Process of change for people with knee osteoarthritis undergoing cognitive functional therapy: a replicated single-case experimental design study.

PURPOSE: To examine the applicability and process of change of Cognitive Functional Therapy (CFT) in the management of pain and disability in people with knee osteoarthritis who were offered knee replacement surgery and had risk factors for poor response to surgery. METHODS: Single-case experimental design with a mixed-methods, repeated measures approach was used to investigate the process of change through CFT in four participants. Qualitative interviews investigated beliefs, behaviours and coping responses, and self-reported measures assessed pain, disability, psychological factors, and function at 25 timepoints. Study registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12619001491156). RESULTS: Qualitative data indicate that CFT promoted helpful changes in all participants, with two responses observed. One reflected a clear shift to a biopsychosocial conceptualisation of osteoarthritis, behavioural re-engagement and the view that a knee replacement was no longer necessary. The other response reflected a mixed conceptualisation with dissonant beliefs about osteoarthritis and its management. Psychological and social factors were identified as potential treatment barriers. Overall, quantitative measures supported the qualitative findings. CONCLUSION: The process of change varies between and within individuals over time. Psychological and social barriers to treatment have implications for future intervention studies for the management of knee osteoarthritis.IMPLICATIONS FOR REHABILITATIONCognitive Functional Therapy is applicable in the management of knee osteoarthritis.Reconceptualisation of osteoarthritis reflected a helpful change.Psychological and social factors emerged as barriers to recovery.

Predicting Knee Joint Kinematics from Wearable Sensor Data in People with Knee Osteoarthritis and Clinical Considerations for Future Machine Learning Models.

Deep learning models developed to predict knee joint kinematics are usually trained on inertial measurement unit (IMU) data from healthy people and only for the activity of walking. Yet, people with knee osteoarthritis have difficulties with other activities and there are a lack of studies using IMU training data from this population. Our objective was to conduct a proof-of-concept study to determine the feasibility of using IMU training data from people with knee osteoarthritis performing multiple clinically important activities to predict knee joint sagittal plane kinematics using a deep learning approach. We trained a bidirectional long short-term memory model on IMU data from 17 participants with knee osteoarthritis to estimate knee joint flexion kinematics for phases of walking, transitioning to and from a chair, and negotiating stairs. We tested two models, a double-leg model (four IMUs) and a single-leg model (two IMUs). The single-leg model demonstrated less prediction error compared to the double-leg model. Across the different activity phases, RMSE (SD) ranged from 7.04° (2.6) to 11.78° (6.04), MAE (SD) from 5.99° (2.34) to 10.37° (5.44), and Pearson's R from 0.85 to 0.99 using leave-one-subject-out cross-validation. This study demonstrates the feasibility of using IMU training data from people who have knee osteoarthritis for the prediction of kinematics for multiple clinically relevant activities.

The Relationship Between Changes in Movement and Activity Limitation or Pain in People With Knee Osteoarthritis: A Systematic Review.

OBJECTIVE: To report whether changes in knee joint movement parameters recorded during functional activities relate to change in activity limitation or pain after an exercise intervention in people with knee osteoarthritis (OA). DESIGN: Etiology systematic review. LITERATURE SEARCH: Four databases (MEDLINE, Embase, CINAHL, and AMED) were searched up to January 22, 2021. STUDY SELECTION CRITERIA: Randomized controlled trials or cohort studies of exercise interventions for people with knee OA that assessed change in knee joint movement parameters (moments, kinematics, or muscle activity) and clinical outcomes (activity limitation or pain). DATA SYNTHESIS: A descriptive synthesis of functional activities, movement parameters, and clinical outcomes. RESULTS: From 3182 articles, 22 studies met the inclusion criteria, and almost all were of low quality. Gait was the only investigated functional activity. After exercise, gait parameters changed 26% of the time, and clinical outcomes improved 90% of the time. A relationship between group-level changes in gait parameters and clinical outcomes occurred 24.5% of the time. Two studies directly investigated an individual-level relationship, reporting only 1 significant association out of 8 correlations tested. CONCLUSION: Most studies reported no change in gait-related movement parameters despite improvement in clinical outcomes, challenging the belief that changing movement parameters is always clinically important in people with knee OA. J Orthop Sports Phys Ther 2021;51(10):492-502. doi:10.2519/jospt.2021.10418.

