A Multi-Criteria Decision Analysis of Open-Skill Exercise-Based Sports for Cognitive Health Promotion in Older Adults

A Multi-Criteria Decision Analysis of Open-Skill Exercise-Based Sports for Cognitive Health Promotion in Older Adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multi-Criteria Decision Analysis of Open-Skill Exercise-Based Sports for Cognitive Health Promotion in Older Adults Takao Yamasaki, Kazuto Hamaguchi, Takuro Ikeda, Shigetada Hiraoka, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8671463/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Cognitive decline and dementia are major challenges in aging societies. Open-skill exercise (OSE), characterized by unpredictable environments requiring rapid perceptual–cognitive–motor adaptation, has emerged as a promising approach for cognitive health. However, systematic cross-sport comparisons remain scarce. This study evaluated eight OSEs—tennis, table tennis, badminton, basketball, volleyball, soccer, baseball, and non-combat judo—using a multidimensional framework to assess their relative suitability for cognitive health promotion and community implementation among older adults. A multi-criteria decision analysis was conducted using eight criteria covering key cognitive, physical, social, safety, operational, sustainability, and digital aspects. Cognitive load was quantified using an established composite metric, with all criteria normalized and weighted for dementia prevention relevance. Weighted scores were integrated to generate an overall composite suitability score for each sport. Table tennis achieved the highest score, reflecting strong performance across cognitive, physical, safety, feasibility, sustainability, and digital domains. Badminton also scored highly, driven by strong cognitive and practical attributes. Team sports showed broad cognitive demands and high social interaction but were limited by lower individual decision frequency or elevated injury risk. Soccer and basketball had high physical load, whereas baseball and non-combat judo scored lower due to comparatively limited real-time cognitive demands and feasibility constraints. Overall, OSEs differed markedly across cognitive, physical, and operational domains. Table tennis emerged as a highly scalable and well-balanced option for cognitive health interventions in older adults, followed by badminton and selected team sports. These findings provide guidance for community programming and future neurocognitive and implementation-oriented research. Taken together, these multidimensional characteristics suggest potential relevance to the prevention of cognitive, physical, and social frailty. open-skill exercise cognitive health healthy aging multi-criteria decision analysis community implementation dementia prevention racket sports 1 Introduction Cognitive decline and dementia represent some of the most pressing challenges confronting rapidly aging societies. As global life expectancy continues to rise, the prevalence of cognitive disorders is projected to increase substantially, imposing profound social, economic, and healthcare burdens at both individual and societal levels [ 1 , 2 ]. Accordingly, the identification of scalable and evidence-based strategies capable of preserving cognitive function and promoting healthy brain aging has emerged as a critical public health priority. Consistent with global prevention strategies, regular physical activity is recommended as a key modifiable lifestyle factor for reducing the risk of cognitive decline and dementia [ 3 ]. A growing body of evidence demonstrates that physical activity exerts robust and multifaceted benefits on brain health through several converging neurobiological pathways. These include improvements in cardiovascular and cerebrovascular function, upregulation of neurotrophic signaling—particularly brain-derived neurotrophic factor—enhancement of synaptic plasticity and large-scale brain network organization, attenuation of chronic neuroinflammatory processes, and facilitation of protein homeostasis mechanisms such as amyloid-β clearance [ 4 – 8 ]. At the molecular and cellular levels, exercise-induced adaptations involve coordinated regulation of neurotrophic, metabolic, immune, and autophagic pathways, collectively enhancing neuronal resilience and plasticity [ 4 – 8 ]. Through these interrelated mechanisms, physical activity contributes to the preservation of brain structure and function and supports cognitive performance across multiple domains during aging. These mechanistic insights are supported by accumulating clinical evidence, with systematic reviews, meta-analyses, and umbrella reviews consistently demonstrating that physical activity is associated with meaningful improvements in cognitive function across a broad range of neurocognitive conditions and aging populations [ 9 – 12 ]. Within the broad category of physical activity, accumulating evidence suggests that the cognitive and neural benefits of exercise may depend not only on intensity or volume, but also on the environmental and cognitive demands imposed by the activity itself. In this study, the term open-skill exercise (OSE) is used to refer to sport-based physical activities performed in externally paced, unpredictable environments that require continuous perceptual–motor adaptation. Examples include table tennis, tennis, and badminton [ 13 – 17 ]. In contrast, closed-skill exercise (CSE) is typically performed in stable and predictable environments, such as walking or stationary cycling [ 13 – 17 ]. OSE inherently involves continuous processing of environmental cues, dynamic decision-making, attentional switching, and visuomotor integration. These features impose greater cognitive demands and may stimulate frontal–parietal, cerebellar, and sensorimotor networks more extensively than CSE, leading to enhancements in executive function, visuospatial processing, and processing speed [ 13 – 17 ]. Empirical findings increasingly support the potentially superior cognitive benefits of OSE in older adults [ 13 – 17 ]. Beyond cognitive outcomes, OSE also has the potential to address multiple domains of frailty, including physical and social frailty, which are increasingly recognized as interrelated determinants of functional decline and dementia risk in aging societies [ 18 , 19 ]. In particular, sport-based activities that require agility, rapid motor responses, and interpersonal interaction may contribute to the maintenance of muscle power, coordination, and social connectedness in older adults [ 20 , 21 ]. However, how different OSEs balance cognitive demand, physical load, social engagement, safety, and real-world feasibility remains insufficiently understood. Despite growing interest in OSE as an environmental–cognitive intervention, the current literature remains fragmented. Many studies focus on a single sport or specific training protocol [ 22 – 24 ], limiting understanding of how different OSEs compare in terms of their neural, cognitive, and practical attributes. Moreover, factors such as injury risk, accessibility of facilities, social engagement opportunities, and cost strongly shape the real-world feasibility of regular participation. Although meta-analyses have contrasted OSE and CSE in general [ 15 – 17 ], systematic comparisons across different OSEs, grounded in the environmental demands they impose on the nervous system, remain scarce. To address this gap, the present study evaluates eight OSEs that are widely accessible to older adults, examining their cognitive and physical characteristics as well as the environmental demands imposed on perceptual, motor, and neural systems. Using a transparent multi-criteria decision analysis (MCDA) framework—a structured approach for integrating multiple, often competing criteria into a single evaluative framework [ 25 , 26 ]—we integrate cognitive load, physical demands, social interaction potential, and environmental and practical feasibility to derive an overall suitability ranking. We hypothesize that OSEs characterized by higher environmental unpredictability, particularly racket sports, will show greater alignment with neural mechanisms supporting cognitive resilience. Ultimately, by linking environmental characteristics of sports with objective cognitive-health considerations, this study provides actionable guidance for community program development, resource allocation, and policy design. The findings contribute to ongoing efforts to develop ecologically valid, environment-based strategies that promote cognitive health and adaptive brain function in aging populations. 2 Methods 2.1 Selection of OSEs The conceptual distinction between OSEs and CSEs provides a useful theoretical framework for classifying sports, although most sports incorporate both elements to varying degrees. These activities exist along a continuum, with higher categories emphasizing externally driven, unpredictable environments characteristic of OSEs, and lower categories emphasizing self-paced, repetitive movements typical of CSEs [ 13 , 14 ]. Based on this established classification, fourteen sports have been identified as Category 4, representing a high degree of open-skill characteristics: tennis, table tennis, badminton, basketball, volleyball (including beach volleyball), soccer, handball, American football, wushu, martial arts (judo), fencing, korfball, hockey, and baseball [ 13 , 14 ]. For the present study, this initial list was refined to ensure both theoretical rigor and practical relevance for older adult populations. Refinement was guided by three predefined criteria: (i) global or regional participation, (ii) feasibility of community-level implementation among older adults, and (iii) available evidence supporting safety, accessibility, and cognitive benefits. Six sports were excluded accordingly. Korfball and wushu were removed due to limited international dissemination and minimal adoption among older adults. American football was excluded despite the existence of senior-oriented variants (e.g., flag football) because of concerns regarding accessibility, safety, and insufficient supporting evidence. Fencing, hockey, and handball were also omitted due to low participation rates among older adults and limited evidence regarding their feasibility as community-based health-promoting activities. Regarding martial arts, the scope was restricted to judo, specifically non-combat modalities such as kata and structured training sessions, which have demonstrated greater adaptability and safety for older adults [ 24 ]. As a result, eight OSEs were retained for systematic evaluation: tennis, table tennis, badminton, basketball, volleyball (including beach volleyball), soccer, baseball, and martial arts (non-combat judo). Although some of these sports may present practical challenges for direct implementation in older populations, their inclusion allows a comprehensive comparison of OSE-related mechanisms and their potential relevance to dementia prevention and community-based interventions. 