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Review

A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers

1
Department of Industrial Design, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
2
HCI Research Group, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg
3
School for Allied Health Professions, Fontys University of Applied Sciences, 5600 AH Eindhoven, The Netherlands
4
Department of the Built Environment, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
5
School of Sport Studies, Fontys University of Applied Sciences, 5644 HZ Eindhoven, The Netherlands
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(2), 499; https://doi.org/10.3390/ijerph17020499
Submission received: 1 October 2019 / Revised: 13 December 2019 / Accepted: 7 January 2020 / Published: 13 January 2020
(This article belongs to the Special Issue The Vital Worker: Towards Sustainable Performance at Work)

Abstract

:
Background: There is increasing interest in the role that technology can play in improving the vitality of knowledge workers. A promising and widely adopted strategy to attain this goal is to reduce sedentary behavior (SB) and increase physical activity (PA). In this paper, we review the state-of-the-art SB and PA interventions using technology in the office environment. By scoping the existing landscape, we identified current gaps and underexplored possibilities. We discuss opportunities for future development and research on SB and PA interventions using technology. Methods: A systematic search was conducted in the Association for Computing Machinery digital library, the interdisciplinary library Scopus, and the Institute of Electrical and Electronics Engineers Xplore Digital Library to locate peer-reviewed scientific articles detailing SB and PA technology interventions in office environments between 2009 and 2019. Results: The initial search identified 1130 articles, of which 45 studies were included in the analysis. Our scoping review focused on the technologies supporting the interventions, which were coded using a grounded approach. Conclusion: Our findings showed that current SB and PA interventions using technology provide limited possibilities for physically active ways of working as opposed to the common strategy of prompting breaks. Interventions are also often offered as additional systems or services, rather than integrated into existing office infrastructures. With this work, we have mapped different types of interventions and provide an increased understanding of the opportunities for future multidisciplinary development and research of technologies to address sedentary behavior and physical activity in the office context.

1. Introduction

A crucial factor that negatively affects a person’s vitality is the lack of physical activity (PA) and high levels of sedentary behavior (SB) throughout the day [1]. Prolonged periods of sedentary behavior, characterized by waking behavior equal to or below 1.5 METs [2], can have a severe negative effect on health [3,4,5]. Sedentary behavior is associated with the development of diseases such as type II diabetes, cardiovascular diseases, colon and breast cancer, increased morbidity, and premature mortality [3,5,6,7,8,9,10]. Our increasingly sedentary lives have thus become a major public health risk [11]. Conversely, engaging in physical activity, defined as any body movement that raises energy expenditure above resting metabolic rate [12], is positively linked to improved vitality [1].
To combat the negative health effects of prolonged sitting, it is important to integrate physical activity into daily routines and reduce the amount of sedentary behavior. This, however, proves difficult in office contexts. We currently spend up to 71% of our working hours sitting [13], and trend analysis indicates that sedentary behavior will continue to increase in the near future [14]. To counteract this trend, there is a growing need to investigate how to increase PA and reduce SB in office settings. In addition, a growing body of work shows that increasing and embedding physical activities in work routines does not only increase workers’ health and wellbeing, but also improves social interaction and work performance [15].
A myriad of interventions targeting sedentary behavior or physical activity in workplace contexts have been developed by researchers from different disciplines. In recent years, several systematic reviews have assessed these interventions [16,17,18,19]. The reviews have shown that only a small portion of the interventions that were assessed had a digital component. This is despite the fact that digital technologies have the potential to “revolutionize the way individuals can monitor and improve their health” [20]. For instance, one might use a personalized services such as Google Goals, a calendar application to integrate personal goals into a user’s digital calendar [21]. These types of tools may increase reflection on personal goals and thereby advance the effectiveness of the intervention [22].
Few reviews could be found that focused on or included interventions using technology. In a systematic review on the effectiveness of SB workplace interventions by Chau et al. [23], three studies had a technological element [23,24,25,26] consisting of either email or the use of a pedometer. Another four studies were included in a review by Shrestha et al. [27], involving computer prompts [28,29,30] and e-newsletters [31]. In a study by Bort-Roig et al. [32] on smartphone strategies to influence physical activity, a total of 17 articles were reviewed. This study concluded that smartphone strategies tended to be ad hoc rather than theory-based [32].
In 2017, Stephenson et al. [15] systematically reviewed computer, mobile, and wearable technology SB interventions for healthy adults and found that these technologies can be effective in reducing SB. Their meta-analysis of 15 studies showed a mean reduction of 41 min/day in the intervention group at end-point follow-up. Another systematic review focusing solely on digital SB interventions was conducted by Huang et al. in 2019 [17]. This work differed from previous reviews by classifying technological features and annotated technological configurations of the interventions. In addition, they included engineering and computer science literature, while other reviews mainly included health and life science literature.
Including interventions from the field of engineering and computer science, but also the fields of industrial, architectural, and urban design research is of great importance when developing an understanding of the opportunities for future development of SB and PA interventions. It is in these fields especially that we see the development of new and explorative approaches and interventions using technology. By rapid prototyping, development, and piloting of novel digital technologies, these fields may lay the groundwork for the development of future health-promotion technologies.
In this paper, we reviewed recent interventions with a technological component aimed at reducing sedentary behavior or increasing physical activity of office workers. We included interventions from the fields of human computer interaction, engineering, computer sciences, and digital health. In our search, we not only included full text articles, but also case studies and work-in-progress papers. With this approach, we aimed to incorporate the latest ideas and developments in PA and SB interventions with a focus on the design of the interventions. Rather than focusing on the outcomes of the interventions, this review aimed to provide an overview of trends in how SB and PA interventions are shaped. By analyzing current approaches and trends in the form and function of the interventions, we identified underexplored possibilities and gaps for the design and development of future interventions and tools. We furthermore provide an increased understanding of the opportunities for future development of research and technologies that address sedentary behavior and physical activity in the office context.
The findings of this review can inform both the public health and design research fields, and address how the different fields can benefit from each other’s work. An increased understanding between these research fields and multi-disciplinary expertise is crucial in the development and evaluation of digital health interventions [33]. This review therefore provides considerations for the development of future SB and PA interventions using technology, as well as implications for more collaborative and interdisciplinary work utilizing these interventions.

