Original Paper
- Kristell M Penfornis1, MSc ;
- Nele Albers2, PhD ;
- Willem-Paul Brinkman2, PhD ;
- Mark A Neerincx2,3, PhD ;
- Andrea WM Evers1, PhD ;
- Winifred A Gebhardt1, PhD ;
- Eline Meijer4, PhD
1Unit Health-, Medical and Neuropsychology, Institute of Psychology, Leiden University, Leiden, The Netherlands
2Department of Intelligent Systems, Delft University of Technology, Delft, The Netherlands
3Department of Perceptual and Cognitive Systems, Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, Soesterberg, The Netherlands
4Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
Corresponding Author:
Kristell M Penfornis, MSc
Unit Health-, Medical and Neuropsychology
Institute of Psychology
Leiden University
Wassenaarseweg 52
Leiden, 2333 AK
The Netherlands
Phone: 31 71 527 5081
Email: k.m.penfornis@fsw.leidenuniv.nl
Abstract
Background: Smoking and physical inactivity compromise health, especially in combination. Interventions to promote smoking cessation and increased physical activity (PA) often lack impact, especially in the long term. Digital future-self interventions (FSIs), which prompt individuals to imagine who they do and do not want to become (ie, their desired and undesired future selves), show promise in encouraging sustainable changes in both behaviors. However, knowledge of user experiences with digital FSIs is limited. A deeper understanding of these experiences could help optimize FSIs, enhancing their efficacy in supporting smoking cessation and increased PA sustainably.
Objective: This study examined behavioral, cognitive, and affective experiences with digital FSIs focused on smoking, PA, or both. Potential differences in user experiences based on behavior (smoking vs PA), polarity (desired vs undesired future self), and modality (verbal vs visual description of future selves) were explored.
Methods: Secondary analyses of quantitative and qualitative survey data from 3 studies using digital FSIs as a means to encourage smoking cessation or increase PA were conducted. In study 1, participants (N=144) thought about how it would be to complete the FSI. In studies 2 (N=447) and 3 (N=87), they completed an FSI. Each study highlighted different aspects of user experiences with FSIs, namely, behavioral (eg, time spent), cognitive (eg, mental effort exerted), or affective (eg, emotions) experiences. Quantitative and qualitative findings were integrated for a comprehensive interpretation.
Results: Regarding behavioral experiences, participants completed future-self tasks promptly (mean 6.64, SD 8.30 minutes), spent less time completing the desired- versus undesired-future-self (P<.001; ηp2=0.227) and verbal versus visual (P=.03; ηp2=0.060; quantitative) tasks, and integrated the tasks into their lives (qualitative). Despite tasks being preparatory and not actively encouraging behavior change, multiple participants reported implementing changes in their smoking or PA (qualitative). Regarding cognitive experiences, moderate effort (mean 5.85/10, SD 2.56) was exerted on the tasks regardless of behavior (P=.69; ηp2=0.002), modality (P=.45; ηp2=0.004), or polarity (P=.69; ηp2=0.002; quantitative). Experiences of task difficulty were inconsistent across studies, individuals, and tasks, although mental visualization and describing one’s future self using images were consistently reported as challenging (quantitative and qualitative). Future-self tasks were reported to prompt cognitive processes such as contemplating consequences of smoking and PA behavior (qualitative). Regarding affective experiences, desired- and undesired-future-self tasks elicited different emotions (P<.001; ηp2=0.630; quantitative). Desired-future-self tasks were perceived as enjoyable and happiness inducing, whereas undesired-future-self tasks were perceived as confronting and unpleasant, evoking feelings of sadness, fear, and anger (quantitative and qualitative).
Conclusions: Digital FSIs appeared to be a time-efficient, feasible, and acceptable way of strengthening identities as a means to encourage smoking cessation and PA. Findings support continued implementation of digital FSIs, although further research is required to optimize their operationalization. Avenues in that regard are proposed and discussed.
doi:10.2196/63893
Keywords
Introduction
Background
Smoking is the leading behavioral risk factor for disease and premature death worldwide, and physical inactivity is the tenth [Global burden of disease (GBD). Institute for Health Metrics and Evaluation. URL: https://www.healthdata.org/research-analysis/gbd [accessed 2024-02-09] 1]. Annually, tobacco is responsible for approximately 8 million deaths worldwide, and physical inactivity is responsible for approximately 1 million [Child mortality rate, 2022. Our World in Data. URL: https://ourworldindata.org/explorers/global-health [accessed 2025-04-23] 2,Ritchie H, Roser M. Smoking. Our World in Data. URL: https://ourworldindata.org/smoking [accessed 2024-02-09] 3]. Combined, smoking and physical inactivity more than double the likelihood of premature death [Yang Y, Xu H, Liu X, Li J, Liew Z, Liu X, et al. Joint association of smoking and physical activity with mortality in elderly hypertensive patients: a Chinese population-based cohort study in 2007-2018. Front Public Health. Sep 29, 2022;10:1005260. [FREE Full text] [CrossRef] [Medline]4] and decrease disease-free life years by 6 years [Stenholm S, Head J, Kivimäki M, Kawachi I, Aalto V, Zins M, et al. Smoking, physical inactivity and obesity as predictors of healthy and disease-free life expectancy between ages 50 and 75: a multicohort study. Int J Epidemiol. Aug 2016;45(4):1260-1270. [FREE Full text] [CrossRef] [Medline]5]. Consequently, interventions targeting both smoking cessation and physical activity (PA) have great potential to reduce worldwide mortality and morbidity, with multi-behavior interventions potentially enhancing effectiveness through synergistic effects [Duan Y, Shang B, Liang W, Du G, Yang M, Rhodes RE. Effects of eHealth-based multiple health behavior change interventions on physical activity, healthy diet, and weight in people with noncommunicable diseases: systematic review and meta-analysis. J Med Internet Res. Feb 22, 2021;23(2):e23786. [FREE Full text] [CrossRef] [Medline]6,Prochaska JJ, Prochaska JO. A review of multiple health behavior change interventions for primary prevention. Am J Lifestyle Med. May 2011;5(3):208-221. [FREE Full text] [CrossRef] [Medline]7]. Digital platforms such as eHealth and mobile health further enable scalable, accessible support [Marcolino MS, Oliveira JA, D'Agostino M, Ribeiro AL, Alkmim MB, Novillo-Ortiz D. The impact of mHealth interventions: systematic review of systematic reviews. JMIR Mhealth Uhealth. Jan 17, 2018;6(1):e23. [FREE Full text] [CrossRef] [Medline]8,Fang YE, Zhang Z, Wang R, Yang B, Chen C, Nisa C, et al. Effectiveness of eHealth smoking cessation interventions: systematic review and meta-analysis. J Med Internet Res. Jul 28, 2023;25:e45111. [FREE Full text] [CrossRef] [Medline]9].
Quitting smoking and increasing PA immediately mitigate health risks even among older individuals and those with long-standing histories of smoking or sedentary behavior [Smoking cessation: a report of the surgeon general. U.S. Department of Health and Human Services. 2020. URL: https://www.hhs.gov/sites/default/files/2020-cessation-sgr-full-report.pdf [accessed 2024-09-02] 10,Europe physical activity factsheet 2021. European Commission. URL: https://sport.ec.europa.eu/document/europe-physical-activity-factsheet-2021 [accessed 2025-05-15] 11]. However, quitting smoking and increasing PA are often challenging. To illustrate, long-term smoking abstinence may require 20 to 30 attempts [Chaiton M, Diemert L, Cohen JE, Bondy SJ, Selby P, Philipneri A, et al. Estimating the number of quit attempts it takes to quit smoking successfully in a longitudinal cohort of smokers. BMJ Open. Jun 09, 2016;6(6):e011045. [FREE Full text] [CrossRef] [Medline]12]. While numerous smoking cessation and PA promotion interventions exist, their effects tend to be small to moderate and are rarely sustained beyond a year [Hartmann-Boyce J, Livingstone-Banks J, Ordóñez-Mena JM, Fanshawe TR, Lindson N, Freeman SC, et al. Behavioural interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. Jan 04, 2021;1(1):CD013229. [CrossRef] [Medline]13-Murray JM, Brennan SF, French DP, Patterson CC, Kee F, Hunter RF. Effectiveness of physical activity interventions in achieving behaviour change maintenance in young and middle aged adults: a systematic review and meta-analysis. Soc Sci Med. Nov 2017;192:125-133. [CrossRef] [Medline]15]. This leaves individuals vulnerable to relapses and renewed risks of negative health outcomes.
Identity-focused health behavior change interventions, which aim to connect healthy behavior to central components of who one is (ie, one’s self-identity), present a promising avenue to enhance the effectiveness of smoking cessation and PA promotion programs. Such interventions are rooted in identity theories that propose that, as people prefer to act in line with their self-identity [Burke PJ, Stets JE. Identity Theory. Oxford, UK. Oxford University Press; 2009. 16,Oyserman D. Identity‐based motivation: implications for action‐readiness, procedural‐readiness, and consumer behavior. J Consum Psychol. Jun 25, 2009;19(3):250-260. [CrossRef]17], one is more likely to abstain from smoking or engage in regular PA when such healthy behavior is integrated into one’s self-identity. Empirical research supports this—individuals identifying with smoking show weaker intentions to quit [Meijer E, Van den Putte B, Gebhardt WA, Van Laar C, Bakk Z, Dijkstra A, et al. A longitudinal study into the reciprocal effects of identities and smoking behaviour: findings from the ITC Netherlands Survey. Soc Sci Med. Mar 2018;200:249-257. [FREE Full text] [CrossRef] [Medline]18,Smit ES, Hoving C, Schelleman-Offermans K, West R, de Vries H. Predictors of successful and unsuccessful quit attempts among smokers motivated to quit. Addict Behav. Sep 2014;39(9):1318-1324. [FREE Full text] [CrossRef] [Medline]19] and are less likely to attempt cessation [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20-van den Putte B, Yzer M, Willemsen MC, de Bruijn GJ. The effects of smoking self-identity and quitting self-identity on attempts to quit smoking. Health Psychol. Sep 2009;28(5):535-544. [CrossRef] [Medline]22], whereas those identifying as quitters or nonsmokers are more likely to attempt [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20,van den Putte B, Yzer M, Willemsen MC, de Bruijn GJ. The effects of smoking self-identity and quitting self-identity on attempts to quit smoking. Health Psychol. Sep 2009;28(5):535-544. [CrossRef] [Medline]22] and achieve cessation [Meijer E, Van den Putte B, Gebhardt WA, Van Laar C, Bakk Z, Dijkstra A, et al. A longitudinal study into the reciprocal effects of identities and smoking behaviour: findings from the ITC Netherlands Survey. Soc Sci Med. Mar 2018;200:249-257. [FREE Full text] [CrossRef] [Medline]18]. Similarly, identifying with PA is linked to more intensive and frequent PA [de Bruijn GJ, van den Putte B. Exercise promotion: an integration of exercise self‐identity, beliefs, intention, and behaviour. Eur J Sport Sci. Feb 29, 2012;12(4):354-366. [CrossRef]23-Strachan SM, Perras MG, Forneris T, Stadig GS. I'm an exerciser: common conceptualisations of and variation in exercise identity meanings. Int J Sport Exerc Psychol. Oct 19, 2015;15(3):321-336. [CrossRef]26].
