Prosocial Behavior and School Performance in the Transition to Adolescence: A Multicultural Study.

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Published before final editing as: Appl Dev Sci. 2025 May 31:10.1080/10888691.2025.2498747. doi: 10.1080/10888691.2025.2498747 Prosocial Behavior and School Performance in the Transition to Adolescence: A Multicultural Study Flavia Cirimele a, * , Concetta Pastorelli b , Marc H Bornstein c, d, e , Antonio Zuffianò b , Chiara Remondi b , Maria Gerbino b , Dario Bacchini f , Laura Di Giunta b , Paul Oburu g , Ann T Skinner h , Emma Sorbring i , Laurence Steinberg j, k , Liliana Maria Uribe Tirado l , Saengduean Yotanyamaneewong m , Liane Peña Alampay n , Suha M Al-Hassan o , Lei Chang p , Kirby Deater-Deckard q , Kenneth A Dodge h , Sevtap Gurdal i , Daranee Junla m , Jennifer E Lansford h Author information Copyright and License information a Department of Culture and Society, University of Palermo, Palermo, Italy b Department of Psychology, Sapienza University of Rome, Rome, Italy c Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, United States d United Nations Children’s Fund (UNICEF), New York, NY, United States e Institute for Fiscal Studies, London, United Kingdom f Department of Humanistic Studies, University of Naples ‘Federico II’, Naples, Italy g Education Psychology, Maseno University, Maseno, Kenya h Center for Child and Family Policy, Duke University, Durham, NC, United States i Department of Social and Behavioural Studies, University West, Trollhättan, Sweden j Department of Psychology, Temple University, Philadelphia, PA, United States k Department of Psychology, King Abdulaziz University, Jeddah, Saudi Arabia l Facultad de Psicología, Universidad San Buenaventura, Medellín, Colombia m Department of Psychology, Chiang Mai University, Chiang Mai, Thailand n Ateneo de Manila University, Quezon City, Philippines o Special Projects and Partnerships, Abu Dhabi Early Childhood Authority, Abu Dhabi, United Arab Emirates p Department of Psychology, University of Macau, Macau, China q Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, MA, United States * Correspondence should be addressed to Dr. Flavia Cirimele, Department of Culture and Society, University of Palermo, Viale delle Scienze, Ed. 15, 90128 Palermo (Italy). flavia.cirimele@unipa.it PMC Copyright notice PMCID: PMC12383974  NIHMSID: NIHMS2078473  PMID: 40880668 The publisher's version of this article is available at Appl Dev Sci Abstract The present study explored the bidirectional longitudinal associations between prosocial behavior and school performance during adolescence in six countries (Colombia, Italy, Jordan, the Philippines, Thailand, and the United States). A total sample of 884 adolescents (T1: M age = 10.34 years, SD = 0.69) reported their prosocial behavior, while adolescents’ mothers ( N = 871) and fathers ( N = 773) reported their children’s school performance over three-time points covering the transition to adolescence (from ages 10 to 16). A Random-Intercept Cross-Lagged Panel Model, controlling for countries’ Human Development Index, child gender, and family SES, showed that adolescents with high levels of prosocial behavior also have high school performance on a stable basis over time. Moreover, being more prosocial than usual is positively associated with higher-than-expected school performance at each time point. The implications of the interplay between prosocial behavior and school performance during the transition to adolescence in multicultural contexts are discussed. Keywords: prosocial behavior, school performance, cascade models, multicultural perspective, adolescence Introduction Improving education quality for children and adolescents worldwide is one of the 2030 UN Agenda for Sustainable Development Goals that calls for researchers to recognize those determinants that promote students’ potential at school ( UNICEF, 2018 ). Although researchers have strengthened efforts to identify economic policies and educational curricula that may improve school performance globally (e.g., Delprato & Antequera, 2021 ), the protective role of positive individual factors against academic pitfalls is partly understudied ( Farrington et al., 2012 ). Among many positive individual factors, prosocial behavior, defined as voluntary actions aimed to benefit others, such as helping, comforting, and sharing ( Eisenberg et al., 2006 ), has proven beneficial to school performance, improving the quality of relationships with classmates and teachers, and facilitating learning processes and achievement (e.g., Caprara et al., 2000 ; Jensen et al., 2023 ). Hence, several cross-sectional (e.g., Bandura et al., 1996 ) and longitudinal (e.g., Caprara et al., 2000 ) studies have examined the predictive role of prosocial behavior on school performance, suggesting that being more prone to help, comfort, and share predicts better performance at school. However, to our knowledge, only one recent study showed that a related construct of school performance (i.e., school engagement) fosters later prosocial growth ( Li et al., 2025 ). Echoing Masten and Cicchetti’s model (2010) , the longitudinal association between prosocial behavior and school performance may be a developmental cascade characterized by reciprocity over time. The cascade model, which was corroborated by previous longitudinal studies, assumes that changes in one domain (e.g., social) trigger changes in other domains (e.g., cognitive), creating dynamic interactions over time ( Bornstein et al., 2013 ; Lansford et al., 2010 ; Racz et al., 2017 ). Developmental cascades describe the over-time effects of interactions and exchanges within evolving factors of individual function. These effects can manifest in direct or indirect ways, either unidirectional or bidirectional, but they ultimately shape the trajectory of development rather than being temporary ( Masten & Cicchetti, 2010 ). Thus, one may hypothesize that prosocial behavior developed within the family context is carried forward at school, triggering a cascade process that increases the opportunities to build better relationships with classmates and teachers ( Bergin, 2014 ; Coolahan et al., 2000 ; Malti & Speidel, 2023 ; McClelland & Morrison, 2003 ) and hold a greater capacity to engage in school activities that determine better academic performance over time than those with low levels of prosocial behavior ( Bierman et al., 2009 ; Witkow & Fuligni, 2011 ). On the other hand, in the developmental literature (e.g., Christenson et al., 2012 ), there is evidence that academic success plays a strong protective role in reducing risky behaviors and favoring psychosocial adjustment during adolescence ( Dishion & Patterson, 2015 ; Elder & Conger, 2000 ). Thus, we cannot exclude the possibility that academic competence and success increase prosocial behavior over time, perhaps as a result of strong school engagement. Students who perform well academically also tend to develop higher academic and self-regulatory efficacy, better social skills, and a stronger sense of belonging within the school environment ( Catalano et al., 2004 ; Farrington et al., 2012 ). Highly engaged students may invest more time and effort in building positive social relationships, cooperation, and empathy toward their peers, ultimately enhancing their prosocial tendencies ( Christenson et al., 2012 ; Li et al., 2025 ). Therefore, building on the cascade model, the current study aims to extend existing research about the longitudinal pathways between prosocial behavior and school performance using a Random-Intercept Cross-Lagged Panel Model (RI-CLPM; Hamaker et al., 2015 ). Specifically, we investigated the longitudinal association between prosocial behavior and school performance using three waves of data over six years spanning from late childhood (age 10 years) to adolescence (age 16 years), to investigate three research questions: (1) Are stable individual differences in prosocial behavior and school performance related to each other? (2) Are fluctuations from the stable level of prosocial behavior associated with higher-than-expected levels of adolescent school performance at each time point? (3) Are fluctuations from the stable level of school performance associated with higher-than-expected levels of children’s prosocial behavior at a subsequent time point? The present study uses a large multicultural sample from six countries (Colombia, Italy, Jordan, the Philippines, Thailand, and the United States) to identify whether the socioeconomic context accounts for a portion of the association between prosocial behavior and school performance. Indeed, most studies have been conducted in the minority world (i.e., countries that include a minor percentage of the world population, e.g., Italy and the United States), leaving underrepresented youth experience from the majority world (i.e., countries that include the majority of the world population; e.g., Colombia, Jordan, Philippines, and Thailand; Khan et al., 2022 ). Concurrent and Longitudinal Associations between Prosocial Behavior and School Performance Previous studies have found concurrent ( Bandura et al., 1996 ; Emagnaw & Hong, 2018 ; Shirin, 2020 ; Wentzel, 1993 ) and longitudinal ( Caprara et al., 2000 ; Carlo et al., 2018 ; Chen et al., 1997 ; Gerbino et al., 2018 ; Guo et al., 2018 ) associations between prosocial behavior and school performance over the transition to adolescence in both the minority and majority world. Previous cross-sectional findings have focused on late childhood and adolescence and evidenced a positive relation between prosocial behavior and school performance in minority world samples ( Bandura et al., 1996 ; Wentzel, 1993 ) and mixed results in studies conducted with majority world samples ( Emagnaw & Hong, 2018 ; Shirin, 2020 ). In a study with a sample of 423 students aged 11 to 13 from the United States, peer- and teacher-reported prosocial behavior was linked with higher grades in reading, math, art, history, and science, beyond the effects of previous grades, sociodemographic characteristics, students’ IQ, and days absent from school (( Wentzel, 1993 ). Similarly, a study of 279 Italian children aged 11 to 14 years evidenced that self-reported prosocial behavior was highly associated with academic grades ( Bandura et al., (1996) . To our knowledge, only two studies have examined associations between prosocial behavior and school performance in the majority world, and they produced contradictory results ( Emagnaw & Hong, 2018 ; Shirin, 2020 ). Specifically, Emagnaw and Hong (2018) , with a sample of 210 Ethiopian preadolescents (i.e., from 13 to 14 years), found a moderate positive association, but Shirin (2020) , with a sample of 150 Bangladeshi students aged approximately 14 years, did not find any significant associations between self-reported prosocial behavior and academic grades. Concerning longitudinal studies, previous research has focused on the predictive role of prosocial behavior on better school functioning during the transition to adolescence in the minority ( Adams et al., 1999 ; Caprara et al., 2000 ; Carlo et al., 2018 ; Gerbino et al., 2018 ; Jensen et al., 2023 ) and majority (i.e., Chen et al., 1997 ; Guo et al., 2018 ) world. Regarding the minority world, Adams et al. (1999) conducted a short-term longitudinal study with 364 children between 8 and 11 years from the United Kingdom. Teacher-reported student prosocial behavior at the beginning of the academic year predicted students’ reading and math grades one year later. Examining a more extended time lag, Caprara and colleagues (2000) , with a sample of 294 Italian children of four cohorts (ages 8 to 14 years), found that prosocial behavior reported by self, peer, and teachers at 8 years strongly predicted academic achievement at 13–14 years, controlling for previous levels of academic achievement and aggressive behaviors. Similar results were found by Gerbino and colleagues (2018) with a sample of Italian preadolescents, showing that prosocial behavior at 12 years predicted better academic achievement over 5 years, controlling for personality traits and intelligence. Likewise, a 3-wave study with 462 U.S. Mexican youth aged 10 to 18 years revealed that previous self- and teacher-reported prosocial behavior predicted subsequent better academic grades through the mediating effect of academic self-efficacy ( Carlo et al., (2018) . Finally, Jensen and colleagues (2023) studied two cohorts of more than 1000 German adolescent students; prosocial behavior significantly predicted school grades two years later, over and above the effects of externalizing problems, general cognitive abilities, self-concept, and prior school achievement. Regarding longitudinal findings in the majority world, Chen and colleagues (1997) involved 470 children from Shanghai at age 12 and found that prosocial behavior assessed by peers predicted adolescents’ school grades two years later, beyond the effect of previous academic achievement and gender. Guo et al. (2018) conducted a longitudinal study with 456 Chinese preadolescents aged approximately 11 years at the beginning of the academic year, showing that both self- and peer-reported prosocial behavior positively predicted academic grades at the end of the academic year, controlling for gender, family socioeconomic status (SES), school grades, previous academic achievement, and peer acceptance. To our knowledge, only two studies ( Li et al., 2025 ; Miles & Stipek, 2006 ) tested bidirectional associations between school performance and prosocial behavior. However, Miles and Stipek (2006) focused on a developmental period covering early to late childhood, which precedes the age range considered for the present study. Specifically, in a 3-wave longitudinal cohort study involving approximately 200 economically disadvantaged children, they found that prosocial behavior positively predicted literacy achievement during middle childhood (7–8 years). However, neither bidirectional associations nor predictive effects of prosocial behavior on literacy achievement emerged during late childhood (10–11 years). Regarding the recent longitudinal study by Li and colleagues (2025) , involving 4,691 children (approximately ages 9 to 14), results showed that school engagement (i.e., children’s tendency to learn