05. Children and Youth at Risk and Urban Education
Poster
Developing a Digital Mental Health Program for Adolescents: Key Takeaways from Digital-based Programs
Igor Peras1, Manja Veldin1, Maša Vidmar1, Michaela Wright2, Franziska Reitegger3, Barbara Gasteiger-Klicpera2,3
1Educational Research Institute, Slovenia; 2Research Center for Inclusive Education Graz, Austria; 3University of Graz, Austria
Presenting Author: Peras, Igor
Adolescence is characterized as a stage of human development in which individuals attain and develop the skills and competencies necessary for becoming productive and functioning adults (Barker, 2007). This critical point in human development is characterised by changes (such as physical and socio-emotional), as well as social and cognitive development (Slater & Bremner, 2017). Due to the mentioned changes and development undergone, adolescents can be at risk for mental health concerns (e.g., anxiety). WHO (2021) reports that one in seven adolescents aged between 10 and 19 experiences a mental health concern which is often left untreated. Thus, prevention programs offer opportunities for supporting the mental health of adolescents. By increasing their mental health literacy (Jorm, 2012) we can equip them with the knowledge of recognizing and properly responding to mental health issues in themselves and others. By developing effective prevention programs for adolescents we can mitigate at least some of the mental health issues that spill over from adolescence to adulthood, as for example many anxiety and depression-related disorders have their onset in adolescence (Gibb et al., 2010; Kim-Cohen et al., 2003). As adolescents are the most active users of digital devices (UNICEF, 2017) it is reasonable to focus on programs that can be accessed on digital devices (e.g., computers, smartphones) as this builds on their willingness to use such devices (Gibson & Trnka, 2020) and enable the development of interventions that are aligned with their habits.
The need for digital prevention programs that can be implemented independently of time, geographical or personnel restrictions has been further exacerbated by the COVID-19 pandemic (Kaess et al., 2021). For example, Ravens-Sieberer et al. (2022) found more mental health problems and higher anxiety in children and adolescents during the pandemic. Moreover, authors (e.g., Babbage et al., 2018; Kaess et al., 2021) agree that there is a clear need and value for such programs/interventions, but caution has to be put in place as digital resources for mental health are not always formally evaluated or evidence-based in their development (Domhardt et al., 2021; Torous et al., 2019).
In order to support the development of a digital mental health tool for adolescents, the present paper builds on a previously conducted systematic review (Wright et al., in press) and aims to provide recommendations for creating a digital tool for the mentioned age group. The tool is being developed as a part of the ongoing Erasmus project me_HeLi-D (Mental Health Literacy and Diversity. Enhancing Mental Health and Resilience through digital Resources for Youth). In line with the goals of the project, the following contribution focuses on existing mental health programs with a digital/online component that focuses on the mental health of adolescents (aged between 11 to 18 years) and the following domains of mental health: mindfulness, resilience, and help-seeking. We are particularly interested in the content, design, and activities of existing evidence-based programs in order to inform the development of our own digital program with recommendations that are based on findings and good practices from existing programs.
In the present paper, we aim to answer three research questions: 1) Which evidence-based mental health programs/interventions with a digital component have been shown to be effective in supporting the mental health of adolescents aged 11 to 18 years? 2) What were the contents of effective mental health programs/interventions? 3) How were effective mental health programs/interventions designed?
Methodology, Methods, Research Instruments or Sources UsedA systematic literature search was conducted in the databases PsychInfo, PubMed, and The Cochrane Library. The search aimed to identify preventive interventions with a digital component that promote mental health in general, as well as well-being, mental health literacy, resilience, help-seeking behavior, and mindfulness. The following inclusion criteria were implemented: participants (children/adolescents aged between 11 and 18 years), intervention (preventive interventions with >= 50% digital delivery), study type (quantitative or mixed-methods studies), study design (controlled studies-CT with pre-post comparison), and publication (peer-reviewed; published between 2000 and 2021). A detailed description of the methodology (search terms and results according to PRISMA recommendations, risk of bias assessment) is available in another publication (Wright et al., in press).
The systematic literature search identified 27 studies matching the inclusion criteria. In order to further evaluate the interventions according to our research questions, we conducted a backward search by also identifying papers that are connected to the interventions (i.e., protocol papers, papers focused on different results of the same interventions), as well as accessing the interventions (applicable, if the intervention was accessible online). This approach enabled a comprehensive overview of how the interventions were created and presented to students.
