Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 19th Aug 2026, 21:30:09 EET
|
Daily Overview |
| Session | ||
05 SES 12 A: School Leaving and Drop-out
Paper Session | ||
| Presentations | ||
05. Children and Youth at Risk and Education
Paper Observing Classroom Dynamics for Equity. Dropout Prevention in Complex and Multilingual School Contexts University of Milano-Bicocca, Italy Presenting Author:This proposal presents research that is part of the PRIN (Projects of Significant National Interest) project entitled "Educational poverty, cultural disadvantage, and social inclusion inside and outside school. Teacher professional development and research-training in the post-Covid era" (2024-2026), focused on preventing school dropout and combating educational poverty and academic failure in disadvantaged urban areas involving teachers (Agrusti, Vannini, & Asquini, 2024). The research, which involved the use of different research tools (both quantitative and qualitative), was conducted in five Italian urban contexts. This contribution focuses on the case of Milan, where the study involved a Grade 7 class at a lower secondary school in San Siro (a highly problematic district with a high concentration of disadvantaged people with migrant backgrounds). The class consisted of 14 students, all with migrant backgrounds, characterised by pervasive socio-emotional and behavioural difficulties (SEBD - Social, Emotional and Behavioural Difficulties: Zweers et al., 2021), significant linguistic vulnerability in Italian as a second language (L2), fragile self-regulation skills, high instructional and relational complexity, and low academic achievement. This study adopts a conception of teaching practice as a situated, interactive, and multidimensional professional activity (Altet, 2017). Teaching is understood not as the application of predefined techniques, but as a continuous and recursive process of situated decision-making shaped by school ecology, institutional constraints, and interactional dynamics. According to the ecological approach and the socio-constructivist framework (Bronfenbrenner, 2005; Vygotsky, 1978), the classroom is a complex microsystem which should be conceived as a dynamic process of constructing learning conditions, taking into account individual, relational, and contextual variables. If learning is a socially mediated process that takes place within shared practices and through cultural mediators, an equitable classroom is one that intentionally adapts its teaching practices to compensate for structural inequalities and different starting conditions, recognizing that formally equal treatment can produce profoundly unfair outcomes (OECD, 2018). An equitable classroom should create accessible learning environments in which all students can participate meaningfully in the process of knowledge construction, receiving differentiated forms of support (scaffolding) that are sensitive to their cognitive, linguistic, and cultural needs (Hammond & Gibbons, 2005). Within this framework, the aim here is to reflect on the conditions and relational dynamics that promote equity within the classroom, focusing on how youth who are at risk of dropping out of school respond to certain variables related to the context and educational and teaching methods. To this end, the results of the observations conducted in the classroom by the researchers will be presented. The observation system adopted a naturalistic approach (Lincoln & Guba, 1985) and was based on narrative and descriptive notes organized around descriptors and analytical focuses. The guiding questions for these observations were inspired by Altet’s multidimensional model of teaching practices aligned with the OPERA framework (Altet, Paré Kaboré, & Sall, 2015) and by the ICF - International Classification of Functioning, Disability and Health (WHO, 2001). In line with international literature (Bell et al., 2014; Cohen & Goldhaber, 2016), the system is designed to balance analytical structure with ecological validity, across three interrelated domains in particular: (1) Relational and socio-emotional domain, focusing on classroom climate, teacher-student relationships, peer interactions, and responses to disruptive or avoidant behaviours; (2) Pedagogical-organizational domain, addressing instructional formats, classroom management, task structure, time, and student engagement; (3) Didactic-epistemic domain, examining language demands, cognitive processes, and access to knowledge. Methodology, Methods, Research Instruments or Sources Used During the first year (school year 2023/2024), each research unit carried out a case study in lower secondary schools (Bologna, Milan, Palermo, Perugia, and Rome), using a convergent mixed-method approach (Creswell & Plano Clark, 2006), to explore indicators of socio-cultural disadvantage and risk/protective factors for the 11-14 age group (at both the micro-systemic and meso-systemic levels). These 5 case studies were preparatory to