記住我
Neurological disorders stand as the primary cause of global disability []. Within this category, Parkinson disease (PD) is exhibiting the most rapid increase in disability, fatalities, and prevalence, with an anticipated doubling within the next 2 decades []. In Europe, the current PD population exceeds 1.2 million, contributing to an annual economic burden of €13.9 billion (US $15.5 billion) []. The annual cost per individual rises with the severity of the condition, while nonmotor symptoms significantly contribute to hospitalizations and institutionalizations. Beyond the challenging aspects of PD itself, individuals with PD grapple with notable comorbidities and a high frequency of falls []. Aging is correlated with an accelerated motor progression of the disease; reduced responsiveness to levodopa; heightened severity in gait, posture, and cognitive impairment; and an increased likelihood of developing dementia [].
With the aging of the global population, the prevalence of PD is on the rise, making it an increasingly significant public health concern. Effective management and rehabilitation strategies are essential to mitigate the debilitating effects of this condition and to enhance the functional independence of older individuals living with PD.
From a clinical perspective, the top priorities in PD management include the delay and prevention of disability []. Despite symptomatic relief through medical, surgical, and rehabilitative interventions, older individuals with PD experience a persistent deterioration in disability, marked by a decline in quality of life, diminished functional mobility, decreased performance in daily activities, and worsening neurological impairments. Guidelines suggest early initiation of physical therapy at the onset of the disease for addressing functional decline []. However, the evidence regarding its effectiveness in delaying symptom onset or reducing severity is not robust. Recognizing the crucial role of gait and balance in daily function has significant clinical implications, indicating impending disability and necessitating a reassessment of management strategies. The identification of new and effective interventions for symptoms contributing to significant disability is a key priority []. In particular, there is a growing body of evidence indicating that exercise and physical activity interventions can slow the rate of functional mobility decline, ultimately improving quality of life, as tertiary prevention solutions [].
Over the years, advances in technology have revolutionized the field of health care, offering innovative tools and interventions for the diagnosis, monitoring, and treatment of various medical conditions. In recent decades, there has been a growing interest in harnessing the potential of technology to aid in the rehabilitation of patients with PD, particularly in the older population. This shift reflects a broader trend toward incorporating digital solutions into health care, driven by the desire to optimize therapeutic outcomes and improve the overall well-being of patients.
For this reason, recent research [-] indicates that balance training delivered through technology leads to performance enhancements that align with noticeable neurobiological changes in the cerebral cortex [,]. This underscores the encouraging potential of technological interventions in aiding individuals with PD in managing balance and other motor disorders.
This paper presents a systematic review that critically examines the existing body of literature on the use of technology in the rehabilitation of older patients with PD. By synthesizing current evidence, we aim to provide insights into the state of the field, identify gaps in knowledge, and offer recommendations for future research and clinical practice.
In this comprehensive review, we will explore a wide range of technological applications, including wearable devices, telerehabilitation platforms, virtual reality systems, and robotics, among others. We will evaluate the effectiveness, usability, and safety of these technologies in improving motor function, balance, mobility, and overall quality of life in older patients with PD. Furthermore, we will consider the potential challenges and ethical implications associated with the integration of technology into rehabilitation protocols for this vulnerable population.
The methodology of this systematic review was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines ( []) [], with the main aim of analyzing the use of technology in the rehabilitation of older patients with PD.
