The Digital Platform and Its Emerging Role in Decentralized Clinical Trials.

Decentralized clinical trials (DCTs) are becoming increasingly popular. Digital clinical trial platforms are software environments where users complete designated clinical trial tasks, providing investigators and trial participants with efficient tools to support trial activities and streamline trial processes. In particular, digital platforms with a modular architecture lend themselves to DCTs, where individual trial activities can correspond to specific platform modules. While design features can allow users to customize their platform experience, the real strengths of digital platforms for DCTs are enabling centralized data capture and remote monitoring of trial participants and in using digital technologies to streamline workflows and improve trial management. When selecting a platform for use in a DCT, sponsors and investigators must consider the specific trial requirements. All digital platforms are limited in their functionality and technical capabilities. Integrating additional functional modules into a central platform may solve these challenges, but few commercial platforms are open to integrating third-party components. The lack of common data standardization protocols for clinical trials will likely limit the development of one-size-fits-all digital platforms for DCTs. This viewpoint summarizes the current role of digital platforms in supporting decentralized trial activities, including a discussion of the potential benefits and challenges of digital platforms for investigators and participants. We will highlight the role of the digital platform in the development of DCTs and emphasize where existing technology is functionally limiting. Finally, we will discuss the concept of the ideal fully integrated and unified DCT and the obstacles developers must address before it can be realized.

Stepping Forward: A Scoping Systematic Literature Review on the Health Outcomes of Smart Sensor Technologies for Diabetic Foot Ulcers.

Diabetic foot ulcers (DFUs) pose a significant challenge in diabetes care, demanding advanced approaches for effective prevention and management. Smart insoles using sensor technology have emerged as promising tools to address the challenges associated with DFU and neuropathy. By recognizing the pivotal role of smart insoles in successful prevention and healthcare management, this scoping review aims to present a comprehensive overview of the existing evidence regarding DFU studies related to smart insoles, offloading sensors, and actuator technologies. This systematic review identified and critically evaluated 11 key studies exploring both sensor technologies and offloading devices in the context of DFU care through searches in CINAHL, MEDLINE, and ScienceDirect databases. Predominantly, smart insoles, mobile applications, and wearable technologies were frequently utilized for interventions and patient monitoring in diabetic foot care. Patients emphasized the importance of these technologies in facilitating care management. The pivotal role of offloading devices is underscored by the majority of the studies exhibiting increased efficient monitoring, prevention, prognosis, healing rate, and patient adherence. The findings indicate that, overall, smart insoles and digital technologies are perceived as acceptable, feasible, and beneficial in meeting the specific needs of DFU patients. By acknowledging the promising outcomes, the present scoping review suggests smart technologies can potentially redefine DFU management by emphasizing accessibility, efficacy, and patient centricity.

A Semantic Framework to Detect Problems in Activities of Daily Living Monitored through Smart Home Sensors.

Activities of daily living (ADLs) are fundamental routine tasks that the majority of physically and mentally healthy people can independently execute. In this paper, we present a semantic framework for detecting problems in ADLs execution, monitored through smart home sensors. In the context of this work, we conducted a pilot study, gathering raw data from various sensors and devices installed in a smart home environment. The proposed framework combines multiple Semantic Web technologies (i.e., ontology, RDF, triplestore) to handle and transform these raw data into meaningful representations, forming a knowledge graph. Subsequently, SPARQL queries are used to define and construct explicit rules to detect problematic behaviors in ADL execution, a procedure that leads to generating new implicit knowledge. Finally, all available results are visualized in a clinician dashboard. The proposed framework can monitor the deterioration of ADLs performance for people across the dementia spectrum by offering a comprehensive way for clinicians to describe problematic behaviors in the everyday life of an individual.

Detection of Health-Related Events and Behaviours from Wearable Sensor Lifestyle Data Using Symbolic Intelligence: A Proof-of-Concept Application in the Care of Multiple Sclerosis.

