08. Health and Wellbeing Education
Paper
Mental Health and Wellbeing Coordinators in Primary Schools – Outcomes From a Quasi-Experimental Study
Jon Quach1, Simone Darling2, Georgia Dawson1, Rachel Smith2, Frank Oberklaid2
1University of Melbourne, Australia; 2Murdoch Childrens Research Institute, Australia
Presenting Author: Quach, Jon
Objective
This paper presents findings from a quasi-experimental study to evaluate the Mental Health in Primary Schools program. We aimed to determine whether compared to matched comparison schools, primary schools that implemented the MHiPS intervention had:
- Improved Teacher outcomes related to their attitudes, confidence and skills in identifying and responding to the mental health and wellbeing of their students
- Increased school prioritisation of mental health and wellbeing
- Improved engagement with school and community mental health support.
Theoretical framework
In recent years there has been increasing international policy attention related to child mental health. This is timely and follows reports of worrying increases in mental health concerns in schools and increased presentations of children with mental health issues to medical services. The Report on the Second Australian Child and Adolescent Survey of Mental Health and Wellbeing (Lawrence et al., 2016) [4] found that the impact of mental health disorders on children’s education includes absenteeism, impaired functioning at school, and poorer academic performance compared to peers without mental health concerns. Left unaddressed, mental health challenges in childhood are related to increased school absenteeism, poorer peer relationships and increased risk of substance abuse and unemployment (Patel et al., 2007).
Schools are one setting where children can be supported in their development of mental health competencies, especially as some children require effective mental health support to succeed at school. Their success in adjusting emotionally and socially when young is a strong predictor of their adjustment into adulthood (Vogler, 2008). While there are effective interventions available to change this trajectory, the prevalence of childhood mental health continues to increase, with children not accessing help soon enough or for long enough (Tully, et.al., 2019). A range of barriers exist inhibiting children from accessing mental health services, including lack of parental knowledge, cost of treatment, stigma and lack of service availability (CCCH, 2006; CCCH, 2012; Rhodes, 2017). Schools have been responding to this by increasingly focusing on prevention and intervention, with many incorporating wellbeing into their values and vision (Allen, 2017).
The primary school period presents a unique opportunity to intervene early and modify the trajectory of many mental health issues and prevent progression to chronic conditions. The intervention in this study has been designed to leverage this developmental window and address the gaps in the school-based child mental health system by introducing the concept of a Mental Health and Wellbeing Coordinator (MHWC) role. The MHWC is an experienced qualified educator who will be an additional resource for the schools and will take up their role alongside participation in a comprehensive training program designed within an implementation science framework. The role and the training program combine to form the “MHWC model”, which aims to build mental health capacity within the school. The MHWC will act as the liaison between the school and community-based health and other community-based services. The role within schools involved:
- Receive evidence-based training around supporting the mental health needs of primary school students;
- Embed evidence-based training and professional development (Tier 1 practices & frameworks) across the school and build the capability of teaching and education support staff to better identify and support students with mental health issues;
- Support the referral pathway for students identified as requiring further assessment and intervention within the school or to external community-based services (the MHWC role will not involve providing 1:1 counselling support to students);
- Work proactively within school and community services
- Connect wellbeing initiatives across the school and be responsible for implementing whole-school approaches to mental health and wellbeing, including the social and emotional learning curriculum.
Methodology, Methods, Research Instruments or Sources UsedDesign: This paper will present findings from a quasi-experimental study involving 16 schools that participated in 2021 with 21 matched comparison schools.
Participants and sample size: 16 primary schools were recruited to participate in the program based on mental health need (through consultation with regional stakeholders and Incident Reporting Information System (IRIS) data), readiness (ensuring schools have the capacity and willingness to participate) and context diversity (including metropolitan, regional and rural contexts). 21 primary schools were recruited by the research team to participate as ‘business as usual’ comparison schools matched on sociodemographic characteristics (ie. ICSEA), school size (ie. the number of enrolments) and location (ie. metropolitan/regional/rural). Parents of students in Year 2 (2-8 years old) and Year 4 (9-10 years old) were approached to participate at the start of 2021 with a final sample of 686 participants. All school staff at participating schools were approached to participate, with 821 recruited.
