<abstract> <p>Occupational sedentariness is problematic for office-based workers because of their prolonged sitting periods and the advent of technology which reduces work-based movement. A common workplace strategy to deal with this preventable health risk is to have workers engage in brief movement breaks throughout the workday. To date, the use of interventions underpinned by individual self-regulation has had less than optimal impact on changing workers sedentary work behaviours. An alternative design for workplace interventions is the use of nudge theory. Nudge theory incorporates strategies that are delivered at the point of choice designed to influence individual decision making regarding alternative behaviour options. In this study, desk-based workers were exposed to two nudge strategies which suggested alternative behaviours of regular standing and taking movement breaks during work periods to the default behaviours of prolonged sitting and sedentary work behaviour. A small group of women managers who served as peer champions (n = 6), withdrew early from the study, and then took part in an exit interview to gain an understanding of their experiences of being exposed to the two nudge strategies. Verbatim transcripts were analysed using inductive, reflexive thematic analysis. Two major themes with seven second order themes central to their experiences were extracted: facilitative behaviour and feelings (advocacy, acceptance & facilitative burden) and dysfunctional behaviours and feelings (dysfunctional behaviour & feelings, control, reactance & presenteeism). Participants initially perceived a positive exchange associated with exposure to nudge strategies. Yet, participants' emotional connection to their work roles and behaviour were perceived as a negative exchange. Participants cited numerous maladaptive feelings because of a perception of incongruency with the established work normative behaviour. These findings reveal that nudge strategies of reduced choice and social norms are viable, but perceptions of monitoring can moderate adherence.</p> </abstract>
Smart workplace Internet of Things (IoT) solutions rely on several sensors deployed efficiently in the workplace environment to collect accurate data to meet system goals. A vital issue for these sensor-based IoT solutions is privacy. Ideally, the occupants must be monitored discreetly, and the strategies for maintaining privacy are dependent on the nature of the data required. This paper proposes a new sensor design approach for IoT solutions in the workplace that protects occupants’ privacy. We focus on a novel sensor that autonomously detects and captures human movements in the office to monitor a person’s sedentary behavior. The sensor guides an eHealth solution that uses continuous feedback about desk behaviors to prompt healthy movement breaks for seated workers. The proposed sensor and its privacy-preserving characteristics can enhance the eHealth solution system’s performance. Compared to self-reporting, intrusive, and other data collection techniques, this sensor can collect the information reliably and timely. We also present the data analysis specific to this new sensor that measures two physical distance parameters in real-time and uses their difference to determine human actions. This architecture aims to collect precise data at the sensor design level rather than to protect privacy during the data analysis phase.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.