Physical Activity - Digital Phenotyping - Activity TrackingMIADPNCT06094374
Unveiling the Digital Phenotype of PA Behavior
An observational study of Physical Activity - Digital Phenotyping - Activity Tracking, run by PXL University College.
Trial summary
Observational data from healthy adults aged 65+ will be collected through cross-sectional and longitudinal methods to analyze physical activity patterns, identifying digital phenotypes. Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Physical Activity - Digital Phenotyping - Activity Tracking
- What is being tested?
- observation of physical activity behavior
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 200 participants
- Where
- No sites listed yet
- Study dates
- 15 Jan 2024to 15 Jan 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- Older adult
Study population: Healthy Community Dwelling older adults aged 65 years or more
Who may be able to join
- Participants are 65 years of older
- Participants are competent to give informed consent
- Participants are able to actively participate in the study
- Participants are community-dwelling (living independent at home or in a service apartment)
- Without a severe illness
- Dutch language proficiency as native speaker
Who cannot join
- Current neurological disorder such as Parkinson's disease, multiple sclerosis, cerebrovascular accident, …
- Current cardiovascular disorder such as stroke, acute myocardial infarct, coronary artery bypass grafting, percutaneous coronary intervention less than 5 years ago
- Current respiratory disorder, such as chronic obstructive pulmonary disease, pneumonia, pulmonary fibrosis, asthma, …
- Current severe metabolic disorder, such as diabetes type 1 and 2, severe osteoporosis, …
- Current severe cognitive disorders, such as Alzheimer's disease, vascular dementia, Lewy Body dementia, frontotemporal dementia,
Trial locations and contacts
No sites are listed yet.
About this study
Official title: Unveiling the Digital Phenotype: A Protocol for a Prospective Study on Physical Activity Behavior in Community-dwelling Older Adults
Observational data from healthy adults aged 65+ will be collected through cross-sectional and longitudinal methods to analyze physical activity patterns, identifying digital phenotypes. Measurements include self-reports, clinical assessments, and EMA, with statistical analysis using multivariate regression and time series analysis, and a neural network if needed to find digital phenotypes related to physical activity in older adults.
Read the detailed description
Observational data will be collected in healthy older adults aged 65 or above combining both cross-sectional and longitudinal data collection methods to analyze patterns of PA behavior and identify prognostic factors affecting PA outcomes in order to identify digital phenotypes related to PA.
The measurements are based on the Behavioral Change Wheel and include self-reporting assessments, clinical assessments for cross-sectional data collection and ecological momentary assessment (EMA) as well as time series data collection for longitudinal data. The statistical analysis will involve multivariate regression analysis and time series analysis, with a Bonferroni correction to account for multiple comparisons. A machine learning algorithm is used due to the complexity of the data. If no suitable model is found, a neural network will be used to determine digital phenotypes related to PA behavior in older adults.
- Being tested
- observation of physical activity behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
observation of physical activity behaviorBehavioural
An observational study will be conducted to gather data on multiple levels aiming to identify diverse digital phenotypes related to PA behavior among community-dwelling older adults.
A hybrid approach will be employed, combining both cross-sectional and longitudinal data collection methods. The overall aim is to employ data analysis to identify patterns of PA - behavior (referred to as phenotypes) and to pinpoint prognostic factors that affect PA outcomes.
This integrated strategy will be complemented by four distinct measurement approaches, ensuring a comprehensive assessment of the research objectives. These measurement approaches include:self-reporting, clinical, ecological momentary and time series assessment.
| Study group | Role | What they receive |
|---|---|---|
| Community Dwellling Healthy Older Adults | * 65 years or older
* able to give informed consent
* community dwelling
* no severe illness (neurological, cardiovascular, respiratory, metabolic, cognitive disorder)
* dutch language profiency Receives: Behavioral: observation of physical activity behavior |
What is being measured
The primary outcome is the main question the study is designed to answer.
Digital phenotypes of PA
Patterns of physical activity behavior
Measured: 14 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Oct 2023
- Study start15 Jan 2024 (estimated)
- Primary completion30 Jan 2024 (estimated)
- Study completion15 Jan 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Physical Activity - Digital Phenotyping - Activity TrackingStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- PXL University College
- Sponsor type
- University, hospital or other
- Collaborators
- Hasselt University
- Responsible party
- Sponsor
- Investigators
- Kim Daniels, MS, Principal investigator, PXL University College of Applied Sciences and Arts
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06094374
- Sponsor's protocol ID
- MIADP
- Acronym
- MIADP
- Status last verified
- Oct 2023
- First submitted
- 17 Oct 2023
- Last updated
- 23 Oct 2023
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Daniels K, Vonck S, Robijns J, Spooren A, Hansen D, Bonnechere B. Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol. BMJ Open. 2025 May 24;15(5):e095769. doi: 10.1136/bmjopen-2024-095769.
