Dementia represents a growing global public health challenge, driving the rapid expansion of educational interventions aimed at improving awareness and promoting risk-reduction behaviours. Despite this growth, existing research demonstrates a persistent gap between knowledge acquisition and meaningful behavioural change. This paper presents a realist-informed conceptual analysis and proposes an integrative conceptual framework for evaluating the real world effectiveness of digital dementia education. Integrating health literacy theory, the Capability–Opportunity–Motivation Behaviour (COM-B) model, and implementation science, the framework conceptualises dementia education as a dynamic, multi-component process involving resource availability, user engagement, interpretative engagement, behavioural readiness, contextual influences, and real-world outcomes. Particular emphasis is placed on interpretative engagement, grounded in constructivist and sensemaking perspectives, as a key mechanism linking exposure to educational content with behavioural intention and action. The paper identifies critical limitations in current evaluation approaches, including overreliance on knowledge-based outcomes and insufficient consideration of contextual, emotional, and implementation influences. By advancing a user-centred and context-sensitive framework, this study contributes to the development of more theoretically informed and implementation-oriented approaches for evaluating digital dementia risk-reduction education, particularly among midlife populations.

• Dementia Education; Health Literacy; Behaviour Change; COM-B Model; Digital Health; Engagement; Implementation Science; Prevention; Realist Evaluation; Conceptual Framework

Carey P (2026) Beyond Information Delivery: Towards a Realist-Informed Conceptual Framework for the Evaluation of Digital Dementia Education. J Prev Med Healthc 8(2): 1048.

Dementia is one of the most significant and rapidly growing global public health challenges, with major implications for individuals, families, healthcare systems, and economies worldwide. Global prevalence is projected to increase substantially over coming decades, particularly within ageing populations such as those in Australia [1,2]. In response, dementia prevention and risk-reduction strategies have become an increasing focus of public health policy and research, contributing to rapid growth in educational interventions designed to improve awareness, knowledge, and behavioural risk reduction.

Digital technologies now play a central role in this expansion. Online learning platforms, mobile applications, web-based programs, and public health campaigns provide scalable opportunities for dementia education across diverse populations [3,4]. Contemporary initiatives increasingly target not only healthcare professionals and caregivers but also midlife populations who may benefit from early prevention and risk-reduction strategies.

However, despite increasing availability and participation, evidence regarding the real-world effectiveness of dementia education remains inconsistent. Educational interventions often improve knowledge and attitudes, but are less consistent in achieving lasting behavioural change and longer-term implementation outcomes [5-9]. This limitation reflects a broader challenge within behavioural and implementation science: informational access alone rarely produces meaningful behavioural change.

Existing dementia education research has largely focused on intervention development, dissemination, and knowledge acquisition, with comparatively limited attention to the mechanisms through which individuals interpret, internalise, and apply educational content within everyday contexts [10,11]. Consequently, many evaluations emphasise participation, reach, or short-term learning outcomes while under examining contextual influences, interpretative processes, and behavioural enactment in real-world settings.

In this paper argues that dementia education is better conceptualised as a dynamic interplay of context, engagement, interpretation, behavioural readiness and implementation conditions [12], rather than a linear delivery of information. Drawing on realist evaluation principles [13], health literacy theory, the Capability-Opportunity–Motivation Behaviour (COM-B) model, and implementation science, this paper presents a realist-informed conceptual framework for evaluating digital dementia education.

Rather than asking only whether educational interventions increase knowledge, the framework seeks to explain how, for whom, and under what conditions digital dementia education contributes to meaningful behavioural and health-related outcomes. In particular, interpretative engagement is highlighted as a key mechanism linking exposure to educational content with behavioural intention and enactment [14]. By integrating behavioural, contextual, and implementation perspectives, the framework advances a more comprehensive approach to evaluating the effectiveness of digital dementia education in practice.

Dementia education has expanded substantially in scope, delivery, and target population over the past decade, reflecting broader public health priorities surrounding prevention, early intervention, and evidence translation. Educational initiatives now encompass public awareness campaigns, workforce training programs, community based interventions, digital learning platforms, and blended educational models.

Digital technologies have become increasingly central to this expansion because they offer scalable and potentially cost-effective approaches for delivering health education across geographically dispersed populations [4-15]. In dementia contexts, digital education has been used to support caregiver education, workforce development, and public awareness initiatives through online modules, mobile applications, webinars, and Massive Open Online Courses (MOOCs) [3].