2.2 Evaluation Criteria and Scoring Framework This study employed a MCDA framework to systematically compare the selected OSEs across multiple dimensions relevant to cognitive health promotion and community implementation (see Supplementary Methods for detailed procedures). 2.2.1 Evaluation Domains and Criteria Overview Each sport was evaluated using eight predefined criteria, organized into four conceptual domains: Domain A: Intrinsic features — cognitive demand (criterion 1), physical demand and exercise intensity (criterion 2), safety (criterion 3), and social interaction (criterion 4); Domain B: Implementation feasibility — facility and cost demand (criterion 5), and instructor and operational demand (criterion 6); Domain C: Sustainability and attractiveness — continuity, enjoyment, and personal cost (criterion 7); Domain D: Digital extensibility — applicability to virtual reality (VR) and e-sports environments (criterion 8). Together, these criteria capture cognitive, physical, social, safety-related, operational, sustainability, and technological dimensions relevant to community-based exercise programs. 2.2.2 Assessment of Individual Criteria Cognitive demand (criterion 1) was quantified as a composite measure comprising two components: cognitive breadth (CB) and decision intensity (DI). CB was operationalized as the number of cognitive domains engaged during active play, calculated as a cumulative score across six core domains: perceptual–attentional control, processing speed and reactive adaptation, executive and strategic control, visuospatial awareness and anticipation, decision-making and tactical reasoning, and multitasking and cognitive flexibility [ 27 – 33 ]. DI was defined as the frequency of decision-making events per minute during active play. Estimates were derived through an integrative review of evidence from systematic reviews, meta-analyses, narrative reviews, sport-specific game-dynamics studies, and data reported on official sport organization websites [ 34 – 46 ]. Both CB and DI were normalized independently using min–max scaling. The composite cognitive demand score (CCD) was calculated multiplicatively as: $$\:CC{D}_{i}={CB}_{i}^{{\prime\:}}\times\:{DI}_{i}^{{\prime\:}}$$ This formulation captures both the breadth and intensity of cognitive engagement. Physical demand (criterion 2) was represented by normalized metabolic equivalent of task (MET) values [ 47 ]. For sports not explicitly listed in standard MET compendiums [ 48 , 49 ], supplementary data were obtained from relevant published studies [ 50 – 53 ]. Safety (criterion 3) was assessed using sport-specific injury incidence data from national surveys conducted in Japan [ 54 ]. As injury incidence data for non-combat judo are not available in these surveys, injury risk was conservatively approximated as one order of magnitude lower than that reported for competitive judo, based on established differences between competitive and practice-based settings in judo epidemiology [ 55 ]. Social interaction (criterion 4) and feasibility-related criteria (criteria 5–7) were evaluated using ordinal scales based on structured assessments conducted by domain experts, followed by normalization. Applicability to VR and e-sports environments (criterion 8) was similarly assessed and normalized to ensure comparability across traditional and digitally extensible sports. To enhance transparency and methodological rigor, literature searches of PubMed and Web of Science (2000–2024) were conducted primarily to inform criteria requiring empirical quantification, particularly cognitive demand (criterion 1) and physical demand (criterion 2), and were supplemented by reference tracking of key reviews, consensus statements, and sport-specific reports. Importantly, this process was not intended as a formal systematic review or meta-analysis. Rather, it was designed to support criterion operationalization within a MCDA framework, where the primary objective is structured comparison across heterogeneous sport characteristics rather than exhaustive evidence synthesis. To minimize arbitrariness, multiple independent sources were consulted for each criterion, and extracted values were cross-checked against established benchmarks and prior comparative studies. This expert-informed, evidence-grounded approach is consistent with recommended practices for MCDA applications in health and implementation research. 2.2.3 Normalization Procedure To integrate heterogeneous data types, all criteria were normalized to a 0–1 range using min–max scaling with a small constant (ε = 0.01) to ensure numerical stability: $$\:{{C}^{{\prime\:}}}_{ij}=\frac{{C}_{ij}-min\left({C}_{j}\right)+\epsilon\:}{max\left({C}_{j}\right)-min\left({C}_{j}\right)+\epsilon\:}\:\:\epsilon\:=0.01$$ where \(\:{C{\prime\:}}_{ij}\) represents the normalized score of sport \(\:i\) for criterion \(\:j\) . For inverse criteria such as injury risk (criterion 3), the scaling was inverted so that higher values indicate greater favorability: $$\:{Safety}_{i}^{{\prime\:}}=\frac{max\left(Risk\right)-{Risk}_{i}+\epsilon\:}{max\left(Risk\right)-min\left(Risk\right)+\epsilon\:}\:\:\epsilon\:=0.01$$ 2.2.4 Integration into MCDA All normalized criteria were compiled into a unified dataset formatted for direct input into the MCDA framework, ensuring analytical compatibility prior to weighting and aggregation. 2.3 Weighting and Composite Score Integration To reflect the primary focus on dementia prevention, greater weights were assigned to cognitive and physical dimensions. Specifically, cognitive demand (criterion 1) and physical demand (criterion 2) were weighted at 1.5 and 1.2, respectively, while all remaining criteria (criteria 3–8) were equally weighted at 1.0. This weighting scheme is consistent with evidence on the combined cognitive and physical contributions to dementia and frailty prevention [ 56 , 57 ] and aligns with previous MCDA applications [ 25 , 26 ]. For each sport \(\:i\) , the weighted composite score was calculated as: where \(\:{C{\prime\:}}_{ij}\) denotes the normalized score for criterion \(\:j\) , and \(\:{w}_{j}\) represents the assigned weight. The resulting scores were used to rank sports according to their overall suitability for community-based implementation and their capacity for combined cognitive–physical engagement in older adults. The scoring of all criteria and the weighting scheme were developed through iterative discussions among all co-authors. Final values were confirmed by unanimous agreement to ensure methodological consistency and rigor. The co-author team comprised clinicians and researchers with expertise in neurology, dementia medicine, geriatric medicine, rehabilitation science, sports and exercise science, exercise physiology, and epidemiology/public health, ensuring that all evaluative decisions were grounded in multidisciplinary perspectives relevant to cognitive health and community exercise implementation. 3 Results 3.1 Intrinsic Performance Characteristics (Criteria 1–4) Intrinsic performance characteristics varied substantially across OSEs (Tables S1–S4). Table tennis demonstrated the highest cognitive demand, as indicated by the highest CCD score, followed by badminton. Basketball, volleyball, and soccer exhibited high CB but substantially lower DI, resulting in moderate-to-low CCD scores. Soccer showed one of the lowest CCD values, driven by particularly low DI, while baseball and non-combat judo also demonstrated very low CCD scores (Table S1 ). Physical demand differed markedly across OSEs. Soccer exhibited the highest MET-derived physical demand, followed by basketball and badminton. Tennis and table tennis showed moderate physical demand, whereas volleyball and non-combat judo demonstrated lower intensity. Baseball exhibited the lowest physical demand among the evaluated sports (Table S2 ). Safety scores were highest for non-combat judo and table tennis, whereas basketball and baseball showed comparatively lower safety scores (Table S3). Social interaction was greatest in soccer, followed by basketball and volleyball, while racket sports and non-combat judo demonstrated more limited interactive engagement (Table S4). 3.2 Feasibility Characteristics (Criteria 5–6) Feasibility-related characteristics also varied across sports (Tables S5–S6). Table tennis showed the most favorable facility and cost profile, with badminton, volleyball, and non-combat judo also scoring highly. In contrast, tennis, basketball, and soccer required greater facility and cost investments, while baseball demonstrated the lowest feasibility due to substantial space and equipment requirements (Table S5). Operational demands followed a similar pattern. Table tennis required the least instructor and operational support, whereas baseball and non-combat judo showed comparatively higher instructional and operational burdens (Table S6). 3.3 Sustainability and Digital Extensibility (Criteria 7–8) Sustainability-related characteristics (Table S7) were highest for table tennis, basketball, and volleyball, which scored favorably in terms of continuity, enjoyment, and personal cost. Tennis, badminton, soccer, and non-combat judo demonstrated moderate sustainability, whereas baseball showed the lowest sustainability score. Digital extensibility (Table S8) was greatest for table tennis, basketball, and baseball, reflecting their adaptability to VR and e-sports platforms. Tennis, badminton, volleyball, and soccer showed moderate digital applicability, while non-combat judo demonstrated minimal digital extensibility. 