Analysis of Musculoskeletal Pain Patterns in Adults and Demand for Physiotherapeutic Digital Intervention (Posture Correction and Matching) Applications
This study aims to investigate musculoskeletal pain patterns among adults and examine associations to provide basic data for expanding physical therapist-centered non-face-to-face rehabilitation platforms. This cross-sectional survey design targeted Korean adults who daily use smart devices, with data collected via a web-based survey from January 17 to 31, 2023. A 12-item questionnaire, validated through content validity index (CVI) review by three academic professors and two clinical experts, was developed to assess general characteristics, offline hospital use constraints, musculoskeletal discomfort patterns in specific body and joint areas, and digital intervention demand. Data from 234 respondents collected through snowball sampling were processed using multiple response analysis and Pearson's chi-square tests to identify correlations between demographic variables and healthcare needs. The results showed that shoulder pain was significantly more frequent in men and those in their 30s or older. Patients experiencing neck and waist pain strongly demanded matching with offline manual therapy experts beyond simply watching videos. Furthermore, time-pressed consumers preferred rehabilitation content in the form of micro-learning under 5 minutes. These findings suggest that digital healthcare platforms can serve as supplementary gateways connecting patients and therapists. However, as this study relies on self-reported questionnaires, the level of evidence is limited in supporting strong clinical recommendations. Future randomized controlled trials are required to verify actual therapeutic effects, which will ultimately enable practical discussions on building a physical therapist-centered non-face-to-face rehabilitation ecosystem.
목차
Abstract Ⅰ. Introduction Ⅱ. Methods 1. Study design 2. Subjects and samplin 3. Measurement tools 4. Data Analysis Ⅲ. Results 1. General characteristics of study subjects and offline use constraints Ⅳ. Discussion 1. Significant differences in shoulder jointpain according to gender and age: Biomechanical and degenerative factors 2. Micro-learning based on motor learning to overcome time limits 3. Clinical severity of pain and justification for O2O manual therapy matching 4. Research limitations and suggestions Ⅴ. Conclusion References