In this paper, we demonstrate the potential of a knowledge-driven framework to improve the efficiency and effectiveness of care through remote and intelligent assessment. More specifically, we present a rule-based approach to detect health related problems from wearable lifestyle sensor data that add clinical value to take informed decisions on follow-up and intervention. We use OWL 2 ontologies as the underlying knowledge representation formalism for modelling contextual information and high-level concepts and relations among them. The conceptual model of our framework is defined on top of existing modelling standards, such as SOSA and WADM, promoting the creation of interoperable knowledge graphs. On top of the symbolic knowledge graphs, we define a rule-based framework for infusing expert knowledge in the form of SHACL constraints and rules to recognise patterns, anomalies and situations of interest based on the predefined and stored rules and conditions. A dashboard visualizes both sensor data and detected events to facilitate clinical supervision and decision making. Preliminary results on the performance and scalability are presented, while a focus group of clinicians involved in an exploratory research study revealed their preferences and perspectives to shape future clinical research using the framework.

Our experience with informative and communication technologies (ICT) in dementia.

Our research is implementing high quality next generation services for the Prediction, Early Diagnosis, Monitoring, and Support of patients with Cognitive Impairment (Subjective Cognitive Impairment -SCI-, Mild Cognitive Impairment -MCI-, Mild Dementia) and Education and Training for all stakeholders. Prediction, Early Diagnosis and Monitoring: The first idea was to Research and Develop a novel System using motion detection devices, depth cameras, and intelligent objects of everyday use (ranging from cooking implements such as kitchen to furniture (e.g. sofa, bed, etc.) which are appropriately adapted in order to capture changes of subject's Activities of Daily Living -ADL- and behavioural patterns (including mobility, nutrition, exercising and medication schedule). We also demonstrated the potential of a virtual supermarket (VSM) cognitive training game as a screening tool for patients with MCI in a sample of older adults. We have indicated that this VSM application displayed a correct classification rate (CCR) of 87.30%, achieving a level of diagnostic accuracy similar to standardized neuropsychological tests, which are the gold standard for MCI screening http://www.en-noisis.gr/ Support of patients: Cognitive tasks and cognitive exercises for patients suffering from Alzheimer's Disease (AD) through web-based applications. These exercises have been developed in such a way in order to exploit rich interactive multimedia interfaces (including music) based on human computer interaction principles. To this direction we are implementing a web based portal with supportive services such as (a) on-line monitoring of patient's progress by health care professionals, (b) statistical representation of patients' progress. Multimedia enriched cognitive exercises in virtual reality form (i.e. 3D Serious Games) use suitable modalities for such activities through the creation probable of new brain cells and by assisting the brain to find out alternative methods to execute functions, which are controlled by damaged brain regions. Another program the "robot-programming-as-cognitive-training" approach aims to explore the impact that the activity of programming a friendly robot might have on AD and MCI patients' condition. http://aspad.csd.auth.gr. Another study aimed at investigating the benefits of combined physical and cognitive training on global cognition while assessing the effect of training dosage and exploring the role of several potential effect modifiers. The results indicate that combined physical and cognitive training improves global cognition in a dose-responsive manner but these benefits may be less pronounced in older adults with mild dementia. The long-lasting impact of combined training on the incidence and trajectory of cognitive disorders in relation to its severity should be assessed in future long-term trials. www.longlastingmemories.eu. Finally, Symbiosis is a revolutionary system aiming at providing integrated solutions to a series of problems related with MCI and AD. It is the first integrated AD support system that takes into account patient's response in an adaptive way that fulfills each patient's special needs and provides to caregivers and doctors considerable facilitations, unlocking the potential of innovative supporting role. www.youtube.com/watch?v=BDkLz-T-jYE. Education and training for all stakeholders (i.e. health professionals and informal and formal caregivers) through distance education platforms and e-collaboration services. To augment this effort, the research team integrates biofeedback modules for stress measurement in teleconferences in order to support the emotional awareness of the participants. The depression, anxiety and burden of caregivers were reduced significantly in the same way as in a face to face intervention. http://aspad.csd.auth.gr. In conclusion ICT can help health professionals and caregivers to support in a better way the patients with cognitive, functional and behavioral problems.

An Overview of the ADReSS-M Signal Processing Grand Challenge on Multilingual Alzheimer's Dementia Recognition Through Spontaneous Speech.

The ADReSS-M Signal Processing Grand Challenge was held at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023. The challenge targeted difficult automatic prediction problems of great societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD) and the estimation of cognitive test scoress. Participants were invited to create models for the assessment of cognitive function based on spontaneous speech data. Most of these models employed signal processing and machine learning methods. The ADReSS-M challenge was designed to assess the extent to which predictive models built based on speech in one language generalise to another language. The language data compiled and made available for ADReSS-M comprised English, for model training, and Greek, for model testing and validation. To the best of our knowledge no previous shared research task investigated acoustic features of the speech signal or linguistic characteristics in the context of multilingual AD detection. This paper describes the context of the ADReSS-M challenge, its data sets, its predictive tasks, the evaluation methodology we employed, our baseline models and results, and the top five submissions. The paper concludes with a summary discussion of the ADReSS-M results, and our critical assessment of the future outlook in this field.

