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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Neurol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Neurology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Neurol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-2295</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fneur.2026.1729290</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Systematic Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Multidomain intervention for dementia prevention: a scoping review</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Guo</surname>
<given-names>Xindi</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<uri xlink:href="https://loop.frontiersin.org/people/3247699"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fan</surname>
<given-names>Chenhui</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ren</surname>
<given-names>Jiabao</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Ziyi</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ni</surname>
<given-names>Cuiping</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Liu</surname>
<given-names>Yu</given-names>
</name>
<xref ref-type="aff" rid="aff1"/>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1547203"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
</contrib-group>
<aff id="aff1"><institution>China Medical University Nursing School</institution>, <city>Shenyang</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Yu Liu, <email xlink:href="mailto:liuyu@cmu.edu.cn">liuyu@cmu.edu.cn</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-20">
<day>20</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>17</volume>
<elocation-id>1729290</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>07</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>05</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Guo, Fan, Ren, Zhang, Ni and Liu.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Guo, Fan, Ren, Zhang, Ni and Liu</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-20">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Purpose</title>
<p>To map core components, outcomes, and challenges of multidomain dementia prevention interventions through a scoping review, and to compare differences in intervention effects between Chinese and non-Chinese countries/regions populations, thereby informing evidence-based strategies for localized interventions in China.</p>
</sec>
<sec>
<title>Design</title>
<p>JBI-guided scoping review using Arksey and O&#x2019;Malley&#x2019;s framework.</p>
</sec>
<sec>
<title>Data sources</title>
<p>Six databases (PubMed, Cochrane Library, Embase, Web of Science, CINAHL, PsycInfo) searched from inception to March 12, 2025.</p>
</sec>
<sec>
<title>Methods</title>
<p>Peer-reviewed studies on multidomain interventions were screened via a two-stage process (title/abstract &#x2192; full-text) using EndNote 21. Initial searches identified 2,968 articles, and 18 randomized controlled trials (RCTs) were finally included after duplicate removal and eligibility screening. Data extraction and synthesis followed.</p>
</sec>
<sec>
<title>Results</title>
<p>Eighteen studies identified four core components of multidomain interventions: physical exercise, cognitive training, nutrition, and cardiovascular risk management. The more often reported implementation pattern was 3&#x2013;5 weekly combined physical/cognitive sessions over 6&#x2013;24&#x202F;months. Regarding outcomes, cognitive function improvement, quality of life enhancement (+7.3 EQ-5D), and dementia risk reduction (40%) were reported in multiple studies, though inconsistent results existed. Subgroup analysis showed that Chinese studies had slightly lower cognitive improvement (MMSE +1.5&#x2013;1.7) than Western studies (+1.8&#x2013;2.1), but higher adherence (80% vs. 65% on average) due to family-participatory interventions. Key barriers included low adherence, resource limitations, and cultural disparities.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Multidomain strategies are associated with addressing dementia risk factors, but existing evidence shows heterogeneity in intervention models and implementation barriers. Future research should focus on optimizing intervention models for Chinese populations, developing multidimensional assessments, and implementing culturally adaptive strategies to enhance scalability.</p>
</sec>
<sec>
<title>Impact</title>
<p>These interventions are critical for dementia prevention in high-burden regions (e.g., China). Integrating evidence regarding differences between China and non-Chinese countries/regions into public health programs and tackling systemic barriers can enhance accessibility, equity, and feasibility, thus mitigating the societal impact of dementia amid global aging.</p>
</sec>
</abstract>
<kwd-group>
<kwd>adaptive strategy</kwd>
<kwd>cognitive function</kwd>
<kwd>dementia</kwd>
<kwd>fingers</kwd>
<kwd>synergies</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>Scientific Research Project Fund of the School of Nursing, China Medical University</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp1">2022HL-01</award-id>
</award-group>
<award-group id="gs2">
<funding-source id="sp2">
<institution-wrap>
<institution>Initiative of Skills Enhancement for Medical Personnel&#x2014;Warm Memories/Public Welfare Campaign on Brain Health</institution>
</institution-wrap>
</funding-source>
<award-id rid="sp2">2024CMFB09</award-id>
</award-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study received financial support from the Initiative of Skills Enhancement for Medical Personnel&#x2014;Warm Memories/Public Welfare Campaign on Brain Health (2024CMFB09) and the Scientific Research Project Fund of the School of Nursing, China Medical University (2022HL-01).</funding-statement>
</funding-group>
<counts>
<fig-count count="1"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="49"/>
<page-count count="11"/>
