Understanding the prevalence and the scope of mental health conditions

Investing in accurate measurement of child and adolescent mental health is essential to understand the burden of poor mental health, to ensure early detection and treatment, and to prioritise relevant services and programmes to improve child and adolescent mental health in meaningful ways (Hayes et al., Reference Hayes, Carvajal, Hijazi, Ahs, Doraiswamy, El Azzouzi, Fox, Herrman, Gornitzka, Staglin and Wolpert2021). Despite the importance of mental health, measurement efforts for children and adolescents are complicated by several factors, necessitating thoughtful planning and flexible measurement approaches, including cultural adaptation of the tools used for data collection with this group.

First, the timing of measurement is important, given clear age-related patterns in mental health and differences in disease burden profiles between children, younger adolescents and older adolescents (Guthold et al., Reference Guthold, Carvajal, Adebayo, Azzopardi, Baltag, Dastgiri, Dua, Fagan, Ferguson, Inchley, Mekuria, Moller, Servili and Requejo2021). Tools that are appropriate and valid for children and younger adolescents, including those with more severe mental health challenges, are extremely limited. Recent work has highlighted the insufficiency of screening and assessment items for suicidal ideation and risk in children aged 5–11 years, who represent a small but growing proportion of suicides (Ayer et al., Reference Ayer, Colpe, Pearson, Rooney and Murphy2020).

Second, the focus of measurement is also important, given the wide spectrum of mental disorders, understanding and experiences of mental health by age, gender, culture and geography. Focusing on epidemiological data and psychopathology alone may miss the diversity and depth of experiences with mental health, especially for children and adolescents. Additionally, these developmental periods are often characterised by a variety of co-occurring risk factors, which require specific measurement considerations. Engaging children and adolescents with lived experience in formative work, and later development and adaptation activities, can provide essential insights on context, experience and acceptability (Reed et al., Reference Reed, Couturiaux, Davis, Edwards, Janes, Kim, Melendez-Torres, Murphy, Rotevatn and Smith2021).

Lastly, few valid, reliable tools to measure positive aspects of mental health during childhood and adolescence are available or feasible across a range of contexts, cultures and populations (Erskine et al., Reference Erskine, Baxter, Patton, Moffitt, Patel, Whiteford and Scott2017). Ideally, these tools should enable both service providers and researchers to engage with children and adolescents in their home language, using local definitions and understandings of mental health symptoms. Self-report measurement approaches provide an opportunity for children and adolescents to be involved in the assessment process (De Vries et al., Reference De Vries, Davids, Mathews and Aarø2018), but may also be shaped by social desirability bias, when participants consciously or subconsciously over- or under-state an issue to conform to perceived social norms (Simkiss et al., Reference Simkiss, Gray, Dunne and Snowden2021). This issue is particularly complex given the stigma associated with mental health. Self-reports might be triangulated with other sources of data; for instance, caregivers and teachers can also complete observational assessments of the child or adolescent (De Vries et al., Reference De Vries, Davids, Mathews and Aarø2018). As observational approaches are typically more costly and resource-intensive, however, participatory methods may be an alternative, promising mode of engaging children while collecting accurate data (Fenwick-Smith et al., Reference Fenwick-Smith, Dahlberg and Thompson2018). In low-resource settings, brief self-report screening measures are frequently used to estimate the scope of the problem, or to make decisions about mental health policy and practice. This can be problematic, since using screening tools with inappropriate validity risks under or overestimating the burden of mental health problems, both of which have negative consequences for research and programming efforts (Kohrt and Kaiser, Reference Kohrt and Kaiser2021).

Using appropriate, validated tools and correctly interpreting the results is therefore central to improving global child and adolescent mental health measurement.

Recent work by the Measurement of Mental Health Among Adolescents at the Population Level (MMAP) initiative, spearheaded by UNICEF and supported by WHO and other global partners, has sought to narrow this gap (Carvajal et al., Reference Carvajal, Harris Requejo, Ahs, Idele, Adewuya, Cappa, Guthold, Kapungu, Kieling, Patel, Patton, Scott, Servili, Wasserman and Kohrt2021). MMAP has supported extensive validation work to fill this need with adolescents aged 10–19 years, and its protocol provides guidance to conduct cultural adaptation of tools to make them suitable for specific settings (Carvajal et al., Reference Carvajal, Ahs, Requejo, Kieling, Lundin, Kumar, Luitel, Marlow, Skeen, Tomlinson and Kohrt2022). Such data and evidence are urgently needed to guide strategic actions allowing for timely, effective mental health prevention and treatment efforts to improve outcomes across the life course.

