Abstract
This is the protocol for a Campbell evidence and gap map. The objectives are as follows: to identify and describe the available evidence on interventions designed to improve financial literacy, digital financial skills, financial decision-making, and resilience to fraud and abuse among older adults; map the scope and focus of existing research, including the type of interventions implemented, target populations, delivery modalities, and contextual factors; assess the quality of the types of evidence available, including randomised and non-randomised controlled trials, as well as qualitative studies exploring the effectiveness and acceptability of financial literacy interventions; identify evidence clusters where sufficient studies exist to support further synthesis (e.g., systematic reviews or meta-analyses) and highlight evidence gaps where additional primary research is most needed, and; provide a structured and accessible resource for policymakers, practitioners, researchers, and advocacy groups to inform the design, adaptation, and implementation of financial literacy programmes for older adults.
Keywords
Background
Introduction
The Problem, Condition, or Issue
Global Aging and Financial Vulnerability in Later Life
Global populations are ageing at an unprecedented rate. By 2030, one in six people in the world will be aged 60 years or over, and by 2050, this number is expected to reach 2.1 billion, with the population aged 80+ projected to triple to 426 million (World Health Organisation, WHO, 2022). As individuals live longer and spend more years in retirement, their financial well-being in later life becomes a critical concern.
Evidence from high-income countries highlights the scale of this issue. In the United States (U.S.), for instance, 80% of households aged 60+ are financially struggling or at increased risk of economic insecurity due to rising costs of necessities, healthcare, and long-term care services (Popham et al., 2021). Nearly 50% of people over 50 in the U.S. have no retirement savings (National Council on Ageing, 2021), leaving many older adults reliant on basic pensions or family support to meet their needs (Leung et al., 2022). Even those with some savings often carry debt or face the burden of increasing living costs, leaving them financially vulnerable (Leung et al., 2022). While these figures refer to the U.S., similar concerns are observed globally, although the nature and severity of financial vulnerability vary across high-, middle-, and low-income contexts (Cupák et al., 2021). Such economic insecurity in later life not only undermines healthy ageing but also places significant strain on social support systems (McMaughan et al., 2020).
Moreover, in the current scenario of digitalisation, many older adults with low digital and financial literacy can be exposed to online fraud, data misuse, and scams due to their lack of skills to navigate modern banking securely (Organisation for Economic Co-operation and Development; OECD, 2022). Greater digitalisation can also create new forms of exclusion, particularly for groups with limited digital skills or restricted access to technology, such as older adults. Many older adults use the internet less frequently, often perceiving digital tools as complex or difficult to learn, which reduces their familiarity with online security procedures and increases vulnerability to scams and data breaches. These challenges are compounded by age-related cognitive decline, which may hinder the acquisition of new skills, as well as by heightened anxiety or reduced self-esteem that can discourage engagement with technologies perceived as intimidating (OECD, 2022). Furthermore, digital channels may prompt consumers to make impulsive financial decisions due to the immediacy of access to financial products and services, which can result in adverse outcomes such as increased indebtedness (Banco de Portugal, 2023).
Age-Related Changes Underlying Financial Vulnerability
Understanding how ageing affects economic decision-making is essential to explain financial vulnerability in later life. In particular, age-related cognitive and neurobiological changes play a critical role in shaping how older adults process financial information, evaluate risk, and respond to potential losses.
As individuals age, they may experience a natural decline in certain cognitive abilities such as memory, processing speed, and cognitive flexibility (Salthouse, 2019). These changes can hinder the ability to process complex financial information and make advantageous decisions. Evidence from cognitive psychology and neuroscience has shown, in controlled laboratory settings, that cognitively healthy ageing alters economic decision-making processes, with potentially negative consequences (Lusardi, 2008).
A robust body of literature has demonstrated that, during ageing, the brain areas that compose the reward neural system show decreased activity during the processing of monetary losses, both in their anticipation and occurrence, while neural responses to monetary gains remain preserved (Fernandes et al., 2022; Samanez-Larkin & Knutson, 2015).
These findings are consistent with evidence suggesting that older adults, compared to younger counterparts, exhibit increased attention and improved memory for positive over negative stimuli, a pattern known as the “positivity effect” of ageing (Mather, 2016). A meta-analysis of behavioural economic studies encompassing over 4,000 participants revealed that older adults display paradoxical risk behaviour: they are more risk-seeking than younger adults in contexts where advantageous decisions require caution, but more risk-averse when advantageous decisions require risk-taking (Mata et al., 2011).
These neural and behavioural effects are paradoxical for older adults’ well-being. On one hand, diminished anticipation of losses may contribute to enhanced subjective well-being, but on the other hand, it may also increase susceptibility to financial threats. Such vulnerability could explain the growing incidence of financial abuse and fraud against older adults, who constitute the majority of victims globally (DeLiema et al., 2020).
Financial Literacy as a Response to Financial Vulnerability in Older Adults
Strengthening financial literacy and decision-making abilities among older adults is increasingly recognised as a key determinant of their well-being, independence, security, and quality of life (Lusardi & Mitchell, 2014; OECD, 2022). Financial literacy is commonly defined as the knowledge and skills needed to make important financial decisions, such as where to open a bank account or how to save for retirement (Lusardi, 2008). Low levels of financial literacy are consistently associated with increased vulnerability to fraud, poor financial decision-making, and economic insecurity (Lusardi & Mitchell, 2014; Stolper & Walter, 2017).
Moreover, evidence suggests that financial literacy often deteriorates with age. A longitudinal study found that older adults (mean age 81) had an average baseline financial literacy score of 69.6% (out of 100%), which declined by approximately one percentage point per year. Men score 3.6 percentage points higher than women at baseline, but their likelihood and rates of decline over time do not differ, after controlling for age, income, education, and medical conditions (Boyle et al., 2025). This erosion of financial literacy can significantly impair older adults’ ability to make advantageous decisions, leaving them more vulnerable to financial abuse or fraud (Boyle et al., 2025). This scenario is further exacerbated among populations with lower educational attainment or income, more common in older cohorts, as these factors are associated with poorer financial decision-making (Fong et al., 2021).
Evidence from observational studies conducted in ecological contexts indicates that older adults are disproportionately vulnerable to economic fraud on a global scale. Moreover, the severity of fraudulent schemes successfully targeting this population has been shown to correlate with comparatively low levels of financial literacy (Lusardi, 2008).
Financial abuse, which includes theft of money or property, coercion, financial mismanagement, undue influence or pressure to hand over assets, and the misuse of legal authority (Setterlund et al., 2007), has a global prevalence of 6.8% among adults aged 60 and over (O’Keeffe et al., 2007; Yon et al., 2017). Typically, this type of abuse is perpetrated by a trusted person, which differentiates it from fraud or scams, which are carried out by strangers (Burnes et al., 2017).
Notably, when scams are examined separately, a meta-analysis estimates that they affect 5.6% of U.S. adults aged 70 and older each year (Burnes et al., 2017), highlighting the considerable additional burden posed by financial fraud beyond financial abuse. Importantly, both financial abuse and fraud may have severe and lasting impacts beyond monetary loss. These impacts may compromise older adults’ ability to live independently and diminish their quality of life, restrict their capacity to afford necessary health and social care (Rosen et al., 2019), and lead to significant psychological distress, including social isolation, depression, and suicidal ideation (Deem et al., 2007; Fraga Dominguez et al., 2022).
