Skip to main content

Episodic Future Thinking as Digital Micro-interventions

  • Conference paper
  • First Online:
HCI International 2023 – Late Breaking Papers (HCII 2023)

Abstract

Micro-interventions are quick focused behavioural interventions aimed at matching users’ current capacity for engagement. Mobile devices are powerful, interactive, and sensor-rich platforms for delivering micro-interventions and for determining when and where to do so. This paper presents a novel smart-phone based approach to micro-interventions based on established ‘Episodic Future Thinking (EFT)’ research. The paper both presents the background for EFT-based micro-interventions and the design of an ‘EFT’ smartphone application implementing this. The approach and technology were evaluated in a feasibility study including 14 participants using the system for 14 days. Results demonstrate the feasibility of implementing EFT as micro-interventions, with participants willing to use the application, providing positive feedback and constructive suggestions. The paper concludes with a thorough discussion of the implications for smartphone-based EFT delivered as micro-interventions and how these can be used as part of a larger behaviour change and health improvement initiatives.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Average blood glucose over 2–3 months, also known as the Hemoglobin A1 test.

  2. 2.

    http://carp.cachet.dk/.

References

  1. Alexander, B., et al.: A behavioral sensing system that promotes positive lifestyle changes and improves metabolic control among adults with type 2 diabetes. In: 2017 Systems and Information Engineering Design Symposium (SIEDS), pp. 283–288. IEEE (2017). https://doi.org/10.1109/SIEDS.2017.7937732

  2. Amlung, M., Vedelago, L., Acker, J., Balodis, I., MacKillop, J.: Steep delay discounting and addictive behavior: a meta-analysis of continuous associations. Addiction 112(1), 51–62 (2017). https://doi.org/10.1111/add.13535

    Article  Google Scholar 

  3. Aonso-Diego, G., González-Roz, A., Martínez-Loredo, V., Krotter, A., Secades-Villa, R.: Episodic future thinking for smoking cessation in individuals with substance use disorder: treatment feasibility and acceptability. J. Subst. Abuse Treat. 123, 108259 (2021). https://doi.org/10.1016/j.jsat.2020.108259

    Article  Google Scholar 

  4. Atance, C.M., O’Neill, D.K.: Episodic future thinking. Trends Cogn. Sci. 5(12), 533–539 (2001). https://doi.org/10.1016/S1364-6613(00)01804-0

    Article  Google Scholar 

  5. Athamneh, L.N., et al.: Setting a goal could help you control: comparing the effect of health goal versus general episodic future thinking on health behaviors among cigarette smokers and obese individuals. Exp. Clin. Psychopharmacol. 29(1), 59 (2021). https://doi.org/10.1037/pha0000351

    Article  Google Scholar 

  6. Balaskas, A., Schueller, S.M., Cox, A.L., Doherty, G.: Ecological momentary interventions for mental health: a scoping review. PLoS ONE 16(3), e0248152 (2021). https://doi.org/10.1371/journal.pone.0248152

    Article  Google Scholar 

  7. Bardram, J.E.: The carp mobile sensing framework-a cross-platform, reactive, programming framework and runtime environment for digital phenotyping. arXiv preprint arXiv:2006.11904 (2020). https://doi.org/10.48550/arXiv.2006.11904

  8. Baumel, A., Fleming, T., Schueller, S.M., et al.: Digital micro interventions for behavioral and mental health gains: core components and conceptualization of digital micro intervention care. J. Med. Internet Res. 22(10), e20631 (2020). https://doi.org/10.2196/20631

    Article  Google Scholar 

  9. Baumel, A., Muench, F., Edan, S., Kane, J.M., et al.: Objective user engagement with mental health apps: systematic search and panel-based usage analysis. J. Med. Internet Res. 21(9), e14567 (2019). https://doi.org/10.2196/14567