and perform well academically) consistently predicted later prosocial behavior at both the between- and within-person levels. These findings suggest that strong academic performance favors prosocial development during the transition to adolescence. Extant research provides evidence of concurrent and longitudinal associations between prosocial behavior and school performance, but important limitations should be noted. First, although the existence of reciprocal associations between prosocial behavior and academic achievement seems plausible ( Malti & Speidel, 2023 ), the failure to gather longitudinal data spanning more than one developmental period (i.e., Miles & Stipek, 2006 ) and the scarcity of studies that test bidirectional associations during adolescence imposes serious limits on the understanding of how behaving prosocially in an earlier developmental phase fosters better academic achievement in a later stage, and vice versa. In fact, during the transition to adolescence, students experience many school transitions (i.e., from elementary to middle school and from middle to high school) that, in line with developmental cascade assumptions, may challenge both their social adjustment (e.g., disruptions of friendships and school ties) and school competencies (e.g., academic achievements; Catalano et al., 2004 ; Masten & Cicchetti, 2010 ). Therefore, it is crucial to test whether and how prosocial behavior and academic achievement reciprocally influence one another in different developmental periods. Second, from a methodological perspective, only one study has examined the link between prosocial behavior and a related construct of school performance (i.e., engagement; Li et al., 2025 ) using the novel RI-CLPM ( Hamaker, 2023 ; Hamaker et al., 2015 ). However, this model is particularly suitable for studying developmental cascades, as it helps examine the direction and timing of associations between prosocial behavior and school performance. The RI-CLPM distinguishes whether the variance is explained at the between-person level, capturing stable individual differences over time (i.e., variations between individuals over a given developmental period; e.g., do more prosocial children have higher school performance than less prosocial children?), and at the within-person level, representing state-like (or temporary) individual fluctuations from its usual level (i.e., stability; e.g., is being more prosocial than usual related to higher-than-usual levels of school performance?). This distinction is crucial because it helps investigate to what extent the relation between prosocial behavior and school performance reflects trait-like, between-person differences and/or dynamic, state-like, within-person associations. In other words, using the RI-CLPM facilitates the understanding of the extent to which (1) a general tendency to behave prosocially over time is associated with a general tendency to perform better at school (i.e., between-person level) and (2) higher-than-usual levels of both prosocial and school performance influence each other over time (i.e., within-person level). Third, most of what is known about the relation between prosocial behavior and school performance lacks evidence from diverse multicultural contexts. In fact, most studies come from samples of the minority world ( Adams et al., 1999 ; Caprara et al., 2000 ; Carlo et al., 2018 ; Gerbino et al., 2018 ; Jensen et al., 2023 ). Thus, the experience of children and adolescents in the majority of the world is largely underrepresented in the prosocial literature ( Armstrong-Carter & Telzer, 2021 ). Nevertheless, contextualizing research in countries that differ in national wealth and educational systems may increase understanding of whether and how adolescents in different contexts enact other-oriented behaviors and perform at school. Socioeconomic and Educational Differences Worldwide Educational challenges occur in each country worldwide. All countries need to accelerate the application of strategies that may be conducive to better educational quality ( UNICEF, 2018 ). However, as evidenced by some international reports (e.g., OECD, 2021 ), countries in the majority world rank lower compared to the minority world in educational indicators, such as access to education, the proportion of children that at the end of primary and secondary school achieve minimum proficiency levels in reading and math, or government financial investment in education. In the majority world, factors such as the low percentage of teachers for students and diminished allocations to school infrastructure (e.g., physical, educational, and technology) negatively affect children’s socioemotional skills, socialization processes, school climate, and school competences ( Delprato & Antequera, 2021 ; OECD, 2019 ). At the socioeconomic level, the majority world is more characterized by recent historical and political issues that make the general environment uncertain and unpredictable ( OECD, 2017 ), whereas the minority world is generally characterized by higher gross national income per capita, which allows the implementation of more legislation efforts for population welfare (World World Bank, 2022 ). The environment in which children and adolescents from the majority world grow is characterized by less access to water, sanitation, and hygiene; less infrastructure; lower education levels; systemic political instability; and more significant health risks than the minority world. In contrast, children and adolescents who grow up in the minority world tend to experience more school opportunities, environmental infrastructure, and stable health systems ( UNFPA, 2010 ). These differences may affect the development of positive behaviors and psychosocial adjustment (Cirimele et al., 2024; Flay et al., 2009 ), mainly in the transition to adolescence, which seems to be a sensitive period for conforming to local social norms and becoming part of the larger society outside family contexts ( House et al., 2013 ; Lancy & Grove, 2011 ; Thompson & Nelson, 2011 ). Thus, deepening knowledge about the positive role of prosocial behavior on school performance among contexts with different national wealth could be informative for policies aimed at achieving education quality worldwide. The Present Study The present study extends previous literature by investigating longitudinal bidirectional associations between prosocial behavior and school performance in the transition to adolescence (from age 10 to 16 years) in a large multicultural sample. The aims of the present study are twofold. First, we examine the bidirectional longitudinal associations between prosocial behavior and school performance in the transition to adolescence by implementing the RI-CLPM. Based on previous arguments ( Christenson et al., 2012 ; Hammond et al., 2023 ; Malti & Speidel, 2023 ; Masten & Cicchetti, 2010 ), it might be that a higher general tendency of being prosocial is associated with higher performance at school (i.e., between-person level), as well as higher-than-expected levels of prosocial behavior at a given time point are associated with higher-than-expected levels of school performance, and