NCT06094374

Unveiling the Digital Phenotype of PA Behavior

Unveiling the Digital Phenotype: A Protocol for a Prospective Study on Physical Activity Behavior in Community-dwelling Older Adults

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 200 (estimated)
• Sponsor: PXL University College · Academic / Other
• Sex: All
• Age: 65 Years
• Healthy volunteers: —

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.

Conditions

• Physical Activity - Digital Phenotyping - Activity Tracking

Interventions

Type	Name	Description
BEHAVIORAL	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.

Timeline

• Start date: 2024-01-15
• Primary completion: 2024-01-30
• Completion: 2025-01-15
• First posted: 2023-10-23
• Last updated: 2023-10-23