Evidence suggests that dementia education programs can improve knowledge, confidence, and attitudes among both healthcare staff and community participants [12-16]. Increasing attention has also been given to culturally responsive and person-centred educational approaches designed to improve accessibility and relevance across diverse populations [17].

Despite this growth, implementation research consistently demonstrates that educational effectiveness is strongly influenced by contextual and delivery conditions. Knowledge improvements do not always translate into sustained behavioural or practice change [18-20]. Many interventions continue to be evaluated primarily through participation metrics, satisfaction scores, or short-term knowledge gains rather than through meaningful behavioural, implementation, or long-term outcomes [21,22].

As a result, there remains limited understanding of how individuals engage with, interpret, and apply dementia education in everyday life. This represents a critical gap within current approaches to evaluating digital dementia education.

A central assumption underpinning many educational interventions is that increased knowledge naturally leads to behavioural change. However, this assumption has been repeatedly challenged within behavioural science and health education research. Research continuously shows that awareness, intention, and sustained action differ significantly [5-23]. Within dementia prevention contexts, individuals may understand risk factors and recommended behaviours without successfully adopting or maintaining lifestyle changes. This gap reflects broader insights from behavioural science, which emphasise that behaviour is shaped by multiple interacting influences, including capability, opportunity, motivation, social environment, emotional readiness, and contextual constraints.

The COM-B model provides a useful framework for understanding these interactions by conceptualising behaviour as emerging through relationships between capability, opportunity, and motivation [24]. From this perspective, knowledge represents only one component of behavioural capability and is insufficient on its own to produce sustained behavioural enactment.

Consequently, educational interventions that focus predominantly on information transmission may improve awareness while failing to address the broader contextual and motivational conditions required for behavioural change. This limitation highlights the need for evaluation approaches capable of examining not only what information is delivered, but also how individuals interpret, internalise, and apply educational content within real-world contexts.

Health literacy is increasingly recognised as a critical determinant of health engagement and behavioural outcomes. Contemporary models define health literacy not simply as reading comprehension or information access, but as the capacity to access, understand, appraise, and apply health information within social and contextual environments [25]. Furthermore, health literacy is becoming recognised as a more comprehensive social indicator of health that influences inequality in outcomes, participation, and access [26]. Importantly, individuals do not passively receive educational information. Instead, individuals actively analyse, assess, and create meaning based on their lived experiences, cultural background, emotional reactions, past knowledge, and beliefs [27]. This process, referred to in this paper as interpretative engagement, represents a central mechanism linking exposure to educational content with behavioural readiness.

Interpretative engagement extends beyond basic participation or attention. It involves reflection, sensemaking, appraisal of personal relevance, and integration of new information into existing understandings and identities. Individuals exposed to identical educational content may therefore experience substantially different outcomes depending on how meaning is constructed within their particular context.

Interpretative engagement is still understudied in dementia education research, despite its significance [12]. Existing evaluations frequently focus on measurable indicators such as participation rates, completion metrics, or knowledge scores while overlooking the interpretative processes through which educational content becomes behaviourally meaningful.

Behavioural and implementation sciences both emphasise that interventions function differently across contexts. Educational interventions that demonstrate effectiveness under controlled conditions may produce weaker or inconsistent outcomes when implemented in routine practice.

The COM-B model highlights how behavioural enactment depends on interactions between psychological and physical capability, environmental opportunity, and reflective and automatic motivation [24]. This perspective helps explain why knowledge acquisition alone rarely predicts sustained behaviour change.

Implementation science further extends this understanding by emphasising usability, scalability, acceptability, implementation fidelity, and contextual adaptation [28,29]. Real-world implementation is shaped by organisational systems, competing demands, policy environments, social support, and broader contextual conditions [30].

Digital inequality research also demonstrates that disparities in digital access, literacy, and technological confidence continue to influence who benefits from digital health interventions [31]. Consequently, educational resources that appear accessible in principle may remain inaccessible or ineffective for particular populations.

Together, these perspectives highlight the need for evaluation approaches capable of examining not only whether interventions produce outcomes, but how contextual conditions shape the mechanisms through which outcomes emerge.

