Background
The vast majority (90%) of the world’s growing population of 1.2 billion adolescents live in low- and middle-income countries (LMICs). Almost one third (30.5%) of these adolescents are multidimensionally poor, i.e., they live in households facing multiple monetary, education or basic service infrastructure deprivations (Alkire et al., Reference Alkire, Kanagaratnam and Suppa2019). Investing in the health and human capital of adolescents is critical for their future well-being as adults, and it is a key driver of long-term health and economic prosperity in LMICs (Patton et al., Reference Patton, Olsson, Skirbekk, Saffery, Wlodek, Azzopardi, Stonawski, Rasmussen, Spry, Francis, Bhutta, Kassebaum, Mokdad, Murray, Prentice, Reavley, Sheehan, Sweeny, Viner and Sawyer2018).
Depression and anxiety significantly impair the ability of adolescents to succeed in their life goals and lead healthy lives. Depression and anxiety affect millions of adolescents worldwide and are the leading contributors to the global burden of disease among young people, accounting for over a third (34.8%) of years lived with disability and contributing significantly to excess mortality through suicide (Erskine et al., Reference Erskine, Moffitt, Copeland, Costello, Ferrari, Patton, Degenhardt, Vos, Whiteford and Scott2015).
There is growing evidence for the efficacy of interventions that prevent adolescent depression and anxiety in high-income countries (HIC) (Skeen et al., Reference Skeen, Laurenzi, Gordon, du Toit, Tomlinson, Dua, Fleischmann, Kohl, Ross, Servili, Brand, Dowdall, Lund, van der Westhuizen, Carvajal-Aguirre, Eriksson de Carvalho and Melendez-Torres2019; Stockings et al., Reference Stockings, Degenhardt, Dobbins, Lee, Erskine, Whiteford and Patton2016), but the evidence base is weak in LMIC (Skeen et al., Reference Skeen, Laurenzi, Gordon, du Toit, Tomlinson, Dua, Fleischmann, Kohl, Ross, Servili, Brand, Dowdall, Lund, van der Westhuizen, Carvajal-Aguirre, Eriksson de Carvalho and Melendez-Torres2019). Increasing the evidence base in LMIC is important because adolescents in LMICs face particular challenges that are fundamentally different from those in HICs, namely higher rates of poverty, exposure to more violence and crime, diminished social and economic opportunities and severely under-resourced mental healthcare systems. Interventions tested in HICs frequently do not address these fundamental challenges, and in particular, most HIC study samples do not capture the same constellation of economic and other adversities representative of many LMIC settings (Lund et al., Reference Lund, Brooke-Sumner, Baingana, Baron, Breuer, Chandra, Haushofer, Herrman, Jordans, Kieling, Medina-Mora, Morgan, Omigbodun, Tol, Patel and Saxena2018).
A further challenge is that the mechanisms that link poverty to mental health in LMICs are poorly understood (Ridley et al., Reference Ridley, Rao, Schilbach and Patel2020). One hypothesis arising from research in HICs points to the mediating role of self-regulation (Palacios-Barrios and Hanson, Reference Palacios-Barrios and Hanson2019). Self-regulation entails the capacity to set goals, maintain goal-directed behaviour in the face of distractors or setbacks and flexibly adapt behaviour to achieve goals. Studies in HIC suggest that strengthening self-regulation may help reduce depression and anxiety among adolescents by strengthening their ability to set goals, deal with the emotional impact of failure and adapt goal-directed behaviour (Strauman and Eddington, Reference Strauman and Eddington2017).
Yet it is unlikely that improving self-regulation alone will be sufficient to prevent depression and anxiety, given the wide array of social and economic challenges faced by adolescents in these settings. Poverty may also independently increase the risk of depression and anxiety through various mechanisms, including negative income shocks (Christian et al., Reference Christian, Hensel and Roth2019), earnings uncertainty, poor education and employment outcomes and social stigma (Ghosal et al., Reference Ghosal, Jana, Mani, Mitra and Roy2022; Ridley et al., Reference Ridley, Rao, Schilbach and Patel2020).