The following data was extracted from the interventions: design of the intervention (e.g., number of sessions, length of sessions, number of modules), content of intervention (e.g., which topics were included in the programs), and activities (e.g., quizzes, reflective writing, games, mood ratings, mindfulness exercises).
Conclusions, Expected Outcomes or FindingsFrom the 27 studies matching the criteria for inclusion we focused on 20 studies that showed significant effects of digital interventions. Specifically, 15 studies reported significant effects favouring the intervention group (between-group effects), 3 reported significant within-group effects but no between-group effects and 2 studies that incorporated an alternative intervention showed both conditions (digital intervention and alternative intervention) led to significant improvements in outcome measures with no between-group effects.
In general, results showed that digital interventions differ according to content, design, and activities. For example, with regard to the design, interventions can range from a single-session digital intervention (Osborn et al., 2020) to a self-paced intervention with various modules in which students are free to choose activities (O’Dea et al., 2019). In terms of content, digital mental health interventions focused on various topics, such as mindfulness, problem-solving, goal-setting and skills development.
Based on these results, recommendations for developing our own digital mental health intervention for students aged 12 to 15 years (target group in me_HeLi-D) are formulated (e.g. Digital mental health programs should include elements of gamification in order to engage, motivate and capture the attention of students in supporting their learning). In the presentation, these recommendations will be presented as key take-aways that researchers and developers are encouraged to keep in mind when developing digital interventions that will be formally evaluated. In the me_HeLi-D project, the recommendations will be further assessed with input from students in an iterative content and design development process (Thabrew et al., 2018) in order to tailor the digital intervention to the needs and preferences of the relevant stakeholders (i.e. adolescents).
ReferencesBarker, G. (2007). Adolescents, social support and help-seeking behaviour. World Health Organization. https://apps.who.int/iris/handle/10665/254500
Domhardt, M. et al. (2021). Mobile-based interventions for common mental disorders in youth: A systematic evaluation of pediatric health apps. Child and Adolescent Psychiatry and Mental Health, 15(1), 49.
Gibb, S. J. et al. (2010). Burden of psychiatric disorder in young adulthood and life outcomes at age 30. British Journal of Psychiatry, 197(2), 122–127. https://doi.org/10.1192/bjp.bp.109.076570
Gibson, K., & Trnka, S. (2020). Young people’s priorities for support on social media: “It takes trust to talk about these issues.” Computers in Human Behavior, 102, 238–247.
Jorm, A. F. (2012). Mental health literacy: Empowering the community to take action for better mental health. American Psychologist, 67(3), 231–243.
Kaess, M. et al. (2021). Editorial Perspective: A plea for the sustained implementation of digital interventions for young people with mental health problems in the light of the COVID‐19 pandemic. Journal of Child Psychology and Psychiatry, 62(7), 916–918.
Kim-Cohen, J. et al. (2003). Prior Juvenile Diagnoses in Adults With Mental Disorder: Developmental Follow-Back of a Prospective-Longitudinal Cohort. Archives of General Psychiatry, 60(7), 709.
O’Dea, B. et al (2019). Evaluating a Web-Based Mental Health Service for Secondary School Students in Australia: Protocol for a Cluster Randomized Controlled Trial. JMIR Research Protocols, 8(5), e12892.
Osborn, T. L. et al. (2020). Single-Session Digital Intervention for Adolescent Depression, Anxiety, and Well-Being: Outcomes of a Randomized Controlled Trial With Kenyan Adolescents.
Ravens-Sieberer, U. et al. (2022). Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany. European Child & Adolescent Psychiatry, 31(6), 879–889.
Slater, A., & Bremner, J. G. (Eds.). (2017). An introduction to developmental psychology (Third edition). John Wiley & Sons Inc.
Thabrew, H. et al. (2018). Co-design of eHealth Interventions With Children and Young People. Frontiers in Psychiatry, 9, 481.
Torous, J. et al. (2019). Towards a consensus around standards for smartphone apps and digital mental health. World Psychiatry, 18(1), 97–98.
UNICEF (Ed.). (2017). Children in a digital world. UNICEF.
