Author(s): CHIU, Y., TIEN, T., SUNG, W., Institution: NATIONAL CHENG KUNG UNIVERSITY, Country: TAIWAN, Abstract-ID: 220

INTRODUCTION:
Shoulder pain is among the most common musculoskeletal disorders, and evidence-based practice supports physical therapy as an effective management approach. However, accurate shoulder assessment requires integration of multiple examination findings to establish differential diagnoses and guide interventions. Incomplete or delayed diagnostic reasoning may contribute to persistent pain and suboptimal recovery. With advances in mobile technology, digital clinical tools may help standardize assessment workflows and improve clinical efficiency. This study aimed to develop a smart technology–based shoulder assessment support system and to preliminarily evaluate its usability for orthopedic physical therapy practice.
METHODS:
The system was developed using Xcode 16.1 and Swift with a storyboard interface. The assessment framework was based on Orthopedic Physical Assessment (Magee, 2014) and included history taking, pain assessment (VAS), observation, range of motion, resisted and joint play tests, neurological examination, palpation, special tests, and functional questionnaires (Chinese versions of SPADI, DASH, and SF-36). Core functions comprised (1) encrypted user accounts, (2) automatic patient record generation, and (3) guided documentation forms with embedded clinical references. Five licensed physical therapists (2 males, 3 females) participated in usability testing. After a 20-minute training session, each therapist independently completed a standardized simulated case. Task completion time, errors/corrections, and System Usability Scale (SUS) scores were recorded, along with qualitative feedback.
RESULTS:
All participants completed the simulation successfully. Mean completion time was 21 min 51 s (range 14:35–35:30), including an average of 3 min 38 s spent on corrections. The mean SUS score was 71.0 ± 24.2, exceeding the commonly used benchmark score of 68 and indicating acceptable usability. Qualitative feedback suggested that the system’s structure and workflow were clear and logical, although minor navigation issues were reported.
CONCLUSION:
The usability findings suggest that this smart technology–based system can support a structured, evidence-aligned shoulder assessment process and may enhance documentation consistency and clinical training efficiency. The relatively wide variability in SUS scores and the navigation comments indicate opportunities for interface refinement. Limitations include the small sample size and the use of a simulated case, which may not fully reflect real-world clinical complexity and time constraints. Future work should incorporate interative UI improvements and evaluate performance in clinical settings, including impacts on assessment completeness, decision-making consistency, and time efficiency. Overall, the developed system demonstrates promising clinical and educational value as an intelligent assistive tool for students, novice therapists, and practicing clinicians.