Human Activity Recognition for People with Knee Osteoarthritis-A Proof-of-Concept.

Clinicians lack objective means for monitoring if their knee osteoarthritis patients are improving outside of the clinic (e.g., at home). Previous human activity recognition (HAR) models using wearable sensor data have only used data from healthy people and such models are typically imprecise for people who have medical conditions affecting movement. HAR models designed for people with knee osteoarthritis have classified rehabilitation exercises but not the clinically relevant activities of transitioning from a chair, negotiating stairs and walking, which are commonly monitored for improvement during therapy for this condition. Therefore, it is unknown if a HAR model trained on data from people who have knee osteoarthritis can be accurate in classifying these three clinically relevant activities. Therefore, we collected inertial measurement unit (IMU) data from 18 participants with knee osteoarthritis and trained convolutional neural network models to identify chair, stairs and walking activities, and phases. The model accuracy was 85% at the first level of classification (activity), 89-97% at the second (direction of movement) and 60-67% at the third level (phase). This study is the first proof-of-concept that an accurate HAR system can be developed using IMU data from people with knee osteoarthritis to classify activities and phases of activities.

Does Movement Change When Low Back Pain Changes? A Systematic Review.

OBJECTIVE: To investigate the relationship between changes in volitional spinal movement (including muscle activity) and changes in pain or activity limitation at the individual level in people with nonspecific low back pain. DESIGN: Etiology systematic review. LITERATURE SEARCH: MEDLINE, Embase, CINAHL, and AMED were searched from inception to January 2020. STUDY SELECTION CRITERIA: The study included peer-reviewed articles that reported the relationship between changes in volitional spinal movement and changes in pain or activity limitation at the individual level in people with nonspecific low back pain. DATA SYNTHESIS: The data were descriptively synthesized to identify a relationship between change in movement and improved pain or activity limitation. RESULTS: We included 27 studies involving 2739 participants. There was low-quality evidence of a relationship between change in movement and change in pain or activity limitation at the individual level 31% of the time (20 of the 65 times investigated within the 27 studies). Increases in spinal range of motion, velocity, and flexion relaxation of the back extensors were consistently related to improved pain or activity limitation (93%, 18.5/20 relationships observed). CONCLUSION: A relationship between changes in movement and changes in pain or activity limitation was infrequently observed at the individual level; however, a paucity of high-quality evidence precludes a definitive understanding of this relationship. J Orthop Sports Phys Ther 2020;50(12):664-680. Epub 28 Oct 2020. doi:10.2519/jospt.2020.9635.

Implementation of Questionnaire-Based Risk Profiling for Clients in a Workers' Compensation Environment: An Example in Australian Physiotherapy Practice.

Purpose This study investigated the implementation of a risk profiling process for physiotherapy clients with a compensable musculoskeletal problem. Implementation targeted personal (clinician) and external (organisational) factors to facilitate behavioural change with regard to the use of formal, questionnaire-based risk profiling. Methods A theoretical construct was developed for formal questionnaire-based screening to be implemented across 12 private, metropolitan physiotherapy clinics. To target personal (clinician) factors, a multimodal educational procedure was developed focused on use of the ten-item Orebro Musculoskeletal Pain Screening Questionnaire (OMPSQ-10). To target external (organisational) factors, an administrative process was enacted to ensure routine completion of the OMPSQ-10 by compensable clients. Global practice behaviour with regard to the use of formal risk profiling was complete pre- and post-implementation. Results Pre-implementation physiotherapists understood the potential usefulness of formal risk profiling, but the large majority did not routinely have clients complete these types of questionnaires. Post-implementation there was a significant positive shift in behaviour to more frequent use the OMPSQ-10 for new compensable clients. Conclusions The results provide initial support for the use of a framework to develop an implementation strategy to increase physiotherapist adherence to the use of guideline recommended risk profiling questionnaires in clinical practice.