    Article  Google Scholar 

  10. Bromberg, U., Lobatcheva, M., Peters, J.: Episodic future thinking reduces temporal discounting in healthy adolescents. PLoS ONE 12(11), e0188079 (2017). https://doi.org/10.1371/journal.pone.0188079

    Article  Google Scholar 

  11. Campbell, J.A., Williams, J.S., Egede, L.E.: Examining the relationship between delay discounting, delay aversion, diabetes self-care behaviors, and diabetes outcomes in us adults with type 2 diabetes. Diabetes Care 44(4), 893–900 (2021). https://doi.org/10.2337/dc20-2620

    Article  Google Scholar 

  12. Chan, C.K., Cameron, L.D.: Promoting physical activity with goal-oriented mental imagery: a randomized controlled trial. J. Behav. Med. 35(3), 347–363 (2012). https://doi.org/10.1007/s10865-011-9360-6

    Article  Google Scholar 

  13. Conroy, D.E., Hojjatinia, S., Lagoa, C.M., Yang, C.H., Lanza, S.T., Smyth, J.M.: Personalized models of physical activity responses to text message micro-interventions: a proof-of-concept application of control systems engineering methods. Psychol. Sport Exerc. 41, 172–180 (2019). https://doi.org/10.1016/j.psychsport.2018.06.011

    Article  Google Scholar 

  14. Daniel, T.O., Stanton, C.M., Epstein, L.H.: The future is now: comparing the effect of episodic future thinking on impulsivity in lean and obese individuals. Appetite 71, 120–125 (2013). https://doi.org/10.1016/j.appet.2013.07.010

    Article  Google Scholar 

  15. Dassen, F.C., Jansen, A., Nederkoorn, C., Houben, K.: Focus on the future: episodic future thinking reduces discount rate and snacking. Appetite 96, 327–332 (2016). https://doi.org/10.1016/j.appet.2015.09.032

    Article  Google Scholar 

  16. Elefant, A.B., Contreras, O., Muñoz, R.F., Bunge, E.L., Leykin, Y.: Microinterventions produce immediate but not lasting benefits in mood and distress. Internet Interv. 10, 17–22 (2017). https://doi.org/10.1016/j.invent.2017.08.004

    Article  Google Scholar 

  17. Epstein, L.H., et al.: Effects of 6-month episodic future thinking training on delay discounting, weight loss and HbA1c changes in individuals with prediabetes. J. Behav. Med. 45(2), 227–239 (2022). https://doi.org/10.1007/s10865-021-00278-y

    Article  Google Scholar 

  18. Epstein, L.H., et al.: Role of delay discounting in predicting change in HBA1c for individuals with prediabetes. J. Behav. Med. 42(5), 851–859 (2019). https://doi.org/10.1007/s10865-019-00026-3

    Article  Google Scholar 

  19. Epstein, L.H., et al.: Delay discounting, glycemic regulation and health behaviors in adults with prediabetes. Behav. Med. 47(3), 194–204 (2021). https://doi.org/10.1080/08964289.2020.1712581

    Article  Google Scholar 

  20. Everitt, N., et al.: Exploring the features of an app-based just-in-time intervention for depression. J. Affect. Disord. 291, 279–287 (2021). https://doi.org/10.1016/j.jad.2021.05.021

    Article  Google Scholar 

  21. Eyles, H., et al.: Co-design of mHealth delivered interventions: a systematic review to assess key methods and processes. Curr. Nutr. Rep. 5(3), 160–167 (2016). https://doi.org/10.1007/s13668-016-0165-7

    Article  Google Scholar 

  22. Fleming, G.A., Petrie, J.R., Bergenstal, R.M., Holl, R.W., Peters, A.L., Heinemann, L.: Diabetes digital app technology: benefits, challenges, and recommendations. a consensus report by the European association for the study of diabetes (EASD) and the American diabetes association (ADA) diabetes technology working group. Diabetes Care 43(1), 250–260 (2020). https://doi.org/10.2337/dci19-0062

