Review
Abstract
Background: Age-related physiological changes in older adults involve a rapid decline in motor exercise ability; some older adults may also experience difficulties in maintaining focus, memory loss, and a decline in reaction time, which consequently impair their ability to perform dual tasks. Motor-cognitive training (MCT) refers to a blend of motor activity and cognitive training that occurs simultaneously and can assist older adults in enhancing their physical function, cognitive abilities, and dual-task performance. In recent years, the use of technology for delivering MCT has become increasingly popular in research. This has been achieved through various technologies that simplify MCT for older adults.
Objective: This study aimed to systematically examine the feasibility and effectiveness studies on technology-assisted MCT among older adults.
Methods: This rapid review was conducted following the updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 standards, and the Synthesis Without Meta-analysis (SWiM) in systematic reviews reporting guideline. Four databases were searched, including CINAHL, Embase, PubMed, and Scopus, from January 2013 to March 2025. Search strategies were constructed based on three main topics: (1) older adults, (2) MCT, and (3) technology. Inclusion criteria followed the population, intervention, comparator, outcome, and study design framework as follows: older adults (population); technology-assisted MCT (intervention); standard treatment control, active control, partial intervention control, placebo control, and dose-response control (comparator); various measures of physical, cognitive, and dual-task performance (outcome); and randomized controlled trials (RCTs) and pilot RCTs (study design). The Cochrane Risk of Bias Tool was applied for quality appraisal of the included studies. The feasibility of the included studies was assessed using completion rates and attrition rates. Descriptive statistics were used to describe the demographic and clinical characteristics of the groups, while narrative methods were used to categorize and synthesize their effectiveness.
Results: In total, 20 studies were included, comprising 16 RCTs and 4 pilot RCTs, most of which were conducted within a 6-week period. Each session typically lasted between 10 and 30 minutes and was held 2 to 3 times per week. Feasibility analysis showed that technology-assisted MCT was generally feasible. While the workload was high, the perceived usability was also high, with a considerable amount of positive feedback and very few reported adverse events. The types of MCT varied in terms of components, duration, and frequency. The majority of studies (18/20, 90%) demonstrated statistically significant improvements in physical, cognitive, and dual-task performance because of technology-assisted MCT.
Conclusions: The feasibility of technology-assisted MCT among older adults was high regardless of the perceived high workload, and most studies showed statistical effectiveness in improving physical, cognitive, and dual-task performance.
Trial Registration: Open Science Foundation (OSF) Registries 10.17605/OSF.IO/5SRCQ; https://osf.io/5srcq
doi:10.2196/67250
Keywords
Introduction
Background
The United Nations projects that the number of people aged ≥65 years will reach 1.6 billion by 2050, accounting for 16% of the total population []. Older adults will experience age-related decline regarding their physical, cognitive, and dual-task reserves and functions []. For example, physically, most of them will experience osteoporosis, connective tissue problems [,], and muscle fiber loss [], contributing to dysfunction [,]. Cognitively, processing speed demonstrates the earliest decline [], along with a serious decline in learning ability, attention, visual-spatial capability, and working memory [-]. These factors collectively decrease their physical and motor reserves and functions, while cognitive decline will further lead to issues such as memory loss, difficulty maintaining focus, and ultimately slower thinking [,]. “Dual tasking” refers to performing 2 tasks simultaneously, typically combining cognitive and motor tasks of varying complexity, such as doing simple arithmetic like addition or subtraction while walking [,]. Dual tasks are common in daily life and demand the simultaneous processing of multiple pieces of information and tasks, placing greater strain on physical and cognitive reserves and functions [,]. Older adults not only experience a simultaneous reduction in both motor and cognitive reserves and functions, resulting in a gradual or sharp decline in their ability to perform dual tasks, but also reductions in both processing speed, as mentioned earlier, and reaction time [], which further impairs their ability to perform dual tasks. In the meantime, limited opportunities to perform dual tasks in daily life conversely result in the deterioration of physical, cognitive, and dual-task reserves and functions []. These changes result in decreased physical, cognitive, and dual-task reserve and functions in older adults [-], and they ultimately impact their activities of daily living (ADLs) [].
Motor-cognitive training (MCT) is the most typical type of dual task, which combines motor activity (eg, aerobic, strength, and endurance training) with cognitive training (eg, memory and attention training) [,]. This approach significantly improves physical, cognitive, and dual-task performance in various populations [-]. For instance, a systematic review and meta-analysis of 11 randomized controlled trials (RCTs) with 322 participants showed that MCT improved gait, motor symptoms, and balance in patients with Parkinson disease (PD) []. Another review of 13 studies with 584 patients found MCT to be beneficial for balance in patients with multiple sclerosis []. In addition, MCT offers synergistic benefits by combining motor and cognitive training, enhancing brain adaptations and cognition []. A review of 21 studies with 2221 participants showed small-to-medium improvements in cognitive functions in older adults with cognitive impairment []. Synthesized evidence on MCT showed that it improves dual-task performance in patients with PD [] and positively impacts cognitive and physical functions in individuals with dementia or mild cognitive impairment [].
In recent years, as technology is becoming increasingly integrated into our daily lives, its use for delivering MCT has also become increasingly popular in research []. Technology-assisted intervention involves incorporating technology—such as digital devices, tele-technology, monitoring, and assistive technology—into clinical interventions to assess, monitor, educate, and enhance the effectiveness of an intervention []. Technology can address challenges in traditional MCT by refining technological innovations in response to specific needs and creating interactive scenarios []. The use of technology can provide participants with standardized and uniform instructions on their interventions, ensuring consistency of MCT [,]. Technology can make MCT more feasible, enjoyable, and relaxing for older adults [-], providing timely assistance and feedback [-], and increasing the likelihood of voluntary participation and long-term adherence [-]. Technology enhances the motor activity component of MCT by offering premade demonstrations and real-time environments, reducing the need for trainers and reserved spaces [,]. Sensors and interactive technologies can monitor movements in real time, ensuring proper posture and technique [-], and record exercise processes for future improvement [,]. In addition, technology can expand cognitive training beyond basic tasks, offering diverse and engaging exercises through virtual reality (VR) and exergames, which simulate complex cognitive scenarios [,]. Despite these advantages, few reviews have investigated the feasibility and effectiveness of technology-assisted MCT among older adults.
Objectives
In this study was a rapid systematic review to identify various types of technology-assisted MCT and examine the literature in terms of the feasibility and effectiveness of technology-assisted MCT in older adults.
Methods
Overview
This rapid review was conducted in accordance with the updated Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 standards [], and the Synthesis Without Meta-analysis (SWiM) in systematic reviews reporting guidelines []. The PRISMA and SWiM checklists can be found in and , respectively. In addition, 2 other guidelines were used: “Rapid Reviews to Strengthen Health Policy and Systems: A Practical Guide” from the Alliance for Health Policy and Systems Research, World Health Organization (WHO) [], and “Conducting a Rapid Review for Quick Turnaround Knowledge Synthesis” [,]. These methodologies were integrated into the process from the search strategy to the presentation of results. This review was registered on the Open Science Framework platform []. Details of registration are provided in .
Search Methods
We conducted a rapid systematic search for relevant studies using 4 databases, including CINAHL, Embase, PubMed, and Scopus, focusing on literature from the past decade (from January 2013 to March 2025) [,]. To ensure comprehensiveness, we also reached out to the authors of eligible studies without full texts, authors of conference abstracts, and authors of important studies. Our search terms centered on three main topics: (1) older adults, (2) MCT, and (3) technology, by using Medical Subject Headings (MeSH), terms Emtree terms, free-text terms, combinations of these terms, and Boolean operators (eg, and, or, and not). For example, terms like aged (MeSH, Emtree), senior*, elderly (Emtree) for older adults; DT, concurrent-task, cognitive-motor for MCT; and technology (MeSH, Emtree), virtual reality (MeSH, Emtree), exergaming (MeSH) for technology were applied. Details of our search strategies can be found in .
Inclusion and Exclusion Criteria
Published papers were included in this review according to the inclusion criteria following the population, intervention, comparator, outcome, and study design (PICOS) framework []. The exclusion criteria are also provided in the subsequent sections. More details of the inclusion and exclusion criteria for the included studies in this review are in .
Inclusion criteria
- Older adults aged >55 years
- Motor-cognitive training (MCT) delivered using any technology as a whole or part of the intervention
- Standard treatment control, active control, partial intervention control, placebo control, and dose-response control
- A variety of measures related to the physical, cognitive, and dual-task performance
- Randomized controlled trials (RCTs) and pilot RCTs
Exclusion criteria
- Adults aged <55 years
- Non-MCT or MCT not delivered using any technology as a whole or part of the intervention
- Other measures not focusing on physical, cognitive, and dual-task performance
- Other non-RCT studies (eg, pre-post studies)
Inclusion Criteria
Details on inclusion criteria following the PICOS framework are as follows:
For population, we included studies that reported that their participants were older adults, without restrictions based on sociodemographic characteristics such as gender, medical background (clinical or nonclinical population), residence, ethnicity, educational background, or occupational status.
For interventions, technology-assisted MCT was defined as MCT delivered using any technology (including VR, exergames, phones, computers, tele-technology, and other types of technology). We also included studies that used technology-assisted MCT as part of the overall intervention.
For comparators or control, we included studies that compared technology-assisted MCT to treatment. This could be standard treatment control, active control, partial intervention control, placebo control, or dose-response control.
For main outcomes, indicators included a variety of measures related to the physical, cognitive, and dual-task performance of the participants. These measures involved the use of scales, instruments, and sensors to measure physiological metrics of the patient and other tools.
