Test-Retest Reliability and Responsiveness of the Machine Learning-Based Short-Form of the Berg Balance Scale in Persons With Stroke

Po-Ting Chen; I-Ping Hsueh; Shih-Chie Lee; Meng-Lin Lee; Chih-Wen Twu; Ching-Lin Hsieh

doi:10.1016/j.apmr.2024.10.013

Test-Retest Reliability and Responsiveness of the Machine Learning-Based Short-Form of the Berg Balance Scale in Persons With Stroke

Arch Phys Med Rehabil. 2024 Nov 9:S0003-9993(24)01319-4. doi: 10.1016/j.apmr.2024.10.013. Online ahead of print.

Authors

Po-Ting Chen¹, I-Ping Hsueh², Shih-Chie Lee³, Meng-Lin Lee⁴, Chih-Wen Twu⁵, Ching-Lin Hsieh⁶

Affiliations

¹ Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan; School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan.
² School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Taipei, Taiwan.
³ School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan.
⁴ Division of Cardiovascular Surgery, Department of Surgery, Cathay General Hospital, Taipei, Taiwan; School of Medicine, National Tsing Hua University, Hsinchu, Taiwan.
⁵ Department of Otorhinolaryngology-Head and Neck Surgery, Changhua Christian Hospital, Changhua, Taiwan; Department of Quality Management, Changhua Christian Hospital, Changhua, Taiwan; Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan. Electronic address: [email protected].
⁶ School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Taipei, Taiwan; Department of Occupational Therapy, College of Medical and Health Sciences, Asia University, Taichung, Taiwan.

PMID: 39522673
DOI: 10.1016/j.apmr.2024.10.013

Abstract

Objective: To examine the test-retest reliability, responsiveness, and clinical utility of the machine learning-based short form of the Berg Balance Scale (BBS-ML) in persons with stroke.

Design: Repeated-measures design.

Setting: A department of rehabilitation in a medical center.

Participants: This study recruited 2 groups: 50 persons who were more than 6 months post-stroke to examine the test-retest reliability, and 52 persons who were within 3 months post-stroke to examine the responsiveness. Test-retest reliability was investigated by administering assessments twice at a 2-week interval. Responsiveness was investigated by gathering data at admission and discharge from the hospital.

Interventions: Not applicable.

Main outcome measure: BBS-ML.

Results: The BBS-ML exhibited excellent test-retest reliability (intraclass correlation coefficient=0.99), acceptable minimal random measurement error (minimal detectable change %=13.6%), and good responsiveness (Kazis' effect size and standardized response mean values≥1.34). On average, the participants completed the BBS-ML in around 6 minutes per administration.

Conclusions: Our findings indicate that the BBS-ML appears an efficient measure with excellent test-retest reliability and responsiveness. Moreover, the BBS-ML may be used as a substitute for the original BBS to monitor the progress of balance function in persons with stroke.

Keywords: Berg Balance Scale; Clinical utility; Machine learning; Rehabilitation; Responsiveness; Stroke; Test–retest reliability.