A Novel Smartphone-Based Intervention Aimed at Increasing Future Orientation via the Future Self: a Pilot Randomized Controlled Trial of a Prototype Application

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Prevention Science
https://doi.org/10.1007/s11121-023-01609-y
A Novel Smartphone‑Based Intervention Aimed atIncreasing Future
Orientation viatheFuture Self: aPilot Randomized Controlled Trial
ofaPrototype Application
EstherC.A.Mertens1· AniekM.Siezenga1,2· JobvanderSchalk1· Jean‑LouisvanGelder1,2
Accepted: 18 October 2023
© The Author(s) 2023
Abstract
We developed and tested a smartphone-based intervention, FutureU, that aims to stimulate future-oriented thinking and
behavior by strengthening the degree to which people identify with their future self. In order to examine the potential of this
intervention prototype and opportunities for further optimization, we evaluated 1) the immediate and long-term efficacy of
the intervention, and 2) intervention effects after each of three intervention modules. To this end, we conducted a randomized
controlled pilot study among first-year university students (N = 176). Results showed a decrease in goal commitment imme-
diately after the intervention. At 3-months follow-up, trends showed an increase in future orientation and in self-efficacy.
During the intervention, there was a positive effect on vividness of the future self after the first module. Although there is
scope for improvement, the findings highlight the potential of the intervention to increase people’s future-oriented thinking
and behavior.
Keywords Future self-identification· Future orientation· Smartphone application intervention· mHealth· Randomized
controlled trial (RCT)· Goal achievement· Positive development· Self-defeating behavior
Introduction
Shortsighted behavior, i.e., favoring immediate gains over
potential future costs, can negatively impact people’s devel-
opment in both the psychological and the social domain
(Steinberg etal., 2009). The preference for immediate grati-
fication often coincides with discounting the future, which
generally results in negative outcomes, such as self-defeating
behavior (e.g., delinquency, substance use, unhealthy life-
style; e.g., Hershfield etal., 2009; Rutchick etal., 2018).
In contrast, considering possible future consequences
when making decisions has been associated with positive
outcomes, such as enhanced self-esteem and goal-directed
behavior (e.g., Schmid etal., 2011; Zimbardo & Boyd,
1999), and refraining from negative behavior (Carmi, 2013).
Despite the positive effects future orientation can have on
one’s development, people generally find it difficult to make
future-oriented choices (Hershfield, 2018). Young people in
particular are typically oriented towards the present, find it
difficult to plan ahead, and struggle to envisage the longer
term consequences of their decisions. This youthful short-
sightedness has been suggested as an underlying cause of
poor and risky decision making (Steinberg etal., 2009).
Therefore, increasing future orientation may decrease nega-
tive behavior and foster positive development.
Existing interventions that address future orientation
often aim to change specific behaviors, such as food pur-
chases (Hollis-Hansen etal., 2020) or academic perfor-
mance (Nurra & Oyserman, 2018). Although an intervention
addressing one specific behavior can be helpful for people
struggling with this exact problem, it misses the opportu-
nity to explicitly cultivate future orientation and related
outcomes in multiple domains, both negative (e.g., self-
defeating behavior) and positive (e.g., self-esteem).
We developed a novel smartphone-based intervention,
FutureU, that aims to stimulate future-oriented thinking and
behavior more broadly. In the present pilot study, we tested
the efficacy of the FutureU smartphone application (app)
* Jean-Louis van Gelder
j.vangelder@csl.mpg.de
1 Institute ofEducation andChild Studies, Leiden University,
Leiden, Netherlands
2 Department ofCriminology, Max Planck Institute
fortheStudy ofCrime, Security andLaw, Freiburg, Germany

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prototype among a relatively young population (i.e., uni-
versity students). That is, we tested intervention effects after
each of three intervention modules, immediately following
the intervention, and at 3-months follow-up, with the inten-
tion of gaining insight into the potential of the intervention
on a broad range of outcomes and opportunities for further
development of the app.
