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Updated: Jun 30, 2025

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
Published on: November 8, 2013
Uncovering clinical rehabilitation technology trends: field observations, mixed methods analysis, and data
Objective:
To analyze real-world rehabilitation technology (RT) use, with a view toward enhancing RT development and adoption.
Design:
A convergent, mixed-methods study using direct field observations, semi-structured templates, and summative content analysis.
Setting:
Ten neurorehabilitation units in a single health system.
Participants:
3 research clinicians (1OT, 2PTs) observed ∼60 OTs and 70 PTs in inpatient; ∼18 OTs and 30 PTs in outpatient.
Interventions:
Not applicable.
Main Outcome Measures:
Characteristics of RT, time spent setting up and using RT, and clinician behaviors.
Results:
90 distinct devices across 15 different focus areas were inventoried. 329 RT-uses were documented over 44 hours with 42% of inventoried devices used. RT was used more during interventions (72%) than measurement (28%). Intervention devices used frequently were balance/gait (39%), strength/endurance (30%), and transfer/mobility training (16%). Measurement devices were frequently used to measure vitals (83%), followed by grip strength (7%), and upper extremity function (5%). Device characteristics were predominately AC-powered (56%), actuated (57%), monitor-less (53%), multi-use (68%), and required little familiarization (57%). Set-up times were brief (mean ± SD = 3.8±4.21 and 0.8±1.3 for intervention and measurement, respectively); more time was spent with intervention RT (25.6±15) than measurement RT (7.3±11.2). RT nearly always involved verbal instructions (72%) with clinicians providing more feedback on performance (59.7%) than on results (30%). Therapists' attention was split evenly between direct attention towards the patient during clinician treatment (49.7%) and completing other tasks such as documentation (50%).
Conclusions:
Even in a tech-friendly hospital, majority of available RT were observed un-used, but identifying these usage patterns is crucial to predict eventual adoption of new designs from earlier stages of RT development. An interactive data visualization page supplement is provided to facilitate this study.
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