vice versa (i.e., within-person level). Second, we aimed to take into account differences in national wealth in the bidirectional associations between prosocial behavior and school performance. Given that each country is characterized by socioeconomic peculiarities that differently affect social and academic outcomes (Cirimele et al., 2024; Delprato & Antequera, 2021 ), we included the Human Development Index (i.e., HDI, composite index at the country-level covering long and healthy life, knowledge, and decent standard of living) as a time-invariant predictor in our analyses. Finally, we controlled for child gender and family SES in our analyses. Regarding child gender, previous studies have found that during childhood and adolescence, girls seem to show more prosocial behavior ( Caprara et al., 2000 ; Eisenberg et al., 2006 ; Luengo Kanacri et al., 2013 ; Nantel-Vivier et al., 2009 ; Van der Graaff et al., 2018 ) and score higher in school performance ( Carvalho, 2016 ; Marcenaro–Gutierrez et al., 2018 ). Regarding SES, a review by ( Robinson & Piff, 2017 ) evidenced that individuals with lower SES are more prone to engage in other-oriented behaviors compared to those with high SES. Low SES sometimes undermines successful school performance ( Caro et al., 2009 ; Chung, 2015 ). Thus, child gender and family SES are included as time-invariant predictors in our models. Materials and Method Participants Participants were recruited from the longitudinal and cross-cultural study Parenting Across Cultures (for more details, see Lansford & Bornstein, 2011; Lansford et al., 2014). The present study sample included 884 children, 871 mothers, and 773 fathers across six countries (Colombia, Italy, Jordan, Philippines, Thailand, and the United States), who provided data over six years in 3 waves. Children were aged an average of 10.34 years ( SD = 0.69, range 8–13, 50.2% boys) at Time 1 (T1), 12.95 years ( SD = 0.77, range 11–15, 50.1% males) at Time 2 (T2), and 16.46 years ( SD = 0.91, range 15–19, 50.3% males) at Time 3 (T3). Mothers averaged 39.94 years ( SD = 6.72, range 21–72 at T1) and fathers 42.77 ( SD = 7.06, range 25–75) years at T1. Regarding years of education, mothers and fathers completed an average of 12.68 ( SD = 4.36, range 0 – 27) and 12.58 ( SD = 4.40, range 1 – 27) years, respectively. The retention rate remained moderately high (i.e., 88.1% from T1 to T3) over time and across countries. Attrition Overall, the retention rate remained high (i.e., 88.1% from T1 to T3). The retention rates across the countries were as follows. In Colombia, the retention rate was 85.0% from T1 to T2, 80.0% from T1 to T3, and 87.5% from T2 to T3. In Italy, the retention rates were 90.2% from T1 to T2, 88.7% from T1 to T3, and 91.5% from T2 to T3. Jordan reported retention rates of 92.0% from T1 to T2, 89.4% from T1 to T3, and 97.1% from T2 to T3. In the Philippines, the retention rates were 84.8% from T1 to T2, 77.6% from T1 to T3, and 81.6% from T2 to T3. Thailand showed retention rates of 82.7% from T1 to T2, 67.3% from T1 to T3, and 81.2% from T2 to T3. Finally, the United States had retention rates of 87.9% from T1 to T2, 81.9% from T1 to T3, and 87.5% from T2 to T3. Analyses of variance revealed no significant differences in prosocial behavior between missing and retained participants across the three time points: T1 to T2 [ F (2, 881) = 0.07, p = 0.80], T1 to T3 [ F (2, 881) = 0.02, p = 0.88], and T2 to T3 [ F (2, 828) = 2.86, p = 0.09]. Similarly, no significant differences were observed in school performance between attrited and retained participants from T1 to T2 [ F (2, 892) = 1.01, p = 0.36], T1 to T3 [ F (2, 895) = 0.16, p = 0.86], and T2 to T3 [ F (2, 836) = 2.60, p = 0.08]. Regarding HDI, no differences were found between the groups from T1 to T2 [ F (2, 912) = 2.10, p = 0.12] or from T2 to T3 [ F (2, 855) = 0.73, p = 0.48]. However, from T1 to T3, retained participants scored significantly higher in HDI compared to attrited participants [ M attrited = 0.80 ( SD = 0.01) vs. M retained = 0.82 ( SD = 0.10); F (2, 915) = 3.16, p < .05]. Procedure The present study used data collected in each country from 2010 to 2016, and the procedures were the same at each site. Letters describing the study were sent home from schools. Those parents who agreed to be contacted to participate in the study returned a signed form. During the sampling procedure within each country, families involved were proportionally equivalent to the socioeconomic characteristics of each city from which they were recruited to ensure the sample’s representativeness. Families were sampled from private and public schools belonging to low-, middle-, and high-income status. The research team of each country conducted a translation and back-translation procedure to ensure the linguistic, conceptual, and cultural equivalence of the measures used. The study received approval from Institutional Review Boards (IRBs) at participating universities in each country. The interview procedure was performed as follows. Parental informed consent and children’s assent were obtained at each wave before the interview started. Participants chose the location (e.g., home, university) for the interviews. Parents were given the choice between oral and written completion of the interviews. In the initial years, interviewers carefully read each item of the questionnaire and recorded children’s answers; in later years, children were given the choice between oral and written completion. For oral interviews, interviewers provided visual aids of rating scales. Interviews took approximately 2 hours. In accordance with each country’s IRBs, families received modest financial or other compensation for their participation. Measures Prosocial Behavior Children’s prosocial behavior was measured using the 5-item self-report Prosocial Behavior Scale ( Caprara & Pastorelli, 1993 ; Pastorelli et al., 1997 ) for children (e.g., ‘I try to help others’). For study design reasons, at Time 3, prosocial behavior was measured using 3 items representing this construct’s main facets (i.e., comforting, helping, and sharing). Due to the availability of two more items at Times 1 and 2, we selected five items at these time points and adopted a parcel method ( Little et al., 2022 ) to increase the representativeness of two facets of prosocial behavior (i.e., helping and sharing). Specifically, common items of these facets were identified based on their conceptual and theoretical overlap (i.e., content validity approach; Haynes et al., 1995 ). Subsequently, to ensure the consistency of the prosocial behavior construct over time using a different set of items, we conducted a series of measurement invariance models ( Putnick & Bornstein, 2016 ); details of these invariance tests are provided in the online supplement . Each item was rated on a 3-point scale (1 = never/almost never to 3 = often). Omega reliability coefficients were .677, .669, and .676 at T1, T2, and T3, respectively. School Performance School performance was assessed by adopting the performance in academic subjects section of the Child Behavior Checklist (CBCL; Achenbach, 1991 ). Mothers and fathers were asked