Conference Agenda
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08 SES 08 B: Digital Wellbeing, Implementation and Engagement
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08. Health and Wellbeing Education
Paper Invisible Pressures, Measurable Strain: Educator Well-Being through Wearable Technology and Work Activity Mapping 1: Nord University, Norway; 2: Stockholm School of Economics, Sweden Presenting Author:Educator well-being has emerged as a central challenge for the sustainability of contemporary education systems, with recent increasing research interest in work-related stress (Alegre & Labajo, 2023; Gudelos & Mabitad, 2025). Work-related stress remains a leading cause of sick leave and exhaustion among educational professionals, occurring in a context characterised by increasing instructional demands, diverse student needs, chronic absenteeism, mental health challenges among students, and expanding administrative responsibilities (Howard & Howard, 2020; Pavlidou & Alevriadou, 2022; Skaalvik & Skaalvik, 2017). Although schools have introduced organisational responses for teacher well-being, such as co-teaching, inclusive classroom arrangements, and expanded support staff, there is limited empirical knowledge of how such arrangements and educators’ everyday work experiences relate to physiological stress and recovery over time. Responding to the ECER 2026 theme, ‘Knowing and Acting: the changing conditions and potentials of education research,’ this study examines how emerging data practices reshape what is known about educator well-being and how this knowledge may inform organisational action in schools. Rather than conceptualising stress as a psychological outcome from respondent metrics (e.g., Mañas & Ang, 2025), the study approaches well-being as an embodied, practice-based phenomenon produced through the temporal and organisational conditions of school work. Methodologically, the study employs a mixed-methods design integrating three data sources: (1) continuous psychophysiological data from wearable smartbands (e.g. stress and sleep-related indicators), (2) individual-level survey data based on the Swedish version of the Warwick–Edinburgh Mental Well-Being 7 Item Scale (SWEMWBS) (Stewart-Brown et al., 2009), and (3) administrative and observational data capturing daily work activities. The empirical material is collected across multiple school contexts and includes a range of professional roles, such as principals, teachers, teaching assistants, and support staff. Biometric data are linked to temporal distinctions between work, non-work, and sleep to examine patterns of stress and recovery across individuals and educational roles (Gunnars, 2026). Initial findings from the first sub-study demonstrate systematic differentiation between activity states. Preliminary analyses indicate heightened stress during scheduled work hours than during non-work time, suggesting distinct physiological patterns associated with the temporal organisation of school work. When linked to survey data, tentative patterns further indicate that lower self-reported well-being tends to co-occur with elevated physiological activation during work and less pronounced differentiation between work and recovery periods. While exploratory, these findings expand research that emphasises roles of meaning in life (e.g., Yildirim et al., 2024) by suggesting an alignment between subjective well-being and physiological embodied stress regulation. It also highlights the importance of developing organisational temporal work structures that enable proper recovery at home, rather than isolated high-intensity intervention events. In subsequent phases, the study will extend this integration by linking biometric and survey data to individual scheduling information detailing activity type, duration, and instructional formats, enabling fine-grained analyses of how pedagogical organisation and workload configurations shape physiological stress and collaboration over time (Gunnars, 2025). The study contributes to health and well-being research in education in two key ways. Empirically, it provides, through the smartbands, a granular account of educator stress that moves beyond self-report by situating well-being within everyday educational work practices (Gunnars, 2026). Methodologically, it demonstrates how combining wearable data, survey instruments, and organisational information expands the epistemic conditions of education research, making otherwise invisible pressures visible and supporting more informed and actionable approaches to designing sustainable and health-promoting educational work environments. Methodology, Methods, Research Instruments or Sources Used The study adopts a mixed-methods design to examine educator well-being as an embodied and practice-based phenomenon, combining continuous