  23. Fleming, T., Bavin, L., Lucassen, M., Stasiak, K., Hopkins, S., Merry, S., et al.: Beyond the trial: systematic review of real-world uptake and engagement with digital self-help interventions for depression, low mood, or anxiety. J. Med. Internet Res. 20(6), e9275 (2018). https://doi.org/10.2196/jmir.9275

    Article  Google Scholar 

  24. Fuller-Tyszkiewicz, M., et al.: A randomized trial exploring mindfulness and gratitude exercises as ehealth-based micro-interventions for improving body satisfaction. Comput. Hum. Behav. 95, 58–65 (2019). https://doi.org/10.1016/j.chb.2019.01.028

    Article  Google Scholar 

  25. Gobin, K.C., McComb, S.E., Mills, J.S.: Testing a self-compassion micro-intervention before appearance-based social media use: implications for body image. Body Image 40, 200–206 (2022). https://doi.org/10.1016/j.bodyim.2021.12.011

    Article  Google Scholar 

  26. Golay, A., et al.: Taking small steps towards targets-perspectives for clinical practice in diabetes, cardiometabolic disorders and beyond. Int. J. Clin. Pract. 67(4), 322–332 (2013). https://doi.org/10.1111/ijcp.12114

    Article  Google Scholar 

  27. Griauzde, D., et al.: A mobile phone-based program to promote healthy behaviors among adults with prediabetes who declined participation in free diabetes prevention programs: mixed-methods pilot randomized controlled trial. JMIR Mhealth Uhealth 7(1), e11267 (2019). https://doi.org/10.2196/11267

    Article  Google Scholar 

  28. Hollis-Hansen, K., Seidman, J., O’Donnell, S., Epstein, L.H.: Episodic future thinking and grocery shopping online. Appetite 133, 1–9 (2019). https://doi.org/10.1016/j.appet.2018.10.019

    Article  Google Scholar 

  29. Howe, E., et al.: Design of digital workplace stress-reduction intervention systems: effects of intervention type and timing. In: CHI Conference on Human Factors in Computing Systems, pp. 1–16 (2022). https://doi.org/10.1145/3491102.3502027

  30. Jones, A., et al.: Integrated personalized diabetes management goes Europe: a multi-disciplinary approach to innovating type 2 diabetes care in Europe. Prim. Care Diabetes 15(2), 360–364 (2021). https://doi.org/10.1016/j.pcd.2020.10.008

    Article  Google Scholar 

  31. Karapanos, E., Zimmerman, J., Forlizzi, J., Martens, J.B.: User experience over time: an initial framework. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 729–738 (2009). https://doi.org/10.1145/1518701.1518814

  32. Kirby, K.N., Petry, N.M., Bickel, W.K.: Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls. J. Exp. Psychol. Gen. 128(1), 78 (1999). https://doi.org/10.1037/0096-3445.128.1.78

    Article  Google Scholar 

  33. Klasnja, P., Consolvo, S., Pratt, W.: How to evaluate technologies for health behavior change in HCI research. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 3063–3072 (2011). https://doi.org/10.1145/1978942.1979396

  34. Klasnja, P., et al.: Microrandomized trials: an experimental design for developing just-in-time adaptive interventions. Health Psychol. 34(S), 1220 (2015). https://doi.org/10.1037/hea0000305

  35. Lebeau, G., et al.: Delay discounting of gains and losses, glycemic control and therapeutic adherence in type 2 diabetes. Behav. Proc. 132, 42–48 (2016). https://doi.org/10.1016/j.beproc.2016.09.006

    Article  Google Scholar 

  36. Levesque, C.S., Williams, G.C., Elliot, D., Pickering, M.A., Bodenhamer, B., Finley, P.J.: Validating the theoretical structure of the treatment self-regulation questionnaire (TSRQ) across three different health behaviors. Health Educ. Res. 22(5), 691–702 (2007). https://doi.org/10.1093/her/cyl148