PubMed 40413040
Study at a glance
From the registry record, last updated by the sponsor on 23 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Unveiling the Digital Phenotype: A Protocol for a Prospective Study on Physical Activity Behavior in Community-dwelling Older Adults
- ClinicalTrials.gov ID
- NCT06094374
- Acronym / sponsor ID
- MIADP / MIADP
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- PXL University CollegeUniversity, hospital or other
- Collaborators
- Hasselt University
- Study start
- 15 Jan 2024 (estimated)
- Primary completion
- 30 Jan 2024 (estimated)
- Study completion
- 15 Jan 2025 (estimated)
- First posted
- 23 Oct 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Observational data from healthy adults aged 65+ will be collected through cross-sectional and longitudinal methods to analyze physical activity patterns, identifying digital phenotypes. Measurements include self-reports, clinical assessments, and EMA, with statistical analysis using multivariate regression and time series analysis, and a neural network if needed to find digital phenotypes related to physical activity in older adults.
Detailed description
Observational data will be collected in healthy older adults aged 65 or above combining both cross-sectional and longitudinal data collection methods to analyze patterns of PA behavior and identify prognostic factors affecting PA outcomes in order to identify digital phenotypes related to PA.
The measurements are based on the Behavioral Change Wheel and include self-reporting assessments, clinical assessments for cross-sectional data collection and ecological momentary assessment (EMA) as well as time series data collection for longitudinal data. The statistical analysis will involve multivariate regression analysis and time series analysis, with a Bonferroni correction to account for multiple comparisons. A machine learning algorithm is used due to the complexity of the data. If no suitable model is found, a neural network will be used to determine digital phenotypes related to PA behavior in older adults.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Community Dwellling Healthy Older Adults | – | Behavioral: observation of physical activity behavior* 65 years or older * able to give informed consent * community dwelling * no severe illness (neurological, cardiovascular, respiratory, metabolic, cognitive disorder) * dutch language profiency |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Age groups
- Older adult
- Study population
- Healthy Community Dwelling older adults aged 65 years or more
Key inclusion criteria (6 listed)
- Participants are 65 years of older
- Participants are competent to give informed consent
- Participants are able to actively participate in the study
- Participants are community-dwelling (living independent at home or in a service apartment)
- Without a severe illness
Key exclusion criteria (5 listed)
- Current neurological disorder such as Parkinson's disease, multiple sclerosis, cerebrovascular accident, …
- Current cardiovascular disorder such as stroke, acute myocardial infarct, coronary artery bypass grafting, percutaneous coronary intervention less than 5 years ago
- Current respiratory disorder, such as chronic obstructive pulmonary disease, pneumonia, pulmonary fibrosis, asthma, …
- Current severe metabolic disorder, such as diabetes type 1 and 2, severe osteoporosis, …
- Current severe cognitive disorders, such as Alzheimer's disease, vascular dementia, Lewy Body dementia, frontotemporal dementia,
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| observation of physical activity behaviorAn observational study will be conducted to gather data on multiple levels aiming to identify diverse digital phenotypes related to PA behavior among community-dwelling older adults. A hybrid approach will be employed, combining both cross-sectional and longitudinal data collection methods. The overall aim is to employ data analysis to identify patterns of PA - behavior (referred to as phenotypes) and to pinpoint prognostic factors that affect PA outcomes. This integrated strategy will be complemented by four distinct measurement approaches, ensuring a comprehensive assessment of the research objectives. These measurement approaches include:self-reporting, clinical, ecological momentary and time series assessment. | Behavioural | Community Dwellling Healthy Older Adults |
Primary outcome
Digital phenotypes of PA
Time frame: 14 days
Patterns of physical activity behavior
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Oct 2023.
- Derived from this study: PubMed 40413040Daniels K, Vonck S, Robijns J, Spooren A, Hansen D, Bonnechere B. Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol. BMJ Open. 2025 May 24;15(5):e095769. doi: 10.1136/bmjopen-2024-095769.
- Individual participant dataSharing planned: Undecided
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Kim Daniels, MS principal investigator
PXL University College of Applied Sciences and Arts
Questions about this trial
What is this clinical trial studying?
An observational study of Physical Activity - Digital Phenotyping - Activity Tracking, run by PXL University College.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 23 Oct 2023. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Kim Daniels, MS (0032485763451, kim.daniels@pxl.be), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Digital phenotypes of PA (time frame: 14 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06094374, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Oct 2023.