physiological measurements with self-reported well-being and organisational data. In the first sub-study, physiological data were collected using wearable smartbands worn by staff at a Swedish compulsory school for three consecutive workdays in November 2025. Data were collected from multiple professional roles, such as teachers, principals, teaching assistants, and support staff. The devices recorded physiological indicators, including heart rate, stress, movement and sleep-related measures, at high temporal resolution. The photoplethysmography sensor in the smartbands show physiological activation and recovery, enabling analysis of sustained stress patterns rather than isolated peak events (Gunnars, 2026). Sleep data provided a complementary indicator of physiological recovery and baseline regulation. While the present analyses treat sleep primarily as a recovery context, the smartband data also enable detailed examination of sleep duration and variability across individuals and nights, which will be explored in subsequent phases of the study. Each participant was assigned a unique pseudonymised identifier, which was used consistently across all data sources. Smartband data were time-stamped and temporally organised into analytically meaningful activity states: scheduled work time, non-work time, and sleep. This temporal structuring enabled physiological data to be analysed in relation to the organisation of everyday work rather than solely individual tasks. Continuous measurements were aggregated to individual-level indicators to reduce noise while preserving systematic differences across contexts. Self-reported well-being was captured using the Warwick–Edinburgh Mental Well-Being Scale (SWEMWBS) (Stewart-Brown et al., 2009), administered after the smartband data collection. Participants were asked to reflect on their well-being over the preceding two weeks, a period that included the study duration, allowing subjective accounts to be analytically related to the biometric data recorded during the same timeframe. In subsequent phases, smartband-derived physiological data and survey-based well-being measures will be jointly linked to individual scheduling information specifying the type and duration of work activities, whether instructional tasks are conducted individually or collaboratively with other teachers, and the number of students present in each learning setting. This integration enables fine-grained analyses of how pedagogical formats, collaborative arrangements, and workload configurations are associated with physiological stress patterns and perceived well-being over time. All participants provided informed consent. Data were pseudonymised, securely stored, and analysed in accordance with approved ethical protocols. The study was approved by the Swedish National Ethics Board (DNR 2025–06479-01). Conclusions, Expected Outcomes or Findings By approaching educator stress as an embodied and practice-based phenomenon, the study moves beyond individualised or solely self-reported accounts and makes visible how physiological activation and recovery are patterned through the temporal organisation of school work. The tentative empirical findings indicated that scheduled work time constitutes a distinct physiological state, characterised by sustained activation relative to non-work time and sleep. The observed intensity varied between the recorded days, showing potential patterns for more detailed analysis of activities. When linked to self-reported well-being, these patterns suggest that subjective experiences align with embodied stress regulation and recovery rather than being isolated psychological perceptions. Importantly, stress appeared not only to be associated with specific demanding events, but with the everyday structuring of work across the school day. Sleep duration across days further showed participants’ recovery, providing a rich context for further analysis. Methodologically, the study contributes to discussions on changing conditions of knowledge production in education research, as digital and data-intensive methods increasingly shape what can be known and how knowledge is produced in everyday educational practice (Williamson, 2018; Fenwick & Edwards, 2016). By integrating continuous physiological data with survey instruments and organisational information, the study illustrates how new data practices can render previously invisible pressures empirically accessible. Rather than positioning physiological data as objective replacements for subjective measures, the study demonstrates their value as complementary lens responding to the increasing research interest in educator work-related well-being (Alegre & Labajo, 2023; Skaalvik & Skaalvik, 2017). Findings open possibilities for more sustainable educational work environments, particularly relevant for leaders