This article aims to introduce the ‘Improving Adolescent mentaL health by reducing the Impact of poVErty (ALIVE)’ study, its conceptual framework, objectives, methods and expected outcomes. The overarching premise of ALIVE is that interventions that combine psychosocial components to strengthen self-regulation with poverty reduction strategies have the potential to prevent depression and anxiety among adolescents in LMICs (Fig. 1).
Poverty reduction and self-regulation interventions that tackle the relationship between poverty and its neuropsychological consequences to reduce risk of depression and anxiety.
Aim and objectives
The aim of the ALIVE study is to develop and pilot-test an intervention that combines poverty reduction with strengthening self-regulation in order to prevent depression and anxiety among adolescents living in urban poverty in Colombia, Nepal and South Africa. This aim will be achieved by addressing four objectives: (1) develop a conceptual framework that identifies the causal mechanisms linking poverty, self-regulation and depression and anxiety; (2) develop a multi-component selective prevention intervention targeting self-regulation and poverty among adolescents at high risk of developing depression or anxiety; (3) adapt and validate instruments to measure the incidence of depression and anxiety, mediators and implementation parameters of the preventive intervention; and (4) undertake a four-arm pilot cluster randomised controlled trial (RCT) to assess the feasibility, acceptability and cost of the selective prevention intervention in the three study sites (Fig. 2).
ALIVE study overview.
The focus on evaluating a prevention intervention is in line with recent calls for reframing global mental health efforts more as a continuum (Patel et al., Reference Patel, Saxena, Lund, Thornicroft, Baingana, Bolton, Chisholm, Collins, Cooper, Eaton, Herrman, Herzallah, Huang, Jordans, Kleinman, Medina-Mora, Morgan, Niaz, Omigbodun, Prince, Rahman, Saraceno, Sarkar, De Silva, Singh, Stein, Sunkel and UnUtzer2018; Purgato et al., Reference Purgato, Uphoff, Singh, Thapa Pachya, Abdulmalik and van Ginneken2020), clearly distinguishing prevention (and promotion) interventions from treatment by applying a public mental health framework (Tol et al., Reference Tol, Purgato, Bass, Galappatti and Eaton2015), and by applying a study design that assesses the effect on the incidence of mental health problems in those who did not have problems at baseline, rather than the reduction of symptoms as is commonly done in so-called prevention studies (Cuijpers, Reference Cuijpers2022). Selective prevention is thereby defined as targeting one or more subgroups of a population determined to be at risk of developing depression or anxiety. As opposed to indicated prevention (i.e., targeting individuals who have symptoms of a condition but do not yet meet the clinical threshold for that condition), selective prevention relies upon one or more factors that have been prospectively demonstrated to increase the future risk of a condition. There are few risk factors that, in isolation, are shown to have strong predictive validity of future development of depression or anxiety among adolescents (Pedersen et al., Reference Pedersen, Lam, Hoffmann, Zajkowska, Walsh, Kieling, Mondelli, Fisher, Gautam and Kohrt2023). Following a selective preventative study design, we aim to enrol adolescents who score ‘below’ validated clinical thresholds for depression and anxiety and score ‘above’ a validated total score of multiple risk factors that have been established through multiple prospective samples in LMICs, demonstrating that a constellation of risk factors predict future depression development (Kieling et al., Reference Kieling, Buchweitz, Caye, Manfro, Pereira, Viduani, Anes, Battel, Benetti, Fisher, Karmacharya, Kohrt, Martini, Petresco, Piccin, Rocha, Rohde, Rohrsetzer, Souza, Velazquez, Walsh, Yoon, Zajkowska, Zonca, Swartz and Mondelli2021).
