Author(s):
- Sumer S. Vaid
- Gabriella M. Harari
Abstract:
Recent years have seen a growth in the spread of digital technologies for self-tracking and personal informatics. Smartphones‚ in particular, stand out as being an ideal self-tracking technology that permits both active logging (via self-reports) and passive tracking of information (via phone logs and mobile sensors). In this chapter, we present the results of a literature review of smartphone-based personal informatics studies across three different disciplinary databases (computer science, psychology, and communication). In doing so, we propose a conceptual framework for organizing the smartphone-based personal informatics literature. Our framework situates self-tracking studies based on their substantive focus across two domains: (1) the measurement domain (whether the study uses subjective or objective data) and (2) the outcome of interest domain (whether the study aims to promote insight or change in physical and/or mental characteristics). We use this framework to identify and discuss research trends and gaps in the literature. For example, most research has been concentrated on tracking of objective measurements to change either physical or mental characteristics, while less research used subjective measures to study a physical outcome of interest. We conclude by pointing to promising future directions for research on self-tracking and personal informatics and emphasize the need for a greater appreciation of individual differences in future self-tracking research.
Documentation: https://doi.org/10.1007/978-3-030-31620-4_5
References:
Abney A, White B, Glick J, Bermudez A, Breckow P, Yow J, Heath P et al (2014) Evaluation of recording methods for user test sessions on mobile devices. In: Proceedings of the first ACM SIGCHI annual symposium on Computer-human interaction in play. ACM, pp 1–8
Ajzen I (1985) From intentions to actions: a theory of planned behavior. In: Action control. Springer, Berlin, pp 11–39
Athukorala K, Lagerspetz E, Von Kügelgen M, Jylhä A, Oliner AJ, Tarkoma S, Jacucci G (2014) How carat affects user behavior: implications for mobile battery awareness applications. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 1029–1038
Bai Y, Xu B, Jiang S, Yang H, Cui J (2013) Can you form healthy habit?: predicting habit forming states through mobile phone. In: Proceedings of the 8th international conference on body area networks. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), pp 144–147
Bandura A (2004) Health promotion by social cognitive means. Health Educ Behav 31(2):143–164
Barbarin AM, Saslow LR, Ackerman MS, Veinot TC (2018) Toward health information technology that supports overweight/obese women in addressing emotion-and stress-related eating. In: Proceedings of the 2018 CHI conference on human factors in computing systems. ACM, p 321
Bentley F, Tollmar K (2013) The power of mobile notifications to increase wellbeing logging behavior. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 1095–1098
Bentley F, Tollmar K, Stephenson P, Levy L, Jones B, Robertson S, Wilson J et al (2013) Health Mashups: presenting statistical patterns between wellbeing data and context in natural language to promote behavior change. ACM Trans Comput-Human Interact (TOCHI) 20(5):30
Bexheti A, Fedosov A, Findahl J, Langheinrich M, Niforatos E (2015) Re-live the moment: visualizing run experiences to motivate future exercises. In: Proceedings of the 17th international conference on human-computer interaction with mobile devices and services adjunct. ACM, pp 986–993
Bickmore TW, Kimani E, Trinh H, Pusateri A, Paasche-Orlow MK, Magnani JW (2018) Managing chronic conditions with a smartphone-based conversational virtual agent. In: Proceedings of the 18th international conference on intelligent virtual agents. ACM, pp 119–124
Brewer RS, Verdezoto N, Holst T, Rasmussen MK (2015) Tough shift: exploring the complexities of shifting residential electricity use through a casual mobile game. In: Proceedings of the 2015 annual symposium on computer-human interaction in play. ACM, pp 307–317
Campbell AT, Lane ND (2013) Smartphone sensing: a game changer for behavioral science. Workshop held at the summer institute for social and personality psychology. The University of California, Davis
Canzian L, Musolesi M (2015) Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 1293–1304
Chaudhry BM, Schaefbauer C, Jelen B, Siek KA, Connelly K (2016) Evaluation of a food portion size estimation interface for a varying literacy population. In: Proceedings of the 2016 CHI conference on human factors in computing systems. ACM, pp 5645–5657
