Investigating ProCare4Life Impact on Quality of Life of Elderly Subjects With Neurodegenerative Diseases

NCT ID: NCT05538455

Last Updated: 2023-08-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

558 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-09-30

Study Completion Date

2023-04-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

Personalized Integrated Care Promoting Quality of Life for Elderly People (ProCare4Life, PC4L) project was created to finalize a digital platform with integrated sensors , for monitoring the health status of the elderly subjects with neurodegenerative diseases and comorbidities.

In fact, an integrated care platform - able to establish correlations between comorbidities, investigate the intake of different drugs, mitigate potential health risks, study the social variables and promote unified therapeutic procedures or social services - could help patients, caregivers, healthcare professionals and social health workers to monitor various diseases parameters.

The main contribution of the PC4L project is to propose an integrated, scalable and interactive care system that can be easily adapted to the reality of various chronic diseases, care institutions and end-user needs, for the benefit of all the actors involved. The main expected results are to improve patients' quality of life, enable an active life and better disease management, support professionals in decision making, facilitate efficient communication between all stakeholders and ensure reliable and secure access to data at the within Europe.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

There is an urgent need to increase the efficiency and sustainability of health and social care systems across Europe, as there is a growing trend in public spending, which is expected to reach 14% of GDP by 2030. The main causes are the aging of the population, and the increase of chronic diseases, including cardiovascular diseases, diabetes, asthma, mental and physical disorders and neurodegenerative conditions. Comorbidities and the confluence of various chronic diseases is increasingly common in the elderly, which increases the need to develop models and tools to improve integrated health systems.

Population aging has also led to major reforms in long-term care policies and systems in many European countries, increasing the need for alternatives. This implies the need for help with housework or other practical errands, transportation by doctors or social visits, social companionship, emotional guidance, or help in organizing professional care. In most European countries, much of the care people over 60 receive is informal care.

Among the most common chronic diseases in the elderly population, neurocognitive deterioration in the stages of dementia associated with Alzheimer's and Parkinson's are the most disabling. Today, more than 10 million Europeans live with neurocognitive disorders in stages of dementia.

This situation can be improved through the creation of an integrated care platform, able to establish correlations between co-morbidities, investigate the use of the intake of different drugs, mitigate potential health risks, study the social variables involved and promote unified therapeutic procedures or social services. This solution could help patients, health professionals and social health workers to monitor various diseases, also considering the social context. In addition, people with chronic diseases face difficulties in their daily life and need specialized care services and care. This situation imposes high burdens on the public budget, which require particular attention to adequately address the sustainability of the social and health system in Europe.

The main contribution of the PC4L project is to propose an integrated, scalable and interactive care system that can be easily adapted to the reality of various chronic diseases, care institutions and end-user needs, for the benefit of all the actors involved (e.g. patients, caregivers and health experts). The main expected results are to improve patients' quality of life, enable an active life and better disease management, support professionals in decision making, facilitate efficient communication between all stakeholders and ensure reliable and secure access to data at the within Europe.This study is part of the European multicenter project Horizon 2020, called Personalized Integrated Care Promoting Quality of Life for Elderly People (ProCare4Life, PC4L), which involves several European partners and was created with the aim of finalizing a digital platform with integrated sensors, aimed at home monitoring of health status and treatment of the elderly patient with Parkinson's disease or Alzheimer's disease and other dementias.The PC4L Project was funded by the European Community Horizon 2020 innovation and research program (grant agreement No 875221), for the development of an international research project aimed at exploring the potential of assistive technologies in monitoring the behavior of elderly subjects. The project involves in fact the elderly population suffering from chronic neurological diseases and other comorbidities such as diabetes mellitus and arthritis. This project also aims to provide home support to the caregivers of subjects affected by these diseases.

PC4L-Pilot3 represents the third and last large-scale pilot study within the project, where the first one was aimed to explore feasibility and usability of the solution, and the second one investigated the characteristics of the metrics generated by the PC4L platform in real-life conditions.

In this pilot study, six clinical centers are involved, in five different European countries (Italy, Spain, Portugal, Romania, Germany), operating in the neurological context both at hospital and home care, as well as daycare centers.

An interventional, multicenter, randomized controlled trial will be conducted. The duration of the study per patient at home will be 3 months. Participants admitted to rehabilitation and daycare centers will use the PC4L platform for the entire duration of their stay in the center (not exceeding the 3 months).

Patients will be randomized into two groups: experimental group, which will use the PC4L platform for the duration envisaged by the study and will receive notifications and recommendations from the system; and the control group, which will follow the recommendations in paper form for the period envisaged by the study. Caregivers and health professionals will also be involved.

In-person assessments will take place at baseline and at the end of the study (3-month follow-up or at discharge from the rehabilitation/daycare program).

