":"2016","journal-title":"Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining"},{"key":"B19","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.1111\/bjep.12715","article-title":"A machine-learning model of academic resilience in the times of the COVID-19 pandemic: evidence drawn from 79 countries\/economies in the PISA 2022 mathematics study","volume":"94","author":"Cheung","year":"2024","journal-title":"Br. J. Educ. Psychol"},{"key":"B20","doi-asserted-by":"publisher","first-page":"582","DOI":"10.3390\/educsci15050582","article-title":"Interventions to improve connectedness, belonging, and engagement in secondary schools: a systematic review and meta-analysis","volume":"15","author":"Davies","year":"2025","journal-title":"Educ. Sci"},{"key":"B21","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1007\/s10212-022-00623-y","article-title":"Testing measurement invariance of mathematics self-concept and self-efficacy in PISA using MGCFA and the alignment method","volume":"38","author":"Ding","year":"2023","journal-title":"Eur. J. Psychol. Educ"},{"key":"B22","doi-asserted-by":"publisher","first-page":"1594131","DOI":"10.3389\/fpsyg.2025.1594131","article-title":"The mediating role of math self-efficacy between school-based parental involvement and math performance among students in Southeast Asia: evidence from PISA 2022","volume":"16","author":"Djekourmane","year":"2025","journal-title":"Front. Psychol"},{"key":"B23","doi-asserted-by":"publisher","first-page":"1697010","DOI":"10.3389\/feduc.2025.1697010","article-title":"Multilevel determinants of school belonging: the moderating role of national safety climate","volume":"10","author":"Elizondo-Gonz\u00e1lez","year":"2025","journal-title":"Front. Educ"},{"key":"B24","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1002\/1520-6807(199301)30:1(79::AID-PITS2310300113)3.0.CO;2-X","article-title":"The psychological sense of school membership among adolescents: scale development and educational correlates","volume":"30","author":"Goodenow","year":"1993","journal-title":"Psychol. Schools"},{"key":"B25","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1038\/s41586-024-08328-6","article-title":"Accurate predictions on small data with a tabular foundation model","volume":"637","author":"Hollmann","year":"2025","journal-title":"Nature"},{"key":"B26","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1177\/1073191103010002008","article-title":"The Abbreviated Math Anxiety Scale (AMAS): construction, validity, and reliability","volume":"10","author":"Hopko","year":"2003","journal-title":"Assessment"},{"key":"B27","doi-asserted-by":"publisher","first-page":"93","DOI":"10.3390\/jintelligence12100093","article-title":"Applying machine learning and SHAP method to identify key influences on middle-school students' mathematics literacy performance","volume":"12","author":"Huang","year":"2024","journal-title":"J. Intell"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1080\/0305764X.2026.2688797","article-title":"The link between perceived academic control, responsibility and the development of reading skills","author":"Jerrim","year":"2026","journal-title":"Cambridge J. Educ"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.21203\/rs.3.rs-8286764\/v1","article-title":"Always read the data documentation carefully. a case study using PISA data","author":"Jerrim","year":"2026","journal-title":"Res. Square"},{"key":"B30","doi-asserted-by":"publisher","author":"Jerrim","year":"2026","DOI":"10.1080\/03050068.2026.2681383"},{"key":"B31","doi-asserted-by":"publisher","first-page":"13492","DOI":"10.1007\/s12144-023-05280-y","article-title":"Where does culture belong at school? Exploring the role of individualism and power distance in school belonging across cultures","volume":"43","author":"Johnson","year":"2024","journal-title":"Curr. Psychol"},{"key":"B32","first-page":"3146","article-title":"\u201cLightGBM: a highly efficient gradient boosting decision tree,\u201d","author":"Ke","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"B33","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/978-3-030-47515-4_3","article-title":"\u201cPlausible values: principles of item response theory and multiple imputations,\u201d","author":"Khorramdel","year":"2020","journal-title":"Large-Scale