Cancer Patients' Perspectives and Requirements of Digital Health Technologies: A Scoping Literature Review.

Digital health technologies have the potential to alleviate the increasing cancer burden. Incorporating patients' perspectives on digital health tools has been identified as a critical determinant for their successful uptake in cancer care. The main objective of this scoping review was to provide an overview of the existing evidence on cancer patients' perspectives and requirements for patient-facing digital health technologies. Three databases (CINAHL, MEDLINE, Science Direct) were searched and 128 studies were identified as eligible for inclusion. Web-based software/platforms, mobile or smartphone devices/applications, and remote sensing/wearable technologies employed for the delivery of interventions and patient monitoring were the most frequently employed technologies in cancer care. The abilities of digital tools to enable care management, user-friendliness, and facilitate patient-clinician interactions were the technological requirements predominantly considered as important by cancer patients. The findings from this review provide evidence that could inform future research on technology-associated parameters influencing cancer patients' decisions regarding the uptake and adoption of patient-facing digital health technologies.

Language Markers of Dementia and Their Role in Early Diagnosis of Alzheimer's Disease: Exploring Grammatical and Syntactic Competence via Sentence Repetition.

Background: Earlier research focuses primarily on the cognitive changes due to Alzheimer's disease (AD); however, little is known with regard to changes in language competence across the lifespan. Objective: The present study aims to investigate the decline of language skills at the grammatical and syntactic levels due to changes in cognitive function. Methods: We administered the Litmus Sentence Repetition Task (SRT) to 150 native speakers of Greek who fall into five groups: 1) young healthy speakers, 2) cognitively intact elder healthy speakers, 3) speakers with subjective cognitive impairment (SCI), 4) speakers with mild cognitive impairment (MCI); and 5) speakers with AD dementia at the mild/moderate stages. All participants underwent a physical and neurological examination and cognitive screening with a standardized neuropsychological battery to assess cognitive status comprehensively and evaluate aspects like working memory, executive function, attention and memory to appropriately classify them. Results: The data analysis revealed that the SRT had high discriminatory value in the development of AD; specifically, both accuracy and grammaticality indices were related to cognitive decline. Additionally, syntax significantly affected the performance of speakers with structures such as clitics being particularly challenging and in most structures the performance of speakers with MCI drops significantly compared to speakers with SCI. Conclusions: Linguistic indices revealed subtle early signs of cognitive decline that can be helpful in the early detection of AD, thus facilitating the clinical process offering support to language-based assessment tools such as sentence repetition, a non-invasive type of assessment to evaluate symptoms of AD.

Assessing the Linguistic Capacity Across Alzheimer's Disease and Its Preclinical Stages: Evidence from Narrative Macrostructure in Elderly Speakers of Greek.

Background: The assessment of language deficits can be valuable in the early clinical diagnosis of neurodegenerative disorders, including Alzheimer's disease (AD). Objective: The present study aims to explore whether language markers at the macrostructural level could assist with the placement of an individual across the dementia continuum employing production data from structured narratives. Methods: We administered a Picture Sequence Narrative Discourse Task to 170 speakers of Greek: young healthy controls (yHC), cognitively intact healthy elders (eHC), elder participants with subjective cognitive impairment (SCI), with mild cognitive impairment (MCI), and with AD dementia at the mild/moderate stages. Structural MRIs, medical history, neurological examination, and neuropsychological/cognitive screening determined the status of each speaker to appropriately groupthem. Results: The data analysis revealed that the Macrostructure Index, Irrelevant Info, and Narration Density markers can track cognitive decline and AD (p < 0.001; Macrostructural Index: eHC versus AD Sensitivity 93.8%, Specificity 74.4%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%; Narration Density: eHC versus AD Sensitivity 90.6%, Specificity 71.8%, MCI versus AD Sensitivity 93.8%, Specificity 66.7%). Moreover, Narrative Complexity was significantly affected for subjects with AD, Irrelevant Info increased in the narrations of speakers with MCI and AD, while Narration Length did not appear to indubitably differentiate between the cognitively intact groups and the clinical ones. Conclusions: Narrative Macrostructure Indices provide valuable information on the language profile of speakers with(out) intact cognition revealing subtle early signs of cognitive decline and AD suggesting that the inclusion of language-based assessment tools would facilitate the clinical process.

