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Digital Tools to Promote Healthy Eating for Working-Age Individuals: A Scoping Review

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Aarnout BrombacherAuthors Info & Claims

Chinese CHI '21: Proceedings of the Ninth International Symposium of Chinese CHI

Pages 1 - 8

https://doi.org/10.1145/3490355.3490356

Published: 07 February 2022 Publication History

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Abstract

In this scoping review, we aimed to understand current developments of digital tools for promoting healthy eating behaviors in a work context among working-age individuals and identify research gaps for future design opportunities. The papers published over the last decade (2010-2021) were searched in three databases: the Association for Computing Machinery (ACM) digital library, the interdisciplinary library Scopus, and the PubMed database. Initially, 2098 papers were identified, of which 16 papers were included in the final analysis. These 16 papers were published in 15 various conference proceedings or journals between 2010 and 2021, and mainly focused on tracking eating moment and promoting healthy food intake. Our findings showed that four types of digital tools for healthy eating promotion were commonly used, including mobile applications, wearables, service, and multicomponent (i.e., a combination between mobile apps and wearables). Moreover, we found that current digital tools made small using a range of existing working infrastructures. Future design research could focus on personalized, interactive, and playful digital tools in human-computer interaction field with behavior change techniques and user-centered approaches to promote healthy eating behaviors in daily work routines.

References

[1]

Alinia, S., Lassen, A.D., Krogholm, K.S., Christensen, T., Hels, O.H. and Tetens, I. 2011. A workplace feasibility study of the effect of a minimal fruit intervention on fruit intake. Public health nutrition. 14, 8 (2011), 1382–1387.

[2]

Allan, J., Querstret, D., Banas, K. and de Bruin, M. 2017. Environmental interventions for altering eating behaviours of employees in the workplace: a systematic review. Obesity Reviews. 18, 2 (2017), 214–226.

[3]

Almaghrabi, R., Villalobos, G., Pouladzadeh, P. and Shirmohammadi, S. 2012. A novel method for measuring nutrition intake based on food image. 2012 IEEE I2MTC - International Instrumentation and Measurement Technology Conference, Proceedings. (2012), 366–370.

[4]

Amft, O. 2008. Automatic dietary monitoring using on-body sensors: Detection of eating and drinking behaviour in healthy individuals.

[5]

Amft, O., Stäger, M., Lukowicz, P. and Tröster, G. 2005. Analysis of chewing sounds for dietary monitoring. International Conference on Ubiquitous Computing (2005), 56–72.

[6]

Amft, O. and Troster, G. 2006. Methods for detection and classification of normal swallowing from muscle activation and sound. 2006 Pervasive Health Conference and Workshops (2006), 1–10.

[7]

Anderson, L.M., Quinn, T.A., Glanz, K., Ramirez, G., Kahwati, L.C., Johnson, D.B., Buchanan, L.R., Archer, W.R., Chattopadhyay, S. and Kalra, G.P. 2009. The effectiveness of worksite nutrition and physical activity interventions for controlling employee overweight and obesity: a systematic review. American journal of preventive medicine. 37, 4 (2009), 340–357.

[8]

Arksey, H. and O'Malley, L. 2005. Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology: Theory and Practice. 8, 1 (2005), 19–32.

[9]

Bedri, A., Verlekar, A., Thomaz, E., Avva, V. and Starner, T. 2015. A wearable system for detecting eating activities with proximity sensors in the outer ear. ISWC 2015 - Proceedings of the 2015 ACM International Symposium on Wearable Computers. (2015), 91–92.

Digital Library

[10]

Benedict, M.A. and Arterburn, D. 2008. Worksite-based weight loss programs: a systematic review of recent literature. American Journal of Health Promotion. 22, 6 (2008), 408–415.

[11]

Bertran, F.A., Wilde, D., Berezvay, E. and Isbister, K. 2019. Playful human-food interaction research: State of the art and future directions. CHI PLAY 2019 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play (2019), 225–237.

Digital Library

[12]

Bi, S., Wang, T., Davenport, E., Peterson, R., Halter, R., Sorber, J. and Kotz, D. 2017. Toward a wearable sensor for eating detection. WearSys 2017 - Proceedings of the 2017 Workshop on Wearable Systems and Applications, co-located with MobiSys 2017 (2017), 17–22.