For study design, RCTs and pilot RCTs were included. RCTs use an experimental research design that minimizes bias by randomly assigning participants to intervention and control groups to evaluate the effect of a specific intervention on study outcomes []. In contrast, a pilot RCT is a smaller-scale version of an RCT, typically conducted before a formal RCT study, to assess the feasibility of the intervention, the validity of experimental procedures, and the operationalization of data collection, as well as to test the study design []. RCTs were included in this review because they provide robust evidence, are better able to minimize bias, and offer high internal validity. Pilot RCTs were also considered because the research question addressed by this rapid systematic review concerns a relatively new intervention that has not been widely studied. Pilot RCTs offer preliminary evidence on feasibility, aligned with the review’s objectives, and provide a reasonable foundation for informing larger RCTs.
Exclusion Criteria
Exclusion criteria were studies of adults aged <55 years; non-MCT or MCT not delivered using any technology as a whole or part of the intervention; other measures not focusing on physical, cognitive, and dual-task performance; and other non-RCT studies (eg, pre-post studies).
Screening and Selection
All articles retrieved from the literature search were imported into EndNote (Clarivate), where duplicates were automatically removed. Two researchers (Y Li and Y Liu) managed and selected the literature, following this screening process: first, titles and abstracts were independently screened by the researchers. Full texts were obtained if at least 1 reviewer believed an article met the inclusion criteria. Subsequently, 2 reviewers independently verified the eligibility of references through full-text screening. If disagreements on inclusion arose and could not be resolved through discussion, a third reviewer (JM) was consulted. Reasons for exclusion were documented. The general process of literature search and study selection was described using a flowchart following the updated PRISMA 2020 guidelines [].
Quality Appraisal
Two researchers independently reviewed each study for methodological quality and rigor. They used the Cochrane Risk of Bias Tool (version 2.0) [] for RCTs. In cases of disagreement, a third researcher (JM) was consulted.
Data Abstraction
Data were independently extracted by 2 researchers using a standardized form, and all processes involved in obtaining and validating data from the original authors were documented. The form included the following information: (1) characteristics of the included papers, such as author, country, year of publication, information regarding participants (sample size, age, and gender), and experimental design; (2) intervention details, including study duration, type of intervention, intervention components (physical and cognitive part), dosages, duration of each session, frequency, intensity, type of control, the content of control, technological device applied in the studies, the form of delivery (online, offline, mixed); (3) information on feasibility, including overall recruitment, retention, attainment, and dropout rates; (4) measures of participants’ physical, cognitive, and dual-task performance. Disagreements during the data extraction process were resolved through discussions with a third-party researcher (JM). All recommendations were incorporated once a consensus was reached. When study data were published in multiple articles, the article with the most detailed information or the largest sample size was selected.
Data Analysis
The feasibility of the included studies in this review was assessed using completion rates and attrition rates for calculations. In addition, the most-used scales to assess the feasibility of the intervention systems were presented in this review, along with statistical analysis of scores obtained in each study. We reviewed feedback on each intervention from participants in each study and presented several narratives from participants. The frequency of adverse events associated with the interventions was also calculated, along with specific descriptions of those events.
In this study, a rapid systematic review was conducted due to the significant variation among the included studies. These variations encompassed differences in the intervention components (motor and cognitive), settings, the total duration, the duration of each session, frequency, the technologies applied, the time points for outcome measurement, and the outcome indicators. Descriptive statistics were used to describe the demographic and clinical characteristics of the groups, while narrative methods were used to categorize and synthesize the effectiveness.
Quality Evaluation of the Configuration of the Intervention Components (Motor and Cognitive)
This review analyzed the quality of the configuration for each component, including motor activity and cognitive training parts, and evaluated them according to previous standards or guidelines, to determine if they meet the training standards. The criteria for the quality assessment of each component compiled in this review simply represent the criteria for conducting quality evaluations in this review, to facilitate the following analysis of the effects of all included studies. The aspects and criteria for each inspection were as follows. First, the motor activity aspect: components were considered effective if the study stated that the intervention design was based on exercise guidelines, specific research findings (eg, previous studies or expert opinions), or if the design—including the components, session duration, frequency, and total volume—met WHO recommendations for exercise for older adults []. In such cases, interventions were marked with a checkmark. Second, the cognitive training aspect: interventions were considered effective if the study indicated that the intervention design was based on guidelines related to cognitive interventions, or specific research findings (eg, previous studies or expert opinions). In these cases, interventions were marked with a checkmark.
Evaluation of Effects
In this review, we carefully examined each included study for statistical significance across the following 3 outcome metrics: physical, cognitive, or dual task–related measures. If a study demonstrated statistical significance for a particular outcome (any related outcome indicators in physical, cognitive, or dual-task performance), it was considered valid in that area (eg, physical, cognitive, or dual-task performance). In these cases, if there are some outcome indicators with statistical significance, they were marked with a checkmark.
Results
Overview
The literature search yielded 5874 potentially relevant studies. After removing 567 duplicates using EndNote, 5307 were screened by 2 independent researchers. After a thorough evaluation of titles and abstracts, 5253 studies were excluded, of which 4782 were excluded based on their titles, and an additional 471 were removed after reviewing their abstracts, as they did not meet the inclusion criteria of this review. Following this preliminary screening, we conducted a full-text review of the remaining 54 articles, of which 34 were further excluded due to specific reasons outlined in the PRISMA flowchart in . Consequently, 20 articles met our inclusion criteria and were included.

Quality Appraisal
Of the 20 RCTs, 8 (40%) had high risk, 10 (50%) had some risk, and only 2 (10%) had low risk. This indicates that most of the trials had some level of risk in their design, resulting in an overall moderate quality. To be specific, there were high levels of risks in 10% (2/20) of studies (studies 8 and 20; the number of studies is consistent with the values presented the tables) and some risks in 45% (9/20) of studies (studies 1, 2, 4, 7, 9, 10, 14, 17, and 18) regarding randomization [-]. Regarding deviations from the intended intervention, 10% (2/20) of studies (studies 16 and 18) had a high level of risk, and 30% (6/20) of studies (studies 5, 11, 13, 14, 19, and 20) had some risk. For the measurement of outcomes, 25% (5/20) of studies (studies 5, 8, 13, 17, and 19) showed high risk. Finally, in the selection of reported results, 50% (10/20) of studies (studies 2, 3, 4, 7, 8, 14, 15, 16, 17, and 19) had some risk. The details of quality appraisals of these 20 RCT studies are presented in and and .


| Number | Study | Randomization | Deviations from intended intervention | Missing outcome data | Measurement of outcome | Selection of reported result | Overall |
| 1 | Menengi et al [], 2022 | Some concerns | Low | Low | Low | Low | Some concerns |
| 2 | Jäggi et al [], 2023 | Some concerns | Low | Low | Low | Some concerns | Some concerns |
| 3 | Kwan et al [], 2021 | Low | Low | Low | Low | Some concerns | Some concerns |
| 4 | Altorfer et al [], 2021 | Some concerns | Low | Low | Low | Some concerns | Some concerns |
| 5 | Manser et al [], 2023 | Low | Some concerns | Low | High | Low | High |
| 6 | Fishbein et al [], 2019 | Low | Low | Low | Low | Low | Low |
| 7 | Kannan et al [], 2019 | Some concerns | Low | Low | Low | Some concerns | Some concerns |
| 8 | Uematsu et al [], 2023 | High | Low | Low | High | Some concerns | High |
| 9 | Liao et al [], 2019 | Some concerns | Low | Low | Low | Low | Some concerns |
| 10 | Schoene et al [], 2015 | Some concerns | Low | Low | Low | Low | Some concerns |
| 11 | Forte et al [], 2023 | Low | Some concerns | Low | Low | Low | Some concerns |
| 12 | Pelosin et al [], 2021 | Low | Low | Low | Low | Low | Low |
| 13 | Eggenberger et al [], 2015 | Low | Some concerns | Low | High | Low | High |
| 14 | Delbroek et al [], 2017 | Some concerns | Some concerns | Low | Low | Some concerns | Some concerns |
| 15 | Hagovska and Nagyova[], 2017 | Low | Low | Low | Low | Some concerns | Some concerns |
| 16 | Park et al [], 2020 | Low | High | Low | Low | Some concerns | High |
| 17 | Villa-Sánchez et al [], 2023 | Some concerns | Low | Low | High | Some concerns | High |
| 18 | Buele et al [], 2024 | Some concerns | High | Low | Low | Low | High |
| 19 | Zak et al [], 2024 | Low | Some concerns | Low | High | Some concerns | High |
| 20 | Kwan et al [], 2024 | High | Some concerns | Low | Low | Low | High |
Data Characteristics of Included Studies
A total of 20 RCTs were included in this review, of which only 4 (20%) were pilot RCTs (studies 1, 2, 4, and 5); the remaining 16 (80%) studies were RCTs. Only 5% (1/20) of study focused solely on feasibility (study 17), while 20% (4/20) of studies examined both feasibility and effects (studies 2, 3, 4, and 5). The remaining 75% (15/20) of studies exclusively investigated the effectiveness of their research subject (eg, improvement of gait performance, balance performance, and fall prevention). These papers were published between 2015 and 2024, with a notable uptick in 2023 (6/20, 30%), and were published in 13 different countries, namely, Switzerland (4/20, 20%), Italy (3/20, 15%), China (3/20, 15%), and other countries (10/20, 50%), including the United States, Korea, Ecuador, Poland, Turkey, Israel, Japan, Australia, Belgium, and Slovak Republic. These works were disseminated across 17 distinct journals, with the highest number of publications found in Frontiers in Aging Neuroscience (4/20,20%). In total, 10% (2/20) of studies applied co-design (studies 5 and 20) while others reported no co-design elements, and only 5% (1/20) of study reported study fidelity (study 20). Co-design is a design methodology that emphasizes collaboration among multiple parties, particularly stakeholders such as end users, researchers, and others []. It encourages active participation throughout the design process by communication, creative input, sharing insights, and testing new ideas, to ensure the outcome better aligns with the needs, desires, and real-world contexts of the stakeholders (eg, development of a new exergame). Half of the included studies (studies 3, 6-9, 12-15, and 18; 10/20, 50%; all RCTs) did not perform sample size calculations. More details are provided in the summary table in .