professional development research pathways conducted with teachers in Grade 7 classes of the schools involved (s.y. 2024/2025), with the aim of promoting innovation in teaching and learning practices to improve the school climate and the processes of support, involvement, and motivation of students at risk. This contribution presents part of the research carried out in Milan, at San Siro, a highly problematic district with a high concentration of people with immigrant backgrounds, suffering from educational poverty and socio-economic and cultural disadvantage (Grassi, 2022). Specifically, the research was conducted during the 2024/2025 s.y. in a Grade 7 class at the Negri lower secondary school, Calasanzio Comprehensive Institute. The class, consisting of 14 students, was chosen for research by the University of Milano-Bicocca in light of the results achieved in the previous year (Fredella, Cotza, & Agrusti, 2025). These results showed a class characterized by students with SEBD, several fragilities related to Italian as a second language, and low levels of academic achievement. The students, all from families with a migrant background, had low levels of socio-cultural capital. A total of 23 non-participant classroom observations were conducted between October 2024 and May 2025, each lasting an average of 4 hours. These observations focused on the following areas: problem behaviors and teachers’ responses; peer interactions; Italian L2 skills; cognitive and attentional functions; management of independent work and academic motivation; relationships with adults and climate; functioning according to different types of lessons; coordination between adults; and the structure of lessons and teaching methods in relation to classroom management, engagement and containing/channeling problem behaviors. Data analysis followed a reflective thematic approach (Braun & Clarke, 2021) aimed at identifying recurring patterns, critical incidents, and variations between different educational formats and over time. Conclusions, Expected Outcomes or Findings Findings highlight the deeply situated nature of teaching practices and the strong interdependence between instructional design, class management, and language demands. Interactive and student-centred approaches did not automatically foster engagement: when activities were weakly structured, poorly scaffolded, or linguistically demanding, they often intensified disruptive behaviours, avoidance strategies, and off-task conduct, particularly among students with SEBD and limited L2 proficiency. Conversely, very structured interactive lessons – characterised by explicit routines, clear micro-objectives, predictable activity cycles, visual and linguistic supports, and immediate feedback – were associated with good levels of engagement, improved attention, and a reduction in disruptive behaviours. Classroom observation revealed that students frequently demonstrated cognitive competence when tasks were adequately scaffolded, supporting international findings on the importance of instructional clarity and scaffolding in complex classrooms (Rosenshine, 2012). Across observations, persistent challenges emerged and a crucial finding concerns adult coordination, such as inconsistent coordination among teachers and educators, difficulties in differentiating tasks and timeframes according to students’ diverse needs, and ambiguity in adult roles. Micro-collapses of activities were frequent when communicative coherence weakened or when interactive approaches were not sufficiently structured. In line with research on instructional coherence (Newmann et al., 2001), the presence of multiple professional figures did not automatically enhance instructional effectiveness. In fact, in the absence of shared planning and coherent communicative practices, adult density sometimes generated confusion, weakened classroom regulation, and diluted instructional responsibility. Rather than prescribing solutions, observation fostered reflective dialogue, feedback loops, and iterative instructional redesign. The study contributes to the international literature on observation by understanding the dynamics that are triggered within the classroom and how these relationships contribute or do not contribute to a climate that is perceived as equal in complex, multilingual, and socially vulnerable settings. References Agrusti, G., Vannini, I., & Asquini, G. (2024). Povertà educativa, svantaggio culturale e inclusione sociale dentro e fuori la scuola. Sviluppo professionale degli insegnanti e Ricerca-Formazione nell’era post-Covid. Cadmo, 1, 7-23. Altet, M. (2017). Les pratiques enseignantes: Une approche plurielle. De Boeck Supérieur. Altet, M., Paré Kaboré, A., & Sall, H.N. (2015). OPERA - Observation des pratiques enseignantes dans leur rapport avec les apprentissages des élèves. Recherche menée dans 45 écoles du Burkina Faso (2013-2014). Agence universitaire de la Francophonie (AUF). Bell, C.A., Gitomer, D.H., McCaffrey, D.F., Hamre, B.K., & Pianta, R.C. (2014). An argument approach to observation protocol validity. Educational Assessment, 19(2), 62-87. Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. Sage. Bronfenbrenner, U. (2005). Making human beings human. Bioecological perspectives on human development. Sage. Cohen, D.K., & Goldhaber, D. (2016). Building a more complete understanding of teacher evaluation using classroom observations. Educational Researcher, 45(6), 378-387. Creswell, J.W., & Plano Clark, V.L. (2006). Designing and conducting mixed methods research. Sage. Fredella, C., Cotza, V., & Agrusti, G. (2025). Le rappresentazioni degli insegnanti sulla dispersione scolastica. Risultati di un’analisi qualitativa. Form@are, 25(2), 265-284. Grassi, P. (2022). Barrio San Siro. Interpretare la violenza a Milano. FrancoAngeli. Hammond, J., & Gibbons, P. (2005). Putting scaffolding to work. Prospect, 20(1), 6-30. Lincoln, Y.S., & Guba, E.G. (1985). Naturalistic inquiry. Sage. OECD (2018). Equity in education. OECD Publishing. Newmann, F.M., Smith, B., Allensworth, E., & Bryk, A.S. (2001). Instructional program coherence. Educational Evaluation and Policy Analysis, 23(4), 297-321. Rosenshine, B. (2012). Principles of instruction. American Educator, 36(1), 12-19. Vygotsky, L.S. (1978). Mind in society. Harvard University Press. WHO (2001). International classification of functioning, disability and health (ICF). Zweers, I., van de Schoot, R.A.G.J., Tick, N.T., Depaoli, S., Clifton, J.P., Orobio de Castro, B., & Bijstra, J.O. (2021). Social-emotional development of students with social-emotional and behavioral difficulties in inclusive regular and special education. International Journal of Behavioral Development, 45(1), 59-68. 05. Children and Youth at Risk and Education
Paper Diversity of Adolescents at Risk of Early School Leaving: Group Specific Risk and Protective Factors University of Iceland, Iceland Presenting Author:Early school leaving is of concern across nations. In Europe as well as in the other OECD countries, upper secondary education is regarded as the minimal level of necessary educational attainment. Still many young people leave school. Although the situation has been improving, in 2024, on average 9.3% of those aged 18-24 in the EU left education with only lower secondary education or less (Eurostat, n.d.). In modern knowledge-based societies, with mass education and increasing reliance on highly skilled labour, early school leavers face more disadvantage than ever before. Findings indicate that early leavers are at risk of being exposed to negative economic and psychosocial consequences, such as poorer prospects in the labour market, unemployment, less participation in further education and civic life (e.g. European Commission, 2018; Nilsen & Holm Reiso, 2014; Nordic Social Statistical Committee, 2011; Rumberger, 2011). Given the well-documented negative consequences of early school leaving, it is a social justice issue to develop evidence based preventive strategies and thereby promoting educational equality. Students who drop out of school form a large and diverse group and leave for a variety of reasons. Early school leaving is a complex process of interactions between the characteristics of the student and the social context in the family, the school and the community, a process which often starts at an early age (Blöndal & Adalbjarnardottir, 2014; Entwisle et al., 2005; Rumberger, 2011). Although it has been established that early school leavers form a heterogenic group (Blöndal & Hafþórsson, 2018; Etzion & Romi, 2015), research is still wanting in addressing the diversity of the group as foundation for enhanced and targeted preventive measures (Blöndal & Adalbjarnardottir, 2012; Gal, 2022; Fortin et al., 2006; Janosz et al., 2000) The aim of our research is to address this wanting building on extensive quantitative longitudinal study: First, by identifying different subgroups of adolescents at risk of dropping out of upper secondary school. The typology is based on significant factors during adolescence (age 15, end of compulsory school) that predict early school leaving. These are behavioural, emotional and cognitive engagement - the three main dimensions of student engagement (Fredricks et al., 2004) - academic self-concept and sense of purpose, as well as academic achievement which is the single strongest predictor of school dropout (Blöndal & Adalbjarnardottir, 2014; Rumberger, 2011). Second, by employing a longitudinal approach to assess how the identified subgroups react differently to known important risk and protective factors for dropping out. The focus is on family and school factors as well as students’ future prospects, both at age 15 and age 19. The objective is to enhance comprehensive understanding of this internationally recognized problem and thereby promoting more effective preventive and interventive strategies that address the different needs and strengths of students at risk of leaving school early.