2. Materials and Methods

2.1. Search and Selection

A literature search was conducted in the Association for Computing Machinery (ACM) digital library, the interdisciplinary library Scopus, and the Institute of Electrical and Electronics Engineers (IEEE) Xplore Digital Library. The search included full-text scientific articles, case studies, and late-breaking work published between January 2009 and June 2019. All libraries were searched for designs or interventions aimed at increasing PA or reducing SB of knowledge workers using digital technology.
A search strategy was performed on title, abstract, and keywords using the following keywords: “sedentary” OR “sitting” OR "physical activity" OR “inactivity” AND “office OR work*” AND “intervention” OR “design” OR “present*” OR “propose”. The search excluded “children” and “patient*”. To adjust the search to the nature of the different databases, two additions were made to the search queries. To limit the search in Scopus to designs with a digital component, the string “technology” OR “digital” was added. For the IEEE search, an extra exclusion string was added to exclude all SAT- and car-related papers. In addition to the database search, reference lists of existing reviews [15,17,24] on workplace SB reduction and PA promotion were manually searched to identify additional eligible studies. Titles and abstracts were reviewed for eligibility based on the following including criteria:
  • Presents a design targeting reduction of SB or increasing PA or both;
  • Partly or exclusively during office hours;
  • Including digital technology in the delivery;
  • Published in peer-reviewed scientific journals or conference proceedings between 2009 and June 2019;
  • Published in the English language.
The selection of studies was done independently by the first two authors based on a screening of titles and abstracts. The selected papers were cross-checked, and any discrepancies were resolved by including a third author to reach a consensus about study inclusion.

2.2. Data Synthesis

A grounded approach was used to develop a coding scheme for analysis of the designs. Two authors independently coded nine designs for an initial coding scheme. Consensus on the scheme was sought by including a third and fourth author. Based on the coding scheme, all eligible studies were reviewed and the designs were annotated. The following information was extracted: publication data, design details like mode of delivery, underpinning theories, behavior change techniques, objectives, targeted behavior, and details on the input and output of the design.

3. Results

3.1. Study Selection

A structured database search identified 1258 potentially relevant abstracts (Figure 1). After removing 128 duplicates, 1130 unique references remained. The titles and abstracts of these articles were screened, after which 61 articles were selected for potential inclusion (Figure 1). Out of those, papers were excluded if there was no design presented (n = 5), if it had no digital component (n = 2), if the intervention did not target SB or PA (n = 3), or if it did not partially or fully target the office environment (n = 6). In total, 45 relevant articles were included in this review (Table 1).

3.2. Submission Type and Venue

Of the 45 included papers (Figure 1), 9 were full text journal articles, 22 were full-text conference proceedings articles, and 14 were short (work-in-progress) conference papers. The 45 included papers presented 47 unique designs to combat physical inactivity. The studies were published in 27 different journals or conference proceedings between 2010 and 2019 (Figure 2) by 41 different first authors. Twenty-four studies were published in the field of human–computer interaction (HCI), 12 studies originated from computer science journals or conference proceedings, and 9 studies were published in the field of digital health. However, it must be noted that many of the journals and conferences had an interdisciplinary character; it was thus complex to make a clear demarcation of the research fields to precisely categorize the papers in this review.

3.3. Theoretical Underpinning and Behavior Change Techniques

Of the 45 studies, 34 did not specify a theoretical underpinning of their design. Of the 11 papers that did use a theoretical model, the most commonly used theory was the transtheoretical model (25%) [37,58,68], followed by the theory of planned behavior (17%) [41,46] and self-determination theory (17%) [50,74]. Five other papers based their designs on, respectively, persuasive system design model [65], goal setting theory [55], distributed prospective memory approach [48], social cognitive theory [38] and social learning theory combined with the theory of reasoned action [46].
Eighteen different behavior change techniques (BCT) were specified in the papers, although 17 studies did not specify any BCT (Table 2) The most commonly used BCT was the use of rewards, for instance through gamification processes (e.g., earning points). Another common strategy, included in nine papers, was to include social support or sharing experiences with peers in the intervention.

3.4. Targeted Behavior

Twenty-six interventions were specifically designed for the office environment, while 19 studies had a more generic approach in which they did not specify the context of use. Eight papers reported an evaluation of their intervention on SB or PA [35,37,43,65,66,77,78]. Thirty-three studies did not give a definition of PA or SB, while nine studies provided a definition of PA and four studies offered a definition of SB (Table 3).
Although the majority of the papers did not provide a definition of SB or PA, a general distribution of the main targeted behavior could be made based on the description of the interventions. Just over half of the interventions targeted PA (24) while 9 interventions targeted SB and 12 targeted both PA and SB. More specifically, 18 interventions targeted break-taking behavior, 20 interventions targeted non-work-related PA, 3 interventions targeted work-related tasks, and 4 interventions were categorized as “other targeted behavior”. The studies that were categorized as other targeted behavior included an intervention to moderate and maintain cadence [58], one intervention that stimulated connectedness using an ambient light system and PA visualizations on a screen [49], and two designs that targeted multiple lifestyle factors including diet, sleeping habits, and PA [37,46]. Of the three work-related behavior interventions, two designs aimed to stimulate walking meetings [41,49] and one intervention used movement on an interactive chair to control a workplace computer [69].
Another distinction could be made in the different approaches the interventions adopted to obtain the targeted behavior, namely creating awareness, creating opportunities, and teaching new behaviors (Table 4). The number of interventions that were classified as “creating awareness” exceeded the number of papers that stated intent to use awareness as a BCT, for instance because they used prompts to inform the user of prolonged sitting behavior. These interventions were categorized as creating awareness, even though this was not stated in the paper as a BCT. Twenty-three interventions aimed to create awareness of the user’s current behavior to let them reflect and act on their behavior. The most commonly used form of delivery was via prompting or messages. This strategy was adopted by 18 interventions. Seven interventions aimed to create opportunities for users to perform the targeted behavior [34,38,41,52,58,69,76]. Only one intervention aimed to transform old behavior into new, healthier behavior. This study by Probst et al. [69] provided office workers with the possibility to use tilting, rotating, or bouncing movements on an interactive chair to control their workplace computer.

3.5. Technology Type

Several types of technology were used in the interventions (Table 5). Nineteen studies presented an intervention with a physical component (42%), such as a robot or an interactive lamp, while 26 of the studies (57.8%) showed purely digital designs like applications or computer software. Of the 19 studies with a physical component, 6 used a lamp as their primary feedback mechanism, 3 used a chair, 3 designs used robots, and 2 used 3D printing to represent physical activity (Figure 3; examples in Appendix A). Of the five remaining interventions with a physical component, one intervention used an ambient desk object [61], one intervention used an interactive fountain [57], one intervention integrated a physical line in a service design for walking meetings [41], and one was an interactive shirt [51].
Twenty-four interventions were purely digital, of which phone applications were most common. Phone applications in combination with wearables were often used to give information or prompts, and as a data collection tool. Seven interventions did not have a physical component, of which one used break-prompting software [60], one used a projected avatar [76], one was an email-based intervention [35], and four were platform-based interventions [37,44,46,47]. Figure 3 shows the different types of technologies used by the interventions in relation to the targeted behavior.
Several types of objective data were collected as input measures by the interventions. Twenty-one interventions used step count as input, six measured heartrate, eight used motions or gestures as input, and three calculated caloric intake or energy expenditure (Table 6). Thirteen interventions used real-time data collection in their interventions.
Of the 45 interventions, 7 employed existing infrastructures or tools. The tool most commonly used to build upon was the office chair [12,69,71,72]. Two interventions used office communication software in their design, by means of email [35] or a room booking system [41]. One intervention used a social communication channel (i.e., Facebook) as a platform for their design intervention [44].
In addition to the seven studies that used existing tools and digital services, there were two studies that restructured the built environment. The intervention “Breaksense” by Cambo et al. [40] introduced a Bluetooth beacon infrastructure to promote context-aware physical breaks within the workplace. Bluetooth beacons are low-energy devices that enable portable devices such as phones to be identified. By using this structure, Breaksense was able to trigger an action if a knowledge worker was close to a beacon, thereby encouraging workers to explore the office environment. Damen et al. [43] restructured the office campus environment by adding a physical line to their service design for walking meetings.

4. Discussion

This review set out to scope the landscape of technological sedentary behavior (SB) and physical activity (PA) interventions used in the office environment. Through a systematic literature search in the Association for Computing Machinery digital library, the interdisciplinary library Scopus, and the Institute of Electrical and Electronics Engineers Xplore Digital Library, we identified and analyzed 45 interventions published between 2009 and 2019. This paper provides an overview of the study characteristics, including a description of the interventions, intervention objectives, theoretical underpinning, and behavior change techniques. The analysis revealed two important gaps in the current research and development of technological SB and PA interventions.
A first underexplored opportunity in current interventions is the use of existing infrastructures. Seven studies employed existing office tools or systems, like chairs and emailing software. More often, interventions are offered as additional systems, tools, and services—an extra application on a phone or a robot is used to deliver SB or PA interventions. In future investigations, it might be possible to examine whether integrating interventions into existing office infrastructure will lower the threshold for people to use a system. Using existing systems and tools might limit additional the time investment required of users, which is an important design consideration for health-promotion interventions [11].
Second, the results showed that a clear distinction could be made in the objectives of the interventions. While a frequently adopted strategy of the interventions was supporting break-taking behavior, only a handful of studies attempted to create new, more active ways of working, i.e., how work can be transformed to be more physically active by making physical activity a more integral part of work and not merely a break from work, for instance by targeting walking meetings [41,79]. Only three studies targeted work-related tasks by transforming sedentary work behavior into physically active work behavior [41,69,79]. This finding was consistent despite the increased interest in sustainable performance at work, which extends the focus of worker health and wellbeing to health and wellbeing while maximizing work performance [82]. Interventions that focus on integrating physical activity with work may be more suitable to maximize work performance, compared to interventions that approach physical activity as a break from work. However, more work is needed on how SB and PA interventions can link to work performance.
In addition, the two most common intervention strategies in our review were rewarding “good” behavior and creating awareness of “bad” behavior. Other frequently used techniques included goal setting, persuasion, and creating social support. The use of these behavior change techniques is in line with previous work on effective strategies in SB interventions by Gardner et al. [83] and Bort et al. [32]. These reviews found that persuasion [83], goal setting, and social support [32] were among the most promising behavior change techniques for SB interventions. Other highlighted strategies were environmental restructuring (i.e., changing the physical or social context), education and training, self-monitoring, and problem solving [32,83]. However, these techniques were only seldom used in the interventions included in this review. Moreover, eight of the included studies did not specify any behavior change techniques. In future work, researchers should thus strive to formulate behavior change techniques more clearly to create a more unified terminology for intervention strategies.
In addition to formulating behavior change techniques, more clarity is needed on how SB and PA are defined within interventions. This review showed that a mere 12 of the included 45 interventions provided a definition of SB and PA. By adopting a unified terminology, a more profound exchange can be made between studies detailing development of interventions and evaluation studies. This can facilitate the adoption of novel technologies and interventions from design and engineering fields to be used in other fields. This is particularly important since the research and development of technological health interventions requires a multidisciplinary approach [33].
Our scoping review had a couple of limitations. First, by restricting our search to three databases, we may have excluded relevant publications. Similarly, by limiting our scope to scientific literature, we may have missed interventions that are used in practice but have not been reported on in the academic literature. We did, however, provide a broader scope than previous work by including short papers. By including exploratory or “late-breaking” work, we increased the chances of a more diverse scope of novel technologies being reviewed in this study. Focusing our review mainly on artefacts rather than studies, we obtained an overview of the strategies used and underused to address SB/PA in the context of office work. Although including short papers may have affected the level of information on interventions—and thus could have resulted in a lower overall quality of the included studies—this did not impede us in attaining the objectives of our study. Positioning this work as a scoping review of artefacts, we did not intend to report on the evaluation and impact of these technological interventions, and thus did not report on the methodological quality of the included studies or their reported results. Our present contribution instead focused on technology characteristics and identified current gaps and opportunities for future research and development of SB and PA interventions using technology.

5. Conclusions

In this investigation, we aimed to review the state-of-the-art technology interventions to reduce sedentary behavior or increase physical activity in the office environment, published in the fields of human computer interaction, engineering, computer science, and digital health and life sciences between 2009 and 2019. We included 45 interventions, identified using a systematic literature search. This study identified two main underexplored gaps and opportunities for future research and development of SB and PA interventions. With our work, we showed that current interventions make limited use of existing infrastructures and systems. The second major finding was that physical activity is approached as a break from work instead of an alternative, more active, way of working. Future work could investigate how physical activity can used as an active way of working instead of as a break from work. This new understanding should help to improve the understanding of current practice and provide opportunities for future research and development of SB and PA interventions. In addition, this work aimed to enhance the exchange of knowledge between different research fields and research phases by including papers reporting on the development of interventions as well as evaluation studies. We hope to improve a mutual understanding of the current SB and PA intervention practice, and thereby improve multidisciplinary work within the field of digital SB and PA interventions. Moreover, the list of artefacts can serve as an inspiration source for future development, and may help designers and developers to locate possibilities for novel design ideas [80].

Author Contributions

All authors together conceived the presented idea, under the lead of I.D., S.V., R.B., A.B., P.v.W., and C.L. supervised the project. I.D. designed the search model and analyzed the data. H.B., C.L. and S.V. aided in the analysis and in interpreting the results. H.B. contributed to the visuals and tables. I.D. wrote the original draft preparation. S.V., R.B., A.B., P.v.W., and C.L. reviewed, revised, and edited several earlier versions of this paper. All authors discussed the results and contributed to the final manuscript. All authors read and approved the final draft of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Figure A1. Examples of interventions categorized by technology types.
Figure A1. Examples of interventions categorized by technology types.
Ijerph 17 00499 g0a1