Engagement with dementia education is shaped by a wide range of emotional, social, and contextual influences. Emotional responses such as fear, anxiety, denial, stigma, or perceived vulnerability may either facilitate or inhibit engagement with dementia-related information [32,33].

Similarly, social and environmental conditions influence individuals’ capacity to engage with and apply educational content. Family support, peer influence, cultural norms, work demands, socioeconomic conditions, and access to supportive environments all affect behavioural enactment and maintenance.

These findings reinforce the importance of person-centred and context-sensitive educational approaches. Educational interventions that fail to account for emotional and contextual variability may overestimate their effectiveness by assuming uniform engagement and behavioural capacity across populations.

Despite substantial advances in digital health innovation, a persistent gap remains between intervention efficacy under controlled research conditions and effectiveness within real-world settings.

Evidence from digital health research suggests that online and mobile interventions can demonstrate positive outcomes within structured environments; however, their effectiveness frequently declines during routine implementation because of variability in engagement, context, usability, and delivery conditions [4].

Many evaluation studies continue to prioritise short term or proximal outcomes while under examining implementation sustainability, behavioural maintenance, and contextual adaptation. Consequently, interventions may appear successful within research environments while producing weaker or inequitable outcomes in practice.

This implementation gap is particularly important within dementia prevention, where meaningful behavioural change often requires long-term engagement, sustained motivation, and supportive environmental conditions.

These limitations underscore the need for more theoretically integrated and context-sensitive approaches to evaluating digital dementia education.

The conceptual framework presented in this paper was developed using a realist-informed narrative synthesis approach. This approach was selected to enable the integration of diverse theoretical perspectives across health literacy, behavioural science, implementation science, and digital health engagement research, without restricting the analysis to a single disciplinary methodology.

The development process was iterative and interpretive rather than protocol driven. Relevant literature was identified through targeted and iterative searching of peer-reviewed publications and foundational theoretical works, including realist evaluation, COM-B behaviour change theory, health literacy frameworks, and implementation science models. Key concepts and explanatory mechanisms were extracted and mapped across these domains to identify areas of conceptual convergence, complementarity, and tension.

Through successive cycles of analysis, synthesis, and refinement, core constructs were organised into a preliminary explanatory structure describing how digital dementia education may lead to behavioural outcomes. Attention was given to mechanisms of engagement, interpretation, behavioural readiness, and contextual influence. The concept of interpretative engagement emerged through this synthesis as a central explanatory mechanism linking exposure to educational content with behavioural intention and enactment.

Rather than seeking statistical aggregation or formal realist program theory testing, the aim of this process was to generate a coherent, theory-driven conceptual framework capable of guiding future empirical validation. The resulting framework is therefore intended as an explanatory model rather than an empirically tested theory.

To address limitations in existing evaluation approaches, this paper proposes a realist-informed conceptual framework that conceptualises digital dementia education as a dynamic and context-dependent process through which educational resources may—or may not—produce meaningful behavioural outcomes (Figure 1).

Figure 1: Realist-Informed Conceptual Framework for Evaluating Digital Dementia Education NOTE: The framework illustrates how digital dementia education produces outcomes through interactions between context, mechanisms, and outcomes. It conceptualises dementia education as a dynamic process involving resource availability, engagement, interpretative engagement, behavioural readiness, contextual influences, and real-world outcomes. The framework is informed by realist evaluation theory, the COM-B model of behaviour, health literacy theory, and implementation science.

The framework is informed by realist evaluation theory [13], which conceptualises outcomes as emerging through interactions between contexts, mechanisms, and outcomes (CMO configurations). Within this perspective, digital dementia education does not operate as a universally effective intervention; rather, its impact depends on how individuals engage with, interpret, and apply educational content within specific social, emotional, and environmental contexts.

The framework integrates three complementary theoretical perspectives:

• Health literacy theory,

• The COM-B model of behaviour,

• Implementation science.

Health literacy operates across all stages of the framework, shaping individuals’ capacity to Health literacy influences people’s ability to access, comprehend, evaluate, and use knowledge at every level of the framework [25-35]. The COM-B model explains how capability, opportunity, and motivation influence behavioural readiness and enactment [24], while implementation science contributes attention to contextual variability, usability, scalability, and real-world delivery conditions [28,29].

