Work in Progress

Supporting Anxiety Patients’ Self-Reflection through Visualization of Physiological Data.

Authors:

Rikke Hagensby JensenAuthors Info & Claims

OzCHI '20: Proceedings of the 32nd Australian Conference on Human-Computer Interaction

Pages 742 - 747

https://doi.org/10.1145/3441000.3441037

Published: 15 February 2021 Publication History

Abstract

Anxiety patients are often constrained in daily life to an extent where they experience severe difficulties in keeping a job or being with family, hereby leading to a decreased quality of life. Self-reflecting on emotional reactions during daily life activities is a critical part of anxiety treatment, and can lead to increased self-awareness and eventually behavior change to cope with the disorders. mHealth technologies have emerged as a means to improve effectiveness of treatment for mental disorders, yet few studies have utilized real-time data from physiological sensors to support self-reflection on emotions. We conducted a study with two anxiety patients and their psychiatrists to explore their experiences of using GSR sensor data as visual cues to support daily self-reflection on anxiety episodes. We contribute with findings indicating that GSR visualization as part of anxiety treatment can support patients in confirming episodes. Furthermore, we present design considerations for such visualizations.

References

[1]

Amy M. Bauer, Matthew Iles-Shih, Reza Hosseini Ghomi, Tessa Rue, Tess Grover, Naomi Kincler, Monica Miller, and Wayne J. Katon. 2018. Acceptability of mHealth augmentation of Collaborative Care: A mixed methods pilot study. General Hospital Psychiatry 51, November 2017: 22–29. https://doi.org/10.1016/j.genhosppsych.2017.11.010

[2]

Judith S. Beck. 2011. Cognitive Behavior Therapy: Basics and Beyond. Guilford Publications.

[3]

Kirsten Boehner, Rogério DePaula, Paul Dourish, and Phoebe Sengers. 2005. Affect: From information to interaction. In Critical Computing - Between Sense and Sensibility - Proceedings of the 4th Decennial Aarhus Conference, 59–68. https://doi.org/10.1145/1094562.1094570

Digital Library

[4]

Mehdi Boukhechba, Philip Chow, Karl Fua, Bethany A. Teachman, and Laura E. Barnes. 2018. Predicting social anxiety from global positioning system traces of college students: Feasibility study. Journal of Medical Internet Research 20, 7. https://doi.org/10.2196/10101

[5]

Mehdi Boukhechba, Jiaqi Gong, Kamran Kowsari, Mawulolo K. Ameko, Karl Fua, Philip I. Chow, Yu Huang, Bethany A. Teachman, and Laura E. Barnes. 2018. Physiological changes over the course of cognitive bias modification for social anxiety. 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018 2018-Janua, March: 422–425. https://doi.org/10.1109/BHI.2018.8333458

[6]

Anders Bruun. 2018. It's Not Complicated: A Study of Non-specialists Analyzing GSR Sensor Data to Detect UX Related Events. In Proceedings of the 10th Nordic Conference on Human-Computer Interaction (NordiCHI ’18), 170–183. https://doi.org/10.1145/3240167.3240183

Digital Library

[7]

Anders Bruun and Simon Ahm. 2015. Mind the Gap! Comparing Retrospective and Concurrent Ratings of Emotion in User Experience Evaluation. In 15th IFIP TC13 Conference on Human-Computer Interaction (INTERACT), 237–254. https://doi.org/http://dx.doi.org/10.1007/978-3-319-22701-6_17

Digital Library

[8]

Anders Bruun, Effie Lai-Chong Law, Matthias Heintz, and Poul Svante Eriksen. 2016. Asserting Real-Time Emotions through Cued-Recall: Is it Valid? In Proceedings of the 9th Nordic Conference on Computer-Human Interaction (NordiCHI). https://doi.org/http://dx.doi.org/10.1145/2971485.2971516

Digital Library

[9]

Anders Bruun and Martin Lynge Stentoft. 2019. Lifelogging in the Wild: Participant Experiences of Using Lifelogging as a Research Tool. In Proceedings of the 17th IFIP TC13 Conference on Human-Computer Interaction (INTERACT), 431–451. https://doi.org/10.1007/978-3-030-29387-1_24

Digital Library

[10]

Laura Jane Bry, Tommy Chou, Elizabeth Miguel, and Jonathan S. Comer. 2018. Consumer Smartphone Apps Marketed for Child and Adolescent Anxiety: A Systematic Review and Content Analysis. Behavior Therapy 49, 2: 249–261. https://doi.org/10.1016/j.beth.2017.07.008