    Article  Google Scholar 

  37. Lewis, J.R.: Psychometric evaluation of the PSSUQ using data from five years of usability studies. Int. J. Hum.-Comput. Interact. 14(3–4), 463–488 (2002). https://doi.org/10.1080/10447318.2002.9669130

    Article  Google Scholar 

  38. Matta, A.D., Gonçalves, F.L., Bizarro, L.: Delay discounting: concepts and measures. Psychol. Neurosci. 5(2), 135–146 (2012). https://doi.org/10.3922/j.psns.2012.2.03

  39. Mazur, J.E.: An adjusting procedure for studying delayed reinforcement. Quant. Anal. Behav. 5, 55–73 (1987)

    Google Scholar 

  40. Meinlschmidt, G., et al.: Smartphone-based psychotherapeutic micro-interventions to improve mood in a real-world setting. Front. Psychol. 7, 1112 (2016). https://doi.org/10.3389/fpsyg.2016.01112

    Article  Google Scholar 

  41. Meinlschmidt, G., et al.: Personalized prediction of smartphone-based psychotherapeutic micro-intervention success using machine learning. J. Affect. Disord. 264, 430–437 (2020). https://doi.org/10.1016/j.jad.2019.11.071

    Article  Google Scholar 

  42. Meyerowitz-Katz, G., Ravi, S., Arnolda, L., Feng, X., Maberly, G., Astell-Burt, T., et al.: Rates of attrition and dropout in app-based interventions for chronic disease: systematic review and meta-analysis. J. Med. Internet Res. 22(9), e20283 (2020). https://doi.org/10.2196/20283

    Article  Google Scholar 

  43. Miller, C.K.: Adaptive intervention designs to promote behavioral change in adults: what is the evidence? Curr. Diab.Rep. 19(2), 1–9 (2019). https://doi.org/10.1007/s11892-019-1127-4

    Article  Google Scholar 

  44. Mönninghoff, A., et al.: Long-term effectiveness of mhealth physical activity interventions: systematic review and meta-analysis of randomized controlled trials. J. Med. Internet Res. 23(4), e26699 (2021). https://doi.org/10.2196/26699

    Article  Google Scholar 

  45. O’Donnell, S., Daniel, T.O., Epstein, L.H.: Does goal relevant episodic future thinking amplify the effect on delay discounting? Conscious. Cogn. 51, 10–16 (2017). https://doi.org/10.1016/j.concog.2017.02.014

    Article  Google Scholar 

  46. Odum, A.L.: Delay discounting: i’m ak, you’re ak. J. Exp. Anal. Behav. 96(3), 427–439 (2011). https://doi.org/10.1901/jeab.2011.96-423

    Article  Google Scholar 

  47. O’Neill, J., Daniel, T.O., Epstein, L.H.: Episodic future thinking reduces eating in a food court. Eat. Behav. 20, 9–13 (2016). https://doi.org/10.1016/j.eatbeh.2015.10.002

    Article  Google Scholar 

  48. Persson, D.R., Zhukouskaya, K., Wegener, A.M.K., Jørgensen, L.K., Bardram, J.E., Bækgaard, P.: Exploring patient needs and solutions in type 2 diabetes: a co-creation study. Publication in preparation (2023)

    Google Scholar 

  49. Schacter, D.L., Benoit, R.G., Szpunar, K.K.: Episodic future thinking: mechanisms and functions. Curr. Opin. Behav. Sci. 17, 41–50 (2017). https://doi.org/10.1016/j.cobeha.2017.06.002

    Article  Google Scholar 

  50. Skinner, T., Joensen, L., Parkin, T.: Twenty-five years of diabetes distress research. Diabet. Med. 37(3), 393–400 (2020). https://doi.org/10.1111/dme.14157