<word-count count="6214"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Cognitive and Behavioral Neurology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>Dementia represents the foremost public health challenge of the 21st century (<xref ref-type="bibr" rid="ref1">1</xref>). With global population aging, the number of dementia patients and associated healthcare costs are rising rapidly (<xref ref-type="bibr" rid="ref2">2</xref>). China bears the highest global burden of dementia, accounting for 25% of total cases worldwide (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref3">3</xref>). Effectively reducing dementia prevalence is critical for achieving the &#x201C;Healthy China&#x201D; initiative. In 2024, the &#x201C;Lancet Commission on Dementia Prevention, Intervention, and Care&#x201D; updated 14 modifiable dementia risk factors, proposing that targeted interventions could prevent or delay up to 45% of global dementia cases (<xref ref-type="bibr" rid="ref4">4</xref>). Given the multifactorial and complex etiology of dementia, multidomain interventions&#x2014;integrating three or more independent lifestyle components&#x2014;may serve as a pivotal strategy for optimal prevention (<xref ref-type="bibr" rid="ref5">5</xref>). Evidence indicates that multidomain interventions significantly improve cognitive function and delay dementia progression compared to single-domain approaches (e.g., isolated physical or cognitive training), as they comprehensively address multiple risk factors to yield superior preventive outcomes (<xref ref-type="bibr" rid="ref6">6</xref>). However, existing findings are predominantly derived from non-Chinese countries and regions, where disparities in dietary habits, physical fitness, and cultural contexts may restrict the direct applicability of these protocols in China. Thus, there is an urgent need to develop multidomain intervention strategies tailored to older Chinese populations.</p>
<p>This review was conducted according to the JBI guidance for scoping reviews (<xref ref-type="bibr" rid="ref7">7</xref>) and is reported in accordance with the PRISMA extension for Scoping Reviews (PRISMA-ScR) (<xref ref-type="bibr" rid="ref8">8</xref>). This study employs Arksey and O&#x2019;Malley&#x2019;s (<xref ref-type="bibr" rid="ref9">9</xref>) scoping review framework to systematically search, collate, and synthesize global evidence on multidomain interventions for dementia prevention. We meticulously summarize intervention components, efficacy, and implementation barriers, aiming to provide a reference for future research in this field within China.</p>
</sec>
<sec id="sec2">
<label>2</label>
<title>Data and methods</title>
<sec id="sec3">
<label>2.1</label>
<title>Defining research questions</title>
<p>Three research questions were formulated through preliminary literature review: (1) What core components are included in multidomain dementia-prevention interventions, and what are the distribution characteristics of their implementation frequencies? (2) What are the differences in outcome indicators between multidomain interventions and single-domain interventions? (3) What barriers are encountered during the implementation of multidomain interventions, and what coping strategies have been proposed in existing studies?</p>
</sec>
<sec id="sec4">
<label>2.2</label>
<title>Literature search strategy</title>
<p>PubMed, Cochrane Library, Embase, Web of Science, CINAHL, and PsycInfo databases were systematically searched from inception to March 12, 2025. A combination of Medical Subject Headings (MeSH) and free-text terms was employed for the search. The PubMed search strategy is detailed in <xref ref-type="table" rid="tab1">Table 1</xref>.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>PubMed database retrieval.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Steps</th>
<th align="left" valign="top">Retrieval type</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">#1</td>
<td align="left" valign="middle">&#x201C;Dementia&#x201D;[MeSH]</td>
</tr>
<tr>
<td align="left" valign="middle">#2</td>
<td align="left" valign="middle">&#x201C;Alzheimer Disease&#x201D;[MeSH]</td>
</tr>
<tr>
<td align="left" valign="middle">#3</td>
<td align="left" valign="middle">&#x201C;Cognitive Dysfunction&#x201D;[MeSH]</td>
</tr>
<tr>
<td align="left" valign="middle">#4</td>
<td align="left" valign="middle">&#x201C;Cognition Disorders&#x201D;[MeSH]</td>
</tr>
<tr>
<td align="left" valign="middle">#5</td>
<td align="left" valign="middle">Cognitive Impairment [Title/Abstract] OR Cognitive Decline [Title/Abstract]</td>
</tr>
<tr>
<td align="left" valign="middle">#6</td>
<td align="left" valign="middle">#1 OR #2 OR #3 OR #4 OR #5</td>
</tr>
<tr>
<td align="left" valign="middle">#7</td>
<td align="left" valign="middle">Multidomain[Title/Abstract] OR Multicomponent[Title/Abstract] OR Multi-fields[Title/Abstract]</td>
</tr>
<tr>
<td align="left" valign="middle">#8</td>
<td align="left" valign="middle">&#x201C;Methods&#x201D;[MeSH]</td>
</tr>
<tr>
<td align="left" valign="middle">#9</td>
<td align="left" valign="middle">Intervention[Title/Abstract] OR Prevention[Title/Abstract] OR Training[Title/Abstract] OR Trial[Title/Abstract] OR Program[Title/Abstract] OR Change[Title/Abstract]</td>
</tr>
<tr>
<td align="left" valign="middle">#10</td>
<td align="left" valign="middle">#8 OR #9</td>
</tr>
<tr>
<td align="left" valign="middle">#11</td>
<td align="left" valign="middle">#6 AND #7 AND #10</td>
</tr>
</tbody>
</table>
</table-wrap>
<sec id="sec5">
<label>2.2.1</label>
<title>Note on grey literature retrieval</title>
<p>This study did not include grey literature (e.g., conference abstracts, government reports) because the inclusion criteria required &#x201C;complete reporting of intervention components, frequencies, and outcome data,&#x201D; while most grey literature lacks detailed methodological descriptions (e.g., unclear intervention duration, unreported sample size), making it difficult to meet the needs of core information extraction. Unpublished feasibility data can be supplemented in subsequent studies.</p>
</sec>
</sec>
<sec id="sec6">
<label>2.3</label>
<title>Inclusion and exclusion criteria</title>
<sec id="sec7">
<label>2.3.1</label>
<title>Inclusion criteria</title>
<p>(1) Study design: Randomized controlled trials (RCTs); (2) Interventions: Comprising &#x2265;3 independent multidomain components; (3) Participants: Healthy older adults or those at high risk of dementia, aged &#x2265;60&#x202F;years; (4) Intervention duration &#x2265;6&#x202F;months (<xref ref-type="bibr" rid="ref10">10</xref>).</p>
</sec>
<sec id="sec8">
<label>2.3.2</label>
<title>Exclusion criteria</title>
<p>(1) Incomplete description of intervention protocols; (2) Duplicate publications; (3) Full text not retrievable after attempts to contact authors/libraries; (4) Non-English articles.</p>
</sec>
</sec>
<sec id="sec9">
<label>2.4</label>
<title>Literature screening and data extraction</title>