3.4 Overall Composite Suitability Scores and Ranking Applying the predefined weighting scheme, table tennis achieved the highest overall composite suitability score (6.541), indicating the most favorable balance across cognitive, physical, feasibility, and sustainability dimensions. Soccer (4.646), badminton (4.627), and basketball (4.495) followed with intermediate composite scores. Tennis (3.457), volleyball (3.413), and non-combat judo (2.550) showed lower overall suitability, while baseball ranked lowest among the eight sports (1.520). Detailed composite suitability scores are presented in Table 1 . Table 1 Normalized Criterion Scores and Weighted Composite Suitability Scores for Eight Open-Skill Exercises. Sport C1 Cognitive C2 Physical C3 Safety C4 Social C5 Facility/Cost C6 Operational C7 Continuity C8 Digital Overall Composite Suitability Score Tennis 0.364 0.354 0.471 0.005 0.336 0.507 0.500 0.667 3.457 Table tennis 0.769 0.425 0.872 0.005 1.000 1.000 1.000 1.000 6.541 Badminton 0.592 0.706 0.544 0.005 0.668 0.507 0.500 0.667 4.627 Basketball 0.146 0.706 0.084 0.502 0.336 0.507 1.000 1.000 4.495 Volleyball 0.354 0.237 0.254 0.502 0.668 0.507 1.000 0.667 3.413 Soccer 0.054 1.000 0.355 1.000 0.336 0.507 0.500 0.667 4.646 Baseball 0.000 † 0.002 0.002 0.502 0.003 0.005 0.005 1.000 1.520 Non-combat Judo 0.000 † 0.307 1.000 0.005 0.668 0.005 0.500 0.003 2.550 Notes: (1) † Values before rounding: Baseball = 0.00016164; Non-combat Judo = 0.00001640. (2) Scores shown are normalized (0–1) and unweighted. (3) For calculation of the Overall Composite Suitability Score, Criterion 1 (C1) and Criterion 2 (C2) were multiplied by 1.5 and 1.2, respectively; all other criteria (C3–C8) were weighted 1.0. (4) Overall Composite Suitability Score = Σ (normalized score × weight). (5) Social Interaction scores reflect team-based and multi-player interaction intensity during typical play, rather than dyadic or turn-based interaction. (6) Criterion definitions: C1 = Cognitive demand, C2 = Physical demand and exercise intensity, C3 = Safety, C4 = Social interaction, C5 = Facility and cost demand, C6 = Instructor and operational demand, C7 = Continuity, enjoyment, and personal cost, C8 = Applicability to VR and e-sports environments. 4 Discussion This study provides a comprehensive multidimensional comparison of eight OSEs using a transparent MCDA framework that integrates cognitive, physical, social, safety, operational, sustainability, and digital-replicability dimensions. The findings indicate substantial heterogeneity across sports and highlight that OSEs differ not only in their cognitive–physical profiles but also in their feasibility for large-scale implementation in aging communities. The following sections elaborate on mechanistic interpretations, practical implications, and the broader significance of these results for cognitive health promotion, with particular attention to frailty prevention and public health relevance. 4.1 Intrinsic Determinants of Cognitive–Physical Engagement in OSEs The most prominent findings relate to the substantial variability in CCD, arising from distinct combinations of CB and DI across sports. Table tennis and badminton—both characterized by rapid ball trajectories, high temporal pressure, unpredictable bounce patterns, and continuous bidirectional visuomotor exchange [ 22 , 23 ]—exhibited the highest CCD values, reflecting the concurrent presence of both high CB and high DI. These sports require engagement across a wide range of cognitive domains, including sustained and selective attention, visuospatial prediction, working-memory updating, and rapid reactive decision-making, while also demanding frequent, time-critical decisions during active play [ 22 , 23 ]. Such high-tempo, perceptually dynamic environments are known to engage frontoparietal attention networks, visuocerebellar pathways, and sensorimotor integration circuits—neural systems that play key roles in cognitive resilience [ 22 , 23 , 58 – 61 ]. Consistent with this interpretation, prior narrative and systematic reviews have repeatedly associated open-skill racket sports with preserved cognitive function in later life, suggesting that the combination of broad cognitive engagement (high CB) and sustained decisional pressure (high DI), as captured by elevated CCD, may underlie their observed cognitive benefits [ 22 , 23 , 62 , 63 ]. In contrast, team-based invasion sports such as basketball, volleyball, and soccer demonstrated high CB but substantially lower DI, resulting in moderate-to-low CCD values. Although these sports involve cognitively rich and unpredictable environments, the distributed decision-making structure intrinsic to team play reduces the number of discrete, high-stakes decisions executed by an individual player per unit time. This dissociation highlights the importance of jointly considering cognitive breadth and decision intensity when characterizing real-time cognitive load in OSEs. Baseball and non-combat judo exhibited near-minimum CCD values, primarily driven by extremely low DI, indicating limited continuous cognitive challenge despite containing elements traditionally classified as open-skill. These findings support our initial hypothesis that OSEs characterized by high environmental unpredictability coupled with frequent individual decision-making—most notably racket sports—would impose greater real-time cognitive demands and more strongly engage neural systems implicated in cognitive resilience. Physical demand also varied widely across sports. Soccer, basketball, and badminton demonstrated the highest metabolic intensities [ 48 , 49 ], consistent with prior time–motion analyses [ 23 , 64 , 65 ]. Both aerobic and anaerobic components of OSEs are known to support cognitive health through mechanisms including brain-derived neurotrophic factor upregulation, improved cerebral perfusion, enhanced mitochondrial function, and modulation of inflammatory pathways [ 13 , 14 ]. Importantly, beyond cardiometabolic load, many racket sports also require repeated rapid accelerations, decelerations, and directional changes [ 22 , 23 ]. Such movement patterns preferentially recruit fast-twitch (type II) muscle fibers, which are known to decline disproportionately with aging [ 66 ]. The preservation and functional engagement of these fibers may contribute to the maintenance of agility, balance recovery, and reactive motor responses, thereby supporting not only physical function but also mobility-related aspects of cognitive–motor integration [ 67 , 68 ]. From this exercise-physiological perspective, open-skill racket sports may offer added benefits for mitigating age-related declines in neuromuscular responsiveness, complementing their cognitive demands. Moderate-intensity sports such as table tennis and tennis offer cognitively meaningful stimulation while minimizing cardiometabolic burden, rendering them accessible to older adults with varying fitness levels [ 13 , 14 , 22 ]. Volleyball and non-combat judo fell at the lower end of metabolic intensity, suggesting their suitability for participants requiring lighter physical activity. These results emphasize the importance of aligning physical intensity with participant functional status and intervention objectives, particularly in aging populations. Safety scores varied substantially. Table tennis and non-combat judo showed the most favorable safety profiles, while basketball, volleyball, and baseball showed comparatively high injury incidence, largely driven by collision mechanisms, rapid directional changes, and ball-related impacts [ 54 ]. Injury risk is a critical determinant of long-term adherence among older adults, as fear of injury and perceived unsafety are common barriers to sustained participation [ 69 ]. Even minor injuries may precipitate deconditioning, mobility loss, or withdrawal from structured exercise programs, underscoring the importance of safety-oriented sport selection and age-adapted rule modifications. Substantial variation was also observed in social interaction scores. Soccer, basketball, and volleyball exhibited high levels of multilateral social interaction, which may support motivation, social cohesion, and emotional well-being—factors consistently linked to cognitive resilience and reduced dementia risk [ 70 – 72 ]. In contrast, racket sports and non-combat judo showed limited social interaction, which may be advantageous for individuals preferring low-interaction environments. Tailoring sport selection to social preference profiles may enhance adherence and program effectiveness. Collectively, these findings indicate that intrinsic sport characteristics—including real-time cognitive demand, neuromuscular engagement, physical intensity, injury risk, and social interaction—jointly shape the quality and feasibility of cognitive–physical engagement in OSEs. Importantly, these multidimensional attributes suggest that OSEs may contribute not only to cognitive health but also to the prevention or mitigation of cognitive, physical, and social frailty, a construct of growing global relevance in aging societies. 4.2 Practical Feasibility and Implementation Constraints Feasibility characteristics emerged as essential differentiators. Table tennis and badminton required minimal space, inexpensive equipment, and limited supervision, making them highly compatible with community centers, public halls, and multipurpose indoor facilities. Sports requiring large fields (soccer, baseball) or dedicated courts (tennis, basketball) may face infrastructural barriers, particularly in densely populated urban areas. Operational demands were lowest for table tennis and highest for baseball and non-combat judo, highlighting the importance of technical complexity and supervision requirements in scaling interventions. These findings align with implementation science frameworks emphasizing cost-effectiveness, adaptability, and infrastructural compatibility as key determinants of successful community-based physical activity programs for older adults [ 73 – 75 ]. 4.3 Sustainability, Enjoyment, and Long-Term Adherence Long-term adherence reflects a combination of enjoyment, perceived competence, accessibility, and social reinforcement. Extensive evidence indicates that intrinsic motivation and supportive environmental contexts are central determinants of sustained physical activity participation in older adults [ 76 – 78 ]. In the present analysis, table tennis, basketball, and volleyball scored highest in sustainability, consistent with their recreational appeal and manageable participation barriers. In contrast, sports associated with greater organizational complexity or equipment demands, such as baseball, demonstrated lower sustainability scores. Given the central role of adherence in preventing functional decline and frailty progression, sustainability should be considered a primary criterion in the design of community-based cognitive–physical interventions. 