seeking to address staff well-being through work organisation rather than solely through individual resilience-based interventions. References Alegre, E. M., & Labajo, J. K. M. (2023). The impact of work stress on the psychological well-being of public elementary school teachers. Int. J. Membr. Sci. Technol., 10, 719–727. Gudelos, J., & Mabitad, B. (2025). Work-related stress, workloads, and performance: A case of senior high school teachers. Workloads, and Performance: A Case of Senior High School Teachers. https://doi.org/10.47772/ijriss.2025.9010121 Gunnars, F. (2025). Collaborative dynamics and psychophysiological variances in teaching methods measured through teacher-students compliance: A cross-classified multilevel analysis. Technology, Knowledge and Learning. https://doi.org/https://doi.org/10.1007/s10758-025-09832-y Gunnars, F. (2026). Smartbands and behavioural interventions in the classroom: Multimodal learning analytics stress-level visualisations for primary education teachers. International Journal of Disability, Development and Education, 73(1), 176–195. https://doi.org/10.1080/1034912X.2024.2355625 Howard, J. T., & Howard, K. J. (2020). The effect of perceived stress on absenteeism and presenteeism in public school teachers. Journal of Workplace Behavioral Health, 35(2), 100–116. https://doi.org/10.1080/15555240.2020.1724794 Mañas, J. L., & Ang, R. S. (2025). Stress, stressors, and stress management practices among public-schoolteachers. International Journal of Public Health Science (IJPHS), 14(2), 818–818. https://doi.org/10.11591/ijphs.v14i2.24869 Pavlidou, K., & Alevriadou, A. (2022). An assessment of general and special education teachers’ and students’ interpersonal competences and its relationship to burnout. International Journal of Disability, Development and Education, 69(3), 1080–1094. https://doi.org/10.1080/1034912X.2020.1755425 Skaalvik, E. M., & Skaalvik, S. (2017). Motivated for teaching? Associations with school goal structure, teacher self-efficacy, job satisfaction and emotional exhaustion. Teaching and Teacher Education, 67, 152–160. https://doi.org/10.1016/j.tate.2017.06.006 Stewart-Brown, S., Tennant, A., Tennant, R., Platt, S., Parkinson, J., & Weich, S. (2009). Internal construct validity of the Warwick-Edinburgh mental well-being scale (WEMWBS): A Rasch analysis using data from the Scottish health education population survey. Health and Quality of Life Outcomes, 7(1), 15. Yildirim, M., Dilekçi, Ü., & Manap, A. (2024). Mediating roles of meaning in life and psychological flexibility in the relationships between occupational stress and job satisfaction, jobperformance, and psychological distress in teachers. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1349726 08. Health and Wellbeing Education
Paper Digital Wellbeing in European School Education: Bridging Research Evidence, Policy Frameworks, and Educational Practice Dublin City University, Ireland Presenting Author:Digital wellbeing has emerged as a key concern in education systems worldwide as digital technologies increasingly mediate children’s learning, social relationships, and everyday experiences. Across Europe, policy frameworks such as the Digital Education Action Plan, DigComp, and the Better Internet for Kids (BIK+) strategy explicitly position schools and educators as central actors in supporting digital wellbeing. However, despite this policy emphasis, research and practice remain fragmented, with persistent gaps between conceptual definitions, governance frameworks, and school-level implementation. This proposal addresses this fragmentation by examining how digital wellbeing is conceptualised, governed, and enacted across European education systems. The central research question guiding this study is: How is digital wellbeing conceptualised, governed, and enacted in school education across European contexts, and what systemic conditions enable or constrain its sustainable implementation? Sub-questions include:
The study is grounded in a systemic and relational theoretical framework, drawing on three complementary strands of scholarship. First, it engages with digital wellbeing theory, which conceptualises wellbeing not as an individual trait but as an emergent property of socio-technical environments shaped by design, context, and power relations (Büchi, 2024; Smits et al., 2022). Second, it draws on policy enactment theory, which highlights how policies are interpreted, translated, and negotiated within schools rather than implemented in linear ways (Ball et al., 2012; Bacchi & Goodwin, 2016). This perspective is particularly relevant in European education systems, where supranational frameworks are adapted within diverse national and institutional contexts. Third, the study is informed by socio-cultural and ecological approaches to education, which emphasise the