to report their children’s school performance in four areas common across the six countries involved in the study (i.e., reading, math, social studies, and science). Parents rated each item on a 4-point scale (1 = failing, 2 = below average, 3 = average, or 4 = above average). Given high correlations among informants in each wave ( r = .69 to r = .71), a single measure of school performance was computed as an average of the 4-item of mothers’ and fathers’ reports. Omega reliability coefficients were .851, .854, and .871 at T1, T2, and T3, respectively. Time-Invariant Predictors Human Development Index. Differences in national wealth were measured with the Human Development Index (HDI), defined in 2010 by the United Nations Development Programme (UNDP), representing T1 of the present study. The HDI measures countries’ development along three dimensions: (1) long and healthy life (i.e., life expectancy at birth), (2) knowledge (i.e., expected years of schooling and mean years of schooling), and (3) decent standard of living (i.e., gross national income per capita). The average of these three dimensions offers a country-level composite measure ranging from 0 to 1, in which scores closer to zero represent lower achievements in key dimensions of human development and scores closer to 1 represent countries with higher achievements along these three dimensions. The HDI was retrieved from the Human Development Reports of the UNDP website ( https://hdr.undp.org/data-center/human-development-index#/indicies/HDI ) and merged with our dataset. The countries involved in our study ranked in HDI as follows: Philippines (0.67), Colombia (0.73), Jordan (0.73), Thailand (0.74), Italy (0.88), and United States (0.92). Gender. Children were asked to report their gender. This variable was coded 0 for boys and 1 for girls. Family SES. Family SES was assessed using an average of standardized values within countries of mothers’ reports of family income and mothers’ and fathers’ reports of their years of education. Data Analytic Approach In order to ascertain measurement invariance across time, we preliminary tested a series of longitudinal (T1 vs T2 vs T3) measurement invariance models on the measures of prosocial behavior and school performance (see supplementary material for more details on measurement invariance procedure and results). Subsequently, to test reciprocal longitudinal relations between prosocial behavior and school performance, we implemented the RI-CLPM ( Hamaker, 2023 ; Hamaker et al., 2015 ). This model allowed us to estimate: (a) stable individual differences in prosocial behavior and school performance over time (i.e., random-intercept); (b) covariation between the two random-intercepts, which represents the correlation between the time-invariant (stable) part of prosocial behavior and the time-invariant (stable) part of school performance over time; (c) carry-over paths that represent the persistence of the deviations in prosocial behavior (or school performance) over time; (d) spill-over paths that represent within-level bidirectional effects of higher-than-usual levels of prosocial behavior at a given time point on higher-than-usual levels of school performance at the subsequent time point (and vice versa); and (e) temporal dynamics associations that estimate, at the within-level, the time-specific correlations between the deviations of prosocial behavior and school performance (i.e., representing whether a peak in prosocial behavior at a given time point is associated with a simultaneous peak in school performance at the same time point). We tested an unconstrained model in which all parameters were freely estimated and a constrained model in which bidirectional association at the between-level, the carry-over, spill-over, and temporal dynamics parameters were constrained to be equal over time. Subsequently, to account for the HDI, child gender, and family SES on these longitudinal associations, we tested a conditional model in which the observed prosocial behavior and school performance variables at each time point were regressed on these three time-invariant predictors. To understand whether the effect of each time-invariant predictor differs across time, we tested an unconstrained versus constrained model in which each predictor was constrained to be equal in its associations with observed variables across time. All comparisons between the unconstrained versus the constrained model were carried out using the corrected Satorra-Bentler Chi-square Difference Test (Δχ2; Muthén & Muthén, 1998–2016 ). All analyses were conducted using M plus 8.4 ( Muthén & Muthén, 1998–2016 ), applying the Maximum Likelihood with standard errors robust to non-normality (MLR) estimator to estimate all parameters and handle missing data. To evaluate the goodness of fit of our models, we used the following indicators: Chi-square index (χ 2 ), Comparative-Fit-Index (CFI) and Tucker-Lewis-Index (TLI) values greater than 0.90 as indicators of acceptable model fit, and CFI/ TLI >0.95 as indicators of good model fit ( Brown, 2015 ; Kelloway, 1998 ; Kline, 2023 ), as well Root-Mean-Square-Error-of-Approximation (RMSEA) with 90% Confidence Interval (CI), and Standardized-Root-Mean-Square-Residual (SRMR) values lower than 0.08 as indicators of acceptable model fit and below 0.05 as indicators of good model fit ( Brown, 2015 ; Iacobucci, 2010 ). Results Descriptive Statistics and Correlations The means, standard deviations, and Pearson correlation coefficients of the total sample are reported in Table 1 . Moreover, we reported the means and standard deviations of variables of interest in each country in Table 2 . Prosocial behavior and school performance were positively associated across time, ranging from r = .13 ( p < .001) to r = .22 ( p < .001). Table 1. Descriptive Statistics and Correlations for Study Variables. Variables M SD Skewness Kurtosis 1 2 3 4 5 6 7 8 9 1. HDI 0.82 0.09 - - - 2. Gender (0= boys, 1=girls) 0.49 0.50 - - -.01 - 3. Family Socioeconomic Status -0.02 0.86 - - -.01 .01 - 4. Prosocial Behavior T1 2.46 0.40 -0.42 -0.64 .20 ** .18 ** .07 * - 5. Prosocial Behavior T2 2.48 0.38 -0.69 0.08 .15 ** .21 ** .09 * .36 ** - 6. Prosocial Behavior T3 2.60 0.43 -0.72 -0.47 -.08 * .10 ** .08 * .16 ** .23 ** - 7. School Performance T1 3.35 0.48 -0.40 0.00 .03 .06 .35 ** .20 ** .17 ** .17 ** - 8. School Performance T2 3.30 0.52 -0.43 0.04 -.00 .09 ** .36 ** .14 ** .18 ** .20 ** .75 ** - 9. School Performance T3 3.31 0.54 -0.58 0.40 -.01 .12 ** .35 ** .13 ** .20 ** .22 ** .72 ** .78 ** - Open in a new tab Note . To increase readability, HDI was centered on the grand mean for correlation analyses. * p < .05. ** p < .001. Table 2. Descriptive Statistics for Study Variables across Countries. Colombia Italy Jordan Philippines Thailand United States N 100 194 113 103 101 273 Age T1 M ( SD ) 9.70 (0.67) 10.41 (0.71) 10.33 (0.47) 10.11 (0.48) 10.35 (0.62) 10.60 (0.68) Gender (% male) 50.8 50.70 52.60 50.80 50.80 51.40 HDI T1 0.73 0.88 0.73 0.67 0.74 0.92 Family Socioeconomic Status 0.00 (0.91) -0.01 (0.89) -0.02 (0.69) 0.00 (0.86) -0.02 (0.84) -0.04 (0.89) Prosocial Behavior T1 M ( SD ) 2.54 (0.43) 2.50 (0.38) 2.40 (0.37) 