[11]

Philippi C.l and Koenigs M. 2014. The neuropsychology of self-reflection in psychiatric illness. Journal of Psychiatric Research: 55–63. https://doi.org/10.1016/j.jpsychires.2014.03.004.The

[12]

Giancarlo Dimaggio, Stijn Vanheule, Paul H. Lysaker, Antonino Carcione, and Giuseppe Nicolò. 2009. Impaired self-reflection in psychiatric disorders among adults: A proposal for the existence of a network of semi independent functions. Consciousness and Cognition 18, 3: 653–664. https://doi.org/10.1016/j.concog.2009.06.003

[13]

Gavin Doherty, David Coyle, and Mark Matthews. 2010. Design and evaluation guidelines for mental health technologies. Interacting with Computers 22, 4: 243–252. https://doi.org/10.1016/j.intcom.2010.02.006

Digital Library

[14]

Empatica. E4 Wristband.

[15]

Malin Forne. 2012. Physiology as a Tool for UX and Usability Testing. Stockholm University.

[16]

Eva Ganglbauer, Stephanie Deutsch, and Manfred Tscheligi. 2009. Applying psychophysiological methods for measuring user experience: possibilities, challenges and feasibility. In User Experience Evaluation Methods in Product Development (UXEM). https://doi.org/10.1.1.189.3410

[17]

Yiwen Gao, He Li, and Yan Luo. 2015. An empirical study of wearable technology acceptance in healthcare. Industrial Management and Data Systems 115, 9: 1704–1723. https://doi.org/10.1108/IMDS-03-2015-0087

[18]

Enrique Garcia-Ceja, Michael Riegler, Tine Nordgreen, Petter Jakobsen, Ketil J. Oedegaard, and Jim Tørresen. 2018. Mental health monitoring with multimodal sensing and machine learning: A survey. Pervasive and Mobile Computing 51: 1–26. https://doi.org/10.1016/j.pmcj.2018.09.003

[19]

Tian Hao, Jeffrey Rogers, Hung-Yang Chang, Marion Ball, Kimberly Walter, Si Sun, Ching-Hua Chen, and Xinxin Zhu. 2017. Towards Precision Stress Management: Design and Evaluation of a Practical Wearable Sensing System for Monitoring Everyday Stress. Iproceedings 3, 1: e15. https://doi.org/10.2196/iproc.8441

[20]

Marc Hassenzahl. 2001. The effect of perceived hedonic quality on product appealingness. International Journal of Human-Computer Interaction 13, 4: 481–499. https://doi.org/10.1207/S15327590IJHC1304_07

[21]

Nicholas C. Jacobson, Berta Summers, and Sabine Wilhelm. 2020. Digital biomarkers of social anxiety severity: Digital phenotyping using passive smartphone sensors. Journal of Medical Internet Research 22, 5: e16875. https://doi.org/10.2196/16875

[22]

Daniel Kahneman, Alan B Krueger, David A Schkade, Norbert Schwarz, and Arthur A Stone. 2004. A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method. Science 306, 5702: 1776 LP – 1780. Retrieved from http://science.sciencemag.org/content/306/5702/1776.abstract

[23]

Daniel Kahneman, Alan B Krueger, David Schkade, Norbert Schwarz, and Arthur Stone. 2004. The Day Reconstruction Method (DRM): Instrument Documentation.

[24]

Nikolaos Kazantzis, Craig Whittington, and Frank Dattilio. 2010. Meta-analysis of homework effects in cognitive and behavioral therapy: A replication and extension. Clinical Psychology: Science and Practice 17, 2: 144–156. https://doi.org/10.1111/j.1468-2850.2010.01204.x

[25]

Mathias Kivikangas, Inger Ekman, Guillaume Chanel, Simo Jävelä, Ben Cowley, Mikko Salminen, Pentti Henttonen, and Niklas Ravaja. 2010. Review on Psychophysiological Methods in Game Research. In Nordic Digital Games Research Association.