This review analyzed data from 20 studies, encompassing 1197 participants. The population size in these studies ranged from a minimum of 16 to a maximum of 293 participants, with an average of 59.9 (SD 4075.5) participants per study. Although all the included studies stated they would focus on older adults, and most participants were aged ≥60 years, only 1 (5%) study included individuals aged ≥50 years in their study (study 7).
Study Designs of Included Studies
The following are some of the basic characteristics of the included studies.
Inclusion and Exclusion Criteria of Participants in the Included Studies
Most of the included studies stipulated that participants should be older adults; however, the age of participants stipulated in these studies ranged from >50 years (studies 2, 4, and 5), to ≥70 years (studies 10, 13, and 19). The participants’ physical conditions differed, encompassing healthy and nondependent community-dwelling older adults (studies 3, 8, 10, 11, 13, and 17), individuals with mild cognitive impairment (studies 9, 16, 18, and 20), those diagnosed with idiopathic PD (studies 2 and 12), stroke patients (studies 6 and 7), hospitalized older adults (studies 4 and 14), and patients with Alzheimer (study 1).
At baseline, many studies screened participants using cognitive assessment tools, such as the Brief Mental State Examination (studies 1, 2, 4, 16, 17, and 19), or the Montreal Cognitive Assessment (studies 3, 9, 14, 18, 20). In addition, regarding physical abilities, standing or walking for a specified duration was another criterion. These included standing for 3 minutes (studies 2 and 4), standing unassisted or assisted for 5 minutes (studies 7 and 12), and standing for 10 minutes (study 5). Additional criteria encompassed walking with or without a walker (study 10), walking unassisted or assisted for 10 meters (studies 6, 9, and 14), and walking with or without assistance for 20 meters (study 13).
Independence in performing daily activities was also a common requirement (studies 5, 8, 9, 10, 11, and 16). Furthermore, participants were expected to possess the ability to provide informed consent (studies 2, 4, 13, 16, and 18), and adequate communication skills (studies 1, 7, and 16). Finally, some studies also had criteria related to a stable medication regimen or a history of specific treatments (studies 1, 2, and 12) and if the participant had a history of falls (studies 8 and 12).
Exclusion Criteria Applied in the Studies
The most-mentioned exclusion criteria among included studies were cognitive impairment, such as dementia (studies 3, 7, 9, 10, 12-15, 18, and 20), or significant cognitive deficits in potential participants. In addition, the inability to comprehend instructions or effectively communicate (often due to language barriers or sensory impairments), often led to exclusion in some cases (studies 1-7, 12, 14-16, and 18-20). Moreover, individuals with unstable or acute medical conditions, including major mental illnesses, were also typically ineligible (studies 1, 2, 4, 5, 9, 10, 12, 15, 16, 18, and 19). Finally, participants who had recently undergone major surgery or had acute orthopedic conditions were generally excluded (study 14). The history of falls also served as an exclusion criterion in certain studies (study 6).
Technologies Applied in the Studies and Configuration of the Intervention Components (Motor and Cognitive) of MCT
In this review, we reviewed and confirmed that all the included studies used simultaneous MCT, except the study by Buele et al []. Notably, we found that MCT showed significant variation in the configuration of components (motor activity and cognitive training), as well as in the duration and frequency of each session of each component. Among the included types of MCT, some were more focused on motor activity interventions involving simple cognitive tasks such as performing addition and subtraction while engaging in specific-intensity, multicomponent, structured motor exercise (eg, aerobic, strength, and balance training). Others were more cognitively focused, structured within a broad cognitive exercise framework, where participants performed simple gross motor activities such as moving their legs back and forth. Also, there were no golden-standard guidelines on how to structure MCT interventions to simultaneously improve physical, cognitive, and dual-task performance. More details are provided in .
In , we briefly describe the components of the motor activities and cognitive training interventions for each MCT, noting whether technology was used in these 2 components, and specifying the technologies used in either 1 part or the overall MCT. We also report whether either intervention component (physical and cognitive) was developed based on ADLs (eg, dressing, eating, or mobility), or instrumental ADLs (IADLs; eg, shopping, housekeeping, or laundry). In , for the motor activity part, studies 2, 4, and 5 were developed based on ADLs, while study 16 was based on IADLs. Studies 3, 6, 12, 15, 18, and 20 did not use technology for motor activities. Among these, studies 3, 6, and 12 used treadmills, whereas study 15 focused on stamina training. Regarding cognitive training, studies 2, 4, 5, and 15 were based on ADLs, whereas studies 3, 9, 16, 18, and 20 were based on IADLs. Only study 7 did not incorporate technology. The following technologies frequently mentioned among the included studies, including the Dividat Senso (3/20, 15%), the Wii Fit Games (2/20, 10%), exergames besides Wii Fit Games (5/20, 25%), VR noted in various forms (8/20, 40%), and 2 other technologies in 2 (10%) studies. In this study, there were 7 active controls (studies 3, 9, 11, 15, 16, 18, and 19), 5 (25%) studies used standard treatment control as a control group (studies 1, 2, 4, 5, and 20), 4 placebo controls (studies 8, 10, 14, and 17), 3 partial intervention control (studies 6, 7, and 13), and 1 dose-response control (study 12). In addition, regarding the implementation of MCT, 12 (60%) out of 20 studies reported their intervention settings. Specifically, 4 (20%) out of 20 studies (studies 3, 18, 19, and 20) in community settings, 3 (15%) studies (studies 1, 5, and 10) implemented interventions at home, 3 (15%) studies (studies 2, 4, and 7) in clinical rehabilitation settings, 1 (5%) study (study 15) in outpatient settings, and 1 (5%) study (study 14) in a residential care center. More details are provided in .
| Number | Study | Physical | Cognitive | How to cooperate | Control group | Settings |
| 1 | Menengi et al [], 2022 | Chair-based exercises | Cognitive training facilitated through a computer or tablet | Online supervision (Zoom) | Standard treatment control | Home-based |
| 2 | Jäggi et al [], 2023 | Regular rehabilitation and exercises included in the Dividat Sensoa | Exercises included in the Dividat Sensoa | The Dividat Senso | Standard treatment control | In an inpatient rehabilitation setting |
| 3 | Kwan et al [], 2021 | Cycling on an ergometerb | Cognitive training on VRc | VR platform | Active control | In community |
| 4 | Altorfer et al [], 2021 | Regular rehabilitation therapy and exercises included in the Dividat Sensoa | Exercises included in the Dividat Sensoa | The Dividat Senso | Standard treatment control | In a geriatric inpatient rehabilitation setting |
| 5 | Manser et al [], 2023 | Exercise based on the brain-IT system (heart rate variability-induced resonance respiration) in combination with the exercises included in the Dividat Sensoa | Combination of cognitive traininga based on the brain-IT system and the Dividat Senso | The brain-IT system and the Dividat Senso | Standard treatment control | At home |
| 6 | Fishbein et al [], 2019 | Treadmillb | The SeeMee system | The SeeMee system | Partial intervention control | —d |
| 7 | Kannan et al [], 2019 | Body movement, balance games | Addition, subtraction, and multiplicationb | Wii Fit, balance board | Partial intervention control | In clinical stroke rehabilitation settings |
| 8 | Uematsu et al [], 2023 | Balance training | Cognitive training included in Wii Fit Games | Wii Fit | Placebo control | — |
| 9 | Liao et al [], 2019 | The physical regimen comprised resistance, aerobic, and balance exercises aligned with the American College of Sports Medicine standards for older adults | Activities like reciting poems while walking, naming flowers and animals while navigating obstacles, and solving math problems during resistance exercisesc | VR | Active control | — |
| 10 | Schoene et al [], 2015 | 4 specific stepping games, balance training | Stepping training targeted cognitive functions of fall prevention in older adults | Electronic pedals, computer interface, and television screen | Placebo control | At home |
| 11 | Forte et al [], 2023 | Gross motor coordination (upper and lower body movements designed to enhance both static and dynamic balance) | Stimulus-response cognitive tasks generated by an device (Witty-SEM) | Witty-SEM | Active control | — |
| 12 | Pelosin et al [], 2021 | Using a Kinect camera to capture participants’ foot movements on a treadmill, the system integrated these movements into a computer-generated virtual environment displayed on a screen, and participants were required to avoid virtual obstaclesb | Various cognitive domains, such as executive functions, attention, working memory, and visual processing | A TT+VR system (V-TIME), a Kinect camera | Dose-response control | — |
| 13 | Eggenberger et al [], 2015 | The training was designed following current physical fitness and fall prevention recommendations for older adults, focusing on aerobic endurance exercises | Cognitive training | A VR video game, DANCE | Partial intervention control | — |
| 14 | Delbroek et al [], 2017 | Physical training in 9 exercises designed to improve balance, weight-bearing, memory, attention, and dual-tasking abilities | Cognitive training in 9 exercises designed to improve balance, weight-bearing, memory, attention, and dual-tasking abilities | The BioRescue | Placebo control | In a residential care center |
| 15 | Hagovska and Nagyova [], 2017 | Physical trainingb | Cognifita | Cognifit | Active control | In an outpatient psychiatric clinic of the Highly Specialized Geriatric Institute |
| 16 | Park et al [], 2020 | A device with software using VR for activities such as driving, bathing, cooking, and shoppingc | This setup facilitated training in attention, memory, problem-solving, and executive functionsc | The MOTOcog system | Active control | — |
| 17 | Villa-Sánchez et al [], 2023 | Walking on carpet | Counting backward | Sensing carpet | Placebo control | — |
| 18 | Buele et al [], 2024 | Balance exercises (eg, walking in a straight line, squats, brisk walking, going up and down stairs, and social dancing individually and in pairs)b | Collective social interaction activities, and an immersive VR-based system that simulates a task of searching for ingredients in a kitchen cupboardc | VR | Active control | Community |
| 19 | Zak et al [], 2024 | Walking, walking with putting a ball between the hands, and walking with tossing a ball | Cognitive exercises, talking, adding up numbers, subtracting numbers, repeating phrases, reciting a word chain, and identifying objects | VR | Active control | Community |
| 20 | Kwan et al [], 2024 | Bikingb | The VR game contains 8 different themes: orientation, finding a bus stop, reporting lost items, finding a supermarket, grocery shopping, cooking, finding a travel hot spot, and bird watchingc | VR | Standard treatment control | Community |
aInterventions developed based on activities of daily living.
bNontechnologically supported components.
cInterventions developed based on instrumental activities of daily living.
dNot available.