[13]

Bi, Y., Lv, M., Song, C., Xu, W., Guan, N. and Yi, W. 2015. AutoDietary: A Wearable Acoustic Sensor System for Food Intake Recognition in Daily Life. IEEE Sensors Journal. 16, 3 (2015), 806–816.

[14]

Branca, F., Nikogosian, H. and Lobstein, T. 2007. The challenge of obesity in the WHO European Region and the strategies for response: summary. World Health Organization.

[15]

Cahalin, L.P., Kaminsky, L., Lavie, C.J., Briggs, P., Cahalin, B.L., Myers, J., Forman, D.E., Patel, M.J., Pinkstaff, S.O. and Arena, R. 2015. Development and implementation of worksite health and wellness programs: a focus on non-communicable disease. Progress in cardiovascular diseases. 58, 1 (2015), 94–101.

[16]

Cheng Chia, G.L., Anderson, A. and McLean, L.A. 2019. Behavior change techniques incorporated in fitness trackers: Content analysis. JMIR mHealth and uHealth. 7, 7 (2019).

[17]

Chung, J., Chung, J., Oh, W., Yoo, Y., Lee, W.G. and Bang, H. 2017. A glasses-type wearable device for monitoring the patterns of food intake and facial activity. Scientific Reports. 7, December 2016 (2017), 1–8.

[18]

Close, M.A., Lytle, L.A., Chen, D.-G. and Viera, A.J. 2018. Using the theory of planned behavior to explain intention to eat a healthful diet among Southeastern United States office workers. Nutrition & Food Science. (2018).

[19]

Dong, Y., Scisco, J., Wilson, M., Muth, E. and Hoover, A. 2014. Detecting periods of eating during free-living by tracking wrist motion. IEEE Journal of Biomedical and Health Informatics. 18, 4 (2014), 1253–1260.

[20]

Evans, D. 2017. MyFitnessPal. Br J Sports Med. 51, 14 (2017), 1101–1102.

[21]

French, S.A., Jeffery, R.W., Story, M., Breitlow, K.K., Baxter, J.S., Hannan, P. and Snyder, M.P. 2001. Pricing and promotion effects on low-fat vending snack purchases: the CHIPS Study. American journal of public health. 91, 1 (2001), 112.

[22]

Hartwell, H., Appleton, K.M., Bray, J., Price, S., Mavridis, I., Giboreau, A., Perez-Cueto, F.J.A. and Ronge, M. 2019. Shaping smarter consumer food choices: The FoodSMART project. Nutrition Bulletin. 44, 2 (2019), 138–144.

[23]

He, S., Li, S., Nag, A., Feng, S., Han, T., Mukhopadhyay, S.C. and Powel, W. 2020. A comprehensive review of the use of sensors for food intake detection. Sensors and Actuators, A: Physical. 315, (2020).

[24]

Higgins, J.P. 2016. Smartphone applications for patients’ health and fitness. The American journal of medicine. 129, 1 (2016), 11–19.

[25]

Junker, H., Amft, O., Lukowicz, P. and Tröster, G. 2008. Gesture spotting with body-worn inertial sensors to detect user activities. Pattern Recognition. 41, 6 (2008), 2010–2024.

Digital Library

[26]

Lassen, A.D., Ernst, L., Poulsen, S., Andersen, K.K., Hansen, G.L., Biltoft-Jensen, A. and Tetens, I. 2012. Effectiveness of a Canteen Take Away concept in promoting healthy eating patterns among employees. Public health nutrition. 15, 3 (2012), 452–458.

[27]

Lazar, A., Koehler, C., Tanenbaum, J. and Nguyen, D.H. 2015. Why we use and abandon smart devices. UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. (2015), 635–646.

Digital Library

[28]

Maes, L., Van Cauwenberghe, E., Van Lippevelde, W., Spittaels, H., De Pauw, E., Oppert, J.-M., Van Lenthe, F.J., Brug, J. and De Bourdeaudhuij, I. 2012. Effectiveness of workplace interventions in Europe promoting healthy eating: a systematic review. European journal of public health. 22, 5 (2012), 677–683.

[29]

Martin, C.K., Nicklas, T., Gunturk, B., Correa, J.B., Allen, H.R. and Champagne, C. 2014. Measuring food intake with digital photography. Journal of Human Nutrition and Dietetics. 27, SUPPL.1 (2014), 72–81.

[30]

Matsushita, S. and Kaneshima, R. 2019. Motion sensing eyewear for daily healthcare monitoring. 2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019. (2019), 925–928.

[31]

Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G. and Group, P. 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS medicine. 6, 7 (2009), e1000097.

[32]

Neil, D., Lapierre, N., Bal, H., Perrault, S., Parker, D. and Reilly, D. 2013. Limber: Exploring motivation in a workplace exergame. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW. (2013), 239–242.

Digital Library

[33]

Orji, R. and Moffatt, K. 2018. Persuasive technology for health and wellness: State-of-the-art and emerging trends. Health informatics journal. 24, 1 (2018), 66–91.

[34]

Patrick, K., Hekler, E.B., Estrin, D., Mohr, D.C., Riper, H., Crane, D., Godino, J. and Riley, W.T. 2016. The pace of technologic change: implications for digital health behavior intervention research. Elsevier.

[35]

Quintiliani, L., Poulsen, S. and Sorensen, G. 2010. Healthy eating strategies in the workplace. International Journal of Workplace Health Management. 3, 3 (2010), 182–196.

[36]

Rahman, T., Adams, A.T., Zhang, M., Cherry, E., Zhou, B., Peng, H. and Choudhury, T. 2014. BodyBeat: A mobile system for sensing non-speech body sounds. MobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services. (2014), 2–13.

Digital Library

[37]

Rahman, T., Czerwinski, M., Gilad-Bachrach, R. and Johns, P. 2016. Predicting “about-To-eat” moments for just-in-Time eating intervention. DH 2016 - Proceedings of the 2016 Digital Health Conference. (2016), 141–150.

Digital Library

[38]

Siegel, J.A. and Sawyer, K.B. 2019. Eating disorders in the workplace: A qualitative investigation of women's experiences. Psychology of Women Quarterly. 43, 1 (2019), 37–58.

[39]

Soler, R.E. 2010. A Systematic Review of Selected Interventions for Worksite Health Promotion. The Assessment of Health Risks with Feedback. American Journal of Preventive Medicine. 38, 2 SUPPL. (2010), S237–S262.

[40]

Spahn, J.M., Reeves, R.S., Keim, K.S., Laquatra, I., Kellogg, M., Jortberg, B. and Clark, N.A. 2010. State of the evidence regarding behavior change theories and strategies in nutrition counseling to facilitate health and food behavior change. Journal of the American Dietetic Association. 110, 6 (2010), 879–891.

[41]

Stawarz, K.M. and Cox, A.L. 2015. Designing for health behavior change: HCI research alone is not enough. CHI’15 workshop: Crossing HCI and Health: Advancing Health and Wellness Technology Research in Home and Community Settings (2015).

[42]

Sysoeva, E., Zusik, I. and Symonenko, O. 2017. Food-to-person interaction: How to get information about what we eat? DIS 2017 Companion - Proceedings of the 2017 ACM Conference on Designing Interactive Systems. (2017), 106–110.

Digital Library

[43]

Thomas, J. and Harden, A. 2008. Methods for the thematic synthesis of qualitative research in systematic reviews. BMC medical research methodology. 8, 1 (2008), 1–10.

[44]

Thomaz, E., Essa, I. and Abowd, G.D. 2015. A practical approach for recognizing eating moments with wrist-mounted inertial sensing. (2015), 1029–1040.

Digital Library

[45]

Thomaz, E., Parnami, A., Essa, I. and Abowd, G.D. 2013. Feasibility of identifying eating moments from first-person images leveraging human computation. Proceedings of the 4th International SenseCam & Pervasive Imaging Conference (2013), 26–33.

