An mHealth Workplace-Based “Sit Less, Move More” Program: Impact on Employees’ Sedentary and Physical Activity Patterns at Work and Away from Work

Abstract

Background: Most workplace interventions that aim to reduce sedentary behaviour have 38 focused on employees’ sedentary patterns at-work but less have focused on understanding the 39 impact beyond working time. The aim of this study was to evaluate the impact of a 13-week m-40 health workplace-based ‘sit less, move more’ intervention (Walk@WorkApp; W@W-App) on 41 physical activity (PA) and sitting in desk-based employees at-work and away from work. Methods: Participants (n = 141) were assigned by hospital to an intervention group (IG; used the W@W-App; n = 90) or an active comparison group (A-CG; monitored occupational activity; n = 51). The W@W-App, installed on the participants´ own smartphones, provided real-time feedback for occupational sitting, standing, and stepping, and gave access to automated strategies to sit less and move more at work. Changes between groups were assessed for total sitting time, sedentary bouts and breaks, and light and moderate-to-vigorous PA (activPAL3TM; min/day) between the baseline and after program completion. Results: Compared to the A-CG, employees that used the W@W-App program increased their number of daily breaks and the time spent on short sedentary bouts (<20 min, p = 0.047) during weekends. Changes in shortest sedentary bouts (5–10 min) during weekends were also statistically significant (p < 0.05). No changes in workday PA or sitting were observed. Conclusion: Desk-based employees seemed to transfer the W@W-App program knowledge outside of work. Evaluating the impact of workplace (mHealth-based or not) interventions at work but also away from work would provide a better understating of the impact of such interventions.

Rise and Recharge: Effects on Activity Outcomes of an e-Health Smartphone Intervention to Reduce Office Workers’ Sitting Time

“…Alternatively, electronic-health (e-health) interventions delivered via computer software have typically decreased sitting time by 14 and 55 min at 3 and 10 months, respectively [ 17 ]. Preliminary evidence suggests that a simple e-health intervention via an activity tracker and mobile application can elicit short-term (3-month) reductions in total daily sitting by an average of 42.4 min/workday [ 18 ]. While reductions in total occupational sitting time are smaller compared to multi-component interventions, reductions of more than 30 min per day are potentially clinically meaningful [ 19 ] and cost effective [ 20 ].…”

The Effects of UPcomplish on Office Workers’ Sedentary Behaviour, Quality of Life and Psychosocial Determinants: A Stepped-Wedge Design

“…Additionally, SB has become a habitual process because it is linked to diverse contexts and activities, such as work, and standing at work is perceived as uncomfortable [65][66][67]. Unsurprisingly, therefore, that others only found significant SB reductions on weekends [20,26]. SB might be less of a reasoned behaviour and more determined by environmental, societal, or habitual factors.…”

“…Using technology to communicate tailored feedback and advice might be a more cost-efficient way than regular personal coaching [21][22][23]. Yet, purely computertailored SB interventions having shown reductions in workplace SB did not find these effects when combining working and leisure time SB [24][25][26]. Therefore, a personal coach providing tailored but automated feedback might be the optimal mixture of a low-cost yet personal intervention.…”

Rise and Recharge: Exploring Employee Perceptions of and Contextual Factors Influencing an Individual-Level E-Health Smartphone Intervention to Reduce Office Workers’ Sedentary Time at Work

“…Notably, both intervention groups felt their adherence to the e-health smartphone prompts diminished over the 12 weeks despite elements of social support and encouragement, which is of concern since intervention dose is associated with intervention efficacy [ 20 ] and indicates the limited sustainability of an e-health smartphone intervention among this population [ 20 , 43 ]. Over the 12 week intervention, EMA and focus group data indicated that high workload had a negative impact on participant’s ability to engage with the prompts, with participants in both Prompt 30 and Prompt 60 arms commonly and consistently reporting workload as a factor negatively influencing adherence to breaks.…”

“…To date, workplace e-health interventions primarily utilize prompts, cues and self-monitoring as behavior change techniques [ 22 ]. Preliminary evidence from a recent systematic review suggests that workplace interventions consisting of a smartphone application and wearable technology can elicit short-term (3 month) reductions in total daily SB of an average of 42.4 min/workday [ 23 ]. Given that a high proportion (80%) of the working-age population in the UK utilize a smartphone device daily, this highlights the potential for e-health technologies to provide a low-cost and widely accessible alternative to address what has been described as the pandemic of sedentary behavior [ 21 , 22 , 24 ].…”