Duration of Total Experiments and Each Session and Intervention Frequency
The intervention period varied from 2 weeks to 6 months, with many studies lasting 6 weeks (6/20, 30%), 2 to 4 weeks (4/20, 20%), 8 weeks (3/20, 15%), and 12 weeks (3/20, 15%). Each intervention session lasted between 10 and 30 minutes (12/20, 60%), followed by 30 minutes (4/20, 20%), 40 to 60 minutes (3/20, 15%), the other studies did not specify the exact times for the interventions. Regarding frequency, most interventions occurred 2 to 3 days per week (8/20, 40%), followed by 4 to 5 days per week (4/20, 20%). More details can be found in .
Feasibility Analysis
Feasibility, Acceptability, and Adherence
Regarding feasibility, acceptability, and adherence, most included studies have shown high completion and low attrition rates (studies 1, 2, 4, 6-8, 10, and 13-17), indicating high participant engagement and intervention suitability.
The NASA Task Load Index and the System Usability Scale
The NASA Task Load Index (TLX) is a widely used subjective multidimensional assessment tool that rates perceived workload to evaluate the effectiveness or other aspects of the performance of a task, system, or team. The scale has a total score of 100, with workload score values of 0 to 9 as low, 10 to 29 as moderate, 30 to 49 as slightly high, 50 to 79 as high, and 80 to 100 as very high []. Two articles in this review applied the NASA-TLX (studies 2 and 4), with the highest NASA-TLX mean score of 56.2 (study 2) and the lowest of 45.5 (study 4), indicating high workloads.
The System Usability Scale (SUS) is a commonly used tool to analyze the perceived usability of a system, product, or service, scored on a scale of 0 to 100, where the higher the score, the better the usability []. Total 3 (15%) of the 20 included studies measured SUS (studies 2, 4, and 5), with mean SUS scores ranging from 71.7 to 83.6, providing better information on overall participant satisfaction and user-perceived usability of the system.
Positive Feedback
Positive feedback from participants and medical staff (studies 1 and 14) included the following: “the caregivers stated that they agreed 100% with the expressions-my patient was satisfied with the online exercise treatment” and “I was satisfied with the online exercise treatment” from study 1 and “Interviews with participants from the intervention group showed that they found the program useful for their concentration, memory, and balance, according to the results of the IMI, which resulted in high compliance. They scored the program as very interesting and pleasant to do and perceived their performance of the different exercises as good to very good” from study 14. This demonstrated acceptance and satisfaction with the interventions. These similarities suggest that the interventions were generally well-received, feasible to implement, and safe for participants from different study backgrounds.
Adverse Events
The results from the included studies consistently highlight the absence of significant adverse events throughout the study period across studies as follows: most of the studies reported no dropouts or adverse events linked to the exercise treatment (studies 1, 2, 4, and 6-17). Among these studies, 20% (4/20) of minor adverse events were noted; however, all evidence suggests that there is no direct link between these adverse events and the intervention. They were “minor technical issues, such as video sound and connection problems, were reported but did not impede the sessions, and caregivers expressed high levels of satisfaction” (study 1); “most participants did not experience symptoms of VR sickness, while two individuals in the control group withdrew due to moderate joint and muscle pain” (study 3); and “specifically falls resulting in bruises, were noted in the intervention group, importantly, these events were unrelated to the ‘Brain-IT’ training” (study 5). Overall, the prevalence of adverse events in these included studies underscores the safety and minimal adverse effects associated with the interventions examined in the review.
Quality Evaluation of the Configuration of the Intervention Components (Motor and Cognitive)
On the basis of the quality evaluation criteria mentioned in the Quality Evaluations of the Configuration of the Intervention Components (Motor and Cognitive) subsection in the Methods section, 6 of 20 (30%) studies met the standards for motor activity design (studies 5, 6, 9, 11, 13, and 19). In total, 12 of 20 (60%) studies were qualified for cognitive training design (studies 2-5, 10-12, 14-16, 19, and 20). However, only 3 of 20 (15%) studies qualified in both aspects (studies 5, 11, and 19). Details are provided in .
| Number | Study | Physical | Cognitive |
| 1 | Menengi et al [], 2022 | ||
| 2 | Jäggi et al [], 2023 | ✓ | |
| 3 | Kwan et al [], 2021 | ✓ | |
| 4 | Altorfer et al [], 2021 | ✓ | |
| 5 | Manser et al [], 2023 | ✓ | ✓ |
| 6 | Fishbein et al [], 2019 | ✓ | |
| 7 | Kannan et al [], 2019 | ||
| 8 | Uematsu et al [], 2023 | ||
| 9 | Liao et al [], 2019 | ✓ | |
| 10 | Schoene et al [], 2015 | ✓ | |
| 11 | Forte et al [], 2023 | ✓ | ✓ |
| 12 | Pelosin et al [], 2021 | ✓ | |
| 13 | Eggenberger et al [], 2015 | ✓ | |
| 14 | Delbroek et al [], 2017 | ✓ | |
| 15 | Hagovska and Nagyova [], 2017 | ✓ | |
| 16 | Park et al [], 2020 | ✓ | |
| 17 | Villa-Sánchez et al [], 2023 | ||
| 18 | Buele et al [], 2024 | ||
| 19 | Zak et al [], 2024 | ✓ | ✓ |
| 20 | Kwan et al [], 2024 | ✓ |
Effects of Interventions and Study Characteristics
Except for 10% (2/20) studies (studies 5 and 17), nearly all studies reported the effects of the intervention, including in physical, cognitive, and dual-task performance, in at least 1 or 2 aspects. The physical and cognitive quality evaluations in are derived from the assessments presented in . More details are provided in , which is a summary of whether there were any statistically significant outcome indicators in each 3 domains (“yes,” “no,” or “was not tested in this domain”), and , which provides the details of statistically significant outcome indicators in the 3 domains.
| Number | Study | Physical (quality)a | Physical (results)b | Cognitive (quality)a | Cognitive (results)b | Dual-task (results)c |
| 1 | Menengi et al [], 2022 | Xd | ✓d | Xe | ✓e | — |
| 2 | Jäggi et al [], 2023f | Xd | ✓d | ✓ | ✓ | X |
| 3 | Kwan et al [], 2021g | Xd | ✓d | ✓ | ✓ | — |
| 4 | Altorfer et al [], 2021f | Xh | Xh | ✓ | ✓ | ✓ |
| 5 | Manser et al [], 2023f | ✓i | Xi | ✓j | Xj | — |
| 6 | Fishbein et al [], 2019 | ✓k | ✓k | Xl | — | — |
| 7 | Kannan et al [], 2019 | Xd | ✓d | Xe | ✓e | X |
| 8 | Uematsu et al [], 2023 | Xd | ✓d | Xl | — | — |
| 9 | Liao et al [], 2019g | ✓k | ✓k | Xe | ✓e | ✓ |
| 10 | Schoene et al [], 2015 | Xh | Xh | ✓ | ✓ | — |
| 11 | Forte et al [], 2023 | ✓k | ✓k | ✓ | ✓ | — |
| 12 | Pelosin et al [], 2021 | Xh | Xh | ✓ | ✓ | — |
| 13 | Eggenberger et al [], 2015 | ✓k | ✓k | Xl | — | ✓ |
| 14 | Delbroek et al [], 2017 | Xh | Xh | ✓ | ✓ | X |
| 15 | Hagovska and Nagyova [], 2017f | Xd | ✓d | ✓ | ✓ | — |
| 16 | Park et al [], 2020g | Xh | —h | ✓ | ✓ | — |
| 17 | Villa-Sánchez et al [], 2023 | Xh | Xh | Xl | Xl | X |
| 18 | Buele et al [], 2024 | Xh | —h | Xe | ✓e | — |
| 19 | Zak et al [], 2024 | ✓k | ✓k | ✓j | Xj | — |
| 20 | Kwan et al [], 2024 | Xd | ✓d | ✓ | ✓ | — |
aIn the physical (quality) and cognitive (quality) columns, “✓” means met the criteria, “X” means did not meet the criteria, and “—” means not measured.
bIn the physical (results) and cognitive (results) columns, “✓” means met statistical significance, “X” means did not meet statistical significances, and “—” mean not measured.
cIn the dual-task (results) column, “✓” means effective in dual-task performance, “X” means ineffective in dual-task performance, and “—” mean not measured.
dConsistency of design and results in the motor activity designation did not meet the previous training standards, guidelines for motor activity design, but had motor effects.
eConsistency of design and results in the cognitive training designation did not meet the previous training standards, guidelines of cognitive design, but had cognitive effects.
fInterventions developed based on activities of daily living.
gInterventions developed based on instrumental activities of daily living.
hConsistency of design and results in the motor activity designation did not meet the previous training standards, guidelines of motor design, and was without motor effects.
iConsistency of design and results in the motor activity designation met the previous training standards, guidelines of motor activity design, but without motor effects.
jConsistency of design and results in the cognitive training designation met the previous training standards, guidelines of cognitive training design, but without cognitive effects.
kConsistency of design and results in the motor activity designation met the previous training standards, guidelines of motor activity design, and received statistically significant outcomes.
lConsistency of design and results in the cognitive training designation did not meet the previous training standards, guidelines of cognitive design, and was without cognitive effects.
