1. Introduction
Mild cognitive impairment (MCI) is a mild neurocognitive disorder characterized by a subjective and objective decline from a previous level of functioning in one or more of the six cognitive domains that does not substantially interfere with the instrumental activities of daily living and does not occur in the context of delirium or other psychological disorders [
1]. The key criteria that distinguish MCI from dementia are preservation of independence in functional abilities and lack of significant impairment in social or occupational functioning. In addition, MCI subtypes are sometimes defined on the basis of the presence or absence of memory difficulties and the number of affected cognitive domains [
2]. The estimated prevalence of MCI ranges from 18.8% to 28.3% in people over 60 years of age, with people affected by this condition being at greater risk of developing dementia than the general population and with annual progression rates between 10% and 15% [
3,
4,
5].
There are several risk factors that increase the probability of developing MCI. While age is the strongest risk factor, other well-established factors include male sex; the presence of the apolipoprotein E allele; a family history of cognitive impairment; and vascular risk factors such as hypertension, hyperlipidemia, coronary artery disease, stroke, and other chronic medical conditions, such as chronic obstructive pulmonary disease, depression, and diabetes mellitus [
6,
7,
8]. Currently, there are no available disease-modifying therapies for MCI, although symptomatic and supportive treatments have proven to be valuable [
9]. In fact, among the risk factors, sedentary behavior and low physical activity might play a role in the transition from MCI to dementia. Physical activity and exercise have been shown to improve not only global cognition but also several noncognitive outcomes, such as disability, falls, and neuropsychiatric symptoms, in participants affected by dementia [
10,
11].
In this context, COGNIVITRA is an information and communications technology (ICT)-based solution that targets people ≥50 years old at risk for cognitive impairment, at risk of worsening cognitive impairment or with MCI [
12,
13]. Its aim is to support cognitive vitality training at home, extending cognitive and physical stimulation programs performed in hospital or clinical environments to a community setting (e.g., home care center or patient home). It integrates both supporting cognitive and physical exercises (dual-task training) [
14] through web-based tools and movement sensors, building a centralized platform that facilitates the interface and communication between patients and care providers. The objective of the present study was to determine the implementation of this dual-task training system and analyze its usability, the impact of its implementation strategy on the population’s access to specialized cognitive care, and its economic impact.
2. Materials and Methods
COGNIVITRA is an application aimed at delaying cognitive decline through active engagement in mental, physical, and social activities. Its primary goal is to improve cognitive performance and physical well-being in individuals at risk of cognitive impairment. Unlike traditional programs that require commuting, COGNIVITRA eliminates the need for extensive travel, reducing the burden on both patients and caregivers. The application integrates cognitive and physical exercises, featuring a user-friendly interface with a virtual coach for a seamless user experience. Building on the success of the Cogweb project [
15], COGNIVITRA includes more than 100 cognitive training exercises tested for usability across diverse age groups and disease models. Additionally, it introduces new content for cognitive and proprioceptive stimulation, incorporating features such as automatic hit/miss rate detection and adaptive exercise difficulty. COGNIVITRA utilizes an interface and advanced natural interaction (IANI)-friendly interface, emphasizing embodied conversational agents, environment-based interaction modalities, and multimodal interaction strategies. Overall, it represents a comprehensive solution to enhance cognitive health and physical well-being in individuals vulnerable to cognitive decline [
13].
2.1. Study Design
The inclusion criteria were people living independently; aged ≥50 years; being either at risk for cognitive impairment or worsening cognitive impairment or with MCI, which was measured with the Mini Mental State Examination (MMSE); and having both digital literacy and internet access. The exclusion criteria included taking drugs that could affect cognition within the previous three months; alcohol or substance abuse in the previous two years; and having any other condition that, in the opinion of the investigator, might have affected the study. All participants provided informed consent, the study was approved by the Ethics Committee of Fundació Sant Joan de Déu, and all procedures were performed in accordance with the Declaration of Helsinki and its later amendments.