Assessing the cognitive decline of people in the spectrum of AD by monitoring their activities of daily living in an IoT-enabled smart home environment: a cross-sectional pilot study.

Introduction: Assessing functional decline related to activities of daily living (ADLs) is deemed significant for the early diagnosis of dementia. As current assessment methods for ADLs often lack the ability to capture subtle changes, technology-based approaches are perceived as advantageous. Specifically, digital biomarkers are emerging, offering a promising avenue for research, as they allow unobtrusive and objective monitoring. Methods: A study was conducted with the involvement of 36 participants assigned to three known groups (Healthy Controls, participants with Subjective Cognitive Decline and participants with Mild Cognitive Impairment). Participants visited the CERTH-IT Smart Home, an environment that simulates a fully functional residence, and were asked to follow a protocol describing different ADL Tasks (namely Task 1 - Meal, Task 2 - Beverage and Task 3 - Snack Preparation). By utilizing data from fixed in-home sensors installed in the Smart Home, the identification of the performed Tasks and their derived features was explored through the developed CARL platform. Furthermore, differences between groups were investigated. Finally, overall feasibility and study satisfaction were evaluated. Results: The composition of the ADLs was attainable, and differentiation among the HC group compared to the SCD and the MCI groups considering the feature "Activity Duration" in Task 1 - Meal Preparation was possible, while no difference could be noted between the SCD and the MCI groups. Discussion: This ecologically valid study was determined as feasible, with participants expressing positive feedback. The findings additionally reinforce the interest and need to include people in preclinical stages of dementia in research to further evolve and develop clinically relevant digital biomarkers.

Electronic prescription systems in Greece: a large-scale survey of healthcare professionals' perceptions.

BACKGROUND: The national e-prescription system in Greece is one of the most important achievements in the e-health sector. Healthcare professionals' feedback is essential to ensure the introduced system tends to their needs and reduces their everyday workload. The number of surveys collecting the users' views is limited, while the existing studies include only a small number of participants. METHODS: In this study, healthcare professionals' perceptions on e-prescription are explored. For this, a questionnaire was distributed online, containing closed- and open-ended questions aiming to address strengths and identify drawbacks in e-prescription. Answers were collected from primary health care physicians, specialized medical doctors and pharmacists. RESULTS: In total, 430 answers were collected (129 from primary health care physicians, 164 responses from specialized medical doctors and 137 pharmacists). Analysis of the collected answers reveals that the views of the three groups of healthcare professionals mostly converge. The positive impact e-prescribing systems have on the overall prescribing procedure in preventing errors and providing automation is commented. Among gaps identified and proposed improvements, health care professionals note the need for access to information on adverse drug reactions, side effects, drug-to-drug interactions and allergies. Flexible interaction with Therapeutic Prescription Protocols is desired to ameliorate monitoring and decision-making, while drug dosing features, and simplified procedures for copying, repeating, canceling a prescription, are perceived as useful to incorporate. CONCLUSIONS: Collecting healthcare professionals' feedback is important, as their views can be transcribed to system requirements, to further promote e-prescribing and improve the provided health care services by facilitating decision making through safer and more efficient e-prescription. Introduction of the identified improvements can simplify the everyday workflow of healthcare professionals. To the best of our knowledge, a survey with more than 400 answered questionnaires on the use of e-prescription systems by healthcare professionals has never been conducted in Greece before.

Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study.