    Article  Google Scholar 

  51. Stein, J.S., et al.: Bleak present, bright future: II. Combined effects of episodic future thinking and scarcity on delay discounting in adults at risk for type 2 diabetes. J. Behav. Med. 44(2), 222–230 (2020). https://doi.org/10.1007/s10865-020-00178-7

    Article  Google Scholar 

  52. Stein, J.S., Sze, Y.Y., Athamneh, L., Koffarnus, M.N., Epstein, L.H., Bickel, W.K.: Think fast: rapid assessment of the effects of episodic future thinking on delay discounting in overweight/obese participants. J. Behav. Med. 40(5), 832–838 (2017). https://doi.org/10.1007/s10865-017-9857-8

    Article  Google Scholar 

  53. Stein, J.S., Tegge, A.N., Turner, J.K., Bickel, W.K.: Episodic future thinking reduces delay discounting and cigarette demand: an investigation of the good-subject effect. J. Behav. Med. 41(2), 269–276 (2017). https://doi.org/10.1007/s10865-017-9908-1

    Article  Google Scholar 

  54. Stein, J.S., Wilson, A.G., Koffarnus, M.N., Daniel, T.O., Epstein, L.H., Bickel, W.K.: Unstuck in time: episodic future thinking reduces delay discounting and cigarette smoking. Psychopharmacology 233(21), 3771–3778 (2016). https://doi.org/10.1007/s00213-016-4410-y

  55. Sze, Y.Y., Daniel, T.O., Kilanowski, C.K., Collins, R.L., Epstein, L.H.: Web-based and mobile delivery of an episodic future thinking intervention for overweight and obese families: a feasibility study. JMIR Mhealth Uhealth 3(4), e4603 (2015). https://doi.org/10.2196/mhealth.4603

    Article  Google Scholar 

  56. Sze, Y.Y., Stein, J.S., Bickel, W.K., Paluch, R.A., Epstein, L.H.: Bleak present, bright future: online episodic future thinking, scarcity, delay discounting, and food demand. Clin. Psychol. Sci. 5(4), 683–697 (2017). https://doi.org/10.1177/2167702617696511

    Article  Google Scholar 

  57. Tatara, N., Årsand, E., Bratteteig, T., Hartvigsen, G.: Usage and perceptions of a mobile self-management application for people with type 2 diabetes: qualitative study of a five-month trial (2013). https://doi.org/10.3233/978-1-61499-289-9-127

  58. Weller, R.E., Cook, E.W., III., Avsar, K.B., Cox, J.E.: Obese women show greater delay discounting than healthy-weight women. Appetite 51(3), 563–569 (2008). https://doi.org/10.1016/j.appet.2008.04.010

    Article  Google Scholar 

  59. Xu, X., et al.: Creating a smartphone app for caregivers of children with atopic dermatitis with caregivers, health care professionals, and digital health experts: participatory co-design. JMIR Mhealth Uhealth 8(10), e16898 (2020). https://doi.org/10.2196/16898

    Article  Google Scholar 

  60. Ye, J.Y., et al.: A meta-analysis of the effects of episodic future thinking on delay discounting. Q. J. Exp. Psychol. 1876–1891 (2021). https://doi.org/10.1177/17470218211066282

Download references

Acknowledgements

This research is part of the iPDM-GO project [30] that has received funding from EIT Health. EIT Health is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union that receives support from the European Union’s Horizon Europe research and innovation programme.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dan Roland Persson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Persson, D.R., Yoo, S., Bardram, J.E., Skinner, T.C., Bækgaard, P. (2023). Episodic Future Thinking as Digital Micro-interventions. In: Kurosu, M., et al. HCI International 2023 – Late Breaking Papers. HCII 2023. Lecture Notes in Computer Science, vol 14054. Springer, Cham. https://doi.org/10.1007/978-3-031-48038-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48038-6_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48037-9

  • Online ISBN: 978-3-031-48038-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics