PhD defence J. (Jie) Deng

Below is a brief summary of the dissertation: 

Patellar tendinopathy is a common and often persistent knee condition, particularly affecting physically active individuals and athletes. Despite its prevalence, optimal management remains challenging and is frequently guided by imaging findings, physical tests, or emerging digital health tools.

This PhD thesis aimed to improve the management of patellar tendinopathy by focusing on patient education and by better understanding the response to exercise-based rehabilitation. First, the thesis examined whether an artificial intelligence–based tool (ChatGPT-4) could provide reliable patient education about patellar tendinopathy. The results showed that although such tools can generate extensive information, a large proportion of the content was inaccurate or outdated, emphasizing that healthcare professionals should remain the primary source of patient education.

Second, this thesis investigated whether commonly used physical tests and imaging findings could explain or predict treatment outcomes following exercise-based therapy. The findings demonstrated that these measures do not mediate treatment response nor predict long-term recovery.

Overall, this thesis concludes that effective management of patellar tendinopathy should rely on evidence-informed, individualized exercise-based rehabilitation and high-quality clinician-led patient education, rather than on imaging results, physical test outcomes, or independent use of AI-based tools.