The intervention plan took place through the deployment of a multicenter study with a total duration of 12 weeks (6 mandatory + 6 voluntary), with an expected total sample size of 20 professionals, 90 patients and 20 caregivers. The study consisted of the following two settings: a clinical setting and a home setting. While the clinical setting sessions included the activities conducted at the clinical institutions that were supervised by a therapist, the home sessions were individual sessions in which COGNIVITRA was used at home without supervision while doing the session (
Figure 1). Within these studies, the usability and user experience (UX), workflow and impact, and overall effectiveness were evaluated. With respect to the usability and UX, the interaction between the users and the COGNIVITRA interface was analyzed, considering the parameters of the user interface, UX and overall usability of the system. In the case of the workflow and impact, tests of the utility and impact of the system in users’ lives were carried out, focusing on the workflow of the professional when handling and supervising activities, as well as its impact on both patients and caregivers. Finally, overall effectiveness was used to analyze the global effectiveness of the COGNIVITRA program, which was centered on the impact of the use of the system at both the institutional and public health levels. The schedule is summarized in
Table 1.
2.2. Study Variables and Data Collection
The main objective was the implementation of a system for a dual-task training program (COGNIVITRA). The secondary objectives included the assessment of the usability and UX of the system’s features among the major subgroups of target users, the impact of its implementation strategy on the population’s access to specialized cognitive care, and the economic impact at the institutional level.
The data collected included sociodemographic data from the participants. Regarding the usability and UX evaluation, a test with a session script was delivered to the user in which they had to perform the tasks described in it while their performance in the observation grid (number of errors, task execution time, and success/failure) and the occurrence of unforeseen events in the critical incident log sheet performance were recorded. In addition, the System Usability Scale (SUS), the International Classification of Functionality-based Usability Scale (ICF-US), and the Unified Theory of Acceptance and Use of Technology (UTAUT) were used to measure intention of use after the test was performed. Finally, user satisfaction was recorded through general satisfaction assessment questions. In the case of the workflow and impact, patients were asked about topics such as the utility of the COGNIVITRA system, impact on both patients and caregivers, and functionalities that could be changed or enhanced. In terms of the overall effectiveness, instruments such as the EQ-5D-5L questionnaire for the assessment of patients’ quality of life, the Timed 25-Foot Walk (T25-FW), and a dual-task activity consisting of the repetition of the T25-FW counting backward from 100, and the Montreal Cognitive Assessment Scale (MoCA) were used. Data were gathered at baseline and after 6 and 12 weeks from the start of the trial, although in the latter case, only the overall satisfaction questionnaire was assessed.
The SUS is a generic usability rating scale that consists of a 10-item questionnaire scored on a 5-point Likert scale, with the final score ranging from 0 to 100, where higher values indicate better usability. While scores of ≥68 are considered above average, values under that value are considered below average [
16]. The ICF-US is a usability assessment scale that is based on the opinion of the observer and consists of two subscales. The first subscale, the ICF-US I, allows for a comprehensive usability assessment, whereas the second subscale, the ICF-US II, allows for the classification of the application components as barriers and facilitators, identifying the application’s strengths and weaknesses. The ICF-US I scores all items from −3 to 3, representing the most and least positive answers, respectively. The score ranges between −30 and 30, and whenever a user scores below 10, there is room for improvement, and the ICF-US II should be applied. The ICF-US II scale is composed of items that identify different application components (e.g., menu navigation, image, or interaction), consisting of three parts (i.e., application components, detailed usability, and overall assessment) that are classified as either barriers or facilitators. Whenever a component is classified as a barrier, the evaluator must identify the characteristic that is causing the component to be classified as a barrier, allowing the identification of which items require more work to improve the application [
17,
18]. The UTAUT, whose values range from 1 to 7, was only applied to the professional’s group and is a technology acceptance model formulated from the conceptual and empirical integration of eight previously developed models. This model assesses the intention to use and effective use of technological solutions, enabling the identification of key aspects to improve the solution to increase exploitation by potential users. It consists of a set of items that are scored on a 7-point Likert scale, with a value of 1 corresponding to “strongly disagree” and a value of 7 corresponding to “strongly agree” [