Future Self‑Identification
Preferences in intertemporal decision making have been
viewed as a function of discrepancies between the needs and
wants of a ‘present self’ and those of a ‘future self’ (Frederick
etal., 2002). People are only willing to make choices in
which they prioritize the future over the present when they
identify with their future self (Hershfield, 2018). Such future
self-identification has been argued to depend on the vividness
of the imagined future self, the feelings towards this self,
and the degree of perceived similarity and connectedness
(i.e., relatedness) with it (Bixter etal., 2020). A desire for
immediate gratification and temporal discounting may be
more pronounced when people lack a vivid image of the
future self, feel negatively about their future self, and/or lack
a sense of relatedness to this future self.
Research has related (aspects of) future self-identification,
which is also referred to as future-self continuity (e.g.,
Hershfield, 2011), to behavior in various domains. For
example, increases in vividness of the future self have been
related to reductions in delinquency (Van Gelder etal.,
2015) and other self-defeating behavior (Van Gelder etal.,
2022). Rutchick etal. (2018) have shown that a stronger
sense of relatedness (i.e., similarity and continuity) to the
future self was associated with better subjective health and
with increased exercising. In addition, a stronger sense of
continuity of the future self has been shown to be related to
increased financial savings (Hershfield etal., 2011).
The FutureU intervention is based on the future self-
identification framework. During the intervention, partici-
pants are stimulated to actively contemplate their future
self and discover who this self is. We theorize that by doing
so, participants gain a clearer and more vivid image of the
future and their future self, develop (stronger) positive
feelings towards this future self, and feel more related to
this self. Together, this is assumed to result in a stronger
identification with the future self, which, in turn, increases
future-oriented thinking and behavior.
Mental Time Travel
To increase people’s motivation and drive to consider the
future consequences of their behavior, prior interventions
have implemented Episodic Future Thinking (EFT) – a form
of mental time travel (Suddendorf & Corballis, 2007). EFT
is an intervention technique in which people are asked
to vividly imagine and describe a realistic positive event
or experience that could happen in their personal future
(Hollis-Hansen etal., 2020). This technique builds on
humans’ ability to pre-live events by mentally projecting
themselves to the future which allows them to foresee,
shape, and plan specific future events (Suddendorf &
Corballis, 2007). By simulating the experience of receiving
a larger future reward by deferring an immediate smaller
reward, more farsighted behavior can be motivated (Schacter
etal., 2017). EFT-based interventions have shown positive
effects on specific financial and health related intertemporal
choices (Rösch etal., 2021), such as food purchases (Hollis-
Hansen etal., 2020), impulsive eating (Daniel etal., 2013),
smoking (Stein etal., 2016), and monetary discounting
(Daniel etal., 2013; Stein etal., 2016). The general finding
is that intervention effects become stronger the more
vividly the prospective event is imagined, underscoring
the important role of vividness in EFT (Daniel etal., 2013;
Rösch etal., 2021). We integrated EFT in the FutureU
intervention to bolster a vivid imagination of the future self
and future achievements.
Smartphone‑Based Interventions
Implementing interventions via technology, such as smart-
phone apps, provides unique opportunities compared to
more traditional (face-to-face) interventions. For example,
intervention apps can be programmed to automatically
deliver intervention content and facilitate large-scale imple-
mentation. One major advantage is the possibility of apps
to expose participants to intervention content on a regular
basis. For most people, their smartphone is integrated in
daily routines enabling its use throughout the day wherever
and whenever they want (Linardon etal., 2019; Schoeppe
etal., 2016). To remind users to engage with the app, pre-
programmed push notifications can be sent (Linardon etal.,
2019). Multimedia tools can provide content in different
formats, such as video, audio, text, and graphic illustrations
(e.g., Tielman etal., 2017).
Smartphone-based interventions have been shown to be
effective across a variety of domains, such as mental health
(e.g., internalizing problems, stress, quality of life; Donker
etal., 2022; Linardon etal., 2019) and lifestyle choices (e.g.,
diet, sedentary behavior, physical activity; Fanning etal.,
2017; Schoeppe etal., 2016). These positive effects have
been related to various intervention components of apps. In
their meta-analysis on smartphone-based interventions for
mental health problems, Linardon etal. (2019) showed that
stronger effects were related to the inclusion of push noti-
fications as engagement reminders, supportive messages,

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and personalized feedback. Fanning etal. (2017) in their
randomized factorial trial and Schoeppe etal. (2016) in their
systematic review also showed a positive effect of (perfor-
mance) feedback on intervention effects and found indica-
tions that an integrated goal-setting component was related
to stronger intervention effects. These findings suggest that
these specific components, i.e., push notifications, support-
ive messages, feedback, and goal-setting, may be effective
ingredients of smartphone-based interventions.