Intervention:
The training aimed to increase their knowledge, skills, and attitudes to effectively focus on building the capacity of the whole school, working with individual teachers and the whole staff cohort. The training comprised three core modules: Mental Health Literacy; Supporting Needs; and Building Capacity as well as regular Communities of Practice
DATA SOURCES
Outcome data: Outcome data were collected across six-time points, being time 1 (2 months post allocation) and then 3, 5, 6, 10 and 17 months post allocation
Measures: School staff and parent-reported measures were chosen to measure proximal and distal outcomes that align with our intervention’s theory of change. School staff and parent-reported measures were chosen to measure proximal and distal outcomes that align with our intervention’s theory of change. The primary outcome was the School Mental Health Self-Efficacy Teacher Survey (SMH-SETS), with secondary measures capturing student mental health, staff mental health literacy, service use, stigma and implementation. Focus groups with stakeholders were also conducted. Interviews/focus groups with school staff and MHWC at intervention schools.
Statistical Analysis: Statistical analysis will follow standard methods for cluster randomized trials and the primary analysis will be by intention to treat. Multiple imputation will be conducted separately in the two arms using chained equations applied to all outcomes simultaneously, including baseline measures as auxiliary variables.
Conclusions, Expected Outcomes or FindingsThe outcome data from educators, school leadership and parents are currently being analysed and will be presented at ECER annual meeting.
This project is significant and innovative in that it:
• Evaluates the teacher and student outcomes of increasing school capacity to support the mental health and well-being of their students
• Tests the efficacy of a system-focused, whole-school mental health approach.
• Examines the sustainability of the whole school approach across two years, with data collected about teachers and students.
• Considers the implementation process, identifying for whom and under what conditions the intervention may be beneficial.
If our study demonstrates positive outcomes, we expect:
• The best evidence yet that whole school mental health and wellbeing intervention focused on improving teacher and school capacity, can improve key early implementation outcomes.
• A ready-to-use intervention that focuses on building teacher practice in primary school settings
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Krueger, R. A. (2014). Focus groups: A practical guide for applied research. Sage publications.
Lawrence, D., Hafekost, J., Johnson, S. E., Saw, S., Buckingham, W. J., Sawyer, M. G., Ainley, J., & Zubrick, S. R. (2016). Key findings from the second Australian child and Adolescent Survey of Mental Health and Wellbeing. Australian & New Zealand Journal of Psychiatry, 50(9), 876-886. https://doi.org/10.1177/0004867415617836
Nelson, J., & Campbell, C. (2017). Evidence-informed practice in education: meanings and applications. In: Taylor & Francis.
