NCT05031299

Brief Summary

In GATEKEEPER intervention, Big Data Analytics techniques will be exploited to address risk stratification and early detection, based on lifestyles analysis including: pattern recognition for the improvement of public health surveillance and for the early detection of chronic conditions; data mining for inductive reasoning and exploratory data analysis; Cluster Analysis for identifying high-risk groups among elder citizens. In the above cases timely intervention is provided by through AI-based, digital coaches, structured conversations, consultation and education. The main target group (N=960) is older adults and elderly citizens with risk factors for MetS and their carers. Therefore, the GATEKEEPER intervention aims at primary (avoid occurrence of disease) and secondary (early detection and management) prevention of the ageing population at risk for MetS.

Trial Health

43
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
960

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Mar 2021

Geographic Reach
1 country

2 active sites

Status
unknown

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

March 1, 2021

Completed
5 months until next milestone

First Submitted

Initial submission to the registry

July 29, 2021

Completed
1 month until next milestone

First Posted

Study publicly available on registry

September 1, 2021

Completed
1.2 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 1, 2022

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2022

Completed
Last Updated

September 1, 2021

Status Verified

August 1, 2021

Enrollment Period

1.8 years

First QC Date

July 29, 2021

Last Update Submit

August 26, 2021

Conditions

Keywords

metabolic syndromelifestyle interventionpreventiondigital toolselderlyolder adults

Outcome Measures

Primary Outcomes (1)

  • Change in Waist circumference (cm) from baseline to 3 months

    Participants' waist circumference will be measured in triplicates (in cm) at baseline and at the 3rd month follow-up visit.

    baseline and monthly until 3-month follow-up

Secondary Outcomes (8)

  • Changes in body mass index (kg/m2) from baseline to 3 months

    baseline and monthly until 3-month follow-up

  • Changes in percentage of body fat from baseline to 3 months

    baseline and monthly until 3-month follow-up

  • Patient-reported outcome measures (PROMs)

    baseline and 3 months

  • Changes in Diet quality on FFQ and healthy diet score from baseline to 3 months

    baseline and 3 months

  • Changes in Quality of life on EQ5D (Generic HRQL) from baseline to 3 months

    baseline and 3 months

  • +3 more secondary outcomes

Study Arms (3)

Control group (Standard care)

ACTIVE COMPARATOR

Participants in the control group will receive only the standard care as provided by the local and national healthcare system as well as one face-to-face counselling session for lifestyle modification to improve their risk factors for 3 months.

Behavioral: Standard care

Intervention group 1 (Application)

EXPERIMENTAL

Participants will will be additionally provided with a health-promotion application for self-management for 3 months.

Behavioral: Health-promotion application for self-management

Intervention group 2 (Devices)

EXPERIMENTAL

Participants will be additionally provided with wearables and devices for 3 months including: * A weighing scale (assessing also body composition) device * A smartwatch/wristband to assess physical activity but also sleep pattern.

Device: Wearables and devices

Interventions

Standard careBEHAVIORAL

Participants will receive only the standard care as provided by the local and national healthcare system as well as one face-to-face counselling session for lifestyle modification to improve their risk factors.

Control group (Standard care)

Participants will be provided with a health-promotion application for self-management for 3 months, additionally to the standard care.

Intervention group 1 (Application)

Participants will be provided with wearables and devices, including a weighing scale (assessing also body composition) device and a smartwatch/wristband to assess physical activity but also sleep pattern, for 3 months, additionally to the standard care and the Health-promotion application.

Intervention group 2 (Devices)

Eligibility Criteria

Age55 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Males and females aged ≥55 years old
  • Having any of the following risk factors for MetS:
  • waist circumference \>94 cm for men and \>80 cm for women
  • Triglycerides (TG) ≥150 mg/dL
  • High-density lipoprotein cholesterol (HDL-C) \<40 mg/dL for men and \<50 mg/dL for women
  • Fasting glucose ≥100 mg/dL
  • Blood pressure ≥130 /≥85 mm Hg
  • Living at home (either alone or with relatives)
  • Informed consent form provided

You may not qualify if:

  • Having severe hearing or vision problems or any other acute or chronic condition that would limit the ability of the user to participate in the study
  • Having dementia or cognitive impairment
  • Being institutionalised
  • Participation in another research project

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

Harokopio University of Athens

Kallithea, Attica, 17671, Greece

RECRUITING

University of Thessaly

Trikala, 42132, Greece

RECRUITING

Related Publications (14)

  • Zimmet P, M M Alberti KG, Serrano Rios M. [A new international diabetes federation worldwide definition of the metabolic syndrome: the rationale and the results]. Rev Esp Cardiol. 2005 Dec;58(12):1371-6. No abstract available. Spanish.

    PMID: 16371194BACKGROUND
  • Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; Hational Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009 Oct 20;120(16):1640-5. doi: 10.1161/CIRCULATIONAHA.109.192644. Epub 2009 Oct 5.

    PMID: 19805654BACKGROUND
  • Martin-Timon I, Sevillano-Collantes C, Segura-Galindo A, Del Canizo-Gomez FJ. Type 2 diabetes and cardiovascular disease: Have all risk factors the same strength? World J Diabetes. 2014 Aug 15;5(4):444-70. doi: 10.4239/wjd.v5.i4.444.

    PMID: 25126392BACKGROUND
  • Saklayen MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep. 2018 Feb 26;20(2):12. doi: 10.1007/s11906-018-0812-z.

    PMID: 29480368BACKGROUND
  • Lesjak V, Stanojevic-Jerkovic O. Physical Activity, Sedentary Behavior and Substance Use among Adolescents in Slovenian Urban Area. Zdr Varst. 2015 Jun 9;54(3):168-74. doi: 10.1515/sjph-2015-0024. eCollection 2015 Sep.

    PMID: 27646724BACKGROUND
  • Scuteri A, Laurent S, Cucca F, Cockcroft J, Cunha PG, Manas LR, Mattace Raso FU, Muiesan ML, Ryliskyte L, Rietzschel E, Strait J, Vlachopoulos C, Volzke H, Lakatta EG, Nilsson PM; Metabolic Syndrome and Arteries Research (MARE) Consortium. Metabolic syndrome across Europe: different clusters of risk factors. Eur J Prev Cardiol. 2015 Apr;22(4):486-91. doi: 10.1177/2047487314525529. Epub 2014 Mar 19.

    PMID: 24647805BACKGROUND
  • Devers MC, Campbell S, Simmons D. Influence of age on the prevalence and components of the metabolic syndrome and the association with cardiovascular disease. BMJ Open Diabetes Res Care. 2016 Apr 25;4(1):e000195. doi: 10.1136/bmjdrc-2016-000195. eCollection 2016.

    PMID: 27158519BACKGROUND
  • Kraja AT, Borecki IB, North K, Tang W, Myers RH, Hopkins PN, Arnett D, Corbett J, Adelman A, Province MA. Longitudinal and age trends of metabolic syndrome and its risk factors: the Family Heart Study. Nutr Metab (Lond). 2006 Dec 5;3:41. doi: 10.1186/1743-7075-3-41.

    PMID: 17147796BACKGROUND
  • Athyros VG, Ganotakis ES, Bathianaki M, Monedas I, Goudevenos IA, Papageorgiou AA, Papathanasiou A, Kakafika AI, Mikhailidis DP, Elisaf M; MetS-Greece Collaborative Group. Awareness, treatment and control of the metabolic syndrome and its components: a multicentre Greek study. Hellenic J Cardiol. 2005 Nov-Dec;46(6):380-6.

    PMID: 16422124BACKGROUND
  • Park MJ, Kim HS. Evaluation of mobile phone and Internet intervention on waist circumference and blood pressure in post-menopausal women with abdominal obesity. Int J Med Inform. 2012 Jun;81(6):388-94. doi: 10.1016/j.ijmedinf.2011.12.011. Epub 2012 Jan 21.

    PMID: 22265810BACKGROUND
  • Konerding U, Elkhuizen SG, Faubel R, Forte P, Malmstrom T, Pavi E, Janssen MF. The validity of the EQ-5D-3L items: an investigation with type 2 diabetes patients from six European countries. Health Qual Life Outcomes. 2014 Dec 5;12:181. doi: 10.1186/s12955-014-0181-5.

    PMID: 25479769BACKGROUND
  • Kokaliari ED, Roy AW. Validation of the Greek translation of the multicultural quality of life index (MQLI-gr). Health Qual Life Outcomes. 2020 Jun 15;18(1):183. doi: 10.1186/s12955-020-01426-9.

    PMID: 32539776BACKGROUND
  • Liu D, Maimaitijiang R, Gu J, Zhong S, Zhou M, Wu Z, Luo A, Lu C, Hao Y. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) to Investigate the Intention to Use Physical Activity Apps: Cross-Sectional Survey. JMIR Mhealth Uhealth. 2019 Aug 22;7(9):e13127. doi: 10.2196/13127.

    PMID: 31507269BACKGROUND
  • Soldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria. J Psychosom Res. 2000 Jun;48(6):555-60. doi: 10.1016/s0022-3999(00)00095-7.

    PMID: 11033374BACKGROUND

MeSH Terms

Conditions

Metabolic Syndrome

Interventions

Standard of CareSelf-ManagementEquipment and Supplies

Condition Hierarchy (Ancestors)

Insulin ResistanceHyperinsulinismGlucose Metabolism DisordersMetabolic DiseasesNutritional and Metabolic Diseases

Intervention Hierarchy (Ancestors)

Quality Indicators, Health CareQuality of Health CareHealth Services AdministrationHealth Care Quality, Access, and EvaluationRehabilitationHealth ServicesHealth Care Facilities Workforce and Services

Study Officials

  • Odysseas Androutsos, PhD

    University of Thessaly

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Yannis Manios, PhD

CONTACT

Eva Karaglani, PhD-c

CONTACT

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
PREVENTION
Intervention Model
PARALLEL
Model Details: The present study is a cluster-randomized lifestyle intervention aimed at primary and secondary prevention of MetS, including three study arms: standard care (control group), standard care plus lifestyle application (intervention group 1) and standard care plus lifestyle application and wearables and devices (intervention group 2). It is conducted with older adults and elderly (aged ≥55 years old) living at home and at risk for MetS, as well as their carers. The total duration of the intervention for each participant will be 3 months.
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Professor

Study Record Dates

First Submitted

July 29, 2021

First Posted

September 1, 2021

Study Start

March 1, 2021

Primary Completion

December 1, 2022

Study Completion

December 1, 2022

Last Updated

September 1, 2021

Record last verified: 2021-08

Data Sharing

IPD Sharing
Will not share

Locations