BackgroundPatellofemoral pain (PFP) is a prevalent condition in sports medicine, with rising incidence as sports competitions become increasingly popular. South Africa’s healthcare system faces substantial challenges in delivering rehabilitation services due to geographical constraints, limited resources including professional shortages, and inadequate access to specialised musculoskeletal care. This study evaluated the feasibility of implementing a hybrid telerehabilitation program combining face-to-face sessions with WhatsApp video consultations for managing PFP in South African runners.MethodsA feasibility case series was conducted with five runners aged 25–39 years with PFP duration ≥6 weeks, recruited from Johannesburg. The 6-week intervention comprised an initial in-person assessment, weekly WhatsApp video consultations, and bi-weekly face-to-face sessions. Primary feasibility outcomes included recruitment success, session adherence, and acceptability measured using the Telehealth Usability Questionnaire (TUQ). Secondary clinical outcomes assessed pain intensity (Numerical Pain Rating Scale) and functional status (Anterior Knee Pain Scale).ResultsRecruitment targets were fully achieved with 100% adherence to all scheduled sessions. Participants demonstrated high exercise compliance and good acceptability scores (mean TUQ 5.9/7), though participants expressed a preference for in-person consultations. Significant clinical improvements were observed, with pain scores decreasing from 3.8 to 0.6 and functional scores improving from 79.6 to 94.0 over six weeks.ConclusionHybrid telerehabilitation demonstrated feasibility and preliminary effectiveness for PFP management in South African runners, achieving excellent adherence rates and clinically meaningful improvements in pain and function. This approach shows promise for addressing healthcare delivery challenges in resource-constrained settings.
Advancing the adoption of oncology decision support tools in Europe: insights from CAN.HEAL
Effective cancer care increasingly depends on digital decision support tools (DSTs) to interpret complex clinical, molecular, and genomic data and guide personalised treatment decisions. However,