At the policy level, financial and digital education, financial consumer protection, and financial inclusion are recognized as essential for individual empowerment and the stability of financial systems. These priorities are reflected in G20-endorsed principles on Innovative Financial Inclusion (2010), Financial Consumer Protection (2011), and National Strategies for Financial Education (2012) (OECD, 2020b). Yet, according to the OECD survey of adult financial literacy (2020b), about half of middle-aged adults in OECD countries lack an adequate understanding of basic financial concepts, with older adults and low-income groups scoring significantly lower (OECD, 2020b).
These trends reinforce the need described above to support and protect the financial well-being of the older population. To address these challenges, communities, together with governmental and non-governmental organisations, have increasingly implemented a wide array of programmes aimed at strengthening financial literacy and planning skills among older adults. Recent years have seen a global push to develop interventions tailored to their needs, from retirement planning workshops and money management classes to one-on-one financial coaching and fraud-prevention seminars. Many countries have even incorporated financial education for older adults into their national strategies (OECD, 2022). For example, Portugal’s National Plan for Financial Education supports courses to build digital banking skills among the senior population, and Sweden’s national financial literacy strategy includes the programme “Secure Your Finances in Old Age”, covering pensions, online banking, taxes, and consumer protection (Banco de Portugal, 2023; OECD, 2022).
These initiatives, often developed with banks, consumer protection agencies, and elder advocacy groups, aim to empower older adults to manage their finances confidently and safeguard them from exploitation. Early evidence suggests that improving financial literacy can not only enhance older adults’ financial behaviours but may also confer broader benefits (for instance, higher financial literacy has been linked to better cognitive health outcomes in older age; Yu et al., 2020). Nonetheless, programmes vary widely in content, delivery, and target populations, and their effectiveness is not yet fully understood. This diversity underscores the importance of systematically mapping existing initiatives to better understand what has been attempted, evaluate their effectiveness, and identify the gaps that future programmes should address.
Investigating how to improve financial literacy among older adults is therefore essential to minimize the impact of biopsychosocial vulnerabilities on economic decision-making. Moreover, financial literacy interventions contribute not only to individual autonomy and protection from exploitation but also to broader social and economic stability. For this reason, they are increasingly recognised as central to policies on ageing, consumer protection, and financial inclusion.
These goals align with the United Nations 2030 Agenda, in particular the aims to “ensure healthy lives and promote well-being for all at all ages” and to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (United Nations, 2015).
The Intervention
Financial well-being in later life depends not only on material resources but also on the knowledge, skills, and confidence to make advantageous economic decisions and to avoid becoming vulnerable to economic fraud and abuse. In this context, financial literacy is defined as the knowledge and understanding of financial concepts and risks, as well as the skills and attitudes to apply such knowledge and understanding to make effective decisions across a range of financial contexts, to improve the financial well-being of individuals and society, and to enable participation in economic life (OECD, 2025). With the increasing digitalisation of financial systems, digital financial literacy has become equally important for older adults, being defined as the financial knowledge applied to four dimensions: digital knowledge, awareness of digital financial services, practical know-how of using digital financial services, and the ability to avoid digital fraud (Choung et al., 2023).
Considering this background, we will investigate interventions that aim to strengthen financial and digital financial literacy, as well as decision-making abilities among older adults. These interventions may operate at multiple levels: • Individual-focused education and training: Structured financial literacy and digital financial literacy programmes, retirement planning workshops, online or face-to-face courses on budgeting, saving, debt management, and pension planning. • Fraud and abuse prevention initiatives: Seminars, campaigns, and tailored training designed to help older adults recognise, avoid, and respond to financial fraud, scams, or undue influence. • Digital financial literacy programmes: Interventions to enhance skills in online banking, digital payment systems, cybersecurity, and safe digital financial practices. • One-to-one financial guidance or counselling: Individual financial training, advisory services, or case management tailored to older adults. • Community and peer-support models: Intergenerational financial literacy and digital financial literacy education, peer-led groups, and community-based initiatives aimed at building confidence and resilience. • Policy-led national strategies: National plans and government programmes that incorporate financial education for older adults, often in collaboration with banks, regulators, and consumer protection agencies. • Multi-component programmes that may combine financial education with health or social support.
These interventions may be delivered through diverse modalities, including classroom-based education, online platforms, hybrid approaches, printed materials, or personalised support. Importantly, effective interventions often adapt delivery to age-related cognitive, emotional, and technological needs (e.g., using simplified language, user-friendly digital interfaces, personalised assistance, or anxiety-reducing pedagogical approaches).
Why Is It Important to Develop the EGM?
As populations age, ensuring financial well-being in later life has become a pressing social, economic, and public health concern. Older adults are disproportionately exposed to financial insecurity, limited retirement savings, and rising costs of living, which can undermine their independence, well-being, and quality of life. In parallel, cognitive and affective changes associated with ageing, combined with the rapid digitalisation of financial services, increase the risk of poor financial decision-making, reduce financial literacy, and enhance vulnerability to fraud and abuse. These risks carry not only immediate financial consequences but also long-term psychological and social impacts, such as reduced access to care, isolation, and loss of autonomy.
In response, a growing number of financial literacy and digital literacy interventions have been developed worldwide to support older adults. These include national strategies, community-based programmes, individual financial counselling, and targeted fraud-prevention initiatives. However, interventions vary widely in scope, delivery mode, and target population. Their effectiveness and equity impacts remain unclear, particularly for subgroups most at risk, such as women, low-income older adults, and those with limited digital access or lower educational attainment.
Thereby, despite the growing attention to financial literacy in older age, the landscape of research and evidence on what works in this area remains fragmented and unclear. Stakeholders, including policymakers in ageing and finance, service providers, and older adults’ representatives, lack a clear overview of which financial literacy interventions have been evaluated, in what contexts, and with what results. It is currently uncertain what the scale and focus of existing research on financial literacy programmes for older adults are, or where critical knowledge gaps remain.
An evidence and gap map (EGM) is therefore warranted to systematically gather and visualize the available evidence. By mapping out all relevant studies and reviews, an EGM can identify areas where there is sufficient research to inform policy or to conduct full systematic reviews, and, more importantly, highlight areas where little or no evidence exists, and further primary research is needed. The ultimate goal is to support efficient research prioritization and decision-making. Evidence gap maps are explicitly designed to inform strategic policy and programme decisions by making the state of evidence accessible to decision-makers (Saran & White, 2018).
In line with this purpose, the scope of the present EGM has been formulated in accordance with the guidelines issued by government policymakers, financial education practitioners, and older-adult advocacy organizations (OECD, 2020a, 2020b, 2022, 2023; Banco de Portugal, 2023) to ensure it addresses the most pressing questions and information needs. These guidelines emphasize the need for interventions that go beyond the theoretical knowledge, focusing on practical skills for daily financial management, resilience against increasingly sophisticated digital fraud, and the promotion of financial autonomy as a pillar of healthy ageing.
By considering the guidelines of these stakeholders in defining the EGM’s focus, we aim to produce a resource that is directly relevant to those who will use it, helping guide future investments in research and practice on financial literacy programmes for the ageing population.
This protocol outlines the rationale and approach for developing the EGM, which will map the existing evidence on financial literacy interventions for older adults and identify gaps where new research or evaluations are most urgently needed.
Objectives
This EGM aims to systematically identify, organise, summarise, and present the available evidence on financial literacy interventions targeting older adults aged 60 and above, including digital financial literacy and fraud-prevention initiatives. Specifically, this EGM seeks to: 1. Identify and describe the available evidence on interventions designed to improve financial literacy, digital financial skills, financial decision-making, and resilience to fraud and abuse among older adults. 2. Map the scope and focus of existing research, including the type of interventions implemented, target populations, delivery modalities, and contextual factors. 3. Assess the quality of the types of evidence available, including randomised and non-randomised controlled trials, as well as qualitative studies exploring the effectiveness and acceptability of financial literacy interventions. 4. Identify evidence clusters where sufficient studies exist to support further synthesis (e.g., systematic reviews or meta-analyses) and highlight evidence gaps where additional primary research is most needed. 5. Provide a structured and accessible resource for policymakers, practitioners, researchers, and advocacy groups to inform the design, adaptation, and implementation of financial literacy programmes for older adults.