Country settings
We have selected study settings from Latin America (Bogotá, Colombia), sub-Saharan Africa (Cape Town, South Africa) and South Asia (Kathmandu, Nepal) for four reasons: (1) these urban settings all have large populations of adolescents living in circumstances of multidimensional poverty (Table 1); (2) diverse settings are important because the characteristics of multidimensional poverty, mental health consequences, and their interactions will differ by context (Botter-Maio Rocha et al., Reference Botter-Maio Rocha, Fisher, Caye, Anselmi, Arseneault, Barros, Caspi, Danese, Goncalves, Harrington, Houts, Menezes, Moffitt, Mondelli, Poulton, Rohde, Wehrmeister and Kieling2021); (3) we wish to develop an intervention framework that can be adapted and potentially applied in diverse settings; and (4) our study team has extensive experience of working with adolescents in these cities.
Socioeconomic and mental health characteristics of proposed country sites
a National poverty line, reported in Global Multidimensional Poverty Index (2019).
Research methods
The research objectives, methods and outputs are summarised in Table 2.
ALIVE research objectives, methods and outputs
Objective 1: Conceptual framework
To develop our conceptual framework, we will conduct a realist synthesis and qualitative formative research in parallel. The aim of the realist synthesis is to summarise existing knowledge regarding the validity of our initial theoretical framework (Fig. 1) and to identify evidence-supported mechanisms of action that will form the basis of intervention development. In contrast to the causal models underlying conventional systematic reviews in evidence-based medicine (i.e., intervention X leads to outcome Y), realist syntheses operate from a ‘generative’ model of causality in which intervention outcomes O are generated by relevant mechanisms M which are triggered in context C (so-called C-M-O models). The realist synthesis’ emphasis on identifying mechanisms of action aligns with guidance on complex health interventions, which highlights the importance of developing detailed theoretical models prior to feasibility testing (Craig et al., Reference Craig, Dieppe, MacIntyre, Michie, Nazareth and Petticrew2008; Pawson et al., Reference Pawson, Greenhalgh, Harvey and Walshe2005).
The aim of the qualitative formative research is to examine the underlying mechanisms linking poverty, self-regulation and depression or anxiety among adolescents across the three sites. We will adapt a narrative approach previously used to explore the process of adolescent self-regulation in conflict situations (Conover and Daiute, Reference Conover and Daiute2017). This method encourages participants through interviews and journals to narrate different situations that are realistic and relevant to their lives and explores their knowledge and utilisation of various self-regulation strategies. In line with our definition, we will explore strategies used in circumstances of multidimensional poverty.
Combining findings from the realist synthesis with the qualitative formative research, we will iteratively develop a conceptual framework that elaborates the hypothesised causal mechanisms linking poverty, self-regulation and depression or anxiety.
Objective 2: Intervention development
Informed by the theoretical model, we will develop a modular selective prevention intervention that comprises ‘poverty reduction’ components and ‘self-regulation’ components.
We will follow a phased process of designing public health interventions (Wight et al., Reference Wight, Wimbush, Jepson and Doi2016), adhering to the following three design principles. First, to be evidence-informed, we will rely on existing empirically supported poverty reduction and self-regulation interventions that map onto the conceptual framework. Second, we will adopt ‘an interdisciplinary modular approach’. By modular approach, we mean breaking down complex interventions into simpler parts that function independently (Chorpita et al., Reference Chorpita, Daleiden and Weisz2005). A modular intervention approach has been successfully applied for psychological treatment in LMICs for adults (Murray et al., Reference Murray, Dorsey, Haroz, Lee, Alsiary, Haydary, Weiss and Bolton2014; Vellakkal and Patel, Reference Vellakkal and Patel2015) and children (Murray et al., Reference Murray, Hall, Dorsey, Ugueto, Puffer, Sim, Ismael, Bass, Akiba and Lucid2018; Jordans et al., Reference Jordans, Komproe and Tol2011) and for poverty reduction interventions (Alfonsi et al., Reference Alfonsi, Bandiera, Bassi, Burgess, Rasul, Sulaiman and Vitali2020). We will not be able to test the effects of individual modules as in a dismantling study. However, we will be able to assess the feasibility and acceptability of delivering each of the modules and how they are able to function together in an integrated programme that is delivered to adolescents and their carers in these settings. The selection of intervention modules will follow a process of identifying content based on existing literature reviews and the aforementioned realist review and qualitative research (Chorpita et al., Reference Chorpita, Daleiden and Weisz2005). In other words, the modules will be selected based on the identification of evidence-informed active ingredients that address key mechanisms by which either poverty or self-regulation increases the risk for depression or anxiety among adolescents. Third, we will follow an iterative approach that actively engages stakeholders (i.e., adolescents and service providers) in the process of co-design to ensure interventions are context-appropriate for end users. This will include consulting with stakeholders through Theory of Change workshops in each country site with local experts, policy stakeholders and adolescents, as well as consultations and pilot testing modules with our Adolescent Advisory Groups (AAGs) in each country. This will also include small-scale (N = 1) evaluations to do early field testing of intervention content and to allow for fine-tuning, selecting or changing specific strategies.