4.4 Digital Extensibility and Hybrid Training Opportunities Digital replicability varied substantially across sports. Table tennis, basketball, and baseball demonstrated high VR and e-sports applicability, benefiting from established simulation technologies capable of reproducing perceptual–motor timing and decision-making demands. In contrast, sports requiring paired or synchronized full-body interaction, such as non-combat judo, showed limited digital extensibility. Emerging evidence suggests that VR-based and digitally mediated exercise interventions can enhance motivation, engagement, and accessibility while supporting integrated cognitive and physical training in older adults [ 79 – 81 ]. Hybrid digital–physical paradigms may therefore complement traditional community sports by mitigating space, staffing, and accessibility constraints, rather than replacing in-person activities. 4.5 Integrative Interpretation and Public Health Implications When weighted according to dementia-prevention priorities, table tennis emerged as the most balanced OSE across cognitive, physical, safety, operational, sustainability, and digital dimensions. Its integrated profile aligns well with the heterogeneous neurocognitive, functional, and practical needs of aging adults. From a public health perspective, these findings argue against a one-size-fits-all approach. Instead, offering a diversified portfolio of OSEs—combining cognitively demanding racket sports, socially engaging team activities, and low-intensity accessible formats—may maximize reach, adherence, and impact across diverse aging populations, while simultaneously addressing multiple domains of frailty. 4.6 Strengths, Limitations, and Future Directions This study has several strengths, including the use of a transparent MCDA framework, the operationalization of cognitive demand using a dual-component CCD metric, and the inclusion of emerging dimensions such as digital extensibility. However, several limitations warrant consideration. CB and DI estimates were derived from published match analyses and may not generalize across populations or modified formats. MET values reflect typical intensities and may differ in age-adapted implementations. Several criteria relied on structured expert evaluation rather than large-scale empirical data, and the applied weighting scheme represents one of several plausible modeling choices. In addition, sport participation and performance may be influenced by sex-related physiological and sociocultural factors, potentially limiting the generalizability of findings across genders. Future studies should explicitly examine sex-specific responses to OSE participation. Future research should include mechanistic validation using mobile neuroimaging and wearable sensors, longitudinal intervention trials comparing high- and low-CCD sports, and pragmatic implementation studies evaluating cost-effectiveness and adherence across diverse populations. Further development of VR-based and hybrid OSE platforms may also expand accessibility and scalability. 5 Conclusions This multidimensional evaluation demonstrates that OSEs exhibit marked heterogeneity across cognitive, physical, social, safety, operational, sustainability, and digital-extensibility dimensions, underscoring the limitations of single-domain approaches to sport-based dementia prevention. By applying a transparent, dementia-prevention–oriented MCDA framework, this study advances a structured and reproducible method for comparing heterogeneous sports in terms of both neurocognitive engagement and real-world feasibility. Within this integrative framework, racket-based sports—most notably table tennis and badminton—emerged as among the most well-balanced options. Their combination of high real-time cognitive demand, agility-oriented neuromuscular engagement, moderate and adaptable physical load, favorable safety profiles, minimal infrastructural requirements, and strong potential for digital extension provides a coherent mechanistic and practical explanation for their consistently reported cognitive benefits in later life. Beyond identifying individual “optimal” sports, the present findings support a portfolio-based public health strategy that integrates cognitively demanding, socially engaging, and highly accessible activities to accommodate heterogeneity in functional capacity, motivational profiles, sex-related differences, and community infrastructure. By bridging neurocognitive mechanisms, exercise physiology, implementation science, and emerging digital modalities, this framework offers an evidence-informed foundation for designing sustainable activity ecosystems that support healthy brain aging and frailty prevention in rapidly aging societies. Declarations Contributions Conceptualization, T.Y.; Methodology, T.Y.; Data Collection, T.Y., K.H., T.I., and S.H.; Analysis, T.Y., K.H., T.I., S.H., and S.K.; Writing—Original Draft Preparation, T.Y.; Writing—Review and Editing, T.Y., K.H., T.I., S.H., and S.K.; Supervision, S.K., All authors have read and agreed to the published version of the manuscript. Funding This research received no external funding. Ethics declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. References World Health Organization. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8671463","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584600525,"identity":"12451fa7-569b-4998-8c53-f524ed7b042c","order_by":0,"name":"Takao Yamasaki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYPCCBB5+HiDFwyDBwNhArBbJHlK1MBicAWshAhgcP5348UdNmozxmTNmEm9qLBiYZxOwxuBM7mZpnmM5PGZne8wk5xwDOmzOAQJaDuRukGZgq+AxO89jJs3DBtQyI4GAlvNvN//88a+Cx7gfpOUfMVpu5G6T4G3L4THg7TGT5m0jQovkjbfbrHn70ngkzhwrtpzbJ8FD0C9853M33/zxLdmevyd544033+rkDAmFmALCSA4DEMljOAO/DgZ5hJHsDyAiEgS0jIJRMApGwYgDAI1MQzDrJUbzAAAAAElFTkSuQmCC","orcid":"","institution":"Minkodo Minohara Hospital","correspondingAuthor":true,"prefix":"","firstName":"Takao","middleName":"","lastName":"Yamasaki","suffix":""},{"id":584600527,"identity":"360d7bb7-357a-4ba7-9a05-ccdd1a001f04","order_by":1,"name":"Kazuto Hamaguchi","email":"","orcid":"","institution":"Hiroshima University","correspondingAuthor":false,"prefix":"","firstName":"Kazuto","middleName":"","lastName":"Hamaguchi","suffix":""},{"id":584600530,"identity":"0625e39e-acf7-48ef-b4e7-7568085a4df8","order_by":2,"name":"Takuro Ikeda","email":"","orcid":"","institution":"Fukuoka International University of Health and Welfare","correspondingAuthor":false,"prefix":"","firstName":"Takuro","middleName":"","lastName":"Ikeda","suffix":""},{"id":584600531,"identity":"bdb586c5-26d9-48f6-93db-9f677c70fe87","order_by":3,"name":"Shigetada Hiraoka","email":"","orcid":"","institution":"Kumagai Institute of Health Policy","correspondingAuthor":false,"prefix":"","firstName":"Shigetada","middleName":"","lastName":"Hiraoka","suffix":""},{"id":584600534,"identity":"34ae7607-c36d-412c-93fc-8ab2db079443","order_by":4,"name":"Shuzo Kumagai","email":"","orcid":"","institution":"Kumagai Institute of Health Policy","correspondingAuthor":false,"prefix":"","firstName":"Shuzo","middleName":"","lastName":"Kumagai","suffix":""}],"badges":[],"createdAt":"2026-01-22 15:38:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8671463/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8671463/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101882967,"identity":"9a18a4ad-c437-406e-8ec1-c79f845e625e","added_by":"auto","created_at":"2026-02-04 15:26:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":945098,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8671463/v1/233be1a2-0caf-4b9c-9aed-3b7a6e83774a.pdf"},{"id":101881411,"identity":"22fd5a8e-3c27-4955-ba70-471d8949cfd8","added_by":"auto","created_at":"2026-02-04 15:11:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":45642,"visible":true,"origin":"","legend":"","description":"","filename":"YamasakiDiscoverAgingSupplmentaryMaterialTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8671463/v1/ffbaf9f3f183b9a4af681964.docx"},{"id":101844278,"identity":"8bd09459-af40-4b6a-b0b6-9336c53356b7","added_by":"auto","created_at":"2026-02-04 09:05:25","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":47076,"visible":true,"origin":"","legend":"","description":"","filename":"YamasakiDiscoverAgingSupplmentaryMaterialMethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-8671463/v1/5d5a01e27ae15166f643f27a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multi-Criteria Decision Analysis of Open-Skill Exercise-Based Sports for Cognitive Health Promotion in Older Adults","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eCognitive decline and dementia represent some of the most pressing challenges confronting rapidly aging societies. As global life expectancy continues to rise, the prevalence of cognitive disorders is projected to increase substantially, imposing profound social, economic, and healthcare burdens at both individual and societal levels [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Accordingly, the identification of scalable and evidence-based strategies capable of preserving cognitive function and promoting healthy brain aging has emerged as a critical public health priority.\u003c/p\u003e \u003cp\u003eConsistent with global prevention strategies, regular physical activity is recommended as a key modifiable lifestyle factor for reducing the risk of cognitive decline and dementia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A growing body of evidence demonstrates that physical activity exerts robust and multifaceted benefits on brain health through several converging neurobiological pathways. These include improvements in cardiovascular and cerebrovascular function, upregulation of neurotrophic signaling\u0026mdash;particularly brain-derived neurotrophic factor\u0026mdash;enhancement of synaptic plasticity and large-scale brain network organization, attenuation of chronic neuroinflammatory processes, and facilitation of protein homeostasis mechanisms such as amyloid-β clearance [\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. At the molecular and cellular levels, exercise-induced adaptations involve coordinated regulation of neurotrophic, metabolic, immune, and autophagic pathways, collectively enhancing neuronal resilience and plasticity [\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThrough these interrelated mechanisms, physical activity contributes to the preservation of brain structure and function and supports cognitive performance across multiple domains during aging. These mechanistic insights are supported by accumulating clinical evidence, with systematic reviews, meta-analyses, and umbrella reviews consistently demonstrating that physical activity is associated with meaningful improvements in cognitive function across a broad range of neurocognitive conditions and aging populations [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the broad category of physical activity, accumulating evidence suggests that the cognitive