Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability of these tasks in 262 PD participants and 50 controls by evaluating machine learning models based on wearable-sensor-derived measures and statistical metrics. This evaluation examines total duration, subtask duration, and other quantitative measures across two trials.

Optimizing public private partnerships to support clinical cancer research.

Public-private partnerships (PPPs) in cancer research have emerged as a pivotal model in the development of strategies to rapidly advance therapeutic innovations. The collaboration between public entities, such as government agencies and research institutions, and private entities, including pharmaceutical and biotechnology companies, as well as nonprofit organizations, brings together diverse expertise, resources, and perspectives to address the challenges of efficient drug development and equitable care delivery. This synergy has the potential to accelerate the translation of basic research findings into tangible clinical applications.

The Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT) intervention: A personalized approach to dementia risk reduction.

Background: Addressing modifiable risk factors such as physical inactivity and social isolation could reduce risk of Alzheimer's disease and all-cause dementia, but little is known about which factors individuals are most willing to address or how they prefer to address them.

Objective: To examine and describe behavior change goals set by participants during the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT).

Methods: In SMARRT, older adults worked with a health coach and nurse over 2 years to set incremental, personalized goals to reduce dementia risk.

Using the Translational Science Benefits Model to assess the impact of the Penn Implementation Science Center in Cancer Control.

Traditional approaches for evaluating the impact of scientific research - mainly scholarship (i.e., publications, presentations) and grant funding - fail to capture the full extent of contributions that come from larger scientific initiatives.

Understanding Goal Setting and Behavior Change Mechanics in an Older Adult Sitting Reduction Intervention.

Purpose: We explored intervention fidelity, participant satisfaction, and the goals and reminder strategies participants chose to reduce sitting.

Approach: Mixed methods approach leveraging data collected during study coaching and fidelity monitoring.

Setting: A successful 6-month randomized controlled trial of a sedentary behavior (SB) intervention for adults ≥60 years in Washington, USA.