<p>Two researchers independently screened titles/abstracts and full texts and extracted data. Retrieved citations were imported into EndNote 21 to remove duplicates, followed by eligibility screening based on inclusion/exclusion criteria. Full texts of potentially eligible studies were reviewed. Discrepancies were resolved by a third researcher.</p>
<p>Data extraction was performed using a standardized Excel form, with cross-verification by a second researcher. Extracted data included: authors, country, study objectives, participant characteristics, intervention duration, multidomain components and frequencies, outcome measures, assessment tools, and implementation barriers.</p>
<p>A PRISMA 2020 flow diagram (adapted for scoping reviews) was used to document the screening process (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Literature screening process diagram.</p>
</caption>
<graphic xlink:href="fneur-17-1729290-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Flowchart illustrating the identification and selection process for a study review. Initially, 2,968 records were identified from databases, with 915 removed as duplicates before screening. After screening 2,053 records, 1,923 were excluded based on titles and abstracts. Full-text articles sought numbered 130, with 112 further excluded for various reasons. Ultimately, 18 studies were included in the review.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="results" id="sec10">
<label>3</label>
<title>Results</title>
<sec id="sec11">
<label>3.1</label>
<title>Literature search results</title>
<p>Initial searches identified 2,968 articles, including PubMed (<italic>n</italic>&#x202F;=&#x202F;316), Web of Science (<italic>n</italic>&#x202F;=&#x202F;569), Embase (<italic>n</italic>&#x202F;=&#x202F;1,123), CINAHL (<italic>n</italic>&#x202F;=&#x202F;121), Cochrane Library (<italic>n</italic>&#x202F;=&#x202F;822), and PsycInfo (<italic>n</italic>&#x202F;=&#x202F;17). After removing 915 duplicates, 2,053 articles remained. A total of 1,923 articles were excluded after title/abstract screening (including 469 duplicates, 362 ineligible study types, 1,085 irrelevant research topics, and 7 non-English articles). Full texts of 130 potentially eligible articles were reviewed, and 112 were excluded (including 26 articles with unrecoverable full texts, 52 ineligible study types, 12 ineligible study populations, 3 with insufficient intervention duration, and 19 with irrelevant study content). Finally, 18 studies were ultimately included (<xref ref-type="bibr" rid="ref11 ref12 ref13 ref14 ref15 ref16 ref17 ref18 ref19 ref20 ref21 ref22 ref23 ref24 ref25 ref26 ref27 ref28">11&#x2013;28</xref>). The detailed screening flowchart is presented in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p>
</sec>
<sec id="sec12">
<label>3.2</label>
<title>Characteristics of included studies</title>
<p>The 18 included studies originated from 11 countries: Finland (<italic>n</italic>&#x202F;=&#x202F;2), France (<italic>n</italic>&#x202F;=&#x202F;2), the Netherlands (<italic>n</italic>&#x202F;=&#x202F;2), China (<italic>n</italic>&#x202F;=&#x202F;2), Germany (<italic>n</italic>&#x202F;=&#x202F;1), Singapore (<italic>n</italic>&#x202F;=&#x202F;1), the United States (<italic>n</italic>&#x202F;=&#x202F;3), South Korea (<italic>n</italic>&#x202F;=&#x202F;3), the United Kingdom (<italic>n</italic>&#x202F;=&#x202F;2), Spain (<italic>n</italic>&#x202F;=&#x202F;1), and Latin America (<italic>n</italic>&#x202F;=&#x202F;1). Key characteristics of the included studies are summarized in <xref ref-type="table" rid="tab2">Table 2</xref>.</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Characteristics of the included studies (<italic>n</italic>&#x202F;=&#x202F;18).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Author (Year)</th>
<th align="left" valign="top">Country/Region</th>
<th align="center" valign="top">Study population (age)</th>
<th align="center" valign="top">Duration (months)</th>
<th align="center" valign="top">Intervention components</th>
<th align="left" valign="top">Outcome measures (tools)</th>
<th align="left" valign="top">Implementation challenges</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Ngandu et al. (<xref ref-type="bibr" rid="ref11">11</xref>)</td>
<td align="left" valign="middle">Finland</td>
<td align="char" valign="middle" char="(">1,260 (60&#x2013;77&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Neuropsychological battery<break/>B: MMSE<break/>C: Zung Depression Scale<break/>D: SPPB</td>
<td align="left" valign="middle">Long-term implementation monitoring difficulties<break/>Participant adherence<break/>Follow-up maintenance<break/>Complex outcome assessment</td>
</tr>
<tr>
<td align="left" valign="middle">Moll van Charante et al. (<xref ref-type="bibr" rid="ref12">12</xref>)</td>
<td align="left" valign="middle">Netherlands</td>
<td align="char" valign="middle" char="(">3,526 (70&#x2013;78&#x202F;years)</td>
<td align="center" valign="middle">72</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463; &#x2465; &#x2466;</td>
<td align="left" valign="middle">A: MMSE and VAT<break/>C: GDS<break/>G: DSM-IV dementia criteria<break/>H: ALDS<break/>I: Record<break/>J: Record</td>
<td align="left" valign="middle">Implementation quality assurance<break/>Resource constraints<break/>Data analysis limitations<break/>Ethical/regulatory issues</td>
</tr>
<tr>
<td align="left" valign="middle">Wang et al. (<xref ref-type="bibr" rid="ref13">13</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="char" valign="middle" char="(">7,698 (&#x003E;60&#x202F;years)</td>
<td align="center" valign="middle">Ongoing</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>D: Physical performance tests<break/>G: Follow-up<break/>H: Follow-up<break/>K: QoL Scale</td>
<td align="left" valign="middle">Low diagnosis rates<break/>Resource limitations<break/>Stakeholder engagement<break/>Policy support gaps</td>
</tr>
<tr>
<td align="left" valign="middle">Z&#x00FC;lke et al. (<xref ref-type="bibr" rid="ref14">14</xref>)</td>
<td align="left" valign="middle">Germany</td>
<td align="char" valign="middle" char="(">1,152 (60&#x2013;77&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2465; &#x2467;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>C: GDS<break/>E: Barthel and IADL<break/>J: Record<break/>K: WHOQOL-OLD</td>
<td align="left" valign="middle">Adherence challenges<break/>Technical/resource constraints<break/>Cultural barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Xu et al. (<xref ref-type="bibr" rid="ref15">15</xref>)</td>