and neural benefits of exercise may depend not only on intensity or volume, but also on the environmental and cognitive demands imposed by the activity itself. In this study, the term open-skill exercise (OSE) is used to refer to sport-based physical activities performed in externally paced, unpredictable environments that require continuous perceptual\u0026ndash;motor adaptation. Examples include table tennis, tennis, and badminton [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In contrast, closed-skill exercise (CSE) is typically performed in stable and predictable environments, such as walking or stationary cycling [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. OSE inherently involves continuous processing of environmental cues, dynamic decision-making, attentional switching, and visuomotor integration. These features impose greater cognitive demands and may stimulate frontal\u0026ndash;parietal, cerebellar, and sensorimotor networks more extensively than CSE, leading to enhancements in executive function, visuospatial processing, and processing speed [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Empirical findings increasingly support the potentially superior cognitive benefits of OSE in older adults [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeyond cognitive outcomes, OSE also has the potential to address multiple domains of frailty, including physical and social frailty, which are increasingly recognized as interrelated determinants of functional decline and dementia risk in aging societies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In particular, sport-based activities that require agility, rapid motor responses, and interpersonal interaction may contribute to the maintenance of muscle power, coordination, and social connectedness in older adults [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, how different OSEs balance cognitive demand, physical load, social engagement, safety, and real-world feasibility remains insufficiently understood.\u003c/p\u003e \u003cp\u003eDespite growing interest in OSE as an environmental\u0026ndash;cognitive intervention, the current literature remains fragmented. Many studies focus on a single sport or specific training protocol [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], limiting understanding of how different OSEs compare in terms of their neural, cognitive, and practical attributes. Moreover, factors such as injury risk, accessibility of facilities, social engagement opportunities, and cost strongly shape the real-world feasibility of regular participation. Although meta-analyses have contrasted OSE and CSE in general [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], systematic comparisons across different OSEs, grounded in the environmental demands they impose on the nervous system, remain scarce.\u003c/p\u003e \u003cp\u003eTo address this gap, the present study evaluates eight OSEs that are widely accessible to older adults, examining their cognitive and physical characteristics as well as the environmental demands imposed on perceptual, motor, and neural systems. Using a transparent multi-criteria decision analysis (MCDA) framework\u0026mdash;a structured approach for integrating multiple, often competing criteria into a single evaluative framework [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u0026mdash;we integrate cognitive load, physical demands, social interaction potential, and environmental and practical feasibility to derive an overall suitability ranking. We hypothesize that OSEs characterized by higher environmental unpredictability, particularly racket sports, will show greater alignment with neural mechanisms supporting cognitive resilience.\u003c/p\u003e \u003cp\u003eUltimately, by linking environmental characteristics of sports with objective cognitive-health considerations, this study provides actionable guidance for community program development, resource allocation, and policy design. The findings contribute to ongoing efforts to develop ecologically valid, environment-based strategies that promote cognitive health and adaptive brain function in aging populations.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Selection of OSEs\u003c/h2\u003e\n \u003cp\u003eThe conceptual distinction between OSEs and CSEs provides a useful theoretical framework for classifying sports, although most sports incorporate both elements to varying degrees. These activities exist along a continuum, with higher categories emphasizing externally driven, unpredictable environments characteristic of OSEs, and lower categories emphasizing self-paced, repetitive movements typical of CSEs [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. Based on this established classification, fourteen sports have been identified as Category 4, representing a high degree of open-skill characteristics: tennis, table tennis, badminton, basketball, volleyball (including beach volleyball), soccer, handball, American football, wushu, martial arts (judo), fencing, korfball, hockey, and baseball [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFor the present study, this initial list was refined to ensure both theoretical rigor and practical relevance for older adult populations. Refinement was guided by three predefined criteria: (i) global or regional participation, (ii) feasibility of community-level implementation among older adults, and (iii) available evidence supporting safety, accessibility, and cognitive benefits.\u003c/p\u003e\n \u003cp\u003eSix sports were excluded accordingly. Korfball and wushu were removed due to limited international dissemination and minimal adoption among older adults. American football was excluded despite the existence of senior-oriented variants (e.g., flag football) because of concerns regarding accessibility, safety, and insufficient supporting evidence. Fencing, hockey, and handball were also omitted due to low participation rates among older adults and limited evidence regarding their feasibility as community-based health-promoting activities. Regarding martial arts, the scope was restricted to judo, specifically non-combat modalities such as kata and structured training sessions, which have demonstrated greater adaptability and safety for older adults [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eAs a result, eight OSEs were retained for systematic evaluation: tennis, table tennis, badminton, basketball, volleyball (including beach volleyball), soccer, baseball, and martial arts (non-combat judo). Although some of these sports may present practical challenges for direct implementation in older populations, their inclusion allows a comprehensive comparison of OSE-related mechanisms and their potential relevance to dementia prevention and community-based interventions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Evaluation Criteria and Scoring Framework\u003c/h2\u003e\n \u003cp\u003eThis study employed a MCDA framework to systematically compare the selected OSEs across multiple dimensions relevant to cognitive health promotion and community implementation (see Supplementary Methods for detailed procedures).\u003c/p\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Evaluation Domains and Criteria Overview\u003c/h2\u003e\n \u003cp\u003eEach sport was evaluated using eight predefined criteria, organized into four conceptual domains:\u003c/p\u003e\n \u003cp\u003eDomain A: Intrinsic features \u0026mdash; cognitive demand (criterion 1), physical demand and exercise intensity (criterion 2), safety (criterion 3), and social interaction (criterion 4);\u003c/p\u003e\n \u003cp\u003eDomain B: Implementation feasibility \u0026mdash; facility and cost demand (criterion 5), and instructor and operational demand (criterion 6);\u003c/p\u003e\n \u003cp\u003eDomain C: Sustainability and attractiveness \u0026mdash; continuity, enjoyment, and personal cost (criterion 7);\u003c/p\u003e\n \u003cp\u003eDomain D: Digital extensibility \u0026mdash; applicability to virtual reality (VR) and e-sports environments (criterion 8).\u003c/p\u003e\n \u003cp\u003eTogether, these criteria capture cognitive, physical, social, safety-related, operational, sustainability, and technological dimensions relevant to community-based exercise programs.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Assessment of Individual Criteria\u003c/h2\u003e\n \u003cp\u003eCognitive demand (criterion 1) was quantified as a composite measure comprising two components: cognitive breadth (CB) and decision intensity (DI).\u003c/p\u003e\n \u003cp\u003eCB was operationalized as the number of cognitive domains engaged during active play, calculated as a cumulative score across six core domains: perceptual\u0026ndash;attentional control, processing speed and reactive adaptation, executive and strategic control, visuospatial awareness and anticipation, decision-making and tactical reasoning, and multitasking and cognitive flexibility [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eDI was defined as the frequency of decision-making events per minute during active play. Estimates were derived through an integrative review of evidence from systematic reviews, meta-analyses, narrative reviews, sport-specific game-dynamics studies, and data reported on official sport organization websites [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eBoth CB and DI were normalized independently using min\u0026ndash;max scaling. The composite cognitive demand score (CCD) was calculated multiplicatively as:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:CC{D}_{i}={CB}_{i}^{{\\prime\\:}}\\times\\:{DI}_{i}^{{\\prime\\:}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eThis formulation captures both the breadth and intensity of cognitive engagement.\u003c/p\u003e\n \u003cp\u003ePhysical demand (criterion 2) was represented by normalized metabolic equivalent of task (MET) values [\u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]. For sports not explicitly listed in standard MET compendiums [\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e], supplementary data were obtained from relevant published studies [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eSafety (criterion 3) was assessed using sport-specific injury incidence data from national surveys conducted in Japan [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e]. As injury incidence data for non-combat judo are not available in these surveys, injury risk was conservatively approximated as one order of magnitude lower than that reported for competitive judo, based on established differences between competitive and practice-based settings in judo epidemiology [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eSocial interaction (criterion 4) and feasibility-related criteria (criteria 5\u0026ndash;7) were evaluated using ordinal scales based on structured assessments conducted by domain experts, followed by normalization.