In fulfilling these objectives, this EGM will systematically synthesise and map the available evidence, identifying what types of interventions have been implemented, which populations have been reached, the delivery methods employed, and the outcomes assessed. At the same time, it will highlight critical knowledge gaps that constrain the effectiveness, reach, and equity of current financial literacy efforts, thereby guiding the development of future research and policy. By doing so, the EGM will strengthen the connections between research, policy, and practice in the fields of ageing, consumer protection, and financial inclusion, while also supporting the strategic prioritisation of resources to ensure that older adults are equipped to safeguard their financial well-being, independence, and quality of life.
Methods
Evidence and Gap Map: Definition and Purpose
EGMs are designed to highlight what research exists on a given topic, while also pointing out where evidence is missing. Their purpose is to guide strategic priorities in health, social policy, programmes, and future research (Welch et al., 2021). EGMs can reveal areas where there are few or no primary studies, or where many studies exist but no systematic review has yet been conducted. They can also highlight cases where a large number of reviews are available, suggesting that umbrella reviews may be appropriate (White et al., 2020). The goal of an EGM is to help users quickly identify and access the most relevant evidence (or gaps in evidence) related to specific populations and interventions. To achieve this, we will follow a five-step process: 1. Define a framework. 2. Identify all available evidence. 3. Assess the quality of the evidence. 4. Extract, code, and summarize data linked to our objectives. 5. Present the findings visually in a clear and accessible way.
For this project, we will use the Campbell Collaboration’s mapping tool, developed by the EPPI-Centre (https://eppi.ioe.ac.uk/cms/default.aspx?tabid=3790), to display the studies we identify within the agreed framework.
Framework Development and Scope
The framework for this EGM was developed through an iterative process combining (i) a review of strategic policy documents and national guidelines on financial literacy and consumer protection for older adults (e.g., OECD, WHO, Banco de Portugal, United Nations), (ii) consultation with stakeholders including policymakers, practitioners, older-adult and older adults’ organisations, and (iii) adaptation of existing conceptual frameworks for financial literacy and digital financial literacy (Choung et al., 2023; OECD, 2025). This approach ensures that the EGM addresses the most pressing knowledge needs for both researchers and decision-makers.
Specifically, we identified key intervention domains and outcomes of interest. Early discussions with financial education practitioners and elder advocacy groups highlighted priority areas such as fraud prevention and both financial and digital financial literacy, accounting for cognitive and affective age-related changes associated with later life. These inputs guided the structure of our intervention categories and the outcomes to be mapped.
The scope of the EGM is therefore defined by interventions aimed at improving financial literacy, digital financial literacy, economic decision-making, and resilience to fraud and abuse among older adults aged 60 years and above. The definitions of these variables are provided below: • Financial literacy: is defined as a combination of financial awareness, knowledge, skills, attitude, and behaviours necessary to make sound financial decisions and ultimately achieve financial well-being (OECD, 2022). This implies having the understanding and confidence to manage personal finances wisely, from budgeting and saving to informed investing. In the context of ageing, international bodies emphasize tailoring financial education to older adults’ needs. For instance, the OECD recommends programmes for older adults focusing on retirement planning and prevention of financial fraud (OECD, 2022). • Digital financial literacy: extends the concept of financial literacy into the online context, referring to the capacity to safely use digital technologies for financial services. It is defined as a combination of knowledge, skills, attitudes, and behaviours necessary for individuals to be aware of and safely use digital financial services and digital technologies with a view to contributing to their financial well-being (OECD, 2022). Individuals with digital financial literacy can navigate online banking, mobile payments, and fintech applications securely and effectively. This is especially pertinent for older adults in an increasingly digitised society. Many older adults face lower digital skills and confidence, which can exclude them from online financial services (OECD, 2023a, 2023b). International strategies call for empowering older adults with digital financial know-how to ensure they can manage finances online and avoid cyber-fraud. The emphasis is on equipping older adults to confidently engage with digital banking and payments, while adopting safe online behaviours to protect themselves (OECD, 2023a, 2023b). • Economic decision-making: in the ageing context, economic decision-making refers to the process and capacity of older adults to make informed choices about financial and economic matters affecting their lives. This can range from daily budgeting and expenses to major decisions about savings, investments, pensions, or care costs. It is recognized as a crucial facet of autonomy in later life. For example, United Nations consultations on ageing argue that older adults have the right to make decisions in all aspects of life, including choices about their property, income and finances (Sleap, 2018). In academic terms, economic decision-making involves cognitive and deliberative processes such as weighing costs and benefits, considering future needs, and selecting among financial options. It also involves affective processes such as positive affect to approach rewarding decisions and negative affect to avoid harmful ones (Samanez-Larkin & Knutson, 2015). Ageing can introduce challenges, such as cognitive decline or reduced neural processing of anticipated and received losses or complexity of choices, that affect decision-making competence (Samanez-Larkin & Knutson, 2015). In sum, economic decision-making denotes an older individual’s ability to autonomously manage and decide on financial affairs, which is fundamental for their autonomy and economic well-being. • Resilience to fraud and abuse: in the ageing context, it refers to older adults’ ability to withstand, avoid, and recover from attempts of financial exploitation or other forms of elder abuse. The WHO states abuse as a single or repeated act, or lack of appropriate action, occurring within any relationship where there is an expectation of trust, which causes harm or distress to an older person,” and this includes financial or material abuse (misuse of an older person’s money, property or assets; WHO, 2024; OECD, 2020a). On the other side, fraud against older adults, including scams, identity theft, or coercive asset transfers, is one common type of financial abuse. Building resilience to fraud and abuse means empowering older adults with the knowledge, vigilance, and support needed to recognize, resist, and recover from exploitation, thereby preventing financial harm and safeguarding their rights and security (OECD, 2023a, 2023b).
The framework will organise evidence along two principal dimensions: • Interventions (rows of the map): interventions targeting categories of financial literacy and digital financial literacy, economic decision-making, and prevention of fraud and abuse, as described above. • Outcomes/experiences (columns of the map): measures relating to financial knowledge, skills, and behaviours (e.g., budgeting, saving, debt management, fraud avoidance), digital competencies, autonomy, confidence, well-being, and resilience to financial exploitation, alongside qualitative evidence on acceptability and user experience.
The EGM framework will inform the inclusion and exclusion criteria of the EGM.
Stakeholder Engagement
Stakeholders’ involvement is a central component of this EGM, as it ensures that the scope, framework, and guiding questions reflect the real-world needs of decision-makers, practitioners, and older adults’ representatives.
In this protocol, the current framework, policy concerns, and key questions have already been shaped through a combination of the analysis of major international stakeholder documents, including strategic guidelines and policy frameworks from the WHO, the United Nations, the OECD, and national-level strategies such as those of the Banco de Portugal with preliminary consultations with academic experts in financial education and gerontology. This process ensured that the initial scope of the EGM reflects the most pressing concerns identified by global and national authorities in ageing, consumer protection, and financial education.
For the next stages of the project, a formal Advisory Group will be convened to guide the refinement and implementation of the EGM. This Advisory Group will bring together multidisciplinary expertise, including specialists in law, economics, criminology, gerontology, psychology, and neuropsychology. Where feasible, representation from different sectors will be sought, including public sector institutions (e.g., ministries or regulatory bodies), as well as non-governmental and civil society organisations working in ageing, consumer protection, or financial education.