The framework consists of six interrelated domains:

1. Resource Availability (Context)

Access to digital educational resources, including technological accessibility, usability, and opportunity for engagement.

2. User Engagement (Mechanism)

Initial interaction with educational content, including attention, participation, and motivational engagement.

3. Interpretative Engagement (Core Mechanism)

The process through which users actively construct meaning from educational content by reflecting on relevance, personal applicability, and lived experience.

4. Behavioural Readiness (Mechanism)

Development of understanding, self-efficacy, risk perception, and intention to act.

5. Contextual Influences (Context)

Social, cultural, emotional, and environmental factors that facilitate or constrain behavioural enactment.

6. Real-World Outcomes (Outcome)

Adoption of dementia risk-reduction strategies, altered behaviour, enhanced wellbeing, and long-lasting effects [35].

A central innovation of the framework is the explicit positioning of interpretative engagement as a core explanatory mechanism linking exposure to educational information with behavioural outcomes. Existing evaluation models frequently assume that engagement or knowledge acquisition alone predicts behaviour change. In contrast, this framework argues that individuals must actively interpret and contextualise information before behavioural readiness can emerge.

The framework also incorporates feedback loops, recognising that outcomes reshape future engagement, perceptions, and contextual conditions over time. This reflects the iterative and non-linear nature of behaviour change and implementation processes in real-world environments.

To strengthen the realist orientation of the framework, several illustrative Context–Mechanism–Outcome (CMO) configurations are presented below. These configurations demonstrate how differing contextual conditions activate specific mechanisms that generate variable outcomes.

CMO Configuration 1: Low literacy context

• Context: Limited digital literacy and low prior health knowledge

• Mechanism: Limited interpretative engagement (difficulty interpreting educational content) and contextualising

• Outcome: Minimal behavioural readiness and limited adoption of risk-reduction behaviours.

In this context, the availability of digital dementia education alone is insufficient to produce behavioural change. Users may struggle to interpret or contextualise information, constraining engagement at a deeper interpretative level.

CMO Configuration 2: High literacy and supportive design context

• Context: Higher digital and health literacy, supported by accessible and user-centred design features

• Mechanism: Interpretative engagement and reflective processing (relevance appraisal and meaning-making)

• Outcome: Increased behavioural readiness and adoption of risk-reduction behaviours.

In this context, educational content is more likely to activate reflective and interpretative processes, facilitating translation into behavioural intention and action.

CMO Configuration 3: Emotional and social environment effects

• Context: Emotionally supportive and socially reinforcing environments vs. environments characterised by stigma, isolation, or competing demands

• Mechanism: Strengthened or inhibited behavioural motivation and enactment processes

• Outcome: Sustained behavioural adoption or reduced maintenance of behaviour change despite initial engagement.

These contrasting contexts illustrate how emotional and social conditions can either enable or constrain the maintenance of behavioural change over time.

Summary

Collectively, these configurations illustrate that outcomes are not produced by educational exposure alone, but through interactions between contextual conditions and underlying mechanisms. This reinforces the realist proposition that outcomes are contingent on specific Context–Mechanism–Outcome configurations rather than uniform causal effects.

This framework advances digital dementia education research by shifting emphasis from information delivery and knowledge acquisition toward the mechanisms through which educational content is interpreted, contextualised, and translated into behavioural readiness and action. It positions interpretative engagement as a central explanatory mechanism within a realist-informed structure that integrates behavioural science and implementation science.

A key contribution of the framework is that it challenges the assumption that informational exposure alone is sufficient to produce behavioural change. Existing research often evaluates dementia education interventions through knowledge gain, participation, or short-term attitudinal change, yet these outcomes provide limited insight into whether learning is meaningfully interpreted or translated into sustained behavioural action.

From a realist perspective, these findings suggest that outcomes are not produced by the intervention itself, but by the interaction between context and mechanisms that shape how individuals engage with and respond to educational content. Rather than linear effects, the framework proposes that outcomes emerge through specific Context–Mechanism–Outcome (CMO) configurations, where variation in context activates different interpretative and behavioural mechanisms, leading to divergent outcomes across individuals and settings.

This interpretation aligns with established implementation science and behaviour change theory. The Consolidated Framework for Implementation Research (CFIR) reinforces the importance of context in shaping implementation outcomes, highlighting that organisational, external, and individual-level conditions influence whether and how interventions are adopted and sustained [30]. Within a CMO logic, CFIR primarily strengthens understanding of contextual conditions (C) that enable or constrain mechanisms.