Self-regulation intervention modules that have resulted in positive outcomes in prevention programmes for adolescent depression or anxiety, and which may be considered for our intervention, include (Horowitz and Garber, Reference Horowitz and Garber2006; Nijjar et al., Reference Nijjar, Puppala, Dickinson, Duval, Duprez, Kreitzer and Benditt2014; Takacs and Kassai, Reference Takacs and Kassai2019): (1) emotion regulation techniques; (2) biofeedback; (3) cognitive techniques; (4) behavioural activation; (5) social coping techniques; (6) physical activity; and (7) parenting support.
Poverty reduction intervention modules will be equally informed by recent literature, which shows that poverty reduction policy should not only provide transient, short-term protection against poverty but also help families and children escape poverty through the accumulation of human capital. This second goal of poverty reduction policy is often referred to as the promotion role and resonates with recent conceptualisations of poverty as a multidimensional concept that incorporates non-monetary poverty measures (Stiglitz et al., Reference Stiglitz, Sen and Fitoussi2009), such as health, education and access to basic service infrastructure (Alkire et al. Reference Alkire, Kanagaratnam and Suppa2019). Consequently, the ALIVE intervention will include multiple mechanisms to reduce the key constraints associated with poverty: (1) a cash transfer component that addresses household income constraints; complemented by (2) a series of modules for both the adolescent and the household that address other constraints associated with poverty: information (on the benefits of education), negotiation (bargaining skills) and financial literacy.
Objective 3. Instrument development
Instrument development, adaptation and validation will be achieved in three steps. First, we will go through a process of instrument selection based on our research aims and prior use of instruments in the three study sites or languages spoken in those sites. A variety of self-report and neuropsychological instruments will be provisionally selected to determine eligibility, outcomes, mediation and implementation (Table 3).
Potential ALIVE measuresa
a This table presents a list of the constructs that ALIVE plans to measure. The final selected instruments will be presented in a future protocol publication.
Second, we will go through a multi-stage process of transcultural adaptation, validation and data harmonisation that is widely used in global mental health with children and adolescents (Kohrt et al., Reference Kohrt, Jordans, Tol, Luitel, Maharjan and Upadhaya2011). The process involves the following steps: (1) selecting qualified translators; (2) evaluation of the synthesised version by experts; (3) evaluation of the intelligibility of the items by the target population; (4) back-translation; and (5) pilot testing among a small group of adolescents.
Third, we will validate the primary and secondary mental health outcome tools for depression, anxiety and externalising symptoms against clinical diagnoses using the Kiddie Schedule for Affective Disorders and Schizophrenia, Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) version. We will also adapt neuropsychological assessment tools that can be easily administered digitally to adolescents to assess self-regulation and other domains. Finally, we will validate low-cost, wearable devices for the assessment of heart rate variability and the deployment of biofeedback in low-resource settings.