Chen Y, Randriambelonoro M, Geissbuhler A, Pu P (2016) Social Incentives in pervasive fitness apps for obese and diabetic patients. In: Proceedings of the 19th ACM conference on computer supported cooperative work and social computing companion. ACM, pp 245–248
Choi HS, Lee HK, Ha JC (2012) The influence of smartphone addiction on mental health, campus life and personal relations-focusing on K university students. J Korean Data Inf Sci Soc 23(5):1005–1015
Choudhury T, Borriello G, Consolvo S, Haehnel D, Harrison B, Hemingway B, LeGrand L et al (2008) The mobile sensing platform: an embedded activity recognition system. IEEE Pervasive Comput 7(2):32–41
Ciman M, Donini M, Gaggi O, Aiolli F (2016) Stairstep recognition and counting in a serious game for increasing users’ physical activity. Pers Ubiquit Comput 20(6):1015–1033
Cuttone A, Larsen JE (2014) The long tail issue in large scale deployment of personal informatics. In: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing: adjunct publication. ACM, pp 691–694
Di Lascio E, Gashi S, Krasic D, Santini S (2017) In-classroom self-tracking for teachers and students: preliminary findings from a pilot study. In: Proceedings of the 2017 ACM international joint conference on pervasive and ubiquitous computing and proceedings of the 2017 ACM international symposium on wearable computers. ACM, pp 865–870
Doryab A, Frost M, Faurholt-Jepsen M, Kessing LV, Bardram JE (2015) Impact factor analysis: combining prediction with parameter ranking to reveal the impact of behavior on health outcome. Pers Ubiquit Comput 19(2):355–365
Du H, Youngblood GM, Pirolli P (2014) Efficacy of a smartphone system to support groups in behavior change programs. In: Proceedings of the wireless health 2014 on national institutes of health. ACM, pp 1–8
Du J, Wang Q, de Baets L, Markopoulos P (2017) Supporting shoulder pain prevention and treatment with wearable technology. In: Proceedings of the 11th EAI international conference on pervasive computing technologies for healthcare. ACM, pp 235–243
Epstein DA, Ping A, Fogarty J, Munson SA (2015) A lived informatics model of personal informatics. In: Proceedings of the UbiComp 2015 international joint conference on pervasive and ubiquitous computing. ACM, New York
Fang B, Xu Q, Park T, Zhang M (2016) AirSense: an intelligent home-based sensing system for indoor air quality analytics. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 109–119
Fox S, Duggan M (2013) Tracking for health. Available from http://www.pewinternet.org/2013/01/28/tracking-for-health
Fujiki Y, Kazakos K, Puri C, Pavlidis I, Starren J, Levine J (2007) NEAT-o-games: ubiquitous activity-based gaming. In: CHI2007 extended abstracts on Human factors in computing systems. ACM, pp 2369–2374
Gerson J, Plagnol AC, Corr PJ (2017) Passive and active facebook use measure (PAUM): validation and relationship to the reinforcement sensitivity theory. Personality Individ Differ 117:81–90
Glanz K, Rimer BK, Viswanath K (eds) (2008) Health behavior and health education: theory, research, and practice. Wiley, New York
Götz FM, Stieger S, Reips UD (2017) Users of the main smartphone operating systems (iOS, Android) differ only little in personality. PLoS ONE 12(5):e0176921
Gouveia R, Karapanos E, Hassenzahl M (2015) How do we engage with activity trackers?: a longitudinal study of habito. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 1305–1316
Greis M, Dingler T, Schmidt A, Schmandt C (2017) Leveraging user-made predictions to help understand personal behavior patterns. In: Proceedings of the 19th international conference on human-computer interaction with mobile devices and services. ACM, p 104
Grimes A, Kantroo V, Grinter RE (2010) Let’s play!: mobile health games for adults. In: Proceedings of the 12th ACM international conference on Ubiquitous computing. ACM, pp 241–250
Gui X, Chen Y, Caldeira C, Xiao D, Chen Y (2017) When fitness meets social networks: investigating fitness tracking and social practices on werun. In: Proceedings of the 2017 CHI conference on human factors in computing systems. ACM, pp 1647–1659
Gweon G, Kim B, Kim J, Lee KJ, Rhim J, Choi J (2018) MABLE: mediating young children’s smart media usage with augmented reality. In: Proceedings of the 2018 CHI conference on human factors in computing systems. ACM, p 13
Harari GM, Gosling SD, Wang R, Chen F, Chen Z, Campbell AT (2017a) Patterns of behavior change in students over an academic term: A preliminary study of activity and sociability behaviors using smartphone sensing methods. Comput Hum Behav 67:129–138
