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Further development and acceptability of a Sensorbased Movement Analysis Feedback Toolkit (SMAFT) for physiotherapy rehabilitation of people with knee pain

Felemban, Mohannad 2022. Further development and acceptability of a Sensorbased Movement Analysis Feedback Toolkit (SMAFT) for physiotherapy rehabilitation of people with knee pain. PhD Thesis, Cardiff University.
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Background: Chronic knee pain is a common clinical symptom presented by individuals with musculoskeletal conditions. Chronic knee pain can have several significant physical and functional impacts on individuals, potentially resulting in reduced effectiveness of physiotherapy treatments and a lower quality of life. Limitations in functionality of the knee joint and physical activity may result from the alterations in movement presented in individuals with knee pain when performing everyday functional activities, as suggested by the pain adaptation theory. This theory proposes that unnecessary altered movement patterns can endure long-term, resulting in further pain and functional restrictions. Therefore, physiotherapy rehabilitation designed for individuals with knee pain should consider unnecessary altered movement patterns, by identifying and individualising treatments accordingly. This suggests a need for a portable clinic-based movement analysis system. Inertial measurement sensors could represent a promising movement analysis system within clinical practice, offering feedback about individuals’ kinematics and targeting treatment. Moreover, reporting and interpreting the huge volume of kinematic data provided by a three-dimensional (3D) movement analysis system is subjective and varied among its users, which might restrict its clinical access and utility. To eliminate this limitation, standardising the way of interpreting kinematic data designed in a user-friendly format is needed, which can enhance accuracy and consistency among users. Therefore, the aim of this PhD thesis is to further develop and evaluate the acceptability of a sensor-based movement analysis feedback toolkit (SMAFT) for clinical practice using an iterative process. Methods: This PhD thesis was undertaken in two phases. In the first phase, an exploratory study was conducted to inform the development of SMAFT. The study aimed to create a standardised reporting framework designed to improve clinicians’ accuracy and consistency when interpreting the kinematic data provided by a sensorbased movement analysis. Six raters, each with varying levels of experience in musculoskeletal clinical practice and movement analysis, were identified as participants. The raters interpreted 252 kinematic waveform graphs by identifying the presence of the altered movement patterns and describing them in writing. Withinand between-rater agreements were quantified using the observed agreement and Gwet's agreement coefficient, and the qualitative descriptions of the movement alterations were analysed using quantitative content analysis. This study was integrated with other developmental studies conducted by another PhD student to inform the development of a preliminary version of SMAFT. In the second phase, a mixed-methods case study was implemented to explore the acceptability of SMAFT when used alongside physiotherapy treatment as usual for individuals with knee pain within the physiotherapy clinical practice. The data was collected from multiple sources. Qualitative interviews for SMAFT’s users (individuals II with knee pain and clinicians) were analysed by employing a thematic analysis. Furthermore, quantitative descriptions of the individuals’ pain and function levels, their altered movement patterns identified, and their treatments given by clinicians were conducted. Results: In Phase one, the average score for the between-raters agreement when identifying the altered movement patterns was substantial (Gwet’s AC1 = 0.64) for all kinematic waveform graphs across all the lower limb joints, planes of movement, and functional tasks. The within-rater agreement presented a range from substantial to almost perfect agreement (Gwet’s AC1 = 0.70 – 0.99) across all the waveform graphs and over all joints, planes, and tasks. However, the way in which raters described and interpreted the identified movement alterations varied. Thus, a reporting template was created to standardise the process of interpreting the waveform graphs. The findings from this study were combined with other developmental studies to inform the development of a preliminary version of SMAFT that consists of portable inertial sensors, a movement analysis feedback report, avatar videos, and a standardised reporting template. This was used in Phase 2 to explore its acceptability among users within physiotherapy clinical practice. In phase two, integrating quantitative and qualitative components gave a more comprehensive view of SMAFT’s acceptability within clinical practice. The study’s findings suggested that the users showed broad acceptability towards the use of SMAFT alongside physiotherapy treatment from the perspective of being beneficial, practical, and usable. However, some challenges regarding its usability and practicality were identified. The findings afforded a clearer understanding of the design and delivery of SMAFT within clinical practice, which requires further refinements and investigations. Conclusion: The findings from the two phases of this PhD thesis contributed to the development of SMAFT to be used alongside physiotherapy treatment as usual for individuals with knee pain within clinical practice. A refined version of SMAFT was clearly described using the Template for Intervention Description and Replication (TIDier) checklist. Recommendations for the next stage of SMAFT development were also discussed.

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Healthcare Sciences
Date of First Compliant Deposit: 9 November 2023
Last Modified: 09 Nov 2023 11:00

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