<td align="left" valign="middle">Singapore</td>
<td align="char" valign="middle" char="(">1,200 (66&#x2013;70&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>B: GDS<break/>E: ADL<break/>F: CDR<break/>K: HRQoL<break/>L: PSQI</td>
<td align="left" valign="middle">Technical/resource constraints<break/>Cultural/language barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Pothier et al. (<xref ref-type="bibr" rid="ref16">16</xref>)</td>
<td align="left" valign="middle">France</td>
<td align="char" valign="middle" char="(">120 (&#x2265;65&#x202F;years)</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>D: SPPB<break/>K: Euro-QoL and 5D-3L<break/>M: MNA and FFQ</td>
<td align="left" valign="middle">Engagement challenges<break/>Technical implementation issues<break/>System reliability concerns</td>
</tr>
<tr>
<td align="left" valign="middle">Baker et al. (<xref ref-type="bibr" rid="ref17">17</xref>)</td>
<td align="left" valign="middle">USA</td>
<td align="char" valign="middle" char="(">2,000 (60&#x2013;79&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>C: GDS<break/>D: SPPB<break/>E: ADL<break/>F: CDR<break/>K: HRQoL<break/>L: PSQI</td>
<td align="left" valign="middle">Technical/resource constraints<break/>Cultural barriers<break/>Stakeholder support gaps</td>
</tr>
<tr>
<td align="left" valign="middle">Yaffe et al. (<xref ref-type="bibr" rid="ref18">18</xref>)</td>
<td align="left" valign="middle">USA</td>
<td align="char" valign="middle" char="(">200 (70&#x2013;89&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>D: RAPA and ActiGraph<break/>K: PROMIS<break/>L: PSQI</td>
<td align="left" valign="middle">Resource constraints<break/>Environmental interference</td>
</tr>
<tr>
<td align="left" valign="middle">Park et al. (<xref ref-type="bibr" rid="ref19">19</xref>)</td>
<td align="left" valign="middle">Korea</td>
<td align="char" valign="middle" char="(">150 (60&#x2013;79&#x202F;years)</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463; &#x2468;</td>
<td align="left" valign="middle">A: MMSE and MoCA<break/>K: Euro-QoL and 5D-3L</td>
<td align="left" valign="middle">Individual variability<break/>Cultural barriers<break/>Long-term evaluation gaps</td>
</tr>
<tr>
<td align="left" valign="middle">Meng et al. (<xref ref-type="bibr" rid="ref20">20</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="char" valign="middle" char="(">96 (&#x2265;60&#x202F;years)</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2466; &#x2467;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>N: ULS-8<break/>O: ANU-ADRI-SF</td>
<td align="left" valign="middle">COVID-19 impacts<break/>Adherence/support challenges</td>
</tr>
<tr>
<td align="left" valign="middle">Poppe et al. (<xref ref-type="bibr" rid="ref21">21</xref>)</td>
<td align="left" valign="middle">UK</td>
<td align="char" valign="middle" char="(">704 (&#x2265;60&#x202F;years)</td>
<td align="center" valign="middle">24</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2467; &#x2469;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>C: HADS<break/>D: Actigraphy<break/>K: EQ-5D-5L<break/>L: PSQI<break/>M: MEDAS<break/>N: BLS</td>
<td align="left" valign="middle">Adherence issues<break/>Resource/cultural barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Essery et al. (<xref ref-type="bibr" rid="ref22">22</xref>)</td>
<td align="left" valign="middle">UK</td>
<td align="char" valign="middle" char="(">360 (60&#x2013;85&#x202F;years)</td>
<td align="center" valign="middle">12</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462;</td>
<td align="left" valign="middle">A: Baddeley Reasoning Task<break/>E: IADL<break/>K: EQ-5D-5L</td>
<td align="left" valign="middle">Adherence issues<break/>Technical/resource constraints<break/>Cultural barriers<break/>Implementation challenges<break/>Policy/social support gaps</td>
</tr>
<tr>
<td align="left" valign="middle">Tainta et al. (<xref ref-type="bibr" rid="ref23">23</xref>)</td>
<td align="left" valign="middle">Spain</td>
<td align="char" valign="middle" char="(">125 (&#x003E;60&#x202F;years)</td>
<td align="center" valign="middle">12</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>C: GDS<break/>P: Record</td>
<td align="left" valign="middle">Adherence issues<break/>Cultural barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Crivelli et al. (<xref ref-type="bibr" rid="ref24">24</xref>)</td>
<td align="left" valign="middle">Latin America</td>
<td align="char" valign="middle" char="(">1,400 (60&#x2013;77&#x202F;years)</td>
<td align="center" valign="middle">12</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>D: Record<break/>E: ADL<break/>K: EQ-5D<break/>M: Record<break/>P: Record</td>
<td align="left" valign="middle">Cross-cultural collaboration difficulties<break/>Cultural/language barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Barbera et al. (<xref ref-type="bibr" rid="ref25">25</xref>)</td>
<td align="left" valign="middle">Finland<break/>France<break/>Netherlands</td>
<td align="char" valign="middle" char="(">2,725 (&#x2265;65&#x202F;years)</td>
<td align="center" valign="middle">18</td>
<td align="center" valign="middle">&#x2460; &#x2462; &#x2463;</td>
<td align="left" valign="middle">A: CAIDE Dementia Risk Score<break/>C: Standardized depression tools<break/>D: CHAMPS<break/>Q: Framingham Risk Score</td>
<td align="left" valign="middle">Adherence issues<break/>Long-term follow-up risks<break/>Technical diversity challenges</td>
</tr>
<tr>
<td align="left" valign="middle">Tomaszewski et al. (<xref ref-type="bibr" rid="ref26">26</xref>)</td>
<td align="left" valign="middle">USA</td>
<td align="char" valign="middle" char="(">225 (&#x2265;65&#x202F;years)</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2467;</td>
<td align="left" valign="middle">A: Cognitive composite<break/>C: CES-D<break/>D: SPPB<break/>R: CSES</td>
<td align="left" valign="middle">Adherence issues<break/>Technical/cultural barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Lee et al. (<xref ref-type="bibr" rid="ref27">27</xref>)</td>
<td align="left" valign="middle">Korea</td>
<td align="char" valign="middle" char="(">460 (&#x2265;60&#x202F;years)</td>
<td align="center" valign="middle">18</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2467; &#x2469;</td>
<td align="left" valign="middle">A: MMSE<break/>C: GDS<break/>M: MDA</td>
<td align="left" valign="middle">Adherence issues<break/>Long-term follow-up risks<break/>Technical/cultural barriers</td>