Among identity-focused interventions, future-self interventions (FSIs) appear particularly promising. FSIs are rooted in possible self–related theories, one branch of identity theory, which posit that possible future identities and not only current identity influence current behavior [Markus H, Nurius P. Possible selves. Am Psychol. 1986;41(9):954-969. [CrossRef]27,Oyserman D, Bybee D, Terry K, Hart-Johnson T. Possible selves as roadmaps. J Res Pers. Apr 2004;38(2):130-149. [CrossRef]28]. A clear vision of one’s desired or undesired future self can motivate self-regulatory processes to become the desired future self [Oyserman D, Bybee D, Terry K, Hart-Johnson T. Possible selves as roadmaps. J Res Pers. Apr 2004;38(2):130-149. [CrossRef]28,Oettingen G. Future thought and behaviour change. Eur Rev Soc Psychol. Mar 13, 2012;23(1):1-63. [CrossRef]29]. This is why FSIs generally prompt people to imagine who they want to become (ie, desired future self) or who they want to avoid becoming (ie, undesired future self). Research recommends envisioning both desired and undesired future selves for greater effect on identity and, subsequently, behavior [Oettingen G. Future thought and behaviour change. Eur Rev Soc Psychol. Mar 13, 2012;23(1):1-63. [CrossRef]29,Oyserman D, Destin M, Novin S. The context-sensitive future self: possible selves motivate in context, not otherwise. Self Identity. Oct 08, 2014;14(2):173-188. [CrossRef]30]. Common tasks include writing about the envisioned future selves (ie, verbal future-self tasks), and searching for images that describe them (ie, visual future-self tasks) is also common [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20,Rutchick AM, Slepian ML, Reyes MO, Pleskus LN, Hershfield HE. Future self-continuity is associated with improved health and increases exercise behavior. J Exp Psychol Appl. Mar 2018;24(1):72-80. [CrossRef] [Medline]31]. Such tasks help create a more vivid image of the future self, ultimately increasing the likelihood of behaving in ways confirming or disconfirming that possible future identity [Rutchick AM, Slepian ML, Reyes MO, Pleskus LN, Hershfield HE. Future self-continuity is associated with improved health and increases exercise behavior. J Exp Psychol Appl. Mar 2018;24(1):72-80. [CrossRef] [Medline]31]. FSIs are increasingly being delivered digitally [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20,Meijer E, Gebhardt WA, van Laar C, van den Putte B, Evers AW. Strengthening quitter self-identity: an experimental study. Psychol Health. Oct 2018;33(10):1229-1250. [FREE Full text] [CrossRef] [Medline]32].
Despite a solid theoretical foundation, experimental studies using FSIs in the context of smoking and PA have shown mixed results. While FSIs have repeatedly promoted PA [Rutchick AM, Slepian ML, Reyes MO, Pleskus LN, Hershfield HE. Future self-continuity is associated with improved health and increases exercise behavior. J Exp Psychol Appl. Mar 2018;24(1):72-80. [CrossRef] [Medline]31,Chan CK, Cameron LD. Promoting physical activity with goal-oriented mental imagery: a randomized controlled trial. J Behav Med. Jun 2012;35(3):347-363. [CrossRef] [Medline]33-Ouellette JA, Hessling R, Gibbons FX, Reis-Bergan M, Gerrard M. Using images to increase exercise behavior: prototypes versus possible selves. Pers Soc Psychol Bull. May 2005;31(5):610-620. [CrossRef] [Medline]35] and impacted smoking cessation–related outcomes (eg, lower craving intensity, greater quit intention, and smoking reduction and abstinence [Shadel WG, Cervone D. Evaluating social-cognitive mechanisms that regulate self-efficacy in response to provocative smoking cues: an experimental investigation. Psychol Addict Behav. Mar 2006;20(1):91-96. [CrossRef] [Medline]36-Wynd C. Guided health imagery for smoking cessation and long-term abstinence. J Nurs Scholarsh. 2005;37(3):245-250. [FREE Full text] [CrossRef] [Medline]38]), some studies have found no effect on smoking [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20,Meijer E, Gebhardt WA, van Laar C, van den Putte B, Evers AW. Strengthening quitter self-identity: an experimental study. Psychol Health. Oct 2018;33(10):1229-1250. [FREE Full text] [CrossRef] [Medline]32] or PA [Meslot C, Gauchet A, Allenet B, François O, Hagger MS. Theory-based interventions combining mental simulation and planning techniques to improve physical activity: null results from two randomized controlled trials. Front Psychol. Nov 16, 2016;7:1789. [FREE Full text] [CrossRef] [Medline]39]. The effectiveness of digital health behavior change interventions appears to hinge on user engagement [Yardley L, Spring BJ, Riper H, Morrison LG, Crane DH, Curtis K, et al. Understanding and promoting effective engagement with digital behavior change interventions. Am J Prev Med. Nov 2016;51(5):833-842. [CrossRef] [Medline]40]. Understanding user experiences is essential to determine the ideal type and level of engagement [Scarpa MP, Prilletensky I, McMahon A, Myers ND, Prilleltensky O, Lee S, et al. Is fun for wellness engaging? Evaluation of user experience of an online intervention to promote well-being and physical activity. Front Comput Sci. Jun 18, 2021;3. [CrossRef]41]. However, beyond one study reporting FSIs as useful to reduce smoking [Tindle HA, Barbeau EM, Davis RB, Eisenberg DM, Park ER, Phillips RS, et al. Guided imagery for smoking cessation in adults: a randomized pilot trial. Complement Health Pract Rev. Jan 2006;11(3):166-175. [CrossRef]37] and 2 reporting that future-self imagery can influence affect [Boyatzis RE, Akrivou K. The ideal self as the driver of intentional change. J Manag Dev. Aug 1, 2006;25(7):624-642. [CrossRef]42,Schubert T, Eloo R, Scharfen J, Morina N. How imagining personal future scenarios influences affect: systematic review and meta-analysis. Clin Psychol Rev. Feb 2020;75:101811. [CrossRef] [Medline]43], little is known about user experiences with FSIs. Therefore, understanding user experiences is crucial for optimizing FSIs to facilitate smoking cessation and PA promotion.
Objectives
Examination of user experiences is most complete when considering behavioral (eg, use and time spent), cognitive (eg, [mental] effort, interest, and attention), and affective (eg, emotional response) experiences [Kelders SM, van Zyl LE, Ludden GD. The concept and components of engagement in different domains applied to eHealth: a systematic scoping review. Front Psychol. May 27, 2020;11:926. [FREE Full text] [CrossRef] [Medline]44-Short CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring engagement in eHealth and mHealth behavior change interventions: viewpoint of methodologies. J Med Internet Res. Nov 16, 2018;20(11):e292. [FREE Full text] [CrossRef] [Medline]47]. Relying on a single study risks offering a narrow or skewed viewpoint influenced by the specific FSI examined. Therefore, this multistudy paper triangulates behavioral, cognitive, and affective user experiences across several digital FSIs aimed at facilitating smoking cessation or PA promotion to offer a more comprehensive overview.
The 3 digital FSIs in this study asked people to envision smoking- or PA-related desired and undesired future selves and complete verbal and/or visual tasks about these self-views. Given that smoking is a health-compromising behavior that is preferably quit and PA is a health-promoting behavior that is preferably increased, user experiences with FSIs may differ by behavior. Therefore, we explored potential differences in user experiences by behavior (smoking vs PA). As examining desired and undesired future selves jointly may mask varying experiences with one versus the other, we also explored differences in user experiences by task polarity (desired- vs undesired-future-self task). Third, because individuals may experience verbal and visual tasks differently, we explored whether user experiences vary by modality (visual vs verbal future-self task). Finally, to gain full insight into user experiences with FSIs, we explored interactions among behavior, polarity, and/or modality and also explored free-text responses.
Methods
Overview
This multistudy report is an observational, exploratory analysis of secondary quantitative and qualitative survey data from 3 empirical studies that used distinct digital FSIs. Combining quantitative and qualitative methods from multiple studies enabled data triangulation across contexts while providing deeper, more nuanced insights into individuals’ experiences [Short CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring engagement in eHealth and mHealth behavior change interventions: viewpoint of methodologies. J Med Internet Res. Nov 16, 2018;20(11):e292. [FREE Full text] [CrossRef] [Medline]47-Lynn M. More multi-study articles wanted. Cornell Hosp Q. Jun 23, 2017;58(3):228. [CrossRef]49]. The multistudy approach enhanced comprehensive understanding of experiences with FSIs and reduced the likelihood of chance effects. This study followed the Mixed Methods Article Reporting Standards. The 3 studies are, from this point on, referred to as study 1, study 2, and study 3. Personal characteristics of the participants included in the 3 studies are presented in Table 1.
The characteristics of the 3 original studies and outcomes used in this multistudy report to explore user experiences are presented in Table 2. Each study provides complementary insights into user experiences compared to the previous ones. Study 1 primarily explored cognitive experiences with a smoking- and PA-related desired- and undesired-FSI. Study 2 primarily explored cognitive and behavioral experiences with a smoking- and PA-related desired- and undesired-FSI and provided some insights into affective experiences as well. Study 3 explored behavioral, cognitive, and affective experiences with a smoking-related desired- and undesired-FSI. Collectively, the 3 studies offer a comprehensive understanding of experiences with FSIs.
Characteristic | Study 1 (N=144) | Study 2 (N=447) | Study 3 (N=87) | ||||
Age (y), mean (SD; range) | 37.55 (11.76; 20-69) | 36.25 (11.44; 19-71) | 37.84 (19.22; 18-82) | ||||
Gendera, n (%) | |||||||
Men | 72 (50) | 211 (47.2) | 27 (31) | ||||
Women | 72 (50) | 222 (49.7) | 60 (69) | ||||
Nonbinary or other | 0 (0) | 14 (3.1) | 0 (0) | ||||
Socioeconomic positionb, n (%) | |||||||
Do not know | —c | 3 (0.7) | — | ||||
Lower | 1 (0.7) | 2 (0.4) | 13 (14.9) | ||||
Middle | 32 (22.2) | 126 (28.2) | 45 (51.7) | ||||
Higher | 111 (77.1) | 316 (70.7) | 29 (33.3) | ||||
Cigarette or e-cigarette consumptiond, n (%) | |||||||
Once per day | 5 (3.5) | 25 (5.6) | 1 (1.1) | ||||
2-5 times per day | 97 (67.4) | 73 (16.3) | 28 (32.2) | ||||
6-10 times per day | 48 (33.3) | 93 (20.8) | 21 (24.1) | ||||
11-19 times per day | 45 (31.3) | 104 (23.3) | 13 (14.9) | ||||
≥20 times per day | 25 (17.4) | 152 (34) | 24 (27.6) | ||||
Weekly exercisee, n (%) | |||||||
Never to little | 30 (20.8) | 124 (27.7) | — | ||||
Sometimes | 80 (55.6) | 193 (43.2) | — | ||||
Often | 34 (23.6) | 129 (28.9) | — |
aFor studies 1 and 2, the “men” and “women” categories include transgender individuals.
bLower: no formal education, primary education, and high school or equivalent; middle: tertiary education; higher: technical or community college or undergraduate, graduate, or doctoral degree as per the International Standard Classification of Education [International standard classification of education (ISCED). International Labor Organization. URL: https://ilostat.ilo.org/methods/concepts-and-definitions/classification-education/ [accessed 2024-02-20] 50].
cThis answer option was not provided in the study.
dFor study 2, the numbers reflect smoking and vaping together.
eNever to little: 0 to 60 minutes per week; sometimes: 60 to 150 minutes per week; often: >150 minutes per week.
Study 1: cognitive experiences with a future-self intervention | Study 2: behavioral and cognitive experiences with a future-self intervention | Study 3: behavioral, cognitive, and affective experiences with a future-self intervention | ||
Design, measurements, and future-self intervention | ||||
Study design |
|
|
| |
Data collection mode |
|
|
| |
Type of data |
|
|
| |
Measurement number and moments |
|
|
| |
Survey language |
|
|
| |
Studied health behaviors |
|
|
| |
Future-self intervention |
|
|
| |
Outcomes reflecting behavioral, cognitive, and affective user experiences | ||||
Behavioral experiences | —b |
|
| |
Cognitive experiences |
|
|
| |
Affective experiences | — |
|
|
aPA: physical activity.
bNot applicable.
cThe “do” part of the question was expected to probe participants to share their behavioral experiences with the future-self tasks, the “approach” part of the question was expected to probe participants to share their behavioral and cognitive experiences, and the “experience” part of the question was expected to probe participants to share their affective experiences.
dThis question was expected to probe participants to share their behavioral, cognitive, and affective experiences with the future-self tasks. Deductive coding during data analysis allowed for the determination of which answer informed which experiential dimension.
Data Analysis
For studies 1, 2, and 3, quantitative analyses were conducted in SPSS Statistics for Windows (version 29; IBM Corp), with statistical significance set at P<.05 (2-tailed). Bonferroni corrections were applied for multiple testing [Tabachnick BG, Fidell LS. Using Multivariate Statistics. London, UK. Pearson; 2018. 51]. Effect sizes were interpreted according to the Cohen d (small≥0.2, medium≥0.5, and large≥0.8) for t tests and the Cohen f (small≥0.1, medium≥0.25, and large≥0.4) for ANOVAs [Cohen J. Statistical Power Analysis for the Behavioral Sciences Second Edition. Milton Park, UK. Routledge; 1988. 52]. The syntaxes are publicly available [Penfornis KM, Albers N. User experiences with digital future-self interventions in the contexts of smoking and physical activity: a mixed methods multi-study exploration - data and analysis code. 4TU.ResearchData. 2025. URL: https://data.4tu.nl/datasets/951b2dc4-a59e-48ed-9856-af484b125393 [accessed 2025-04-23] 53].