interaction between learners, educators, institutions, and broader governance structures. Together, these perspectives support a reframing of digital wellbeing as a shared, system-level educational responsibility, rather than an individual behavioural outcome. The European and international dimension is central to the study, as it explicitly examines cross-national policy frameworks, comparative national strategies, and transferable educational practices. By integrating evidence from multiple European contexts, the research aims to contribute to international debates on how education systems can respond more coherently and equitably to the wellbeing challenges of digitally mediated childhoods. Methodology, Methods, Research Instruments or Sources Used The study adopts an integrative mixed-methods research design, combining systematic review, policy analysis, and practice mapping to generate a comprehensive, cross-level understanding of digital wellbeing in school education. First, a systematic review of empirical literature will synthesise peer-reviewed studies published between 2020 and 2025 that address digital wellbeing among school-aged children and adolescents. Following PRISMA 2020 guidelines, the review will include quantitative, qualitative, and mixed-methods studies from European and international contexts. This component will identify dominant conceptualisations, measurement approaches, and reported outcomes related to digital wellbeing in educational settings. Second, a comparative policy analysis will examine European-level frameworks (e.g., Digital Education Action Plan, DigComp 2.2, BIK+) alongside selected national strategies from EU member states. Using critical policy analysis methods, documents will be analysed to explore how digital wellbeing is problematised, how responsibility is distributed, and what forms of support or accountability are articulated. This analysis will foreground policy coherence, governance mechanisms, and implicit assumptions about schools, teachers, and learners. Third, a mapping of educational practices and initiatives will be conducted using project documentation, grey literature, and institutional reports. Initiatives will be analysed thematically with attention to pedagogical design, stakeholder involvement, scalability, and evaluation practices. This component will highlight promising approaches as well as structural barriers to sustainable implementation. Across all components, data will be integrated thematically to identify convergences, tensions, and gaps between research, policy, and practice. This integrative approach enables the study to move beyond isolated findings toward system-level insights relevant to European education systems. Conclusions, Expected Outcomes or Findings The study is expected to generate three key outcomes. First, it will provide conceptual clarity by synthesising diverse definitions and operationalisations of digital wellbeing into a coherent, multidimensional framework suitable for educational contexts. This framework will move beyond narrow behavioural indicators and foreground relational, institutional, and governance dimensions. Second, the research will identify systemic misalignments between European and national policy aspirations and the realities of school-level enactment. It is anticipated that findings will show how responsibility for digital wellbeing is frequently delegated to schools and educators without sufficient structural support, professional development, or evaluative capacity. These insights will contribute to critical discussions on policy design and implementation in digital education. Third, the study will highlight conditions for effective and sustainable practice, drawing on examples of whole-school approaches, participatory design, and curriculum-integrated initiatives. By identifying enabling conditions rather than prescriptive solutions, the research will offer transferable insights for policymakers, researchers, and practitioners across European and international contexts. Overall, the study aims to support more coherent, system-aware approaches to digital wellbeing in school education, contributing to international debates on digital governance, educational responsibility, and children’s wellbeing in digitally mediated societies. References Bacchi, C., & Goodwin, S. (2016). Poststructural policy analysis: A guide to practice. Palgrave Macmillan. Ball, S. J., Maguire, M., & Braun, A. (2012). How schools do policy: Policy enactments in secondary schools. Routledge. Büchi, M. (2024). Digital wellbeing theory and research. New Media & Society, 26(1), 172–189. European Commission. (2022). A digital decade for children and youth: The BIK+ strategy. OECD. (2019). Educating 21st century children: Emotional wellbeing in the digital age. Smits, M., Kim, C. M., Van Goor, H., & Ludden, G. D. S. (2022). From digital health to digital wellbeing. Journal of Medical Internet Research, 24(4), e33787. Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The digital competence framework for citizens. European Commission. 08. Health and Wellbeing Education