[26]

Predrag Klasnja and Wanda Pratt. 2012. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. Journal of Biomedical Informatics 45, 1: 184–198. https://doi.org/10.1016/j.jbi.2011.08.017

Digital Library

[27]

Evan Kleiman, Alexander J. Millner, Victoria W. Joyce, Carol C. Nash, Ralph J. Buonopane, and Matthew K. Nock. 2019. Using wearable physiological monitors with suicidal adolescent inpatients: Feasibility and acceptability study. Journal of Medical Internet Research 21, 9: e13725. https://doi.org/10.2196/13725

[28]

Kurt Kroenke, Robert L. Spitzer, Janet B. W. Williams, Patrick O. Monahan, and Bernd Löwe. 2007. Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Annals of Internal Medicine 146, 5: 317–325.

[29]

Peter J. Lang. 1995. The emotion probe: Studies of motivation and attention. American Psychologist 50, 5: 372–385. https://doi.org/10.1037/0003-066X.50.5.372

[30]

Fanny Levy, Pierre Leboucher, Gilles Rautureau, and Roland Jouvent. 2016. E-virtual reality exposure therapy in acrophobia: A pilot study. Journal of Telemedicine and Telecare 22, 4: 215–220. https://doi.org/10.1177/1357633X15598243

[31]

Diana MacLean, Asta Roseway, and Mary Czerwinski. 2013. MoodWings: A wearable biofeedback device for real-time stress intervention. ACM International Conference Proceeding Series. https://doi.org/10.1145/2504335.2504406

Digital Library

[32]

Daniel McDuff, Amy Karlson, Ashish Kapoor, Asta Roseway, and Mary Czerwinski. 2012. AffectAura: An intelligent system for emotional memory. Conference on Human Factors in Computing Systems - Proceedings: 849–858. https://doi.org/10.1145/2207676.2208525

Digital Library

[33]

David C. Mohr, Mi Zhang, and Stephen M. Schueller. 2017. Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning. Annual Review of Clinical Psychology 13, 1: 23–47. https://doi.org/10.1146/annurev-clinpsy-032816-044949

[34]

Ramin Mojtabai, Mark Olfson, Nancy A. Sampson, Robert Jin, Benjamin Druss, Philip S. Wang, Kenneth B. Wells, Harold A. Pincus, and Ronald C. Kessler. 2011. Barriers to mental health treatment: Results from the National Comorbidity Survey Replication. Psychological Medicine 41, 8: 1751–1761. https://doi.org/10.1017/S0033291710002291

[35]

Merete M. Mørch and Nicole K Rosenberg. 2005. Kognitiv terapi: modeller og metoder. Hans Reitzels Forlag.

[36]

Jennifer Nicholas, Katie Shilton, Stephen M Schueller, Elizabeth L Gray, Mary J Kwasny, and David C Mohr. 2019. The Role of Data Type and Recipient in Individuals’ Perspectives on Sharing Passively Collected Smartphone Data for Mental Health: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 7, 4: e12578. https://doi.org/10.2196/12578

[37]

C Matthew Northrup, Johanna Lantz, and Theresa Hamlin. 2016. Wearable Stress Sensors for Children With Autism Spectrum Disorder With In Situ Alerts to Caregivers via a Mobile Phone. Iproceedings 2, 1: e9. https://doi.org/10.2196/iproc.6119

[38]

Miranda Olff. 2015. Mobile mental health: A challenging research agenda. European Journal of Psychotraumatology 6: 1–8. https://doi.org/10.3402/ejpt.v6.27882

[39]

Mary M. Omodei and Jim McLennan. 1994. Studying complex decision making in natural settings: using a head-mounted video camera to study competitive orienteering. Perceptual and motor skills 79, 3 Pt 2: 1411–25. https://doi.org/10.2466/pms.1994.79.3f.1411

[40]

Ming Zher Poh, Nicholas C. Swenson, and Rosalind W. Picard. 2010. A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. IEEE Transactions on Biomedical Engineering 57, 5: 1243–1252. https://doi.org/10.1109/TBME.2009.2038487

[41]

Nicole K. Rosenberg and Charlotte Emborg. 2012. Håndbog om Angst. Pfizer Danmark, Ballerup.

[42]

Moushumi Sharmin, Andrew Raij, David Epstien, Inbal Nahum-Shani, J. Gayle Beck, Sudip Vhaduri, Kenzie Preston, and Santosh Kumar. 2015. Visualization of time-series sensor data to inform the design of just-in-Time adaptive stress interventions. UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing: 505–516. https://doi.org/10.1145/2750858.2807537

Digital Library

[43]

Charles D. Spielberger. 1972. Anxiety: Current Trends in Theory and Research. Academic Press.

