Skip to main content
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2022 Sep 5.
Published in final edited form as: Lancet Child Adolesc Health. 2017 Oct 9;1(4):258–259. doi: 10.1016/S2352-4642(17)30117-7

Measuring neurodevelopment in low-resource settings

Melissa Gladstone 1,, Amina Abubakar 2, Richard Idro 3, John Langfitt 4, Charles R Newton 5
PMCID: PMC7613512  EMSID: EMS153420  PMID: 30169180

graphic file with name EMS153420-f001.jpg

The burden of neurodevelopmental, cognitive, behavioural, and mental health disorders in children will continue to rise as infant and child mortality is reduced with improvements in medical care.1 In recognition of this epidemiological transition, the international community is shifting the focus from child survival to so-called child thrival, with the aim of supporting children to fulfil their developmental potential and promote their wellbeing. This transition is encapsulated in the WHO Global Strategy for Women’s, Children’s, and Adolescent’s Health 2016–2030: to survive, thrive, and transform. The new Sustainable Development Goals (SDGs) now include a focus on early child development (SDG4) to address this goal.2 In the past 10 years, funding agencies have increased spending on large-scale studies on the underlying causes and epidemiology of these disorders, and on interventional research to improve outcomes. In doing so, researchers and clinicians working in low-income and middle-income countries (LMICs) require reliable and valid tools to screen, identify, and assess children in their local settings.

Most available tools for measuring childhood outcomes were developed and validated in high-income countries and thus reflect the expectations for children of those cultures.3 Clinicians and researchers cannot assume that translating such measurement tools into a local language also transfers its validity, since cross-cultural differences in concepts, norms, beliefs, and values for children’s behaviour are considerable.4,5 At present, no framework or formal guidance has been agreed upon for cross-cultural adaptation and validation. Some tools that are used in LMICs ave been formally adapted on an ad-hoc basis, while others have not.6 Normative data from high-income settings are often used to develop these tools, but some culture-specific items might not be relevant in other settings, or the tools might be poorly and literally translated.7 Only few new tools have been created for use in LMICs.6 Time and effort are needed develop culturally robust tools, and investment in more trained personnel (psychologists and developmental paediatricians) is therefore needed.

In addition to the problem of how to measure outcomes in LMIC settings, there is the problem of which outcomes to measure. The field is wide and multidisciplinary, and spans disciplines of epidemiology, infectious diseases, nutrition, economics, mental health, and education. Many researchers might not necessarily have expertise in the science of measurement, which makes the choice of tools for these studies narrow and predictable. It is difficult to come to a common understanding and framework of what should be measured, let alone how. Organisations such as the World Bank and the Bill & Melinda Gates Foundation have attempted to create repositories of tools.8 However, many tools focus on measuring early child development, and only few are validated for use in assessing cognition, behaviour, and mental health. This often leads to a one-size-fits-all approach9 that might facilitate some cross-country comparisons, but might also fail to reflect important culture-specific and disease-specific outcomes. Moreover, these tools do not take into account the wider agenda of the International Classification of Functioning and Disability (ICF), which emphasises functioning, participation, and the wider family and community environments as vital aspects that need to be considered in most studies.10 For example, most follow-up studies of children affected by congenital Zika virus infection use the Bayley-III screening test score as the major outcome measure even though these children are often severely disabled. The Bayley-III scores provide only some information on the functioning of these children, whereas more information might be gleaned by assessing adaptive functioning, parent–child interaction, and parental wellbeing. Another example is the focus on assessing specific cognitive domains of children with cerebral malaria without measuring the wider aspects of the effect of this disease on the child and family, such as quality of life, participation, and school attendance. Potentially, in areas with poor human resource capacity, a screening programme with appropriately developed screening tools could be implemented and children failing such tests could be assessed in more detail by the few experts.