19]. The EQ-5D-5L is a questionnaire for the assessment of patients’ quality of life, consisting of a descriptive system (EQ-5D) and a visual analog scale (EQ-VAS). The first part, the EQ-5D, comprises five dimensions (mobility, self-care, usual activities, pain/discomfort and anxiety/depression), with each one having five levels (no problems, slight problems, moderate problems, severe problems and extreme problems). The score for each item ranges from 1 to 5, in which 1 represents “no problems” and 5 represents “extreme problems”, whereas the “index value” ranges from 0 to 1 [
20]. The second part, the EQ-VAS, measures health outcomes according to the patient’s own judgment on a vertical VAS, where the endpoints range from “The best health you can imagine” to “the worst health you can imagine”, with scores ranging from 0 to 100. The T25-FW is the most commonly used standalone measure of physical activity and is based on a timed 25-foot walk, measuring the time needed to complete the task. The patient is instructed to walk as fast and as safely as possible across a clearly marked, linear 25-foot course, with the task immediately administered again by having the patient walk the same distance while counting backward from 100. The T25-FW score is the average (in seconds) of the two successive trials [
21]. Finally, the MoCA is a brief screening tool for mild cognitive impairment that assesses different cognitive domains (executive function; visuospatial capacity; memory; attention and concentration; working memory; language; and both temporal and spatial orientation), and its score varies between zero and 30 [
22].
2.3. Statistical Analysis
While continuous variables are represented as the means and standard deviations (SDs), categorical variables are depicted as percentages. Either a chi-square test or Fisher test was used to compare the categorical variables between groups, and the Student’s t test for independent samples or the Mann‒Whitney U test was used to compare the continuous variables between groups. Changes in week 6 from baseline were analyzed according to the group via paired samples t tests or Wilcoxon tests if applicable. Statistical significance was established at p ≤ 0.05, and statistical analyses were performed with SAS 9.4 software.
4. Discussion
According to the results presented in this study, the evaluation of usability revealed notable results among patients, particularly in the home study. Patient responses indicated favorable outcomes in terms of user satisfaction and learning simplicity. With respect to usability, while higher values were observed, no statistically significant differences were found in the overall SUS scores between 6 weeks and baseline. However, in the home setting, these differences were statistically significant, indicating a better SUS score at 6 weeks than at baseline. Additionally, professionals reported high SUS scores. High adherence was observed overall, with participants exceeding the mandatory number of weeks, especially among those in the home setting compared with those in the clinical setting. In addition, some participants, all from the home study group, surpassed the prescribed frequency of sessions. However, it is noteworthy that the percentage of completed weeks was lower in the home setting than in the clinical setting. One potential explanation could be the lack of immediate professional assistance when issues arose or differences in motivation levels. Nonetheless, the total number of training hours was greater among the participants in the home study. Observational grid assessments demonstrated a high success rate for tasks, although an increase in errors was noted during the home study. In the case of the professionals, they provided positive feedback on the use of the device, while patients also reported heightened satisfaction levels and a positive inclination toward adopting COGNIVITRA. With respect to effectiveness, a noninferiority significant change toward improving patient quality of life, ambulation, and cognitive improvement was reported. In fact, the values obtained at the 6-week time point indicate that patients perceived themselves to be in general good health (according to EQ-5D-5L values) [
20], to have good mobility with some difficulties but still relatively functional (according to the T25-FW scores) [
21], and as having mild cognitive impairment (according to the MoCA scores) [
22]. The slight improvement in most values or the maintenance of the patient’s situation for some scores remains a strength of the obtained results. Although there was a nonsignificant increase in satisfaction after 6 and 12 weeks of training, satisfaction seemed to be more pronounced in the home setting than in the clinical setting. Importantly, most participants reported a positive experience with COGNIVTIRA, with many noting an overall improvement in their subjective perception of general health, as evidenced by the EQ-VAS scores. This satisfaction with the device was translated as 75.0% of patients and caregivers being willing to pay either a monthly/per use fee or purchase the product.
