Yitong Huang
Feasibility and acceptability of an Internet of Things-enabled sedentary behavior intervention: mixed-methods study
Huang, Yitong; Benford, Steve; Price, Dominic; Li, Benqian; Blake, Holly
Authors
Professor STEVE BENFORD steve.benford@nottingham.ac.uk
DUNFORD CHAIR IN COMPUTER SCIENCE
Mr DOMINIC PRICE dominic.price@nottingham.ac.uk
RESEARCH FELLOW
Benqian Li
Professor HOLLY BLAKE holly.blake@nottingham.ac.uk
PROFESSOR OF BEHAVIOURAL MEDICINE
Abstract
Background:
Encouraging office workers to break up prolonged sedentary behavior (SB) at work with regular micro-breaks can be beneficial yet challenging. Internet of Things (IoT) offers great promise for delivering more subtle and hence acceptable behavior change interventions in the workplace. We have previously developed an IoT-enabled SB intervention, called WorkMyWay, by applying a combination of theory-informed and human-centered design approaches. As per the Medical Research Council(MRC)’s framework, for complex interventions like WorkMyWay, process evaluation in the feasibility phase can help establish the viability of novel modes of delivery, to clarify on mechanisms of impacts and to identify contextual factors that affect delivery and interplay with intervention mechanisms.
Objective:
To evaluate the feasibility and acceptability of the WorkMyWay intervention and its technological delivery system.
Methods:
The study was informed by the MRC guidance on process evaluations of complex interventions. A mixed-methods approach was adopted. A convenience sample of 15 office workers used WorkMyWay during work hours for six weeks. Questionnaires were administered before and after the intervention period to assess psychological variables theoretically aligned with SB. Behavioral and interactional data were obtained through the system database to determine adherence, quality of delivery, compliance, and behavioral outcomes. Semi-structured interviews were conducted at the end of the study and thematic analysis was performed.
Results:
All 15 participants completed the study and on average used the system for 25 tracking days (out of a possible 30 days; adherence = 83.3%). For compliance, participants responded to 38.5% of the prompts within 15 minutes. Although no significant changes were observed in either technology-captured or self-reported occupational sitting and physical activity (OSPA) (p>0.05), post-intervention improvements were significant in automaticity of regular break behaviors (t(14)=2.606, p=.021), retrospective memory of breaks (t(14)=7.926, p<.001) and prospective memory of breaks (t(14)=-2.661, p=.019). Qualitative data revealed favorable attitudes towards the intervention components despite compromised delivery resulting from data connection problems. A range of intended and unintended mechanisms of action were revealed, suggesting high promise for behavior change.
Conclusions:
It is acceptable and feasible to deliver a SB intervention with an IoT system that involves a wearable activity tracking device, an App and a digitally augmented everyday object (eg. cup). The object component is particularly suitable and promising for delivering Behavior Change Techniques (BCTs) like “action planning”, “conserve mental resources”, “prompts and cues”, “add objects to the environment”, “habit formation”, and potentially “social comparison”. More technological development and engineering work on WorkMyWay is warranted to improve delivery before proceeding to the evaluation phase of research.
Citation
Huang, Y., Benford, S., Price, D., Li, B., & Blake, H. (2023). Feasibility and acceptability of an Internet of Things-enabled sedentary behavior intervention: mixed-methods study. Journal of Medical Internet Research, 25, Article e43502. https://doi.org/10.2196/43502
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 23, 2023 |
Online Publication Date | Feb 27, 2023 |
Publication Date | Feb 27, 2023 |
Deposit Date | Jan 30, 2023 |
Publicly Available Date | Feb 27, 2023 |
Journal | Journal of Medical Internet Research |
Electronic ISSN | 1438-8871 |
Publisher | JMIR Publications |
Peer Reviewed | Peer Reviewed |
Volume | 25 |
Article Number | e43502 |
DOI | https://doi.org/10.2196/43502 |
Keywords | Health Informatics |
Public URL | https://nottingham-repository.worktribe.com/output/16790641 |
Publisher URL | https://www.jmir.org/2023/1/e43502 |
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