Harari GM, Müller SR, Aung MS, Rentfrow PJ (2017b) Smartphone sensing methods for studying behavior in everyday life. Curr Opin Behav Sci 18:83–90
Harari GM, Müller SR, Gosling SD (2018) Naturalistic assessment of situations using mobile sensing methods. In: The Oxford handbook of psychological situations
Henrich J, Heine SJ, Norenzayan A (2010) The weirdest people in the world? Behav Brain Sci 33(2–3):61–83
Hirano SH, Farrell RG, Danis CM, Kellogg WA (2013) WalkMinder: encouraging an active lifestyle using mobile phone interruptions. In: CHI2013 extended abstracts on human factors in computing systems. ACM, pp 1431–1436
Hollis V, Konrad A, Springer A, Antoun M, Antoun C, Martin R, Whittaker S (2017) What does all this data mean for my future mood? actionable analytics and targeted reflection for emotional well-being. Human–Computer Interact 32(5–6):208–267
Hsu A, Yang J, Yilmaz YH, Haque MS, Can C, Blandford AE (2014) Persuasive technology for overcoming food cravings and improving snack choices. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 3403–3412
Huang Y, Xiong H, Leach K, Zhang Y, Chow P, Fua K, Barnes LE et al (2016) Assessing social anxiety using GPS trajectories and point-of-interest data. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 898–903
Hwang C, Pushp S (2018) A mobile system for investigating the user’s stress causes in daily life. In: Proceedings of the 2018 ACM international joint conference and 2018 international symposium on pervasive and ubiquitous computing and wearable computers. ACM, pp 66–69
Johansen B, Petersen MK, Pontoppidan NH, Sandholm P, Larsen JE (2017) Rethinking hearing aid fitting by learning from behavioral patterns. In: Proceedings of the 2017 CHI conference extended abstracts on human factors in computing systems. ACM, pp 1733–1739
Jylhä A, Nurmi P, Sirén M, Hemminki S, Jacucci G (2013) Matkahupi: a persuasive mobile application for sustainable mobility. In: Proceedings of the 2013 ACM conference on pervasive and ubiquitous computing adjunct publication. ACM,pp 227–230
Kadomura A, Li CY, Tsukada K, Chu HH, Siio I (2014) Persuasive technology to improve eating behavior using a sensor-embedded fork. In: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 319–329
Kamphorst BA, Klein MC, Van Wissen A (2014) Autonomous E-coaching in the wild: empirical validation of a model-based reasoning system. In: Proceedings of the 2014 international conference on autonomous agents and multi-agent systems. International Foundation for Autonomous Agents and Multiagent Systems, pp 725–732
Kersten-van Dijk ET, Westerink JH, Beute F, IJsselsteijn WA (2017) Personal informatics, self-insight, and behavior change: a critical review of current literature. Human–Computer Interact 32(5–6):268–296
Ko M, Choi S, Yang S, Lee J, Lee U (2015) FamiLync: facilitating participatory parental mediation of adolescents’ smartphone use. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 867–878
Kocielnik R, Avrahami D, Marlow J, Lu D, Hsieh G (2018) Designing for workplace reflection: a chat and voice-based conversational agent. In: Proceedings of the 2018 on designing interactive systems conference 2018. ACM, pp 881–894
Kocielnik R, Xiao L, Avrahami D, Hsieh G (2018b) Reflection companion: a conversational system for engaging users in reflection on physical activity. Proc ACM Interact Mob Wearable Ubiquitous Technol 2(2):70
Kuo PYP (2018) Design for self-experimentation: participant reactions to self-generated behavioral prompts for sustainable living. In Proceedings of the 2018 ACM international joint conference and 2018 international symposium on pervasive and ubiquitous computing and wearable computers. ACM, pp 802–808
Lacroix J, Saini P, Holmes R (2008) The relationship between goal difficulty and performance in the context of a physical activity intervention program. In: Proceedings of the 10th international conference on Human computer interaction with mobile devices and services. ACM,pp 415–418
Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150
Lee ML, Dey AK (2014) Real-time feedback for improving medication taking. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 2259–2268
Lee J, Cho D, Kim J, Im E, Bak J, Lee KH, Kim J (2017) Itchtector: a wearable-based mobile system for managing itching conditions. In: Proceedings of the 2017 CHI conference on human factors in computing systems. ACM, pp 893–905