WHO. (2021). Adolescent mental health. https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health
Wright, M. et al. (in press). Interventions With Digital Tools for Mental Health Promotion Among 11-18 Year Olds: A Systematic Review and Meta-Analysis. Journal of Youth and Adolescence.
05. Children and Youth at Risk and Urban Education
Poster
Factors Predicting Sense of Belonging to School among Students with Migrant Background in Slovenia, Portugal and Hungary
Ana Mlekuž, Klaudija Šterman Ivančič
Educational Research Institute, Slovenia
Presenting Author: Mlekuž, Ana
Feelings of association with a particular cultural group and consequently sense of belonging to it is one of the important factors in immigrant adaptation process which affects both sociocultural adaptation together with academic achievement and psychological adaptation (Phinney et al, 2001). School is usually the first socio-cultural institution in which students with migrant background are included. Consequently, school environment also provides these students with an introduction to host country’s social, political and cultural values and attitudes, which fosters their sense of belonging to wider host society. It can be concluded that sense of belonging to school is a precondition of (successful) adaptation of migrant students in school environment, which foretells the (successful) adaptation to wider society. Additionally, sense of belonging to school is connected to cognitive and psychosocial functioning (Aderman & Freeman, 2004). Namely, higher sense of belonging to school is connected to higher intrinsic motivation and higher academic achievement, which is linked to more favourable occupational possibilities. Thus, it can be concluded that sense of belonging to school plays an important role in successful adaptation of students with migrant background (Chui et al., 2012).
In order to determine the factors influencing the development of sense of belonging to school, El Zaatari and Maalouf (2022) argue that Bronfenbrenner’s Ecological Systems Theory can provide a comprehensive basis. The Bronfenbrenner’s Ecological Systems Theory (Bronfenbrenner, 1979) views child development as a complex system of relationships affected by multiple levels of the surrounding environment, from immediate settings of family and school to broad cultural values, laws, and customs. The Bronfenbrenner’s model puts the individual (student) and their characteristics (biological and dispositional), which affect the interactions with their environment (e.g. peers, parents, teachers, school as an institution etc.) in the center of the model. Student however exists in several systems of interconnected relationships, roles, activities and settings (Shelton, 2019). The first system – microsystem, focuses on students’ proximal relationships with their peers, family, teachers, friends. The second system is mesosystem which includes distal relationships, which include school climate, school policies, rules, practices etc. In this system students’ individual microsystems are interconnected and influence each other (Saab, 2009). Then exosystem, macrosystem and chronosystem follow.
The main focus of this poster is to examine the differences in feeling of belonging to school and factors affecting it based on Bronfenbrenner's Ecological Systems Theory on the individual, micro- and mesosystem level among Slovenian students with migrant background included in the PISA sample. The decision to only analyse the first two systems is based on the premise, that they are most influential to child’s development. Additionally, the poster compares Slovenian data to data from two other EU countries, namely Portugal and Hungary. The selection of these two countries was based on the Migrant Integration Policy Index assessment of responsiveness of the educational systems to the needs of immigrant children, where Portugal represents a highly responsive educational system and Hungary represents a non-responsive educational system.
Using the PISA 2018 data the paper firstly examines the differences in feeling of belonging as one of the prerequisites of successful adaptation of immigrant students (first- and second-generation) and then analyses and compares the individual factors, namely, resilience and cognitive flexibility/adaptablity, which are proved to be linked to positive and successful adaptation of migrants (Albuquerque & Bueno, 2020), and factors of micro- (teacher support in test language lesson, parental support) and mesosystems (discriminative school climate, disciplinary climate) which predict the feeling of belonging to school. The overall goal of the paper is to determine which individual and ecological system factors predict the feeling of belonging to school in the three chosen countries.
Methodology, Methods, Research Instruments or Sources UsedParticipants:
The current study analyses three PISA 2018 representative migrant student samples from Slovenia (Nfirst-generation = 213; Nsecond-generation = 200; Ntotal sample = 5.088), Portugal (Nfirst-generation = 104; Nsecond-generation = 172; Ntotal sample = 4.902), Hungary (Nfirst-generation = 38; Nsecond-generation = 54; Ntotal sample = 4.253). The PISA focuses on a sample of 15-year-old students. For purposes of this poster, only subsamples of first-generation and second-generation migrant students respectively are used.
Instruments and included variables:
Each sampled student answered a background questionnaire, where scales were derived from.