Digital Library

[46]

Thomaz, E., Zhang, C., Essa, I. and Abowd, G.D. 2015. Inferring meal eating activities in real world settings from ambient sounds: A feasibility study. International Conference on Intelligent User Interfaces, Proceedings IUI. 2015-Janua, (2015), 427–431.

Digital Library

[47]

Tondello, G.F. 2016. An introduction to gamification in human-computer interaction. XRDS: Crossroads, The ACM Magazine for Students. 23, 1 (2016), 15–17.

Digital Library

[48]

Upadhyaya, M., Sharma, S., Pompeii, L.A., Sianez, M. and Morgan, R.O. 2020. Obesity prevention worksite wellness interventions for health care workers: A narrative review. Workplace health & safety. 68, 1 (2020), 32–49.

[49]

Verweij, L.M., Coffeng, J., van Mechelen, W. and Proper, K.I. 2011. Meta‐analyses of workplace physical activity and dietary behaviour interventions on weight outcomes. Obesity reviews. 12, 6 (2011), 406–429.

[50]

Vu, T., Lin, F., Alshurafa, N. and Xu, W. 2017. Wearable food intake monitoring technologies: A comprehensive review. Computers. 6, 1 (2017).

[51]

West, J.H., Belvedere, L.M., Andreasen, R., Frandsen, C., Hall, P.C. and Crookston, B.T. 2017. Controlling your “app” etite: how diet and nutrition-related mobile apps lead to behavior change. JMIR mHealth and uHealth. 5, 7 (2017), e95.

[52]

Wohlin, C. 2014. Guidelines for Snowballing in Systematic Literature Studies and a Replication in Software Engineering. (2014).

[53]

Zhang, C., Van Gorp, P., Derksen, M., Nuijten, R., IJsselsteijn, W.A., Zanutto, A., Melillo, F. and Pratola, R. 2021. Promoting Occupational Health through Gamification and E-Coaching: A 5-Month User Engagement Study. International Journal of Environmental Research and Public Health. 18, 6 (2021), 2823.

[54]

Zhang, R. and Amft, O. 2018. Free-living eating event spotting using EMG-monitoring eyeglasses. 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. 2018-Janua, March (2018), 128–132.

Cited By

Wimer BSzymanski AMetoyer R(2024)Beyond Static Labels: Unpacking Nutrition Comprehension in the Digital AgeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642672(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642672
Szymanski AWimer BAnuyah OEicher-Miller HMetoyer R(2024)Integrating Expertise in LLMs: Crafting a Customized Nutrition Assistant with Refined Template InstructionsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641924(1-22)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641924
Pan SBrouwer-Brolsma ERen XVos SBrombacher ALucassen D(2022)Record or Recall? Exploring Self-Reported Dietary Assessment Methods for Office Workers during the COVID-19 Work-from-Home PeriodNordic Human-Computer Interaction Conference10.1145/3546155.3546649(1-12)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546649

Index Terms

Digital Tools to Promote Healthy Eating for Working-Age Individuals: A Scoping Review
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
    2. Health informatics
2. Human-centered computing
  1. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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cover image ACM Other conferences

Chinese CHI '21: Proceedings of the Ninth International Symposium of Chinese CHI

October 2021

166 pages

ISBN:9781450386951

DOI:10.1145/3490355

Copyright © 2021 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

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Published: 07 February 2022

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Chinese CHI 2021: The Ninth International Symposium of Chinese CHI

October 16 - 17, 2021

Online, Hong Kong

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Cited By

Wimer BSzymanski AMetoyer R(2024)Beyond Static Labels: Unpacking Nutrition Comprehension in the Digital AgeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642672(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642672
Szymanski AWimer BAnuyah OEicher-Miller HMetoyer R(2024)Integrating Expertise in LLMs: Crafting a Customized Nutrition Assistant with Refined Template InstructionsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641924(1-22)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641924
Pan SBrouwer-Brolsma ERen XVos SBrombacher ALucassen D(2022)Record or Recall? Exploring Self-Reported Dietary Assessment Methods for Office Workers during the COVID-19 Work-from-Home PeriodNordic Human-Computer Interaction Conference10.1145/3546155.3546649(1-12)Online publication date: 8-Oct-2022
https://dl.acm.org/doi/10.1145/3546155.3546649

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