Li I, Dey A, Forlizzi J (2010) A stage-based model of personal informatics systems. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 557–566
Li N, Zhao C, Choe EK, Ritter FE (2015) HHeal: a personalized health app for flu tracking and prevention. In: Proceedings of the 33rd annual ACM conference extended abstracts on human factors in computing systems. ACM, pp 1415–1420
Li Y, Cao Z, Wang J (2017) Gazture: design and implementation of a gaze based gesture control system on tablets. Proc ACM Interact, Mob, Wearable Ubiquitous Technol 1(3):74
Lien CH, Cao Y (2014) Examining WeChat users’ motivations, trust, attitudes, and positive word-of-mouth: Evidence from China. Comput Hum Behav 41:104–111
LiKamWa R, Liu Y, Lane ND, Zhong L (2013) Moodscope: building a mood sensor from smartphone usage patterns. In: Proceeding of the 11th annual international conference on Mobile systems, applications, and services. ACM, pp 389–402
Luhanga ET (2015) Evaluating effectiveness of stimulus control, time management and self-reward for weight loss behavior change. In: Adjunct proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing and Proceedings of the 2015 ACM international symposium on wearable computers. ACM, pp 441–446
Lupton D (2013) Quantifying the body: monitoring and measuring health in the age of mHealth technologies. Crit Public Health 23(4):393–403
Lupton D (2014) Self-tracking cultures: towards a sociology of personal informatics. In: Proceedings of the 26th Australian computer-human interaction conference on designing futures: the future of design. ACM, pp 77–86
Madan A, Moturu ST, Lazer D, Pentland AS (2010) Social sensing: obesity, unhealthy eating and exercise in face-to-face networks. In: Wireless Health 2010. ACM, pp 104–110
Marcu G, Misra A, Caro K, Plank M, Leader A, Barsevick A (2018) Bounce: designing a physical activity intervention for breast cancer survivors. In: Proceedings of the 12th EAI international conference on pervasive computing technologies for healthcare. ACM, pp 25–34
Mashhadi A, Kawsar F, Mathur A, Dugan C, Shami NS (2016) Let’s talk about the quantified workplace. In: Proceedings of the 19th ACM conference on computer supported cooperative work and social computing companion. ACM, pp 522–528
Mehrotra A, Hendley R, Musolesi M (2016) Towards multi-modal anticipatory monitoring of depressive states through the analysis of human-smartphone interaction. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing: adjunct. ACM, pp 1132–1138
Meyer J, Heuten W, Boll S (2016) No effects but useful? long term use of smart health devices. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing: adjunct. ACM, pp 516–521
Mollee JS, Middelweerd A, Velde SJT, Klein MC (2017) Evaluation of a personalized coaching system for physical activity: user appreciation and adherence. In: Proceedings of the 11th EAI international conference on pervasive computing technologies for healthcare. ACM, pp 315–324
Möller A, Kranz M, Schmid B, Roalter L, Diewald S (2013) Investigating self-reporting behavior in long-term studies. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 2931–2940
Montag C, Błaszkiewicz K, Lachmann B, Sariyska R, Andone I, Trendafilov B, Markowetz A (2015) Recorded behavior as a valuable resource for diagnostics in mobile phone addiction: evidence from psychoinformatics. Behav Sci 5(4):434–442
Montag C, Becker B, Gan C (2018) The multi-purpose application WeChat: a review on recent research. Front Psychol 9:2247
Muaremi A, Seiter J, Tröster G, Bexheti A (2013) Monitor and understand pilgrims: data collection using smartphones and wearable devices. In: Proceedings of the 2013 ACM conference on pervasive and ubiquitous computing adjunct publication. ACM, pp 679–688
Paay J, Kjeldskov J, Skov MB, Srikandarajah N, Brinthaparan U (2015) QuittyLink: using smartphones for personal counseling to help people quit smoking. In: Proceedings of the 17th international conference on human-computer interaction with mobile devices and services. ACM, pp 98–104
Pardes A (2019) Curb your time wasted on the web with this browser extension. Retrieved from https://www.wired.com/story/habitlab-browser-extension/
Paré G, Leaver C, Bourget C (2018) Diffusion of the digital health self-tracking movement in canada: results of a national survey. J Med Internet Res 20(5)
Parecki A (2018) My GPS Logs. Retrieved from https://aaronparecki.com/gps/
Paredes P, Gilad-Bachrach R, Czerwinski M, Roseway A, Rowan K, Hernandez J (2014) PopTherapy: coping with stress through pop-culture. In: Proceedings of the 8th international conference on pervasive computing technologies for healthcare. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), pp 109–117
Pipke RM, Wegerich SW, Saidi A, Stehlik J (2013) Feasibility of personalized nonparametric analytics for predictive monitoring of heart failure patients using continuous mobile telemetry. In: Proceedings of the 4th conference on wireless health. ACM, p 7
Prochaska JO, Velicer WF (1997) The transtheoretical model of health behavior change. Am J Health Promot 12(1):38–48
Quantified Self Labs (2015) Quantified self—self knowledge through numbers. Retrieved from http://www.quantifiedself.com
Rabbi M, Aung MH, Zhang M, Choudhury T (2015) MyBehavior: automatic personalized health feedback from user behaviors and preferences using smartphones. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 707–718
Rentfrow PJ, Gosling SD (2012) Using smart-phones as mobile sensing devices: a practical guide for psychologists to current and potential capabilities. In: Preconference for the annual meeting of the Society for personality and social psychology. San Diego, CA
Rooksby J, Rost M, Morrison A, Chalmers MC (2014) Personal tracking as lived informatics. In: Proceedings of the 32nd annual ACM conference on human factors in computing systems. ACM, pp 1163–1172
Sanders R (2017) Self-tracking in the digital era: biopower, patriarchy, and the new biometric body projects. Body Soc 23(1):36–63
Sasaki W, Nakazawa J, Okoshi T (2018) Comparing ESM timings for emotional estimation model with fine temporal granularity. In: Proceedings of the 2018 ACM international joint conference and 2018 international symposium on pervasive and ubiquitous computing and wearable computers. ACM, pp 722–725
Simon J, Jahn M, Al-Akkad A (2012) Saving energy at work: the design of a pervasive game for office spaces. In: Proceedings of the 11th international conference on mobile and ubiquitous multimedia. ACM, p 9
Singh P (2012) Smartphone: the emerging gadget of choice for the urban Indian. The Nielsen Company Retrived from http://www.nielsen.com/content/dam/corporate/india/reports/2012/Featured
Springer A, Hollis V, Whittaker S (2018) Mood modeling: accuracy depends on active logging and reflection. Pers Ubiquitous Comput 1–15
Sullivan J (2014) China’s Weibo: Is faster different? New Media Soc 16(1):24–37
Swan M (2012) Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0. J Sens Actuator Netw 1(3):217–253
Tang LY, Hsiu PC, Huang JL, Chen MS (2013) iLauncher: an intelligent launcher for mobile apps based on individual usage patterns. In: Proceedings of the 28th annual ACM symposium on applied computing. ACM, pp 505–512
Tulusan J, Staake T, Fleisch E (2012) Providing eco-driving feedback to corporate car drivers: what impact does a smartphone application have on their fuel efficiency? In: Proceedings of the 2012 ACM conference on ubiquitous computing. ACM, pp 212–215
Van Bruggen D, Liu S, Kajzer M, Striegel A, Crowell CR, D’Arcy J (2013) Modifying smartphone user locking behavior. In: Proceedings of the ninth symposium on usable privacy and security. ACM, p 10
Wang R, Harari G, Hao P, Zhou X, Campbell AT (2015) SmartGPA: how smartphones can assess and predict academic performance of college students. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 295–306
Wang R, Aung MS, Abdullah S, Brian R, Campbell AT, Choudhury T, Tseng VW et al (2016) CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 886–897
Wang W, Harari GM, Wang R, Müller SR, Mirjafari S, Masaba K, Campbell AT (2018a) Sensing behavioral change over time: using within-person variability features from mobile sensing to predict personality traits. Proc ACM Interact Mob Wearable Ubiquitous Technol 2(3):141
Wang R, Wang W, daSilva A, Huckins JF, Kelley WM, Heatherton TF, Campbell AT (2018b) Tracking depression dynamics in college students using mobile phone and wearable sensing. Proc ACM Interact Mob Wearable Ubiquitous Technol 2(1):43
Weiss M, Staake T, Mattern F, Fleisch E (2012) PowerPedia: changing energy usage with the help of a community-based smartphone application. Pers Ubiquit Comput 16(6):655–664
Wolf G (2010) The data-driven life. N Y Times 28:2010
Yangjingjing X (2012) The science of the self. Global Times. Retrieved from http://www.globaltimes.cn/content/750476.shtml
Zheng Y, Li Q, Chen Y, Xie X, Ma WY (2008) Understanding mobility based on GPS data. In: Proceedings of the 10th international conference on Ubiquitous computing. ACM, pp 312–321
Zuckerman O, Gal-Oz A (2014) Deconstructing gamification: evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity. Pers Ubiquitous Comput 18(7):1705–1719