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Patalay, P., Giese, L., Stanković, M., Curtin, C., Moltrecht, B., & Gondek, D. (2016). Mental health provision in schools: priority, facilitators and barriers in 10 European countries. Child and Adolescent Mental Health, 21(3), 139-147. https://doi.org/10.1111/camh.12160
Peterson, J. W., Loeb, S., & Chamberlain, L. J. (2018). The Intersection of Health and Education to Address School Readiness of All Children. Pediatrics, 142(5), e20181126. https://doi.org/ARTN e20181126
Quach, J., Nguyen, C., O'Connor, M., & Wake, M. (2017). The Cumulative Effect of Health Adversities on Children's Later Academic Achievement. Academic pediatrics, 17(7), 706-714. https://doi.org/10.1016/j.acap.2017.03.002
Spencer, N. (2008). European Society for Social Pediatrics and Child Health (ESSOP)* Position Statement: Social inequalities in child health–towards equity and social justice in child health outcomes. Child Care Health Dev, 34(5), 631-634. https://doi.org/10.1111/j.1365-2214.2008.00826.x
Wolfe, I., Thompson, M., Gill, P., Tamburlini, G., Blair, M., van den Bruel, A., Ehrich, J., Pettoello-Mantovani, M., Janson, S., & Karanikolos, M. (2013). Health services for children in western Europe. The Lancet, 381(9873), 1224-1234. https://doi.org/10.1016/S0140-6736(12)62085-6
08. Health and Wellbeing Education
Paper
Promotion of Children’s Mental Health in the Educational Context – the Views of Policymakers, Officeholders, and Public Health Nurses
Outi Savolainen, Marjorita Sormunen, Hannele Turunen
University of Eastern Finland, Finland
Presenting Author: Savolainen, Outi
Children’s mental health promotion aims to create supportive living conditions and reduce harmful mental health risk factors (Klemera et al. 2017; Min et al. 2017; WHO 2001). Early childhood education and care and basic education are key development environments in which children’s well-being and mental health promotion can be significantly affected (Barry & Jenkins 2007). The promotion of mental health in the environments of everyday life affects the well-being of the individual in a long term; therefore, early intervention is particularly important in children's mental health problems (Cefai & Camilleri 2015). In a school environment an implementation of a structured and systematic plan for the health and well-being of all pupils and of teaching and non-teaching staff strengthens healthy settings for living, learning, and working (SHE Network 2020). In Finland, basic education is a single-structure system that provides compulsory schooling for all young people between 7 and 15 years and in grades 1–9 (Ministry of Education and Culture 2021). Finnish education system includes early childhood education and care, which refers to children’s planned education and care. It is an important step in a child’s growth and learning path. The right to participate in early childhood education and care is subjective, meaning that all children under school age can participate in it. (EDUFI 2021.)
Like many countries of Northern Europe, Finland is a parliamentary democracy with a majority in parliament (The Nordic Council and the Nordic Council of Ministers 2021). Municipal administration, in turn, is based on the self-government of municipalities. Municipalities have the overall responsibility for mental health promotion of children. Municipalities have a dual management system, which means that local authority management is characterized by division into political and professional management. Political management consists of decision-makers elected to municipal councils, boards, and committees. Professional management, in turn, consists of leading office holders who act as professional representatives of the administration and participate extensively in the various stages of the decision-making process in their area of administration, such as early childhood education and care, and basic education. (Local Government Act of Finland 410/2015; Constitution of Finland 731/1999.)
Public health nurses in child health clinics and schools assess the physical, mental, and social condition of children, provide vaccinations, support parents, and promote healthy growing environments for children and healthy family lifestyles (Student Welfare Act of Finland 1287/2013; Health Care Act of Finland 1326/2010; Government decree 338/2011). Although public health nurses generally aim to promote mental health in children, it is also important for them to identify the risks for potential mental disorders during childhood.
Knowledge on mental health promotion in children is widely available (Drange & Havnes 2019; Neuhaus et al. 2020). However, there is a need to obtain stronger and broader evidence about these issues from the perspective of political decision-makers and leading officeholders in municipal administrations, as well as professionals working with children, such as public health nurses (O’Reilly et al. 2018). The socioecological model of health promotion (Stokols 1996) formed a theoretical framework for this study. The model covers both risk and promotive factors at five levels of the socioecological environment (i.e., individual, interpersonal, organizational, community, and public policy). This study aimed to describe promotion of children’s mental health at the organizational level of the socio-ecological environment, specifically in the early childhood education and care, and basic education from the perspective of political decision-makers and leading officeholders, as well as public health nurses.
Methodology, Methods, Research Instruments or Sources UsedUsing qualitative research methodology, open-ended semi-structured individual interviews were conducted in Finland interviewing public health nurses, who worked at maternity and child health services or at school health care (n=23), policymakers from municipal councils, municipal governments, and committees and leading officeholders from different service sectors as part of the city’s service organization, including social and health services, growth and learning, wellbeing promotion, and environment (n=25; Denzin & Lincoln 2008). Purposive sampling was used to identify potential participants who would produce rich, dense, and focused information on children’s mental health issues (Curtis et al. 2000). Potential participants’ contact information was obtained from nursing managers, public websites of the municipalities and municipal administrative services.