Effects on Physical Performance
This part reported physical performance across multiple studies that showed effectiveness (studies 1-3, 6-9, 11, 13, 15, 19, and 20). Among the physical function-related outcome indicators demonstrating statistical significance, the most commonly applied indicators, including the 5 times sit to stand test (studies 1, 2, and 11), walking speed or time (studies 6, 11, and 13), the timed up and go test (studies 1 and 11), ADL (studies 1 and 15), the Short Physical Performance Battery (studies 2 and 13), gait performance (studies 9 and 13), and fall-related metrics (studies 10 and 13).
Effects on Cognitive Performance
Results in cognitive function measurements were also reported as effective in some studies (studies 1-4, 7, 9-12, 14-16, 18, and 20). Among the cognitive outcome indicators demonstrating statistical significance, the most common ones included the Montreal Cognitive Assessment (studies 3, 11, 16, 18, and 20), the trail making test parts A and B (studies 9, 15, and 16), the go or no-go test (studies 2 and 4), and visuospatial ability (studies 10 and 12).
Effectiveness on Dual-Task Performance
Dual-task performance was assessed in only 35% (7/20) of the studies (studies 2, 4, 7, 9, 13, 14, and 17), while only 15% (3/20) of them (studies 4, 9, and 13) showed the effectiveness of the intervention in dual-task performance. Of these 7 studies, there were 2 studies (studies 2 and 4) that were pilot RCTs, while the others were full RCTs.
Discussion
General Characteristics of the Included Studies
This is the first systematic review specifically assessing the feasibility and effectiveness of technology-assisted MCT in older adults with various physical conditions. Upon review, there were only 20 RCT studies of technology-assisted MCT interventions. Although interest has been growing yearly, and an uptick in 2023 was captured (6/20, 30%), the number of studies remains relatively sparse. Most studies included in this review used exergame technology to deliver MCT (including systems such as Dividat Senso, Wii Fit Games, and other exergames; 10/20, 50%), and this was closely followed by the use of VR technology (8/20, 40%). Only 5% (1/20) of studies used remote intervention design, and nearly half (10/20, 50%) focused on fall prevention, walking performance, balance, or gait performance. Moreover, co-design was not widely applied (2/20, 10%), despite its importance for boosting user engagement, system usability, user experience [], and potentially increasing the effectiveness of the training [,]. Finally, the sample sizes were generally small, for both the total number of participants and the average number per study. In the meantime, proper sample size estimation methods were only applied in half (10/20, 50%) of the included studies. The average number of participants was <60 [] and was not only typically seen in all pilot RCTs (studies 1, 2, 4, and 5), but most of the RCTs (studies 3, 6-9, 11, 14, and 16-18).
There are some positive aspects to highlight. This review includes a relatively representative sample involving both healthy and older adults with chronic conditions. Participants were selected based on their physical and cognitive functioning to ensure a proper intervention basis for MCT (eg, sufficient physical, cognitive functioning, communication skills, while excluding participants with severe cognitive or mobility impairments, sensory deficits, acute illnesses, unstable medical conditions, recent major surgeries, or a significant history of falls). The most common total experiment duration was 6 weeks, each session typically lasted 10 to 30 minutes, and they took place 2 to 3 times per week. In experiments, shorter durations with higher frequency effectively avoid participant fatigue, which may also have the potential to impact performance and response [], reduce attrition, maintain compliance [,], and lower the overall cost of the experiment. In addition, the primary outcome of this review demonstrated excellent feasibility, acceptability, and adherence. Although the perceived workload was average to high, the perceived usability of the systems was also high. Furthermore, most studies received positive feedback with few negative events. Overall, the data suggest that the feasibility of this technology-assisted MCT intervention is high, with minimal prevalence of adverse events.
Relationship Between the Varied Effects and the Different Configurations (Motor and Cognitive Components) of the Technology-Assisted MCT
As mentioned in the introduction, MCT has proven effective in improving physical, cognitive, and dual-task performance among older adults []. However, the effectiveness of MCT varied across studies. For example, it varied in exercise effectiveness among older adults [], gait and balance effectiveness varied among older adults with cognitive impairments [], cognitive function effectiveness varied among individuals with various clinical conditions [], and balance-oriented motor activity, cognitive training, and dual-task performance enhancement through performance-related interventions varied among normal older adults []. To achieve these benefits, training interventions should have increased difficulty, appropriate intensity, sufficient duration, task specificity, and variable task prioritization []. In addition, after carefully examining and cross-checking the effects from each included study of their MCT delivered via various technologies (eg, exergames, VR, and other technologies), we found no significant results. On this basis, we can see that the differences in effects may be blamed on the various configurations of MCT, including motor and cognitive components.
In this review, all the studies included were interpretable except for study 5, which showed inconsistent results. This may be attributed to the small sample size in this study (16/20, 80%) among all the included studies, the older aged participants (mean age 79.9 years in the intervention group and 73.7 years in the control group), and the occurrence of adverse events (3 slight adverse events happened in the intervention group, such as falls in homes with bruises, but no more serious injuries) weakened the effectiveness of the interventions. For control groups, there were 7 active controls, 25% (5/20) of studies used standard treatment as a control, 4 used placebo controls, 3 used partial intervention controls, and 1 used a dose-response control. Except for studies that included standard treatment as a control or a placebo control, the remaining studies with other kinds of control groups can be compared to noninferior experiment designs. As a result, there may be an ability to account for the greater effectiveness in the experimental group than the control group.
This review found that physical designs that follow the recommended requirements (eg, for volume, duration, frequency) for motor activity training based on previous research and WHO guidelines [,] form a basis to receive exercise benefits. Cognitive gain, on the other hand, depends not only on physical design, but also the cognitive design and whether the participant has an associated cognitive impairment. Moreover, it is possible that physical designs meeting the above criteria are a basis for obtaining beneficial performance in dual tasks. Regarding the design of motor activity interventions, 5 of 20 (25%) studies, (partial intervention control: studies 6 and 13; active control: studies 9, 11, and 19) met the criteria for motor activity, and all these 5 physical measures showed statistical significance. For cognitive design, studies 6 and 13 did not meet the criteria and did not assess cognitive performance. The cognitive intervention in study 11 met the criteria and showed statistically significant cognitive outcomes. Study 9 did not meet the criteria for cognitive training but demonstrated statistical significance in cognitive outcome measures. This may be attributed to the achieved level of physical activity in study 9, which was based on neuroplasticity theory [], positively influencing cognitive function. Conversely, study 19 met the criteria for cognitive training, but did not show significant cognitive improvements. Upon reviewing study 19, which focused on healthy older adults whose score on the Brief Mental State Examination was >23, its absence of cognitive impairment potentially explains the lack of statistical significance. Finally, studies 6, 11, and 19 did not measure dual-task effects, while studies 9 and 13 demonstrated statistical significance.
All adults should undertake regular physical activity (a strong recommendation with moderate-certainty evidence) according to the WHO guidelines []. In this review, 7 studies (standard treatment control: studies 1, 2, and 20; active control: studies 3 and 15; partial intervention control: study 7; placebo control: study 8) did not meet the criteria for motor activity yet showed physical statistical significance. This discrepancy, along with the WHO recommendations for older adults’ motor activity, may suggest that even though their motor activity did not meet recommended standards, participants still gained exercise benefits. In addition, this finding also reveals that this rule is adaptive to technology-assisted MCT. Among these 8 studies, only 4 (studies 2, 3, 15, and 20) met the criteria for cognitive intervention. However, all studies except for study 8, which did not measure cognitive outcomes, showed significant results. These results also can be explained by the neuroplasticity theory that motor activity can enhance participants’ cognitive performance []. In addition, the WHO recommendations for cognitive intervention for older adults with or without cognitive decline [] support the use of cognitive interventions to prevent cognitive deterioration. Overall, the cognitive intervention designs in these studies yielded statistically significant results, even though only half of these studies (4/20, 20%) met the criteria for cognitive intervention design. Of the 7 studies, only studies 2 and 7 assessed dual-task performance, but neither showed statistical significance.
Although motor activity prompts positive and statistically significant effects as advocated by the WHO, the exact tipping point for achieving physical gains remains unclear. In this review, 7 studies (standard treatment control: study 4; placebo control: studies 10, 14, and 17; active control: studies 16 and 18; dose-response control: study 12) did not meet the criteria for motor activity and did not show any statistically significant physical effects (study 16 did not measure physical effects). More research will be needed to determine the type of motor activity, frequency, session duration, and total volume to start to achieve physical benefits. For cognitive training, 5 studies (studies 4, 10, 12, 14, and 16) met the criteria and showed effects, while study 18, despite it not meeting the criteria, showed statistically significant cognitive gains. Compared to the 5 studies (studies 6, 9, 11, 13, and 19) and 7 studies (studies 1, 2, 3, 7,8, 15, and 20) mentioned earlier, this demonstrates that, in technology-assisted MCT, even if the motor activity does not meet the criteria and does not result in effects, the cognitive component, if met, can still achieve a significant cognitive effect (studies 4, 10, 12, 14, and 16). In addition, these 5 studies (studies 4, 10, 12, 14, and 16) also support the WHO recommendation that “cognitive interventions should be provided to older adults, regardless of their cognitive status, to decrease their deterioration in cognitive functions” [].
Relationship Between the Varied Dual-Task Effects and Whether the Motor and Cognitive Components in MCT Were Constructed Based on the ADL and IADL Frameworks
Finally, this review included 4 studies with at least one part of the intervention (motor or cognitive) designed based on an ADL framework (studies 2, 4, 5, and 15), and 5 studies with at least one part of the intervention (motor or cognitive) designed based on an IADL framework (studies 3, 9, 16, 18, and 20). Among these, studies 3, 5, 15, 16, 18, and 20 did not measure dual-task performance. Study 2 measured dual-task performance but found no statistical significance, while studies 4 and 9 measured dual-task performance and reported statistical significance. Examining the motor and cognitive design of studies 4 and 9, we found that although the motor activity in study 4 was substandard and the cognitive design in study 9 was substandard, the intervention design in study 4 followed the ADL framework for both motor and cognitive parts, while study 9 followed the IADL design for the cognitive part. On the basis of these findings and the small sample sizes in this review, we may tentatively hypothesize that it may be possible to improve participants’ dual-task performance or even achieve statistical significance if the intervention constructs the motor and cognitive components of MCT based on the ADL and IADL frameworks.
Conclusions
This rapid systematic review provides an up-to-date synthesis of evidence for technology-assisted MCT in older adults, addressing a significant knowledge gap in the field. The review found that there is little research on technology-assisted MCT; however, it has been relatively successful in participant inclusion and exclusion for this type of intervention. The review also outlines the most used experimental setups in the included studies. Preliminary results indicate that technology-assisted MCT is highly feasible, with almost no reported adverse events, suggesting it merits further research and replication. In addition, this review analyzed and evaluated the composition and quality of motor activity, cognitive training components, the techniques used, and the effectiveness of these interventions. Most of the included studies showed statistically significant effectiveness. We thoroughly examined the contextual settings of each study (eg, the techniques used and the populations studied) to assess their research outcomes. However, we did not observe any significant differences in the effects of the various techniques applied in these included studies. This review suggests that motor activity and cognitive training that meet the criteria yield statistical significance. However, the exact tipping point for achieving physical or cognitive gains remains unclear. Moreover, given the relatively limited sample sizes in this review, it might be tentatively suggested that to potentially enhance participants’ dual-task performance or even achieve statistical significance, researchers can try to construct the intervention of the motor and cognitive components of MCT based on the ADL and IADL frameworks.
Recommendation
More research will be needed to determine types of motor and cognitive components, frequency, session duration, total volume, and type of technology to start to achieve physical and cognitive benefits from technology-assisted MCT.
Acknowledgments
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Authors' Contributions
The authors contributed to the research and manuscript in the following ways: Y Li, AYML, and JM conceptualized the study. Y Li and JM developed the methodology. Y Li and Y Liu curated the data, were responsible for the software, and analyzed the data. Y Li, AYML, and JM interpreted the results. Y Li drafted the original manuscript. Y Li and JM contributed to the review and editing. AYML and JM supervised the project.
Conflicts of Interest
None declared.
PRISMA 2020 checklist.
DOCX File , 34 KBSynthesis Without Meta-analysis (SWiM) in systematic reviews checklist.
DOCX File , 21 KBOpen Science Framework Registries technology-assisted motor-cognitive training among older adults; a rapid systematic review of randomized controlled trials.
PDF File (Adobe PDF File), 413 KBSearch strategy (updated version in March 2025).
DOCX File , 26 KBSummary table.
DOCX File , 92 KBDetails on statistically significant outcome indicators in each of 3 domains.
DOCX File , 21 KBReferences
- Global issues: population. United Nations. URL: https://www.un.org/en/global-issues/population [accessed 2025-05-14]
- Hertzog C, Kramer AF, Wilson RS, Lindenberger U. Enrichment effects on adult cognitive development: can the functional capacity of older adults be preserved and enhanced? Psychol Sci Public Interest. Oct 2008;9(1):1-65. [CrossRef] [Medline]
- Zanker J, Duque G. Osteoporosis in older persons: old and new players. J Am Geriatr Soc. Apr 2019;67(4):831-840. [CrossRef] [Medline]
- Barnsley J, Buckland G, Chan PE, Ong A, Ramos AS, Baxter M, et al. Pathophysiology and treatment of osteoporosis: challenges for clinical practice in older people. Aging Clin Exp Res. Apr 2021;33(4):759-773. [FREE Full text] [CrossRef] [Medline]
- Faulkner JA, Larkin LM, Claflin DR, Brooks SV. Age-related changes in the structure and function of skeletal muscles. Clin Exp Pharmacol Physiol. Nov 2007;34(11):1091-1096. [FREE Full text] [CrossRef] [Medline]
- Tieland M, Trouwborst I, Clark BC. Skeletal muscle performance and ageing. J Cachexia Sarcopenia Muscle. Mar 2018;9(1):3-19. [FREE Full text] [CrossRef] [Medline]
- Mitchell WK, Williams J, Atherton P, Larvin M, Lund J, Narici M. Sarcopenia, dynapenia, and the impact of advancing age on human skeletal muscle size and strength; a quantitative review. Front Physiol. 2012;3:260. [FREE Full text] [CrossRef] [Medline]
- Hughes ML, Agrigoroaei S, Jeon M, Bruzzese M, Lachman ME. Change in cognitive performance from midlife into old age: findings from the Midlife in the United States (MIDUS) study. J Int Neuropsychol Soc. Sep 2018;24(8):805-820. [FREE Full text] [CrossRef] [Medline]
- Piefke M, Onur Ö, Fink GR. Aging-related changes of neural mechanisms underlying visual-spatial working memory. Neurobiol Aging. Jul 2012;33(7):1284-1297. [CrossRef] [Medline]
- Novotný JS, Gonzalez-Rivas JP, Medina-Inojosa JR, Lopez-Jimenez F, Geda YE, Stokin GB. Investigating cognition in midlife. Alzheimers Dement (N Y). 2021;7(1):e12234. [FREE Full text] [CrossRef] [Medline]
- Inzitari M, Newman AB, Yaffe K, Boudreau R, de Rekeneire N, Shorr R, et al. Gait speed predicts decline in attention and psychomotor speed in older adults: the health aging and body composition study. Neuroepidemiology. 2007;29(3-4):156-162. [FREE Full text] [CrossRef] [Medline]
- Murman DL. The impact of age on cognition. Semin Hear. Aug 2015;36(3):111-121. [FREE Full text] [CrossRef] [Medline]
- Glisky EL, Riddle DR. Changes in cognitive function in human aging. In: Brain Aging: Models, Methods, and Mechanisms. Boca Raton, FL. CRC Press; 2007.
- Risk reduction of cognitive decline and dementia: WHO guidelines. World Health Organization. 2019. URL: https://www.who.int/publications/i/item/risk-reduction-of-cognitive-decline-and-dementia [accessed 2025-05-14]
- Tait JL, Duckham RL, Milte CM, Main LC, Daly RM. Influence of sequential vs. simultaneous dual-task exercise training on cognitive function in older adults. Front Aging Neurosci. 2017;9:368. [FREE Full text] [CrossRef] [Medline]
- Liebherr M, Schubert P, Schiebener J, Kersten S, Haas CT. Dual-tasking and aging—about multiple perspectives and possible implementations in interventions for the elderly. Cogent Psychol. 2016;3(1):1261440. [CrossRef]
- Mack M, Stojan R, Bock O, Voelcker-Rehage C. The association of executive functions and physical fitness with cognitive-motor multitasking in a street crossing scenario. Sci Rep. Jan 13, 2023;13(1):697. [FREE Full text] [CrossRef] [Medline]
- Schmidt GJ, Boechat YE, van Duinkerken E, Schmidt JJ, Moreira TB, Nicaretta DH, et al. Detection of cognitive dysfunction in elderly with a low educational level using a reaction-time attention task. J Alzheimers Dis. 2020;78(3):1197-1205. [CrossRef] [Medline]
- Abo M, Hamaguchi T. Effectiveness of a dual-task intervention involving exercise and vocalized cognitive tasks. J Clin Med. May 17, 2024;13(10):2962. [FREE Full text] [CrossRef] [Medline]
- Brustio PR, Magistro D, Zecca M, Liubicich ME, Rabaglietti E. Fear of falling and activities of daily living function: mediation effect of dual-task ability. Aging Ment Health. Jun 2018;22(6):856-861. [FREE Full text] [CrossRef] [Medline]
- Ewolds H, Broeker L, de Oliveira RF, Raab M, Künzell S. Ways to improve multitasking: effects of predictability after single- and dual-task training. J Cogn. Jan 07, 2021;4(1):4. [FREE Full text] [CrossRef] [Medline]
- Strobach T, Wendt M, Janczyk M. Editorial: multitasking: executive functioning in dual-task and task switching situations. Front Psychol. 2018;9:108. [FREE Full text] [CrossRef] [Medline]
- Ali N, Tian H, Thabane L, Ma J, Wu H, Zhong Q, et al. The effects of dual-task training on cognitive and physical functions in older adults with cognitive impairment; a systematic review and meta-analysis. J Prev Alzheimers Dis. 2022;9(2):359-370. [CrossRef] [Medline]
- He Y, Yang L, Zhou J, Yao L, Pang MY. Dual-task training effects on motor and cognitive functional abilities in individuals with stroke: a systematic review. Clin Rehabil. Jul 2018;32(7):865-877. [CrossRef] [Medline]
- Malik J, Stemplewski R, Maciaszek J. The effect of juggling as dual-task activity on human neuroplasticity: a systematic review. Int J Environ Res Public Health. Jun 09, 2022;19(12):7102. [FREE Full text] [CrossRef] [Medline]
- Li Z, Wang T, Liu H, Jiang Y, Wang Z, Zhuang J. Dual-task training on gait, motor symptoms, and balance in patients with Parkinson's disease: a systematic review and meta-analysis. Clin Rehabil. Nov 2020;34(11):1355-1367. [CrossRef] [Medline]
- Martino Cinnera A, Bisirri A, Leone E, Morone G, Gaeta A. Effect of dual-task training on balance in patients with multiple sclerosis: a systematic review and meta-analysis. Clin Rehabil. Oct 2021;35(10):1399-1412. [CrossRef] [Medline]
- Manser P, de Bruin ED. Making the best out of IT: design and development of exergames for older adults with mild neurocognitive disorder - a methodological paper. Front Aging Neurosci. 2021;13:734012. [FREE Full text] [CrossRef] [Medline]
- Johansson H, Folkerts AK, Hammarström I, Kalbe E, Leavy B. Effects of motor-cognitive training on dual-task performance in people with Parkinson's disease: a systematic review and meta-analysis. J Neurol. Jun 2023;270(6):2890-2907. [FREE Full text] [CrossRef] [Medline]
- Yu D, Li X, He S, Zhu H, Lam FM, Pang MY. The effect of dual-task training on cognitive ability, physical function, and dual-task performance in people with dementia or mild cognitive impairment: a systematic review and meta-analysis. Clin Rehabil. Apr 2024;38(4):443-456. [CrossRef] [Medline]
- Tuena C, Borghesi F, Bruni F, Cavedoni S, Maestri S, Riva G, et al. Technology-assisted cognitive motor dual-task rehabilitation in chronic age-related conditions: systematic review. J Med Internet Res. May 22, 2023;25:e44484. [FREE Full text] [CrossRef] [Medline]
- Chong MS, Sit JW, Karthikesu K, Chair SY. Effectiveness of technology-assisted cardiac rehabilitation: a systematic review and meta-analysis. Int J Nurs Stud. Dec 2021;124:104087. [CrossRef] [Medline]
- Peska DN, Lewis KO. Uniform instruction using web-based, asynchronous technology in a geographically distributed clinical clerkship: analysis of osteopathic medical student participation and satisfaction. J Am Osteopath Assoc. Mar 2010;110(3):135-142. [Medline]
- DiCerbo KE, Shute V, Kim YJ. The future of assessment in technology-rich environments: psychometric considerations. In: Learning, Design, and Technology: An International Compendium of Theory, Research, Practice, and Policy. Cham, Switzerland. Springer; 2023.