Objectives: Meditation imparts relaxation and constitutes an important non-pharmacological intervention for people with cognitive impairment. Moreover, EEG has been widely used as a tool for detecting brain changes even at the early stages of Alzheimer's Disease (AD). The current study investigates the effect of meditation practices on the human brain across the AD spectrum by using a novel portable EEG headband in a smart-home environment. Methods: Forty (40) people (13 Healthy Controls-HC, 14 with Subjective Cognitive Decline-SCD and 13 with Mild Cognitive Impairment-MCI) participated practicing Mindfulness Based Stress Reduction (Session 2-MBSR) and a novel adaptation of the Kirtan Kriya meditation to the Greek culture setting (Session 3-KK), while a Resting State (RS) condition was undertaken at baseline and follow-up (Session 1-RS Baseline and Session 4-RS Follow-Up). The signals were recorded by using the Muse EEG device and brain waves were computed (alpha, theta, gamma, and beta). Results: Analysis was conducted on four-electrodes (AF7, AF8, TP9, and TP10). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance. The results revealed that both states of MBSR and KK lead to a marked difference in the brain's activation patterns across people at different cognitive states. Wilcoxon Signed-ranks test indicated for HC that theta waves at TP9, TP10 and AF7, AF8 in Session 3-KK were statistically significantly reduced compared to Session 1-RS Z = -2.271, p = 0.023, Z = -3.110, p = 0.002 and Z = -2.341, p = 0.019, Z = -2.132, p = 0.033, respectively. Conclusion: The results showed the potential of the parameters used between the various groups (HC, SCD, and MCI) as well as between the two meditation sessions (MBSR and KK) in discriminating early cognitive decline and brain alterations in a smart-home environment without medical support.

Correction: Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study.

[This corrects the article DOI: 10.1371/journal.pone.0285807.].

Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study.

INTRODUCTION: Clinical research with remote monitoring technologies (RMTs) has multiple advantages over standard paper-pencil tests, but also raises several ethical concerns. While several studies have addressed the issue of governance of big data in clinical research from the legal or ethical perspectives, the viewpoint of local research ethics committee (REC) members is underrepresented in the current literature. The aim of this study is therefore to find which specific ethical challenges are raised by RECs in the context of a large European study on remote monitoring in all syndromic stages of Alzheimer's disease, and what gaps remain. METHODS: Documents describing the REC review process at 10 sites in 9 European countries from the project Remote Assessment of Disease and Relapse-Alzheimer's Disease (RADAR-AD) were collected and translated. Main themes emerging in the documents were identified using a qualitative analysis approach. RESULTS: Four main themes emerged after analysis: data management, participant's wellbeing, methodological issues, and the issue of defining the regulatory category of RMTs. Review processes differed across sites: process duration varied from 71 to 423 days, some RECs did not raise any issues, whereas others raised up to 35 concerns, and the approval of a data protection officer was needed in half of the sites. DISCUSSION: The differences in the ethics review process of the same study protocol across different local settings suggest that a multi-site study would benefit from a harmonization in research ethics governance processes. More specifically, some best practices could be included in ethical reviews across institutional and national contexts, such as the opinion of an institutional data protection officer, patient advisory board reviews of the protocol and plans for how ethical reflection is embedded within the study.

Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire-Based Usability Study.

We have designed a platform to aid people with motor disabilities to be part of digital environments, in order to create digitally and socially inclusive activities that promote their quality of life. To evaluate in depth the impact of the platform on social inclusion indicators across patients with various motor disabilities, we constructed a questionnaire in which the following indicators were assessed: (i) Well Being, (ii) Empowerment, (iii) Participation, (iv) Social Capital, (v) Education, and (vi) Employment. In total 30 participants (10 with Neuromuscular Disorders-NMD, 10 with Spinal Cord Injury-SCI, and 10 with Parkinson's Disease-PD) used the platform for ~1 month, and its impact on social inclusion indicators was measured before and after the usage. Moreover, monitoring mechanisms were used to track computer usage as well as an online social activity. Finally, testimonials and experimenter input were collected to enrich the study with qualitative understanding. All participants were favorable to use the suggested platform, while they would prefer it for longer periods of time in order to become "re-awakened" to possibilities of expanded connection and inclusion, while it became clear that the platform has to offer them further the option to use it in a reclining position. The present study has clearly shown that the challenge of social inclusion cannot be tackled solely with technology and it needs to integrate persuasive design elements that foster experimentation and discovery.

Exploring Network Properties Across Preclinical Stages of Alzheimer's Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study.

