"Guttmann Cognitest®," a digital solution for assessing cognitive performance in adult population: A feasibility and usability pilot study

Background

As the world population continues to age, the prevalence of neurological diseases, such as dementia, poses a significant challenge to society. Detecting cognitive impairment at an early stage is vital in preserving and enhancing cognitive function. Digital tools, particularly mHealth, offer a practical solution for large-scale population screening and prompt follow-up assessments of cognitive function, thus overcoming economic and time limitations.

Objective

In this work, two versions of a digital solution called Guttmann Cognitest® were tested.

Methods

Two hundred and one middle-aged adults used the first version (Group A), while 132 used the second one, which included improved tutorials and practice screens (Group B). This second version was also validated in an older age group (Group C).

Results

This digital solution was found to be highly satisfactory in terms of usability and feasibility, with good acceptability among all three groups. Specifically for Group B, the system usability scale score obtained classifies the solution as the best imaginable in terms of usability.

Conclusions

Guttmann Cognitest® has been shown to be effective and well-perceived, with a high potential for sustained engagement in tracking changes in cognitive function.

"Guttmann Cognitest"®, preliminary validation of a digital solution to test cognitive performance

Thanks to technological advances, the administration of cognitive assessments via digital solutions continues to increase, both in research and clinical practice. "Guttmann Cognitest"°ledR is a digital solution for cognitive assessment which includes seven computerized tasks designed to assess main cognitive functions requiring approximately 20 min to be completed. The purpose of the present study was to validate it against standard and more extensive in-person neuropsychological assessments in the context of the Barcelona Brain Health Initiative (BBHI) cohort study. We studied 274 participants of the BBHI (126 women, mean age = 56.14, age range 44-69), who underwent an extensive in-person assessment, including a classical paper-and-pencil neuropsychological assessment and a cognitive assessment via the "Guttmann Cognitest"°ledR. Principal component analysis indicated that "Guttmann Cognitest"°ledR measures four main cognitive domains and convergent validity analysis demonstrated that cognitive performance was associated with gold standard paper and pencil tests. Results also showed an expected negative correlation with age, a relation with educational level as well as a gender effect. Regression-based norming equations for the sample tested are also reported. Performing a cognitive assessment with this digital solution is feasible and potentially useful to gather information about cognitive functioning in large samples and experimental settings.

Aging in the Digital Age: Using Technology to Increase the Reach of the Clinician Expert and Close the Gap Between Health Span and Life Span

Age-related cognitive impairment (ARCI) has a profound impact on individuals, families, health care systems, and societies at large. Evidence suggests that ARCI is the consequence of underlying brain pathology. Therefore, efforts to minimize the impact of ARCI and thus closing the gap between health span and life span, which has widened in recent years, requires early detection and timely deployment of targeted, personalized interventions. Access to clinical experts is limited and technology screening and assessment methods are thus appealing. However, as traditionally implemented patients were deprived of the benefit of personalized connection with a clinician, which is particularly critical for the prescription and to ensure the adherence to and ultimate success of therapeutic interventions. We present the concept of Intelligent Technology Therapy Assistant (ITA) as a scalable solution that increases the reach of clinical experts while sustaining the personal connection between each patient and their clinician. We illustrate ITA with the "Guttman Neuro Personal Trainer"®, a tele-rehabilitation platform that provides neuropsychological evaluation and care, and the Barcelona Brain Health Initiative (BBHI) multimodal intervention coaching app, a mobile-based platform that provides lifestyle coaching support in domains related to brain health. In addition, we discuss the translation of these models to a large-scale enterprise with Linus Health. To this end, we conclude with a discussion of challenges and opportunities to move the field forward.

Technologies for Monitoring Lifestyle Habits Related to Brain Health: A Systematic Review

Brain health refers to the preservation of brain integrity and function optimized for an individual’s biological age. Several studies have demonstrated that our lifestyles habits impact our brain health and our cognitive and mental wellbeing. Monitoring such lifestyles is thus critical and mobile technologies are essential to enable such a goal. Three databases were selected to carry out the search. Then, a PRISMA and PICOTS based criteria for a more detailed review on the basis of monitoring lifestyle aspects were used to filter the publications. We identified 133 publications after removing duplicates. Fifteen were finally selected from our criteria. Many studies still use questionnaires as the only tool for monitoring and do not apply advanced analytic or AI approaches to fine-tune results. We anticipate a transformative boom in the near future developing and implementing solutions that are able to integrate, in a flexible and adaptable way, data from technologies and devices that users might already use. This will enable continuous monitoring of objective data to guide the personalized definition of lifestyle goals and data-driven coaching to offer the necessary support to ensure adherence and satisfaction.

[Transcranial magnetic stimulation: the foundation and potential of modulating specific neuronal networks]

AIM

To offer an introduction to the neurophysiologic technique of transcranial magnetic stimulation (TMS).

DEVELOPMENT

We summarize the physics foundations and neurobiologic principles of action of TMS. We offer an introduction to the core aspects of instrument design and delivery technique of TMS to assure efficacy and safety. We discuss the possibility of real-time merging of TMS with neuroimaging methods (such as functional magnetic resonance imaging or positron emission tomography) to characterize neural networks in health and disease. We present evidence that repetitive TMS can be used to modulate excitability across a neural network and thus offers therapeutic applications in neurology, psychiatry, and rehabilitation.

CONCLUSIONS

TMS offers a unique opportunity to characterize and modulate neural networks in normal subjects and patients with diverse neuropsychiatric disorders. TMS can be used with diagnostic as well as therapeutic goals children, adults and elderly with neurologic and psychiatric disorders.