Factors influencing the clinical adoption of quantitative gait analysis technology with a focus on clinical efficacy and clinician perspectives: A scoping review.

ABSTRACT

INTRODUCTION: Quantitative gait analysis (QGA) has the potential to support clinician decision-making. However, it is not yet widely accepted in practice. Evidence for clinical efficacy (i.e., efficacy and effectiveness), as well as a users' perspective on using the technology in clinical practice (e.g., ease of use and usefulness) can help impact their widespread adoption. OBJECTIVE: To synthesize the literature on the clinical efficacy and clinician perspectives on the use of gait analysis technologies in the clinical care of adult populations. METHODS: This scoping review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews. We included peer-reviewed and gray literature (i.e., conference abstracts). A search was conducted in MEDLINE (Ovid), CENTRAL (Ovid), EMBASE (Ovid), CINAHL (EBSCO) and SPORTDiscus (EBSCO). Included full-text studies were critically appraised using the JBI critical appraisal tools. RESULTS: A total of 15 full-text studies and two conference abstracts were included in this review. Results suggest that QGA technologies can influence decision-making with some evidence to suggest their role in improving patient outcomes. The main barrier to ease of use was a clinician's lack of data expertise, and main facilitator was receiving support from staff. Barriers to usefulness included challenges finding suitable reference data and data accuracy, while facilitators were enhancing patient care and supporting clinical decision-making. SIGNIFICANCE: This review is the first step to understanding how QGA technologies can optimize clinical practice. Many gaps in the literature exist and reveal opportunities to improve the clinical adoption of gait analysis technologies. Further research is needed in two main areas 1) examining the clinical efficacy of gait analysis technologies and 2) gathering clinician perspectives using a theoretical model like the Technology Acceptance Model to guide study design. Results will inform research aimed at evaluating, developing, or implementing these technologies. FUNDING: This work was supported by the Walter and Maria Schroeder Institute for Brain Innovation and Recovery and AGE-WELL Graduate Student Award in Technology and Aging [2021,2022].