- Brivio E, Serino S, Negro Cousa E, Zini A, Riva G, De Leo G. Virtual reality and 360° panorama technology: a media comparison to study changes in sense of presence, anxiety, and positive emotions. Virtual Real. Jul 09, 2020;25(2):303-311. [CrossRef]
- Furszyfer Del Rio DD, Sovacool BK, Martiskainen M. Controllable, frightening, or fun? Exploring the gendered dynamics of smart home technology preferences in the United Kingdom. Energy Res Soc Sci. Jul 2021;77:102105. [CrossRef]
- Ong TL, Ruppert MM, Akbar M, Rashidi P, Ozrazgat-Baslanti T, Bihorac A, et al. Improving the intensive care patient experience with virtual reality-a feasibility study. Crit Care Explor. Jun 2020;2(6):e0122. [FREE Full text] [CrossRef] [Medline]
- Ponsignon F, Derbaix M. The impact of interactive technologies on the social experience: an empirical study in a cultural tourism context. Tour Manag Perspect. Jul 2020;35:100723. [CrossRef]
- Hurling R, Fairley BW, Dias MB. Internet-based exercise intervention systems: are more interactive designs better? Psychol Health. Dec 2006;21(6):757-772. [CrossRef]
- Ouyang F, Zheng L, Jiao P. Artificial intelligence in online higher education: a systematic review of empirical research from 2011 to 2020. Educ Inf Technol. Feb 26, 2022;27(6):7893-7925. [CrossRef]
- Sallam M, Salim NA, Barakat M, Al-Tammemi AB. ChatGPT applications in medical, dental, pharmacy, and public health education: a descriptive study highlighting the advantages and limitations. Narra J. Apr 2023;3(1):e103. [FREE Full text] [CrossRef] [Medline]
- Zhai X, Chu X, Chai CS, Jong MS, Istenic A, Spector M, et al. A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity. Apr 20, 2021;2021. [CrossRef]
- Bennell K, Nelligan RK, Schwartz S, Kasza J, Kimp A, Crofts SJ, et al. Behavior change text messages for home exercise adherence in knee osteoarthritis: randomized trial. J Med Internet Res. Sep 28, 2020;22(9):e21749. [FREE Full text] [CrossRef] [Medline]
- Canan CE, Waselewski ME, Waldman AL, Reynolds G, Flickinger TE, Cohn WF, et al. Long term impact of PositiveLinks: clinic-deployed mobile technology to improve engagement with HIV care. PLoS One. 2020;15(1):e0226870. [FREE Full text] [CrossRef] [Medline]
- Collado-Mateo D, Lavín-Pérez AM, Peñacoba C, Del Coso J, Leyton-Román M, Luque-Casado A, et al. Key factors associated with adherence to physical exercise in patients with chronic diseases and older adults: an umbrella review. Int J Environ Res Public Health. Mar 19, 2021;18(4):2023. [FREE Full text] [CrossRef] [Medline]
- Pudkasam S, Feehan J, Talevski J, Vingrys K, Polman R, Chinlumprasert N, et al. Motivational strategies to improve adherence to physical activity in breast cancer survivors: a systematic review and meta-analysis. Maturitas. Oct 2021;152:32-47. [CrossRef] [Medline]
- Ollermark K. Designing for body awareness: exploring the interaction between screen and participant in pre-recorded online workouts. Malmö University. 2022. URL: https://www.diva-portal.org/smash/get/diva2:1676394/FULLTEXT02 [accessed 2025-05-14]
- Woessner MN, Tacey A, Levinger-Limor A, Parker AG, Levinger P, Levinger I. The evolution of technology and physical inactivity: the good, the bad, and the way forward. Front Public Health. 2021;9:655491. [FREE Full text] [CrossRef] [Medline]
- Gao L, Zhang G, Yu B, Qiao Z, Wang J. Wearable human motion posture capture and medical health monitoring based on wireless sensor networks. Measurement. Dec 2020;166:108252. [CrossRef]
- Rana M, Mittal V. Wearable sensors for real-time kinematics analysis in sports: a review. IEEE Sensors J. Jan 15, 2021;21(2):1187-1207. [CrossRef]
- Roggio F, Ravalli S, Maugeri G, Bianco A, Palma A, Di Rosa M, et al. Technological advancements in the analysis of human motion and posture management through digital devices. World J Orthop. Jul 18, 2021;12(7):467-484. [FREE Full text] [CrossRef] [Medline]
- Minardi HA, Ritter S. Recording skills practice on videotape can enhance learning - a comparative study between nurse lecturers and nursing students. J Adv Nurs. Jun 1999;29(6):1318-1325. [CrossRef] [Medline]
- Yang K, Perez M, Hubert N, Hossu G, Perrenot C, Hubert J. Effectiveness of an integrated video recording and replaying system in robotic surgical training. Ann Surg. Mar 2017;265(3):521-526. [CrossRef] [Medline]
- Chen EH, Bailey DH. Dual-task studies of working memory and arithmetic performance: a meta-analysis. J Exp Psychol Learn Mem Cogn. Mar 2021;47(2):220-233. [CrossRef] [Medline]
- Liederman J. Subtraction in addition to addition: dual task performance improves when tasks are presented to separate hemispheres. J Clin Exp Neuropsychol. Oct 1986;8(5):486-502. [CrossRef] [Medline]
- Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev. Mar 29, 2021;10(1):89. [FREE Full text] [CrossRef] [Medline]
- Campbell M, McKenzie JE, Sowden A, Katikireddi SV, Brennan SE, Ellis S, et al. Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline. BMJ. Jan 16, 2020;368:l6890. [FREE Full text] [CrossRef] [Medline]
- Tricco AC, Langlois EV, Straus SE. Rapid reviews to strengthen health policy and systems: a practical guide. World Health Organization. 2017. URL: https://iris.who.int/bitstream/handle/10665/258698/9789241512763-eng.pdf [accessed 2025-05-14]
- Hartling L, Guise JM, Hempel S, Featherstone R, Mitchell MD, Motu'apuaka ML, et al. Fit for purpose: perspectives on rapid reviews from end-user interviews. Syst Rev. Mar 17, 2017;6(1):32. [FREE Full text] [CrossRef] [Medline]
- Kazi MR, Chowdhury N, Chowdhury MM, Turin TC. Conducting a rapid review for quick turnaround knowledge synthesis. Health Prim Care. 2021;5. [CrossRef]
- Technology-assisted motor-cognitive training among older adults: a rapid systematic review. OSF Registries. Jul 31, 2024. URL: https://osf.io/5srcq [accessed 2025-05-14]
- Amir-Behghadami M, Janati A. Population, Intervention, Comparison, Outcomes and Study (PICOS) design as a framework to formulate eligibility criteria in systematic reviews. Emerg Med J. Jun 2020;37(6):387. [CrossRef] [Medline]
- Zabor EC, Kaizer AM, Hobbs BP. Randomized controlled trials. Chest. Jul 2020;158(1S):S79-S87. [FREE Full text] [CrossRef] [Medline]
- Feeley N, Cossette S. Pilot studies for randomized clinical trials. In: Henly SJ, editor. Routledge International Handbook of Advanced Quantitative Methods in Nursing Research. London, UK. Routledge; 2015:199-212.
- Tikka C, Verbeek J, Ijaz S, Hoving JL, Boschman J, Hulshof C, et al. Quality of reporting and risk of bias: a review of randomised trials in occupational health. Occup Environ Med. Sep 2021;78(9):691-696. [FREE Full text] [CrossRef] [Medline]
- WHO Guidelines Approved by the Guidelines Review Committee. Geneva, Switzerland. World Health Organization; 2020.