Qualitative survey data were analyzed in Microsoft Excel using qualitative content analysis principles [White MD, Marsh EE. Content analysis: a flexible methodology. Libr Trends. 2006;55(1):22-45. [CrossRef]54]. Two researchers (KMP and a trained psychology master student) independently familiarized themselves with the responses, developed initial inductive codes, compared these, and created a coding tree. Participant responses were then coded jointly, and the coding trees were refined as needed. One researcher (KMP) subsequently created a matrix indexing all codes and counted their frequency for a weighted data representation. Finally, the findings were categorized into behavioral, cognitive, or affective experiences with future-self tasks. Specifications are detailed in the respective Data Analysis sections. Reported coding frequencies indicate how often the code appeared, not the number of participants to whom it applied.
Study 1: Cognitive Experiences With a PA- and Smoking-Related FSI
In study 1, quantitative and qualitative survey data from the original online cross-sectional observational study [Albers N. Psychology-informed reinforcement learning for situated virtual coaching in smoking cessation. Delft University of Technology. 2025. URL: https://doi.org/10.4233/uuid:5e1d1500-1c45-4869-b995-6ed7db8f8b3b [accessed 2025-04-22] 55] were used to explore cognitive experiences with a smoking- and PA-related FSI. Additional information regarding the original study can be found in the preregistration on the Open Science Framework [Albers N, Brinkman WP. Perfect Fit - beliefs about and competencies built by preparatory activities for quitting smoking and becoming more physically active. OSF Registries. 2022. URL: https://osf.io/cax6f [accessed 2024-01-16] 56], and the data related to this study are openly accessible elsewhere [Albers N, Neerincx MA, Brinkman WP. Difficulty and time perceptions of preparatory activities for quitting smoking: Dataset. 4TU.ResearchData. Nov 6, 2023. URL: https://data.4tu.nl/datasets/5198f299-9c7a-40f8-8206-c18df93ee2a0/1 [accessed 2025-04-23] 57].
Methods
Participants
A total of 144 participants were recruited via the online recruitment platform Prolific [Prolific homepage. Prolific. URL: https://www.prolific.com [accessed 2024-10-23]
58] between September 2022 and November 2022. Participants were from countries that belonged to the Organisation for Economic Co-operation and Development, excluding Turkey, Lithuania, Colombia, and Costa Rica but including South Africa [Researcher help center. Prolific. URL: https://researcher-help.prolific.com/hc/en-gb/articles/360009220833-Who-are-the-participants-on-Prolific [accessed 2024-01-16]
59]. Inclusion criteria required being aged 18 years, fluency in English, daily smoking, and an intention to quit within 30 days to 6 months. The original study was primarily focused on smoking cessation, which is why an inclusion criterion was formulated regarding smoking but not PA. Those familiar with similar tasks from a previous study [Albers N, Neerincx MA, Penfornis KM, Brinkman WP. Users' needs for a digital smoking cessation application and how to address them: a mixed-methods study. PeerJ. Aug 19, 2022;10:e13824. [FREE Full text] [CrossRef] [Medline]60] were excluded. Table 1 provides the participant characteristics.
Procedure
In total, 2 online surveys were administered using Qualtrics XM (Qualtrics International Inc) [Qualtrics XM homepage. Qualtrics. URL: https://www.qualtrics.com/nl/ [accessed 2024-10-23]
61]. Interested Prolific members provided digital informed consent and completed a screening survey. Upon meeting the inclusion criteria, participants proceeded to the study survey, which included instructions for 44 different tasks that either aimed to aid smoking cessation or PA enhancement or could be beneficial to either behavior. This multistudy report focuses only on the 8 tasks targeted at one’s smoking- or PA-related future self, involving writing about or searching images describing the desired or undesired future self. Detailed instructions are provided in Instructions for the future-self interventions used in studies 1, 2, and 3.Multimedia Appendix 1
Ethical Considerations
Ethics approval for this study was granted by the Human Research Ethics Committee of Delft University of Technology (letter of approval 2338). Digital consent from participants in the original study enabled secondary analyses without additional approval. Participant data were deidentified for analysis to ensure confidentiality and privacy. Participants were compensated with £6.00 (US $7.69) per hour following Prolific regulations [What is your pricing? Prolific. URL: https://researcher-help.prolific.com/hc/en-gb/articles/360009223533-What-is-your-pricing [accessed 2024-01-17] 62].
Measures
Personal Characteristics
These were collected from Prolific participant profiles and the screening survey and used to describe the participants. Variables included age (derived from year of birth), gender (male, including transgender male; female, including transgender female; or other), and highest completed educational level. The latter was used as an indicator of socioeconomic position [Schaap MM, Kunst AE. Monitoring of socio-economic inequalities in smoking: learning from the experiences of recent scientific studies. Public Health. Feb 2009;123(2):103-109. [CrossRef] [Medline]63] and recoded according to the International Standard Classification of Education [International standard classification of education (ISCED). International Labor Organization. URL: https://ilostat.ilo.org/methods/concepts-and-definitions/classification-education/ [accessed 2024-02-20] 50]. Smoking frequency was assessed using the following question: “How often do you smoke tobacco products?” Participants indicating not smoking daily were informed that they could not continue taking part in the study. One question ascertained participants’ weekly exercise (ie, “How often do you engage in physical exercise per week?”).
Cognitive Experiences
In total, 3 items from the study survey were used to explore cognitive experiences with the FSI. Participants rated the anticipateddifficulty of the 8 future-self tasks on a scale in which −5=very difficult, 0=neutral, and 5=very easy. Second, they provided an estimatedcompletion time ranging from 0 to 30 minutes, indicating exact minutes if the anticipated time exceeded 30 minutes. Third, an open question, “Think of the preparatory activities you have just seen. What makes an activity more difficult than others?” was expected to probe participants to share their cognitive experiences with future-self tasks.
Data Analysis
After computing descriptive statistics, a 1-sample t test examined whether anticipated difficulty scores differed from the neutral 0 point. One- and 3-way repeated-measure (RM) ANOVAs explored differences in anticipated difficulty and anticipated completion time based on behavior (smoking vs PA), polarity (desired vs undesired future self), and modality (verbal vs visual description) of the future-self tasks. Assumptions were verified ( Results of assumption testing and robustness analyses.Multimedia Appendix 2
Qualitative responses ranged from 1 word to 3 sentences. All participant responses (N=144) were coded. The full coding tree can be found in Coding trees for qualitative analyses.Multimedia Appendix 3
Results
Quantitative Results
Overview
The main findings of study 1 are summarized in Table 3.
Study 1 | Study 2 | Study 3 | ||
Behavioral experiences | ||||
Quantitative findings | —a | — |
| |
Qualitative findings | — |
| — | |
Cognitive experiences | ||||
Quantitative findings |
|
|
| |
Qualitative findings |
|
|
| |
Affective experiences | ||||
Quantitative findings | — | — |
| |
Qualitative findings | — |
|
|
aNot applicable for this study.
Anticipated Difficulty of Future-Self Tasks
Figure 1 shows mean anticipated ease by behavior, modality, and polarity. A 1-sample t test showed that anticipated difficulty scores significantly differed from the neutral 0 point, meaning that future-self tasks were anticipated to be relatively easy to complete (mean 1.19, SD 1.75; t143=8.20; P<.001; Cohen d=0.68). RM ANOVAs assessed differences in anticipated difficulty based on behavior, polarity, and modality. There was a significant 3-way interaction among behavior, polarity, and modality on anticipated difficulty of the future-self tasks (F1,143=4.26; P=.04; ηp2=0.029). Follow-up ANOVAs revealed no significant 2-way interactions or main effects of behavior and modality (lowest P>.01). However, they revealed significant main effects of polarity. Specifically, desired-future-self tasks were anticipated to be easier than undesired-future-self tasks for both smoking (F1,143=24.16; P<.001; ηp2=0.145) and PA (F1,143=33.90; P<.001; ηp2=0.192) and when asked to describe the future self verbally (F1,143=23.93; P<.001; ηp2=0.143) and visually (F1,143=30.85; P<.001; ηp2=0.177).

Anticipated Completion Time for Future-Self Tasks
Figure 1 shows mean anticipated completion time by behavior, modality, and polarity. Participants estimated that it would take, on average, 13.28 (SD 5.79) minutes to complete future-self tasks. RM ANOVAs assessed differences in anticipated completion time based on behavior, polarity, and modality. There was no statistically significant 3-way (F1,130=3.54; P=.06; ηp2=0.027) or 2-way interaction for anticipated completion time (P>.05 in all cases), but there were significant main effects of behavior (F1,130=11.30; P=.001; ηp2=0.080) and modality (F1,130=78.66; P<.001; ηp2=0.377). Specifically, the smoking-related future-self task was anticipated to take more time to complete than the PA-related one (∆=0.91, 95% CI 0.38-1.45). In addition, verbal description of future selves was anticipated to take more time than visual description (∆=4.17, 95% CI 3.24-5.11).
Qualitative Results
Cognitive Experiences With Future-Self Tasks
Qualitative analysis indicated that tasks were anticipated to be more difficult if they involved mental visualization (25/144, 17.4%), cognitive effort (24/144, 16.7%), more time (19/144, 13.2%), physical effort (14/144, 9.7%), or multiple components (eg, both visualizing and writing about one’s future self; 4/144, 2.8%). Six reasons emerged for why visualization tasks were anticipated to be difficult: (1) unfamiliarity with mental visualization (3/144, 2.1%; “Visualization is a concept that is foreign to some people. A course is needed” [female participant; aged 64 years]), (2) motivation to perform the tasks or change behavior (3/144, 2.1%), (3) willingness to be honest about (the consequences of) current behavior (3/144, 2.1%), (4) perceived attainability of the future self (2/144, 2.1%), (5) expectation of a negative emotional response (2/144, 2.1%), and (6) the challenge of visualizing compared to taking concrete actions to change the behavior (2/144, 2.1%). In total, 0.7% (1/144) of the participants anticipated envisioning a positive future to be easier, whereas 2.1% (3/144) anticipated the undesired-future-self task to be easier:
For me, thinking about...positives would be difficult, as I don’t often praise myself or congratulate myself or anything like that.
[Female participant; aged 50 years]
Discussion
Regarding cognitive experiences, quantitative results from study 1 showed that future-self tasks were anticipated to be completed relatively easily and in less than 14 minutes, suggesting FSIs can be anticipated to be time efficient and feasible. Desired-future-self tasks were perceived as easier than undesired-future-self tasks. Furthermore, smoking-related future-self tasks and verbal descriptions of future selves were estimated to take more time than PA-related tasks and visual descriptions. These results imply differences in experiences between specific future-self tasks.
Qualitative results indicated that tasks requiring mental visualization, cognitive or physical effort, or more time or tasks having multiple components (eg, visualizing and writing) were anticipated to be difficult. Visualization tasks were seen as challenging due to factors such as unfamiliarity, motivation, and anticipated negative emotional responses. Views varied on whether desired- or undesired-future-self tasks were more challenging in these respects. These findings suggest that, while FSIs are generally considered fairly easy, the mental visualization aspect is viewed as challenging.
Study 2: Behavioral and Cognitive Experiences With PA- or Smoking-Related FSIs
In study 2, quantitative and qualitative survey data from the original online longitudinal observational study [Albers N. Psychology-informed reinforcement learning for situated virtual coaching in smoking cessation. Delft University of Technology. 2025. URL: https://doi.org/10.4233/uuid:5e1d1500-1c45-4869-b995-6ed7db8f8b3b [accessed 2025-04-22] 55] were used to explore behavioral; cognitive; and, where possible, affective experiences with a smoking- or PA-related FSI. Additional information regarding the original study can be found in the preregistration on the Open Science Framework [Perfect Fit - learning when to involve a human coach in an eHealth application for preparing for quitting smoking or vaping. OSF Registries. URL: https://osf.io/78cnr [accessed 2025-05-30] 64], and the data underlying this study have been published elsewhere [Penfornis KM, Albers N. User experiences with digital future-self interventions in the contexts of smoking and physical activity: a mixed methods multi-study exploration - data and analysis code. 4TU.ResearchData. 2025. URL: https://data.4tu.nl/datasets/951b2dc4-a59e-48ed-9856-af484b125393 [accessed 2025-04-23] 53].