Similarly, the Behaviour Change Wheel provides a complementary explanation of mechanisms (M) by conceptualising behaviour as arising from interactions between capability, opportunity, and motivation. This reinforces the premise that knowledge alone is insufficient unless it activates motivational and opportunity structures that translate learning into action [24]. In realist terms, the Behaviour Change Wheel helps specify the psychological and behavioural mechanisms through which educational interventions may generate outcomes.

In addition, the framework integrates previously siloed perspectives by combining health literacy theory, behavioural science, realist evaluation, and implementation science. This synthesis enables a more comprehensive understanding of how educational interventions function in complex real-world settings, where outcomes are contingent on specific CMO configurations rather than uniform causal pathways.

Finally, the framework strengthens implementation oriented evaluation by explicitly accounting for feedback loops, contextual moderators, and variability in behavioural enactment. It supports a shift away from assuming uniform intervention effects toward examining what works, for whom, and under what conditions (i.e., across differing CMO configurations), thereby improving explanatory depth and transferability across settings.

Collectively, the framework offers a theoretically integrated and context-sensitive approach to evaluating digital dementia education, with stronger explanatory power for understanding differential outcomes and guiding more effective intervention design and implementation.

The proposed framework has several implications for future research, intervention design, and public health policy.

For research, the framework highlights the importance of moving beyond outcome-only evaluations toward approaches capable of examining Context–Mechanism-Outcome configurations. Future studies should investigate how interpretative engagement develops across different populations and how contextual conditions shape behavioural enactment and sustainability over time. Mixed-methods and realist-informed evaluation approaches may be particularly valuable for capturing these complex interactions.

For intervention design, the framework emphasises the importance of tailoring educational resources to users’ digital literacy, health literacy, emotional readiness, and sociocultural context. Digital dementia education should move beyond static information delivery toward adaptive, user-centred approaches that facilitate reflection, relevance appraisal, and behavioural capability development.

For policy and implementation, the framework supports the development of equity-focused digital health strategies that recognise variability in access, opportunity, and engagement. Policymakers should avoid assuming uniform benefit from digital educational initiatives and instead prioritise accessibility, inclusivity, and implementation support across diverse populations.

Collectively, these implications suggest that improving dementia prevention outcomes requires alignment between educational design, contextual support, implementation conditions, and evaluation strategy.

Several limitations of the proposed framework should be acknowledged. Consistent with realist-informed programme theory development, the proposed Context-Mechanism–Outcome relationships require empirical refinement and testing [13].

First, the framework is conceptual and has not yet been empirically validated across diverse populations or intervention settings. Future research is required to test the proposed Context–Mechanism–Outcome configurations and examine how the framework operates within different demographic and implementation environments.

Second, while the framework integrates multiple theoretical perspectives, additional mechanisms and contextual influences may emerge through empirical application. Behavioural and implementation processes are inherently complex and may vary substantially across cultural, organisational, and technological contexts.

Third, the framework focuses primarily on digital dementia education related to prevention and risk reduction. Adaptation may be required for other contexts such as caregiver education, workforce training, or clinical dementia education.

Despite these limitations, the framework provides a theoretically grounded foundation for more comprehensive and context-sensitive evaluation of digital dementia education.

Digital dementia education has expanded rapidly in response to growing public health concern surrounding dementia prevention and risk reduction. However, existing evaluation approaches remain heavily focused on information delivery and knowledge acquisition, often overlooking the contextual and interpretative processes that shape whether educational interventions produce meaningful behavioural outcomes in practice.

This paper proposes a realist-informed conceptual framework that reconceptualises digital dementia education as a dynamic interaction between context, engagement, interpretation, behavioural readiness, and implementation conditions. By integrating health literacy theory, the COM-B model, and implementation science, the framework provides a theoretically grounded structure for understanding how digital dementia education functions across diverse real-world settings.

The framework’s explicit acknowledgment of interpretative engagement as a crucial mechanism connecting educational exposure with behavioural enactment is one of its main contributions [36-46]. This shifts evaluation beyond simplistic assumptions that access to information alone leads to action and instead highlights the importance of meaning-making, contextual fit, and behavioural capability.