BACKGROUND: Visual short-term memory (VSTMT) and visual attention (VAT) exhibit decline in the Alzheimer's disease (AD) continuum; however, network disruption in preclinical stages is scarcely explored. OBJECTIVE: To advance our knowledge about brain networks in AD and discover connectivity alterations during VSTMT and VAT. METHODS: Twelve participants with AD, 23 with mild cognitive impairment (MCI), 17 with subjective cognitive decline (SCD), and 21 healthy controls (HC) were examined using a neuropsychological battery at baseline and follow-up (three years). At baseline, the subjects were examined using high density electroencephalography while performing a VSTMT and VAT. For exploring network organization, we constructed weighted undirected networks and examined clustering coefficient, strength, and betweenness centrality from occipito-parietal regions. RESULTS: One-way ANOVA and pair-wise t-test comparisons showed statistically significant differences in HC compared to SCD (t (36) = 2.43, p = 0.026), MCI (t (42) = 2.34, p = 0.024), and AD group (t (31) = 3.58, p = 0.001) in Clustering Coefficient. Also with regards to Strength, higher values for HC compared to SCD (t (36) = 2.45, p = 0.019), MCI (t (42) = 2.41, p = 0.020), and AD group (t (31) = 3.58, p = 0.001) were found. Follow-up neuropsychological assessment revealed converge of 65% of the SCD group to MCI. Moreover, SCD who were converted to MCI showed significant lower values in all network metrics compared to the SCD that remained stable. CONCLUSION: The present findings reveal that SCD exhibits network disorganization during visual encoding and retrieval with intermediate values between MCI and HC.

Cocreating a Harmonized Living Lab for Big Data-Driven Hybrid Persona Development: Protocol for Cocreating, Testing, and Seeking Consensus.

BACKGROUND: Living Labs are user-centered, open innovation ecosystems based on a systematic user cocreation approach, which integrates research and innovation processes in real-life communities and settings. The Horizon 2020 Project VITALISE (Virtual Health and Wellbeing Living Lab Infrastructure) unites 19 partners across 11 countries. The project aims to harmonize Living Lab procedures and enable effective and convenient transnational and virtual access to key European health and well-being research infrastructures, which are governed by Living Labs. The VITALISE consortium will conduct joint research activities in the fields included in the care pathway of patients: rehabilitation, transitional care, and everyday living environments for older adults. This protocol focuses on health and well-being research in everyday living environments. OBJECTIVE: The main aim of this study is to cocreate and test a harmonized research protocol for developing big data-driven hybrid persona, which are hypothetical user archetypes created to represent a user community. In addition, the use and applicability of innovative technologies will be investigated in the context of various everyday living and Living Lab environments. METHODS: In phase 1, surveys and structured interviews will be used to identify the most suitable Living Lab methods, tools, and instruments for health-related research among VITALISE project Living Labs (N=10). A series of web-based cocreation workshops and iterative cowriting processes will be applied to define the initial protocols. In phase 2, five small-scale case studies will be conducted to test the cocreated research protocols in various real-life everyday living settings and Living Lab infrastructures. In phase 3, a cross-case analysis grounded on semistructured interviews will be conducted to identify the challenges and benefits of using the proposed research protocols. Furthermore, a series of cocreation workshops and the consensus seeking Delphi study process will be conducted in parallel to cocreate and validate the acceptance of the defined harmonized research protocols among wider Living Lab communities. RESULTS: As of September 30, 2021, project deliverables Ethics and safety manual and Living lab standard version 1 have been submitted to the European Commission review process. The study will be finished by March 2024. CONCLUSIONS: The outcome of this research will lead to harmonized procedures and protocols in the context of big data-driven hybrid persona development among health and well-being Living Labs in Europe and beyond. Harmonized protocols enable Living Labs to exploit similar research protocols, devices, hardware, and software for interventions and complex data collection purposes. Economies of scale and improved use of resources will speed up and improve research quality and offer novel possibilities for open data sharing, multidisciplinary research, and comparative studies beyond current practices. Case studies will also provide novel insights for implementing innovative technologies in the context of everyday Living Lab research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34567.

Human Factors and Requirements of People with Cognitive Impairment, Their Caregivers, and Healthcare Professionals for mHealth Apps Including Reminders, Games, and Geolocation Tracking: A Survey-Questionnaire Study.