In addition, a group of older adults aged 60 and older will be included to ensure that the perspectives and lived experiences of the target population are directly represented. These participants will be recruited through community, senior citizens’ associations, or partner institutions working with older adults.
The stakeholders’ engagement process will follow a flexible and iterative approach. Consultations may include presential and/or online group discussions (e.g., focus groups), individual feedback via email, or other appropriate formats depending on stakeholders’ availability and preferences. Stakeholders will be invited to provide input on the scope and structure of the EGM, including the classification of interventions and outcomes, and to suggest potentially relevant areas of evidence or gaps.
At later stages, stakeholders may be consulted to review preliminary findings and provide input on the interpretation of results and their relevance for policy and practice. This process aims to ensure that the EGM is both methodologically robust and aligned with user needs, while remaining feasible and proportionate to available resources.
Conceptual Framework
This EGM is grounded in a behavioural – ecological model that integrates: (1) theories of ageing and economic decision-making (2) behaviour change models applied to financial literacy and digital financial literacy, and (3) ecological and consumer-protection perspectives for fraud prevention (Figure 1). 1) Mechanisms underlying age-related differences in financial and economic decision-making. • Psychosocial mechanisms: Socioemotional Selectivity Theory posits that individuals perceive future time horizons diminish with age. This is thought to shift goal orientation, from future- to present-focused, and from self-centered to other-oriented (Carstensen, 1992, 2006). Moreover, according to the “Positivity Effect” of ageing (Mather, 2016), individuals appear to pay more attention to, and better remember, positive information compared to negative information. These psychosocial age-related changes may attenuate risk anticipation and reduce the salience of fraud cues. • Cognitive mechanisms: Ageing is associated with a normative cognitive decline (e.g., slower processing speed, working memory deficits, reduced flexibility; Salthouse, 2019). As a result, the task demands moderate the effects of ageing on economic and financial decision-making, which may explain why age-related differences in economic preferences are more pronounced in tasks with uncertainty and high demands on learning, memory, or cognitive flexibility than in tasks involving risk (Mata et al., 2011). • Neurobiological mechanisms: Among the theories explaining the neurobiological mechanisms for age-related differences in decision-making, the Affect–Integration–Motivation (AIM) framework (Samanez-Larkin & Knutson, 2015) is an influential one. This model conceptualizes economic decisions as the outcome of three sequential stages: affective responses, which elicit anticipatory emotions in response to potential gains or losses; integration processes, which combine these affective signals with higher-order evaluations to assign subjective value to each option; and motivational mechanisms, which translate the integrated evaluation into motor actions. Younger adults had stronger neural responses to both rewards and losses, while older adults had a reduced neural processing to losses as shown by blunted neural responses in reward circuits despite a preserved sensitivity to gains. Ageing also impairs integration neural signals, which can be moderated by cognitive decline (Fernandes et al., 2022; Samanez-Larkin & Knutson, 2015). 2) Theoretical models of behaviour change and their application to financial and economic decision-making. • The Capability, Opportunity, Motivation – Behaviour (COM-B) Model (Michie et al., 2011) provides a comprehensive framework for understanding how and why people change their behaviour. According to the model, behaviour (B) is the result of the dynamic interaction between three components: (1) Capability (C) refers to both the physical and psychological capacity to engage in a behaviour, which includes having the necessary knowledge and skills. In the context of financial literacy, this means understanding financial concepts, being able to navigate digital platforms, and applying practical skills such as budgeting or recognizing fraud cues; (2) Opportunity (O) encompasses all external factors that make a behaviour possible or prompt it, such as access to secure financial tools, supportive social networks, or inclusive service design. For older adults, this may involve user-friendly banking platforms, community workshops, or family support systems; (3) Motivation (M) refers to the internal processes that energize and direct behaviour, including reflective elements such as beliefs, intentions, and risk perceptions, as well as automatic processes like habits or emotional responses. Building self-efficacy, reinforcing social norms around fraud prevention, and reducing financial anxiety are examples of motivational drivers. • Nudge Theory (Mertens et al., 2022; Thaler & Sunstein, 2008) shows that structuring choices in simpler, clearer ways (such as through stepwise tasks, checklists, or defaults) may reduce cognitive load and compensate for age-related declines in memory and attention, thereby supporting better financial decisions. • Protection Motivation Theory (Rogers, 1983) highlights how decision-making can be shaped by changing perceptions of risk and coping capacity. By increasing threat appraisal (e.g., understanding the severity of fraud) and coping appraisal (e.g., confidence in preventive strategies), interventions can reduce risky behaviours and promote resilience to exploitation. • Technology Acceptance Model explain how individuals’ behaviour with technology are influenced by perceptions of usefulness, ease of use, and technological anxiety. In this context, by reducing barriers to adoption and building trust in digital tools by older adults, interventions can increase willingness to engage with secure online financial services, which in turn shapes everyday decision-making in increasingly digital financial environments. 3) Ecological and equity factors shaping financial and economic decision-making. The effectiveness of these intervention models depends not only on the individual but also on the ecological context and equity factors that shape opportunities for financial well-being. An ecological lens considers multiple layers of influence: • Individual level: Enhancing capability through financial knowledge, digital skills, and cognitive supports; • Interpersonal and community level: Leverageing family, peers, and community organisations to provide opportunity structures, such as intergenerational learning programmes or local workshops that reinforce social norms around safe financial behaviour. • System and market level: Designing accessible financial products, user-friendly digital platforms, and proactive fraud-prevention tools that reduce barriers for older adults. • Policy level: Embedding financial literacy into national ageing and consumer protection strategies, regulating providers to ensure transparency and fairness, and mandating inclusive service design. Conceptual Framework
An equity perspective further ensures that interventions reach those at greatest risk of financial vulnerability. To this purpose, interventions can be tailored and evaluated by gender, income, education, rurality, age (e.g., 80+), disability, or social capital. For example: • Gender-sensitive design may address women’s lower average financial literacy and longer life expectancy. • Income- and education-sensitive programmes may simplify content for low-literacy groups and provide affordable access to digital tools. • Rural outreach may require hybrid or offline delivery to overcome digital exclusion. • Support for the very old or cognitively impaired may involve one-to-one counselling, guardian networks, or simplified decision aids.
Below, we hypothesize how the application of these theoretical models of behaviour change may lead to different responses across the four intervention domains: 1. Financial literacy programmes: Build competence by strengthening understanding of key concepts (e.g., interest, inflation, diversification, and pensions) and practical rules (e.g., budgeting and debt management) may foster participants’ advantage decisions, self-efficacy and confidence. Moreover, reducing cognitive load through age-appropriate materials that use simplified language, visuals, and repetition may also improve financial efficacy, well-being, and autonomy. 2. Digital financial literacy programmes: Emphasize procedural know-how (e.g., including secure logins, digital payments, mobile banking, and the use of fintech tools) may enhance metacognitive risk awareness, enabling participants to recognize phishing, identity theft, and social engineering attempts. Practice with real devices, combined with scaffolding techniques such as tutorials, repetition, and cues, reinforces procedural memory. These efforts may generate intermediate outcomes such as increased digital competence, more secure use of online services, and reduced technological anxiety. In the longer term, they may reduce security incidents, expand digital financial inclusion, and support sustained access to financial services. 3. Economic decision-making: Interventions that support decision-making capacity aim to strengthen evaluative processes, planning, and the integration of affective and cognitive information. Tools such as checklists, simplified comparison tables, and stepwise planning aids can reduce complexity and facilitate informed choices about savings, pensions, and investments. Nudges and default options may help older adults avoid inaction or impulsive decisions, while counseling and mentoring can provide compensatory executive support for individuals with cognitive decline. By fostering reflection, reducing decisional conflict, and supporting long-term planning, these interventions may generate intermediate outcomes such as more consistent financial preferences, improved risk–benefit evaluation, and greater alignment between choices and personal goals. In the longer term, they may contribute to enhanced financial stability, reduced susceptibility to costly errors, and stronger autonomy in managing economic challenges. 4. Resilience to fraud and abuse: Interventions targeting fraud prevention and resilience work by rebalancing risk salience, countering the positivity effect, and reinforcing protective routines. Training that uses realistic scenarios, red-flag rules (e.g., “never share passwords”), and repeated exposure to common fraud schemes enhances recognition and response efficacy. Social and institutional support (e.g., guardian networks, bank alerts, or community hotlines) strengthen coping appraisal and provide external monitoring. At the same time, interventions that foster self-efficacy and normalize reporting may reduce stigma and encourage proactive help-seeking. These mechanisms may result in intermediate outcomes such as greater fraud detection, higher refusal rates of suspicious requests, and increased reporting to authorities. Ultimately, they reduce victimisation, financial losses, and psychosocial harms, thereby safeguarding older adults’ well-being and trust in financial systems.