Objective 4. Pilot cluster RCT
In keeping with Consolidated Standards of Reporting Trials (CONSORT) guidelines for pilot cluster RCTs, the aims of the pilot trial are to test the feasibility, acceptability and cost of the intervention and to test the trial procedures and measures to inform a future fully powered multi-site trial. We will conduct a four-arm pilot cluster RCT of the ALIVE intervention with a sample of 240 adolescents (13–15 years) with a high risk of depression or anxiety living in poor urban households in each country. The four groups will be: poverty reduction intervention (n = 60); self-regulation intervention (n = 60); combined (poverty reduction and self-regulation [n = 60]); and control group (n = 60). Assessments of all groups will be conducted at baseline T 0, 6 months (T 1), 12 months (T 2) and 18 months (T 3). The definition of the sample is described previously.
Intervention group participants will receive the modular ALIVE intervention described in Objective 2, and control group participants will receive any services that are already available in the community (treatment as usual). The ALIVE intervention will be delivered in person by our implementation partners after school hours, on a weekly basis for an anticipated period of 6 months.
Feasibility outcomes will be: feasibility of recruitment; retention of participants in the intervention and trial; fidelity in intervention delivery; acceptability of the intervention; appropriateness of data collection processes and outcome measures, including level of missing values; adequacy of randomisation and blinding; level of provider competence and frequency of adverse events. We aim to demonstrate sensitivity to change on the primary outcome, which is defined as cumulative incidence rate of depression or anxiety (i.e., number of new episodes of major depression or anxiety disorders based on validated self-completed symptom checklists) at 1 year post-intervention. Decision rules for progression through to the full trial will be determined a priori.
Adolescent engagement and participation
Involving adolescents in health research is imperative in order to empower adolescents and make sure their views are taken seriously (Warraitch, Reference Warraitch2022). As part of the ALIVE study, AAGs will be set up at each site to seek adolescents’ views and suggestions for each stage of the study. The aim is to ensure that the ALIVE study, and in particular, the way the intervention is designed and delivered, remains relevant to and informed by young people. An engagement plan will be developed in consultation with adolescents, which includes a mix of activities requested by researchers as well as those suggested by adolescents.
While some evidence is available on how to best involve adolescents in health research (Wilson et al., Reference Wilson, Daxenberger, Dieudonne, Eustace, Hanard, Krishnamurti, Quigley and Vergou2020), the overall evaluation of the impact of adolescents’ involvement in health research is limited (Rouncefield-Swales et al., Reference Rouncefield-Swales, Harris, Carter, Bray, Bewley and Martin2021). We will, therefore, conduct a process evaluation to assess the acceptability and feasibility of involving adolescents in the ALIVE study and how to best involve young people in mental health intervention research in LMICs.
Anticipated challenges
The complex multifaceted problem of mental illness among socio-economically deprived adolescents in LMICs requires an interdisciplinary approach. Likely challenges include: (1) feasibility of delivering an integrated complex multi-modal intervention, in a manner that is theoretically and practically coherent; (2) identifying the best delivery mechanism for the cash transfer component, for example, frequency, quantity, whether provided to parents, adolescents or both; (3) the need to carefully adapt instruments to each context, especially for the neuropsychological tests as these have been much less used and tested in LMICs; (4) ensuring relevant, meaningful, respectful engagement of adolescents; (5) collaboration in an interdisciplinary team, with diverse conceptual approaches, requiring integration of diverse theory and methods; (6) ethical challenges, for example, randomising the receipt of cash transfers in circumstances of poverty; and (7) retention of trial participants over time, given the anticipated 6-months period of intervention implementation and follow-up assessments up to 18 months later.
Potential contributions to the field
An approach focused on causal mechanisms
In the past decade, we have seen a burgeoning number of trials evaluating whether a task-shifting approach to mental health treatment in LMIC works. We propose that the agenda should shift to also examining the ‘black box’ of interventions. A recent Wellcome Trust report states that currently we know too little about what helps prevent or treat youth anxiety and depression and why (Wellcome Trust, 2021). In particular, little consensus exists on what constitutes ‘active ingredients’ (by which we mean those aspects of an intervention that drive effect, are conceptually well defined and link to specific hypothesised mechanisms of action). ALIVE will further the knowledge base by adapting and validating measures to evaluate the role of self-regulation and poverty reduction as potential mechanisms of action in this selective prevention intervention.