Demographic and clinical data (age, gender, level of education, professional activity, social support, previous use of technology) will be assesed at baseline. In-person assessments thorugh clinical evaluation will take place at baseline and at the end of the study (3-month follow-up or at discharge from the rehabilitation/daycare program). Clinical assessments are the following:

MDS Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Clinical Dementia Rating Scale (CDRS); Falls Self-Efficacy Scale (FES-I); Berg Balance test; Pittsburgh Sleep quality index score: State-Trait-Anxiety-Inventory (STAI); presence of festination, dysphasia, wandering episodes (last month); EuroQol5D3L; Barthel Index; patient satisfaction and empowerment (PACIC, SAPS); non-programmed medical resources used (last month); Cumulative Illness Rating Scale-Geriatric (CIRS-G) ; adverse events reporting; System Usability Scale (SUS) ; end-of-study survey (Global satisfaction with a 5-point Likert scale; What do you like most/least? Suggestions); end-of-study open questions (Which type of recommendations have you been using? How did you find the recommendations? how it helped in improving your wellbeing? What did you like the most/least?).

The PROCare4Life ecosystem consists of:

* Wearable sensors - to be used by the patient for monitoring disease-related parameters, in passive and interactive paradigms (e.g., simple bio-measurements as heart rate, complex bio-measurements as motor behavior, passive measurement if initiated automatically, interactive measurement if initiated by patient). The wearable sensor used is the smartwatch Fitbit Versa 2. Patients will use the sensor in the dominant arm.
* Fixed sensors (binary sensors) placed on strategic places and rooms in the home environment for assessing motor behaviors and the interaction with the environment (e.g. number of times the patient visits the bathroom, number of times the patient leaves the house). The selected location sensors are the "Xiaomi Aqara Door and Window Sensor (MCCGQ11LM)".
* PROCare4Life app for mobile smartphones to process data directly from smartphone (Samsung A20 or other similar model) IMU sensors and GPS and directly from users (e.g., anthropometric data and symptoms / complaints to be provided directly by the patient or by caregiver or social/healthcare professionals, via questionnaires). In particular, the data collected will be: anthropometric data and symptoms, and data related to medication uptake, to be provided directly by the patient or by caregiver, via short questionnaires and annotations. Data related to motor behaviors through GPS and inertial sensors.
* A local computer- to collect data from the patients via the sensorial ecosystem which includes several fixed and dynamic sensors such as wearables, binary sensors and/or cameras. (wearable and fixed sensors, and cameras).
* PROCare4Life integrated care platform (accessible via Internet browsers) to provide an electronic health record/personal information sheet (fed with data provided by the PROCare4Life ecosystem) and complex interface for personalized interaction/communication between the patients and healthcare professionals.
* Tablet or computer to collect data from the patients related to the cognitive abilities, with the use of the cognitive games application that includes six different games about the short-term memory, the visual recognition, understanding, semantic memory, vocabulary, mathematics, among others. This application collects not only the results of the games, but also information related to the user interaction with the application.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Neurodegenerative Diseases Parkinson Disease Alzheimer Disease Quality of Life

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Patients will be randomized on a 1: 1 ratio to intervention (use the PC4L system) and control group (no intervention) by an independent non-clinical partner of the consortium.

The control group will be assessed at baseline and will receive general written recommendations on the main areas (physical activity, sleep, cognitive, nutrition; social support and stress management for caregivers). At the follow-up, after three months, the same group will be assessed on quality of life using specific scales (EuroQoL53L).

The platform will be installed by one of the project's clinical partners in different scenarios.

Two different versions of the PC4L system will be tested. A fully equipped version, used in the previous 2 pilots, as well as a cloud-based system that requires only a smartphone and a wearable sensor (Fitbit Versa 2). Of those patients using the PC4L system, 25% will use the full system, the remaining (75%) will use the cloud-based system.
Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Experimental group, use of PC4L solutions

Participants who will use the PC4L solutions for the estabilished period of time, in the selected scenario (home, neurorehabilitation and daycare centers), and will receive recommendations in the PC4L app

Group Type EXPERIMENTAL

PC4L solutions

Intervention Type DEVICE

Two different versions of the PC4L system will be tested. A fully equipped version and a cloud-based system that requires only a smartphone and a wearable sensor (Fitbit Versa 2). 25% of participants will use the full system, the remaining 75% will use the cloud-based system. As part of the decision support system, the PC4L platform includes a recommendation component. This component collects information from different sources available (directly from sensors, cognitive games, questionnaires, and the multimodal fusion engine), and under clinical and professional guidance, after evaluating the potential improvement or worsening of patients' conditions, issues personalized recommendations to address identified problems. The recommendations relate to the following areas: physical activities; sleep; cognitive; nutrition. These recommendations will generally be sent to the PC4L application on the patients' smartphone, where they will appear as pop-up notifications.