Cognitive Assessment"},{"key":"B34","doi-asserted-by":"publisher","first-page":"8376","DOI":"10.1038\/s41598-024-55461-3","article-title":"Identifying the top predictors of student well-being across cultures using machine learning and conventional statistics","volume":"14","author":"King","year":"2024","journal-title":"Sci. Rep"},{"key":"B35","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1080\/02671522.2019.1615116","article-title":"The relationships between school belonging and students' motivational, social-emotional, behavioural, and academic outcomes in secondary education: a meta-analytic review","volume":"35","author":"Korpershoek","year":"2020","journal-title":"Res. Papers Educ"},{"key":"B36","doi-asserted-by":"publisher","first-page":"e2115855119","DOI":"10.1073\/pnas.2115855119","article-title":"Disentangling the individual and contextual effects of math anxiety: a global perspective","volume":"119","author":"Lau","year":"2022","journal-title":"Proc. Nat. Acad. Sci. U. S. A"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1416631","DOI":"10.3389\/fpsyg.2024.1416631","article-title":"Investigating adolescent psychological wellbeing in an educational context using PISA 2018 Canadian data","volume":"15","author":"Liu","year":"2024","journal-title":"Front. Psychol"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1705.07874","author":"Lundberg","year":"2017","journal-title":"A Unified Approach to Interpreting Model Predictions"},{"key":"B39","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat. Mach. Intell"},{"key":"B40","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1037\/bul0000352","article-title":"Do growth mindset interventions impact students' academic achievement? A systematic review and meta-analysis with recommendations for best practices","volume":"149","author":"Macnamara","year":"2023","journal-title":"Psychol. Bull"},{"key":"B41","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s40536-021-00099-0","article-title":"Sampling weights in multilevel modelling: an investigation using PISA sampling structures","volume":"9","author":"Mang","year":"2021","journal-title":"Large-scale Assess. Educ"},{"key":"B42","doi-asserted-by":"publisher","first-page":"100971","DOI":"10.1016\/j.intman.2022.100971","article-title":"Do dimensions of culture exist objectively? a validation of the revised Minkov-Hofstede model of culture with World Values Survey items and scores for 102 countries","volume":"28","author":"Minkov","year":"2022","journal-title":"J. Int. Manag"},{"key":"B43","doi-asserted-by":"publisher","first-page":"459","DOI":"10.3102\/0034654319843494","article-title":"The relation between mathematics anxiety and mathematics performance among school-aged students: a meta-analysis","volume":"89","author":"Namkung","year":"2019","journal-title":"Rev. Educ. Res"},{"key":"B44","year":"","journal-title":"PISA 2022 Results (Volume I): The State of Learning and Equity in Education"},{"key":"B45","year":"","journal-title":"PISA 2022 Results (Volume II): Learning During-and From-Disruption"},{"key":"B46","doi-asserted-by":"publisher","year":"2024","journal-title":"PISA 2022 Technical Report","DOI":"10.1787\/01820d6d-en"},{"key":"B47","doi-asserted-by":"publisher","first-page":"1113996","DOI":"10.3389\/feduc.2023.1113996","article-title":"Cooperative and competitive school climate: their impact on sense of belonging across cultures","volume":"8","author":"Ooi","year":"2023","journal-title":"Front. Educ"},{"key":"B48","doi-asserted-by":"publisher","first-page":"7753","DOI":"10.1007\/s10639-024-13110-2","article-title":"Stacking: an ensemble learning approach to predict student performance in PISA 2022","volume":"30","author":"\u00d6z","year":"2025","journal-title":"Edu. Inform. Technol"},{"key":"B49","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1007\/s12310-024-09725-y","article-title":"Individual and contextual factors determining school belonging of adolescents in the UK: evidence from PISA","volume":"17","author":"Palikara","year":"2025","journal-title":"School Ment. Health"},{"key":"B50","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/s10648-006-9029-9","article-title":"The control-value theory of achievement emotions: assumptions, corollaries, and