Methodology, Methods, Research Instruments or Sources Used Participants This study is the Icelandic part of an international, collaborative research project (International Study of City Youth, ISCY) and is an ongoing, longitudinal study (Blöndal, et al., 2019). The sample at baseline was the population of students attending last year of compulsory education (age 15, 10th grade) in 44 public schools in the Reykjavík area in 2014. A total of 1956 students (52.5% female) participated at baseline (response rate 81% of the cohort). Two third of the students participated in a follow up survey four years later, age 19. Procedure The educational authorities in the Reykjavík area, as well as the Icelandic Data Protection Commission (Notification number S7011), granted permission for the study. Letters describing the study were sent to the schools’ administration and to the adolescents and their parents. Parents active consent of their children’s participation was sought. A self-report questionnaire was administered online during school hours. The adolescents were informed that they could refuse or discontinue participation at any time and were assured that their answers were strictly confidential. In 2018, a second data collection was conducted when the adolescents were at age 19 both among those in upper secondary school and those who had left school. In addition to the survey data, information was obtained on students’ performance in standardized national test in 10th grade from the Directorate of Education and Statistic Iceland provided information on students’ progress through upper secondary education. The research is supported by a grant no. 184730 from the Icelandic Research Fund. Measures and analysis We conducted cluster analysis in two steps. First, we conducted hierarchical analysis using Ward’s method. Second, we used K-means cluster analysis to refine the four-cluster solution. We based the clustering on seven indicators collected at the end of compulsory school (age 15), four for student engagement (negative school behavior, academic investment, school bonding, social engagement), sense of purpose of learning, academic self-concept, and academic achievement (average marks on standardized tests in Icelandic and mathematics at age 15). Furthermore, we used measures on student background (SES, parental education), parenting practices, school characteristics and future prospects, both at age 15 and age 19 to explore group specific risk and protective factors. Bi- and multivariate analysis were conducted, among them univariate analysis of variance. Conclusions, Expected Outcomes or Findings Our preliminary findings confirm that adolescents who are at risk of early school leaving are a heterogeneous group. We identified four distinct at risk subgroups based on engagement, sense of purpose of learning, academic self-concept and academic achievement at the end of compulsory school, age 15. All these factors predict school leaving, but not in the same way for different groups. Similar subgroup-specific patterns were observed for other established predictors, including student background, parenting practices, school characteristics and future prospects - both based on students answers at the end of compulsory school and at age 19. These results highlight the complexity of the dropout phenomenon and underscore the need for differentiated prevention and intervention strategies. The findings suggest that the characteristics of the different groups call for not only different types, but also different levels, of support. Furthermore, the results of the strengths and weaknesses of students surrounding at home and at school at different age and school levels gives insight into how coordinated efforts across these systems are essential to support students at risk. References Blöndal, K. S., & Adalbjarnardottir. S. (2012). Student disengagement in relation to expected and unexpected educational pathways. Scandinavian Journal of Educational Research, 56, 85–100. Blöndal, K. S., & Adalbjarnardottir, S. (2014). Parenting in relation to school dropout through student engagement: A longitudinal study. Journal of Marriage and family, 76, 778–795. Blöndal, K. S., & Hafþórsson, A. (2018). Margbreytileiki brotthvarfsnemenda [Diversity of school dropouts. A typological approach]. Netla – Online Journal on Pedagogy and Education. Blöndal, K.S., Jónasson, J.T., & Hafþórsson, A. (2019). Student disengagement in inclusive Icelandic education: A question of school effect in Reykjavík. In Demanet, J. & Van Houtte, M. (Eds.) Resisting education: A cross-national study on systems and school effects (pp. 117–133). Springer. Gal, P. (2022) Typologies of early school Leavers from secondary education: A review study. Studia Paedagogica, 27, 141–161. Entwisle, D. R., Alexander, K. L., & Olsen, L. S. (2005). First grade and educational attainment by age 22: A new story. The American Journal of Sociology, 110(5), 1458-1502. Etzion, D., & Romi, S. (2015). Typology of youth at risk. Children and Youth Services Review, 59, 184–195. European Commission. (2018). Situation of young people in the European Union. https://op.europa.eu/en/publication-detail/-/publication/b6985c0c-743f-11e8-9483-01aa75ed71a1 Eurostat. (n.d.). Early leavers from education and training. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Early_leavers_from_education_and_training Fortin, L., Marcotte, D., Potvin, P., Roeyr, É., & Joly, J. (2006). Typology of students at risk of dropping out of school: Description by personal, family and school factors. European Journal of Psychology of Education, 21(4), 363–383. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109. Janosz, M., Le Blanc, M., Boulerice, B., & Tremblay, R. E. (2000). Predicting different types of school dropouts: A typological approach with two longitudinal samples. Journal of Educational Psychology, 92(1), 171–190. Nilsen, Ö. A. & Holm Reiso, K. (2014). Scarring effects of early-career unemployment. Nordic Economic Policy Review, 1, 13-45 Nordic Social Statistical Committee. (2011). Youth unemployment in the Nordic countries: A study on the rights and measures for young jobseekers. Author. Rumberger, R.W. (2011). Dropping out. Why students drop out of high school and what can be done about it. Harvard University Press. 05. Children and Youth at Risk and Education
Paper Factors Related to School Absenteeism: Evidence from Portugal University of Minho, Portugal Presenting Author:Abstract (600 words) The SOS-Attendance Observatory is a reference center established under the co-financed Erasmus+ project [REF. 2022-1-ES01-KA220-SCH-000088733], involving Spain (project coordinator), Portugal, Italy, and Turkey, aimed at analysing, investigating, and promoting practices to combat school absenteeism and early school leaving. The Observatory serves as a scientific hub for the systematic collection, analysis, and dissemination of data on school attendance, providing methodological and analytical support for research, policy formulation, and the sharing of good practices. Its primary objective is to examine recent advances in research on school attendance, identify the underlying causes and consequences of absenteeism, and guide the development of evidence-based interventions and educational policies that prevent early school leaving. School absenteeism is a multifaceted and complex phenomenon, encompassing late arrivals, partial absences, single-day absences, and prolonged non-attendance over weeks or months. Empirical research has consistently shown that absenteeism can have short- and medium-term consequences on academic performance, school retention, social integration, future employment opportunities, and mental health outcomes (Brandibas, et al., 2004; Kearney & Bates, 2005; Kearney, 2008; Thambirajah et al., 2008). Moreover, recurrent absenteeism may create a self-perpetuating cycle, which is often difficult to reverse if early warning signs are not detected and addressed (Reid, 2005). These findings underscore the critical importance of early identification and timely intervention, which can mitigate the potential social, academic, and psychological consequences associated with prolonged absenteeism (Kearney, 2001; Lyon & Cotler, 2007). Research distinguishes between legitimate and illegitimate reasons for school absence. Approximately 80% of absences are considered legitimate or authorised, typically related to illness or family circumstances (Kearney, 2008; Kearney & Silverman, 1999; Thambirajah et al., 2008; Havik et al., 2015). Among legitimate reasons, subjective or psychosomatic complaints are frequently reported, including headaches, dizziness, muscular pain, and gastrointestinal symptoms, which tend to increase during adolescence (Perquin et al., 2000; Roth-Isigkeit et al., 2004; Simonsson et al., 2008). In contrast, illegitimate absences, often associated with school refusal, arise when students experience anxiety, social discomfort, or difficulties remaining at school for the entire day (Kearney, 2008; Kearney & Albano, 2004; Kearney & Silverman, 1999). Criteria for identifying problematic absenteeism include missing more than 25% of school time over two weeks, experiencing serious difficulties attending school for at least two weeks, or accumulating more than 