Dimensions
The goal of this EGM is to provide a structured overview of the global evidence on interventions to strengthen financial literacy and digital financial literacy, as well as related capacities among older adults (60+), identifying targeted populations, settings, and delivery formats, and highlighting where evidence is lacking to inform future research, practice, and policy. It will encompass programmes, strategies, and tools aimed at improving financial literacy, digital financial literacy, economic decision-making, and resilience to financial abuse and fraud. To this purpose, when present, the following interventions and outcomes will be analyzed:
Interventions (Rows in the Map)
1. Financial literacy • Scope: Interventions that build knowledge, skills, attitudes, and behaviours for day-to-day personal finance (e.g., budgeting, saving, borrowing, pensions, consumer rights). • Examples of Included Components: Classroom or community courses; retirement-planning workshops; rule-of-thumb training; printed toolkits; calculator/worksheet use; cognitive-load–aware materials (plain language, chunking, repetition). • Exclusions: Product marketing/sales and policy changes without an educational/behaviour-change component. 2. Digital financial literacy • Scope: Knowledge, practical know-how, attitudes, and behaviours to safely use digital financial services (online/mobile banking, digital payments, fintech) and to navigate platforms securely. • Examples of Included Components: Hands-on training in secure log-ins/2FA, app navigation, payments/transfers; simulated phishing detection; device setup clinics; helplines or digital buddies. • Exclusions: General digital skills (e.g., email basics) without explicit financial tasks; untested app/tool descriptions; cybersecurity policies with no user-facing training. 3. Economic decision-making • Scope: Interventions that improve the process quality of financial choices (planning, option comprehension, risk perception, cost–benefit evaluation), including decision aids and choice architecture. • Examples of Included Components: Checklists and decision aids; defaults/commitment devices; simplified option menus; future-needs planning tools; nudges that reduce complexity or highlight risks/costs. • Exclusions: Information without an explicit decision-support mechanism; macro nudges implemented by providers without evaluation at the older-adult user level. 4. Resilience to fraud and abuse • Scope: Interventions that increase recognition, avoidance, reporting, and recovery regarding financial exploitation, scams, and undue influence (including abuse within relationships of trust). • Examples of Included Components: Red-flag rules and scam scenario drills; “just-in-time” warnings; verification routines; guardian/monitoring networks with banks/telecoms; reporting/help-seeking pathways; rights education. • Exclusions: Law-enforcement or regulatory actions without an educational/behaviour-change element directed at older adults; general crime-prevention messaging not evaluated for financial harms.
Interventions may be delivered in diverse formats and settings, including community centres, healthcare services, senior organisations, or through digital and remote platforms. Modalities may take the form of educational workshops or seminars, one-to-one financial counselling, printed materials and toolkits, mobile applications, interactive websites, or comprehensive multi-component programmes that combine financial education with other forms of support, such as digital literacy or health-related services. All geographic regions are eligible, and studies published in English, Portuguese, or Spanish, with no restriction on publication date, will be considered.
If we identify intervention programmes within the eligible domains that do not assess effectiveness (e.g., descriptive studies, implementation studies, or qualitative research focusing on acceptability, feasibility, or user experience), these will be included and coded separately. Specifically, such studies will be mapped according to intervention characteristics (e.g., type, delivery mode, target population). If an intervention clearly targets more than one intent (e.g., digital financial skills and scam avoidance), the data will be co-code under each relevant row. Additionally, if only one subgroup is 60 years or older, only data from this group will be coded. Studies with mixed-age samples will also be included, provided that the mean age of participants is 60 years or above. We will exclude interventions that do not explicitly target financial literacy, digital financial literacy, decision-making, or fraud resilience; general economic or social programmes without a financial education component; and interventions aimed exclusively at younger adults.
Outcomes (Columns in the Map)
We are interested in the characteristics, implementation, effectiveness, feasibility, acceptability, and potential unintended consequences of intervention programmes aimed at enhancing financial literacy and digital financial literacy, economic decision-making, and resilience to economic fraud and abuse. Accordingly, the outcomes captured in this map span multiple dimensions, ranging from cognitive and behavioural changes to psychosocial, digital, and systemic impacts, as detailed below: • Financial knowledge and understanding: Objective or self-reported knowledge of core financial concepts (e.g., standardized financial literacy tests; item banks; tailored quizzes; scenario-based assessments). • Financial skills and behaviours: Observable or self-reported financial practices relevant to day-to-day management (e.g., budgeting; timely bill payment; saving; debt management; pension planning; avoidance of unnecessary fees; record-keeping). • Digital competencies in the financial context: Capacity to perform digital financial tasks securely and effectively (e.g., secure log-in execution; online payment completion; phishing or scam recognition; use of two-factor authentication; error rates on digital tasks). • Economic decision-making quality: Processes and outcomes of financial decision-making, including risk perception, option comprehension, cost–benefit • Linked to financial management. (e.g., self-efficacy scales; financial confidence; perceived control; measures of financial anxiety or reduced stress). • Financial well-being and stability: Overall material and subjective financial situation of the individual (e.g., ability to meet expenses; emergency savings; indebtedness levels; subjective financial well-being scales). • Acceptability, feasibility, and user experience: Older adults’ perceptions of intervention relevance, usability, and burden (e.g., qualitative interviews/focus groups; satisfaction ratings; cultural appropriateness; perceived barriers/facilitators evaluation, and decisional satisfaction (e.g., decision aids use; risk comprehension tasks; measures of decisional conflict or regret; behavioural economics tasks such as lotteries, delay discounting, among others). • Resilience to fraud and abuse: Abilities, attitudes, and behaviours that protect older adults from financial exploitation, including recognition, refusal, reporting, and recovery (e.g., recognition of scam cues; reporting rates; self-reported refusal efficacy; incidence of victimisation; financial losses prevented/recovered). • Autonomy, confidence, and self-efficacy: Psychological and perceived-control outcomes. These domains will also capture evidence from qualitative and process-oriented studies. • Adverse effects or unintended consequences: Negative or unintended outcomes resulting from the intervention (e.g., increased scam exposure following online onboarding; anxiety or stress due to training; data breaches; exclusion of very old or low-literacy participants).
Types of Study Design
This EGM will include a wide range of study designs to capture the diversity of financial literacy interventions and their outcomes for older adults. Given the exploratory and mapping nature of the EGM, both quantitative and qualitative evidence will be included, with different types of evidence linked to specific stages in the causal chain and types of outcomes. In addition to completed studies, ongoing studies (e.g., registered trials and protocols) will be identified and documented to provide a comprehensive overview of the evidence landscape. However, due to the absence of results, these will not be included in the main EGM matrix.