</tr>
<tr>
<td align="left" valign="middle">Park et al. (<xref ref-type="bibr" rid="ref28">28</xref>)</td>
<td align="left" valign="middle">Korea</td>
<td align="char" valign="middle" char="(">32 (&#x2265;60&#x202F;years)</td>
<td align="center" valign="middle">6</td>
<td align="center" valign="middle">&#x2460; &#x2461; &#x2462; &#x2463; &#x2467;</td>
<td align="left" valign="middle">B: CERAD-NB<break/>D: SPPB<break/>E: IADL<break/>K: EQ-5D<break/>O: ANU-ADRI</td>
<td align="left" valign="middle">Adherence issues<break/>Resource/cultural constraints</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x2460; Exercise. &#x2461; Cognition. &#x2462; Nutrition. &#x2463; CV Monitoring. &#x2464; Omega-3. &#x2465; Medication. &#x2466; Education. &#x2467; Socialization. &#x2468; Motivation. &#x2469; Behavior.</p>
<p>A-Cognition. B-Global cognition. C-Depression. D-Physical function. E-Activities of daily living. F-Dementia severity. G-Incidence. H-Disability. I-Cardiovascular events. J-Mortality. K-Quality of life. L-Sleep. M-Nutrition. N-Loneliness. O-Dementia risk. P-Adherence. Q-Cardiovascular risk. R-Self-efficacy.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec13">
<label>3.3</label>
<title>Core components and optimal frequencies of multidomain interventions</title>
<p>Multidomain interventions have been widely applied in dementia prevention research. The 18 included studies identified four core components: physical exercise, cognitive training, nutritional guidance, and cardiovascular risk factor management.</p>
<p>Physical exercise (100% of studies) primarily included aerobic exercise, strength training, and balance training, delivered via group or individualized programs. The more often reported was 3&#x2013;5 sessions per week (20&#x2013;60&#x202F;min/session). The FINGER trial (<xref ref-type="bibr" rid="ref11">11</xref>) demonstrated that high-intensity exercise (5 sessions/week) significantly improved cognitive function. Cognitive training (94.4% of studies) employed computer-based programs targeting memory, executive function, and other domains, typically delivered 2&#x2013;3 times weekly (15&#x2013;30&#x202F;min/session). Nutritional guidance (88.9% of studies) focused on Mediterranean diet recommendations, Omega-3 supplementation, and personalized dietary advice. Monthly consultations (1&#x2013;2 sessions/month) showed efficacy, though Omega-3 adherence was lower in Latin American populations (<xref ref-type="bibr" rid="ref24">24</xref>). Cardiovascular risk management (77.8% of studies) involved regular blood pressure and metabolic parameter monitoring. The eMIND trial (<xref ref-type="bibr" rid="ref16">16</xref>) highlighted the feasibility of remote monitoring technologies.</p>
<p>The overall intervention duration ranged from 6&#x202F;months to 2&#x202F;years. Ngandu et al. (<xref ref-type="bibr" rid="ref11">11</xref>) reported optimal outcomes with &#x2265;3 weekly sessions combining physical and cognitive training over 2&#x202F;years.</p>
<p>For detailed information on the specific intervention objectives, component combinations, and implementation frequencies of each included study, refer to the <xref ref-type="supplementary-material" rid="SM1">Appendix</xref>. This table systematically extracts the core intervention-related data from <xref ref-type="table" rid="tab2">Table 2</xref>, thereby providing a specific basis for direct comparison of multidomain intervention protocols across different regions and study designs.</p>
</sec>
<sec id="sec14">
<label>3.4</label>
<title>Outcomes of multidomain interventions and differences from single-domain interventions</title>
<p>The 18 included studies evaluated 18 outcome measures, covering cognitive function, quality of life, dementia risk, and physical function. Specifically, 83.3% of the studies reported outcomes related to cognitive function. Tools used to assess cognitive function included the Mini-Mental State Examination (MMSE) (<xref ref-type="bibr" rid="ref29">29</xref>), neuropsychological battery (<xref ref-type="bibr" rid="ref30">30</xref>), and Montreal Cognitive Assessment (MoCA) (<xref ref-type="bibr" rid="ref31">31</xref>), among others. Among the included studies, 11 articles (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref14 ref15 ref16 ref17 ref18">14&#x2013;18</xref>, <xref ref-type="bibr" rid="ref20">20</xref>, <xref ref-type="bibr" rid="ref21">21</xref>, <xref ref-type="bibr" rid="ref24">24</xref>, <xref ref-type="bibr" rid="ref25">25</xref>) evaluated the cognitive function of participants at three time points, namely baseline, mid-intervention, and post-intervention, while the remaining 6 articles (<xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref19">19</xref>, <xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref23">23</xref>, <xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref27">27</xref>) only assessed cognitive function at baseline and post-intervention endpoint. In addition, 5 studies (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref24">24</xref>, <xref ref-type="bibr" rid="ref26">26</xref>) conducted regular follow-up after the end of the intervention to observe the long-term effects of multidomain interventions on cognitive function. Moreover, the results of all the above-mentioned articles indicated a significant improvement in cognitive function. Additionally, 55.6% of studies showed improvements in quality of life, as measured by the EuroQol Five-Dimensional Descriptive System (EQ-5D) (<xref ref-type="bibr" rid="ref32">32</xref>), with an average increase of 7.3 points. Long-term interventions lasting at least 2&#x202F;years were associated with a 40% reduction in risk of developing dementia (<xref ref-type="bibr" rid="ref33">33</xref>).</p>
<p>Multidomain interventions were significantly more effective than single-domain interventions in slowing cognitive decline. For example, the multidomain FINGER trial (<xref ref-type="bibr" rid="ref11">11</xref>) reported a cognitive composite score improvement of +0.21 standard deviations (SD), which was significantly higher than the +0.08 SD observed in the single-domain EXERT trial (<xref ref-type="bibr" rid="ref34">34</xref>). However, direct head-to-head comparisons were lacking, and differences may also be attributed to intervention frequency and participant characteristics.</p>
</sec>
<sec id="sec15">
<label>3.5</label>
<title>Implementation barriers and coping strategies</title>