10 days (or 15%) of absences during a 15-week period in the school year (Kearney, 2008; Kearney & Silverman, 1999). Within the broader Erasmus+ project, six validated assessment scales from international authors were administered via a student questionnaire to 1,831 students in Portuguese schools to investigate the factors influencing absenteeism. These instruments included the Havik et al. ARNS scale (Assessing Reasons for School Non-Attendance, 2015), which evaluates absenteeism across multiple dimensions, including somatic symptoms, subjective health complaints, truancy, and school refusal. Other scales measured perceived competence, school refusal, teamwork, sense of belonging, and overall school functioning. The main findings indicate that absenteeism was largely occasional and predominantly associated with health-related factors, while other emotional, social, and contextual factors played a smaller role. Although the overall level of absenteeism was low, a notable minority of students still experienced extended or recurrent absences, highlighting the importance of paying attention to at-risk groups. Overall, the study emphasises the relevance of understanding both health-related and psychosocial contributors to school absenteeism, providing essential guidance for early identification of students at risk and the development of preventive interventions. These results underscore the need for coordinated strategies involving students, families, and schools, while promoting the dissemination of effective practices to reduce absenteeism and enhance educational inclusion. Methodology, Methods, Research Instruments or Sources Used The present study is part of a broader research project aimed at understanding school attendance problems through a mixed-methods design, combining quantitative and qualitative approaches in order to obtain a comprehensive and contextualised analysis. The quantitative component consisted of the administration of a student questionnaire comprising six validated scales that assess multiple individual, relational, and school-related factors associated with school attendance. These instruments included: (1) the Assessment of Reasons for School Absenteeism (Havik et al., 2015); (2) What Is Happening at School? (Aldridge & Ala’l, 2013); (3) the Perception of Competence in Life Domains Scale (Losier et al., 1993); (4) the School Refusal Evaluation Scale (Gallé-Tessonneau & Gana, 2019); (5) the Teamwork Scale for Youth (Lower-Hoppe et al., 2015); and (6) the General Belongingness Scale (Malone et al., 2012). Formal authorisation to use all instruments in the Portuguese context was obtained from the original authors. In Portugal, the questionnaire was administered online and face-to-face between May and June 2025 to a total of 1,831 students from two public school clusters in Northern Portugal. Participants were aged between 6 and 19 years, with a balanced gender distribution (51.0% girls and 49.0% boys). Students were enrolled across all levels of compulsory education, from the 1st cycle of basic education to secondary education, and the majority reported Portuguese nationality. The qualitative component involved 18 focus groups (n = 138) conducted with key educational stakeholders: teachers (8 focus groups; n = 82) and parents/guardians (10 focus groups; n = 56). Focus groups were carried out online (via Zoom) and in person in May 2025 and addressed central topics related to school attendance, including perceived attendance problems, strategies and forms of intervention, support needs, and training needs. Ethical approval for the study was granted by the Ethics Committee for Research in Social and Human Sciences (ref. 092/2025), and authorisation to conduct the research in schools was obtained from the Portuguese Ministry of Education / Directorate-General for Education (no. 0803500002). Although the overall project integrates quantitative data from six scales and qualitative data from focus groups, the present communication reports exclusively on the quantitative findings derived from the student questionnaire, with a specific focus on the Norwegian scale assessing reasons for school absenteeism developed by Havik et al. (2015). Results from the remaining instruments and from the qualitative component are not addressed in this communication. Conclusions, Expected Outcomes or Findings The results of this study indicate that school absenteeism was generally limited, with the majority of students reporting either no absences (43.2%) or short periods of absenteeism of 1–4 days (43.8%) during the previous 3 months. Together, these findings suggest that, for most students, school