Understanding which components work

A second cross-cutting priority is to identify components of effective interventions – to distil core “building blocks” and build consensus around what works across a range of settings (Chorpita et al., Reference Chorpita, Daleiden and Weisz2005; Wolpert et al., Reference Wolpert, Pote and Sebastian2021). These approaches can be descriptive, such as common elements analyses (Boustani et al., Reference Boustani, Frazier, Becker, Bechor, Dinizulu, Hedemann, Ogle and Pasalich2015; Boustani et al., Reference Boustani, Frazier, Chu, Lesperance, Becker, Helseth, Hedemann, Ogle and Chorpita2020), or more quantitative in nature in examining which components predict better outcomes (Melendez-Torres et al., Reference Melendez-Torres, Bonell and Thomas2015).

As part of the WHO’s adolescent mental health guidelines, our team meta-analysed components of universal interventions, seeking components that could consistently predict larger effect sizes across outcomes at different timepoints (Skeen et al., Reference Skeen, Laurenzi, Gordon, du Toit, Tomlinson, Dua, Fleischmann, Kohl, Ross and Servili2019). Components were adapted from the PracticeWise manual (PracticeWise, 2009). Seven consistent components emerged: interpersonal skills, emotional regulation, alcohol and drug education, mindfulness, problem-solving, assertiveness training and stress management. We found that two of these, interpersonal skills and emotional regulation, were associated with larger effect sizes for positive mental health outcomes. These components have been integrated into WHO’s guidelines for adolescents as well as the Helping Adolescents Thrive (HAT) toolkit, supporting the implementation of these guidelines (World Health Organization and UNICEF, 2021).

Other recent work, including a body of research funded by the Wellcome Trust Active Ingredients Commission, has explored a more broadly conceptualised set of components that can promote improved mental health. On a more individualised basis, these include components such as self-compassion (Egan et al., Reference Egan, Rees, Delalande, Greene, Fitzallen, Brown, Webb and Finlay-Jones2022) and engagement with the arts (Easwaran et al., Reference Easwaran, Narasimhan, Japee, Raja, Murali and Easwaran2021). Effective components may also be societal or structural in nature, either as interventions themselves or in broader contexts. This type of component may include access to green spaces and recreational areas (Reece et al., Reference Reece, Bray, Sinnett, Hayward and Martin2021), or increased neighbourhood cohesion (Donnelly et al., Reference Donnelly, McLanahan, Brooks-Gunn, Garfinkel, Wagner, Jacobsen, Gold and Gaydosh2016).

By advancing our understanding of which components predict better mental health outcomes, we can move to examine the most promising ways to integrate these components into psychosocial interventions. Importantly, this components work should be continually updated, and also seek to draw across diverse interventions implemented across geographical contexts, enabling a more robust understanding of these components.

Understanding how, and for whom, interventions work in practice

Building from a common understanding of effective components, disentangling the processes underlying these interventions helps us understand the pathways and mechanisms that can lead to specified outcomes. This priority spans theory-building work, implementation science, and longitudinal approaches to evidence generation.

Realist reviews can provide frameworks for understanding underlying theories – describing how one or more interventions work in practice, for which groups, and under which circumstances (Pawson et al., Reference Pawson, Greenhalgh, Harvey and Walshe2004). The review process is inductive and iterative in nature; researchers aim to identify demi-regularities, or semi-predictable patterns of behaviour that re-occur, to examine how these might lead to outcomes (Wong et al., Reference Wong, Greenhalgh and Pawson2010). Contexts and mechanisms are explored as they map onto outcomes, and ultimately researchers can develop, test, and refine theories about how interventions work, leading to a more explanatory style of analysis. A recent realist review examined psychosocial interventions that used emotion regulation skills, finding a number of provisions that supported reduced symptoms of depression and anxiety among adolescents (Skeen et al., Reference Skeen, Laurenzi, Mawoyo, Gemmell, Stewart, Luitel, Coetzee, Servili, Tsai, Melendez-Torres and Tomlinson2020). These include tailoring interventions to target populations (age, developmental stage, gender, culture, neurodiversity, mental health status); selecting skilled, well-trained, empathic and supported practitioners to implement the intervention; and providing opportunities for skills reinforcement and parental/caregiver engagement outside of the intervention context (Pote, Reference Pote2021). Gender and age differences in intervention impact may also emerge within these analyses, as well as differences within groups exposed to adversities.

These findings can be further bolstered by integrating implementation science approaches into intervention evaluation. While implementation science methods may be used alongside more traditional evaluation methods – including measures such as participant attendance, fidelity to the intervention, quality of delivery, participant feedback or cost-effectiveness – these data are rarely used to drive changes in intervention design or delivery (Bauer and Kirchner, Reference Bauer and Kirchner2020). In identifying more suitable ways to reach children and adolescents, to measure unanticipated context- or systems-related factors, and to streamline intervention delivery, researchers can maximise the impact of interventions and enable theories to be testable. Relatedly, engaging children and adolescents in the intervention design and evaluation process can be especially effective (Ozer et al., Reference Ozer, Afifi, Gibbs and Mathur2018). Youth preferences must be well-integrated into interventions, especially for adolescents but even for child-focused interventions. Sustained engagement can be facilitated through using co-development processes that integrate and elevate adolescent perspectives, establishing adolescent advisory boards that oversee and/or govern a research project along its full continuum, and creating protocols to ensure youth engagement is central to research project planning, decision-making and dissemination (Oliveras et al., Reference Oliveras, Cluver, Bernays and Armstrong2018; Ozer et al., Reference Ozer, Afifi, Gibbs and Mathur2018).

