Discussion
Although several systematic reviews have confirmed the effects of exercise on cognitive function in older adults with MCI, few studies have explored the methodological quality of the corresponding studies or the certainty of evidence. All 18 meta-analyses were published after 2018, highlighting the recent and growing interest in this field. Notably, despite each meta-analysis employing corresponding risk-of-bias tools to assess the quality of the included original studies, the overall quality of evidence from these studies typically ranged from “very low” to “low.” The limited quality of evidence considerably affects the reliability of current clinical recommendations regarding exercise interventions for mild cognitive impairment (MCI). This scenario underscores the need for cautious interpretation of the existing data and suggests that any recommendations made based on these meta-analyses should be regarded as preliminary.

Methodological quality assessment of the 18 meta-analyses using the AMSTAR2 scale revealed that the overall methodological quality of the included trials was low. This indicated that individual meta-analytic studies had varying degrees of methodological deficiencies in terms of topic selection, design, registration, data extraction, and statistical analysis. These deficiencies are mainly attributed to the following aspects.

(1) The included studies did not explain whether they had drafted a research proposal, and only a few studies were registered on the systematic review platform in advance. To effectively reduce the risk of selective reporting bias and avoid being affected by arbitrary decisions in data extraction and use, it is necessary to write a plan or pre-register in advance. In addition, registration on registration platforms (such as The Cochrane Library and PROSPERO) is also conducive to improving the transparency of meta-analysis research.

(2) None of the included studies provided a detailed description of the reasons for excluding the literature. Although the included studies reported a two-person search, screening, and data extraction, it is unknown whether this was performed with strict compliance, which increases the risk of bias. It is recommended that journals require authors to provide a list of excluded studies to ensure transparency during the screening process.

(3) The meta-analysis implementation process was not sufficiently rigorous. Seventeen studies did not adequately consider the potential impact of the risk of bias in the included studies on the analysis of results and did not provide satisfactory answers to the heterogeneity in the meta-analysis results. Additionally, three studies did not adequately evaluate publication bias. Meta-analysis is recognized as the best method by which research evidence on a particular issue can be objectively evaluated and synthesized. The risk of bias analysis, interpretation of sources of heterogeneity, and evaluation of publication bias during the implementation of the meta-analysis determined the reliability of the results. When randomized controlled trials or non-randomized intervention studies with different risks of bias are included, the investigator should conduct an in-depth analysis of the risk of bias in the included literature and discuss its impact on the results (qualitative analysis results or pooled effect sizes). In addition, when heterogeneity tests suggest the presence of heterogeneity, researchers should make every effort to find potential causes of heterogeneity and explore the probable causes of heterogeneity in the discussion section.

(4) Ten studies did not specify the funding sources for the studies included in the meta-analysis production process, which may have led to potential bias, opacity, and weakened trust. The source of funding for a study may have an impact on the findings, as funders may have their own interests and preferences. Lack of information on the source of funding may cause readers to doubt the reliability and transparency of the study. Knowing the source of funding can help readers to understand the context of the study and the interests of the researcher. Simultaneously, if readers suspect that the results of the study are influenced by the source of funding, they may be skeptical about the results of the study and reduce trust in the study.

These findings have significant implications for future research methodologies and clinical practices in exercise interventions for MCI. Our results underscore the importance of adhering to rigorous research protocols and pre-registering studies to enhance transparency and replicability in the design and implementation of exercise interventions for MCI. Detailed documentation of excluded literature and clear disclosure of funding sources will contribute to the credibility of the research and public trust in the findings. More stringent analyses of bias risk and heterogeneity in the studies included in the meta-analysis will improve the accuracy and practicality of exercise intervention recommendations in clinical practice.

In conducting the methodological quality assessment of the included meta-analyses, we observed significant heterogeneity among the studies, which notably impacted our evaluation results. The heterogeneity manifested in several key aspects.

(1) Diversity in study design

The meta-analyses varied in their underlying study designs, encompassing differences in the types of exercise interventions, baseline cognitive status of participants, and the duration and frequency of the interventions. This diversity could lead to varying interpretations of the effects of exercise interventions.

