Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
200 participants
OBSERVATIONAL
2024-01-15
2025-01-15
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
OTHER
Study Groups
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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
observation of physical activity behavior
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.
Interventions
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observation of physical activity behavior
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.
Eligibility Criteria
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Inclusion Criteria
* 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
Exclusion Criteria
* 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,
65 Years
ALL
No
Sponsors
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Hasselt University
OTHER
PXL University College
OTHER
Responsible Party
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Principal Investigators
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Kim Daniels, MS
Role: PRINCIPAL_INVESTIGATOR
PXL University College of Applied Sciences and Arts
Central Contacts
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References
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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.
Other Identifiers
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MIADP
Identifier Type: -
Identifier Source: org_study_id
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