The FutureU app contains several components that have
been related to positive intervention effects in previous
studies. More specifically, the FutureU app is designed
for daily use and sends push notifications to remind users
to interact with the app. The app contains a tool to work
towards personal goals (i.e., goal-setting component),
sends personalized messages (e.g., referencing partici-
pants’ personal goals), and provides supportive feedback
(e.g., giving compliments and encouragement). Moreover,
we capitalized on the multimedia possibilities provided by
apps to expose participants to a three-dimensional visual
rendering of their 10-year older future self. This visual
presentation may stimulate the development of a more
vivid image of the future self (McMichael etal., 2022),
which, in turn, plays an important role in both future self-
identification and EFT.
Although implementation of an intervention through
technology, such as smartphone apps, has several advan-
tages, it also comes with the challenge of translating theo-
ries of change (often examined in face-to-face interventions)
into features of the technology (Fairburn & Patel, 2017).
While many studies have focused on translating theories of
change into web-based interventions, translation of theories
into smartphone app features remains largely understudied
(Fairburn & Patel, 2017). Therefore, we not only examined
overall efficacy, but also intervention effects after each inter-
vention module – each of the modules is based on different
theories of change – to assess the degree to which the theo-
ries appeared successfully translated into features of the app.
This knowledge can be used to inform the development of
new intervention apps and identify opportunities for opti-
mization of existing ones, in particular the next iteration of
the FutureU app.
Present Study
The aim of the present pilot study was to evaluate the poten-
tial of a prototype intervention app and identify opportu-
nities for further optimization. To this end, we studied: 1)
the immediate and long-term efficacy of the FutureU app
prototype in stimulating future orientation, decreasing nega-
tive behaviors, and fostering positive development, and 2)
intervention effects after each module, in order to get an
indication of which modules successfully translated theories
of change into technological features. First, we analyzed a
broad range of primary (e.g., future self-identification,
self-defeating behaviors) and secondary (e.g., psychosocial
wellbeing, self-efficacy) outcomes. Second, we focused on
a subsample of behavioral and cognitive outcomes that have
the potential to change over the course of a week (i.e., future
self-identification, self-defeating behavior, psychosocial
wellbeing, weekly goal achievement). Intervention effects
were analyzed in comparison to an active, goal-setting, con-
trol condition in order to examine effects of the app over
and above the potential effects of setting goals (Van Lent &
Souverijn, 2020).
The FutureU intervention was implemented among first-
year university students. This population of relatively young
people was deemed particularly suitable for our purposes
as the transition from high school to university involves
a transformational life event as well as a change of con-
text. During such transitions, people are known to more
often take a ‘big-picture’ view of their life, which makes
it a suitable moment to intervene (Dai etal., 2014). We
hypothesized that the intervention would increase future
orientation and positive development, and decrease nega-
tive behaviors during, immediately after, and three months
after the intervention.
Method
Design andProcedure
The intervention was examined in a Randomized Controlled
Trial (RCT) with two conditions: 1) a smartphone-based
intervention condition, and 2) an active control condition.
Participants were randomly assigned to a condition using
an online number generator and block randomization with
blocks of six on a 1:1 ratio (conducted by AS), meaning
that within a block three participants were allocated to each
condition. See Fig.1 for the flow chart.
Both conditions started out with an intake at the univer-
sity’s lab during which participants gave active informed
consent, completed the baseline questionnaire, and set two
goals. Additionally, participants in the smartphone condition
took a photo of their face (a ‘selfie’), which was digitally
aged and turned into an avatar representing their future self
(see Supplementary materials for details about the soft-
ware used in this process). Subsequently, they installed the
FutureU app on their smartphone.