- Menengi Ç KN, Yeldan İ, Çınar N, Şahiner T. Effectiveness of motor-cognitive dual-task exercise via telerehabilitation in Alzheimer's disease: an online pilot randomized controlled study. Clin Neurol Neurosurg. Dec 2022;223:107501. [CrossRef] [Medline]
- Jäggi S, Wachter A, Adcock M, de Bruin ED, Möller JC, Marks D, et al. Feasibility and effects of cognitive-motor exergames on fall risk factors in typical and atypical Parkinson's inpatients: a randomized controlled pilot study. Eur J Med Res. Jan 16, 2023;28(1):30. [FREE Full text] [CrossRef] [Medline]
- Kwan RY, Liu JY, Fong KN, Qin J, Leung PK, Sin OS, et al. Feasibility and effects of virtual reality motor-cognitive training in community-dwelling older people with cognitive frailty: pilot randomized controlled trial. JMIR Serious Games. Aug 06, 2021;9(3):e28400. [FREE Full text] [CrossRef] [Medline]
- Altorfer P, Adcock M, de Bruin ED, Graf F, Giannouli E. Feasibility of cognitive-motor exergames in geriatric inpatient rehabilitation: a pilot randomized controlled study. Front Aging Neurosci. 2021;13:739948. [FREE Full text] [CrossRef] [Medline]
- Manser P, Poikonen H, de Bruin ED. Feasibility, usability, and acceptance of "Brain-IT"-a newly developed exergame-based training concept for the secondary prevention of mild neurocognitive disorder: a pilot randomized controlled trial. Front Aging Neurosci. 2023;15:1163388. [FREE Full text] [CrossRef] [Medline]
- Fishbein P, Hutzler Y, Ratmansky M, Treger I, Dunsky A. A preliminary study of dual-task training using virtual reality: influence on walking and balance in chronic poststroke survivors. J Stroke Cerebrovasc Dis. Nov 2019;28(11):104343. [CrossRef] [Medline]
- Kannan L, Vora J, Bhatt T, Hughes SL. Cognitive-motor exergaming for reducing fall risk in people with chronic stroke: a randomized controlled trial. NeuroRehabilitation. 2019;44(4):493-510. [CrossRef] [Medline]
- Uematsu A, Tsuchiya K, Fukushima H, Hortobágyi T. Effects of motor-cognitive dual-task standing balance exergaming training on healthy older adults' standing balance and walking performance. Games Health J. Aug 2023;12(4):302-309. [CrossRef] [Medline]
- Liao YY, Chen IH, Lin YJ, Chen Y, Hsu WC. Effects of virtual reality-based physical and cognitive training on executive function and dual-task gait performance in older adults with mild cognitive impairment: a randomized control trial. Front Aging Neurosci. 2019;11:162. [FREE Full text] [CrossRef] [Medline]
- Schoene D, Valenzuela T, Toson B, Delbaere K, Severino C, Garcia J, et al. Interactive cognitive-motor step training improves cognitive risk factors of falling in older adults - a randomized controlled trial. PLoS One. 2015;10(12):e0145161. [FREE Full text] [CrossRef] [Medline]
- Forte R, Trentin C, Tocci N, Lucia S, Aydin M, Di Russo F. Motor-cognitive exercise with variability of practice and feedback improves functional ability and cognition in older individuals. Aging Clin Exp Res. Nov 2023;35(11):2797-2806. [CrossRef] [Medline]
- Pelosin E, Ponte C, Putzolu M, Lagravinese G, Hausdorff JM, Nieuwboer A, et al. Motor-cognitive treadmill training with virtual reality in Parkinson's disease: the effect of training duration. Front Aging Neurosci. 2021;13:753381. [FREE Full text] [CrossRef] [Medline]
- Eggenberger P, Theill N, Holenstein S, Schumacher V, de Bruin ED. Multicomponent physical exercise with simultaneous cognitive training to enhance dual-task walking of older adults: a secondary analysis of a 6-month randomized controlled trial with 1-year follow-up. Clin Interv Aging. 2015;10:1711-1732. [FREE Full text] [CrossRef] [Medline]
- Delbroek T, Vermeylen W, Spildooren J. The effect of cognitive-motor dual task training with the biorescue force platform on cognition, balance and dual task performance in institutionalized older adults: a randomized controlled trial. J Phys Ther Sci. Jul 2017;29(7):1137-1143. [FREE Full text] [CrossRef] [Medline]
- Hagovska M, Nagyova I. The transfer of skills from cognitive and physical training to activities of daily living: a randomised controlled study. Eur J Ageing. Jun 2017;14(2):133-142. [FREE Full text] [CrossRef] [Medline]
- Park JS, Jung YJ, Lee G. Virtual reality-based cognitive-motor rehabilitation in older adults with mild cognitive impairment: a randomized controlled study on motivation and cognitive function. Healthcare (Basel). Sep 11, 2020;8(3):335. [FREE Full text] [CrossRef] [Medline]
- Villa-Sánchez B, Gandolfi M, Emadi Andani M, Valè N, Rossettini G, Polesana F, et al. Placebo effect on gait: a way to reduce the dual-task cost in older adults. Exp Brain Res. Jun 2023;241(6):1501-1511. [CrossRef] [Medline]
- Buele J, Avilés-Castillo F, Del-Valle-Soto C, Varela-Aldás J, Palacios-Navarro G. Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial. J Neuroeng Rehabil. Aug 01, 2024;21(1):130. [FREE Full text] [CrossRef] [Medline]
- Zak M, Sikorski T, Michalska A, Sztandera P, Szczepanowska-Wolowiec B, Brola W, et al. The effects of physiotherapy programmes, aided by virtual reality solutions, on balance in older women: a randomised controlled trial. J Clin Med. Oct 28, 2024;13(21):6462. [FREE Full text] [CrossRef] [Medline]
- Kwan RY, Liu J, Sin OS, Fong KN, Qin J, Wong JC, et al. Effects of virtual reality motor-cognitive training for older people with cognitive frailty: multicentered randomized controlled trial. J Med Internet Res. Sep 11, 2024;26:e57809. [FREE Full text] [CrossRef] [Medline]
- Eisenstein C. Implementing and evaluating co-design: a step-by-step toolkit. New Philanthropy Capital. 2019. URL: https://policycommons.net/artifacts/1572973/implementing-and-evaluating-co-design-a-step-by-step-toolkit-contents/2262752/ [accessed 2025-05-14]
- Prabaswari AD, Mahfudhi MICCC. Comparative analysis of mental workloads for disruption technicians and new installation technicians using the NASA-TLX method (case study: PT Telkom Akses Kandatel Sleman). AIP Conf Proc. 2023:050017c. [FREE Full text] [CrossRef]
- Grier RA, Bangor A, Kortum P, Peres SC. The System Usability Scale: beyond standard usability testing. Proc Hum Factors Ergon Soc Annu Meet. Sep 30, 2013;57(1):187-191. [CrossRef]
- Bird M, McGillion M, Chambers EM, Dix J, Fajardo CJ, Gilmour M, et al. A generative co-design framework for healthcare innovation: development and application of an end-user engagement framework. Res Involv Engagem. Mar 01, 2021;7(1):12. [FREE Full text] [CrossRef] [Medline]
- Maher LM, Hayward B, Hayward P, Walsh C. Increasing sustainability in co-design projects: a qualitative evaluation of a co-design programme in New Zealand. Patient Exp J. Jul 26, 2017;4(2):44-52. [CrossRef]
- Tay BS, Cox DN, Brinkworth GD, Davis A, Edney SM, Gwilt I, et al. Co-design practices in diet and nutrition research: an integrative review. Nutrients. Oct 14, 2021;13(10):3593. [FREE Full text] [CrossRef] [Medline]
- Shanyinde M, Pickering RM, Weatherall M. Questions asked and answered in pilot and feasibility randomized controlled trials. BMC Med Res Methodol. Aug 16, 2011;11:117. [FREE Full text] [CrossRef] [Medline]
- Boksem MA, Meijman TF, Lorist MM. Effects of mental fatigue on attention: an ERP study. Brain Res Cogn Brain Res. Sep 2005;25(1):107-116. [CrossRef] [Medline]
- Eysenbach G. The law of attrition. J Med Internet Res. Mar 31, 2005;7(1):e11. [FREE Full text] [CrossRef] [Medline]
- Gustavson K, von Soest T, Karevold E, Røysamb E. Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study. BMC Public Health. Oct 29, 2012;12:918. [FREE Full text] [CrossRef] [Medline]
- Šlosar L, Voelcker-Rehage C, Paravlić AH, Abazovic E, de Bruin ED, Marusic U. Combining physical and virtual worlds for motor-cognitive training interventions: position paper with guidelines on technology classification in movement-related research. Front Psychol. 2022;13:1009052. [FREE Full text] [CrossRef] [Medline]
- Varela-Vásquez LA, Minobes-Molina E, Jerez-Roig J. Dual-task exercises in older adults: a structured review of current literature. J Frailty Sarcopenia Falls. Jun 2020;5(2):31-37. [FREE Full text] [CrossRef] [Medline]
- Pereira Oliva HN, Mansur Machado FS, Rodrigues VD, Leão LL, Monteiro-Júnior RS. The effect of dual-task training on cognition of people with different clinical conditions: an overview of systematic reviews. IBRO Rep. Dec 2020;9:24-31. [FREE Full text] [CrossRef] [Medline]
- Wollesen B, Voelcker-Rehage C. Training effects on motor–cognitive dual-task performance in older adults. Eur Rev Aging Phys Act. Feb 24, 2013;11(1):5-24. [CrossRef]
- Hötting K, Röder B. Beneficial effects of physical exercise on neuroplasticity and cognition. Neurosci Biobehav Rev. Nov 2013;37(9 Pt B):2243-2257. [CrossRef] [Medline]
Abbreviations
| ADL: activities of daily living |
| IADL: instrumental activities of daily living |
| MCT: motor-cognitive training |
| MeSH: Medical Subject Headings |
| NASA-TLX: NASA Task Load Index |
| PD: Parkinson disease |
| PICOS: population, intervention, comparator, outcome, and study design |
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
| RCT: randomized controlled trial |
| SUS: System Usability Scale |
| SWiM: Synthesis Without Meta-analysis |
| VR: virtual reality |
| WHO: World Health Organization |
Edited by A Coristine; submitted 06.10.24; peer-reviewed by M Takemi, M Gasmi, F Bruni; comments to author 16.12.24; revised version received 25.02.25; accepted 18.04.25; published 03.06.25.
Copyright©Yaqin Li, Yaqian Liu, Angela YM Leung, Jed Montayre. Originally published in JMIR Serious Games (https://games.jmir.org), 03.06.2025.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on https://games.jmir.org, as well as this copyright and license information must be included.