Paper From Implementation to Sustainment: Fidelity and Effects of a Primary School SEL Program in Routine Practice University of Education Upper Austria, Austria Presenting Author:In light of current societal changes and the impacts of crises such as the COVID-19 pandemic, mental health—particularly among children and adolescents—has been deteriorating increasingly (Ravens-Sieberer et al. 2022). Against this background, life skills (LS) and social-emotional competencies such as relationship skills (e.g. empathy) and self-awareness (e.g. regulation of emotions) are gaining importance (Durlak et al. 2022). Promoting such competencies in the school context is proving to be an increasingly promising approach that, in addition to improving mental health, can also yield further positive effects. The evidence base is grounded in a large number of quasi-experimental and experimental studies demonstrating that well-implemented school-based programs social and emotional learning (SEL) programs foster social and emotional competencies, enhance positive behavior, reduce negative behavior, improve emotional well-being, and also lead to improvements in academic outcomes (Durlak et al. 2022). The accumulation of evidence supporting the effectiveness of interventions in everyday classroom practice represents a key milestone on the path toward the widespread integration of evidence-based approaches in educational practice. However, the journey toward the sustainable implementation and institutionalization of evidence-based approaches in the school context, so that they can unfold their intended effects, remains long and marked by numerous challenges (Durlak & DuPre 2008). Notably, the state of research regarding the scaling up of SEL programs is considerably less developed than research on their effectiveness (Combs et al. 2023). Following the initial implementation of evidence-based approaches—which typically requires substantial external support (e.g., professional development) to achieve high fidelity—practitioners (e.g., teachers) are increasingly expected to assume responsibility for sustaining the approach, while external support is gradually reduced. Ultimately, an approach should continue to be delivered with sufficient quality even after the complete withdrawal of external support in order to achieve the intended program goals (see e.g. Shelton et al. 2018). In practice, however, such an ideal-typical implementation process—culminating in the large-scale sustainment of evidence-based approaches in everyday school life—is often not fully realized, which makes fidelity-consistent continuation and the associated intended positive effects less likely (Combs et al. 2023; Lyon et al. 2024). For example, Combs et al. (2023), in their study on the large-scale implementation of an LS program across 158 school districts (419 schools) in the United States, found that two years after the withdrawal of support provided during the initial implementation phase, 59% of schools no longer implemented the program at all, and only 30% continued to deliver the program with fidelity. A further 11% of schools still used the program, but less intensively than intended. Whether the intended positive effects are sustained in schools or classrooms where a program is continued (at least in part) after the initial implementation depends on aspects of implementation quality including fidelity (i.e., adherence to the program) and dosage (i.e., the amount and intensity of program delivery; see e.g. Durlak & DuPre 2008). To sum up, there is a steadily growing body of evidence supporting the effectiveness of SEL-programs. However, less is known about whether programs continue to achieve their intended effects in everyday school practice after the withdrawal of implementation support (Herbein et al. 2020). The present study investigates how an Austrian primary school SEL program, for which an effectiveness study has already demonstrated reductions in internalizing and externalizing problems, is sustained in routine school practice and whether it continues to produce its intended effects. Methodology, Methods, Research Instruments or Sources Used This research uses data from the project Promoting Life Skills (ProLiSk). It employs a quasi-experimental design with intervention and comparison classes to examine the effectiveness of the Zusammen.Wachsen program across the full primary school years (ages 6–10). At the time of data collection, the program had already been implemented in school practice for several years, and the initial implementation support via