The explicit inclusion of interpretative engagement as a core mechanism strengthens the explanatory capacity of the framework by highlighting how individuals actively construct meaning from educational content within specific contextual conditions. This shifts evaluation beyond assumptions that information exposure alone leads to behavioural change and instead emphasises the importance of meaning-making, contextual fit, and behavioural capability.

Ultimately, improving dementia prevention outcomes requires evaluation approaches capable of identifying not only whether digital education works, but how, for whom, and under what conditions change occurs. The proposed framework provides a foundation for more context-sensitive and implementation-oriented evaluation of digital dementia education and offers a basis for future empirical validation.

Ethical approval was not required for this study as it is a conceptual paper based on analysis of existing literature and does not involve human participants, primary data collection, or identifiable data.

1. World Health Organization. Global status report on dementia. WHO.2023.
2. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020; 396: 413-446.
3. Eccleston C, Doherty K, Bindoff A, Robinson A, Vickers J, McInerneyF. Building dementia knowledge globally through the Understanding Dementia Massive Open Online Course (MOOC). NPJ Science Learning. 2019; 4.
4. Murray E, Hekler EB, Andersson G, Collins LM, Doherty A, Hollis C, et al. Evaluating Digital Health Interventions: Key Questions and Approaches. Am J Prev Med. 2016; 51: 843-851.
5. Webb TL, Sheeran P. Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychol Bull. 2006; 132: 249-268.
6. Prestwich A, Sniehotta FF, Whittington C, Dombrowski SU, Rogers L, Michie S. Does theory influence the effectiveness of health behavior interventions? Meta-analysis. Health Psychol. 2014; 33: 465-474.
7. Bailey DH, Duncan GJ, Cunha F, Foorman BR, Yeager DS. Persistence and Fade-Out of Educational-Intervention Effects: Mechanisms and Potential Solutions. Psychol Sci Public Interest. 2020; 21: 55-97.
8. Portela Dos Santos O, Melly P, Hilfiker R, Giacomino K, Perruchoud E, Verloo H, et al. Effectiveness of Educational Interventions to Increase Skills in Evidence-Based Practice among Nurses: The EDITcare Systematic Review. Healthcare (Basel). 2022; 10: 2204.
9. Arlinghaus KR, Johnston CA. Advocating for Behavior Change with Education. Am J Lifestyle Med. 2017; 12: 113-116.
10. Mazzucca S, Arredondo EM, Hoelscher DM, Haire-Joshu D, Tabak RG, Kumanyika SK, et al. Expanding Implementation Research to Prevent Chronic Diseases in Community Settings. Annu Rev Public Health. 2021; 42: 135-158.
11. Kumah EA, McSherry R, Bettany-Saltikov J, van Schaik P, Hamilton S, Hogg J, et al. Evidence-informed practice versus evidence-based practice educational interventions for improving knowledge, attitudes, understanding, and behavior toward the application of evidence into practice: A comprehensive systematic review of UG student. Campbell Syst Rev. 2022; 18: e1233.
12. Surr CA, Gates C, Irving D, Oyebode J, Smith SJ, Parveen S, et al. Effective Dementia Education and Training for the Health and Social Care Workforce: A Systematic Review of the Literature. Rev Educ Res. 2017; 87: 966-1002.
13. Pawson R, Tilley N. Realistic evaluation. Sage. 1997.
14. Perski O, Blandford A, West R, Michie S. Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis. Transl Behav Med. 2017; 7: 254-267.
15. Lustria MLA, Noar SM, Cortese J, Van Stee SK, Glueckauf RL, Lee J. Tailored health interventions delivered over the Internet: A meta-analysis of effectiveness and moderators. Am J Prev Med. 2013; 45: 210-226.
16. Rasmussen BM, Andersen PT, Waldorff FB, Berg-Beckhoff G. Effectiveness of dementia education for professional care staff and factors influencing staff-related outcomes: An overview of systematic reviews. Int J Nurs Stud. 2023; 142: 104469.
17. Hulko W, Mirza N, Christianson T, Nazemi M, Vicic A, Bartle E. A scoping review of dementia education programs to assess for the inclusion of culture. Innovation in Aging. 2024; 8: 533.
18. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011; 38: 65-76.