Participants completed digital questionnaires at baseline
(i.e., during intake; T1), immediately following each of the
three week-long intervention modules (T2 and T3), immedi-
ately after the intervention (T4), and 3months after the end

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of the intervention (T5). In the control condition parallel
timepoints were used. Given that all participants completed
the questionnaires multiple times, potential re-test effects
would appear in both conditions and cannot account for
differences between conditions. Participants received com-
pensation for completing the questionnaires (course credits
or money). Data was collected from October 2021 to June
2022. This trial was approved by the Ethics Board of the
Institute of Education and Child Studies at Leiden University
(ECWP2021-320) and registered in the Netherlands Trial
Register number NL9671 (see Mertens etal., 2022 for the
study protocol).
Fig. 1 Flow chart
Completed post measurement (T4)
n= 84 (97%)
Filled in too late (n= 1)
Completed, but failed attention checks
(n= 14)
Completed follow-up (T5)
n= 73 (84%)
Filled in too late (n= 1)
Completed, but failed attention checks
(n= 7)
Total drop-out (n= 14; 16%)
Non-response (n= 13)
Could not download app (n= 1)
Completed post measurement (T4)
n= 83 (93%)
Filled in too late (n= 5)
Completed, but failed attention checks
(n= 4)

Completed follow-up (T5)
n= 75 (84%)
Filled in too late (n= 2)
Completed, but failed attention checks
(n= 1)
Total drop-out (n= 14; 16%)
Non-response (n= 14)
Randomized (N= 202)
Scheduled intake (N= 202)
Intake intervention condition (T1)
(N= 87)
Intake control condition (T1)
(N= 89)
Experienced app problems, but did not drop
out (n= 10):
Could not download app on own phone
(n= 1)
Problems with avatar creation (n= 3)
Could not transport personality scores
to app (n= 2)
App stopped working (n= 1)
Multiple problems (n= 3)
Drop-out (n= 2):
Could not download app at all (n= 1)
Non-response (n= 1)
Drop-out (n= 1):
Non-response (n= 1)
Canceled intake and did not reschedule (n= 26):
Intervention condition (n= 14)
Control condition (n= 12)

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Participants1
Participants were first-year university students (N = 176)
enrolled at a university in the Netherlands. Most partici-
pants were enrolled in Pedagogical Sciences (57%) or Psy-
chology (38%). Students were on average 19.64years old
(SD = 2.81) and mostly female (n = 155, 88%). There were
no differences between conditions at baseline for age (Inter-
vention Mage = 19.71; Control Mage = 19.21; F(1,174) = 1.39,
p = .240, ηpartial
2 = .008). Conditions did differ on gender dis-
tribution with slightly fewer female participants in the inter-
vention condition than in the control condition (Intervention
82% female; Control condition 94% female; χ2(1) = 8.29,
p = .004, φ = .218). Missing data (6.4% in total) could be
regarded as missing at random (see Supplementary materi-
als for details).
FutureU Intervention Condition
Participants in the FutureU intervention condition started
with an intake during which they set a goal for the coming
month and a goal for the coming year (i.e., a monthly and a
yearly goal). The goal-setting procedure was guided by the
experimenter to ensure that goals followed the SMART-goals
model and Zimmerman’s criteria (Ogbeiwi, 2021) resulting
in specific, measurable, and challenging but attainable goals
– goal characteristics, which are most likely to have a posi-
tive effect on performance (Van Lent & Souverijn, 2020).
Subsequently, participants independently formulated a goal
for the week, intended as a first step towards achieving their
monthly goal, using the SMART criteria. At the end of Week
1 and Week 2 of the intervention, participants independently
set a new goal for the following week.