2.30 (0.38) 2.27 (0.40) 2.55 (0.37) Prosocial Behavior T2 M ( SD ) 2.51 (0.43) 2.49 (0.39) 2.36 (0.38) 2.39 (0.36) 2.42 (0.40) 2.55 (0.35) Prosocial Behavior T3 M ( SD ) 2.46 (0.36) 2.35 (0.43) 2.71 (0.40) 2.77 (0.30) 2.64 (0.42) 2.73 (0.39) School Performance T1 M ( SD ) 3.25 (0.53) 3.31 (0.41) 3.62 (0.49) 3.28 (0.53) 3.18 (0.35) 3.39 (0.49) School Performance T2 M ( SD ) 3.15 (0.54) 3.19 (0.43) 3.55 (0.58) 3.31 (0.49) 3.17 (0.42) 3.36 (0.53) School Performance T3 M ( SD ) 3.34 (0.56) 3.14 (0.42) 3.48 (0.75) 3.28 (0.55) 3.18 (0.42) 3.40 (0.52) Open in a new tab Results of the Unconditional RI-CLPM Before responding to our research questions, we established the best model to explore longitudinal associations between prosocial behavior and school performance. We compared the unconstrained model with all parameters freely estimated with a constrained model, in which the bidirectional associations at the between-level, carry-over, spill-over, and temporal dynamics paths were simultaneously constrained to be equal over time. The fully constrained model, in which all paths were fixed to be equal, showed an acceptable fit (χ 2 (6) = 14.697, p = .02, CFI = .993, TLI = .982, RMSEA = .040 [90% CI: .014, .066], SRMR = .048) but was statistically different (Δχ 2 (5) = 14.425, p < .05) from the unconstrained model (χ 2 (1) = 0.176, p = .675, CFI = 1.000, TLI = 1.000, RMSEA = .000 [90% CI: .000, .066], SRMR = .004). Inspection of Modification Indexes (MI) suggested freely estimating the carry-over path of prosocial behavior from T2 to T3 (MI = 6.073), indicating that the carry-over effect of prosocial behavior from 13- to 16-year-olds differs over time. The final partly constrained model showed a good fit to the data (χ 2 (5) = 9.927, p = .077, CFI = .996, TLI = .988, RMSEA = .033 [90% CI: .000, .063], SRMR = .046) and was retained because of the lack of statistical significance in the Δχ 2 compared to the freely estimated model (Δχ 2 (4) = 9.713, p = .05). All standardized parameters of the unconditional model are depicted in Figure 1 . Figure 1. Open in a new tab Results of the unconditional RI-CLPM Note. RI_PB= Prosocial Behavior; RI_SP=Random-Intercept of School Performance; w_PB= Prosocial behavior at the within-level; w_SP= School Performance at the within-level; T1= Time1 (M age =10); T2= Time 2 (M age =13); T3= Time 3 (M age =16). Solid lines and bold numbers refer to significant paths. * <.05, **<.001 Are stable individual differences in prosocial behavior and school performance related to each other? Results of the RI-CLPM revealed that, at the between-level, a positive association emerged between prosocial behavior and school performance during the transition to adolescence (β = .417, p < .001). Thus, children who reported higher prosocial behavior were also those who, in general, performed better at school than their counterparts over time. Are fluctuations from the stable level of prosocial behavior associated with higher-than-expected levels of adolescents’ school performance at each time point? At the within-level, temporal dynamics paths were statistically significant at T1 ( r = .163, p < .05), T2 ( r = .114, p < .05), and T3 ( r = .104, p < .05), indicating that being more prosocial than usual is positively associated with performing better than usual at school, and vice versa. Thus, those children who showed a peak in prosocial behavior from their stable level at a specific time point showed a simultaneous increase in their performance at school than usual. Are fluctuations from the stable level of prosocial behavior associated with higher-than-expected levels of children’s school performance at a subsequent time point, and vice versa? To respond to our third research question, we examined spill-over effects. Results showed that spill-over associations between prosocial behavior and school performance were not statistically significant, evidencing that a previous peak in prosocial behavior did not relate to children’s fluctuations in school performance at the subsequent time point, and a prior peak in school performance did not influence subsequent fluctuations in prosocial behavior. These results did not support a predictive association between fluctuation of prosocial behavior and school performance during the transition to adolescence. Results of the Conditional RI-CLPM: Effects of Time-Invariant Predictors Once the unconditional model was established, we implemented a conditional model in which the observed prosocial behavior and school performance variables were regressed on HDI, gender, and family SES one at a time. Subsequently, we tested for each time-invariant predictor a fully constrained model (i.e., in which all regression paths were constrained to be equal across time) with a model in which all paths were freely estimated to determine whether each predictor differently influences prosocial behavior or school performance across time points. All regression coefficients of the conditional model are summarized in Table 3 . Table 3. Coefficients of the Conditional RI-CLPM for Relations between Prosocial Behavior (PB) and School Performance (SP), with Time-Invariant Predictors of HDI, Gender, and Family SES. b β SE p RI-PB ↔ RI-SP .020 .348 .006 < .05 Carry-Over effects w_PB (T1) → w_PB (T2) .158 .165 .066 < .05 w_PB (T2) → w_PB (T3) .074 .064 .076 .335 w_SP (T1) → w_SP (T2) .374 .309 .111 < .05 w_SP (T2) → w_SP (T3) .374 .369 .111 < .05 Spill-Over effects w_PB (T1) → w_SP (T2) .011 .012 .038 .782 w_PB (T2) → w_SP (T3) .011 .011 .038 .782 w_SP (T1) → w_PB (T2) .061 .048 .064 .345 w_SP (T2) → w_PB (T3) .061 .050 .064 .345 Temporal Dynamics w_PB (T1) ↔ w_SP (T1) .014 .149 .006 < .05 w_PB (T2) ↔ w_SP (T2) .011 .112 .004 < .05 w_PB (T3) ↔ w_SP (T3) .011 .097 .004 < .05 Time-invariant predictors HDI → PB (T1) .736 .178 .109 < .001 HDI → PB (T2) .736 .184 .109 < .001 HDI → PB (T3) -.277 -.062 .154 .072 HDI → SP (T1) .070 .014 .154 .648 HDI → SP (T2) .070 .013 .154 .648 HDI → SP (T3) .070 .013 .154 .648 Gender → PB (T1) .129 .164 .019 < .05 Gender → PB (T2) .129 .169 .019 < .05 Gender → PB (T3) .129 .152 .019 < .05 Gender → SP (T1) .076 .078 .029 < . 001 Gender → SP (T2) .076 .073 .029 < . 001 Gender → SP (T3) .076 .072 .029 < . 