Students’ immigrant background was used as a grouping variable (first-generation immigrant students: foreign-born students whose parents are also foreign-born; second-generation immigrant students: born in the country of destination, while their parents are foreign-born).
The scale of sense of belonging to school was measured with six items using a four-point Likert scale.
The scales for individual level and micro- and mesosystem were attributed to Bronfenbrenner's Ecological Systems based on definitions as follows:
Individual level:
Resilience (five items using four-point Likert scale)
Cognitive flexibility/adaptability (student’s flexibility/adaptability in dealing with challenging or difficult situations, which may include intercultural situations, measured with six items using a five-point Likert scale)
Microsystem:
Teacher support in test language lessons (four items using four-point Likert scale)
Parental support is understood as perceived emotional support from students’ parents (three items using four-point Likert scale)
Mesosystem:
Discriminative school climate measures the absence of teachers’ stereotypes, prejudice, and discrimination towards migrants (four items using four-point Likert scale)
Disciplinary climate in the test language classroom (five items using four-point Likert scale)
Sampling and procedure:
A two-stage stratified sampling design was used. In the first stage schools from the pool of all schools where 15-year-olds are enrolled are sampled. In the second stage, 42 (or fewer) students within each school included were sampled. These sampling procedures ensured the representativeness of the test population. It took approximately 35 minutes for students to respond to the student background questionnaire.
Statistical analyses:
Firstly, descriptive statistics were used, namely correlations in order to test for multicollinearity. Secondly, differences in sense of belonging to school between the student groups per country were calculated. Finally, linear regression was used in order to determine which factors predict a sense of belonging to school per student group per country. Data were analyzed using the statistical program IEA IDB Analyzer (Version 5.0.17) due to the two-stage sampling in the study (the program uses individual students and sample weights).
Conclusions, Expected Outcomes or FindingsResults show that there are significant differences in sense of belonging to school between first- and second-generation migrant students in Slovenia and Portugal. In both countries first-generation migrant students assess their sense of belonging to school significantly lower than second-generation migrant students. There is no statistically significant difference in sense of belonging between the two student groups in Hungary.
In Slovenia resilience and parental support proved to be significant predictors of sense of belonging to school for first-generation migrant students, whereas cognitive flexibility/adaptability and discriminative school climate proved to be significant predictors for second-generation migrant students. For comparison, in Hungary cognitive flexibility/adaptability and parental support proved to be significant predictors of sense of belonging for first-generation migrant students, while only resilience proved to be statistically significant predictor for second-generation migrant students. On the other hand, in Portugal discriminative school climate is significant predictor of sense of belonging for first-generation migrant students, while both individual factors and teacher support in test language lessons are significant predictors of sense of belonging for second-generation migrant students.
The findings are in line with previous studies which also found parental and teacher support to be positively linked to sense of belonging to school (Chiu et al., 2016). Moreover, the results show that discriminative school climate hinders successful adaptation of migrant student in schools, which is consistent with results of research review by Dimitrova and colleagues (2017), where it was concluded that perceived discrimination is one of the three factors connected to migrant students adaptation.
Since it can be observed that students with migrant background report on lower levels of sense of belonging to school the results of the poster can serve as basis for the design of targeted policies and interventions to support students with migrant background in their adaptation to the school environment.
ReferencesAlbuquerque, E. S. G., & Bueno, J. M. H. (2020). The Effect of Resilience and Cognition on (Im) Migrant Students’ Academic Adaptation. Psico-USF, 25, 223-234.
Anderman, L. H., & Freeman, T. (2004). Students’ sense of belonging in school. In M. L. Maehr & P. R. Pintrich (Eds.), Advances in motivation and achievement: Vol. 13. Motivating students, improving schools: The legacy of Carol Midgley (pp. 27–63). Greenwich, CT: Elsevier
Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Harvard University Press.
Chiu, M. M., Chow, B.W.-Y., McBride, C., & Mol, S. T. (2016). Students’ sense of belonging at school in 41 countries: Cross-cultural variability. Journal of Cross-Cultural Psychology, 47(2), 175–196.
Chiu, M. M., Pong, S.-L., Mori, I., & Chow, B.W.-Y. (2012). Immigrant students’ emotional and cognitive engagement at school: A multilevel analysis of students in 41 countries. Journal of Youth Adolescence, 41(11), 1409–1425. https:// doi. org/ 10. 1007/ s10964- 012- 9763-x.