The general recurring features of the app are an interac-
tion in which users connect with their future self (i.e., a
‘connection mechanic’), a (scripted) chat conversation with
the future self, and push notifications. Participants access the
app via the connection mechanic in which they touch their
future self’s (virtual) finger. This action unblurs the screen
and reveals an image of the future self based on the aged
selfie (see Fig.2A). In the chat (see Fig.2B), participants
‘interact’ with their future self, receive psychoeducation,
answer questions about their future, and receive instruc-
tions for the assignment of that day. Additionally, to keep
the chat interaction engaging, the future self occasionally
makes jokes, uses emojis, and sends funny pictures. The
chat is scripted in such a way that interaction is suggested,
for example, by directly addressing the participants and ask-
ing them multiple choice and open questions (e.g., “Do you
already have an idea about what you can do in the coming
days to achieve your weekly goal?”). The chat is scripted in
such a way that participant responses are inconsequential for
the flow of the chat so that all participants receive identical
intervention content. Furthermore, each day of the interven-
tion participants receive a push notification informing them
that there is a chat message from their future self. In addi-
tion, every other day they receive a push notification with
a general remark by their future self, (e.g., “I heard a good
quote this morning: “Live for today, prepare for tomorrow!”.
Totally us!”).
Intervention Modules
The app is divided into three consecutive, week-long, mod-
ules, each containing core features based on different and
multiple theories of change (see Supplementary materials
TableS1). The different features unlock as participants pro-
gress through the intervention.
Module 1 The aim of the first module is twofold: 1) to
increase vividness, familiarity, and identification with the
future self, and 2) to stimulate thinking about one’s future
circumstances and personality. To this end, participants fill
in a personal profile of their future self, modeled on personal
profile information common on social media. This profile
contains information about demographics (e.g., place of resi-
dence, work experience) as well as information about skills,
accomplishments, and life events. Hence, participants are
encouraged to think about their future life circumstances in
10years. Furthermore, participants receive psychoeduca-
tion about structural models of personality and personal-
ity change via a brief animated video clip embedded in the
chat. In a personality overview screen, they are shown their
own current personality scores (based on the personality
questionnaire they completed at baseline) and norm scores.
Subsequently, they can indicate what their desired score of
their future self would be on these dimensions (see Fig.2C).
Module 2 The second module aims to stimulate future-
oriented decision-making and changing attitudes and behav-
ior in favor of the future self by practicing with temporally
distanced perspective taking. Participants are presented with
a short animated video providing psychoeducation about
psychological and temporal distanced decision-making.
They then practice temporally distanced perspective taking
in a ‘time travel portal’. In this portal, they see their future
self on screen, ostensibly at the other side of the portal. They
1 There was a COVID-19 related lockdown during data collec-
tion. To examine the potential effect of this lockdown, participants
included before (n = 119) and after (n = 57) the lockdown were com-
pared at baseline. We found no significant differences on either demo-
graphic or on the outcome variables, except for relatedness towards
the future self (F(1,174) = 4.14, p = .043, η2
partial = .023). Participants
included after the lockdown reported higher levels of relatedness at
baseline than participants included before the lockdown. As only one
significant difference with low relevance was found, we did not con-
trol for the lockdown in the analyses.

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first address their future self in third person to explain an
issue they are facing in their daily life (this is recorded by the
app). Subsequently, they ‘time travel’ and switch to the per-
spective of their future self, and now face their present self.
They are presented with their own recording, and provide
feedback. Participants switch perspectives multiple times
during each session (see Fig.2D).
Module 3 This module focuses on growth mindsets
(Dweck & Yeager, 2019) and how to set and achieve chal-
lenging goals. In two separate animated videos, participants
learn about the purpose and nature of growth mindsets, and
how Mental Contrasting and Implementation Intentions
(MCII; Oettingen & Gollwitzer, 2010) can be applied when
working towards goals. Participants practice with MCII by
following its steps for their personal goals, which are saved
in the app (see Fig.2E).
Treatment Adherence
The FutureU app is developed for daily use for three con-
secutive weeks (i.e., 21days) for approximately 5min or
less each day. Eight (9.20%) participants used the FutureU
app every day during the intervention period and 32
(36.78%) participants almost every day (check-in range = 16
– 20days). In contrast, 11 (12.64%) participants used the
app only a few days (check-in range = 2 – 8days). In total,
10 (11.49%) participants experienced technical problems
with the app and 1 (1.15%) participant could not download
the app. Most participants checked-in at least once dur-
ing Module 1 (n = 86, 98.85%), during Module 2 (n = 82,
94.25%), and during Module 3 (n = 78, 89.66%). On aver-
age, participants used the app for 14days (SD = 4.73;
Median = 15days) with check-in sessions lasting on average
A) B) C)
D) E)
Fig. 2 FutureU application screenshots of A Connection Mechanic, B Chat, C Personal Profile and Personality Menus, D Time Travel Portal,
and E MCII Goal Schema

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4.39min (SD = 1.71) per day. Generally, treatment adher-
ence was moderate.