Included Study Designs
1. Quantitative studies. These will be used primarily to assess the effectiveness of interventions on final outcomes (e.g., behaviour change, financial decision-making, fraud reduction): • Randomised controlled trials (RCTs); • Quasi-experimental studies with comparison groups (e.g., matched control groups, regression discontinuity, difference-in-differences); • Pre–post intervention studies (with or without control groups); • Cross-sectional surveys reporting outcome data post-intervention, 2. Qualitative studies. These will help assess barriers, facilitators, and perceptions, particularly in understanding reach, relevance, and acceptability: • Qualitative interviews or focus groups; • Case studies describing implementation experiences; • Process evaluations using qualitative methods; • Participatory research involving older adults. 3. Mixed-methods studies. Studies combining quantitative outcome evaluation with qualitative process evaluation will be included in full, with components analysed accordingly. 4. Descriptive and implementation studies. These will be included to map coverage and reach, provided that they describe or assess an intervention: • Studies reporting on programme implementation, uptake, and scalability; • Studies assessing success in reaching target populations, regardless of outcome evaluation. 5. Grey literature. In the category of grey literature, we will include intervention programmes developed and/or evaluated by governmental and non-governmental organisations, as many initiatives in this field are implemented outside the academic sector.
Excluded Study Designs
• Editorials, opinion pieces, or theoretical papers without empirical data; • Protocols without published or completed results; • Reviews (systematic, scoping, or narrative), although their reference lists may be used to identify eligible primary studies; • Commentaries, conference abstracts, or brief communications lacking sufficient methodological detail; • Purely observational or cross-sectional studies that do not involve any intervention (e.g., studies solely assessing levels of financial literacy, cognitive functioning, or decision-making abilities in older adults without the delivery of a programme, training, or initiative).
This inclusive approach allows the EGM to reflect both the effectiveness and the implementation landscape of financial literacy interventions for older adults.
Types of Intervention/Problem
The EGM will include any intervention explicitly aimed at enhancing financial literacy or financial capability in this age group. The specific types of interventions and their categorisation have already been detailed in the dimensions’ framework section, and this subsection provides only a general overview. These interventions may be delivered in diverse formats and settings, such as community centers, healthcare services, senior organisations, or through digital and remote platforms. They may take the form of educational workshops or seminars, one-on-one financial counseling, printed materials and toolkits, mobile applications, interactive websites, or comprehensive multi-component programmes that combine financial education with other forms of support, such as digital literacy or health-related services.
The scope of the EGM covers interventions implemented in all geographic regions and published in English, Portuguese, or Spanish, with no restrictions on publication date. However, the EGM will exclude interventions that do not explicitly target financial literacy or do not focus on individuals aged 60 and over. General economic or social programmes without a financial education component, or those aimed exclusively at younger adults, will also be excluded. Moreover, we will exclude studies that do not evaluate an intervention, such as purely observational or cross-sectional research assessing financial literacy, cognitive functioning, or decision-making abilities in older adults without any programme, training, or initiative being implemented.
Types of Population (as Applicable)
The population included in this EGM consists of older adults aged 60 years and above, regardless of gender, socio-economic status, cognitive capacity, living situation, or geographic location. Studies will be included if they specifically target individuals or groups in this age category, or if the reported data can be disaggregated to focus on this population. The scope will cover both community-dwelling and institutionalized older adults, and will consider subpopulations such as low-income older adults, older adults with limited digital skills, individuals at risk of financial fraud, or those experiencing cognitive decline, as these groups may be particularly vulnerable in the context of financial decision-making.
No restrictions will be placed on country or region; evidence from high-, middle-, and low-income settings will be considered to ensure global relevance. This inclusive approach allows the EGM to capture equity-related dimensions, particularly by highlighting interventions that address disparities in financial literacy outcomes among marginalized older populations.
Studies that focus exclusively on adults under the age of 60, or that include older adults without providing age-specific results, will be excluded. Likewise, programmes targeting general adult populations without tailoring content or analysis to the needs of older individuals will not be considered eligible for inclusion.
Types of Outcome Measures (as Applicable)
The outcomes included in this EGM will reflect the wide range of benefits that financial literacy interventions may aim to achieve for older adults. These outcomes will be used to organize the evidence within the intervention–outcome framework of the EGM. They are grouped into primary and secondary outcomes based on their centrality to the aims of financial literacy interventions. This list will be further refined during the full protocol stage.
Primary Outcomes (Core Financial Literacy Goals)
• Improved financial knowledge or understanding (e.g., knowledge of budgeting, interest rates, savings, pensions); • Enhanced financial decision-making ability; • Increased self-efficacy or confidence in managing financial matters; • Changes in financial behaviours (e.g., saving, budgeting, paying bills, avoiding unnecessary debt); • Fraud prevention awareness or reduced susceptibility to scams; • Digital financial literacy (ability to safely and effectively use online/mobile financial tools).
Secondary Outcomes (Related to Broader Well-Being and Intervention Implementation)
• Financial well-being or perceived financial security; • Emotional outcomes related to finances (e.g., reduced financial stress or anxiety); • Quality of life or autonomy associated with improved financial control; • Social inclusion (e.g., improved ability to participate in financial activities or services); • Programme engagement, satisfaction, or acceptability; • Feasibility or cost-effectiveness of interventions; • Changes in caregiver or family involvement in financial matters (if reported).
Excluded Outcomes
• Outcomes unrelated to financial literacy, such as general health or cognitive outcomes without a financial component; • Broad economic indicators at the population level (e.g., GDP, national debt levels); • Outcomes from interventions that do not explicitly aim to improve financial literacy or capability.
The EGM will aim to capture both quantitative and qualitative outcome data, noting how outcomes are measured (e.g., standardized assessments, self-reports, behavioural tracking).
Other Eligibility Criteria
Studies published in English, Portuguese, or Spanish will be included. Studies in other languages will be excluded due to feasibility constraints.
EGM Inclusion and Exclusion Criteria
Search Methods and Sources
We will conduct comprehensive searches across multiple information sources to identify all relevant studies for this EGM. Electronic bibliographic databases will include PubMed, Scopus, APA PsycINFO (via the APA PsycNet platform), ERIC (through its official web interface), and Web of Science Core Collection, covering literature from biomedical, psychological, educational, and other multidisciplinary fields.
In addition, we will search grey literature sources to capture reports and materials not indexed in academic databases. These will include websites of government and international organisations, and non-governmental organisation (NGO) websites (e.g., OECD, World Bank, European Commission, Banco de Portugal, HelpAge International, and Age Platform Europe), as well as Google Scholar. For Google Scholar, we will systematically screen the first 100 results ordered by relevance and the first 100 results ordered by recency, to balance comprehensiveness with feasibility. These comprehensive searches will be conducted from database inception to 31 January 2027 (the planned cut-off date before finalisation of the EGM).
This multifaceted approach is designed to retrieve both published research and programme documentation, recognizing that many financial literacy initiatives for older adults are implemented outside the academic sector and may only be documented in policy reports or organisational publications. All searches will be performed up to the most recent available date at the time of search (with search dates to be documented for transparency), ensuring the inclusion of the latest evidence. No restrictions on publication date will be applied to any of the searches, allowing us to capture the full historical evolution and breadth of financial literacy interventions targeting older adults. This decision is justified by the need to understand how such interventions have developed over time while avoiding inadvertently excluding older studies that could offer valuable insights into long-term trends or the origins of current practices. We will also apply language criteria in line with our eligibility parameters: only studies available in English, Portuguese, or Spanish will be included, while items in other languages will be excluded for feasibility. These three languages cover a broad range of literature and are those in which the review team is proficient, thereby balancing inclusiveness with practical considerations of screening and analysis.
The search strategies will be tailored to each database to ensure sensitivity and relevance. We will develop specific search queries for each bibliographic database, using appropriate controlled vocabulary and keywords (for example, MeSH terms in PubMed and Thesaurus terms in PsycINFO) combined with free-text terms related to financial literacy and older adults. The search query will include terms for the main concepts: (1) Population (older adults, elderly, seniors, aged 60+, retirement age); (2) Intervention domains (financial literacy, digital financial literacy, economic decision-making, financial abuse/fraud prevention, financial counselling), and (3) Outcomes (knowledge, skills, behaviours, digital competence, fraud resilience, autonomy, well-being). Boolean operators, truncation, and proximity operators will be applied to maximize sensitivity. Filters will be used, where possible, to exclude irrelevant document types (editorials, notes). An initial search strategy for PubMed is provided below, which will be further refined to include the expansion of relevant keywords and synonyms based on existing literature and iterative testing.
((older [tiab] OR elderly [tiab] OR “older adult*” [tiab] OR senior*[tiab] OR ageing [tiab] OR ageing [tiab] OR “aged 60” [tiab] OR “aged 60+” [tiab] OR Aged [MeSH]) AND (“financial literacy” [tiab] OR “financial capability” [tiab] OR “financial education” [tiab] OR “debt management” [tiab] OR pension* [tiab] OR “consumer education” [tiab] OR “economic decision*” [tiab] OR “decision making” [MeSH Terms] OR “digital financial literac*” [tiab] OR “fraud prevention” [tiab] OR scam* [tiab] OR “financial abuse” [tiab] OR “undue influence” [tiab] OR phishing [tiab] OR “identity theft” [tiab] OR “financial exploitation” [tiab])) AND (english [lang] OR portuguese [lang] OR spanish [lang]).
Full detailed search strings for every database, including all keywords, subject headings, and any limits or filters used, will be presented in an Appendix to facilitate reproducibility of the search process. By documenting the exact strategies, we ensure transparency and enable others to replicate or audit our search approach.
Supplementary search methods will be used to enhance the comprehensiveness of the search strategy. These will include backward and forward citation searching, as well as screening relevant systematic reviews. Specifically, we will (i) screen the reference lists of all included studies and relevant systematic reviews (backward citation searching); (ii) examine studies included within relevant systematic reviews to identify additional eligible primary studies; and (iii) use citation tracking tools (e.g., Google Scholar, Scopus) to identify newer studies citing included articles (forward citation searching). All additional records identified through these methods will be screened using the same inclusion and exclusion criteria as the main search results.
To capture ongoing studies, we will search international trial registries such as ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP), and 3ie’s RIDIE. These studies will be included in a separate appendix and described in terms of their key characteristics (e.g., intervention type, target population, and setting). Given the limited availability of outcome data, these studies will not be incorporated into the main EGM but will be reported to highlight areas of emerging evidence.
In summary, our search methods combine broad and targeted strategies across multiple databases, grey literature sources, trial registries, and supplementary citation techniques to ensure a comprehensive and systematic identification of relevant evidence.
Analysis and Presentation
Report Structure
The EGM report will be developed in line with accepted reporting standards for EGMs (White et al., 2020), and will include: summary, background, methods, results, discussion, and conclusions. Any deviations between this protocol and the final report will be clearly documented.
The results section will summarize the number of studies identified through the systematic search and provide an overview of study designs categorized by intervention type (e.g., financial literacy, digital financial literacy, economic decision-making, fraud and abuse prevention), outcomes (e.g., financial knowledge, digital competencies, resilience to fraud, well-being), and key filters such as delivery format.
We will also highlight how equity considerations (e.g., gender, income, education, rurality, cognitive status) have been addressed within the included studies, outline the main gaps in the current evidence base, and discuss the methodological or contextual limitations of the mapped research.
The conclusions will focus on implications for researchers, policymakers, practitioners, and organisations working with older adults, and will propose recommendations to guide future research priorities and investment in financial literacy programmes for ageing populations.
Tables and figures to be included will comprise the PRISMA flowchart (Page et al., 2021) of study selection, a table presenting the number of studies by study design, and a table presenting the number of studies by intervention category and outcomes assessed. Additional tables and figures based on coded information for selected filters (e.g., region, delivery modality, population subgroup) will also be considered. Full search strategies for each database will also be provided as an appendix.
Filters for Presentation
In addition to the main intervention–outcome framework, the EGM will incorporate a set of additional dimensions that are relevant to stakeholders and can provide further insights into the scope and applicability of the evidence. These dimensions will be coded for each included study and presented both in the static report and in the interactive online map: • Country or region: Studies will be categorized according to the geographic location where the intervention was implemented. This will allow stakeholders to explore regional variations, identify evidence gaps in low- and middle-income countries, and assess the transferability of interventions across different contexts. • Age group: Although the EGM focuses on older adults aged 60 years and above, some interventions may target subgroups within this population (e.g., 60–69, 70–79, 80+). Coding by age group will provide a clearer picture of which segments of the ageing population are most frequently studied and where gaps remain. • Delivery channel/place: Interventions will also be coded by delivery channel or setting, such as community centers, healthcare facilities, financial institutions, digital platforms, or home-based approaches. This will enable the identification of trends in how interventions are delivered and highlight underrepresented modalities. • Methodological quality: Studies will be coded according to their methodological quality based on the appraisal tools applied to each study design. For the purposes of visualisation, quality ratings will be grouped into simplified categories (e.g., high vs. low/moderate confidence), allowing users to filter the evidence according to robustness.
In the hard copy report, these dimensions may be represented using multiple tables and figures that cross-tabulate interventions, outcomes, and filters. In the online interactive map, they will function as filters, enabling users to select and visualize subsets of studies according to region, age group, or delivery channel. This multi-dimensional coding will enhance the usability of the EGM by ensuring that stakeholders can access the most relevant evidence for their specific policy, practice, or research needs.
Dependency
In this EGM, the unit of analysis will be the study, rather than the report. Each included study will be coded once, even if it is described in multiple reports or publications. Reports will be considered to originate from the same study when they refer to the same intervention, population, dataset, and study period, or when they share a common study identifier (e.g., trial registration number). In such cases, information will be collated across all relevant reports and coded as a single study, ensuring that no evidence is double-counted. Conversely, when a single report presents findings from multiple distinct studies (e.g., different interventions, populations, or datasets evaluated within the same document), each study will be identified and coded separately. This distinction will be based on whether the report describes clearly separable study designs, samples, or interventions. This approach ensures consistent unit-of-analysis decisions, avoids duplication, and maximises the use of available information.
Data Collection and Analysis
Screening and Study Selection
After completing the database searches, all references will be imported into Rayyan (Ouzzani et al., 2016), a web-based tool designed for systematic review management. Duplicate records will be identified and removed prior to screening. Once the unduplicated results have been obtained, two reviewers will independently apply the inclusion and exclusion criteria to a representative sample of citations (e.g., n = 50). Decisions will be discussed in a group meeting to ensure consistent application of the criteria. This will allow us to clarify the inclusion and exclusion criteria, and revise them where necessary, thereby enabling consistent reviewer interpretation and judgement of the criteria.