Control group, no use of PC4L solutions

Participants who will be monitored for the estabilished period of time, in the selected scenario (home, neurorehabilitation and daycare centers), and will only receive written recommendations

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

PC4L solutions

Two different versions of the PC4L system will be tested. A fully equipped version and a cloud-based system that requires only a smartphone and a wearable sensor (Fitbit Versa 2). 25% of participants will use the full system, the remaining 75% will use the cloud-based system. As part of the decision support system, the PC4L platform includes a recommendation component. This component collects information from different sources available (directly from sensors, cognitive games, questionnaires, and the multimodal fusion engine), and under clinical and professional guidance, after evaluating the potential improvement or worsening of patients' conditions, issues personalized recommendations to address identified problems. The recommendations relate to the following areas: physical activities; sleep; cognitive; nutrition. These recommendations will generally be sent to the PC4L application on the patients' smartphone, where they will appear as pop-up notifications.

Intervention Type DEVICE

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Patients with a clinical diagnosis of Parkinson's (Hoehn and Yahr between II and IV) or another parkinsonian syndrome, Alzheimer's disease, or another dementia
* 65 years of age or more
* Willingness to participate in the study
* Able and willing to provide informed consent or have a legal representative responsible for the signature

Exclusion Criteria

* Presence of fever and / or acute infection such as COVID19 / flu
Minimum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Asociación Parkinson Madrid

OTHER

Sponsor Role collaborator

Universität Münster

OTHER

Sponsor Role collaborator

Wohlfahrtswerk für Baden-Württemberg

UNKNOWN

Sponsor Role collaborator

Campus Neurológico Sénior

OTHER

Sponsor Role collaborator

Carol Davila University of Medicine and Pharmacy

OTHER

Sponsor Role collaborator

Spitalul Universitar de Urgență București

UNKNOWN

Sponsor Role collaborator

International Foundation for Integrated Care

UNKNOWN

Sponsor Role collaborator

Kineticos

UNKNOWN

Sponsor Role collaborator

Casa di Cura Privata del Policlinico SpA

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Elda Judica

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Casa di Cura del Policlinico

Milan, MI, Italy

Site Status

Countries

Review the countries where the study has at least one active or historical site.

Italy

References

Explore related publications, articles, or registry entries linked to this study.

Broese van Groenou MI, De Boer A. Providing informal care in a changing society. Eur J Ageing. 2016;13(3):271-279. doi: 10.1007/s10433-016-0370-7. Epub 2016 Apr 15.

Reference Type BACKGROUND
PMID: 27610055 (View on PubMed)

Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985 Mar-Apr;100(2):126-31.

Reference Type BACKGROUND
PMID: 3920711 (View on PubMed)

Chastin SF, Baker K, Jones D, Burn D, Granat MH, Rochester L. The pattern of habitual sedentary behavior is different in advanced Parkinson's disease. Mov Disord. 2010 Oct 15;25(13):2114-20. doi: 10.1002/mds.23146.

Reference Type BACKGROUND
PMID: 20721926 (View on PubMed)

Crizzle AM, Newhouse IJ. Is physical exercise beneficial for persons with Parkinson's disease? Clin J Sport Med. 2006 Sep;16(5):422-5. doi: 10.1097/01.jsm.0000244612.55550.7d.

Reference Type BACKGROUND
PMID: 17016120 (View on PubMed)

da Silva PG, Domingues DD, de Carvalho LA, Allodi S, Correa CL. Neurotrophic factors in Parkinson's disease are regulated by exercise: Evidence-based practice. J Neurol Sci. 2016 Apr 15;363:5-15. doi: 10.1016/j.jns.2016.02.017. Epub 2016 Feb 10.

Reference Type BACKGROUND
PMID: 27000212 (View on PubMed)

Fan X, Wang D, Hellman B, Janssen MF, Bakker G, Coghlan R, Hursey A, Matthews H, Whetstone I. Assessment of Health-Related Quality of Life between People with Parkinson's Disease and Non-Parkinson's: Using Data Drawn from the '100 for Parkinson's' Smartphone-Based Prospective Study. Int J Environ Res Public Health. 2018 Nov 13;15(11):2538. doi: 10.3390/ijerph15112538.

Reference Type BACKGROUND
PMID: 30428518 (View on PubMed)

Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, Hall K, Hasegawa K, Hendrie H, Huang Y, Jorm A, Mathers C, Menezes PR, Rimmer E, Scazufca M; Alzheimer's Disease International. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005 Dec 17;366(9503):2112-7. doi: 10.1016/S0140-6736(05)67889-0.

Reference Type BACKGROUND
PMID: 16360788 (View on PubMed)

GBD 2016 Parkinson's Disease Collaborators. Global, regional, and national burden of Parkinson's disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018 Nov;17(11):939-953. doi: 10.1016/S1474-4422(18)30295-3. Epub 2018 Oct 1.

Reference Type BACKGROUND
PMID: 30287051 (View on PubMed)

Hillman CH, Erickson KI, Kramer AF. Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci. 2008 Jan;9(1):58-65. doi: 10.1038/nrn2298.

Reference Type BACKGROUND
PMID: 18094706 (View on PubMed)

Hou L, Chen W, Liu X, Qiao D, Zhou FM. Exercise-Induced Neuroprotection of the Nigrostriatal Dopamine System in Parkinson's Disease. Front Aging Neurosci. 2017 Nov 3;9:358. doi: 10.3389/fnagi.2017.00358. eCollection 2017.

Reference Type BACKGROUND
PMID: 29163139 (View on PubMed)

Clarke A. Qualitative research: data analysis techniques. Prof Nurse. 1999 May;14(8):531-3.

Reference Type BACKGROUND
PMID: 10532026 (View on PubMed)

Kwakkel G, de Goede CJ, van Wegen EE. Impact of physical therapy for Parkinson's disease: a critical review of the literature. Parkinsonism Relat Disord. 2007;13 Suppl 3:S478-87. doi: 10.1016/S1353-8020(08)70053-1.

Reference Type BACKGROUND
PMID: 18267287 (View on PubMed)

Lauze M, Daneault JF, Duval C. The Effects of Physical Activity in Parkinson's Disease: A Review. J Parkinsons Dis. 2016 Oct 19;6(4):685-698. doi: 10.3233/JPD-160790.

Reference Type BACKGROUND
PMID: 27567884 (View on PubMed)

Lorenz K, Freddolino PP, Comas-Herrera A, Knapp M, Damant J. Technology-based tools and services for people with dementia and carers: Mapping technology onto the dementia care pathway. Dementia (London). 2019 Feb;18(2):725-741. doi: 10.1177/1471301217691617. Epub 2017 Feb 8.

Reference Type BACKGROUND
PMID: 28178858 (View on PubMed)

Melin J, Bonn SE, Pendrill L, Trolle Lagerros Y. A Questionnaire for Assessing User Satisfaction With Mobile Health Apps: Development Using Rasch Measurement Theory. JMIR Mhealth Uhealth. 2020 May 26;8(5):e15909. doi: 10.2196/15909.

Reference Type BACKGROUND
PMID: 32452817 (View on PubMed)

Petzinger GM, Fisher BE, McEwen S, Beeler JA, Walsh JP, Jakowec MW. Exercise-enhanced neuroplasticity targeting motor and cognitive circuitry in Parkinson's disease. Lancet Neurol. 2013 Jul;12(7):716-26. doi: 10.1016/S1474-4422(13)70123-6.

Reference Type BACKGROUND
PMID: 23769598 (View on PubMed)

Keus SH, Bloem BR, Hendriks EJ, Bredero-Cohen AB, Munneke M; Practice Recommendations Development Group. Evidence-based analysis of physical therapy in Parkinson's disease with recommendations for practice and research. Mov Disord. 2007 Mar 15;22(4):451-60; quiz 600. doi: 10.1002/mds.21244.

Reference Type BACKGROUND
PMID: 17133526 (View on PubMed)

Rabiee F. Focus-group interview and data analysis. Proc Nutr Soc. 2004 Nov;63(4):655-60. doi: 10.1079/pns2004399.

Reference Type BACKGROUND
PMID: 15831139 (View on PubMed)

Block VA, Pitsch E, Tahir P, Cree BA, Allen DD, Gelfand JM. Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review. PLoS One. 2016 Apr 28;11(4):e0154335. doi: 10.1371/journal.pone.0154335. eCollection 2016.

Reference Type BACKGROUND
PMID: 27124611 (View on PubMed)

Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006 Mar 14;174(6):801-9. doi: 10.1503/cmaj.051351.

Reference Type BACKGROUND
PMID: 16534088 (View on PubMed)

Judica E, Tropea P, Bouca-Machado R, Marin M, Calarota E, Cozma L, Badea R, Ahmed M, Brach M, Ferreira JJ, Corbo M. Personalized Integrated Care Promoting Quality of Life for Older People: Protocol for a Multicenter Randomized Controlled Trial. JMIR Res Protoc. 2023 Jul 24;12:e47916. doi: 10.2196/47916.

Reference Type DERIVED
PMID: 37486732 (View on PubMed)

Related Links

Access external resources that provide additional context or updates about the study.

https://bit.ly/2OS67E5

The future of healthcare in Europe

https://procare4life.eu/

ProCare4Life website

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

PC4L-Pilot3

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.