References

  1. Guérin, E. Disentangling vitality, well-being, and quality of life: A conceptual examination emphasizing their similarities and differences with special application in the physical activity domain. J. Phys. Act. Health 2012, 9, 896–908. [Google Scholar] [CrossRef] [PubMed]
  2. Thivel, D.; Tremblay, A.; Genin, P.M.; Panahi, S.; Rivière, D.; Duclos, M. Physical Activity, Inactivity, and Sedentary Behaviors: Definitions and Implications in Occupational Health. Front. Public Heal. 2018, 6, 1–5. [Google Scholar] [CrossRef] [PubMed]
  3. Healy, G.N.; Eakin, E.G.; LaMontagne, A.D.; Owen, N.; Winkler, E.A.H.; Wiesner, G.; Gunning, L.; Neuhaus, M.; Lawler, S.; Fjeldsoe, B.S.; et al. Reducing sitting time in office workers: Short-term efficacy of a multicomponent intervention. Prev. Med. (Baltim). 2013, 57, 43–48. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Owen, N.; Sugiyama, T.; Eakin, E.E.; Gardiner, P.A.; Tremblay, M.S.; Sallis, J.F. Adults’ sedentary behavior: Determinants and interventions. Am. J. Prev. Med. 2011, 41, 189–196. [Google Scholar] [CrossRef] [PubMed]
  5. Schmid, D.; Ricci, C.; Leitzmann, M.F. Associations of objectively assessed physical activity and Sedentary time with all-cause mortality in US adults: The NHANES study. PLoS ONE 2015, 10, 3. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Allender, S.; Peto, V.; Scarborough, P.; Kaur, A.; Rayner, M. Coronary heart disease statistics 2008 edition Contents. Br. Hear. Found. Heal. Promot. Res. Gr. 2008, 1–220. [Google Scholar]
  7. Coombes, J.S.; Law, J.; Lancashire, B.; Fassett, R.G. “Exercise is medicine”: Curbing the burden of chronic disease and physical inactivity. Asia-Pac. J. Public Heal. 2015, 27, 600–605. [Google Scholar] [CrossRef]
  8. Dempsey, P.C.; Owen, N.; Biddle, S.J.H.S.J.; Dunstan, D.W.D. Managing sedentary behavior to reduce the risk of diabetes and cardiovascular disease. Curr. Diab. Rep. 2014, 14, 1–26. [Google Scholar] [CrossRef] [Green Version]
  9. Gibbs, B.B.; Hergenroeder, A.L.; Katzmarzyk, P.T.; Lee, I.; Jakicic, J.M. Definition, Measurement, and Health Risks Associated with Sedentary Behavior. Med. Sci. Sports Exerc. 2015, 47, 1295–1300. [Google Scholar] [CrossRef] [Green Version]
  10. Martin, A.; Fitzsimons, C.; Jepson, R.; Saunders, D.H.; van der Ploeg, H.P.; Teixeira, P.J.; Gray, C.M.; Mutrie, N. Interventions with potential to reduce sedentary time in adults: Systematic review and meta-analysis. Br. J. Sports Med. 2015, 1–10. [Google Scholar] [CrossRef] [Green Version]
  11. Patrick, K.; Hekler, E.B.; Estrin, D.; Mohr, D.C.; Riper, H.; Crane, D.; Godino, J.; Riley, W.T. The Pace of Technologic Change: Implications for Digital Health Behavior Intervention Research. Am. J. Prev. Med. 2016, 51, 816–824. [Google Scholar] [CrossRef]
  12. Xu, L.; Chen, G.; Wang, J.; Shen, R.; Zhao, S. A sensing cushion using simple pressure distribution sensors. In Proceedings of the 2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Hamburg, Germany, 13–15 September 2012; pp. 451–456. [Google Scholar]
  13. Clemes, S.; O’connell, S.; Edwardson, C. Office workers’ objectively measured sedentary behavior and physical activity during and outside working hours. J. Occup. Environ. Med. 2014, 56, 298–303. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Kohl, H.W.; Craig, C.L.; Lambert, E.V.; Inoue, S.; Alkandari, J.R.; Leetongin, G.; Kahlmeier, S.; Andersen, L.B.; Bauman, A.E.; Blair, S.N.; et al. The pandemic of physical inactivity: Global action for public health. Lancet 2012, 380, 294–305. [Google Scholar] [CrossRef] [Green Version]
  15. Stephenson, A.; McDonough, S.M.; Murphy, M.H.; Nugent, C.D.; Mair, J.L. Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: A systematic review and meta-analysis. Int. J. Behav. Nutr. Phys. Act. 2017, 14, 105. [Google Scholar] [CrossRef] [PubMed]
  16. Hazelzet, E.; Picco, E.; Houkes, I.; Bosma, H.; De Rijk, A. Effectiveness of interventions to promote sustainable employability: A systematic review. Int. J. Environ. Res. Public Health 2019, 16, 11. [Google Scholar] [CrossRef] [Green Version]
  17. Huang, Y.; Benford, S.; Blake, H. Digital Interventions to Reduce Sedentary Behaviors of Office Workers: Scoping Review. J. Med. Internet Res. 2019, 21, e11079. [Google Scholar] [CrossRef]
  18. Orji, R.; Moffatt, K. Persuasive technology for health and wellness: State-of-the-art and emerging trends. Health Inform. J. 2018, 24, 66–91. [Google Scholar] [CrossRef]
  19. Stockwell, S.; Schofield, P.; Fisher, A.; Firth, J.; Jackson, S.E.; Stubbs, B.; Smith, L. Digital behavior change interventions to promote physical activity and/or reduce sedentary behavior in older adults: A systematic review and meta-analysis. Exp. Gerontol. 2019, 120, 68–87. [Google Scholar] [CrossRef]
  20. Michie, S.; Yardley, L.; West, R.; Patrick, K.; Greaves, F. Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop. J. Med. Internet Res. 2017, 19, e232. [Google Scholar] [CrossRef]
  21. Google Goals. Available online: https://www.blog.google/products/calendar/find-time-goals-google-calendar/ (accessed on 28 September 2019).
  22. Lee, M.K.; Kim, J.; Forlizzi, J.; Kiesler, S. Personalization revisited. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Osaka, Japan, 9–11 September 2015; pp. 743–754. [Google Scholar]
  23. Chau, J.Y.; Van Der Ploeg, H.P.; van Uffelen, J.G.Z.; Wong, J.; Riphagen, I.; Healy, G.N.; Gilson, N.D.; Dunstan, D.W.; Bauman, A.E.; Owen, N.; et al. Are workplace interventions to reduce sitting effective? A systematic review. Prev. Med. (Baltim). 2010, 51, 352–356. [Google Scholar] [CrossRef]
  24. Gilson, N.D.; Puig-Ribera, A.; McKenna, J.; Brown, W.J.; Burton, N.W.; Cooke, C.B. Do walking strategies to increase physical activity reduce reported sitting in workplaces: A randomized control trial. Int. J. Behav. Nutr. Phys. Act. 2009, 6, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Marshall, A.L.; Leslie, E.R.; Bauman, A.E.; Marcus, B.H.; Owen, N. Print versus website physical activity programs: A randomized trial. Am. J. Prev. Med. 2003, 25, 88–94. [Google Scholar] [CrossRef]
  26. Plotnikoff, R.C.; McCargar, L.J.; Wilson, P.M.; Loucaides, C.A. Efficacy of an e-mail intervention for the promotion of physical activity and nutrition behavior in the workplace context. Am. J. Heal. Promot. 2005, 19, 422–429. [Google Scholar] [CrossRef] [PubMed]
