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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jul 14, 2023
Date Accepted: Nov 9, 2023

The final, peer-reviewed published version of this preprint can be found here:

Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals

Lu Z, Signer T, Sylvester R, Gonzenbach R, von Wyl V, Haag C

Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals

JMIR Mhealth Uhealth 2023;11:e50729

DOI: 10.2196/50729

PMID: 38064263

PMCID: 10746974

Implementation of remote activity sensing to support a rehabilitation aftercare program: Results from an observational mixed-methods study with patients and healthcare professionals

  • Ziyuan Lu; 
  • Tabea Signer; 
  • Ramona Sylvester; 
  • Roman Gonzenbach; 
  • Viktor von Wyl; 
  • Christina Haag

ABSTRACT

Background:

Previous studies have shown that physical activity is beneficial for maintaining the quality of life of patients with complex chronic conditions such as multiple sclerosis or cardiovascular diseases. Therefore, promoting physical activity has become state-of-the-art in neurorehabilitation. However, improvements in daily activity and physical fitness achieved during rehabilitation are often difficult to maintain in daily life. The novel program ‘Stay with it’ is designed to promote regular exercise after a rehabilitation stay by developing and cultivating self-monitoring skills and habits.

Objective:

The objective of this study was to explore the potential of consumer-grade activity sensors to support a routine aftercare program that aims to facilitate the integration of skills acquired during inpatient stays into individuals’ daily lives.

Methods:

Participants were individuals with chronic diseases or such with risk for chronicity and recruited at the Valens Rehabilitation Centre, Switzerland, which specializes in neurorehabilitation. A baseline assessment prior to program participation was followed by an end-of-rehabilitation assessment and a 3-month follow-up. We used a mixed methods approach consisting of standardized questionnaires, activity sensor data, and open-ended questions to explore experiences and needs of program participants. Healthcare professionals completed open-ended, free-text questions. The open-ended questions were derived from the Normalization Process Theory framework to identify mechanisms that facilitate or hinder the implementation of the program into routine clinical care. We further used descriptive visual and statistical methods to analyze activity sensor data and factors associated with study completion.

Results:

A total of 23 participants and 13 healthcare professionals were included. At 3-month follow-up, 11 out of 15 participants (73%) who agreed to activity sensing found both the 'Stay with it' program and the activity sensor to be facilitating physical activity at home and helpful in goal attainment. Participants with higher levels of physical activity at baseline were more likely to perceive an activity tracker as beneficial and to remain active at home compared to those with lower activity levels at baseline. Importantly, dropout was mostly preceded by physical decline, and the activity tracker and study assessment were then perceived as frustrating because they emphasized involuntary reductions in physical activity.

Conclusions:

Our work also highlights the importance of considering the experiences of healthcare professionals when implementing novel measurement devices (such as activity trackers) and novel interventions into routine care. Our analysis also highlights the need to consider patients' individual needs in order to provide optimal support in maintaining physical activity. Furthermore, during periods of physical decline, activity sensors may be perceived as frustrating as they quantify decline and different measures of support may be needed to re-engage in physical activity. Clinical Trial: https://www.clinicaltrials.gov/study/NCT05243407


 Citation

Please cite as:

Lu Z, Signer T, Sylvester R, Gonzenbach R, von Wyl V, Haag C

Implementation of Remote Activity Sensing to Support a Rehabilitation Aftercare Program: Observational Mixed Methods Study With Patients and Health Care Professionals

JMIR Mhealth Uhealth 2023;11:e50729

DOI: 10.2196/50729

PMID: 38064263

PMCID: 10746974

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