We used the PICO (Population, Intervention, Comparator, Outcome) framework as follows:
P: Older patients with PDI: Rehabilitation program with technologyC: Control group that receives a traditional rehabilitation programO: The efficacy of the treatmentA systematic review of the literature was conducted in September 2023. The data were collected from PubMed, Embase, Scopus, CINAHL, and Web of Sciences, analyzing manuscripts and papers of the last 5 years (from September 2018 to September 2023) in order to obtain the latest evidence in the field. The inclusion criteria were as follows: (1) randomized controlled trial, (2) PD in people aged 65 years and older, and (3) use of technology in the rehabilitation training in the older population. Systematic and narrative reviews were excluded. Based on consultation with the multidisciplinary research team, technological intervention studies were searched using the following search terms and the combination thereof: Parkinson, rehabilitation, technology, old*, elder*, effectiveness, randomized control trial. The detailed search strategy used in each database is reported in . After the preliminary search, 190 papers resulted from PubMed, 71 from Embase, 87 from Scopus, 36 from CINAHL, and 1829 from Web of Sciences. Since the CINAHL database was consulted only after the first round of searches and after the duplicate analysis, a different filtering of the results was chosen. In fact, in order to narrow down the number of results, we looked for papers containing the term “randomized control trial” in the title. The findings were analyzed and screened by 4 experts of the team: a bioengineer, a clinical neurologist, a psychologist, and a physiotherapist. Rayyan software has been used in order to remove duplicates. Identified studies were independently reviewed for eligibility in a 2-step process; a first screening was performed by 4 independent authors (EM, GP, RB, and MB) based on the title and abstract. Then, full texts were retrieved for a second screening by the same 4 authors. At both stages, disagreements among reviewers were resolved by consensus and discussed with the other 2 authors (GA and VDD). After these steps, 25 papers resulted from selected databases. An additional researcher, with a background in biomedical engineering, confirmed the accuracy of the papers’ selection and screened for any possible omission. After the screening based on the inclusion or exclusion criteria, conducted on the full-text papers, 14 studies were selected. shows the flowchart search strategy applied. Data extraction, performed by 2 independent raters (EM and MB) included full reference details, sample size, study population details, including gender and mean age, type of technology used, outcomes, and results.
Figure 1. Descriptive analysis of the included clinical studies. Quality appraisal of included studies was carried out by applying the PEDro scale suggested for evidence-based reviews []. The final score was settled when 3 authors reached agreement after repeated review and analysis.
Data SynthesisA descriptive synthesis of the data was performed. The data were grouped and analyzed based on the types of technological interventions used and their reported outcomes. The main areas of focus included cognitive and physical functioning, specifically gait and balance performance. The synthesis aimed to identify common findings and trends across the studies, highlighting the efficacy of technological interventions compared with traditional rehabilitation methods. No meta-analysis was conducted due to the heterogeneity of the study designs, interventions, and outcome measures.
A total of 14 papers were included [-]. Findings reported in this section are organized under macroconcept areas of interest.
reports the quality evaluation of 14 population-based studies. In particular, the PEDro score ranged from 6 to a maximum of 8. The descriptive analysis of the technological intervention and devices used in the studies selected is shown in .
Table 1. Scores of methodological quality assessment of the included studies.PEDroEligibilityRandomized allocationConcealed allocationBaseline comparabilityBlinded subjectBlinded therapistsBlinded ratersKey outcomesIntention to treatComparison between groupsPrecision and variabilityScoreDel Din et al []YaYYYNbNNYYYY8/11Jäggi et al []YYYYNNNYNYN6/11Lau et al []YYYYNNNYNYN6/11Kim et al []YYYYNNNYYYN7/11Maranesi et al []YYYYNNYYNYN7/11Gryfe et al []YYYYNNNYYYN7/11Feng et al []YYYYNNYYNYN7/11Cikajlo and Peterlin Potisk []YYYYNNNYNYN6/11Capecci et al []YYYYNNYYNYN7/11Spina et al []YYYYNNYYNYN7/11Pazzaglia et al []YYYYNNYYNYN7/11Yuan et al []YYYYNNYYNYN7/11Calabrò et al []YYYYNNYYYYN8/11Alagumoorthi et al []YYYYNNYYYYN8/11aY: yes.
bN: No.
General Characteristics of the Study PopulationAll the studies were focused on older people with PD with a mean age of 69.8 (SD 14.4) years for the technological intervention group and mean age of 70.3 (SD 7.3) years in the control group. The number of participants involved in all the studies is 578, ranging from a minimum sample of 18 patients to a maximum of 128. There were 297 males and 281 females.
Descriptive Analysis and Outcome Measuresshows the characteristics of the included studies. All studies evaluated the impact of technological interventions on physical and cognitive domains. Regarding evaluated domains, cognitive functioning was assessed by 4 studies [,,,] and physical functioning was assessed by 13 studies [,-], including gait assessment [,-,-,,] in terms of gait speed or gait performance, falls and fear of falling evaluation [,,,], and balance estimation [-,,,,]. Examining the technology employed, there is a notable preference for using treadmills coupled with virtual reality and exergames [,,,]. In addition, numerous studies [,,,,] incorporate sensitive pressure platforms, both static and dynamic, often in conjunction with nonimmersive virtual exercises. However, for the specific pathology under consideration, the use of exoskeletons [] or gait robots [] appears to be more restricted. It is worth noting that nearly all studies consistently incorporate virtual reality—whether immersive with visors or caves, or nonimmersive through exergames. This technology appears to have effects not only on the cognitive aspect but also on the physical domain. The analysis of the results clearly indicates that, in terms of gait and balance performance, the technological intervention outperforms the traditional approach, irrespective of the specific technology employed. However, from a cognitive perspective, the improvement is limited.
Table 2. Descriptive analysis of the included clinical studies.aEG: experimental group.
bCG: control group.
cPD: Parkinson disease.
dHY: Hoehn & Yahr.
eFRA: Falls Rate and Activity Exposure Index.
fMCI: mild cognitive impairment.
gVR: virtual reality.
hSUS: System Usability Scale.
iNASA TLX: NASA Task Load Index.
jRTT: reaction time test.
kD-KEFS: Delis-Kaplan Executive Function System; color-word interference test.
lTMT: Trail Making Test A and B.
mSPPB: Short Physical Performance Battery.
nTUG: time up and go.
o5×StS: 5 times sit to stand.
p6MWT: 6-minute walking test.
qMoCA: Montreal Cognitive Assessment.
rSDMT: Symbol Digit Modality Test.
s10mWT: 10-minute walking test.
tBBS: Berg Balance Scale.
uMDS-UPDRS: Movement Disorder Society-sponsored version of the Unified Parkinson’s Disease Rating Scale.
vKFES-I: Korean version of Falls Efficacy Scale-International.
wNFOGQ: New Freezing of Gait Questionnaire.
xPOMA: Tinetti Performance Oriented Mobility Assessment.
ySCOPA-COG: Scales for Outcomes in Parkinson’s Disease-Cognition.
zFGA: Functional Gait Assessment.
aaPDQ-39: 39-item Parkinson’s Disease Questionnaire.
abDGI: Dynamic Gait Index.
acDASH: Disabilities of the Arm, Shoulder and Hand.
adSF-36: 36-item Short Form.
aeMFES: Modified Falls Efficacy Scale.
afMDRT: Multi-Directional Reach Test.
agGQI: Gait Quality Index.
This systematic review seeks to shed light on the evolving landscape of technology-assisted rehabilitation for older people with PD. Delving into the available evidence, we assess how technology can serve as a valuable complement to conventional therapy, offering new ways to optimize care and improve outcomes in this growing patient demographic. In particular, the included studies evaluated the impact of technological interventions on physical and cognitive domains. Cognitive functioning was assessed in 4 studies, while physical functioning, including gait, falls, and balance, was assessed in 13 studies. Technologies used included treadmills with virtual reality, exergames, and sensitive pressure platforms. Exoskeletons and gait robots were less commonly used. Most studies incorporated virtual reality, either immersive or nonimmersive. The results indicate that technological interventions significantly improve gait and balance performance compared with traditional methods, though cognitive improvements were limited.
PD poses a serious burden on patients, carers, families, health care providers, and health authorities globally. Within the relevant unmet need in the management of PD [], identifying preventive strategies, particularly tertiary, to mitigate severe progression and ensure an adequate quality of life for older patients is one of the most felt needs, with the final aim of slowing disease progression, enhancing the long-term quality of life, and reducing the costs associated with PD, as the majority of expenses occur in advanced stages.