Dimitrova, R., Özdemir, S. B., Farcas, D., Kosic, M., Mastrotheodoros, S., Michałek, J., & Stefenel, D. (2017). Is there a paradox of adaptation in immigrant children and youth across Europe? A literature review. In R. Dimitrova (Ed.), Well-being of youth and emerging adults across cultures: Novel approaches and findings from Europe, Asia, Africa and America (pp. 261–298).
El Zaatari, W., & Maalouf, I. (2022). How the Bronfenbrenner Bio-ecological System Theory Explains the Development of Students’ Sense of Belonging to School?. SAGE Open, 12(4), 21582440221134089.
MIPEX. (2019). Migrant Integration Policy Index 2020 – Education. Accessed at https://www.mipex.eu/education
OECD. (2017). Student questionnaire for PISA 2018 - Main survey version. Accessed at https://www.oecd.org/pisa/data/2018database/CY7_201710_QST_MS_STQ_NoNotes_final.pdf
OECD. (forthcoming-a). Scaling procedures and construct validation of context questionnaire data. In OECD, PISA 2018 Technical Report. OECD Publishing. Accessed at https://www.oecd.org/pisa/data/pisa2018technicalreport/PISA2018_Technical-Report-Chapter-16-Background-Questionnaires.pdf
OECD. (forthcoming-b). Sample design. In OECD, PISA 2018 Technical Report. OECD Publishing. Accessed at https://www.oecd.org/pisa/data/pisa2018technicalreport/PISA2018%20TecReport-Ch-04-Sample-Design.pdf
Phinney, J. S., Horenczyk, G., Liebkind, K., & Vedder, P. (2001). Ethnic identity, immigration, and well-being: An interactional perspective. Journal of Social Issues, 57(3), 493–510. https://doi.org/10.1111/0022-4537.00225.
Saab, H. (2009). The school as a setting to promote student health and wellbeing. QSPACE.
Shelton, L. G. (2019). The Bronfenbrenner primer: A guide to Develecology. Routledge.
05. Children and Youth at Risk and Urban Education
Poster
The Applicability and Effectiveness of an Early Intervention Program Supporting School Readiness of Children Living in a Segregated Roma Settlement
Reka Kassai1,2, Zsofia K. Takacs3
1Institute of Education, ELTE Eötvös Loránd University, Budapest, Hungary; 2Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary; 3School of Health in Social Science, University of Edinburgh, United Kingdom
Presenting Author: Kassai, Reka
Cognitive aspects of school readiness upon entry to primary education is a strong predictor of later academic achievement (Duncan et al., 2007; Paro & Pianta, 2000). It is also found that young children from low socioeconomic status (SES) families lag behind their higher-SES peers in school readiness related skills, especially executive functions (that involves working memory, inhibition, and switching), which have a negative effect on their performance in school (Nayfeld et al., 2013; Hilferty et al., 2010). Empirical evidence showed that it is possible to support the development of these kind of abilities even in case of at-risk samples of children (Duncan et al., 2018; Takacs & Kassai, 2019), however, families living in poverty may have limited resources and knowledge about prevention and early intervention programs (Leseman & Slot, 2014; Lloyd, 2017). Thus, making these services accessible for at-risk samples is crucial but challenging. One of the most promising form of ensuring available interventions for these vulnerable families are home visiting programmes. These programmes can not only foster children’s cognitive skills directly but also nurture parenting skills of their caregivers, and improve their home environment (Corr et al., 2016; Welsh et al., 2014). The aim of the present study was to address these barriers and reduce inequality in school readiness by examining the feasibility and the effectiveness of a low-threshold early intervention for children living in poverty conducted by volunteer helpers. According to our hypotheses it is feasible to provide early intervention at children’s home even in an adverse environment. Additionally, we expect that, after a year of weekly intervention sessions, the intervention group will outperform the controls on school readiness related cognitive abilities like short-term memory and working memory skills.