001 SES → PB (T1) .035 .075 .011 < .05 SES → PB (T2) .035 .077 .011 < .05 SES → PB (T3) .035 .070 .011 < .05 SES → SP (T1) .205 .359 .016 < .001 SES → SP (T2) .205 .337 .016 < .001 SES → SP (T3) .205 .335 .016 < .001 Open in a new tab Note. Unstandardized (b) and Standardized (β) regression coefficient, standard error (SE), and p-value ( p ) of b are reported. RI-PB= Random-Intercept of Prosocial Behavior; RI-SP= Random-Intercept of School Performance; w_PB= within-level of Prosocial Behavior; w_SP= within-level of School Performance; T1= Time 1 (10-year-old); T2= Time 2 (13-year-old); T3= Time 3 (16-year-old); HDI and SES (Socioeconomic Status) were centered on the grand mean. Gender was coded 0 for boys and 1 for girls. Regarding HDI, the full constrained model (χ 2 (9) = 49.218, p < .001, CFI = .987, TLI = .971, RMSEA = .070 [90% CI: .051, .089], SRMR = .056) differs (Δχ 2 (4) = 39.687, p < .001) from the unconstrained model (χ 2 (5) = 9.989, p = .076, CFI = .998, TLI = .985, RMSEA = .033 [90% CI: .000, .063], SRMR = .042). Inspection of MI indicated to freely estimated the over time constraint of HDI on prosocial behavior at T3 (MI = 33.855), resulting in a final model that did not differ from the unconstrained model (Δχ 2 (3) = 3.811, p = .283) and that showed a good fit to our data (χ 2 (8) = 13.800, p = .087, CFI =.996, TLI =.989, RMSEA = .028 [90% CI: .000, .052], SRMR = .044). Results indicated that HDI predicts only prosocial behavior scores at ages 10 and 13. Higher HDI scores were associated with higher levels of prosocial behavior at these two time points, indicating that, from late childhood to the beginning of adolescence, living in a country characterized by higher long and healthy life, expected years of schooling and mean years of schooling, and gross national income per capita is positively associated with the enactment of other-oriented behaviors. Regarding gender (0=boys and 1=girls), the full constrained model (χ 2 (8) = 22.754, p = .030, CFI = .993, TLI = .984, RMSEA = .031 [90% CI: .010, .051], SRMR = .041) did not differ (Δχ 2 (4) = 9.443, p = .050) from the unconstrained model (χ 2 (8) = 13.289, p = .102, CFI = .996, TLI = .988, RMSEA = .027 [90% CI: .000, .051], SRMR = .040). As summarized in Table 2 , girls tended to be more prosocial and scored higher in school performance than boys. Regarding family SES, the full constrained model (χ 2 (16) = 29.747, p = .019, CFI = .991, TLI = .982, RMSEA = .031 [90% CI: .012, .048], SRMR = .044) was retained because it did not statistically differ (Δχ 2 (4) = 2.622, p = .623) compared to the freely estimated model (χ 2 (12) = 27.010, p = .008, CFI = .991, TLI = .974, RMSEA = .038 [90% CI: .018, .057], SRMR = .041). As reported in Table 2 , higher SES positively predicts prosocial behavior over time. Moreover, during the transition to adolescence, those students who grow up in families with higher economic status perform better at school. Introducing HDI, child gender, and family SES as time-invariant predictors did not alter the strength of the positive between-person and within-person temporal dynamic associations between prosocial behavior and school performance in the transition to adolescence. Discussion The present study extends prior work by providing a longitudinal analysis of the between- and within-person associations of adolescents’ reports of their prosocial behavior and mothers’ and fathers’ reports of their children’s school performance over six years, representing the transition to adolescence (i.e., from 10 to 16 years of age). Overall, results showed significant positive associations between prosocial behavior and school performance at the between-person level, implying that, on average, children with a higher predisposition to enact other-oriented behaviors were also more likely generally to perform better at school and, in turn, children with higher school performance also tended to enact more prosocial behaviors during the transition to adolescence. Above and beyond the between-person association, at the within-person level, we found significant temporal dynamic associations, indicating that individuals’ fluctuations from their stable level of prosocial behavior are associated with higher-than-expected levels of adolescent school performance at each time point. However, we did not find significant spill-over effects, meaning that individuals’ fluctuations from their usual level of prosocial behavior at a given time point did not predict subsequent higher-than-expected levels of school performance, and vice versa. Regarding our first aim, the results about stable individual differences associations between prosocial behavior and school performance align with previous cross-sectional ( Emagnaw & Hong, 2018 ; Wentzel, 1993 ) and longitudinal ( Caprara et al., 2000 ; Carlo et al., 2018 ; Chen et al., 1997 ; Guo et al., 2018 ), evidencing a positive cross-informant correlation between the time-invariant (stable) component of prosocial behavior and the time-invariant (stable) part of school performance over the transition to adolescence. Thus, it is plausible that consistent experiences of school success encourage adolescents to invest more time in building positive social relationships, thereby increasing their opportunities to behave prosocially ( Christenson et al., 2012 ). At the same time, prosocial children are more likely to build better relationships with classmates and teachers, which in turn results in greater school engagement and achievement over time compared with their less prosocial peers ( Hammond et al., 2023 ). Moreover, at the within-person level, we found that higher-than-expected level of prosocial behavior is positively correlated with a higher-than-expected level of school performance at the same time point, suggesting that there a peak in prosocial behavior is associated with simultaneous peak in school performance at each stage of adolescence. However, our results do not provide evidence for spill-over associations at the within-person level. Despite the lack of previous studies concerning the longitudinal association between prosocial behavior and school performance at the within-person level, some interpretations can be made. First, given that prosocial behavior and school performance have high rank-order stability across time ( Eisenberg et al., 2002 ; Nantel-Vivier et al., 2009 ; Putnick et al., 2015 ), the stable components of the random intercepts may absorb the small degree of change at the within-person level. Consequently, it may be more difficult to capture how fluctuating levels of children’s prosocial behavior relate to future fluctuations in school performance, and vice versa (Adachi & Willoughby, 2015). Moreover, other studies adopting the RI-CLPM showed that prosocial behavior was associated with different outcomes (e.g., empathy, Carrizales et al., 2021 ; internalizing, Zondervan-Zwijnenburg et al., 2022 ) only at the between-person level, leaving open the question about what an optimal time interval is to investigate what is stable and what varies in prosocial behavior over time. In fact, the best time interval to detect spill-over effects may depend on the phenomenon under study ( Hamaker, 2023 ). Second, other factors may interfere with this prospective relation. For instance, prosocial behavior enhances school performance via school climate and relationships with teachers and classmates ( Bergin, 2014 ; Luengo Kanacri et al., 2017 ; Wentzel, 2009 ). Also, self-efficacy beliefs ( Carlo et al., 2018 ), cognitive self-control ( Normandeau & Guay, 1998 ), greater capacity to organize oneself for learning, school engagement ( Li et al., 2025 ), and positive emotion ( Reschly et al., 2008 ) influence the relation between prosocial behavior and school performance in the transition from late childhood to adolescence. Thus, significant spill-over effects at the within-person level may emerge when other mediating factors are considered. Regarding the second aim, we found that the associations between prosocial behavior and school performance are not altered by the Human Development Index, meaning that this relation is