After this calibration exercise, two reviewers will independently apply the revised inclusion and exclusion criteria to the title and abstract of each identified citation. We will obtain the full text of papers where either reviewer judges it to meet the criteria, and for those where it is not possible to decide using the information in the title and abstract alone. This approach aims to maximise sensitivity at the screening stage, while feasibility will be managed through an initial calibration exercise and clear inclusion criteria.
Two reviewers will assess the full text of each record independently for inclusion, with disagreements settled through discussion with a third reviewer. Throughout the process, Rayyan’s blinding feature will be used to maintain objectivity during independent screening. The overall study selection process will be presented using a PRISMA flowchart, documenting the number of records identified, screened, excluded (with reasons), and included in the final EGM (Page et al., 2021).
Data Extraction and Management
Two reviewers will independently extract data from all included studies, covering the eligible study designs (randomised controlled trials, quasi-experimental studies, pre–post evaluations, qualitative studies, mixed-methods studies, descriptive and implementation studies). Any discrepancies between reviewers will be resolved through discussion, and, if necessary, a third reviewer will adjudicate.
Coding categories for data extraction will be based on the intervention–outcome framework developed for this EGM. We will extract details on: • Study characteristics: year of publication, country/region, study design, setting (e.g., community, healthcare facility, financial institution, digital/online, home). • Population characteristics: target group (older adults 60+, with subgroups such as 60–69, 70–79, 80+), gender (male only, female only, mixed), socio-economic background, cognitive status (if specified). • Intervention details: type of intervention (financial literacy, digital financial literacy, economic decision-making support, fraud/abuse prevention), delivery channel (e.g., workshops, one-to-one counselling, digital platforms), intensity and duration, providers. • Outcomes: financial knowledge, skills, and behaviours; digital competencies; economic decision-making quality; resilience to fraud and abuse; autonomy, confidence, and self-efficacy; financial well-being and stability; acceptability, feasibility, and unintended effects. • Equity dimensions: data will be coded according to the PROGRESS-Plus framework, including place of residence, race/ethnicity/language/culture, occupation, gender/sex, religion, education, socioeconomic status, as well as additional factors relevant to ageing such as advanced age, disability, and digital exclusion. Where reported, we will also note whether interventions were assessed differentially by equity factors (e.g., gender, socioeconomic status). These data will also be used to analytically explore differential patterns of intervention reach, implementation, and outcomes across subgroups where such information is reported
The standardised coding form is provided in Appendix 1. This form will be piloted and may be refined to ensure clarity and consistency. All data extracted will be included as an annex to the final article. In cases where data are unclear or incomplete, study authors or organisations may be contacted for clarification.
Tools for Assessing Risk of Bias/Study Quality
Given the diversity of study designs included in this EGM, quality appraisal will be tailored to the methodological characteristics of each type of evidence. The objective is not to exclude studies based on quality, but rather to provide stakeholders with transparent information on the level of confidence that can be placed in the available evidence. • Randomised controlled trials and quasi-experimental studies will be assessed using the Cochrane Risk of Bias tool (RoB 2) for RCTs and the ROBINS-I tool for non-randomised studies of interventions. • Qualitative studies will be assessed through the Critical Appraisal Skills Programme (CASP) checklist, which assesses aspects such as credibility, relevance, and transparency of data collection and analysis. • Mixed-methods studies will be appraised by combining the criteria relevant to each methodological component (quantitative and qualitative), drawing on the Mixed Methods Appraisal Tool (MMAT). • Regarding the descriptive and implementation studies, as well as grey literature, since these studies often do not provide outcome evaluations, they will not undergo formal risk of bias assessment. Instead, they will be coded for key indicators of reporting quality and transparency (e.g., clarity of objectives, description of intervention, population, and implementation process).
Quality appraisal will be performed by one reviewer and checked by a second, with disagreements settled by a third reviewer. Quality ratings will be recorded in the coding framework and integrated into the presentation of the map, enabling users to filter and interpret the evidence not only by intervention and outcome but also by methodological robustness.
Methods for Mapping
We will use EPPI-Reviewer Web to create the EGM. All eligible studies will be entered into an interactive online platform to visually display the distribution of evidence across financial literacy domains relevant to older adults. The map will be structured around a two-dimensional framework, with four main intervention categories (e.g., financial literacy, digital financial literacy, economic decision-making, fraud and abuse prevention) represented in the rows and outcomes/experiences (e.g., knowledge, skills, digital competencies, decision-making quality, resilience to fraud, well-being, autonomy, user experience) represented in the columns.
The intervention categories will not be further subdivided in the main map structure in order to maintain clarity and usability. More detailed information on intervention characteristics (e.g., specific components, delivery channel, intensity, or duration) will be captured during data extraction and made available through filters and study-level information.
The initial “surface” view of the map will show the extent of available evidence by study design, displayed in a matrix of intervention type versus outcome. The visual elements of the EPPI-Reviewer platform will represent a limited set of characteristics, such as study type (e.g., quantitative versus qualitative) or overall methodological confidence (e.g., higher versus lower confidence), with the size of the bubbles reflecting the volume of evidence in each cell. More detailed information, including full study design classifications and methodological quality assessments, will be available through interactive filters and study-level metadata. This approach ensures that the map remains visually accessible while allowing users to explore the evidence in greater depth according to their needs.
Each cell in the matrix will be interactive, allowing users to click through to a more detailed layer of the map, where they will be able to view information about the specific studies contributing to that intervention–outcome combination. Additional filters will be available to refine the map according to region, population subgroup (e.g., women, low-income older adults, 80+ age group), delivery channel (e.g., community, digital, healthcare setting), and equity dimensions.
Supplemental Material
Supplemental Material - PROTOCOL: Financial Literacy Programmes for the Ageing Population: An Evidence and Gap Map
Supplemental Material for PROTOCOL: Financial Literacy Programmes for the Ageing Population: An Evidence and Gap Map by Carina Fernandes, Isabel Silva and Inês Gomes in Campbell Systematic Reviews.
Footnotes
Author Contributions
• Content: Carina Fernandes is a neuropsychologist and researcher in cognitive neuroscience and gerontology, with a strong background in economic decision-making in older adults. She contributes expertise on age-related cognitive, psychological, and social factors influencing financial literacy interventions and brings experience in conducting systematic reviews and meta-analyses.
• EGM methods: Isabel Silva is a psychologist and researcher with extensive experience in health literacy, programme evaluation, and psychometric assessment. She leads the design and application of the methodological framework for the EGM, ensuring consistency in screening, coding, and outcome categorisation across quantitative and qualitative studies.
• Statistical analysis: Carina Fernandes provides statistical expertise through her experience in quantitative synthesis, meta-analyses, and interpretation of intervention effects.
• Information retrieval: Inês Gomes is a neuropsychologist and researcher with extensive experience in cognitive ageing, digital inclusion, and health promotion. She is responsible for developing and implementing the search strategy across multiple databases, managing screening and selection processes, and ensuring comprehensive retrieval of relevant literature.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the European Regional Development Fund (ERDF) through the Competitiveness and Internationalisation Operational Programme – COMPETE 2030 (project reference: COMPETE2030-FEDER-00892100), and by Fundação Ensino e Cultura Fernando Pessoa.
Declaration of Conflicting Interests
The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: All authors involved in this review have completed the Campbell Collaboration Conflict of Interest Disclosure Form and declare no conflicts of interest. None of the authors are employed by or affiliated with organisations that may have a vested interest in the results of this review. Additionally, none have participated in the design, conduct, funding, or publication of any studies potentially eligible for inclusion in this EGM. They also report no competing financial, personal, political, or academic interests that could influence the findings or interpretations presented.
Plans for Updating the EGM
Once completed, the EGM will be updated as resources permit.
Supplemental Material
Supplemental material for this article is available online.
References
Supplementary Material
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