school-based professional development was no longer provided. This research uses data from first two measurement points (January 2025 and June/July 2025). The sample compromises 34 classes (12 experimental classes/ 22 comparison classes) with a total of 623 children. For 421 children, data were available for at least one measurement occasion. Child outcomes were assessed using parent questionnaires. Teachers reported on implementation quality of the program lessons that should be carried out during first grade. The study uses several outcomes that have also addressed in other research on SEL. The Strengths and Difficulties Questionnaire (SDQ (Goodman 1997).) was used to assess problem behaviour (conduct problems, hyperactivity, emotional problems, peer problems) and prosocial skills. Further measures include an adaption of the Emotion Regulation Inventory (ERI, Roth et al., 2009) that assess dysregulated and integrated emotion regulation, a measure of empathy (Stadler et al., 2004), and measures of emotional and cognitive-behavioural student engagement (Wang et al., 2018). Descriptive analyses were used to examine how the program was sustained. Bayesian multilevel models were applied to investigate the effects of Zusammen.Wachsen on child outcomes. The software Blimp (Keller & Enders, 2023) was used for multilevel modeling. Separate analyses were conducted for each outcome, controlling for baseline levels of the respective outcome, socioeconomic status, and child gender. Blimp enables state-of-the-art handling of missing data through fully Bayesian estimation (Enders, 2022). Moreover, Bayesian analyses allow inferences about program effects that are qualitatively different from those derived from frequentist hypothesis testing. For example, it is possible to estimate the probability that an intervention effect is in the expected direction. Conclusions, Expected Outcomes or Findings Descriptive analyses show that only six out of the 12 classes that had previously implemented Zusammen.Wachsen continued to deliver the program with high fidelity. In one class, the program was no longer implemented. Moreover, seven teachers from control classes implemented SEL programs comparable to Zusammen.Wachsen, although not consistently across the school year. Therefore, three groups were distinguished for the analysis of program effects: (1) intervention classes that implemented Zusammen.Wachsen with high fidelity (6 classes), (2) classes that partially implemented Zusammen.Wachsen or a comparable program (12 classes), and (3) classes that did not implement any program (control group; 14 classes). Overall, the results consistently show effects in the expected direction for the high-fidelity group compared to the control group. Among other outcomes, parents reported higher empathy (b = .14), higher emotional engagement (b = .13), higher cognitive-behavioral engagement (b = .10), lower conduct problems (b = −.15), and lower dysregulated emotion regulation (b = −.13). The probability that the effects are in the reported direction ranges from 81% to 91%. Although these results might be considered non-significant from a frequentist perspective, it should be noted that it is highly unlikely that such a consistent pattern of effect directions is due to chance. Overall, our findings highlight the importance of implementing evidence-based programs with high fidelity after scaling up in order to achieve the intended outcomes. Importantly, high fidelity appears to be attainable even after external implementation support is no longer available. References Combs, K. M., Drewelow, K. M., Lain, M. A., Håbesland, M., Ippolito, A., & Finigan-Carr, N. (2023). Sustainment of an evidence-based behavioral health curriculum in schools. Prevention Science, 24(3), 541–551. Durlak, J. A., & DuPre, E. P. (2008). Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology, 41(3–4), 327–350. Durlak, J. A., Mahoney, J. L., & Boyle, A. E. (2022). What we know, and what we need to find out about universal, school-based social and emotional learning programs for children and adolescents: A review of meta-analyses and directions for future research. Psychological Bulletin, 148(11–12), 765–782. Enders, C. K. (2022). Applied missing data analysis (2nd ed.). Guilford Press. Goodman, R. (1997). The Strengths and Difficulties Questionnaire: A research note. Journal of Child Psychology and Psychiatry, 38(5), 581–586. Herbein, E., Golle, J., Nagengast, B., & Trautwein, U. (2020). Förderung von Präsentationskompetenz: Schrittweise Implementation und Effektivitätsüberprüfung eines Präsentationstrainings für Grundschulkinder. Zeitschrift für Erziehungswissenschaft, 23(1), 83–120. Keller, B. T., & Enders, C. K. (2023). Blimp user’s guide (Version 3). https://www.appliedmissingdata.com/blimp Lyon, A. R., Connors, E. H., Lawson, G. M., Nadeem, E., & Owens, J. S. (2024). Implementation