implications for educational research and practice","volume":"18","author":"Pekrun","year":"2006","journal-title":"Educ. Psychol. Rev"},{"key":"B51","doi-asserted-by":"publisher","first-page":"100489","DOI":"10.1016\/j.ijedro.2025.100489","article-title":"The impact of the pandemic and school closures on non-cognitive characteristics: evidence from PISA","volume":"9","author":"Quintero Pe\u00f1a","year":"2025","journal-title":"Int. J. Educ. Res. Open"},{"key":"B52","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1177\/07342829241262861","article-title":"Combining statistical and machine learning methods to identify predictors of brazilian students' proficiency in PISA 2018","volume":"42","author":"San Martin Soares","year":"2024","journal-title":"J. Psychoeduc. Assess"},{"key":"B53","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.inffus.2021.11.011","article-title":"Tabular data: deep learning is not all you need","volume":"81","author":"Shwartz-Ziv","year":"2022","journal-title":"Inform. Fus"},{"key":"B54","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1177\/09637214241300111","article-title":"Developing effective interventions for math anxiety","volume":"34","author":"Sidney","year":"2025","journal-title":"Curr. Dir. Psychol. Sci"},{"key":"B55","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1007\/s10639-024-12921-7","article-title":"Evaluating measurement invariance of students' practices regarding online information questionnaire in PISA 2022: a comparative study using MGCFA and alignment method","volume":"30","author":"S\u00f6zer Boz","year":"2025","journal-title":"Educ. Inform. Technol"},{"key":"B56","year":"2023","journal-title":"Country Comparison Tool. Individualism and Long-Term-Orientation Scores Updated 16 October 2023"},{"key":"B57","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1177\/109442810031002","article-title":"A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research","volume":"3","author":"Vandenberg","year":"2000","journal-title":"Organ. Res. Methods"},{"key":"B58","doi-asserted-by":"publisher","first-page":"1646854","DOI":"10.3389\/fpsyg.2025.1646854","article-title":"How does digital learning resource accessibility affects math learning anxiety in high school\u2013an empirical analysis based on PISA 2022","volume":"16","author":"Wang","year":"2025","journal-title":"Front. Psychol"},{"key":"B59","doi-asserted-by":"publisher","first-page":"1863","DOI":"10.1177\/0956797615602471","article-title":"Is math anxiety always bad for math learning? The role of math motivation","volume":"26","author":"Wang","year":"2015","journal-title":"Psychol. Sci"},{"key":"B60","doi-asserted-by":"publisher","first-page":"1368451","DOI":"10.3389\/fpsyg.2024.1368451","article-title":"School belonging mediates the association between negative school climate and depressive symptoms among Chinese adolescents: a national population-based longitudinal study","volume":"15","author":"Yin","year":"2024","journal-title":"Front. Psychol"},{"key":"B61","doi-asserted-by":"publisher","first-page":"101412","DOI":"10.1016\/j.stueduc.2024.101412","article-title":"Predicting the mathematics literacy of resilient students from high-performing economies: a machine learning approach","volume":"83","author":"Zhang","year":"2024","journal-title":"Stud. Educ. Eval"},{"key":"B62","doi-asserted-by":"publisher","first-page":"102537","DOI":"10.1016\/j.ijer.2025.102537","article-title":"Predictive insights into U.S. students' mathematics performance on PISA 2022 using ensemble tree-based machine learning models","volume":"130","author":"Zhu","year":"2025","journal-title":"Int. J. Educ. Res"}],"container-title":["Frontiers in Psychology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyg.2026.1875261\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T06:40:36Z","timestamp":1788417636000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyg.2026.1875261\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,3]]},"references-count":62,"alternative-id":["10.3389\/fpsyg.2026.1875261"],"URL":"https:\/\/doi.org\/10.3389\/fpsyg.2026.1875261","relation":{},"ISSN":["1664-1078"],"issn-type":[{"value":"1664-1078","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,3]]},"article-number":"1875261"}}