  27. Shrestha, N.; Ijaz, S.; Kukkonen-Harjula, K.T.; Kumar, S.; Nwankwo, C.P. Workplace interventions for reducing sitting at work. Cochrane Database Syst. Rev. 2014, 2014, 1. [Google Scholar]
  28. Evans, R.E.; Fawole, H.O.; Sheriff, S.A.; Dall, P.M.; Grant, P.M.; Ryan, C.G. Point-of-choice prompts to reduce sitting time at work: A randomized trial. Am. J. Prev. Med. 2012, 43, 293–297. [Google Scholar] [CrossRef]
  29. Pedersen, S.J.; Cooley, P.D.; Mainsbridge, C. An e-health intervention designed to increase workday energy expenditure by reducing prolonged occupational sitting habits. Work 2014, 49, 289–295. [Google Scholar] [CrossRef] [Green Version]
  30. Swartz, A.M.; Rote, A.E.; Welch, W.A.; Maeda, H.; Hart, T.L.; Cho, Y.I.; Strath, S.J. Prompts to Disrupt Sitting Time and Increase Physical Activity at Work, 2011–2012. Prev. Chronic Dis. 2014, 11, 1–8. [Google Scholar] [CrossRef] [Green Version]
  31. Gordon, A. A Theory-Based Pilot Study to Decrease Sitting Time in the Workplace. Master′s Thesis, Arizona State University, Tempe, Arizona, 2013. [Google Scholar]
  32. Bort-Roig, J.; Gilson, N.D.; Puig-Ribera, A.; Contreras, R.S.; Trost, S.G. Measuring and influencing physical activity with smartphone technology: A systematic review. Sport. Med. 2014, 44, 671–686. [Google Scholar] [CrossRef]
  33. Blandford, A.; Gibbs, J.; Newhouse, N.; Perski, O.; Singh, A.; Murray, E. Seven lessons for interdisciplinary research on interactive digital health interventions. Digit. Heal. 2018, 4, 1–14. [Google Scholar] [CrossRef] [Green Version]
  34. Ahtinen, A.; Andrejeff, E.; Väänänen, K.; Vaananen, K. Brainwolk: A Mobile Technology Mediated Walking Meeting Concept for Wellbeing and Creativity at Work. In Proceedings of the 15th International Conference on Mobile and Ubiquitous Multimedia, Rovaniemi, Finland, 13–15 December 2016; ACM: New York, NY, USA, 2016; pp. 307–309. [Google Scholar]
  35. Andersen, L.L.; Sundstrup, E.; Boysen, M.; Due Jakobsen, M.; Mortensen, O.S.; Persson, R. Cardiovascular health effects of internet-based encouragements to do daily workplace stair-walks: Randomized controlled trial. J. Med. Internet Res. 2013, 15, 6. [Google Scholar] [CrossRef]
  36. Arrogi, A.; Bogaerts, A.; Seghers, J.; Devloo, K.; Vanden Abeele, V.; Geurts, L.; Wauters, J.; Boen, F. Evaluation of stAPP: A smartphone-based intervention to reduce prolonged sitting among Belgian adults. Health Promot. Int. 2017, 34, 16–27. [Google Scholar] [CrossRef] [PubMed]
  37. Bonn, S.E.; Lof, M.; Ostenson, C.-G.; Trolle Lagerros, Y. App-technology to improve lifestyle behaviors among working adults—the Health Integrator study, a randomized controlled trial. BMC Public Health 2019, 19, 273. [Google Scholar]
  38. Brandstetter, J.; Liebman, N.; London, K. Fidgebot: Working Out While Working. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, Portland, OR, USA, 2–5 March 2015; ACM: New York, NY, USA, 2015; pp. 149–150. [Google Scholar]
  39. Brombacher, H.; Megens, C.; Vos, S.; Arts, D.; Megens, C.; Vos, S. Stimulight: Exploring Social Interaction to Reduce Physical Inactivity among Office Workers. In Proceedings of the 37th ACM International Conference on Human Factors in Computing Systems (CHI2019), Glasgow, UK, 4–9 May 2019; pp. 1–6. [Google Scholar]
  40. Cambo, S.A.; Avrahami, D.; Lee, M.L. BreakSense: Combining Physiological and Location Sensing to Promote Mobility During Work-Breaks. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA, 6 May 2017; ACM: New York, NY, USA, 2017; pp. 3595–3607. [Google Scholar]
  41. Damen, I.; Brankaert, R.; Megens, C.; van Wesemael, P.; Brombacher, A.; Vos, S. Let’s Walk and Talk: A Design Case to Integrate an Active Lifestyle in Daily Office Life. In Proceedings of the Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada, 21 April 2018; ACM: New York, NY, USA, 2018; pp. 10:1–10:10. [Google Scholar]
  42. Esakia, A.; Harden, S.M.; McCrickard, D.S.; Horning, M. FitAware: Channeling Group Dynamics Strategies with Smartwatches in a Physical Activity Intervention. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, Denver, CO, USA, 6–11 May 2017; ACM: New York, NY, USA, 2017; pp. 2551–2559. [Google Scholar]
  43. Fortmann, J.; Stratmann, T.C.; Boll, S.; Poppinga, B.; Heuten, W. Make Me Move at Work! An Ambient Light Display to Increase Physical Activity. In Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare, Venice, Italy, 5–8 May 2013; pp. 274–277. [Google Scholar]
  44. Foster, D.; Linehan, C.; Kirman, B.; Lawson, S.; James, G.; Heath, B. Motivating physical activity at work: Using persuasive social media for competitive step counting. In Proceedings of the 14th International Academic MindTrek Conference: Envisioning Future Media Environments, Tampere, Finland, 6 October 2010; pp. 111–116. [Google Scholar]
  45. Garcia, J.J.; Romero, N.A.; Keyson, D.; Havinga, P. Esther 1.3: Integrating in-situ prompts to trigger self-reflection of physical activity in knowledge workers. In Proceedings of the ChileCHI ’13, Temuco, Chile, 11–15 November 2013; pp. 1–4. [Google Scholar]
  46. Goldberg, L.; Lockwood, C.; Garg, B.; Kuehl, K.S. Healthy Team Healthy U: A Prospective Validation of an Evidence-Based Worksite Health Promotion and Wellness Platform. Front. Public Heal. 2015, 3, 1–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Gomes, N.; Merugu, D.; O’Brien, G.; Mandayam, C.; Yue, J.S.; Atikoglu, B.; Albert, A.; Fukumoto, N.; Liu, H.; Prabhakar, B.; et al. Steptacular: An incentive mechanism for promoting wellness. In Proceedings of the Fourth International Conference on Communication Systems and Networks (COMSNETS 2012), Bangalore, India, 3–7 January 2012; pp. 1–6. [Google Scholar]
  48. Grundgeiger, T.; Pichen, J.; Häfner, J.; Wallmann-Sperlich, B.; Löffler, D.; Huber, S. Combating Sedentary Behavior: An App Based on a Distributed Prospective Memory Approach. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, Denver, CO, USA, 6 May 2017; pp. 1632–1639. [Google Scholar]
  49. Güldenpfennig, F.; Ganhör, R.; Fitzpatrick, G. Sitting in the Same Boat: A Case Study of a Combined Awareness System and Behaviour Change Technology. In Proceedings of the Annual Meeting of the Australian Special Interest Group for Computer Human Interaction, Parkville, Australia, 7 December 2015; ACM: New York, NY, USA, 2015; pp. 309–313. [Google Scholar]
  50. Haque, M.S.; Abdullah, W.M.; Rahaman, S.; Kangas, M.; Jämsä, T. Persuasive health and wellbeing application: A theory-driven design in promoting physical activity. In Proceedings of the 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Dhaka, Bangladesh, 17–18 December 2016; pp. 1–5. [Google Scholar]