From our analysis, it seems that including technology into a physical intervention can constitute a driver for ensuring the adherence and compliance to rehabilitation trainings. In particular, our analysis reveals an overall improvement in the physical status and outcomes related to disease severity, even if a not clear improvement in cognitive status and quality of life was observed. This result may suggest the need of conducting longer trials to collect evidence on the impact of rehabilitative interventions with technology also in the long term. Moreover, even if the adherence to rehabilitation training is high in hospital facilities, this should be complemented and sustained with training at home to stimulate compliance to physical exercise, considering that patients with PD should remain active as long as possible to counteract the disease progression. Additionally, digital solutions can be a viable option to support the older patients at home by coaching them in an interactive and engaging way, as already demonstrated by numerous evidence in the field [].
In fact, although in a different context, our analysis has shown that the most engaging interventions involved virtual reality technology, which appears to be the most promising tool for positively impacting cognitive domains due to its highly interactive features. This is in line with recent findings that highlight that virtual reality technology has a particularly promising tool for investigating and rehabilitating gait and balance impairments in people with PD by enabling users to engage in an enriched and highly personalized complex environment [].
The inclusion of technology and virtual reality into rehabilitative training imposes to stress the attention to assessing the usability and accessibility of such technologies by including the patients-in-the-loop since the design of the solutions in order to be suitable and to not compromise the appropriate use. At this purpose, even if there is a plethora of studies and disciplines that underline the needs of involving older adults and vulnerable user groups in the design process, also with a specific focus on age-related conditions such as dementia [], there has been limited exploration of how individuals with PD can actively participate in the design process [], despite the fact that the PD population represents an intriguing user group for design investigation due to the intricate and individual nature of the condition that includes physical and cognitive symptoms, with fluctuations in severity, while dealing with emotional challenges related to social stigma and embarrassment associated with their condition [].
However, this systematic review has its limitations. The low number of studies and their heterogeneity do not favor valid and generalizable conclusions, but this very limitation shows that, despite the good promises, there is still a need to experiment with technological interventions and, in particular, with virtual reality, in the rehabilitation of people with PD. Moreover, all the studies reported show more or less significantly positive results: this aspect is typical of scientific publications, in which there is a tendency to publish this kind of study to the detriment of those with negative results. For the purposes of research into the implementation of new technologies for the treatment of patients with PD, it is very important to know and take into account even those studies that did not produce the desired results, so that lessons should not be learned again.
The integration of technology into PD rehabilitation holds the promise of enhancing the efficacy and accessibility of interventions, addressing the unique challenges faced by older individuals, and facilitating personalized, patient-centered care. Future challenges of sociotechnical interventions should be focused on unmet needs of the older population with PD by combining a multidisciplinary, multicomponent, and personalized approach and addressing challenges related to health literacy, availability of physical and psychological services, and the stigma associated with PD [].
ConclusionsIn summary, this systematic review seeks to shed light on the evolving landscape of technology-assisted rehabilitation for older individuals with PD. The integration of technology into PD rehabilitation holds the promise of enhancing the efficacy and accessibility of interventions, addressing the unique challenges faced by older individuals, and facilitating personalized patient-centered care.
None declared.
Edited by T de Azevedo Cardoso, T Leung; submitted 06.10.23; peer-reviewed by L Wang; comments to author 30.11.23; revised version received 14.12.23; accepted 06.06.24; published 09.09.24.
©Roberta Bevilacqua, Marco Benadduci, Federico Barbarossa, Giulio Amabili, Valentina Di Donna, Clotilda Martella, Giuseppe Pelliccioni, Giovanni Renato Riccardi, Elvira Maranesi. Originally published in JMIR Serious Games (https://games.jmir.org), 09.09.2024.
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.
留言 (0)