The interview guide was developed based on previous literature and the socio-ecological model of health promotion (Stokols 1996). A pilot interviews confirmed the feasibility of the interview guide. The themes were provided to the participants one week before their interviews to familiarize them. In total, 48 participants were recruited in person, gave their consent, and were interviewed face to face or by telephone by the first author between September and November 2019. The Interviews continued until data saturation was reached. The interviews lasted between 21 and 68 minutes and were recorded and transcribed. Ethical approval for the study was obtained from the Ethics Committee of the university (statement 5/2019, 17.4.2019). In addition, a research permit was obtained separately from each municipal administration and organization involved in our study. Written informed consent was obtained from all participants.
The data were analyzed using inductive content analysis (Vaismoradi et al. 2013). The transcribed texts were read several times to obtain an overall impression, and the data were reviewed for their content. Meaning units were sentences or phases (Graneheim & Lundman 2004), and they were chosen in line with the purpose of the study. Meaning units derived were condensed and coded for the identified categories. In the analysis, the similarities and differences between the meaning units were compared, and categories and subcategories were created based on the comparison. An initial reading of the transcripts was conducted by the first author. Preliminary coding and the final analysis were validated by all authors.
Conclusions, Expected Outcomes or FindingsPolitical decision-makers, officeholders, and public health nurses described promotion of children’s mental health in the early childhood education and care, and basic education. In the early childhood education and care, all participant groups pointed the importance of small group sizes, and adequate and qualified staff. Collaborating between early childhood education and care, child health clinic, social care, and parents/guardians was also seen as paramount. In addition, political decision-makers and officeholders highlighted that early childhood education and care promotes children’s mental health by responding to basic needs, enabling the development of social skills, organizing suitable facilities, setting safe boundaries, and maintaining circadian rhythms. Public health nurses described that enabling all children to participate in day care was important in itself from the perspective of children’s mental health.
According to participants, taking care of friendship issues, tackling bullying, as well as multiprofessional collaboration within the school and between school and other parties working with children and parents promoted children’s mental health at school. Political decision-makers and officeholders raised also the importance of small group sizes, guided activities, promotion of inclusion and equality, prevention of exclusion, and teacher training and supervision. Public health nurses called for lessons and theme days for pupils on emotional and interaction skills, mental health, and about developmental phases.
Based on results, political decision-makers, officeholders, and public health nurses had very similar thoughts related to the children’s mental health promotion in the early childhood education and care, and school. However, there were also differences in the responses of different groups. For example, public health nurses called for raising the mental health issues in the educational context. Thus, different perspectives should be taken into account in municipal decision-making to promote children’s mental health in the best possible way.
ReferencesKlemera, E., Brooks, F.M., Chester, K.L., Magnusson, J. & Spencer, N. 2017. Self-harm in adolescence: protective health assets in the family, school and community. International Journal of Public Health, 62, 631-638.
Min, K., Kim, H., Kim, H. & Min, J. 2017. Parks and green areas and the risk for depression and suicidal indicators. International Journal of Public Health, 62, 647-656.
World Health Organization. 2001. Mental health: New understandings, new hope. The world health report. Available at https://www.who.int/whr/2001/en/whr01_en.pdf?ua=1.
Barry, M.M. & Jenkins, R. 2007. Implementing mental health promotion. Edinburgh: Elsevier.
Cefai, C. & Camilleri, L. 2015. A healthy start: promoting mental health and well-being in the early primary school years. Emotional and Behavioural Difficulties, 20(2), 133–152.
Ministry of Education and Culture. 2021. Basic education. Available at https://okm.fi/en/basic-education.
