Biopsychosocial Approach in Identifying Risk Factors of Kinesiophobia in Persons with Subacromial Pain Syndrome and Developing a Clinical Prediction Tool


Karartı C., Basat H. Ç., Özsoy İ., Özyurt F., Özsoy G., Kodak M. İ., ...More

Indian Journal of Orthopaedics, vol.57, no.1, pp.124-136, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 57 Issue: 1
  • Publication Date: 2023
  • Doi Number: 10.1007/s43465-022-00781-7
  • Journal Name: Indian Journal of Orthopaedics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, CINAHL
  • Page Numbers: pp.124-136
  • Keywords: Biopsychosocial models, Painful shoulder, Shoulder, Subacromial pain syndrome
  • Kayseri University Affiliated: No

Abstract

© 2022, Indian Orthopaedics Association.Introduction: Although the negative effects of kinesiophobia on functional status in subacromial pain syndrome (SAPS) patients are clearly demonstrated, no study examines the risk factors of kinesiophobia in individuals with SAPS from a biopsychosocial perspective. The present study aims to determine the risk factors of kinesiophobia in individuals with SAPS using a biopsychosocial approach. This study also aims to explore the compounding effects of multiple associative risk factors by developing a clinical prediction tool to identify SAPS patients at higher risk for kinesiophobia. Materials and methods: This cross-sectional study included 549 patients who were diagnosed with SAPS. The Tampa-Scale of Kinesiophobia (TSK) was used to assess kinesiophobia. Visual analog scale (VAS), The Shoulder Pain and Disability Index (SPADI), Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire, the presence of metabolic syndrome, using any non-steroidal anti-inflammatory drugs, Pain Catastrophizing Scale (PCS), Illness Perception Questionnaire-revised (IPQ-R), Hospital Anxiety and Depression Scale (HADS), behavioral pattern of the patient, sociodemographic characteristics, and treatment expectancy were outcome measures. Results: Thirteen significant risk factors of having kinesiophobia were: VASat rest (≥ 5.2), VASduring activity (≥ 7.1), DASH (≥ 72.1), presence of metabolic syndrome, PCShelplessness (≥ 16.1), IPQ-Rpersonal control (≤ 17.1), IPQ-Rtreatment control (≤ 16.3), HADSdepression (≥ 7.9), avoidance behavior type, being female, educational level (≤ high school), average hours of sleep (≤ 6.8), and treatment expectancy (≤ 6.6). The presence of seven or more risk factors increased the probability of having high level of kinesiophobia from 34.3 to 51%. Conclusions: It seems necessary to address these factors, increase awareness of health practitioners and individuals. Level of evidence: Level IV.