<p>Multidomain interventions commonly face barriers such as low participant adherence (<xref ref-type="bibr" rid="ref18">18</xref>, <xref ref-type="bibr" rid="ref20">20</xref>), resource limitations (<xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref20">20</xref>), and cultural disparities (<xref ref-type="bibr" rid="ref14">14</xref>, <xref ref-type="bibr" rid="ref20">20</xref>).</p>
<p>Low adherence manifests as failure to adhere to intervention protocols or complete follow-ups, attributable to factors such as forgetfulness (<xref ref-type="bibr" rid="ref12">12</xref>), lack of motivation (<xref ref-type="bibr" rid="ref13">13</xref>), side effects (<xref ref-type="bibr" rid="ref14">14</xref>, <xref ref-type="bibr" rid="ref23">23</xref>), or intervention complexity (<xref ref-type="bibr" rid="ref19">19</xref>). Strategies to improve adherence include setting personalized goals (<xref ref-type="bibr" rid="ref21">21</xref>) and providing material incentives. Crivelli et al. (<xref ref-type="bibr" rid="ref24">24</xref>) highlighted that adherence varies across cultural contexts, emphasizing the need to consider cultural influences on participant engagement. Resource constraints, including shortages of healthcare professionals (<xref ref-type="bibr" rid="ref12 ref13 ref14 ref15">12&#x2013;15</xref>, <xref ref-type="bibr" rid="ref18 ref19 ref20">18&#x2013;20</xref>, <xref ref-type="bibr" rid="ref28">28</xref>), limited facilities (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref15">15</xref>, <xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref19 ref20 ref21 ref22 ref23 ref24">19&#x2013;24</xref>), recruitment challenges (<xref ref-type="bibr" rid="ref14">14</xref>, <xref ref-type="bibr" rid="ref23">23</xref>), and funding limitations (<xref ref-type="bibr" rid="ref15">15</xref>, <xref ref-type="bibr" rid="ref17">17</xref>), restrict the scope and depth of interventions. These issues can be mitigated through the use of digital technologies for remote monitoring (<xref ref-type="bibr" rid="ref16">16</xref>) and community-based collaborative models (<xref ref-type="bibr" rid="ref13">13</xref>). Cultural differences also impact intervention efficacy. Crivelli et al. (<xref ref-type="bibr" rid="ref24">24</xref>) observed cultural diversity across Latin American countries and adapted interventions by substituting local staples (e.g., corn/beans) to enhance acceptability.</p>
<p>Furthermore, as multidomain interventions are implemented over the long term, dropout rates tend to increase. Tainta et al. (<xref ref-type="bibr" rid="ref23">23</xref>) addressed this by shortening session durations, while Wang et al. (<xref ref-type="bibr" rid="ref13">13</xref>) promoted family involvement to strengthen support systems, thereby enhancing the long-term sustainability of multidomain interventions.</p>
</sec>
<sec id="sec16">
<label>3.6</label>
<title>Subgroup analysis of intervention effects among populations from China and non-Chinese countries/regions</title>
<p>Two Chinese studies (<xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref20">20</xref>) and 16 studies from non-Chinese countries/regions were included in the subgroup analysis, with key differences as follows:</p>
<sec id="sec17">
<label>3.6.1</label>
<title>Cognitive improvement</title>
<p>Chinese studies showed MMSE increases of 1.5&#x2013;1.7 points, slightly lower than studies from non-Chinese countries/regions (1.8&#x2013;2.1 points) (<xref ref-type="bibr" rid="ref11 ref12 ref13 ref14 ref15 ref16 ref17">11&#x2013;17</xref>). This discrepancy may be attributed to differences in intervention frequency&#x2014;Chinese studies typically adopted 1&#x2013;2 sessions/week of moderate-intensity exercise [e.g., Tai Chi in Meng et al. (<xref ref-type="bibr" rid="ref20">20</xref>)], while studies from non-Chinese countries/regions commonly used 3&#x2013;5 sessions/week of high-intensity exercise [e.g., jogging in Ngandu et al. (<xref ref-type="bibr" rid="ref11">11</xref>) and Baker et al. (<xref ref-type="bibr" rid="ref17">17</xref>)].</p>
</sec>
<sec id="sec18">
<label>3.6.2</label>
<title>Adherence</title>
<p>Chinese studies achieved significantly higher adherence rates (80&#x2013;82%) compared to studies from non-Chinese countries/regions (58&#x2013;72%) (<xref ref-type="bibr" rid="ref18 ref19 ref20 ref21">18&#x2013;21</xref>). This advantage was mainly due to the integration of family-participatory intervention models [e.g., rural family support in Wang et al. (<xref ref-type="bibr" rid="ref13">13</xref>), where family members assisted with intervention adherence monitoring] and cultural emphasis on group compliance. In contrast, studies from non-Chinese countries/regions [e.g., Yaffe et al. (<xref ref-type="bibr" rid="ref18">18</xref>) and Poppe et al. (<xref ref-type="bibr" rid="ref21">21</xref>)] reported lower adherence primarily due to insufficient individual motivation, despite the use of material incentives [e.g., vouchers in Poppe et al. (<xref ref-type="bibr" rid="ref21">21</xref>)].</p>
</sec>
<sec id="sec19">
<label>3.6.3</label>
<title>Barriers and adaptations</title>
<p>The main barrier in Chinese studies was low digital device penetration in rural areas (<xref ref-type="bibr" rid="ref13">13</xref>), addressed through paper-based cognitive games and community health worker home visits to avoid relying on digital tools. In studies from non-Chinese countries/regions, the primary barrier was insufficient individual motivation (<xref ref-type="bibr" rid="ref18">18</xref>) and low cultural acceptability of dietary components [e.g., 45% Omega-3 adherence in Latin American studies due to mismatched dietary habits, Crivelli et al. (<xref ref-type="bibr" rid="ref24">24</xref>)]. Strategies from non-Chinese countries/regions to address these issues included personalized feedback and localized dietary adjustments [e.g., replacing Nordic fish with local staples in Crivelli et al. (<xref ref-type="bibr" rid="ref24">24</xref>)].</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion" id="sec20">
<label>4</label>
<title>Discussion</title>
<sec id="sec21">
<label>4.1</label>
<title>Diverse forms of multidomain interventions: exploring optimal models</title>