EDUFI. 2021. Finnish education system. Available at https://www.oph.fi/en/education-system.
The Nordic Council and the Nordic Council of Ministers. 2021. Nordic Co-operation. Available at https://www.norden.org/en.
Local Government Act of Finland 410/2015.
Constitution of Finland 731/1999.
Student Welfare Act of Finland 1287/2013.
Health Care Act of Finland 1326/2010.
Government decree on maternity and child health clinic services, school and student health services and preventive oral health services for children and youth 338/2011.
Drange, N. & Havnes, T. 2019. Early childcare and cognitive development: Evidence from an assignment lottery. Journal of Labor Economics, 37(2), 581-620.
Neuhaus, R., McCormick, M. & O’Connor, E. 2020. The mediating role of child-teacher dependency in the association between early mother-child attachment and behavior problems in middle childhood. Attachment & Human Development. doi:10.1080/14616734.2020.1751989
O’Reilly, M., Svirydzenka, N., Adams, S. & Dogra, N. 2018. Review of mental health promotion interventions in schools. Social Psychiatry and Psychiatric Epidemiology, 53(7), 647-662.
Stokols, D. 1996. Translating social ecological theory into guidelines for community health promotion. American Journal of Health Promotion: AJHP, 10(4), 282-289.
Denzin, N. K. & Lincoln, Y. (Eds.). 2008. The Landscape of Qualitative Research. SAGE Publications.
Curtis, S., Gesler, W., Smith, G. & Washburn, S. 2000. Approaches to sampling and case selection in qualitative research: Examples in the geography of health. Social Science & Medicine, 50(7-8), 1001-1014.
Vaismoradi, M., Turunen, H. & Bondas, T. 2013. Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & Health Sciences, 15(3), 398-405.
Graneheim, U. H. & Lundman, B. 2004. Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105-112.
08. Health and Wellbeing Education
Paper
Digital Mental Health Interventions for Youth: A Systematic Review and Meta-analysis
Michaela Wright, Franziska Reitegger, Herald Cela, Barbara Gasteiger-Klicpera
University of Graz, Austria
Presenting Author: Wright, Michaela
For approximately half of the individuals suffering from a mental disorder, the onset of illness occurs during adolescence, and in more than a third, the disorder emerges by the age of 14 (Solmi et al., 2022). The estimated worldwide prevalence of mental disorders was reported to be 13.4 % (CI 95% 11.3 – 15.9) for this population (Polanczyk et al., 2015). In addition, mental disorders among adolescents have increased in recent years, with the increase being most notable with respect to developmental and mood disorders (Steffen et al., 2018). Increasingly, digital technologies, such as mobile apps or web-delivered programs, are being used to try to counteract the declining mental health of adolescents. The range and variety of these tools is growing rapidly, and more and more studies report on their potential and value (Lucas-Thompson et al., 2019). An updated overview of tools and programs is essential and the proposed paper presentation aims to provide this overview. Findings from a systematic review and meta-analysis (Wright et al., in press) will be presented that outline the current state of digital, evidence-based programs promoting mental health in young people, and provide insight into the characteristics and effectiveness of such programs. The domain of interest is the promotion of mental health with a focus on mental health literacy, well-being, (mental health) help-seeking behavior, stress management, relaxation, mindfulness, resilience and positive psychology.
