Table 1.

Mapping challenges to solutions, barriers and strategies to bridge local to global actions to empower low- and middle-income countries (LMIC) in the fight against dementia.

Challenges	Solutions	Barriers	Strategies
Culturally valid assessments	• To develop theory-driven cognitive tests to discriminate between normal ageing, non-progressive cognitive impairment, other types of dementia, or depression [12]. • To rely on bespoke rather than off-the-shelf assessments. • To avoid verbal tests which rely on literacy. • To tax low level functions (process pure) rather than complex multidimensional abilities. • To consider relevant cognitive constructs within cultural and behavioural contexts [12,13]. • To validate culturally unbiased tests across a range of equivalent tests currently available.	• Shared understanding of theory-driven assessments (ie, cognitive constructs underpinning these assessments). • Interactions between ageing, culture, and environment (eg, ethnographic factors underpinning stigma and social barriers). • Training of healthcare providers. • Cultural heterogeneity between and within countries (ie, ethnic minorities, stigma). • Lack of shared platforms for data collection, sharing, and big data analysis.	• To set up worldwide initiatives to raise awareness of challenges shared across LMIC (eg, linking LAC-CD & GloDePP). • To work with Diversity and Disparity Initiatives to explore and promote strategies that capture the heterogenous features that preclude standardization of assessments [13]. • To set up communication forums (eg, websites, workshops) to enable interactions, share practices, and encourage collaboration. • To develop integrated data collection, analysis, and sharing platforms.
Providing evidence of brain pathology	• To combine cognitive markers and low-cost technologies that can collect biological data (eg, eye-tracking) [14]. • The STMBT appears promising, and when combined with EEG, accuracy of discrimination should further increase [15]. • Data upload by LMIC clinics for cloud-based automated analysis and production of feedback reports. • Data-driven analyses have the potential to yield novel blood-based biomarkers.	• Training of health care providers and community workers to use novel technologies for dementia. • Identification of optimal set ups for portable assessments (eg, EEG, eye-tracking). • Determining how paradigm delivery could be uniform/controlled across assessment sites. • Large sample sizes are required for the data-driven development of blood-based biomarkers. • Blood-based biomarkers should be developed by training, testing and validating classifier models on diverse populations.	• Interdisciplinary efforts from computer sciences and biomedical engineering is opening new opportunities to implement robust methods such as machine learning algorithms towards data reduction, enhanced classification and diagnosis, and effective analytic pipelines for EEG data [16]. • Behavioural analytics will support the development of potential oculomotor biomarkers for dementia. • Large scale longitudinal research, acquiring a range of oculomotor metrics through tablets and phones, and alongside more established testing regimes, has the potential through machine learning to revolutionise both the diagnosis and the management of dementia. • Exploit data-sharing initiatives and biorepositories to acquire sufficient data for classifier development. • Develop low-cost technologies for point-of-care blood sampling and analytics. • Explore routes for scalable delivery of low-cost peripheral biomarkers for dementia. • Capitalise on emerging initiatives aimed at supporting the development of peripheral biomarkers for dementia [17].
Affordable interventions for dementia	• Lifestyle interventions that could help increase ‘healthy life expectancy’ across the globe [18]. • Use of technology (eg, VR/AR) to slow decline, restore functions, and prolong independent living [19,20].	• Limited awareness about the benefits of non-pharmacological interventions and healthy lifestyles. • Cultural, socio-economic, and ethical barriers which may deter patients and family members from using technology for intervention purposes [19,20].	• Use of information technologies to foster a cultural move towards healthier lifestyles [19]. • Interventions for dementia relying on VR/AR platforms should: i) be available for home use, reducing the financial/time pressure on users and local healthcare providers. ii) Ensure that cloud-based tutorials are developed to enable care-giver training and safe use of technology remotely. • Ethnographic studies to unveil barriers to implement technological development in LMIC.