Methodology, Methods, Research Instruments or Sources UsedThe intervention targeted preschool-aged children living in underprivileged neighborhood in a segregated roma settlement in Hungary. Following the assessment of the children’s individual needs and circumstances, trained volunteer helpers (mentors) visited the participating families at their homes once a week and provided age-appropriate playful sessions, the main focus of which was on the improvement of children’s cognitive and socioemotional skills. A session usually consisted of different actives for example educational games like puzzle or memory, arts and crafts to support fine motor movements, shared storybook reading to widen their vocabulary and improve language comprehension. However, the intervention programme also aimed to improve parenting skills of the caregivers by inviting them to participate in the sessions as much as they could, and provide feedback and time for consultation following each session. The mentors’ work were constantly supported and supervised by child development specialists (a psychologist and a special education teacher). The present data was collected for two consecutive academic years (year 1: 2020-2021, year 2: 2021-2022). As a measure of feasibility, we registered the number of participating children from the targeted age group living in the area, the ratio of successful and cancelled sessions, and the level of parental involvement. The children’s cognitive skills were measured by the Cognitive Profile Test (CPT; Gyarmathy, 2009) upon school entry. The results of the participants of the intervention group (n=16) were compared to a sample of children living in a similar roma settlement without such a home visiting programme (n=14) in a quasi-experimental design. The control group was matched to the participants in the intervention group by age, gender and SES.
Conclusions, Expected Outcomes or FindingsRegarding the feasibility of the intervention, during the first year 70% of the target group on the intervention site were involved in the programme, while in the second year we managed to involve more than 90% of the children. The ratio of the successful sessions were 75% in the first, and 67% in the second year. It should be noted that in the first years we had to suspend the program for 6 weeks due to the COVID-19 pandemic.
Regarding children’s cognitive skills, we focused on short-term memory and executive function related subtests of the CPT. A significant large effect were found on post-test both on the digit span t(27) = 2,15, p = .04, d=0.79 and the word span test t(27) = 2,46, p = .02, d=0.92, which suggests that the intervention had a positive effect on short-term memory skills. While there was a tendency for higher scores in the intervention than in the control group on the backward digit span and nonword repetition test, these differences were not significant. In sum, the home visit intervention was shown to be feasible in such adverse home environments and beneficial for children’s developing short-term memory, which is an important ability for reading skills (Haarmann et al., 2003). Surprisingly, the intervention did not affect children’s working memory skills.
ReferencesCorr, C., Santos, R. M., & Fowler, S. A. (2016). The components of early intervention services for families living in poverty: A review of the literature. Topics in Early Childhood Special Education, 36(1), 55-64.
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., ... & Japel, C. (2007). School readiness and later achievement. Developmental psychology, 43(6), 1428.
Duncan, R. J., Schmitt, S. A., Burke, M., & McClelland, M. M. (2018). Combining a kindergarten readiness summer program with a self-regulation intervention improves school readiness. Early Childhood Research Quarterly, 42, 291-300.
Gyarmathy, É. (2009). Kognitív Profil Teszt. Iskolakultúra, 19(3-4), 60-73.
Haarmann, H. J., Davelaar, E. J., & Usher, M. (2003). Individual differences in semantic short-term memory capacity and reading comprehension. Journal of Memory and Language, 48(2), 320-345.
Hilferty, F., Redmond, G., & Katz, I. (2010). The implications of poverty on children's readiness to learn. Australasian Journal of Early Childhood, 35(4), 63-71.
La Paro, K. M., & Pianta, R. C. (2000). Predicting children's competence in the early school years: A meta-analytic review. Review of educational research, 70(4), 443-484.
Leseman, P. P., & Slot, P. L. (2014). Breaking the cycle of poverty: challenges for European early childhood education and care. European Early Childhood Education Research Journal, 22(3), 314-326.
Lloyd, E. (2017). Early childhood education and care: Poverty and access. Perspectives from England. The SAGE Handbook of Early Childhood Policy. London: SAGE, 268-86.
Nayfeld, I., Fuccillo, J., & Greenfield, D. B. (2013). Executive functions in early learning: Extending the relationship between executive functions and school readiness to science. Learning and Individual Differences, 26, 81-88.
Takacs, Z. K., & Kassai, R. (2019). The efficacy of different interventions to foster children’s executive function skills: A series of meta-analyses. Psychological bulletin, 145(7), 653.
Welsh, J. A., Bierman, K. L., & Mathis, E. T. (2014). Parenting programs that promote school readiness. Promoting school readiness and early learning: The implications of developmental research for practice, 253-278.
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