Further efforts to incorporate the wider ICF framework and to develop internationally agreed guidelines in the adaptation and validation of measurement tools for different settings are needed. This requires funding capacity to enable better triangulation (with external validation) on the use and adaptation of tools in different settings, and an understanding of the use of these outcome measures in multicentre cohort studies. Tools that measure all areas of the ICF framework, are pertinent to local settings, and allow comparison across settings are needed. Such tools will allow researchers to study more robustly the effect of interventions that might treat, support, or prevent an ever-increasing number of children surviving from premature birth, asphyxia, neonatal sepsis, meningitis, and emerging viral infections (eg, congenital Zika virus infection and encephalitis) but who are not thriving.

As we move forward in the new millennium, this shift in focus necessitates an increase in capacity to share expertise and collaborate across diverse global settings, not just within the world of early child development, but more broadly within the framework of disability and the ICF. We propose that the framework of measurement should be consistent to support meta-analysis across settings, but this consistency should be balanced with ensuring that all tools are culturally appropriate and contextually relevant to ensure validity. Without expertise, funding, and capacity building in allied areas (psychology, neuroscience, mental health, therapy-based specialities, education, and social sciences), the agenda, ideas, and ways to progress will be restricted. Finally, the disability agendas need to continue to be connected with views from families and stakeholders, to enable meaningful progression in the future.

Footnotes

We declare no competing interests.

Contributor Information

Melissa Gladstone, Department of Women and Children’s Health, Institute of Translational Medicine, University of Liverpool, Liverpool L12 2AP, UK.

Amina Abubakar, Neuroscience Research Group, Department of Clinical Sciences, KEMRI-Wellcome Trust, Kilifi, Kenya; Department of Psychiatry, Medical Sciences Division, University of Oxford, Oxford, UK; Department of Public Health, Pwani University, Kilifi, Kenya.

Richard Idro, Department of Paediatrics and Child Health, Makerere University, Kampala, Uganda.

John Langfitt, Departments of Neurology and Psychiatry, University of Rochester School of Medicine, Rochester, NY, USA.

Charles R Newton, Neuroscience Research Group, Department of Clinical Sciences, KEMRI-Wellcome Trust, Kilifi, Kenya; Department of Psychiatry, Medical Sciences Division, University of Oxford, Oxford, UK.

References

  • 1.Black MM, Walker SP, Fernald LC, et al. Early childhood development coming of age: science through the life course. Lancet. 2017;389:77–90. doi: 10.1016/S0140-6736(16)31389-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.United Nations. Sustainable development goals; 17 goals to transform our world. 2017. [accessed Sept 17, 2017]. http://www.un.org/sustainabledevelopment/sustainable-development-goals/
  • 3.Henrich J, Heine SJ, Norenzayan A. The weirdest people in the world? Behav Brain Sci. 2010;33:61–83. doi: 10.1017/S0140525X0999152X. [DOI] [PubMed] [Google Scholar]
  • 4.Sternberg R. Culture and intelligence. Am Psychol. 2004;59:325–38. doi: 10.1037/0003-066x.59.5.325. [DOI] [PubMed] [Google Scholar]
  • 5.Lancy DF. The anthropology of childhood: cherubs, chattel and changelings. Cambridge University Press; Cambridge, UK: 2015. [Google Scholar]
  • 6.Sabanathan S, Wills B, Gladstone M. Child development assessment tools in low-income and middle-income countries: how can we use them more appropriately? Arch Dis Child. 2015;100:482–88. doi: 10.1136/archdischild-2014-308114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Palin FL, Armistead L, Clayton A, et al. Disclosure of maternal HIV-infection in South Africa: description and relationship to child functioning. AIDS Behav. 2009;13:1241–52. doi: 10.1007/s10461-008-9447-4. [DOI] [PubMed] [Google Scholar]
  • 8.Fernald LC, Kariger P, Engle P, Raikes A. Examining early child development in low-income countries: a toolkit for the assessment of children in the first five years of life. World Bank; Washington DC: 2009. [Google Scholar]
  • 9.McCoy DC, Peet ED, Ezzati M, et al. Early childhood developmental status in low- and middle-income countries: national, regional, and global prevalence estimates using predictive modeling. PLoS Med. 2016;13:e1002034. doi: 10.1371/journal.pmed.1002034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.WHO. Towards a common language for functioning, disability and health: the ICF beginner’s guide. World Health Organization; Geneva: 2002. [Google Scholar]

RESOURCES