Building a stronger evidence base for prevention interventions
There is a lack of evidence for prevention interventions for mental illness for adolescents in LMIC. While accruing evidence for LMIC treatments is a positive development, relying on treatments alone is insufficient to achieve population-level improvements in adolescent mental health due to the limited availability of quality mental health services in many parts of the world (Andrews et al., Reference Andrews, Issakidis, Sanderson, Corry and Lapsley2004; Cuijpers et al., Reference Cuijpers, Pineda, Quero, Karyotaki, Struijs, Figueroa, Llamas, Furukawa and Munoz2021). ALIVE will set out to improve our understanding of how interventions that address social determinants of mental health can prevent adolescent depression and anxiety.
Interdisciplinary approach
Previous research in mental health has tended to be siloed and restricted to the disciplines of psychology and psychiatry, despite knowledge of diverse factors that contribute to mental health and well-being. For this reason, the Lancet Commission on Global Mental Health and Sustainable Development recommends the principle of convergence, which refers to the alignment of evidence from diverse fields, including the genetic, biological, developmental, social and economic determinants of mental health (Patel et al., Reference Patel, Saxena, Lund, Thornicroft, Baingana, Bolton, Chisholm, Collins, Cooper, Eaton, Herrman, Herzallah, Huang, Jordans, Kleinman, Medina-Mora, Morgan, Niaz, Omigbodun, Prince, Rahman, Saraceno, Sarkar, De Silva, Singh, Stein, Sunkel and UnUtzer2018). ALIVE will further advance the knowledge base by bringing together disciplines of economics, social epidemiology, neuropsychology, psychophysiology, public health, psychology and psychiatry to address this complex multifaceted problem.
Policy-relevant evidence for the Sustainable Development Goals
By developing and evaluating an intervention that addresses multidimensional poverty and self-regulation, ALIVE can make contributions to evidence on the integration of mental health into broader development policy and practice. This includes assessing the feasibility, acceptability and cost of delivering a multi-component intervention in culturally diverse, economically deprived communities in Latin America, sub-Saharan Africa and South Asia.
Availability of data and materials
Data and materials from this study are not yet available for sharing as the study is still in the data collection phase.
Acknowledgements
Scientific Advisory Group: Sarah Baird, Judy Bass, Sarah-Jane Blakemore, Pamela Collins, Pim Cuijpers, John-Joe Dawson-Squib, Jamie Hanson, Zeinab Hijazi, Ichiro Kawachi, Berk Özler, Vikram Patel, Tomas Paus, Alan Stein, Argyris Stringaris and Larry Wissow.
Adolescents were consulted at each site in the process of developing this research project.
G.T. is supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital National Health Service Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. G.T. is also supported by the United Kingdom Research and Innovation (UKRI) for the Indigo Partnership (MR/R023697/1) awards. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence (where permitted by UKRI, ‘Open Government Licence’ or ‘Creative Commons Attribution No-derivatives (CC BY-ND) licence’ may be stated instead) to any Author Accepted Manuscript version arising. N.P.L. is supported by the NIHR and Wellcome Trust [222001/Z/20/Z] under the NIHR-Wellcome Partnership for Global Health Research.
Author contributions
Crick Lund and Mark J.D. Jordans are joint first authors.
Financial support
This work was supported by the NIHR (using the UK’s Official Development Assistance Funding) and Wellcome (grant number: 221940/Z/20/Z) under the Department of Health and Social Care (DHSC)–Wellcome Partnership for Global Health Research. The views expressed are those of the authors and not necessarily those of the Wellcome Trust, NIHR or the DHSC.
Competing interests
The authors declare that they have no conflicts of interest in the publication of this work.
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