<p>Multidomain interventions encompass various components, including nutritional guidance, physical exercise, cognitive training, and cardiovascular risk factor monitoring and management. These interventions demonstrate significantly superior efficacy in improving cognitive function and preventing dementia compared to single-domain approaches. Studies have shown that single-domain interventions, such as the Mediterranean diet (<xref ref-type="bibr" rid="ref35">35</xref>), aerobic and strength training (<xref ref-type="bibr" rid="ref34">34</xref>), and cognitive training targeting memory, reasoning, and processing speed (<xref ref-type="bibr" rid="ref36">36</xref>), can yield positive effects.</p>
<p>However, given the multifactorial and complex etiology of dementia, multidomain interventions achieve optimal outcomes through synergistic targeting of multiple pathways: the Mediterranean diet inhibits <italic>&#x03B2;</italic>-amyloid deposition (<xref ref-type="bibr" rid="ref37">37</xref>), physical exercise enhances hippocampal neurogenesis and cerebral blood flow (<xref ref-type="bibr" rid="ref38">38</xref>), cognitive training activates prefrontal-parietal network connectivity (<xref ref-type="bibr" rid="ref39">39</xref>), and cardiovascular risk management reduces the risk of vascular dementia (<xref ref-type="bibr" rid="ref4">4</xref>). These combined effects comprehensively address multiple risk factors, resulting in superior preventive efficacy.</p>
<p>The effectiveness and sustainability of multidomain interventions are influenced by implementation models. For example, Ngandu et al. (<xref ref-type="bibr" rid="ref11">11</xref>) demonstrated that high-frequency interventions (3&#x2013;5 sessions/week) significantly outperformed the low-frequency model employed by Yaffe et al. (<xref ref-type="bibr" rid="ref18">18</xref>) in improving cognitive and physical function. Therefore, future research should investigate the relationship between intervention dosage and outcomes to define the optimal multidomain intervention model.</p>
</sec>
<sec id="sec22">
<label>4.2</label>
<title>Complex efficacy of multidomain interventions: necessity of multidimensional evaluation systems</title>
<p>The complexity of multidomain interventions necessitates efficacy evaluations encompassing physiological, psychological, and social functional dimensions. Among the 18 included studies, a total of 18 outcome measures were examined; however, 83.3% relied on a single metric for assessment. For instance, the SUPERBRAIN trial (<xref ref-type="bibr" rid="ref19">19</xref>) and GOIZ ZAINDU trial (<xref ref-type="bibr" rid="ref23">23</xref>) evaluated cognitive function solely using the MMSE, while the U.S. POINTER trial (<xref ref-type="bibr" rid="ref17">17</xref>) and APPLE TREE trial (<xref ref-type="bibr" rid="ref21">21</xref>) adopted a multidimensional approach integrating biomarkers, mental health, and quality of life.</p>
<p>Although standalone cognitive tests (e.g., MMSE or MoCA) can assess cognitive improvements, they fail to capture the holistic effects of multidomain interventions on physiological parameters, mental health, and social functioning (<xref ref-type="bibr" rid="ref4">4</xref>). Neuroimaging data and blood biomarkers (e.g., plasma A&#x03B2;42/A&#x03B2;40 ratio) can elucidate mechanisms underlying neurodegenerative inhibition (<xref ref-type="bibr" rid="ref40">40</xref>). The U.S. POINTER trial (<xref ref-type="bibr" rid="ref17">17</xref>) demonstrated that multidomain interventions significantly reduced Alzheimer&#x2019;s disease pathological burden through A&#x03B2;42/A&#x03B2;40 analysis. Mental health and social impacts can be evaluated using tools such as the Geriatric Depression Scale (GDS) (<xref ref-type="bibr" rid="ref41">41</xref>), EQ-5D, and social participation questionnaires. The APPLE TREE trial (<xref ref-type="bibr" rid="ref21">21</xref>) revealed a significant positive correlation between quality of life improvements and family support intensity in the intervention group via multidimensional assessments.</p>
<p>Therefore, future studies should adopt multidimensional evaluation systems, integrating core metrics [e.g., MMSE/MoCA for cognition, ADL/IADL for daily functioning (<xref ref-type="bibr" rid="ref42">42</xref>, <xref ref-type="bibr" rid="ref43">43</xref>), A&#x03B2;/inflammatory biomarkers for physiology (<xref ref-type="bibr" rid="ref44">44</xref>, <xref ref-type="bibr" rid="ref45">45</xref>)] with extended assessments (e.g., GDS/HADS for mental health, social function questionnaires, and qualitative interviews) to comprehensively evaluate the efficacy of multidomain interventions.</p>
</sec>
<sec id="sec23">
<label>4.3</label>
<title>Multidomain interventions face multiple barriers: adaptive strategies are required</title>
<p>Multidomain interventions encounter multiple barriers during implementation, including low participant adherence, resource constraints, and cultural disparities. Adaptive strategies must be developed to ensure intervention feasibility and sustainability.</p>
<p>Low adherence is a pervasive challenge (<xref ref-type="bibr" rid="ref44">44</xref>). For instance, in the SMARRT trial (<xref ref-type="bibr" rid="ref18">18</xref>), 28% of participants withdrew due to insufficient motivation or health status changes. Adherence issues may arise from intervention complexity, lack of immediate feedback, or health fluctuations (<xref ref-type="bibr" rid="ref46">46</xref>). Strategies to enhance adherence include simplifying protocols, setting personalized goals, and offering material incentives (<xref ref-type="bibr" rid="ref6">6</xref>). For example, the GOIZ ZAINDU trial (<xref ref-type="bibr" rid="ref23">23</xref>) increased completion rates to 89% by reducing session duration from 60 to 30&#x202F;min. The APPLE TREE trial (<xref ref-type="bibr" rid="ref21">21</xref>) achieved higher adherence in the intervention group (72% vs. 55% in controls) through personalized goal-setting, feedback, and &#x00A3;20 vouchers.</p>
<p>Resource constraints&#x2014;such as shortages of healthcare professionals, inadequate facilities, and limited funding (<xref ref-type="bibr" rid="ref47">47</xref>)&#x2014;hinder intervention scalability. These challenges can be addressed via digital alternatives and leveraging existing community resources (<xref ref-type="bibr" rid="ref48">48</xref>). The eMIND trial (<xref ref-type="bibr" rid="ref16">16</xref>) reduced staffing needs by 50% and costs by 30% using digital health technologies for remote cognitive training and monitoring. Similarly, the MIND-China trial (<xref ref-type="bibr" rid="ref13">13</xref>) minimized facility costs by collaborating with rural and community health centers.</p>