The ongoing advances in technology mean that more and more mental health promotion programs may be provided successfully, either partly or fully, through digital media (Kaess et al., 2021). As barriers to mental health services increased during the pandemic (due to lockdowns and restrictions), the advantages of choosing a digital mode of delivery have become manifold, e.g., cost-effectiveness, anonymity, accessibility, adaptability, etc. These all serve to lower the threshold when seeking mental health support (Bauer et al., 2005). Accessible, adaptable digital programs lower usage barriers in schools and other institutions, as they require relatively little expertise or effort compared to face-to-face (F2F) interventions. In addition to the high accessibility and availability of digital tools, their potential for successfully promoting young people’s mental health has repeatedly been reported in recent meta-analysis and/or systematic reviews. Harrer et al. (2019) found such tools to have positive effects on depression, anxiety, stress, eating disorder symptoms and role functioning. The findings of Clarke et al. (2015) and Sevilla-Llewellyn-Jones et al. (2018) support the effectivity of online interventions with respect to the treatment of anxiety and depressive symptoms. Noh and Kim (2022) reported beneficial results when preventing an increase in depressive symptoms, but not for anxiety or stress. Furthermore, well-tailored digital interventions are likely to increase engagement with a support tool and to aid the transfer of specific skills into the daily lives of young people (Lucas-Thompson et al., 2019). Indeed, web-based interventions have been reported to improve individuals’ quality of life and functioning (Sevil-la-Llewellyn-Jones et al., 2018).
Within this paper presentation, findings from a systematic review and meta-analysis (Wright et al., in press) on digital tools for mental health promotion among 11–18 year olds will be presented. The review focused on three areas. First, it was of interest to determine, what digital-based interventions promoting mental health are available for children and adolescents aged 11 to 18. Second, the effectiveness of these interventions was analyzed. Third, the factors underlying their effectiveness were assessed. In this paper presentation, special attention is given to the third area, and deeper insights are provided into the impact of moderating factors that potentially influenced the effectiveness of the interventions. In addition, import implications for the design of future interventions are suggested.
Methodology, Methods, Research Instruments or Sources UsedThis study made use of the recommendations of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement.
Search Strategy. Two literature reviews were conducted (May & October 2021) using the electronic databases PubMed, The Cochrane Library and PsycInfo.
Eligibility Criteria. Studies with participants aged between 11 to 18 years were of interest. These studies needed to be controlled studies with a mixed-methods or quantitative design reporting on mental health interventions. Furthermore, only peer-reviewed, English publications published between 2000 and 2021 were eligible for inclusion. Clinical trials, studies lacking a control group or quantitative measures were excluded.
Study Selection Process. The searches yielded 3.809 results and 27 studies were found eligible for inclusion. Both searches followed the same procedure and four reviewers were involved in the application of eligibility criteria. Study identification followed a three-step process: (1) removal of duplicates, (2) screening for inclusion criteria, (3) resolution of discrepancies between reviewers.
Data Extraction. Relevant extractions involved, but were not limited to: theoretical background, medium(s) and mode of intervention, intervention and sample characteristics, study design, method, outcome data/results, effect size, and potential moderators of intervention efficacy (setting, duration of intervention, adherence, attrition, and levels of interaction, support, guidance and digitization).
Quality Assessment. In order to assess the risk of bias, the Cochrane Risk of Bias Tool - RoB and the Risk Of Bias In Non-Randomized Studies – ROBINS-I were applied.
Analysis. In the process of narrative synthesis, the key features of the studies and their interventions were summarized (summary table), and potential intervention barriers and facilitators were put forward. Additionally, a detailed description was provided for variables identified as potential moderators of intervention efficacy. Eight conceptually-related clusters were identified based on the main outcomes of the primary studies (anxiety, depressive symptoms, well-being, stress, internalizing symptoms, externalizing symptoms, protective factors). A meta-analysis was performed separately on each cluster for post-intervention measurements. For each analysis, forest plots were generated, observing effect size (Hedges’ g) and heterogeneity between studies (τ2). A sensitivity analysis was carried out when the heterogeneity for a cluster was higher than moderate (> 50%). To study possible sources of heterogeneity, subgroup analysis was then performed including the previously identified moderators. Finally, to address potential publication bias, funnel plots were inspected and Egger's tests were performed. Where evidence of publication bias was found, the bias was adjusted using the Duval and Tweedie Trim and Fill procedure.