Control Condition
During intake, participants in the control condition fol-
lowed the same procedure as participants in the interven-
tion condition – i.e., setting a goal for the month, a goal
for the year, and a goal for that week. As in the interven-
tion condition, participants independently formulated a
new goal for the coming week at the end of each week.
In contrast to the intervention condition, participants in
the control condition did not receive further support while
working towards their goals.
Measurements
Primary Outcomes
Future Self-Identification The degree to which people
identified with their future self was assessed with three
subscales. All three subscales were assessed before, dur-
ing, immediately after the intervention, and at 3-months
follow-up.
Vividness Vividness measured the extent to which people
had a clear and vivid image of their future self (based on Van
Gelder etal., 2015). The scale consisted of 5 items (e.g.,
“I have a clear image of myself in 10years.”) answered on
a 7-point Likert scale (1 = completely disagree to 7 = com-
pletely agree; α = .92 – .95).
Valence Valence measured participants’ feelings towards
the future self (based on Hershfield etal., 2009) and con-
sisted of 1 item (“How do you feel when you think about
your future?”). This item was answered on a 9-point scale
ranging from negative to positive feelings with the Self-
Assessment Manikin (Bradley & Lang, 1994).
Relatedness Relatedness measured the degree to which
people felt connected to and similar to their future self. This
was assessed with the 2-item Future Self-Continuity Meas-
ure (Hershfield etal., 2009). Both items were answered on a
7-point scale marked by pairs of circles that increase in over-
lap. The more circles overlap, the more connected or similar
participants felt to their future self in 10years (α = .57 – .83).
Future Orientation Future orientation was measured
with the Future Orientation Scale (Steinberg etal., 2009),
which assesses time perspective, anticipation of future con-
sequences, and planning ahead. The questionnaire consists
of 15 items with two pairs of opposite statements (e.g.,
“Some people spend very little time thinking about how
things might be in the future, but other people spend a lot
of time thinking about how things might be in the future.”).
Participants were instructed to choose the statement that best
described them and indicated whether that description was
completely true or a little bit true. When the present-oriented
description was chosen, a score of 1 (= completely true) or
2 (= a little bit true) was given. When the future-oriented
description was chosen, a score of 3 (= a little bit true) or 4
(= completely true) was given (α = .84–.85).
Self-Defeating Behaviors Behaviors with immediate
gains though potential long-term costs were assessed with
16 items, based on Van Gelder etal. (2015), measuring
self-defeating behaviors (e.g., “How often in the last week
have you missed classes or work?”). Items were rated on
a 5-point Likert type scale (1 = never to 5 = more than 10
times). Subsequently, responses were dichotomized into 0
(= never) and 1 (= at least once) for each item and summed
to form one scale (α = .50–.62). This concept was measured
before, during, immediately after the intervention, and at
3-months follow-up.
Goal Achievement Goal achievement was measured with
3 items developed specifically for this study. Participants
indicated to what extent they had thought about their goal,
had worked towards their goal, and had achieved their goal,
on a 5-point Likert scale (1 = completely disagree to 5 = com-
pletely agree). Goal achievement regarding the weekly goal
was measured during and immediately after the intervention
(Weekly goal achievement α = .67–.82). Goal achievement
regarding the monthly goal was measured immediately after
the intervention and at 3-months follow-up (Monthly goal
achievement T4 α = .76, T5 α = .80).
Goal Commitment Goal commitment was assessed with
the Goal Commitment Questionnaire (Hollenbeck etal.,
1989). This questionnaire consists of 7 items (e.g., “I think
this goal is a good goal to shoot for.”) answered on a 7-point
Likert scale (1 = completely disagree to 7 = completely
agree; α = .60–.86).