maintained while taking into account the diverse socioeconomic contexts considered in the present study. Although previous meta-analytic findings evidenced consistent associations between conduct problems and poor performance at school in the majority and minority world (see Sánchez de Ribera et al., 2019 ), our study advanced previous research by focusing on positive other-oriented behaviors. Our results shed light on the positive reciprocal associations between prosocial behavior and school performance in multiple cultural contexts, including experiences from the majority world. Existing evidence on the beneficial role of prosocial behavior on high performance at school mostly derives from minority world countries that, as shown by numerous international reports ( OECD, 2019 ; UNICEF, 2018 ), are highly similar in educational indicators, such as equitable and quality access to primary education, percentage of youth and adults who achieve relevant academic skills, and the supply of human and infrastructure resources to educational contexts. Although the majority world shows an overall lower level of educational indicators than the minority world ( OECD, 2019 ; UNICEF, 2018 ), our results support the generalizability of stable associations and within-time fluctuations between prosocial behavior and school performance across six countries, indicating the importance of sustaining both other-oriented behaviors and performance at school for increasing the likelihood of better educational achievement and positive social adjustment worldwide. Among guidelines from the United Nations (2019), education quality worldwide should be raised through free and compulsory education, increasing teacher hiring, reinforcing school infrastructure, and access to digital resources at school. However, legislative and economic actions alone may be insufficient to ensure school success ( Godfrey et al., 2012 ). Fostering conditions for academically successful youth needs actions at different levels, including socioemotional adaptation of children within the school contexts. Our results support this position, considering that, controlling for HDI, prosocial behavior remains associated with better performance at school during the adolescence. The present study has several strengths. First, it includes a large international sample from six countries, offering insight into the majority world, which is not frequently considered in the prosocial literature. Second, the use of different informants for the variables of interest (i.e., self-reported prosocial behavior, mothers’ and fathers’ report of their children’s school performance) reduces common single-informant bias ( McCrae, 2018 ) and the halo effect (i.e., talented children at school were also perceived as prosocial by the same informants; Bergin, 2014 ), increasing the reliability of our results. Third, we adopted a longitudinal design covering the transition to adolescence over six years and implemented a novel RI-CLPM that allowed us to test the cascade model for the association between prosocial behavior and school performance, by capturing both interindividual variability (between-person differences) and intraindividual difference over time (within-person differences). Fourth, our study spans a developmental window of the transition to adolescence in which social and academic development are crucial. During this transition, many biological, cognitive, and socioemotional changes occur that can affect youth’s future adjustment. Regarding social development, this developmental period is characterized by an increasing time spent cultivating peer relationships outside the family context, and adolescents increasingly feel a need for autonomy and freedom that, in turn, influence parent-adolescent relationships. Regarding school, children are increasingly exposed to curricular demands that are relevant to their academic growth, and how they cope with these demands impacts their later career and identity development ( Steinberg & Morris, 2001 ). Despite these strengths, some limitations should be noted. The present study relied on a brief self-report measure of prosocial behavior that reflects a general tendency to help, comfort, and share with others. A growing body of studies highlights the complexity and several nuances of prosocial behavior (see Eisenberg & Spinrad, 2014 ) associated, for example, with the situation (e.g., public or anonymous; Carlo et al., 2003 ) or the relation with the recipient (e.g., toward family members, friends, or strangers; Padilla-Walker et al., 2018 ). Moreover, previous studies have highlighted the importance of considering multiple informants and observational measures in the study of prosocial behavior ( Whitcomb, 2017 ). Also, one should consider recent advances that point out the necessity to identify new measures of prosocial behavior that may capture the diverse forms of prosocial behavior in the majority world ( Armstrong-Carter & Telzer, 2021 ; Draper et al., 2023 ) and in the school context ( Hammond et al., 2023 ). Thus, future studies might deepen the exploration of these associations using observational and other informant measures and develop more appropriate measures for understudied contexts. In addition, although we have established the longitudinal and across-cultures measurement invariance of the prosocial behavior measure, ensuring meaningful comparisons over time and across countries, our measure was slightly below the acceptable level of reliability, which may reflect the need to use more items to capture the multidimensional nature of prosocial behavior (e.g., Luengo Kanacri et al., 2021 ). Last, school performance was assessed using mothers’ and fathers’ evaluations of their children’s academic achievement. Despite the strength of the two informants and the high reliability of the construct, future studies might include school grades from official transcripts to test these associations with a measure reflecting academic assessment. Conclusions and Implications The present findings advance understanding of the relations between prosocial behavior and school performance in diverse cultural contexts. Findings yielded similar relations across the six countries, demonstrating that children’s ability to engage in socially competent actions goes along with successful school experiences and persists through the transition to adolescence. However, fluctuations in prosocial behavior and school performance did not predict their subsequent temporary levels, leaving open the question of how temporary changes in prosocial behavior and school performance during adolescence may influence future peaks in these domains. Thus, additional multicultural studies are needed to gain deeper insight into the extent to which temporary changes in adolescent social and academic functioning contribute to long-term development. Supplementary Material Supplementary Material NIHMS2078473-supplement-Supplementary_Material.pdf (268KB, pdf) Funding statement. This research was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development grant RO1-HD054805. Footnotes Ethics approval statement. 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