science in school mental health: A 10-year progress update and development of a new research agenda. School Mental Health, 16(4), 1013–1037. https://doi.org/10.1007/s12310-024-09731-0 Ravens-Sieberer, U., Erhart, M., Devine, J., Gilbert, M., Reiss, F., Barkmann, C., et al. (2022). Child and adolescent mental health during the COVID-19 pandemic: Results of the three-wave longitudinal COPSY study. Journal of Adolescent Health, 71(5), 570–578. Roth, G., Assor, A., Niemiec, C. P., Deci, E. L., & Ryan, R. M. (2009). The emotional and academic consequences of parental conditional regard: Comparing conditional positive regard, conditional negative regard, and autonomy support as parenting practices. Developmental Psychology, 45(4), 1119–1142. https://doi.org/10.1037/a0015272 Shelton, R. C., Cooper, B. R., & Stirman, S. W. (2018). The sustainability of evidence-based interventions and practices in public health and health care. Annual Review of Public Health, 39, 55–76. Stadler, C., Janke, W., & Schmeck, K. (2004). IVE: Inventar zur Erfassung von Impulsivität, Risikoverhalten und Empathie bei 9- bis 14-jährigen Kindern. Hogrefe. Wang, M. T., Fredricks, J., Ye, F., Hofkens, T., & Linn, J. S. (2017). Conceptualization and assessment of adolescents’ engagement and disengagement in school. European Journal of Psychological Assessment. 08. Health and Wellbeing Education
Paper Analysing the Link Between Student Engagement and Subjective Well-being in Lower Secondary Education: Evidence from a Cross-lagged Panel Study Johannes Kepler Universität Linz, Austria Presenting Author:This study examines the relationship between student engagement and well-being. Following the research tradition of positive education (Seligman et al., 2009), this paper argues that well-being plays a central role in academic success. A well-established framework within this paradigm is the broaden-and-build theory. The theory states that positive emotions have the potential to broaden people's mental thought-action repertoires and thereby create opportunities for building up personal resources. In contrast, the theory postulates that negative emotions lead to a narrowing of the thought-action repertoires by remembering the urge to act in a certain way. In general, this makes it more difficult to build up resources (Fredrickson, 2001). Based on the broaden-and-build theory, the upward spiral hypothesis was formulated. The hypothesis states that positive emotions can set off an upward spiral. Therefore, personal resources increase the likelihood that positive emotions will be experienced again in the future (or vice versa in the case of negative emotions) (Fredrickson & Joiner, 2002). This study focuses on two key constructs in positive education: the tripartite model of student engagement (Fredricks et al., 2004) and subjective well-being (SWB) (Diener, 1984). The tripartite model consists of three dimensions: behavioural, emotional and cognitive engagement. Behavioural engagement (BE) includes following the class rules, emotional engagement (EE) encompasses the affective reactions (e.g., interest) to the learning activity, the teacher or the school and cognitive engagement (CE) comprises psychological investment in learning. SWB consists of three dimensions: positive affect (PA) (e.g., proud), negative affect (NA) (e.g., sad) and global life satisfaction (LS). A large number of studies have demonstrated the positive link between the two constructs. Some of these studies have modelled SWB as a predictor of student engagement (Datu, 2018), while a second group of studies have chosen an inverse modelling (Kessels & van Houtte, 2022). In addition, there is a third group that have used a reciprocal approach (Datu & King, 2018). The majority of studies in this field of research use cross-sectional data, while longitudinal studies are the exception. There is not only a lack of plurality in terms of study designs. In all reciprocal studies with latent constructs known to the author from 2003 to 2024, no European samples have been examined. Additionally, only in one case (Datu & King, 2018) lower secondary education students were analysed, including all three dimensions of the SWB. This would be important, as they distinguish between affective states and cognitive assessments on the one hand, and on the other hand, the two affective states do not represent opposite poles of one dimension, but can vary independently of each other (Diener, 1984). The present study aims to bring more plurality to this field of research. Therefore, it examines the relationship between the two constructs, considering all dimensions of SWB using a longitudinal European sample of lower secondary education students. Based on the theoretical framework and previous empirical studies, it is hypothesized that