A final key area for assessing how, and for whom, interventions work in practice is through harnessing longitudinal data. Just as more foundational research is needed to understand how mental health trajectories shift along the life course, we need to be able to measure the effects of psychosocial interventions on a longer time horizon. Early childhood interventions may show short-term protective effects, but these impacts may be overwhelmed by social and environmental risks to child development (Tomlinson et al., Reference Tomlinson, Fearon, Christodoulou and Rotheram-Borus2020), especially for populations experiencing multiple adversities. Longitudinal intervention cohorts can provide more granularity as to how intervention effects may be attenuated or strengthened over time – as well as insights into critical life course events at distinct ages. These analyses could pinpoint critical moments in children’s and adolescents’ mental health trajectories where shifts in skills may be needed and may provide important evidence for tailoring strategy by age or mental health experience. These data can also provide important evidence about if and how effectively children and adolescents are able to apply intervention skills over time.

Ensuring supportive infrastructure and political will to intervene at scale

On a broader level, identifying ways to prioritise child and adolescent mental health promotion as part of larger systems is essential. Mental health is ultimately a cross-cutting issue; however, it remains conceptualised as a health issue in global and national development agendas.

Policies that support child and adolescent mental health are critical to promoting mental health and preventing disorders (Mokitimi et al., Reference Mokitimi, Schneider and de Vries2018; Skokauskas et al., Reference Skokauskas, Lavelle, Munir, Sampaio, Nystrand, McCrone, McDaid, Chisholm, Byford and Ganguli2018). While this imperative is echoed in global agendas such as the Sustainable Development Goals, globally, over 40% of countries have no policies that include mental health, and only 10% of countries have policies that include children and adolescents (World Health Organization, 2021b). This misalignment is even greater in LMICs, which often lack resources for “non-essential” areas of health or rely on foreign funding to support their national budgets (Babatunde et al., Reference Babatunde, van Rensburg, Bhana and Petersen2021). The required resources can include trained personnel, adequate facilities and appropriate assessment tools. This oversight can also happen in places where policies do exist: policies may be comprehensive but lack the infrastructure, resources or political will to be effectively implemented or integrated into practice (Mokitimi et al., Reference Mokitimi, Schneider and de Vries2018).

Importantly, few policies conceptualise mental health on a broad spectrum: elevating the significance of mental health promotion alongside prevention and treatment is also a critical priority for expanding access. One way of effectively shifting the framing is to engage stakeholders across sectors including education, social development and labour, in addition to health. Recent guidance, including the HAT Toolkit, has identified key actions for partners from various sectors to engage in mental health promotion collaboratively (World Health Organization and UNICEF, 2021). Approaches such as task-shifting can also be valuable, especially for delivering psychosocial interventions, in strengthening the mental health workforce to reach more individuals at low cost (McInnis and Merajver, Reference McInnis and Merajver2011).

Supportive infrastructure for mental health can be fostered at the level of the home and school environments, where children and adolescents spend most of their time (Wang and Degol, Reference Wang and Degol2016). In addition to the parental/caregiver engagement approaches shared above, which aim to influence how parents interact with their children to promote good mental health, school engagement is an additional critical aspect. The WHO’s Health Promoting Schools framework offers a roadmap for integrating health promotion into educational spaces, advocating a whole-school approach (World Health Organization, 2021a). Practically, this process might involve incorporating health into the school curriculum, changing the social and physical environment of school, and involving families and communities in reinforcing key messages (Langford et al., Reference Langford, Bonell, Komro, Murphy, Magnus, Waters, Gibbs and Campbell2017). School climate interventions may reduce depressive symptoms (Singla et al., Reference Singla, Shinde, Patton and Patel2021), decrease suicidality (La Salle et al., Reference La Salle, Wang, Parris and Brown2017) and enhance resilience (Riekie et al., Reference Riekie, Aldridge and Afari2017) – suggesting that positively altering school environments can have significant outcomes. Beyond these immediate environments, there is a need for sustained engagement at country level to unlock multi-level advocacy and funding – all of which have the capacity to advance youth mental health initiatives (Hayes et al., Reference Hayes, Carvajal, Hijazi, Ahs, Doraiswamy, El Azzouzi, Fox, Herrman, Gornitzka, Staglin and Wolpert2021).