19. Chowdhary N, Barbui C, Anstey KJ, Kivipelto M, Barbera M, Peters R, et al. Reducing the Risk of Cognitive Decline and Dementia: WHO Recommendations. Front Neurol. 2022; 12: 765584.
20. Cullen L, Hanrahan K, Edmonds SW, Reisinger HS, Wagner M. Iowa Implementation for Sustainability Framework. Implement Sci. 2022; 17: 1.
21. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM Planning and Evaluation Framework: Adapting to New Science and Practice With a 20-Year Review. Front Public Health. 2019; 7: 64.
22. Gkioka M, Schneider J, Kruse A, Tsolaki M, Moraitou D, Teichmann B. Evaluation and Effectiveness of Dementia Staff Training Programs in General Hospital Settings: A Narrative Synthesis with Holton’s Three-Level Model Applied. J Alzheimers Dis. 2020; 78: 1089-1108.
23. Conner M, Norman P. Understanding the intention-behavior gap: The role of intention strength. Front Psychol. 2022; 13: 923464.
24. Michie S, Johnston M. Theories and techniques of behaviour change: Developing a cumulative science of behaviour change. Health Psychol Rev. 2012; 6: 1-6.
25. Sørensen K, Van den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health. 2012; 12: 80.
26. Nutbeam D, Lloyd JE. Understanding and Responding to Health Literacy as a Social Determinant of Health. Annu Rev Public Health. 2021; 42: 159-173.
27. Alhazmi AA, Kaufmann A. Phenomenological Qualitative Methods Applied to the Analysis of Cross-Cultural Experience in Novel Educational Social Contexts. Front Psychol. 2022; 13: 785134.
28. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008; 337: a1655.
29. Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ. 2021; 374: n2061.
30. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009; 4: 50.
31. Van Dijk JAGM. Digital divide research: Achievements and shortcomings. Poetics.2006; 34.
32. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004; 31: 143-164.
33. Brewer NT, Chapman GB, Gibbons FX, Gerrard M, McCaul KD, Weinstein ND. Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination. Health Psychol. 2007; 26: 136-145.
34. Sørensen K, Levin-Zamir D, Duong TV, Okan O, Brasil VV, Nutbeam D. Building health literacy system capacity: a framework for health literate systems. Health Promot Int. 2021; 36: i13-i23.
35. Dodds L, Deckers K, Harris CB, Siette J. Behaviour change techniques used in interventions targeting dementia risk factors amongst older adults in rural and remote areas: A systematic review and meta-analysis. J Prev Alzheimers Dis. 2025; 12: 100093.
36. Wang MT, Degol JL, Henry DA. An integrative development-in-sociocultural-context model for children’s engagement in learning. Am Psychol. 2019; 74: 1086-1102.
37. Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016; 9: 211-217.
38. Ananthakrishnan A, Cong C, Riccalton V, Meinert E. Progressing implementation of behaviour change frameworks for digital health interventions: Challenges and ways forward. Transl Behav Med. 2025; 15: ibaf069.
39. Ancker JS, Grossman LV, Benda NC. Health Literacy 2030: Is It Time to Redefine the Term? J Gen Intern Med. 2020; 35: 2427-2430.
40. Batsch NL, Mittelman MS. World Alzheimer report 2012: Overcoming the stigma of dementia. Alzheimer’s Disease Int. 2012.
41. Hagger MS, Moyers S, McAnally K, McKinley LE. Known knowns and known unknowns on behavior change interventions and mechanisms of action. Health Psychol Rev. 2020; 14: 199-212.
42. Kwasnicka D, Dombrowski SU, White M, Sniehotta F. Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories. Health Psychol Rev. 2016; 10: 277-296.
43. Moore KJ, Lee CY, Sampson EL, Candy B. Do interventions that include education on dementia progression improve knowledge, mental health and burden of family carers? A systematic review. Dementia (London). 2020; 19: 2555-2581.
44. World Health Organization. Risk reduction of cognitive decline and dementia: WHO guidelines. 2019.
45. Pas ET, Bradshaw CP. Examining the association between implementation and outcomes: State-wide scale-up of school-wide positive behaviour intervention and supports. J Behav Health Services Res. 2012; 39: 417-433.
46. Yardley L, Morrison L, Bradbury K, Muller I. The person-based approach to intervention development. J Med Internet Res. 2016; 18: e30.