Conclusions, Expected Outcomes or FindingsIn total 27 studies were identified to meet the inclusion criteria. Half of these studies reported significant effects in improving mental health. A meta-analysis was performed based on post-intervention measurements for each of the seven clusters with a total sample of 13,216 participants to identify the effectiveness of the interventions and to examine the impact of eight predefined, underlying factors.
Even though the high heterogeneity of the results calls for careful interpretation, the findings support previous research in that digital interventions have the potential to promote adolescent mental health. Small effects regarding a decrease of anxiety and an increase of well-being were identified. After outlier-removal, small effects were also detected relating to the promotion of protective individual factors, including self-esteem, self-compassion, or help-seeking behavior. No significant effects were found for depressive symptoms, stress, externalizing symptoms (e.g., hyperactivity), and internalizing symptoms (e.g. loneliness).
When examining the impact of underlying predefined factors, the analysis showed that interventions with a school-based setting, consistent adherence, low levels of attrition and some level of professional support and guidance, were found to be most effective. The length of the intervention, the level of digitization, and the level of interaction had no significant impact in the reviewed studies.
With regard to narrative synthesis, in addition to the moderating factors mentioned above, three other important factors need to be considered in the future design of mental health interventions. First, it is suggested that study designs incorporate elements of participatory design research so that interventions are more closely tailored to the preferences and needs of youth. Second, it is recommended that the design and content of the intervention be diversity-sensitive. Third, it is suggested that further research focus as much on maintaining and promoting the availability of an intervention as it does on developing the intervention.
ReferencesBauer, S., Golkaramnay, V., & Kordy, H. (2005). E-Mental-Health. Psychotherapeut, 50(1), 7–15. https://doi.org/10.1007/s00278-004-0403-0
Clarke, A. M., Kuosmanen, T., & Barry, M. M. (2015). A systematic review of online youth mental health promotion and prevention interventions. Journal of Youth and Adolescence, 44(1), 90–113. https://doi.org/10.1007/s10964-014-0165-0
Harrer, M., Adam, S. H., Baumeister, H., Cuijpers, P., Karyotaki, E., Auerbach, R. P., Kessler, R. C., Bruffaerts, R., Berking, M., & Ebert, D. D. (2019). Internet interventions for mental health in university students: A systematic review and meta-analysis. International Journal of Methods in Psychiatric Research, 28(2), e1759. https://doi.org/10.1002/mpr.1759
Kaess, M., Moessner, M., Koenig, J., Lustig, S., Bonnet, S., Becker, K., Eschenbeck, H., Rummel-Kluge, C., Thomasius, R., & Bauer, S. (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, and Allied Disciplines, 62(7), 916–918. https://doi.org/10.1111/jcpp.13317
Lucas-Thompson, R. G., Broderick, P. C., Coatsworth, J. D., & Smyth, J. M. (2019). New Avenues for Promoting Mindfulness in Adolescence using mHealth. Journal of Child and Family Studies, 28(1), 131–139. https://doi.org/10.1007/s10826-018-1256-4
Noh, D., & Kim, H. (2022). Effectiveness of Online Interventions for the Universal and Selective Prevention of Mental Health Problems Among Adolescents: A Systematic Review and Meta-Analysis. Prevention Science : The Official Journal of the Society for Prevention Research, 1–12.
Polanczyk, G. V., Salum, G. A., Sugaya, L. S., Caye, A., & Rohde, L. A [Luis A.] (2015). Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 56(3), 345–365. https://doi.org/10.1111/jcpp.12381
Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., & Fusar-Poli, P. (2022). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry. Advance online publication. https://doi.org/10.1038/s41380-021-01161-7
Steffen, A., Manas K. Akmatov, Holstiege, J., & Bätzing, J. (2018). Diagnoseprävalenz psychischer Störungen bei Kindern und Jugendlichen in Deutschland: eine Analyse bundesweiter vertragsärztlicher Abrechnungsdaten der Jahre 2009 bis 2017.
Wright, M., Reitegger, F., Cela, H., Papst, A., & Gasteiger-Klicpera, B. (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.
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