\u003c/p\u003e\n \u003cp\u003eApplicability to VR and e-sports environments (criterion 8) was similarly assessed and normalized to ensure comparability across traditional and digitally extensible sports.\u003c/p\u003e\n \u003cp\u003eTo enhance transparency and methodological rigor, literature searches of PubMed and Web of Science (2000\u0026ndash;2024) were conducted primarily to inform criteria requiring empirical quantification, particularly cognitive demand (criterion 1) and physical demand (criterion 2), and were supplemented by reference tracking of key reviews, consensus statements, and sport-specific reports. Importantly, this process was not intended as a formal systematic review or meta-analysis. Rather, it was designed to support criterion operationalization within a MCDA framework, where the primary objective is structured comparison across heterogeneous sport characteristics rather than exhaustive evidence synthesis. To minimize arbitrariness, multiple independent sources were consulted for each criterion, and extracted values were cross-checked against established benchmarks and prior comparative studies. This expert-informed, evidence-grounded approach is consistent with recommended practices for MCDA applications in health and implementation research.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Normalization Procedure\u003c/h2\u003e\n \u003cp\u003eTo integrate heterogeneous data types, all criteria were normalized to a 0\u0026ndash;1 range using min\u0026ndash;max scaling with a small constant (\u0026epsilon;\u0026thinsp;=\u0026thinsp;0.01) to ensure numerical stability:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:{{C}^{{\\prime\\:}}}_{ij}=\\frac{{C}_{ij}-min\\left({C}_{j}\\right)+\\epsilon\\:}{max\\left({C}_{j}\\right)-min\\left({C}_{j}\\right)+\\epsilon\\:}\\:\\:\\epsilon\\:=0.01$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C{\\prime\\:}}_{ij}\\)\u003c/span\u003e\u003c/span\u003e represents the normalized score of sport \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e for criterion \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:j\\)\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eFor inverse criteria such as injury risk (criterion 3), the scaling was inverted so that higher values indicate greater favorability:\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e$$\\:{Safety}_{i}^{{\\prime\\:}}=\\frac{max\\left(Risk\\right)-{Risk}_{i}+\\epsilon\\:}{max\\left(Risk\\right)-min\\left(Risk\\right)+\\epsilon\\:}\\:\\:\\epsilon\\:=0.01$$\u003c/div\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.4 Integration into MCDA\u003c/h2\u003e\n \u003cp\u003eAll normalized criteria were compiled into a unified dataset formatted for direct input into the MCDA framework, ensuring analytical compatibility prior to weighting and aggregation.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Weighting and Composite Score Integration\u003c/h2\u003e\n \u003cp\u003eTo reflect the primary focus on dementia prevention, greater weights were assigned to cognitive and physical dimensions. Specifically, cognitive demand (criterion 1) and physical demand (criterion 2) were weighted at 1.5 and 1.2, respectively, while all remaining criteria (criteria 3\u0026ndash;8) were equally weighted at 1.0. This weighting scheme is consistent with evidence on the combined cognitive and physical contributions to dementia and frailty prevention [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e] and aligns with previous MCDA applications [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFor each sport \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e, the weighted composite score was calculated as:\u003c/p\u003e\n \u003cdiv id=\"Equd\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C{\\prime\\:}}_{ij}\\)\u003c/span\u003e\u003c/span\u003e denotes the normalized score for criterion \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:j\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{w}_{j}\\)\u003c/span\u003e\u003c/span\u003e represents the assigned weight. The resulting scores were used to rank sports according to their overall suitability for community-based implementation and their capacity for combined cognitive\u0026ndash;physical engagement in older adults.\u003c/p\u003e\n \u003cp\u003eThe scoring of all criteria and the weighting scheme were developed through iterative discussions among all co-authors. Final values were confirmed by unanimous agreement to ensure methodological consistency and rigor. The co-author team comprised clinicians and researchers with expertise in neurology, dementia medicine, geriatric medicine, rehabilitation science, sports and exercise science, exercise physiology, and epidemiology/public health, ensuring that all evaluative decisions were grounded in multidisciplinary perspectives relevant to cognitive health and community exercise implementation.\u003c/p\u003e\n \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Intrinsic Performance Characteristics (Criteria 1\u0026ndash;4)\u003c/h2\u003e \u003cp\u003eIntrinsic performance characteristics varied substantially across OSEs (Tables S1\u0026ndash;S4). Table tennis demonstrated the highest cognitive demand, as indicated by the highest CCD score, followed by badminton. Basketball, volleyball, and soccer exhibited high CB but substantially lower DI, resulting in moderate-to-low CCD scores. Soccer showed one of the lowest CCD values, driven by particularly low DI, while baseball and non-combat judo also demonstrated very low CCD scores (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePhysical demand differed markedly across OSEs. Soccer exhibited the highest MET-derived physical demand, followed by basketball and badminton. Tennis and table tennis showed moderate physical demand, whereas volleyball and non-combat judo demonstrated lower intensity. Baseball exhibited the lowest physical demand among the evaluated sports (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSafety scores were highest for non-combat judo and table tennis, whereas basketball and baseball showed comparatively lower safety scores (Table S3). Social interaction was greatest in soccer, followed by basketball and volleyball, while racket sports and non-combat judo demonstrated more limited interactive engagement (Table S4).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Feasibility Characteristics (Criteria 5\u0026ndash;6)\u003c/h2\u003e \u003cp\u003eFeasibility-related characteristics also varied across sports (Tables S5\u0026ndash;S6). Table tennis showed the most favorable facility and cost profile, with badminton, volleyball, and non-combat judo also scoring highly. In contrast, tennis, basketball, and soccer required greater facility and cost investments, while baseball demonstrated the lowest feasibility due to substantial space and equipment requirements (Table S5).\u003c/p\u003e \u003cp\u003eOperational demands followed a similar pattern. Table tennis required the least instructor and operational support, whereas baseball and non-combat judo showed comparatively higher instructional and operational burdens (Table S6).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sustainability and Digital Extensibility (Criteria 7\u0026ndash;8)\u003c/h2\u003e \u003cp\u003eSustainability-related characteristics (Table S7) were highest for table tennis, basketball, and volleyball, which scored favorably in terms of continuity, enjoyment, and personal cost. Tennis, badminton, soccer, and non-combat judo demonstrated moderate sustainability, whereas baseball showed the lowest sustainability score.\u003c/p\u003e \u003cp\u003eDigital extensibility (Table S8) was greatest for table tennis, basketball, and baseball, reflecting their adaptability to VR and e-sports platforms. Tennis, badminton, volleyball, and soccer showed moderate digital applicability, while non-combat judo demonstrated minimal digital extensibility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Overall Composite Suitability Scores and Ranking\u003c/h2\u003e \u003cp\u003eApplying the predefined weighting scheme, table tennis achieved the highest overall composite suitability score (6.541), indicating the most favorable balance across cognitive, physical, feasibility, and sustainability dimensions. Soccer (4.646), badminton (4.627), and basketball (4.495) followed with intermediate composite scores. Tennis (3.457), volleyball (3.413), and non-combat judo (2.550) showed lower overall suitability, while baseball ranked lowest among the eight sports (1.520). Detailed composite suitability scores are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNormalized Criterion Scores and Weighted Composite Suitability Scores for Eight Open-Skill Exercises.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSport\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1 Cognitive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC2 Physical\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC3 Safety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC4 Social\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC5 Facility/Cost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eC6 Operational\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eC7 Continuity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eC8 Digital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOverall Composite Suitability Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTennis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.457\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTable tennis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBadminton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.627\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasketball\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.495\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolleyball\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoccer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseball\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000 \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-combat Judo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000 \u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNotes: (1) \u0026dagger; Values before rounding: Baseball\u0026thinsp;=\u0026thinsp;0.00016164; Non-combat Judo\u0026thinsp;=\u0026thinsp;0.00001640. (2) Scores shown are normalized (0\u0026ndash;1) and unweighted. (3) For calculation of the Overall Composite Suitability Score, Criterion 1 (C1) and Criterion 2 (C2) were multiplied by 1.5 and 1.2, respectively; all other criteria (C3\u0026ndash;C8) were weighted 1.0. (4) Overall Composite Suitability Score\u0026thinsp;=\u0026thinsp;Σ (normalized score \u0026times; weight). (5) Social Interaction scores reflect team-based and multi-player interaction intensity during typical play, rather than dyadic or turn-based interaction. (6) Criterion definitions: C1\u0026thinsp;=\u0026thinsp;Cognitive demand, C2\u0026thinsp;=\u0026thinsp;Physical demand and exercise intensity, C3\u0026thinsp;=\u0026thinsp;Safety, C4\u0026thinsp;=\u0026thinsp;Social interaction, C5\u0026thinsp;=\u0026thinsp;Facility and cost demand, C6\u0026thinsp;=\u0026thinsp;Instructor and operational demand, C7\u0026thinsp;=\u0026thinsp;Continuity, enjoyment, and personal cost, C8\u0026thinsp;=\u0026thinsp;Applicability to VR and e-sports environments.