[44]

Anna Ståhl, Kristina Höök, Martin Svensson, Alex S Taylor, and Marco Combetto. 2009. Experiencing the Affective Diary. Personal Ubiquitous Comput. 13, 5: 365–378. https://doi.org/10.1007/s00779-008-0202-7

Digital Library

[45]

David F. Tolin. 2010. Is cognitive-behavioral therapy more effective than other therapies?. A meta-analytic review. Clinical Psychology Review 30, 6: 710–720. https://doi.org/10.1016/j.cpr.2010.05.003

[46]

Fernanda B Viégas, Scott Golder, and Judith Donath. 2006. Visualizing Email Content: Portraying Relationships from Conversational Histories.

[47]

Zachary W. Adams, Erin A. McClure, Kevin M. Gray, Carla Kmett Danielson, Frank A. Treiber, and Kenneth J. Ruggiero. 2017. Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research. Journal of Psychiatric Research 85: 1–14. https://doi.org/10.1016/j.jpsychires.2016.10.019

[48]

Harvey A. Whiteford, Louisa Degenhardt, Jürgen Rehm, Amanda J. Baxter, Alize J. Ferrari, Holly E. Erskine, Fiona J. Charlson, Rosana E. Norman, Abraham D. Flaxman, Nicole Johns, Roy Burstein, Christopher J.L. Murray, and Theo Vos. 2013. Global burden of disease attributable to mental and substance use disorders: Findings from the Global Burden of Disease Study 2010. The Lancet 382, 9904: 1575–1586. https://doi.org/10.1016/S0140-6736(13)61611-6

Cited By

Bosch RNoordzij MWesterhof GBohlmeijer E(2024)Integration of Sensor-Based Technology in Mental Healthcare: A Systematic Scoping ReviewJournal of Technology in Behavioral Science10.1007/s41347-024-00427-5Online publication date: 2-Jul-2024
https://doi.org/10.1007/s41347-024-00427-5
Polhemus ANovak JMajid SSimblett SMorris DBruce SBurke PDockendorf MTemesi GWykes T(2022)Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User PerspectivesJMIR Mental Health10.2196/252499:4(e25249)Online publication date: 28-Apr-2022
https://doi.org/10.2196/25249

Recommendations

Understanding self-reflection: how people reflect on personal data through visual data exploration
PervasiveHealth '17: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

Rapid advancements in consumer technologies enable people to collect a wide range of personal data. With a proper means for people to ask questions and explore their data, longitudinal data feeds from multiple self-tracking tools pose great ...
Psychological and physiological responses to stressful situations in immersive virtual reality

Several studies in the literature have shown positive psychophysical effects during or immediately after mindfulness meditation. However, the extent to which such positive effects are maintained in real-life, stressful contexts, remains unclear. This ...
Boredom, engagement and anxiety as indicators for adaptation to difficulty in games
MindTrek '08: Proceedings of the 12th international conference on Entertainment and media in the ubiquitous era

This paper proposes an approach based on emotion recognition to maintain engagement of players in a game by modulating the game difficulty. Physiological and questionnaire data were gathered from 20 players during and after playing a Tetris game at ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

OzCHI '20: Proceedings of the 32nd Australian Conference on Human-Computer Interaction

December 2020

764 pages

ISBN:9781450389754

DOI:10.1145/3441000

Copyright © 2020 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 February 2021

Check for updates

Author Tags

Qualifiers

Work in progress
Research
Refereed limited

Conference

OzCHI '20

OzCHI '20: 32nd Australian Conference on Human-Computer-Interaction

December 2 - 4, 2020

NSW, Sydney, Australia

Acceptance Rates

Overall Acceptance Rate 362 of 729 submissions, 50%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
245
Total Downloads

Downloads (Last 12 months)74
Downloads (Last 6 weeks)2

Reflects downloads up to 01 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Bosch RNoordzij MWesterhof GBohlmeijer E(2024)Integration of Sensor-Based Technology in Mental Healthcare: A Systematic Scoping ReviewJournal of Technology in Behavioral Science10.1007/s41347-024-00427-5Online publication date: 2-Jul-2024
https://doi.org/10.1007/s41347-024-00427-5
Polhemus ANovak JMajid SSimblett SMorris DBruce SBurke PDockendorf MTemesi GWykes T(2022)Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User PerspectivesJMIR Mental Health10.2196/252499:4(e25249)Online publication date: 28-Apr-2022
https://doi.org/10.2196/25249

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents