Clinical trial NCT06094374: Unveiling the Digital Phenotype of PA Behavior
Official title: Unveiling the Digital Phenotype: A Protocol for a Prospective Study on Physical Activity Behavior in Community-dwelling Older Adults
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Physical Activity - Digital Phenotyping - Activity Tracking
Lead sponsor: PXL University College
Sponsor class: OTHER
Collaborators: name: Hasselt University
First posted: 2023-10-23
Enrollment: 200
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Observational model: COHORT
Time perspective: OTHER
Sampling method: PROBABILITY_SAMPLE
Study population: Healthy Community Dwelling older adults aged 65 years or more

Brief 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. 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.

Eligibility criteria: Inclusion Criteria:

* 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

Exclusion Criteria:

* 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,

Primary outcomes:
measure: Digital phenotypes of PA
timeFrame: 14 days
Secondary outcomes:
Other outcomes:
Locations:
Study officials:
affiliation: PXL University College of Applied Sciences and Arts
name: Kim Daniels, MS
role: PRINCIPAL_INVESTIGATOR
References: