Pain and physical activity variability in runners and non-runners with patellofemoral pain: A longitudinal study.

• Grant number: 24/00269-4
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: August 01, 2024
• End date: January 31, 2025
• Field of knowledge: Health Sciences - Physiotherapy and Occupational Therapy
• Principal Investigator: Ronaldo Valdir Briani
• Grantee: Júlia de Cássia Pinto da Silva
• Supervisor: Neal Robert Glaviano
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Institution abroad: University of Connecticut (UCONN), United States
• Associated to the scholarship: 23/07003-7 - Incidence of patellofemoral pain in the general adult population: A prospective multicenter study, BP.MS

Abstract

Patellofemoral pain (PFP) is one of the most common running-related knee injuries, while also affects one-quarter of the general population that are not runners. Pain intensity is highly variable in these individuals and fluctuates depending on the exposure to increased physical activity and pain-provoking tasks. Although previous literature has already hypothesized that exposure to physical activity plays an important role in pain intensity and variability in individuals with PFP, this has been poorly investigated so far. PFP is prevalent in physically active populations (e.g., runners), even though it is also common in individuals who are not as physically active as runners (e.g., general adult population). Investigating pain and physical activity variability in these two populations that suffer from PFP is warranted. Therefore, the aims of this study are to i) investigate how pain and physical activity vary during one week in runners and non-runners with PFP; and ii) investigate if physical activity level variability predicts pain variability in runners and non-runners with PFP. Men and women with PFP aged 18 to 35 years old will be recruited at Storrs-CT. Pain variability will be collected using a Numeric Pain Rating Scale (NPRS), while physical activity will be collected using digital accelerometers (Actigraph GT3X). Intraindividual variability indices for pain are the mean square of successive difference (MSSD) and probability of acute change (PAC). MSSD will be used as an index of intraindividual variability for physical activity as well. Latent growth curves (LGC) will be used for the modeling of trajectories over time and determining if changes in physical activity level can predict changes in pain. Group-based trajectory modeling (GBTM) will also be used to identify clusters of individuals that follow similar longitudinal trajectories.