Methods
Participants
Participants were 52.5% (447/852) of the included individuals, who completed future-self tasks in the original study between February 2024 and March 2024. Inclusion criteria were being aged 18 years, fluency in English, daily smoking or vaping, intention to quit within 30 days to 6 months, not taking part in a smoking or vaping cessation intervention, and not being familiar with similar tasks from previous studies [Perfect Fit - experiment to gather data for and test a reinforcement learning-approach for motivating people. OSF Registries. URL: https://osf.io/k2uac [accessed 2025-05-30]
65,Albers N, Brinkman WP. Perfect Fit - learning to propose useful preparatory activities for quitting smoking and becoming more physically active. OSF Registries. Jul 21, 2023. URL: https://osf.io/nuy4w [accessed 2025-04-09]
66]. Participants failing attention checks integrated into the survey or not completing tasks within 2 days of having received the invitation were excluded. Dropouts were replaced until the budget of approximately €5000 (US $5475.65) was spent. The personal characteristics of study 2 participants are presented in Table 1.
Procedure
Prolific members who provided digital informed consent and met the inclusion criteria completed a baseline survey via Qualtrics XM, including questions about demographic characteristics. The intervention consisted of up to 5 conversational sessions of 6 to 8 minutes spaced 3 to 5 days apart with coach Kai, a text-based chatbot [Albers N. PerfectFit-project/virtual_coach_human_inv: virtual coach kai for preparing for quitting smoking with human support. Zenodo. May 2, 2024. URL: https://zenodo.org/records/11102861 [accessed 2025-04-22]
67]. During these conversation sessions, participants received instructions for 1 task randomly selected from 37 tasks meant to aid smoking cessation and PA enhancement, of which 8 (22%) were future-self tasks. The tasks were a subset of those in study 1, with more detailed instructions based on the work by Albers et al [Albers N, Neerincx MA, Penfornis KM, Brinkman WP. Users' needs for a digital smoking cessation application and how to address them: a mixed-methods study. PeerJ. Aug 19, 2022;10:e13824. [FREE Full text] [CrossRef] [Medline]60] ( Instructions for the future-self interventions used in studies 1, 2, and 3.Multimedia Appendix 1
Ethical Considerations
Ethics approval was granted by the Human Research Ethics Committee of Delft University of Technology (letter of approval 3683). Digital consent from participants in the original study enabled secondary analyses without additional approval. Participant data were deidentified for analysis to ensure confidentiality and privacy. Participants were compensated with £6.00 (US $7.69) per hour following Prolific regulations [What is your pricing? Prolific. URL: https://researcher-help.prolific.com/hc/en-gb/articles/360009223533-What-is-your-pricing [accessed 2024-01-17] 62].
Measures
Personal Characteristics
The same variables as in study 1 were collected from Prolific profiles and the baseline survey with the exception of smoking or vaping frequency, which were combined into 1 variable. For vaping, the question was adapted to “How often do you vape?”
Cognitive Experiences
In total, 2 survey items administered at the start of each conversational session with coach Kai were used to explore cognitive experiences with the future-self tasks. In conversational sessions 2 to 5, coach Kai asked participants to rate their effort on the assigned future-self task from 0=nothing to 10=extremely strong. This served as an indication of mental effort. Participants then answered an open question, “How did you approach, do, or experience your assigned activity?” requiring a response of at least 20 characters. After providing a response, participants were asked by coach Kai whether they wanted to add something to or modify their response. The approach part of the question was expected to probe participants to share their cognitive experiences with future-self tasks.
Behavioral and Affective Experiences
The do and approach parts of a question “How did you approach, do, or experience your assigned task?” were expected to probe participants to share their behavioral experiences with future-self tasks, whereas the experience part was expected to probe them to share affective experiences.
Data Analysis
Descriptive statistics were computed. Two 1-sample t tests examined whether mean effort on the 8 future-self tasks differed from (1) the midpoint of the scale (ie, 5) and (2) mean effort on the other 29 preparatory tasks. The effort score of 0.2% (1/447) of the participants was adjusted from 0 to 5 following self-report in the free-text response field that they had erroneously selected 0. Three-way and follow-up 1-way ANOVAs explored differences in effort based on behavior (smoking, PA, or both), polarity (desired or undesired future self or both), and modality (verbal or visual description or both) of the future-self tasks. Assumptions were verified ( Results of assumption testing and robustness analyses.Multimedia Appendix 2
Free-text survey answers were coded until no new codes emerged. This resulted in 17.6% (103/586) of free-text responses from 21.3% (95/447) of the participants. Responses ranged from 1 word to 13 sentences. The full coding tree can be found in Coding trees for qualitative analyses.Multimedia Appendix 3
Results
The main findings of study 2 are summarized in Table 3.
Quantitative Results: Effort Deployed on Future-Self Tasks
Participants completed between 1 and 3 future-self tasks. One-sample t tests showed that participants deployed significantly above-average amounts of effort on future-self tasks (mean 5.85, SD 2.56; t446=7.02; P<.001; Cohen d=0.33), akin to the effort deployed on the other preparatory tasks from the same study (t446=0.92; P=.36; Cohen d=0.04). Figure 2 shows mean effort by behavior, polarity, and modality. A 3-way ANOVA assessed possible differences in effort based on behavior, polarity, and modality. There was no significant interaction between behavior, polarity, or modality and effort (F1, 424=1.04; P=.39; ηp2=0.010) and no significant main effects of behavior (F1, 444=0.38; P=.69; ηp2=0.002), modality (F1,444=0.80; P=.45; ηp2=0.004), or polarity (F1,444=0.37; P=.69; ηp2=0.002).

Qualitative Results
Behavioral Experiences With Future-Self Tasks
Participants reported success in writing about their future selves (2/95, 2%) or finding an image representing them (13/95, 14%):
I found a picture of a graveyard, and imagined being laid to rest there earlier than I might be.
[Male participant; aged 59 years]
Several participants reported on the frequency (eg, 1-2 times a day or when craving a cigarette), duration (eg, needing several days to form a clear mental image [male participant; aged 31 years]), time of day (eg, before sleep [male participant; aged 23 years]), or conditions (eg, in a relaxed, quiet, distraction-free environment, 3/95, 3%) required for completing their future-self tasks. In total, 3% (3/95) of the participants were unable to complete the tasks due to forgetting, illness, or parental duties. Overall, participants adapted the future-self tasks to their preferences and lifestyles and integrated them into their lives.
The future-self tasks were reported to have various behavioral outcomes. A total of 15% (14/95) of the participants saw instructions as encouraging them to quit smoking or become more physically active:
I just made an effort to go for a short walk every day after work to destress.
[Female participant; aged 33 years]
In total, 2% (2/95) of the participants searched for information on smoking’s health effects, and others felt invited to formulate goals (11/95, 12%) or an action plan (5/95, 5%) regarding smoking or PA. A total of 8% (8/95) reported the task to be ineffective in changing their PA or smoking behavior:
I found that this task to help quit vaping was ineffective for me as I found it difficult to visualize myself in the future.
[Male participant; aged 59 years]
Cognitive Experiences With Future-Self Tasks
There was quite some variation in how participants experienced future-self tasks. In total, 2% (2/95) found them easy, whereas 5% (5/95) found them difficult. Reported reasons for seeing them as difficult included the inability to produce a clear mental image (5/95, 5%), refusal to think about (1/95, 1%) or identify with (1/95, 1%) an undesired future self, not perceiving the need to quit vaping (1/95, 1%), or addiction standing in the way of visualizing a future without smoking (1/95, 1%).
The future-self tasks were reported to trigger various cognitive processes. The most common was thinking about the consequences of current (14/95, 15%) or changed behavior (9/95, 9%):
I took my time to think about the negative things about vaping and be clear about the type of person I don’t want to become.
[Male participant; aged 42 years]
The second most common cognitive process was facing one’s fears (eg, of disease, premature death, or being a bad romantic partner and example to children, 6/95, 6%). The third most common was identifying positive (3/95, 3%) or negative (3/95, 3%) role models representative of desired or undesired future selves. The fourth most common was comparing desired and undesired future selves (1/95, 1%), desired future or past selves with the undesired current self (1/95, 1%), or past with desired future selves (5/95, 5%; eg, “I looked at pictures of myself when I was at my heaviest weight. I was close to 200 lbs, smoking, feeling like garbage. I don’t EVER want to become that person again” [female participant; aged 57 years]). The fifth most common was increased or decreased motivation for changing behavior following the tasks (1/95, 1%).
Affective Experiences With Future-Self Tasks
Tasks related to the undesired future self were experienced as confronting (6/95, 6%), anxiety inducing (2/95, 2%), worrisome (1/95, 1%), or saddening (1/95, 1%). In contrast, desired-future-self tasks felt inspiring (1/95, 1%) and provided something to look forward to (3/95, 3%).
Discussion
Regarding behavioral experiences, qualitative findings from study 2 indicated that participants successfully integrated future-self tasks into their lives by adjusting frequency, duration, timing, and location to suit their lifestyles and preferences. This aligns with study 1, suggesting that FSIs are feasible for smokers intending to quit and for varying levels of PA. Although the tasks aimed to help prepare for behavior change, numerous participants actually changed their PA and smoking behaviors or formulated goals and action plans to do so, suggesting that the tasks were stimulating enough to prompt action.
Regarding cognitive experiences, quantitative findings showed that participants exerted above-average effort on future-self tasks regardless of behavior, polarity, or modality. This implies that tasks were appropriately challenging. Similar to study 1, mental visualization was seen as complicating the tasks, a result formally assessed in study 3. Future-self tasks were perceived as easier with increased familiarity. They also appeared to stimulate various cognitive processes, suggesting that repeated practice may further enhance engagement.
Regarding affective experiences, future-self tasks elicited contrasting emotional responses—negative for undesired-future-self tasks and positive for desired-future-self tasks—highlighting the importance of considering emotional engagement with FSIs.
Study 3: Behavioral, Cognitive, and Affective Experiences With a Smoking-Related FSI
In study 3, quantitative and qualitative survey data from the original online longitudinal experimental study were used to explore behavioral, cognitive, and affective experiences with a smoking-related FSI. Additional information regarding the methods and results of the original study is reported elsewhere [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20,Meijer E, Gebhardt WA, van Laar C, Chavannes NH, van den Putte B. Identified or conflicted: a latent class and regression tree analysis explaining how identity constructs cluster within smokers. BMC Psychol. Oct 07, 2022;10(1):231. [FREE Full text] [CrossRef] [Medline]69], and the underlying data are openly accessible [Penfornis KM. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. DataverseNL. 2022. [CrossRef]70].
Methods
Participants
Participants were 43.3% (87/201) of the individuals included in the original study (ie, those who completed the FSI). Recruited in the Netherlands and Dutch-speaking part of Belgium between July 2017 and October 2018, they were sourced through various media channels (eg, participation in previous research and social media—the full list of recruitment methods is available elsewhere [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20]). Inclusion criteria were being aged ≥18 years, smoking daily, and intending to quit smoking sometime in the future. Participant characteristics are presented in Table 1.
Procedure
Data were collected using Qualtrics XM. After providing digital informed consent, participants completed the baseline survey and were randomized 1:1 to the intervention or waitlist control condition. Intervention participants imagined a future in which they successfully quit smoking, wrote about this future self (verbal task), and uploaded images describing it (visual task). Afterward, they completed a postintervention survey, which took approximately 20 minutes. Control participants completed similar tasks about washing their hands more often.
Ethical Considerations
Ethics approval was granted by the Research Ethics Committee of Leiden University’s Institute of Psychology (CEP17-0505/192). Digital consent from participants in the original study enabled secondary analyses without additional approval. Participant data were deidentified for analysis to ensure confidentiality and privacy. In total, 2 gift coupons of €100 (US $109.51) and 6 coupons of €50 (US $54.76) were randomly distributed among participants who completed the study.
Measures
Personal Characteristics
Participants indicated their gender, birth year, and cigarette consumption, which was recoded to match smoking frequency in studies 1 and 2. Educational level was used as an indicator of socioeconomic position (as in the studies by Penfornis et al [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20] and Meijer et al [Meijer E, Gebhardt WA, Dijkstra A, Willemsen MC, Van Laar C. Quitting smoking: the importance of non-smoker identity in predicting smoking behaviour and responses to a smoking ban. Psychol Health. 2015;30(12):1387-1409. [CrossRef] [Medline]71]), measured using answer options from no education to university and recoded according to the International Standard Classification of Education [International standard classification of education (ISCED). International Labor Organization. URL: https://ilostat.ilo.org/methods/concepts-and-definitions/classification-education/ [accessed 2024-02-20] 50].