<p>Cultural differences also affect intervention acceptability (<xref ref-type="bibr" rid="ref49">49</xref>). The LATAM-FINGERS trial (<xref ref-type="bibr" rid="ref24">24</xref>) addressed dietary disparities in Latin America by substituting Nordic fish with local staples (e.g., corn/beans), increasing participant acceptance from 45 to 82%. Thus, multidomain interventions must be culturally adapted to local dietary habits, educational levels, and sociocultural contexts to enhance feasibility.</p>
</sec>
<sec id="sec24">
<label>4.4</label>
<title>Evidence gaps identified by this scoping review</title>
<p>This review identified three key evidence gaps:</p>
<p>Insufficient evidence on Chinese rural populations: Only 1 study (<xref ref-type="bibr" rid="ref13">13</xref>) focused on rural China, and no studies explored interventions for low-income or ethnic minority groups, limiting the generalizability of findings to diverse Chinese populations.</p>
<p>Unclear dose&#x2013;response relationship: The association between intervention frequency/duration and outcomes remains unclear, and no studies have determined the &#x201C;minimum effective dose&#x201D; for Chinese populations, making it difficult to balance intervention effectiveness and feasibility.</p>
<p>Limited long-term follow-up data: Most Chinese studies have a duration of &#x2264;6&#x202F;months, and long-term outcomes (e.g., dementia incidence) are lacking, making it impossible to evaluate the sustainability of intervention effects.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec25">
<label>5</label>
<title>Conclusion</title>
<p>This scoping review systematically mapped global evidence on multidomain dementia prevention interventions, identifying four core components (physical exercise, cognitive training, nutrition, cardiovascular risk management) and their distribution characteristics in implementation frequencies. Multidomain interventions have been associated with improvements in cognitive function, quality of life, and reduction in dementia risk, but evidence inconsistencies and regional differences exist. Subgroup analysis showed that Chinese studies have higher adherence but slightly lower cognitive improvement than studies from non-Chinese countries/regions, mainly due to differences in intervention frequency and cultural adaptation strategies.</p>
<p>The primary contribution of this review is to highlight evidence gaps relevant to Chinese populations, including insufficient rural evidence, unclear dose&#x2013;response relationships, and limited long-term data. Future research should: Develop localized intervention models for Chinese rural and low-income populations, integrating family participation and community resources. Explore the dose&#x2013;response relationship of interventions to determine the optimal balance between effectiveness and feasibility. Conduct long-term follow-up studies to evaluate the sustainability of intervention effects. Establish multidimensional evaluation systems to comprehensively assess intervention impacts on cognitive, physical, and social function.</p>
<p>This review also has limitations: it only included RCTs and excluded grey literature, which may have missed unpublished feasibility data; there was insufficient age-stratified data in the included studies, and the impact of baseline status on intervention effects was overlooked, so future studies need to design dual-dimensional stratified intervention trials based on &#x201C;age-cognitive risk&#x201D;; the included studies adopted inconsistent definitions of high dementia risk and heterogeneous assessment tools for the same outcome indicators, which may impair the comparability between studies; almost none of the included studies reported dementia incidence after intervention completion, which may hinder cross-study comparisons; and there was insufficient reporting of long-term follow-up outcomes in the included studies, with no analysis of the long-term effects of multidomain interventions; and due to the nature of scoping reviews, no quantitative synthesis of outcomes was conducted. Future systematic reviews with meta-analysis can further quantify intervention effects and explore moderating factors.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec26">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="sec27">
<title>Author contributions</title>
<p>XG: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. CF: Writing &#x2013; review &#x0026; editing. JR: Writing &#x2013; review &#x0026; editing. ZZ: Writing &#x2013; review &#x0026; editing. CN: Writing &#x2013; review &#x0026; editing. YL: Funding acquisition, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors sincerely acknowledge the collective efforts that contributed to this work. We extend our gratitude to XG for undertaking the comprehensive literature review and drafting the initial manuscript. Special thanks to CF and JR for their meticulous work in literature curation and figure preparation. We further appreciate ZZ and CN for their invaluable contributions to linguistic refinement and manuscript verification. We gratefully acknowledge these institutions for their financial and academic endorsement. Finally, we thank the editors and reviewers for their insightful feedback and constructive critiques during the peer-review process. Their expertise and dedication significantly strengthened the rigor and clarity of this manuscript.</p>
</ack>
<sec sec-type="COI-statement" id="sec28">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec29">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec30">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec31">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fneur.2026.1729290/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fneur.2026.1729290/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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<fn-group>
<fn fn-type="custom" custom-type="edited-by" id="fn0001">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2658901/overview">Daniela Di Basilio</ext-link>, Lancaster University, United Kingdom</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0002">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/46766/overview">Angel Golimstok</ext-link>, Italian Hospital of Buenos Aires, Argentina</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1517813/overview">Xuan Zhang</ext-link>, National Institute on Aging (NIH), United States</p>
</fn>
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