The improvement or maintenance of patients’ cognitive status and user engagement with these types of devices among patients with MCI has already been described in similar studies. A pilot study comprising 49 participants, 20 with MCI and 29 healthy participants, investigated SmartWalk [
23], a novel tool that combines aerobic exercise and cognitive protocols to stimulate cognitive function through the use of foot inertial sensing and a test for the auditory sustained attention domain to detect the user’s gait and performance on cognitive tasks that are synchronized with the user’s walking pace. The results showed that the tool was effective in improving cognitive function in both groups, particularly in the areas of sustained attention and vigilance. In our study, longer training periods were needed to assess the effectiveness of COGNIVITRA thoroughly. With respect to usability, the participants using the SmartWalk tool indicated a mean SUS score of 86.84 ± 9.97 [
23], which is higher than those obtained in our study from both the patients (72.3 ± 17.2) and healthcare professionals (68.9 ± 12.2). Thus, future improvements in the robustness of the technology to improve usability must be made to enhance the patient’s experience.
In a 6-month single-blind randomized controlled trial among 150 community-dwelling older adults with subjective and/or objective cognitive impairment who used the StandingTall program, a digital exercise program designed to improve mobility delivered via a tablet, a nonsignificant difference in gait speed of 0.04 m/s (
p = 0.09) was observed. Thus, this finding reinforces the fact that even longer periods of training still have limitations in terms of effectiveness (in this case, mobility). Finally, the average SUS score was slightly higher than that of our healthcare professionals sample (76.7 ± 15.3 vs. 68.9 ± 12.2), although it was similar to that of the patients in our study (72.3 ± 17.2). In addition, 89.1% of patients reported a subjective benefit from the StandingTall program [
24]. In comparison, in our study, 91.7% of the participants stated that they had an overall positive experience with COGNIVITRA, which was higher than that reported in the StandingTall study.
Tele-FootX
TM is a motion sensor module equipped with a custom application that is designed to improve balance and cognition during distractive conditioning through gamified balance tasks and explicit augmented visual feedback, while a telemedicine interface remotely supervises the exercise [
25]. A clinical trial involving 14 patients with mild cognitive impairment reported good acceptability, perceived benefits, and positive attitudes toward the use of the system. The Technology Acceptance Model (TAM) scores were significantly lower for exergaming adherence and increased for the participants’ level of interest while performing in-home exergaming exercises. In our study, it is noteworthy that overall adherence was high, with participants completing more weeks than needed, which was particularly evident among those in the home setting compared with those in the clinical setting. In fact, as mentioned above, some participants exceeded the prescribed number of sessions, exclusively among those in the home study. On the other hand, values significantly increased for the questions that indicated that participants benefitted from performing in-home exergaming exercises to improve their physical and mental functions and quality of work. In terms of cognition and anxiety, an improvement in the average MoCA score of 9.7% and a decrease in the average Beck Anxiety Inventory (BAI) score of 27.6% were observed [
25]. In our study, a nonsignificant improvement in the MoCA score was also observed, although only in the overall study (from 24.6 ± 3.2 to 25.0 ± 3.8) and clinical setting study samples (from 23.2 ± 3.8 to 24.3 ± 4.8), with a slight decline observed in the home study sample (from 25.9 ± 2.1 to 25.6 ± 2.9). These results might be explained by the different patient populations, study lengths, and numbers of sessions per week.
With respect to the willingness to pay for the device, user satisfaction often correlates with the perceived value of a medical device, as well as its quality, performance, and user-friendly interfaces. This satisfaction can positively influence users’ willingness to pay for the device, as they see it as worth the investment. In our study, most of the participants (75.0%) were willing to pay to use COGNIVITRA, which was positively correlated with the overall high satisfaction scores reported among the users. Interestingly, this scenario is not always observed; as in other devices, user satisfaction and willingness to pay do not always correlate [
26].
COGNIVITRA is an innovative advancement in cognitive care that integrates dual-task training, combining cognitive and physical exercises with advanced information and communications technology (ICT). Unlike traditional cognitive training programs, which are typically confined to clinical settings, COGNIVITRA extends these interventions to the home environment. This extension is made possible through a user-friendly interface, virtual coaching, and real-time feedback mechanisms that adapt to the user’s performance. These features provide a holistic approach to cognitive rehabilitation that is accessible and customizable to individual patient needs. The platform also facilitates seamless communication between patients and care providers, enhancing the continuity of care and potentially leading to more sustained cognitive and physical improvements.
Despite its promising features, the deployment of COGNIVITRA presents challenges. One primary concern is ensuring digital literacy among elderly individuals, as effective use of the platform depends on the user’s comfort with technology. Although the system is designed to be intuitive, varying levels of technology adoption among older adults could impact its overall usability and acceptance. Another challenge is the integration of COGNIVITRA with existing healthcare systems, which requires ensuring compatibility with different electronic health record (EHR) platforms and securing patient data. Additionally, there may be resistance from healthcare providers who are accustomed to traditional methods of cognitive care, highlighting the need for comprehensive training and demonstration of the platform’s efficacy to gain full support.
The anticipated impact of COGNIVITRA on cognitive care is substantial. By enabling continuous cognitive and physical training outside of clinical settings, COGNIVITRA has the potential to significantly enhance patient outcomes, particularly in slowing the progression of MCI. Its accessibility could lead to broader population-level benefits by reaching individuals who are unable or unwilling to visit clinical facilities frequently. Moreover, the platform could have a considerable economic impact at the institutional level by reducing the need for in-person visits and hospital-based interventions, thereby lowering healthcare costs. In the long term, the success of COGNIVITRA could stimulate further technological developments in cognitive care, fostering innovations that integrate AI-driven personalized training programs and expanding the scope of remote healthcare solutions.
COGNIVITRA stands out from other cognitive training solutions through its dual-task training and home-based accessibility. Traditional programs often require in-person attendance, limiting their accessibility and scalability. In contrast, COGNIVITRA is designed for use both in clinical settings and at home, featuring a virtual coach to guide users and advanced motion sensors and real-time feedback systems to enhance the user experience. These design elements ensure that exercises are performed correctly, maximizing the training’s effectiveness. Additionally, COGNIVITRA’s ability to facilitate communication between patients and healthcare providers is a significant advantage over other programs that may operate in isolation from the broader healthcare ecosystem. This integration of communication tools allows for the continuous monitoring and adjustment of the training programs, ensuring that they remain aligned with the patient’s evolving needs. The intended purpose of COGNIVITRA extends beyond providing cognitive exercises; it aims to maintain and enhance cognitive vitality through a multifaceted approach that includes physical activity. While many alternative solutions focus exclusively on cognitive enhancement, COGNIVITRA’s dual-task framework is designed to delay cognitive decline by simultaneously improving physical health. The platform is also intended to be a long-term solution that patients can integrate into their daily lives, offering a more sustainable approach than alternatives that may be episodic or limited in duration. Moreover, by enabling home-based training, COGNIVITRA seeks to reach a broader population, including those with limited access to clinical facilities.
One of COGNIVITRA’s core features is its ability to enhance communication between patients and care providers through integrated real-time data monitoring and reporting systems. This allows healthcare providers to monitor patient progress remotely, making adjustments as necessary to optimize outcomes. By maintaining continuous interaction, particularly for elderly patients, COGNIVITRA helps reduce the sense of isolation that can accompany home-based care, contributing to better mental health and overall patient satisfaction. Finally, COGNIVITRA has significant economic implications for healthcare institutions. By enabling home-based training, it reduces the frequency of in-person visits, leading to cost savings for both providers and patients. The platform’s ability to monitor patient progress remotely also allows for early intervention, potentially preventing more serious cognitive decline and reducing long-term healthcare costs. In this way, COGNIVITRA contributes to a more efficient and cost-effective approach to cognitive rehabilitation. Finally, gathering data from a real-world setting, with the tasks being performed in both home and clinical settings, can be included among the strengths of the study. In contrast, the low number of patients in the analysis can be included among the weaknesses of the study. Therefore, it is essential to conduct prospective studies with larger groups of participants and longer follow-up periods to validate and build upon our results.