Behavioral Experiences
This was measured through time spent on each future-self task (in minutes), extracted from Qualtrics, and 2 open questions about experiences with the desired- and undesired-future-self tasks (ie, “What was it like for you to perform the tasks about yourself in a future when you have [successfully quit/continued] smoking?”). The 2 open questions were expected to probe participants to share their behavioral experiences with future-self tasks. There was no minimum or maximum length for answers.
Cognitive Experiences
A total of 8 items assessed the experienced difficulty of different elements of future-self tasks (ie, “How difficult did you find it to do the following things: [visualize/search for images/write a text/write keywords] describing yourself [as successfully quit smoker/continued smoker]?”), with answer options 1=very difficult to 7=very easy. The variable was recoded so that a higher score indicated greater difficulty. Scores for writing a short text and writing keywords were averaged to create 1 verbal difficulty score. The 2 open questions about experiences with the desired- and undesired-future-self tasks were expected to probe participants to share their cognitive experiences with future-self tasks.
Affective Experiences
In total, 8 items ascertained emotional responses to future-self tasks, asking participants to what extent they felt happy, scared, sad, or angry when imagining a future in which they successfully quit or continued smoking, rated from 1=totally disagree to 5=totally agree. An average score was computed for each emotion. The 2 open questions about experiences with the desired- and undesired-future-self tasks were expected to probe participants to share their affective experiences with future-self tasks.
Data Analysis
Descriptive statistics were computed, and a 1-sample t test examined differences from 3.5, the midpoint of the scale, in the average experienced difficulty across the 2 future-self tasks. RM ANOVAs explored differences in (1) time spent based on polarity (desired vs undesired future self) and modality (verbal vs visual description of the future self) and (2) experienced difficulty based on polarity and future-self task element (ie, mental visualization vs verbal vs visual description of the future self). A multivariate ANOVA ascertained differences in the strength of the 4 emotions (happy, scared, sad, and angry) based on polarity. Assumptions were verified ( Results of assumption testing and robustness analyses.Multimedia Appendix 2
Answers to both open questions—which ranged from 1 word to 3 sentences—were coded for all participants who provided one (83/87, 95%). In total, 6% (5/83) of the participants provided identical answers for both future-self tasks, which were counted and interpreted only on first occurrence. A total of 6 answers of only a few characters in length or irrelevant for describing the experience (eg, “looking in the future”) were excluded from the analysis. The full coding tree can be found in Coding trees for qualitative analyses.Multimedia Appendix 3
Results
The main findings are summarized in Table 3.
Quantitative Results
Time Spent on Future-Self Tasks
Future-self tasks were completed in an average of 6.64 (SD 8.30) minutes. Figure 3 shows mean time spent by polarity and modality. An RM ANOVA assessed differences in time spent based on polarity and modality. There was no significant interaction effect (F1,81=0.74; P=.39; ηp2=0.009), but there were significant main effects of polarity (F1,81=23.81; P<.001; ηp2=0.227) and modality (F1,81=5.18; P=.03; ηp2=0.060) on time spent. Specifically, participants spent significantly more time on the verbal than on the visual task (∆=1.26, 95% CI 0.16-2.36) and on the desired- than on the undesired-future-self task (∆=2.16, 95% CI 1.28-3.04).

Experienced Difficulty of Future-Self Tasks
Future-self tasks were experienced as relatively difficult (mean 3.83, SD 1.02; t86=3.00; P=.002; Cohen d=0.32). Figure 3 shows mean experienced difficulty by polarity and task element. An RM ANOVA assessed differences in experienced difficulty based on polarity and task element. There was no significant interaction between polarity and element regarding experienced difficulty (F2,85=0.23; P=.80; ηp2=0.005). There was a significant main effect of element (F2,85=8.32; P<.001; ηp2=0.134). Specifically, searching for images summarizing the future selves was experienced as significantly more difficult than merely envisioning the future self (∆=−0.84, 95% CI −1.30 to −0.30).
Emotional Response to Future-Self Tasks
Figure 3 shows mean strength of each emotion by polarity. A multivariate ANOVA ascertained differences in the strength of the 4 emotions based on polarity. There was a significant main effect of polarity (F4,83=35.38; P<.001; ηp2=0.630). Specifically, the desired-future-self task elicited significantly more happiness than the undesired-future-self task (F1,86=141.58; P<.001; ηp2=0.622). The undesired-future-self task elicited significantly more anger (F1,86=61.14; P<.001; ηp2=0.416), sadness (F1,86=66.31; P<.001; ηp2=0.435), and anxiety (F1,86=21.60; P<.001; ηp2=0.201).
Qualitative Results
Behavioral Experiences With Future-Self Tasks
Only 2% (2/83) of the responses informed about behavioral experiences with the tasks. Specifically, one participant printed and kept the images describing his future selves, and another mentioned finding the task to be difficult to translate into action.
Cognitive Experiences With Future-Self Tasks
Nearly equal numbers of participants found the desired-future-self task easy (11/83, 13%) or difficult (8/83, 10%), with some describing it as inspiring (3/83, 4%), interesting (3/83, 4%), or important (2/83, 2%). Individual cases found it empowering, insightful, and peculiar. The undesired-future-self task was mostly considered (very) difficult (17/83, 20%). A few participants (2/83, 2%) found it easy, and individual cases found it peculiar, important, interesting, useful, and inspiring. In total, 1% (1/83) of the participants found both tasks equally easy, 2% (2/83) found the undesired-future-self task easier, and 5% (4/83) found the desired-future-self task easier due to difficulties imagining a negative, unwanted outcome.
Familiarity with envisioning one’s future self seemed impactful for task completion. Some participants (2/83, 2%) mentioned that it was their first time considering their future self, whereas others had done so once (1/83, 1%) or repeatedly (3/83, 4%) before. In total, 2% (2/83) of the participants, who were first timers, found the task difficult or “peculiar. I suddenly had to think about what a future without smoking actually means” (female participant; aged 28 years). Among those with previous experience, one participant reported no effect, another participant visualized a clearer future self this time around, and 2 others found the task easy or still difficult.
The desired future self provided something to look forward to (7/83, 8%), although some (3/83, 4%) found it unattainable. It fostered positive perceptions of the future or future self (2/83, 2%) and, in individual cases, prompted reflection on reasons to quit smoking and attitudes toward smoking or had little effect. The undesired-future-self task made clear who participants did not want to become (10/83, 12%):
I don’t want to become the person I outlined myself—surely a right-thinking person doesn’t poison herself!
[Female participant; aged 35 years]
It confronted some with their addiction (2/83, 2%) or its likelihood (2/83, 2%), decreased motivation to quit smoking (1/83, 1%), or felt like “you have to tell bad things about yourself” (male participant; aged 75 years).
Participants’ responses suggest that future-self tasks triggered various cognitive processes, including reflection on smoking consequences (10/83, 12%), cognitive dissonance (8/83, 10%), increased motivation to quit smoking (7/83, 8%), resistance to future-self thinking (3/83, 4%), comparing current and future selves (5/83, 6%) or future and past selves (2/83, 2%), and considering the meaning of being a smoker (2/83, 2%).
Preferences regarding the order of the future-self tasks were mixed. One participant preferred the desired-future-self task first for its pleasantness, whereas another favored the undesired-future-self task first to end positively:
Now the smoker is in my head instead of the nonsmoker.
[Male participant; aged 53 years]
Affective Experiences With Future-Self Tasks
A total of 17 adjectives were used to describe affective experiences with future-self tasks, both positive and negative. The desired-future-self task was most often called enjoyable (21/83, 25%). It was also described as positive (6/83, 7%), confronting (3/83, 4%), unpleasant (1/83, 1%), and depressing (1/83, 1%).
The undesired-future-self task was primarily described as confronting (21/83, 25%), unpleasant (10/83, 12%), depressing (5/83, 6%), negative (6/83, 7%), enlightening (3/83, 4%), anxiety inducing (3/83, 4%), and uncomfortable (2/83, 2%). Some described it as frustrating, humiliating, neutral, positive, and triggering insecurity. Notably, 2% (2/83) of the participants found the task enjoyable.
Discussion
Regarding behavioral experiences, quantitative findings from study 3 showed that future-self tasks were completed in less than 7 minutes, with more time devoted to the desired-future-self and verbal tasks. This indicates that FSIs can be time efficient.
Concerning cognitive experiences, quantitative results indicated that future-self tasks were considered relatively difficult, with visual description of future selves being harder than visualization. Qualitative results revealed variations in experienced difficulty—the desired-future-self task was viewed as both easy and difficult, whereas the undesired-future-self task was mostly seen as difficult. Furthermore, as observed in studies 1 and 2, unfamiliarity with envisioning one’s future self seemed to hinder task performance, although familiarity did not always ease it. Finally, task order preferences varied. These findings highlight the importance of considering differences in individual experiences with FSIs.
In line with the findings of studies 1 and 2, future-self tasks appeared to trigger numerous cognitive processes, further hinting at FSIs having the capacity to prompt action. Coherent with its concept, the desired future self generally provided something to look forward to and sometimes led to reflections on quitting smoking. Conversely, the undesired future self served as something to avoid, was seen as confronting, and sometimes decreased motivation to quit or prompted negative self-reflection.
Regarding affective experiences, quantitative results showed that participants mostly felt happy during the desired-future-self task and sad, angry, or anxious during the undesired-future-self task. Qualitative results supported this, with the desired-future-self task described as enjoyable and the undesired-future-self task described as confronting and unpleasant, although with individual variations. These experiences are understandable given the concept of the future-self tasks and suggest that they had the intended effect.
General Discussion
Principal Findings
Overview
This multistudy report involved various smoking- and PA-related FSIs from multiple empirical studies comprising a large number of participants. It is the first to explore user experiences with smoking- and PA-related FSIs, triangulating behavioral, cognitive, and affective dimensions. Regarding behavioral experiences, participants generally reported successful and timely integration of FSIs into daily life, with some noting changes in PA or smoking behavior despite the tasks being preparatory. Regarding cognitive experiences, a moderate effort was exerted, with task difficulty varying by individual and task, yet future-self tasks consistently prompted cognitive processes supporting behavior change. Regarding affective experiences, desired-future-self tasks were generally seen as enjoyable and happiness inducing, whereas undesired-future-self tasks were perceived as confronting, unpleasant, and evoking negative emotions. The findings of all 3 studies are summarized in Table 3.
Behavioral Experiences With FSIs
Study 3 reflected that participants successfully and quickly completed digital FSIs and integrated them into their lives. With a completion time of less than 7 minutes—much less than the 15 minutes anticipated in study 1 and 14 to 20 minutes reported in previous studies [Tindle HA, Barbeau EM, Davis RB, Eisenberg DM, Park ER, Phillips RS, et al. Guided imagery for smoking cessation in adults: a randomized pilot trial. Complement Health Pract Rev. Jan 2006;11(3):166-175. [CrossRef]37,Wynd C. Guided health imagery for smoking cessation and long-term abstinence. J Nurs Scholarsh. 2005;37(3):245-250. [FREE Full text] [CrossRef] [Medline]38]—these interventions seem time efficient. Differences in completion time in this study compared to previous ones may be due to the digital format allowing for more freedom over exercise length. The discrepancy with study 1’s estimate may stem from difficulties estimating time requirements without completing the intervention.
The successful integration of FSIs into daily life suggests feasibility and acceptability. Participants did not provide negative comments about the digital format, which further supports the feasibility and acceptability of digital implementation. Digital implementation, in turn, optimizes human and monetary resources for smoking cessation and PA promotion and allows for delivering support anywhere, anytime [Marcolino MS, Oliveira JA, D'Agostino M, Ribeiro AL, Alkmim MB, Novillo-Ortiz D. The impact of mHealth interventions: systematic review of systematic reviews. JMIR Mhealth Uhealth. Jan 17, 2018;6(1):e23. [FREE Full text] [CrossRef] [Medline]8].
Studies 1 and 3 provided additional insights into future-self task completion time. Study 3 revealed that verbal descriptions took longer than visual ones, consistent with study 1’s expectations. This may be because visually describing the future self extends the process of producing mental images, partly relying on the same visual cognitive processes [Meijer E, Gebhardt WA, van Laar C, Chavannes NH, van den Putte B. Identified or conflicted: a latent class and regression tree analysis explaining how identity constructs cluster within smokers. BMC Psychol. Oct 07, 2022;10(1):231. [FREE Full text] [CrossRef] [Medline]69,Kavanagh DJ, Andrade J, May J. Imaginary relish and exquisite torture: the elaborated intrusion theory of desire. Psychol Rev. Apr 2005;112(2):446-467. [FREE Full text] [CrossRef] [Medline]72], whereas verbal future-self tasks, which rely on different cognitive processes, would understandably take longer. Alternatively, participants generally used existing images for visual descriptions, which is quicker than creating written materials. Future research could validate and shed light on the origin of this difference. Study 3 also showed that desired-future-self tasks took longer than undesired-future-self ones, possibly because participants were more inclined to invest time in considering and describing a positive future self. Therefore, future research and FSI designs could explore how to optimize task formats to balance cognitive engagement, practical feasibility, and impact.
One study 2 participant attempted to quit smoking, and multiple participants increased their PA after the future-self tasks, suggesting that FSIs can be effective in influencing behavior. These findings echo previous successes of FSIs in influencing smoking and PA behaviors [Rutchick AM, Slepian ML, Reyes MO, Pleskus LN, Hershfield HE. Future self-continuity is associated with improved health and increases exercise behavior. J Exp Psychol Appl. Mar 2018;24(1):72-80. [CrossRef] [Medline]31,Chan CK, Cameron LD. Promoting physical activity with goal-oriented mental imagery: a randomized controlled trial. J Behav Med. Jun 2012;35(3):347-363. [CrossRef] [Medline]33-Wynd C. Guided health imagery for smoking cessation and long-term abstinence. J Nurs Scholarsh. 2005;37(3):245-250. [FREE Full text] [CrossRef] [Medline]38] and support the continued use of these interventions to promote change in these health behaviors. In contrast, no behavior changes were observed in study 3, possibly because study 2 participants were explicitly told that FSIs might help quit smoking—a hypothesis for future research. Reported changes mainly involved increased PA, possibly because the PA-related tasks in study 2 presented PA as a potential facilitator of smoking cessation, empowering participants to increase their PA as a first step. Alternatively, as the participants were daily smokers and, in most cases, regular exercisers, smoking and PA were likely anchored in their identity. We know that people prefer to act in line with their identity and will try to avoid behaviors that do not align with or threaten it [Burke PJ, Stets JE. Identity Theory. Oxford, UK. Oxford University Press; 2009. 16,Oyserman D, Elmore K, Smith G. Self, self-concept, and identity. In: Leary M, Tangney J, editors. Handbook of Self and Identity Second Edition. New York City, NY. Guilford Publications; Jan 2012. 73]. Thus, tasks aiming to connect nonsmoking with their identity may have felt less self-relevant or threatening, discouraging changes, whereas PA-related tasks possibly reinforced PA identity, encouraging the behavior. These findings suggest that interventions are more effective when they build on established identity or carefully frame new behaviors, such as nonsmoking, to align with or positively reinforce the individual’s current identity.
Cognitive Experiences With FSIs
Slightly above-average effort was exerted to complete the tasks in study 2, akin to effort deployed in comparable future-self tasks [Albers N, Neerincx MA, Brinkman WP. Addressing people's current and future states in a reinforcement learning algorithm for persuading to quit smoking and to be physically active. PLoS One. Dec 1, 2022;17(12):e0277295. [FREE Full text] [CrossRef] [Medline]74] and the other preparatory tasks from the study. This effort level suggests that the tasks either included fitting elements to keep individuals engaged [Meijer E, Gebhardt WA, Dijkstra A, Willemsen MC, Van Laar C. Quitting smoking: the importance of non-smoker identity in predicting smoking behaviour and responses to a smoking ban. Psychol Health. 2015;30(12):1387-1409. [CrossRef] [Medline]71] or lacked such elements, resulting in individuals not being sufficiently engaged to exert more effort. This effort level further implies that participants took the tasks seriously, possibly because they found them useful and meaningful [Tindle HA, Barbeau EM, Davis RB, Eisenberg DM, Park ER, Phillips RS, et al. Guided imagery for smoking cessation in adults: a randomized pilot trial. Complement Health Pract Rev. Jan 2006;11(3):166-175. [CrossRef]37,Albers N, Neerincx MA, Penfornis KM, Brinkman WP. Users' needs for a digital smoking cessation application and how to address them: a mixed-methods study. PeerJ. Aug 19, 2022;10:e13824. [FREE Full text] [CrossRef] [Medline]60,Baumel A, Muench FJ. Effort-optimized intervention model: framework for building and analyzing digital interventions that require minimal effort for health-related gains. J Med Internet Res. Mar 12, 2021;23(3):e24905. [FREE Full text] [CrossRef] [Medline]76,Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. Mar 2012;36(1):157-178. [CrossRef]77], and may indicate tasks of appropriate difficulty and emotional engagement (see the motivational intensity theory [Albers N, Neerincx MA, Brinkman WP. Addressing people's current and future states in a reinforcement learning algorithm for persuading to quit smoking and to be physically active. PLoS One. Dec 1, 2022;17(12):e0277295. [FREE Full text] [CrossRef] [Medline]74,Szinay D, Jones A, Chadborn T, Brown J, Naughton F. Influences on the uptake of and engagement with health and well-being smartphone apps: systematic review. J Med Internet Res. May 29, 2020;22(5):e17572. [FREE Full text] [CrossRef] [Medline]75]). No significant differences in effort were observed based on behavior, polarity, or modality, suggesting equal willingness to describe the desired or undesired future self verbally or visually regardless of whether the behavior is health compromising or health promoting. While the aforementioned findings are insightful, more research (eg, conducting in-depth interviews with users to understand their perceptions of effort) would be beneficial for unequivocal conclusions.
Across all studies, task difficulty varied depending on individuals, tasks, and quantitative versus qualitative data. More specifically, in study 1, future-self tasks were anticipated to be relatively easy, whereas in study 3, they were experienced as fairly difficult. In study 1, undesired-future-self, PA-related, and visual future-self tasks were anticipated to be harder, but in study 3, only visual tasks were perceived as more challenging. In addition, while in studies 1 and 2 participants often attributed difficulty to visualization, study 3 found it to be the easiest task component, with visual description being the most challenging. Given that study 3 actually measured difficulty directly—unlike study 1, which measured anticipated completion time—its findings could be considered more reliable. However, its qualitative results partly contradicted its quantitative findings as envisioning future selves was generally considered difficult. In summary, conclusions about future-self task difficulty are inconsistent, warranting further investigation. In total, 2 exceptions emerged. First, visual future-self tasks were generally seen as difficult, suggesting that verbal tasks may be preferable for future interventions, although more time-consuming. Second, all 3 studies found that unfamiliarity with mental visualization complicated future-self tasks, supporting the teaching [Wynd C. Guided health imagery for smoking cessation and long-term abstinence. J Nurs Scholarsh. 2005;37(3):245-250. [FREE Full text] [CrossRef] [Medline]38,Scarpa MP, Prilletensky I, McMahon A, Myers ND, Prilleltensky O, Lee S, et al. Is fun for wellness engaging? Evaluation of user experience of an online intervention to promote well-being and physical activity. Front Comput Sci. Jun 18, 2021;3. [CrossRef]41] and practice of mental visualization.
Future-self tasks in studies 2 and 3 were reported to trigger cognitive processes (eg, considering the consequences of PA or smoking behavior or behavior change motivation fluctuations, which typically precede behavior change [Barnett G, Boduszek D, Willmott D. What works to change identity? A rapid evidence assessment of interventions. J Appl Soc Psychol. May 03, 2021;51(7):698-719. [CrossRef]78-Michie S, Hyder N, Walia A, West R. Development of a taxonomy of behaviour change techniques used in individual behavioural support for smoking cessation. Addict Behav. Apr 2011;36(4):315-319. [CrossRef] [Medline]81]). Sometimes, the tasks seemed to trigger mental contrasting among past, present, or future selves, a process beneficial for achieving the desired identity and avoiding the undesired one [Oettingen G. Future thought and behaviour change. Eur Rev Soc Psychol. Mar 13, 2012;23(1):1-63. [CrossRef]29,Oyserman D. Pathways to Success Through Identity-Based Motivation. Oxford, UK. Oxford University Press; 2015. 82]. Coupled with behavior change reports, it seems that future-self tasks can effectively prepare participants for behavior change by connecting healthier behaviors with their identity. Future research could assess whether FSIs are more suited to change certain health behaviors and whether they have the capacity to change multiple health behaviors simultaneously [Prochaska JJ, Prochaska JO. A review of multiple health behavior change interventions for primary prevention. Am J Lifestyle Med. May 2011;5(3):208-221. [FREE Full text] [CrossRef] [Medline]7,James E, Freund M, Booth A, Duncan MJ, Johnson N, Short CE, et al. Comparative efficacy of simultaneous versus sequential multiple health behavior change interventions among adults: a systematic review of randomised trials. Prev Med. Aug 2016;89:211-223. [CrossRef] [Medline]83].
Affective Experiences With FSIs
All studies showed that desired-future-self tasks were generally experienced as positive and enjoyable and associated with happiness, aligning with previous research [Boyatzis RE, Akrivou K. The ideal self as the driver of intentional change. J Manag Dev. Aug 1, 2006;25(7):624-642. [CrossRef]42,Schubert T, Eloo R, Scharfen J, Morina N. How imagining personal future scenarios influences affect: systematic review and meta-analysis. Clin Psychol Rev. Feb 2020;75:101811. [CrossRef] [Medline]43]. Conversely, undesired-future-self tasks were reported as negative, confronting, and unpleasant and linked to feeling scared, sad, or angry, also supporting previous findings [Schubert T, Eloo R, Scharfen J, Morina N. How imagining personal future scenarios influences affect: systematic review and meta-analysis. Clin Psychol Rev. Feb 2020;75:101811. [CrossRef] [Medline]43]. By allowing individuals to anticipate feeling what it is like to (not) be someone who engages in a certain behavior, future-self imagery can drive intentional behavior change [Markus H, Nurius P. Possible selves. Am Psychol. 1986;41(9):954-969. [CrossRef]27,Oyserman D, Bybee D, Terry K, Hart-Johnson T. Possible selves as roadmaps. J Res Pers. Apr 2004;38(2):130-149. [CrossRef]28] and sustain desire for change until the behavior becomes habitual [Solbrig L, Whalley B, Kavanagh DJ, May J, Parkin T, Jones R, et al. Functional imagery training versus motivational interviewing for weight loss: a randomised controlled trial of brief individual interventions for overweight and obesity. Int J Obes (Lond). Apr 2019;43(4):883-894. [CrossRef] [Medline]84]. Therefore, despite causing some measure of negative arousal, the undesired-future-self task appears crucial for motivating behavior change and should remain part of FSIs. To minimize psychological distress, strategies such as ending with desired-future-self tasks, allowing for task order choice, rehearsing steps to avoid or achieve the undesired or desired future self to boost self-efficacy [Chan CK, Cameron LD. Promoting physical activity with goal-oriented mental imagery: a randomized controlled trial. J Behav Med. Jun 2012;35(3):347-363. [CrossRef] [Medline]33,Tindle HA, Barbeau EM, Davis RB, Eisenberg DM, Park ER, Phillips RS, et al. Guided imagery for smoking cessation in adults: a randomized pilot trial. Complement Health Pract Rev. Jan 2006;11(3):166-175. [CrossRef]37,Solbrig L, Whalley B, Kavanagh DJ, May J, Parkin T, Jones R, et al. Functional imagery training versus motivational interviewing for weight loss: a randomised controlled trial of brief individual interventions for overweight and obesity. Int J Obes (Lond). Apr 2019;43(4):883-894. [CrossRef] [Medline]84], or arranging access to (professional) human support could be used.