BACKGROUND: Mobile Health (mHealth) apps can delay the cognitive decline of people with dementia (PwD), by providing both objective assessment and cognitive enhancement. OBJECTIVE: This patient involvement survey aims to explore human factors, needs and requirements of PwD, their caregivers, and Healthcare Professionals (HCPs) with respect to supportive and interactive mHealth apps, such as brain games, medication reminders, and geolocation trackers through a constructive questionnaire. METHODS: Following the principles of user-centered design to involve end-users in design we constructed a questionnaire, containing both open-ended and closed-ended questions as well as multiple choice and Likert scale, in order to investigate the specific requirements and preferences for mHealth apps. We recruited 48 participants including people with cognitive impairment (n = 15), caregivers (n = 16), and HCPs (n = 17) and administered the questionnaire. RESULTS: All participants are likely to use mHealth apps, with the primary desired features being the improvement of memory and cognition, assistance on medication treatment, and perceived ease to use. HCPs, caregivers, and PwD consider brain games as an important technology-based, non-pharmaceutical intervention. Both caregivers and patients are willing to use a medication reminder app frequently. Finally, caregivers are worried about the patient wandering. Therefore, global positioning system tracking would be particularly important to them. On the other hand, patients are concerned about their privacy, but are still willing to use a geolocation app for cases of emergency. CONCLUSION: This research contributes to mHealth app design and potential adoption. All three groups agree that mHealth services could facilitate care and ameliorate behavioral and cognitive disturbances of patients.

Adaptation and Validation of the Memory Alteration Test (M@T) in Greek Middle-Aged, Older, and Older-Old Population with Subjective Cognitive Decline and Mild Cognitive Impairment.

BACKGROUND: The Memory Alteration Test (M@T) is a verbal episodic and semantic memory screening test able to detect subjective cognitive decline (SCD) and Mild Cognitive Impairment (MCI). OBJECTIVE: To adapt M@T, creating a Greek version of the Memory Alteration Test (M@T-GR), and to validate M@T-GR compared to the Mini-Mental State Examination (MMSE), and Subjective Cognitive Decline- Questionnaire (SCD-Q) MyCog and TheirCog. METHODS: 232 people over 55 years old participated in the study and they were classified as healthy controls (HC, n = 65), SCD (n = 78), or MCI (n = 89). RESULTS: The ANCOVA showed that the M@T-GR's total score was significantly different in HC and SCD (I-J = 2.26, p = 0.032), HC and MCI (I-J = 6.16, p < 0.0001), and SCD compared to MCI (I-J = 3.90, p < 0.0001). In particular, a cut-off score of 46.50 points had an 81%sensitivity and 61%specificity for discriminating HC from SCD (AUC = 0.76, p < 0.0001), while a cut-off score of 45.50 had a sensitivity of 92%and a specificity of 73%for discriminating MCI (AUC = 0.88, p < 0.0001), and a cut-off score of 45.50 points had a sensitivity of 63%and a specificity of 73%for discriminating SCD from those with MCI (AUC = 0.69, p < 0.0021). Exploratory factor analysis indicated that there was one factor explaining 38.46%of the total variance. Internal consistency was adequate (α= 0.75), while convergent validity was found between M@T-GR and MMSE (r = 0.37, p < 0.0001) and SCD-Q TheirCog (r = -0.32, p < 0.0001). CONCLUSION: The M@T-GR is a good to fair screening tool with adequate discriminant validity for administration in people with SCD and MCI in Greece.

Memory Clinics and Day Care Centers in Thessaloniki, Northern Greece: 30 Years of Clinical Practice and Experience.

Background: This review describes the diagnostic and interventional procedures conducted in two university memory clinics (established network of G. Papanikolaou Hospital: 1988-2017 and AHEPA hospital: 2017-today) and 2 day care centers (established network of DCCs: 2005-today) in North Greece and their contribution in the scientific field of dementia. The aims of this work are (1) to provide a diagnosis and treatment protocol established in the network of memory clinics and DCCs and (2) to present further research conducted in the aforementioned network during the last 30 years of clinical practice. Methods: The guidelines to set a protocol demand a series of actions as follows: (1) set the diagnosis criteria, neuropsychological assessment, laboratory examinations, and examination of neurophysiological, neuroimaging, cerebrospinal fluid, blood, and genetic markers; and (2) apply non-pharmacological interventions according to the needs and specialized psychosocial interventions of the patient to the caregivers of the patient. Results: In addition to the guidelines followed in memory clinics at the 1st and 3rd Department of Neurology and two DCCs, a database of patients, educational programs, and further participation in international research programs, including clinical trials, make our contribution in the dementia field strong. Conclusion: In the current paper, we provide useful guidelines on how major and minor neurocognitive disorders are being treated in Thessaloniki, Greece, describing successful practices which have been adapted in the last 30 years.