  51. Harjuniemi, E.; Colley, A.; Rytilahti, P.; Li, H.; Forest, J.; Häkkilä, J. Idle Stripes Shirt: Ambient Wearable Display for Activity Tracking. In Proceedings of the 2018 ACM International Symposium on Wearable Computers, Singapore, 8–12 October 2018; ACM: New York, NY, USA, 2018; pp. 254–259. [Google Scholar]
  52. He, Q.; Agu, E. On11: An Activity Recommendation Application to Mitigate Sedentary Lifestyle. In Proceedings of the 2014 workshop on physical analytics, Bretton Woods, NH, USA, 16 June 2014; pp. 3–8. [Google Scholar]
  53. Hirano, S.H.; Farrell, R.G.; Danis, C.M.; Kellogg, W.A. WalkMinder: Encouraging an Active Lifestyle Using Mobile Phone Interruptions. In Proceedings of the CHI ’13 Extended Abstracts on Human Factors in Computing Systems, Paris France, 27 April–2 May 2013; ACM: New York, NY, USA, 2013; pp. 1431–1436. [Google Scholar]
  54. Kanaoka, T.; Mutlu, B. Designing a Motivational Agent for Behavior Change in Physical Activity. In Proceedings of the CHI ’15, Seoul, Korea, 18–23 April 2015; pp. 1445–1450. [Google Scholar]
  55. Khot, R.A.; Mueller, F.; Hjorth, L. SweatAtoms: Materializing Physical Activity. In Proceedings of the 9th Australasian Conference on Interactive Entertainment: Matters of Life and Death, Melbourne, Australia, 30 September 2013; ACM: New York, NY, USA, 2013; pp. 4:1–4:7. [Google Scholar]
  56. Khot, R.A.; Lee, J.; Hjorth, L.; Mueller, F. “Floyd” SweatAtoms: Understanding Physical Activity Through Material Artifacts. In Proceedings of the CHI ’14 Extended Abstracts on Human Factors in Computing Systems, Toronto, ON, Canada, 26 April–1 May 2014; ACM: New York, NY, USA, 2014; pp. 173–174. [Google Scholar]
  57. Khot, R.A.; Lee, J.; Hjorth, L.; Mueller, F. “Floyd” TastyBeats: Celebrating Heart Rate Data with a Drinkable Spectacle. In Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction, Stanford, CA, USA, 15 January 2015; ACM: New York, NY, USA, 2015; pp. 229–232. [Google Scholar]
  58. Komninos, A.; Dunlop, M.; Rowe, D.; Hewitt, A.; Coull, S. Using Degraded Music Quality to Encourage a Health Improving Walking Pace: BeatClearWalker. In Proceedings of the 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Istanbul, Turkey, 20–23 May 2015. [Google Scholar]
  59. Lin, Y.; Jessurun, J.; de Vries, B.; Timmermans, H. Motivate: Towards Context-Aware Recommendation Mobile System for Healthy Living. In Proceedings of the 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, Dublin, Ireland, 23–26 May 2011; pp. 250–253. [Google Scholar]
  60. Luo, Y.; Lee, B.; Yvette Wohn, D.; Rebar, A.L.; Conroy, D.E.; Kyoung Choe, E. Time for Break: Understanding Information Workers’ Sedentary Behavior Through a Break Prompting System. In Proceedings of the 2018 ACM Conference on Human Factors in Computing Systems (CHI), Montreal, QC, Canada, 21–26 April 2018; pp. 1–14. [Google Scholar]
  61. Ferreira, M.J.; Caraban, A.K.; Karapanos, E. Breakout: Predicting and breaking sedentary behaviour at work. In Proceedings of the Conference on Human Factors in Computing Systems, Toronto, ON, Canada, 26–30 April 2014; pp. 2407–2412. [Google Scholar]
  62. Mateevitsi, V.; Reda, K.; Leigh, J.; Johnson, A. The Health Bar: A Persuasive Ambient Display to improve the office worker’s well being. In Proceedings of the 5th Augmented Human International Conference, Kobe, Japan, 7–9 March 2014; p. 21. [Google Scholar]
  63. Maxhelaku, S.; Veliu, A.; Kika, A.; Greca, S. The use of a smart application to track activities for achieving an active and healthy life recently characterizing the world. In Proceedings of the RTA-CSIT, Tirana, Albania, 23–24 November 2018. [Google Scholar]
  64. Min, D.A.; Kim, Y.; Jang, S.A.; Kim, K.Y.; Jung, S.-E.; Lee, J.-H. Pretty Pelvis. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, Seoul, Korea, 18–23 April 2015; pp. 1259–1264. [Google Scholar]
  65. Mohadis, H.M.; Ali, N.M. Designing persuasive application to encourage physical activity at workplace among older workers. In Proceedings of the 2016 Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), Konya, Turkey, 21–23 July 2016; pp. 126–130. [Google Scholar]
  66. Moradi, F.; Wiberg, M. NEAT-Lamp and Talking Tree: Beyond Personal Informatics towards Active Workplaces. Computers 2017, 7, 4. [Google Scholar] [CrossRef] [Green Version]
  67. Mukhtar, H.; Belaid, D. Using adaptive feedback for promoting awareness about physical activeness in adults. In Proceedings of the 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing, Vietri sul Mere, Italy, 18–21 December 2013; pp. 638–643. [Google Scholar]
  68. Munson, S.; Consolvo, S. Exploring Goal-setting, Rewards, Self-monitoring, and Sharing to Motivate Physical Activity. In Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare, San Diego, CA, USA, 21–24 May 2012; pp. 25–32. [Google Scholar]
  69. Probst, K.; Lindlbauer, D.; Greindl, P.; Trapp, M.; Haller, M.; Schwartz, B.; Schrempf, A. Rotating, Tilting, Bouncing: Using an Interactive Chair to Promote Activity in Office Environments. In Proceedings of the CHI ’13 Extended Abstracts on Human Factors in Computing Systems, Paris, France, 27 April–2 May 2013; ACM: New York, NY, USA, 2013; pp. 79–84. [Google Scholar]
  70. Reeder, S.; Kelly, L.; Kechavarzi, B.; Sabanovic, S. Breakbot: A Social Motivator for the Workplace. In Proceedings of the 8th ACM Conference on Recommender systems, Foster City, CA, USA, 6–10 October 2014; pp. 61–64. [Google Scholar]
  71. Ren, X.; Yu, B.; Lu, Y.; Zhang, B.; Hu, J.; Brombacher, A. LightSit: An unobtrusive health-promoting system for relaxation and fitness microbreaks at work. Sensors (Switzerland) 2019, 19, 2162. [Google Scholar] [CrossRef] [Green Version]
  72. Ren, X.; Yu, B.; Lu, Y.; Brombacher, A. Exploring Cooperative Fitness Tracking to Encourage Physical Activity Among Office Workers. Proc. ACM Hum.-Comput. Interact. 2018, 2, 146:1–146:20. [Google Scholar] [CrossRef] [Green Version]
  73. Ren, X.; Hollander, L.; Van Der Marel, R.; Molenaar, L.; Lu, Y. Step-by-step: Exploring a social exergame to encourage physical activity and social dynamics among office workers. Conf. Hum. Factors Comput. Syst. Proc. 2019, 1–6. [Google Scholar]
  74. Simons, D.; De Bourdeaudhuij, I.; Clarys, P.; De Cocker, K.; Vandelanotte, C.; Deforche, B. Effect and process evaluation of a smartphone app to promote an active lifestyle in lower educated working young adults: Cluster randomized controlled trial. JMIR mHealth uHealth 2018, 6, 8. [Google Scholar] [CrossRef]
  75. Van Dantzig, S.; Geleijnse, G.; Van Halteren, A.T. Toward a persuasive mobile application to reduce sedentary behavior. Pers. Ubiquitous Comput. 2013, 17, 1237–1246. [Google Scholar] [CrossRef]
  76. Shan, W.; Ng, F.; Sharlin, E. Exercise Pal Mootchi. In Proceedings of the International Conference on Entertainment Computing ICEC 2011, Vancouver, BC, Canada, 5–8 October 2011; pp. 395–398. [Google Scholar]
  77. Wang, Y.; Reiterer, H. The Point-of-Choice Prompt or the Always-On Progress Bar? In Proceedings of the CHI’19 Extended Abstracts, Glasgow, Scotland, UK, 4–9 May 2019; pp. 1–6. [Google Scholar]
  78. Khot, R.A.; Pennings, R.; Mueller, F. “Floyd” EdiPulse: Turning Physical Activity Into Chocolates. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, Seoul, Korea, 18–23 April; ACM: New York, NY, USA, 2015; pp. 331–334. [Google Scholar]
  79. Ahtinen, A.; Andrejeff, E.; Harris, C.; Väänänen, K. Let’ s Walk at Work—Persuasion through the Brainwolk Walking Meeting App Full Paper Towards Physically Active Ways of Work. AcademicMindtrek 2017, 2017, 73–82. [Google Scholar]
  80. Yoo, S.; Xue, L.; Kay, J. HappyFit. In Proceedings of the Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, Bratislava, Slovakia, 9 July 2017; pp. 391–394. [Google Scholar]
  81. Hassenzahl, M.; Heidecker, S.; Eckoldt, K.; Diefenbach, S.; Hillmann, U. All you need is love: Current strategies of mediating intimate relationships through technology. ACM Trans. Comput. Interact 2012, 19, 30:1–30:19. [Google Scholar] [CrossRef]
  82. De Jonge, J.; Peeters, M.C.W. The vital worker: Towards sustainable performance at work. Int. J. Environ. Res. Public Health 2019, 16, 910. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Gardner, B.; Smith, L.; Lorencatto, F.; Hamer, M.; Biddle, S.J.H. How to reduce sitting time? A review of behaviour change strategies used in sedentary behaviour reduction interventions among adults. Health Psychol. Rev. 2016, 10, 89–112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Selection of studies: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart.
Figure 1. Selection of studies: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart.
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Figure 2. Number of included articles by year of publication and continent of authors.
Figure 2. Number of included articles by year of publication and continent of authors.
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Figure 3. Approaches in targeted behavior in the included interventions with a physical component.
Figure 3. Approaches in targeted behavior in the included interventions with a physical component.
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Table 1. Descriptions of included studies.
Table 1. Descriptions of included studies.
StudyName of the DesignUser Evaluation (n)Description DesignObjective(s) of the Intervention
1Ahtinen et al. [34]Brainwolk11Walking meeting concept mediated with a mobile appEncouraging and supporting the practice of walking meetings
2Andersen et al. [35]N.S.160Email-based encouragementsEncouraging daily stair-walks together with colleagues
3Arrogi et al. [36]stAPP56Smartphone applicationInterrupting and reducing prolonged sitting behavior
4Bonn et al. [37]Health Integrator.209Platform offering a variety of public, private, and community servicesHealthier lifestyle behaviors (e.g., diet, physical activity, sleep)
5Brandstetter & Liebman [38]Fidgebot4Nao robotEncouraging the use of standing desks and “micro-exercises”
6Brombacher et al. [39]Stimulight61Tangible, ambient design to visualize physical activity level and share it with co-workersImproving physical activity level of office workers
7Cambo et al. [40]Breaksense6Smartphone application using a Bluetooth beacon infrastructure and a smartwatchEncouraging mobility during breaks
8Damen et al. [41]Workwalk-Physical outdoor walking route, which could be booked through the room booking systemEncouraging and supporting the practice of walking meetings
9Esakia et al. [42]FitAware7Three-component system including a smartwatch interface, companion application, and website.Encouraging group cohesion in physical activity intervention
10Fortmann et al. [43]MoveLamp10Ambient light displayMoving more frequently and taking more steps each day
11Foster et al. [44]StepMatron10Facebook application, designed to provide social and competitive context for daily pedometerMotivating physical activity in the working environment
12Garcia et al. [45]ESTHER 1.314Android pedometer applicationActive mini cycles of self-reflection on physical activity
13Goldberg et al. [46]Healthy Team Healthy U466Digital platformTeam-based health promotion and wellness program
14Gomes et al. [47]Steptacular2980Online interactive incentive systemEncouraging people to walk more
15Grundgeiger et al. [48]N.S.5Smartphone applicationCombating sedentary behavior based on human movement research and distributed prospective memory
16Güldenpfennig et al. [49]N.S.2TV visualization including ambient light systemEstablishing connectedness through the shared experience of positive behavior change
17Haque et al. [50]iGo26Smartphone applicationAssisting employees in promoting their physical activities
18Harjuniemi et al. [51]Idle Stripes Shirt-Aesthetic, clothing-integrated displayCreating awareness of immobility periods during typical sitting-intensive office work
19He & Agu [52]On117Smartphone applicationMaking people more aware of their unhealthy behaviors by highlighting sedentary behaviors
20Hirano et al. [53]Walkminder8Smartphone application using vibrationsInterrupting extended periods of inactivity and encouraging a more active lifestyle
21Kanaoka & Mutlu [54]N.S.24Humanlike NAO robot acting as a motivational agent through motivational interviewingIncreasing motivation for behavior change by talking about and reflecting on the causes of lack of motivation
22Khot et al. (2013) [55]Sweatatoms-3D-printed objects using the heartbeat patternMaking the experience of participating in physical activity more engaging beyond screen-based feedback
23Khot et al. (2015) [56]EdiPulse-3D-printed chocolates displaying cheerful messagesOpening new interaction possibilities supporting the physical activity experience