Strengths and Limitations
This multistudy report has several limitations. First, conducting secondary analyses on data from different studies with diverse original aims, interventions, and methodologies complicated the triangulation and interpretation of findings. However, combining mixed methods data across interventions and research fields provided richer insights into user experiences, which can guide hypothesis formulation in future research. Second, post hoc power analyses showed that some effects, especially interaction effects in studies 1 and 3, fell below the conventional 0.80 threshold. Hence, certain effects may have been missed, which calls for research using larger, adequately powered samples to validate the findings. Nevertheless, we systematically tested main and simple main effects across all factors, reducing the likelihood of having missed essential patterns in the data. Third, as the participants were predominantly highly educated—and, therefore, likely digitally literate and used to performing tasks requiring cognitive load—some sampling bias may have been introduced. The findings of this multistudy report may not transfer to populations with middle and lower educational levels [Ritchie H, Samborska V, Ahuja N, Ortiz-Ospina E, Roser M. Global education. Our World in Data. URL: https://ourworldindata.org/global-education [accessed 2024-06-28] 85], in particular people who smoke [Cao P, Jeon J, Tam J, Fleischer NL, Levy DT, Holford TR, et al. Smoking disparities by level of educational attainment and birth cohort in the U.S. Am J Prev Med. Apr 2023;64(4 Suppl 1):S22-S31. [FREE Full text] [CrossRef] [Medline]86-Tomioka K, Kurumatani N, Saeki K. The association between education and smoking prevalence, independent of occupation: a nationally representative survey in Japan. J Epidemiol. Mar 05, 2020;30(3):136-142. [FREE Full text] [CrossRef] [Medline]88], and have to be interpreted carefully. Fourth, while all studies mostly relied on self-report measures, which are less objective than use or performance measures, such measures are commonly used in research and valued for their convenience, efficiency [O'Brien HL, Toms EG. The development and evaluation of a survey to measure user engagement. J Am Soc Inf Sci Technol. Dec 09, 2009;61(1):50-69. [CrossRef]89], and capacity to capture complex experiences. In addition, combining qualitative and quantitative data and exploring behavioral, cognitive, and affective aspects likely mitigated the limitations of individual studies, offering a more thorough perspective on user experiences with FSIs.
Conclusions
The findings of this multistudy report support the future use of FSIs as a time-efficient, feasible, and acceptable method for promoting smoking cessation and PA by connecting healthier behaviors with self-identity. Experiences with FSIs did not appear to significantly differ between smoking, a health-compromising behavior, and PA, a health-promoting behavior. Digital administration seemed acceptable and is beneficial for efficient use of human and monetary resources. We encourage FSIs to include both a desired- and undesired-future-self task and train users in mental visualization. The intervention may be improved by tailoring it to individual preferences, such as choosing to start with the desired- or undesired-future-self task. The results enhance the scientific understanding of FSIs and offer guidance for designing tailored, effective, scalable, user-centered digital interventions promoting smoking cessation and PA. While the results encourage further use, inconsistencies in them highlight the need for more research to optimize FSIs, such as further assessing user experiences; the effectiveness of FSIs in influencing multiple health behaviors; and the impact of factors such as socioeconomic position, self-identity strength, or behavioral history.
Acknowledgments
The authors would like to thank Emma von Haeseler, BS, for her invaluable contribution to the qualitative analyses in this multistudy report. They also give special thanks to Professor Dr Ir Geke Ludden for her input on the manuscript’s structure and narrative and valuable literature references in that regard. This work is part of the multidisciplinary research project Perfect Fit. This research received funding from the Netherlands Organisation for Scientific Research Commit2Data – Big Data & Health program (project 628.011.211). The program was funded by the following parties: the Netherlands Organisation for Scientific Research; the Netherlands Organisation for Health Research and Development; the Dutch Heart Foundation; the Ministry of Health, Welfare, and Sport; Health~Holland; and the Netherlands eScience Center. The publication reflects only the authors’ views, and the funders are not liable for any use that may be made of the information contained herein. ChatGPT (OpenAI) was used to correct spelling and grammatical errors and to shorten the manuscript. All corrections were verified by the first author.
Data Availability
The datasets generated or analyzed during study 1 [Albers N, Neerincx MA, Brinkman WP. Difficulty and time perceptions of preparatory activities for quitting smoking: Dataset. 4TU.ResearchData. Nov 6, 2023. URL: https://data.4tu.nl/datasets/5198f299-9c7a-40f8-8206-c18df93ee2a0/1 [accessed 2025-04-23] 57], study 2 [Penfornis KM, Albers N. User experiences with digital future-self interventions in the contexts of smoking and physical activity: a mixed methods multi-study exploration - data and analysis code. 4TU.ResearchData. 2025. URL: https://data.4tu.nl/datasets/951b2dc4-a59e-48ed-9856-af484b125393 [accessed 2025-04-23] 53], and study 3 [Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]20], as well as the analysis codes for all 3 studies are available online [Penfornis KM, Albers N. User experiences with digital future-self interventions in the contexts of smoking and physical activity: a mixed methods multi-study exploration - data and analysis code. 4TU.ResearchData. 2025. URL: https://data.4tu.nl/datasets/951b2dc4-a59e-48ed-9856-af484b125393 [accessed 2025-04-23] 53].
Conflicts of Interest
None declared.
Multimedia Appendix 1
Instructions for the future-self interventions used in studies 1, 2, and 3.
DOCX File , 19 KBReferences
- Global burden of disease (GBD). Institute for Health Metrics and Evaluation. URL: https://www.healthdata.org/research-analysis/gbd [accessed 2024-02-09]
- Child mortality rate, 2022. Our World in Data. URL: https://ourworldindata.org/explorers/global-health [accessed 2025-04-23]
- Ritchie H, Roser M. Smoking. Our World in Data. URL: https://ourworldindata.org/smoking [accessed 2024-02-09]
- Yang Y, Xu H, Liu X, Li J, Liew Z, Liu X, et al. Joint association of smoking and physical activity with mortality in elderly hypertensive patients: a Chinese population-based cohort study in 2007-2018. Front Public Health. Sep 29, 2022;10:1005260. [FREE Full text] [CrossRef] [Medline]
- Stenholm S, Head J, Kivimäki M, Kawachi I, Aalto V, Zins M, et al. Smoking, physical inactivity and obesity as predictors of healthy and disease-free life expectancy between ages 50 and 75: a multicohort study. Int J Epidemiol. Aug 2016;45(4):1260-1270. [FREE Full text] [CrossRef] [Medline]
- Duan Y, Shang B, Liang W, Du G, Yang M, Rhodes RE. Effects of eHealth-based multiple health behavior change interventions on physical activity, healthy diet, and weight in people with noncommunicable diseases: systematic review and meta-analysis. J Med Internet Res. Feb 22, 2021;23(2):e23786. [FREE Full text] [CrossRef] [Medline]
- Prochaska JJ, Prochaska JO. A review of multiple health behavior change interventions for primary prevention. Am J Lifestyle Med. May 2011;5(3):208-221. [FREE Full text] [CrossRef] [Medline]
- Marcolino MS, Oliveira JA, D'Agostino M, Ribeiro AL, Alkmim MB, Novillo-Ortiz D. The impact of mHealth interventions: systematic review of systematic reviews. JMIR Mhealth Uhealth. Jan 17, 2018;6(1):e23. [FREE Full text] [CrossRef] [Medline]
- Fang YE, Zhang Z, Wang R, Yang B, Chen C, Nisa C, et al. Effectiveness of eHealth smoking cessation interventions: systematic review and meta-analysis. J Med Internet Res. Jul 28, 2023;25:e45111. [FREE Full text] [CrossRef] [Medline]
- Smoking cessation: a report of the surgeon general. U.S. Department of Health and Human Services. 2020. URL: https://www.hhs.gov/sites/default/files/2020-cessation-sgr-full-report.pdf [accessed 2024-09-02]
- Europe physical activity factsheet 2021. European Commission. URL: https://sport.ec.europa.eu/document/europe-physical-activity-factsheet-2021 [accessed 2025-05-15]
- Chaiton M, Diemert L, Cohen JE, Bondy SJ, Selby P, Philipneri A, et al. Estimating the number of quit attempts it takes to quit smoking successfully in a longitudinal cohort of smokers. BMJ Open. Jun 09, 2016;6(6):e011045. [FREE Full text] [CrossRef] [Medline]
- Hartmann-Boyce J, Livingstone-Banks J, Ordóñez-Mena JM, Fanshawe TR, Lindson N, Freeman SC, et al. Behavioural interventions for smoking cessation: an overview and network meta-analysis. Cochrane Database Syst Rev. Jan 04, 2021;1(1):CD013229. [CrossRef] [Medline]
- Jepson RG, Harris FM, Platt S, Tannahill C. The effectiveness of interventions to change six health behaviours: a review of reviews. BMC Public Health. Sep 08, 2010;10:538. [FREE Full text] [CrossRef] [Medline]
- Murray JM, Brennan SF, French DP, Patterson CC, Kee F, Hunter RF. Effectiveness of physical activity interventions in achieving behaviour change maintenance in young and middle aged adults: a systematic review and meta-analysis. Soc Sci Med. Nov 2017;192:125-133. [CrossRef] [Medline]
- Burke PJ, Stets JE. Identity Theory. Oxford, UK. Oxford University Press; 2009.
- Oyserman D. Identity‐based motivation: implications for action‐readiness, procedural‐readiness, and consumer behavior. J Consum Psychol. Jun 25, 2009;19(3):250-260. [CrossRef]
- Meijer E, Van den Putte B, Gebhardt WA, Van Laar C, Bakk Z, Dijkstra A, et al. A longitudinal study into the reciprocal effects of identities and smoking behaviour: findings from the ITC Netherlands Survey. Soc Sci Med. Mar 2018;200:249-257. [FREE Full text] [CrossRef] [Medline]
- Smit ES, Hoving C, Schelleman-Offermans K, West R, de Vries H. Predictors of successful and unsuccessful quit attempts among smokers motivated to quit. Addict Behav. Sep 2014;39(9):1318-1324. [FREE Full text] [CrossRef] [Medline]
- Penfornis KM, Gebhardt WA, Rippe RC, Van Laar C, van den Putte B, Meijer E. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. Soc Sci Med. Mar 2023;320:115667. [FREE Full text] [CrossRef] [Medline]
- Tombor I, Shahab L, Brown J, West R. Positive smoker identity as a barrier to quitting smoking: findings from a national survey of smokers in England. Drug Alcohol Depend. Dec 01, 2013;133(2):740-745. [CrossRef] [Medline]
- van den Putte B, Yzer M, Willemsen MC, de Bruijn GJ. The effects of smoking self-identity and quitting self-identity on attempts to quit smoking. Health Psychol. Sep 2009;28(5):535-544. [CrossRef] [Medline]
- de Bruijn GJ, van den Putte B. Exercise promotion: an integration of exercise self‐identity, beliefs, intention, and behaviour. Eur J Sport Sci. Feb 29, 2012;12(4):354-366. [CrossRef]
- Havitz ME, Kaczynski AT, Mannell RC. Exploring relationships between physical activity, leisure involvement, self-efficacy, and motivation via participant segmentation. Leis Sci. 2013;35(1):45-62. [CrossRef]
- Huffman MK, Christ SL, Ferraro KF, Klenosky DB, Marceau K, Amireault S. Measuring physical activity regulatory styles and identity among adults 55 years or older. J Aging Health. Oct 2022;34(6-8):775-785. [CrossRef] [Medline]
- Strachan SM, Perras MG, Forneris T, Stadig GS. I'm an exerciser: common conceptualisations of and variation in exercise identity meanings. Int J Sport Exerc Psychol. Oct 19, 2015;15(3):321-336. [CrossRef]
- Markus H, Nurius P. Possible selves. Am Psychol. 1986;41(9):954-969. [CrossRef]
- Oyserman D, Bybee D, Terry K, Hart-Johnson T. Possible selves as roadmaps. J Res Pers. Apr 2004;38(2):130-149. [CrossRef]
- Oettingen G. Future thought and behaviour change. Eur Rev Soc Psychol. Mar 13, 2012;23(1):1-63. [CrossRef]
- Oyserman D, Destin M, Novin S. The context-sensitive future self: possible selves motivate in context, not otherwise. Self Identity. Oct 08, 2014;14(2):173-188. [CrossRef]
- Rutchick AM, Slepian ML, Reyes MO, Pleskus LN, Hershfield HE. Future self-continuity is associated with improved health and increases exercise behavior. J Exp Psychol Appl. Mar 2018;24(1):72-80. [CrossRef] [Medline]
- Meijer E, Gebhardt WA, van Laar C, van den Putte B, Evers AW. Strengthening quitter self-identity: an experimental study. Psychol Health. Oct 2018;33(10):1229-1250. [FREE Full text] [CrossRef] [Medline]
- Chan CK, Cameron LD. Promoting physical activity with goal-oriented mental imagery: a randomized controlled trial. J Behav Med. Jun 2012;35(3):347-363. [CrossRef] [Medline]
- Murru EC, Martin Ginis KA. Imagining the possibilities: the effects of a possible selves intervention on self-regulatory efficacy and exercise behavior. J Sport Exerc Psychol. Aug 2010;32(4):537-554. [CrossRef] [Medline]
- Ouellette JA, Hessling R, Gibbons FX, Reis-Bergan M, Gerrard M. Using images to increase exercise behavior: prototypes versus possible selves. Pers Soc Psychol Bull. May 2005;31(5):610-620. [CrossRef] [Medline]
- Shadel WG, Cervone D. Evaluating social-cognitive mechanisms that regulate self-efficacy in response to provocative smoking cues: an experimental investigation. Psychol Addict Behav. Mar 2006;20(1):91-96. [CrossRef] [Medline]
- Tindle HA, Barbeau EM, Davis RB, Eisenberg DM, Park ER, Phillips RS, et al. Guided imagery for smoking cessation in adults: a randomized pilot trial. Complement Health Pract Rev. Jan 2006;11(3):166-175. [CrossRef]
- Wynd C. Guided health imagery for smoking cessation and long-term abstinence. J Nurs Scholarsh. 2005;37(3):245-250. [FREE Full text] [CrossRef] [Medline]
- Meslot C, Gauchet A, Allenet B, François O, Hagger MS. Theory-based interventions combining mental simulation and planning techniques to improve physical activity: null results from two randomized controlled trials. Front Psychol. Nov 16, 2016;7:1789. [FREE Full text] [CrossRef] [Medline]
- Yardley L, Spring BJ, Riper H, Morrison LG, Crane DH, Curtis K, et al. Understanding and promoting effective engagement with digital behavior change interventions. Am J Prev Med. Nov 2016;51(5):833-842. [CrossRef] [Medline]
- Scarpa MP, Prilletensky I, McMahon A, Myers ND, Prilleltensky O, Lee S, et al. Is fun for wellness engaging? Evaluation of user experience of an online intervention to promote well-being and physical activity. Front Comput Sci. Jun 18, 2021;3. [CrossRef]
- Boyatzis RE, Akrivou K. The ideal self as the driver of intentional change. J Manag Dev. Aug 1, 2006;25(7):624-642. [CrossRef]
- Schubert T, Eloo R, Scharfen J, Morina N. How imagining personal future scenarios influences affect: systematic review and meta-analysis. Clin Psychol Rev. Feb 2020;75:101811. [CrossRef] [Medline]
- Kelders SM, van Zyl LE, Ludden GD. The concept and components of engagement in different domains applied to eHealth: a systematic scoping review. Front Psychol. May 27, 2020;11:926. [FREE Full text] [CrossRef] [Medline]
- O'Brien HL, Toms EG. What is user engagement? A conceptual framework for defining user engagement with technology. J Am Soc Inf Sci Technol. Feb 28, 2008;59(6):938-955. [CrossRef]
- Perski O, Blandford A, West R, Michie S. Conceptualising engagement with digital behaviour change interventions: a systematic review using principles from critical interpretive synthesis. Transl Behav Med. Jun 2017;7(2):254-267. [FREE Full text] [CrossRef] [Medline]
- Short CE, DeSmet A, Woods C, Williams SL, Maher C, Middelweerd A, et al. Measuring engagement in eHealth and mHealth behavior change interventions: viewpoint of methodologies. J Med Internet Res. Nov 16, 2018;20(11):e292. [FREE Full text] [CrossRef] [Medline]
- Dawadi S, Shrestha S, Giri RA. Mixed-methods research: a discussion on its types, challenges, and criticisms. J Pract Stud Educ. Feb 24, 2021;2(2):25-36. [CrossRef]
- Lynn M. More multi-study articles wanted. Cornell Hosp Q. Jun 23, 2017;58(3):228. [CrossRef]
- International standard classification of education (ISCED). International Labor Organization. URL: https://ilostat.ilo.org/methods/concepts-and-definitions/classification-education/ [accessed 2024-02-20]
- Tabachnick BG, Fidell LS. Using Multivariate Statistics. London, UK. Pearson; 2018.
- Cohen J. Statistical Power Analysis for the Behavioral Sciences Second Edition. Milton Park, UK. Routledge; 1988.
- Penfornis KM, Albers N. User experiences with digital future-self interventions in the contexts of smoking and physical activity: a mixed methods multi-study exploration - data and analysis code. 4TU.ResearchData. 2025. URL: https://data.4tu.nl/datasets/951b2dc4-a59e-48ed-9856-af484b125393 [accessed 2025-04-23]
- White MD, Marsh EE. Content analysis: a flexible methodology. Libr Trends. 2006;55(1):22-45. [CrossRef]
- Albers N. Psychology-informed reinforcement learning for situated virtual coaching in smoking cessation. Delft University of Technology. 2025. URL: https://doi.org/10.4233/uuid:5e1d1500-1c45-4869-b995-6ed7db8f8b3b [accessed 2025-04-22]
- Albers N, Brinkman WP. Perfect Fit - beliefs about and competencies built by preparatory activities for quitting smoking and becoming more physically active. OSF Registries. 2022. URL: https://osf.io/cax6f [accessed 2024-01-16]
- Albers N, Neerincx MA, Brinkman WP. Difficulty and time perceptions of preparatory activities for quitting smoking: Dataset. 4TU.ResearchData. Nov 6, 2023. URL: https://data.4tu.nl/datasets/5198f299-9c7a-40f8-8206-c18df93ee2a0/1 [accessed 2025-04-23]
- Prolific homepage. Prolific. URL: https://www.prolific.com [accessed 2024-10-23]
- Researcher help center. Prolific. URL: https://researcher-help.prolific.com/hc/en-gb/articles/360009220833-Who-are-the-participants-on-Prolific [accessed 2024-01-16]
- Albers N, Neerincx MA, Penfornis KM, Brinkman WP. Users' needs for a digital smoking cessation application and how to address them: a mixed-methods study. PeerJ. Aug 19, 2022;10:e13824. [FREE Full text] [CrossRef] [Medline]
- Qualtrics XM homepage. Qualtrics. URL: https://www.qualtrics.com/nl/ [accessed 2024-10-23]
- What is your pricing? Prolific. URL: https://researcher-help.prolific.com/hc/en-gb/articles/360009223533-What-is-your-pricing [accessed 2024-01-17]
- Schaap MM, Kunst AE. Monitoring of socio-economic inequalities in smoking: learning from the experiences of recent scientific studies. Public Health. Feb 2009;123(2):103-109. [CrossRef] [Medline]
- Perfect Fit - learning when to involve a human coach in an eHealth application for preparing for quitting smoking or vaping. OSF Registries. URL: https://osf.io/78cnr [accessed 2025-05-30]
- Perfect Fit - experiment to gather data for and test a reinforcement learning-approach for motivating people. OSF Registries. URL: https://osf.io/k2uac [accessed 2025-05-30]
- Albers N, Brinkman WP. Perfect Fit - learning to propose useful preparatory activities for quitting smoking and becoming more physically active. OSF Registries. Jul 21, 2023. URL: https://osf.io/nuy4w [accessed 2025-04-09]
- Albers N. PerfectFit-project/virtual_coach_human_inv: virtual coach kai for preparing for quitting smoking with human support. Zenodo. May 2, 2024. URL: https://zenodo.org/records/11102861 [accessed 2025-04-22]
- Example dialog with the virtual coach kai for preparing to quit smoking with human support. YouTube. URL: https://www.youtube.com/watch?v=gLiy5AnolYE [accessed 2024-11-08]
- Meijer E, Gebhardt WA, van Laar C, Chavannes NH, van den Putte B. Identified or conflicted: a latent class and regression tree analysis explaining how identity constructs cluster within smokers. BMC Psychol. Oct 07, 2022;10(1):231. [FREE Full text] [CrossRef] [Medline]
- Penfornis KM. My future-self has (not) quit smoking: an experimental study into the effect of a future-self intervention on smoking-related self-identity constructs. DataverseNL. 2022. [CrossRef]
- Meijer E, Gebhardt WA, Dijkstra A, Willemsen MC, Van Laar C. Quitting smoking: the importance of non-smoker identity in predicting smoking behaviour and responses to a smoking ban. Psychol Health. 2015;30(12):1387-1409. [CrossRef] [Medline]
- Kavanagh DJ, Andrade J, May J. Imaginary relish and exquisite torture: the elaborated intrusion theory of desire. Psychol Rev. Apr 2005;112(2):446-467. [FREE Full text] [CrossRef] [Medline]
- Oyserman D, Elmore K, Smith G. Self, self-concept, and identity. In: Leary M, Tangney J, editors. Handbook of Self and Identity Second Edition. New York City, NY. Guilford Publications; Jan 2012.
- Albers N, Neerincx MA, Brinkman WP. Addressing people's current and future states in a reinforcement learning algorithm for persuading to quit smoking and to be physically active. PLoS One. Dec 1, 2022;17(12):e0277295. [FREE Full text] [CrossRef] [Medline]
- Szinay D, Jones A, Chadborn T, Brown J, Naughton F. Influences on the uptake of and engagement with health and well-being smartphone apps: systematic review. J Med Internet Res. May 29, 2020;22(5):e17572. [FREE Full text] [CrossRef] [Medline]
- Baumel A, Muench FJ. Effort-optimized intervention model: framework for building and analyzing digital interventions that require minimal effort for health-related gains. J Med Internet Res. Mar 12, 2021;23(3):e24905. [FREE Full text] [CrossRef] [Medline]
- Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. Mar 2012;36(1):157-178. [CrossRef]
- Barnett G, Boduszek D, Willmott D. What works to change identity? A rapid evidence assessment of interventions. J Appl Soc Psychol. May 03, 2021;51(7):698-719. [CrossRef]
- Deci EL, Ryan RM. Self-determination theory: a macrotheory of human motivation, development, and health. Can Psychol. 2008;49(3):182-185. [CrossRef]
- Michie S, Ashford S, Sniehotta FF, Dombrowski SU, Bishop A, French DP. A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: the CALO-RE taxonomy. Psychol Health. Nov 2011;26(11):1479-1498. [CrossRef] [Medline]
- Michie S, Hyder N, Walia A, West R. Development of a taxonomy of behaviour change techniques used in individual behavioural support for smoking cessation. Addict Behav. Apr 2011;36(4):315-319. [CrossRef] [Medline]
- Oyserman D. Pathways to Success Through Identity-Based Motivation. Oxford, UK. Oxford University Press; 2015.
- James E, Freund M, Booth A, Duncan MJ, Johnson N, Short CE, et al. Comparative efficacy of simultaneous versus sequential multiple health behavior change interventions among adults: a systematic review of randomised trials. Prev Med. Aug 2016;89:211-223. [CrossRef] [Medline]
- Solbrig L, Whalley B, Kavanagh DJ, May J, Parkin T, Jones R, et al. Functional imagery training versus motivational interviewing for weight loss: a randomised controlled trial of brief individual interventions for overweight and obesity. Int J Obes (Lond). Apr 2019;43(4):883-894. [CrossRef] [Medline]
- Ritchie H, Samborska V, Ahuja N, Ortiz-Ospina E, Roser M. Global education. Our World in Data. URL: https://ourworldindata.org/global-education [accessed 2024-06-28]
- Cao P, Jeon J, Tam J, Fleischer NL, Levy DT, Holford TR, et al. Smoking disparities by level of educational attainment and birth cohort in the U.S. Am J Prev Med. Apr 2023;64(4 Suppl 1):S22-S31. [FREE Full text] [CrossRef] [Medline]
- Ruokolainen O, Härkänen T, Lahti J, Haukkala A, Heliövaara M, Rahkonen O. Association between educational level and smoking cessation in an 11-year follow-up study of a national health survey. Scand J Public Health. Dec 2021;49(8):951-960. [FREE Full text] [CrossRef] [Medline]
- Tomioka K, Kurumatani N, Saeki K. The association between education and smoking prevalence, independent of occupation: a nationally representative survey in Japan. J Epidemiol. Mar 05, 2020;30(3):136-142. [FREE Full text] [CrossRef] [Medline]
- O'Brien HL, Toms EG. The development and evaluation of a survey to measure user engagement. J Am Soc Inf Sci Technol. Dec 09, 2009;61(1):50-69. [CrossRef]
Abbreviations
FSI: future-self intervention |
PA: physical activity |
RM: repeated-measure |
Edited by A Mavragani; submitted 29.07.24; peer-reviewed by H Bhurawala, A Eisingerich; comments to author 10.10.24; revised version received 08.11.24; accepted 07.02.25; published 20.06.25.
Copyright©Kristell M Penfornis, Nele Albers, Willem-Paul Brinkman, Mark A Neerincx, Andrea WM Evers, Winifred A Gebhardt, Eline Meijer. Originally published in JMIR Formative Research (https://formative.jmir.org), 20.06.2025.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.