positive affect as well as life satisfaction are positive, reciprocal associated with student engagement and negative affect is negative, reciprocal associated with student engagement. Using a cross-lagged panel model (CLPM), a statistically significant bidirectional association between student engagement and PA was identified, whereas the links between student engagement and NA were not significant. With regard to the dimension of LS, it was found that a high level of student engagement at the first measurement point leads to greater life satisfaction at the second measurement point. The inverse effects were not statistically significant. The results show that promoting student engagement can lead to an increase in some dimensions of SWB, and in turn helps to sustain student engagement. Methodology, Methods, Research Instruments or Sources Used In order to examine the complex relationship between the two constructs, two measurement points from a currently ongoing longitudinal study (Mahringer et al., 2025) were used. In January 2025 and in June 2025 5th grade students from 40 schools in Upper Austria completed online questionnaires administered by school staff. The total sample size across both measurement points was 1,762. During the January administration, 1,636 students were included in the sample while 1,622 students completed surveys in June, resulting in an attrition rate of 8% and a late entrant rate of 7%. The mean participants’ age was 10.81 (SD = .75) and the proportion of female students was 42%. The dimension of life satisfaction was measured using the German version of student life satisfaction scale (SLSS) (Weber et al., 2013) and the other two dimensions of SWB were assessed using the children version of the positive-and-negative affect scale (PANAS-C-SF) (Ebesutani et al., 2012). In this study, all three dimensions demonstrated good internal consistency at both time points (e.g., time point one: αPA = .82; αNA = .77; αLS = .88). Student engagement was measured using the multidimensional school engagement scale (Wang et al., 2019). Due to the inconsistency in its multidimensional structure (Wang et al., 2019), a bi-factor model was established, whereby EE remained as a sub-factor alongside the general factor (GENG). Internal consistency was adequate (e.g., time point one: αGENG = .86; ωhierarchical GENG: .67; αEE= .81). For both constructs cross-sectional CFA was conducted at each time point and acceptable fit indices (e.g., CFI, TLI) indicated an adequate fit to the data. Longitudinal CFA supported configural and metric invariance across time points for both constructs, indicating a stable measurement structure over time. A two-wave cross-lagged panel model was employed, which is methodologically more rigorous than cross-sectional analysis, which are dominating in the field. This enables temporal stability to be assessed and the examination of whether SWB dimensions and student engagement are reciprocally related, while controlling for autoregressor effects as well as for other dimensions of the two constructs. Conclusions, Expected Outcomes or Findings First, the CLPM was able to show that student engagement is more stable over time (autoregressor effect) than the dimensions of SWB. This is consistent with similar studies (Datu & King, 2018) and confirms the definition of the two constructs. Second, with regard to the hypotheses, it can be noted that PA is reciprocally related to GENG even after controlling for autoregressor effects and the other dimensions of the two constructs. This could not be found for NA and LS. This confirms the importance of distinguishing between the three dimensions of SWB (Diener, 1984). The results suggest that they may have different effects, indicating that PA is more meaningful for student engagement. The important role of student engagement in predicting PA and LS was also found in another study (Datu & King, 2018). Third, the specific factor of EE also had a statistically significant influence on PA as well as on LS, while the inverse effects were not statistically significant. This result suggests that emotional engagement plays an important role in fostering SWB beyond GENG. Fourth, explorative comparisons of the cross-lagged paths indicated that the effect from student engagement to SWB was stronger than the inverse effect. Although causal claims should be made cautiously given CLPM limitations, this result could indicate that school often functions as a primary life context during early adolescence, making student engagement a driver of LS and PA. Future longitudinal studies should use more than two measurement points in order to estimate more nuanced models (e.g., RI-CLPM). This could lead to a better understanding of the dynamic relationship between the two constructs. 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