(2) Participant characteristics

Variations in participant demographics such as age, gender, and stage of disease could influence the effectiveness of the exercise interventions. Different studies may focus on distinct populations, affecting the perceived efficacy of exercise on cognitive functions.

(3) Methodological variability

Inconsistencies in data extraction, statistical analysis approaches, and bias risk assessment across studies could contribute to variability in conclusions. For instance, the methods for handling missing data and the choice of effect size models varied, potentially leading to different outcomes.

In summary, the heterogeneity of the studies played a significant role in our methodological assessment. Future methodological evaluations of similar meta-analyses should delve deeper into these heterogeneity factors, detailing them in the study design and reporting to enhance the clarity and comprehensiveness of the findings.

Based on the results of this study, the author makes the following recommendations were made to inform future research and evaluation criteria:

(1) Meta-analysis authors should adhere to the appropriate guidelines for study design, implementation, and reporting. Essential strategies include (a) Consulting the Cochrane Handbook for Systematic Reviews of Interventions to grasp meta-analysis fundamentals, applications, and advantages/disadvantages of relevant software ( e.g. , RevMan, Stata, R, CMA, and OpenMetaAnalyst). For instance, despite RevMan’s suitability for exercise intervention trials, it has limitations in publication bias testing, and authors should be familiar with comprehensive tests such as Egger’s regression analysis and Begg’s rank correlation method available in CMA and Stata. Additionally, increasing the pre-registration of protocols is vital. Authors are encouraged to pre-register their study protocols in registries such as PROSPERO, detailing the planned methods and analyses to enhance transparency and aid in reducing publication bias. Furthermore, enhancing the thorough reporting of study screening and reasons for exclusion is critical for improving transparency and reproducibility. Authors must provide detailed accounts of study selection processes, including clear documentation of screening procedures, criteria for inclusion and exclusion, and explicit reasons for excluding studies, especially those that might influence the meta-analysis outcomes. Better handling of heterogeneity is also essential. Authors should not only report the presence of heterogeneity but explore and explain its sources. This can be achieved by conducting subgroup analyses or meta-regression to investigate potential moderators of effect sizes. A detailed interpretation of how variations between studies might impact the overall findings and conclusions will significantly enhance the quality and credibility of the meta-analysis. (b) Refining and pre-registering study plans based on AMSTAR2 and PRISMA checklists, ensuring detailed reporting, particularly in the AMSTAR2 Methods section, to minimize bias. (c) Emphasizing both the theoretical and practical implications of meta-analyses, high-quality studies should provide reliable evidence, adhere to reporting standards, and advance research fields while offering practical guidance.

(2) To improve the quality of meta-analyses, journal editorial boards and departments should strengthen the reporting requirements through review policies. We suggest the following measures: (a) Develop self-checking report guidelines for meta-analysis authors based on AMSTAR2 and PRISMA checklists tailored to specific situations and establish meta-analysis topics to enhance their impact and standardization. (b) Journal editors should refer to meta-analysis reporting guidelines when initially screening manuscripts or conducting peer-expert reviews to ensure the accuracy and coherence of the report. (c) It should be noted that the AMSTAR2 and PRISMA checklists mainly apply to trial (intervention)-type meta-analyses; some entries may not be applicable to meta-analyses of sports science correlation studies.

(3) Universities need to enhance their theoretical and practical courses on systematic reviews and meta-analyses. While some medical schools or comprehensive colleges have already introduced “evidence-based medicine” or “systematic review/meta-analysis” courses, sports colleges often lack such offerings, hindering the development of professionals in the field. Therefore, we suggest that sports colleges and universities incorporate meta-analysis theory and practice courses into their postgraduate training programs or integrate relevant lectures on systematic review/meta-analysis topics into existing “research methods” and “statistics” courses. This approach can better cultivate professionals with systematic review/meta-analysis expertise and improve the overall educational quality.

There are some limitations to this study: (1) only English literature was included, and the search results may not be comprehensive; (2) there is inevitably some subjectivity in the evaluation and analysis process, which may also lead to bias; (3) a lack of discrimination capacity of the AMSTAR 2.0 tool may affect the ability to achieve moderate or high methodological quality in systematic reviews; (4) the NCSE and COR-SOG scales were only administered once, and the results should be treated with caution.