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study provides a comprehensive multidimensional comparison of eight OSEs using a transparent MCDA framework that integrates cognitive, physical, social, safety, operational, sustainability, and digital-replicability dimensions. The findings indicate substantial heterogeneity across sports and highlight that OSEs differ not only in their cognitive\u0026ndash;physical profiles but also in their feasibility for large-scale implementation in aging communities. The following sections elaborate on mechanistic interpretations, practical implications, and the broader significance of these results for cognitive health promotion, with particular attention to frailty prevention and public health relevance.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Intrinsic Determinants of Cognitive\u0026ndash;Physical Engagement in OSEs\u003c/h2\u003e \u003cp\u003eThe most prominent findings relate to the substantial variability in CCD, arising from distinct combinations of CB and DI across sports. Table tennis and badminton\u0026mdash;both characterized by rapid ball trajectories, high temporal pressure, unpredictable bounce patterns, and continuous bidirectional visuomotor exchange [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u0026mdash;exhibited the highest CCD values, reflecting the concurrent presence of both high CB and high DI. These sports require engagement across a wide range of cognitive domains, including sustained and selective attention, visuospatial prediction, working-memory updating, and rapid reactive decision-making, while also demanding frequent, time-critical decisions during active play [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSuch high-tempo, perceptually dynamic environments are known to engage frontoparietal attention networks, visuocerebellar pathways, and sensorimotor integration circuits\u0026mdash;neural systems that play key roles in cognitive resilience [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR59 CR60\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Consistent with this interpretation, prior narrative and systematic reviews have repeatedly associated open-skill racket sports with preserved cognitive function in later life, suggesting that the combination of broad cognitive engagement (high CB) and sustained decisional pressure (high DI), as captured by elevated CCD, may underlie their observed cognitive benefits [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, team-based invasion sports such as basketball, volleyball, and soccer demonstrated high CB but substantially lower DI, resulting in moderate-to-low CCD values. Although these sports involve cognitively rich and unpredictable environments, the distributed decision-making structure intrinsic to team play reduces the number of discrete, high-stakes decisions executed by an individual player per unit time. This dissociation highlights the importance of jointly considering cognitive breadth and decision intensity when characterizing real-time cognitive load in OSEs.\u003c/p\u003e \u003cp\u003eBaseball and non-combat judo exhibited near-minimum CCD values, primarily driven by extremely low DI, indicating limited continuous cognitive challenge despite containing elements traditionally classified as open-skill. These findings support our initial hypothesis that OSEs characterized by high environmental unpredictability coupled with frequent individual decision-making\u0026mdash;most notably racket sports\u0026mdash;would impose greater real-time cognitive demands and more strongly engage neural systems implicated in cognitive resilience.\u003c/p\u003e \u003cp\u003ePhysical demand also varied widely across sports. Soccer, basketball, and badminton demonstrated the highest metabolic intensities [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], consistent with prior time\u0026ndash;motion analyses [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Both aerobic and anaerobic components of OSEs are known to support cognitive health through mechanisms including brain-derived neurotrophic factor upregulation, improved cerebral perfusion, enhanced mitochondrial function, and modulation of inflammatory pathways [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImportantly, beyond cardiometabolic load, many racket sports also require repeated rapid accelerations, decelerations, and directional changes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Such movement patterns preferentially recruit fast-twitch (type II) muscle fibers, which are known to decline disproportionately with aging [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. The preservation and functional engagement of these fibers may contribute to the maintenance of agility, balance recovery, and reactive motor responses, thereby supporting not only physical function but also mobility-related aspects of cognitive\u0026ndash;motor integration [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. From this exercise-physiological perspective, open-skill racket sports may offer added benefits for mitigating age-related declines in neuromuscular responsiveness, complementing their cognitive demands.\u003c/p\u003e \u003cp\u003eModerate-intensity sports such as table tennis and tennis offer cognitively meaningful stimulation while minimizing cardiometabolic burden, rendering them accessible to older adults with varying fitness levels [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Volleyball and non-combat judo fell at the lower end of metabolic intensity, suggesting their suitability for participants requiring lighter physical activity. These results emphasize the importance of aligning physical intensity with participant functional status and intervention objectives, particularly in aging populations.\u003c/p\u003e \u003cp\u003eSafety scores varied substantially. Table tennis and non-combat judo showed the most favorable safety profiles, while basketball, volleyball, and baseball showed comparatively high injury incidence, largely driven by collision mechanisms, rapid directional changes, and ball-related impacts [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Injury risk is a critical determinant of long-term adherence among older adults, as fear of injury and perceived unsafety are common barriers to sustained participation [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Even minor injuries may precipitate deconditioning, mobility loss, or withdrawal from structured exercise programs, underscoring the importance of safety-oriented sport selection and age-adapted rule modifications.\u003c/p\u003e \u003cp\u003eSubstantial variation was also observed in social interaction scores. Soccer, basketball, and volleyball exhibited high levels of multilateral social interaction, which may support motivation, social cohesion, and emotional well-being\u0026mdash;factors consistently linked to cognitive resilience and reduced dementia risk [\u003cspan additionalcitationids=\"CR71\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. In contrast, racket sports and non-combat judo showed limited social interaction, which may be advantageous for individuals preferring low-interaction environments. Tailoring sport selection to social preference profiles may enhance adherence and program effectiveness.\u003c/p\u003e \u003cp\u003eCollectively, these findings indicate that intrinsic sport characteristics\u0026mdash;including real-time cognitive demand, neuromuscular engagement, physical intensity, injury risk, and social interaction\u0026mdash;jointly shape the quality and feasibility of cognitive\u0026ndash;physical engagement in OSEs. Importantly, these multidimensional attributes suggest that OSEs may contribute not only to cognitive health but also to the prevention or mitigation of cognitive, physical, and social frailty, a construct of growing global relevance in aging societies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Practical Feasibility and Implementation Constraints\u003c/h2\u003e \u003cp\u003eFeasibility characteristics emerged as essential differentiators. Table tennis and badminton required minimal space, inexpensive equipment, and limited supervision, making them highly compatible with community centers, public halls, and multipurpose indoor facilities. Sports requiring large fields (soccer, baseball) or dedicated courts (tennis, basketball) may face infrastructural barriers, particularly in densely populated urban areas.\u003c/p\u003e \u003cp\u003eOperational demands were lowest for table tennis and highest for baseball and non-combat judo, highlighting the importance of technical complexity and supervision requirements in scaling interventions. These findings align with implementation science frameworks emphasizing cost-effectiveness, adaptability, and infrastructural compatibility as key determinants of successful community-based physical activity programs for older adults [\u003cspan additionalcitationids=\"CR74\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Sustainability, Enjoyment, and Long-Term Adherence\u003c/h2\u003e \u003cp\u003eLong-term adherence reflects a combination of enjoyment, perceived competence, accessibility, and social reinforcement. Extensive evidence indicates that intrinsic motivation and supportive environmental contexts are central determinants of sustained physical activity participation in older adults [\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present analysis, table tennis, basketball, and volleyball scored highest in sustainability, consistent with their recreational appeal and manageable participation barriers. In contrast, sports associated with greater organizational complexity or equipment demands, such as baseball, demonstrated lower sustainability scores. Given the central role of adherence in preventing functional decline and frailty progression, sustainability should be considered a primary criterion in the design of community-based cognitive\u0026ndash;physical interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Digital Extensibility and Hybrid Training Opportunities\u003c/h2\u003e \u003cp\u003eDigital replicability varied substantially across sports. Table tennis, basketball, and baseball demonstrated high VR and e-sports applicability, benefiting from established simulation technologies capable of reproducing perceptual\u0026ndash;motor timing and decision-making demands. In contrast, sports requiring paired or synchronized full-body interaction, such as non-combat judo, showed limited digital extensibility.