24Khot et al. (2015) [57]TastyBeatsNSA personalized sports drink representing the user’s heart rate dataExpanding the understanding technology potential to support the energy cycle when being physically active
25Komninos et al. [58]BeatClearWalker20Smartphone application including a music playerHelping users to learn how to walk at a moderate cadence
26Lin et al. [59]Motivate6Smartphone applicationProviding personalized and contextualized advice on physical activities
27Luo et al. [60] Time for Break25A break-prompting systemEnabling people to set their desired work duration and prompting them to stand up or move
28Madeira et al. [61]Breakout10Ambient feedback prototype, tangible designRecommending breaks of sedentary behavior at appropriate times
29Mateevitsi et al. [62]Healthbar8Ambient persuasive device (light)Helping users break up their prolonged sitting habits
30Maxhelaku et al. [63]N.S.-Smartphone applicationGiving information on how active people are and how they can improve their life and implement a program with activity tracker
31Min et al. [64]Pretty Pelvis-A virtual pet applicationPersuading social actors for prolonged engagement toward the breaking of sedentary behavior
32Mohadis & Ali [65]WargaFit8Smartphone applicationEncouraging simple physical activity, doable in an office-based environment (such as walking and stretching)
33Moradi and Wiberg [66](NEAT)-Lamp and Talking Tree6Sensor-based lamp connected to a computerIncreasing daily movement
34Mukhtar & Belaïd [67]Sedentaware4Smartphone applicationMotivating users to take corrective actions, after detecting prolonged sedentary behavior
35Munson & Consolvo [68]Goalpost & Goalline23Smartphone applicationSupporting weekly physical activity goal setting and tracking.
36Probst et al. [69]3D Active chair-Interactive office chairReducing sedentariness through smooth integration of light physical activity into the daily work routine
37Reeder et al. [70]BreakbotNSEmotionally expressive companion robotEncouraging employees to take breaks and socialize regularly
38Ren et al. (2019) [71]LightSit50Sensor mat embedded into an office chair and a lighting displayHelping people reduce physical inactivity and managing chronic stress at work
39Ren et al. (2018) [72]PCFT intervention20Activity tracker and smartphone applicationFitness breaks
40Ren et al. 2019 [73]Step-by-Step5 + 3A social exergame mediated by a connected cubic desk widget in a gift formatRelaying an object from a co-worker to another as a fitness task
41Simons et al. [74]Active Coach130Smartphone applicationPromoting an active lifestyle
42van Dantzig et al. [75]Sitcoach86Smartphone applicationProviding timely persuasive messages suggesting active breaks
43Wai Shan Ng and Ehud Sharlin [76]Mootchi2Projected avatar acting as a persuasive physical trainerProviding users with an emotional incentive for exercising
44Wang, Reiterer [77]SedentaryBar8Context-aware reminding system using an always-on progress bar (light)Helping screen-based workers to reduce sedentary behavior
45Xu et al. [12]N.S.7Cushion seat pan and backrest surfaceProviding posture information
Table 2. Behavior change techniques used in the studies included in the analysis.
Table 2. Behavior change techniques used in the studies included in the analysis.
Behavior Change TechniqueStudies
Rewards[36,40,42,44,47,49,50,55,57,63,68,70,78]
Creating awareness/self-reflection[36,39,43,45,51,66,67]
Social support/sharing[35,39,41,42,46,49,68,72,73]
Goal setting[37,40,46,52,68,72,74]
Persuasion[34,38,62,67,79]
Education/instruction/providing information[12,35,36,37,74]
Prompting[45,60,80]
Self-reflection/self-monitoring[68,74]
Tailored feedback[36,71]
Restructuring the physical environment[34,41]
Restructuring the social environment[41]
Reframing beliefs[38,41]
Gamification[40]
Motivational interviewing[54]
Positive feedback[76]
Habit formation[41]
Social cues for motivation[38]
Competition[44]
Not specified[48,53,58,59,61,65,69,75]
Table 3. Studies defining sedentary behavior (SB) or physical activity (PA) in included interventions.
Table 3. Studies defining sedentary behavior (SB) or physical activity (PA) in included interventions.
Targeted BehaviorStudies
Physical activity[35,43,46,53,58,65,66,74,77]
Sedentary behavior[36,45,48,60]
Not defined[12,34,37,38,39,40,41,42,44,47,49,50,51,52,54,55,56,57,59,61,62,63,64,67,68,69,70,71,72,73,75,76]
Table 4. Approaches in targeted behavior in the included interventions.
Table 4. Approaches in targeted behavior in the included interventions.
Approaches I Targeted BehaviorStudies
Learning new behavior[69]
Creating opportunities[34,38,41,52,58,69,76]
Creating awareness[12,35,36,37,39,40,42,43,44,45,46,47,48,49,50,51,53,54,55,56,57,59,60,62,63,64,65,66,67,68,70,71,72,73,74,75,76,77]
Table 5. Technology types of included interventions.
Table 5. Technology types of included interventions.
Technology TypeStudies
Lamp[39,43,49,62,66,77]
Chair[12,69,71,72]
Robots[38,54,70]
3D printing[55,56]
Phone application[34,36,40,42,45,48,50,52,53,58,59,62,64,65,67,68,74,75]
Other, with physical component[41,51,57,61,73]
Other, without physical component[35,37,44,46,47,60,76]
Table 6. Input measures of included interventions.
Table 6. Input measures of included interventions.
Input MeasuresStudies
Step count[1,4,5,13,16,29,31,32,37,41,46,48,52,54,57,62,68,71,72,74,81]
Heartrate[38,40,55,57,71,78]
Motion or gestures[48,52,61,62,66,69,76,77]
Caloric intake or energy expenditure[37,52,63]

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MDPI and ACS Style

Damen, I.; Brombacher, H.; Lallemand, C.; Brankaert, R.; Brombacher, A.; van Wesemael, P.; Vos, S. A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers. Int. J. Environ. Res. Public Health 2020, 17, 499. https://doi.org/10.3390/ijerph17020499

AMA Style

Damen I, Brombacher H, Lallemand C, Brankaert R, Brombacher A, van Wesemael P, Vos S. A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers. International Journal of Environmental Research and Public Health. 2020; 17(2):499. https://doi.org/10.3390/ijerph17020499

Chicago/Turabian Style

Damen, Ida, Hans Brombacher, Carine Lallemand, Rens Brankaert, Aarnout Brombacher, Pieter van Wesemael, and Steven Vos. 2020. "A Scoping Review of Digital Tools to Reduce Sedentary Behavior or Increase Physical Activity in Knowledge Workers" International Journal of Environmental Research and Public Health 17, no. 2: 499. https://doi.org/10.3390/ijerph17020499

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