attendance was relatively regular and absences were largely occasional rather than persistent. However, it is important to emphasise that a non-negligible minority of students experienced more extended absenteeism. Specifically, 7.1% of students reported missing school for 5–7 days, 2.7% for 8–10 days, and 3.1% for more than 10 days. Although these percentages are comparatively low, they represent a group of students potentially at higher risk for developing chronic absenteeism. Across the sample, absenteeism was predominantly explained by health-related complaints, reported far more frequently than other reasons. The most cited health problems included fever (25.2%), headaches (23.4%), constipation or flu-like symptoms (23.3%), and general malaise (20.8%). Gastrointestinal complaints were also frequent, with 14.2% reporting nausea or vomiting and 11.5% reporting stomach pain, while other illnesses accounted for 10.8% of absences. These findings suggest that physical health issues are the primary driver of school absenteeism. In contrast, non-health-related reasons were reported by a much smaller proportion of students: tiredness (6.0%), participation in more attractive activities outside school (2.9%), fear related to school (2.0%), and avoidance of unpleasant situations (1.4%). Although these percentages are relatively low, they may reflect underlying psychosocial or motivational difficulties that, if unaddressed, could contribute to more severe attendance problems over time. Taken together, these results highlight that while school absenteeism is mostly occasional and health-related, the presence of students with prolonged absences and non-health-related difficulties should not be underestimated. As previous research suggests, absenteeism can become a persistent and self-reinforcing cycle if early signs are not identified (Reid, 2005). References Brandibas, G., Jeunier, B., Clanet, C., & Fourasté, R. (2004). Truancy, School Refusal and Anxiety. School Psychology International, 25(1), 117–126. https://doi.org/10.1177/0143034304036299 Havik, T., Bru, E., & Ertesvåg, S. K. (2015). School factors associated with school refusal- and truancy-related reasons for school non-attendance. Social Psychology of Education: An International Journal, 18(2), 221–240. https://doi.org/10.1007/s11218-015-9293-y Kearney, C. A. (2001). School Refusal Behavior in Youth: A Functional Approach to Assessment and Treatment. American Psychological Association. https://doi.org/10.1037/10426-000 Kearney, C. A. (2008). School absenteeism and school refusal behavior in youth: A contemporary review. In Clinical Psychology Review (Vol. 28, Issue 3, pp. 451–471). https://doi.org/10.1016/j.cpr.2007.07.012 Kearney, C. A. & Albano, A. M. (2004). The Functional Profiles of School Refusal Behavior: Diagnostic Aspects. Behavior Modification, 28(1), 147 161. DOI:10.1177/0145445503259263 Kearney, C. A., & Bates, M. (2005). Addressing School Refusal Behavior: Suggestions for Frontline Professionals. Children & Schools, 27(4), 207–216. https://doi.org/10.1093/cs/27.4.207 Kearney, C. A., & Silverman, W. K. (1999). Functionally based prescriptive and nonprescriptive treatment for children and adolescents with school refusal behavior. Behavior Therapy, 30(4), 673–695. https://doi.org/10.1016/S0005-7894(99)80032-X Lyon, A. R., & Cotler, S. (2007). Toward reduced bias and increased utility in the assessment of school refusal behavior: The case for diverse samples and evaluations of context. Psychology in the Schools, 44(6), 551–565. https://doi.org/10.1002/pits.20247 Perquin, C. W., Hazebroek Kampschreur, A. A., Hunfeld, J. A. M., Bohnen, A. M., van Suijlekom Smit, L. W. A., Passchier, J., & van der Wouden, J. C. (2000). Pain in children and adolescents: A common experience. Pain, 87(1), 51–58 Reid, K. (2005). The Implications of Every Child Matters and the Children Act for Schools. Pastoral Care in Education, 23(1), 12–18. https://doi.org/https://doi.org/10.1111/j.0264-3944.2005.00317.x Roth Isigkeit, A., Thyen, U., Raspe, H. H., Stöven, H., & Schmucker, P. (2004). Reports of pain among German children and adolescents: An epidemiological study. Acta Paediatrica, 93(2), 258–263 Simonsson, B., Nilsson, K. W., Leppert, J., & Diwan, V. K. (2008). Psychosomatic complaints and sense of coherence among adolescents in a county in Sweden: A cross-sectional school survey. BioPsychoSocial Medicine, 2, Article 4. https://doi.org/10.1186/1751-0759-2-4 Thambirajah, M. S., Grandison, K. J., & De Hayes, L. (2008). Understanding School Refusal: A Handbook for Professionals in Education, Health and Social Care. Jessica Kingsley Publish | ||