\u003c/p\u003e \u003cp\u003eEmerging evidence suggests that VR-based and digitally mediated exercise interventions can enhance motivation, engagement, and accessibility while supporting integrated cognitive and physical training in older adults [\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Hybrid digital\u0026ndash;physical paradigms may therefore complement traditional community sports by mitigating space, staffing, and accessibility constraints, rather than replacing in-person activities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Integrative Interpretation and Public Health Implications\u003c/h2\u003e \u003cp\u003eWhen weighted according to dementia-prevention priorities, table tennis emerged as the most balanced OSE across cognitive, physical, safety, operational, sustainability, and digital dimensions. Its integrated profile aligns well with the heterogeneous neurocognitive, functional, and practical needs of aging adults.\u003c/p\u003e \u003cp\u003eFrom a public health perspective, these findings argue against a one-size-fits-all approach. Instead, offering a diversified portfolio of OSEs\u0026mdash;combining cognitively demanding racket sports, socially engaging team activities, and low-intensity accessible formats\u0026mdash;may maximize reach, adherence, and impact across diverse aging populations, while simultaneously addressing multiple domains of frailty.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Strengths, Limitations, and Future Directions\u003c/h2\u003e \u003cp\u003eThis study has several strengths, including the use of a transparent MCDA framework, the operationalization of cognitive demand using a dual-component CCD metric, and the inclusion of emerging dimensions such as digital extensibility. However, several limitations warrant consideration. CB and DI estimates were derived from published match analyses and may not generalize across populations or modified formats. MET values reflect typical intensities and may differ in age-adapted implementations. Several criteria relied on structured expert evaluation rather than large-scale empirical data, and the applied weighting scheme represents one of several plausible modeling choices.\u003c/p\u003e \u003cp\u003eIn addition, sport participation and performance may be influenced by sex-related physiological and sociocultural factors, potentially limiting the generalizability of findings across genders. Future studies should explicitly examine sex-specific responses to OSE participation.\u003c/p\u003e \u003cp\u003eFuture research should include mechanistic validation using mobile neuroimaging and wearable sensors, longitudinal intervention trials comparing high- and low-CCD sports, and pragmatic implementation studies evaluating cost-effectiveness and adherence across diverse populations. Further development of VR-based and hybrid OSE platforms may also expand accessibility and scalability.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis multidimensional evaluation demonstrates that OSEs exhibit marked heterogeneity across cognitive, physical, social, safety, operational, sustainability, and digital-extensibility dimensions, underscoring the limitations of single-domain approaches to sport-based dementia prevention. By applying a transparent, dementia-prevention–oriented MCDA framework, this study advances a structured and reproducible method for comparing heterogeneous sports in terms of both neurocognitive engagement and real-world feasibility.\u003c/p\u003e\n\u003cp\u003eWithin this integrative framework, racket-based sports—most notably table tennis and badminton—emerged as among the most well-balanced options. Their combination of high real-time cognitive demand, agility-oriented neuromuscular engagement, moderate and adaptable physical load, favorable safety profiles, minimal infrastructural requirements, and strong potential for digital extension provides a coherent mechanistic and practical explanation for their consistently reported cognitive benefits in later life.\u003c/p\u003e\n\u003cp\u003eBeyond identifying individual “optimal” sports, the present findings support a portfolio-based public health strategy that integrates cognitively demanding, socially engaging, and highly accessible activities to accommodate heterogeneity in functional capacity, motivational profiles, sex-related differences, and community infrastructure. By bridging neurocognitive mechanisms, exercise physiology, implementation science, and emerging digital modalities, this framework offers an evidence-informed foundation for designing sustainable activity ecosystems that support healthy brain aging and frailty prevention in rapidly aging societies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, T.Y.; Methodology, T.Y.; Data Collection, T.Y., K.H., T.I., and S.H.; Analysis, T.Y., K.H., T.I., S.H., and S.K.; Writing—Original Draft Preparation, T.Y.; Writing—Review and Editing, T.Y., K.H., T.I., S.H., and S.K.; Supervision, S.K., All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. 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J Gerontol A Biol Sci Med Sci. 2024;79(4):glae035. doi: 10.1093/gerona/glae035.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Aging](https://link.springer.com/journal/44518)","snPcode":"44518","submissionUrl":"https://submission.springernature.com/new-submission/44518/3","title":"Discover Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"open-skill exercise, cognitive health, healthy aging, multi-criteria decision analysis, community implementation, dementia prevention, racket sports","lastPublishedDoi":"10.21203/rs.3.rs-8671463/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8671463/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCognitive decline and dementia are major challenges in aging societies. Open-skill exercise (OSE), characterized by unpredictable environments requiring rapid perceptual\u0026ndash;cognitive\u0026ndash;motor adaptation, has emerged as a promising approach for cognitive health. However, systematic cross-sport comparisons remain scarce. This study evaluated eight OSEs\u0026mdash;tennis, table tennis, badminton, basketball, volleyball, soccer, baseball, and non-combat judo\u0026mdash;using a multidimensional framework to assess their relative suitability for cognitive health promotion and community implementation among older adults. A multi-criteria decision analysis was conducted using eight criteria covering key cognitive, physical, social, safety, operational, sustainability, and digital aspects. Cognitive load was quantified using an established composite metric, with all criteria normalized and weighted for dementia prevention relevance. Weighted scores were integrated to generate an overall composite suitability score for each sport. Table tennis achieved the highest score, reflecting strong performance across cognitive, physical, safety, feasibility, sustainability, and digital domains. Badminton also scored highly, driven by strong cognitive and practical attributes. Team sports showed broad cognitive demands and high social interaction but were limited by lower individual decision frequency or elevated injury risk. Soccer and basketball had high physical load, whereas baseball and non-combat judo scored lower due to comparatively limited real-time cognitive demands and feasibility constraints. Overall, OSEs differed markedly across cognitive, physical, and operational domains. Table tennis emerged as a highly scalable and well-balanced option for cognitive health interventions in older adults, followed by badminton and selected team sports. These findings provide guidance for community programming and future neurocognitive and implementation-oriented research. Taken together, these multidimensional characteristics suggest potential relevance to the prevention of cognitive, physical, and social frailty.\u003c/p\u003e","manuscriptTitle":"A Multi-Criteria Decision Analysis of Open-Skill Exercise-Based Sports for Cognitive Health Promotion in Older Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-04 09:05:20","doi":"10.21203/rs.3.rs-8671463/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T13:42:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T16:29:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T05:49:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160430418083108768355463391177735131325","date":"2026-02-11T18:44:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"17132033634020938369301166898538017358","date":"2026-02-08T14:38:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-02T12:47:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-23T13:24:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-23T09:40:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-23T09:37:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Aging","date":"2026-01-22T15:22:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-aging","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Aging](https://link.springer.com/journal/44518)","snPcode":"44518","submissionUrl":"https://submission.springernature.com/new-submission/44518/3","title":"Discover Aging","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5806aa57-b1d2-4d3a-904d-f39766b7a57c","owner":[],"postedDate":"February 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T07:39:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-04 09:05:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8671463","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8671463","identity":"rs-8671463","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}