Impulsiveness Impulsiveness was measured with the
Barratt Impulsiveness Scale short form, which assesses
non-planning, motor impulsivity, and attentional impulsivity
(Spinella, 2007). The questionnaire contains 15 items (e.g.,
“I do things without thinking.”) answered on a 4-point Lik-
ert scale (1 = completely disagree to 4 = completely agree;
α = .85–.86).
Secondary Outcomes
Psychosocial Wellbeing.Participants’ positive mental health
was measured with the Warwick-Edinburgh Mental Well-
being scale (Tennant etal., 2007) at baseline, immediately
after the intervention, and at 3-months follow-up. This ques-
tionnaire consists of 14 items (e.g., “How often in the last
week did you feel relaxed?”) answered on a 5-point Likert-
type scale (1 = never to 5 = always; α = .87–.91). For the
interim measurements, the short version (7 items; Ng Fat
etal., 2017) was used (T2 α = .79; T3 α = .81).

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Self-Efficacy Self-efficacy, i.e., sense of competence to
effectively deal with stressors of life, was assessed with the Gen-
eral Self-efficacy Questionnaire (Schwarzer & Jerusalem, 1995).
The questionnaire consists of 10 items (e.g., “I can always man-
age to solve difficult problems if I try hard enough.”) answered
on a 4-point Likert scale (1 = completely disagree to 4 = com-
pletely agree; α = .76–.83).
Self-Esteem Global self-esteem was measured with
the Rosenberg Self-esteem Scale (Rosenberg, 1965). The
questionnaire contains 10 items (e.g., “On the whole, I
am satisfied with myself.”) answered on a 4-point Likert
scale (1 = completely disagree to 4 = completely agree;
α = .85–.88).
Academic Achievement The averaged academic result at
the end of the first academic year was obtained from univer-
sity records in August, i.e., the end of the academic year. In
the Dutch education system scores range from 1 through 10
in which higher scores represent better results.
Analyses
We used an intention-to-treat approach, implying that all
participants who participated at baseline were included in
the analyses regardless of whether they received the inter-
vention or not. Missing data were estimated through Full
Information Maximum Likelihood (FIML) procedures. The
data were analyzed per outcome using autoregressive path
models in R with the LAVAAN package (Rosseel, 2012).
The outcome variable at each time point was regressed on
the corresponding outcome variable of the previous time
point. Additionally, the outcome variables at all time points
were separately regressed on the dummy variable repre-
senting condition, with the control condition as reference
group (including the outcome variable at baseline in order
to control for initial difference between the conditions on the
concerned outcome; see Fig.S1 Supplementary materials).
Given that the main goal of the present study was to evaluate
the potential of the FutureU app for establishing interven-
tion effects and to identify opportunities to further develop
the app, we highlight significant effects (p ≤ .050) as well
as effects showing a trend towards significance (p ≤ .100).
For each time point and outcome variable, effect sizes
were calculated as Cohen’s d with the baseline measurement
as reference point (Cohen’s d = (Mchange intervention / SDpooled)
– (Mchange control / SDpooled)). For variables without a baseline
measurement (i.e., weekly goal achievement, monthly goal
achievement, and academic results), effect sizes were cal-
culated without baseline correction (Feingold, 2013). Effect
sizes were calculated so that positive effect sizes indicated
changes in the desired direction, that is, an increase for posi-
tive outcomes and a decrease for negative outcomes.
Effects established during or immediately after the inter-
vention were analyzed in more detail, whenever possible
(i.e., when interim measurements of the concerned outcome
were available), by examining indirect effects via previous
time points. This provided an indication of whether the
effect after a certain module was mediated by the effect of
an other module. Sensitivity analyses were conducted to test
the robustness of the results (see Supplementary materials).
Results
Descriptive statistics of the proximal and distal outcomes
at baseline, during the intervention, immediately after the
intervention, and at 3-months follow-up are presented per
condition in Table1.
Efficacy FutureU
Results from autoregressive path models are presented in
Table2. Immediately after the intervention, there was a large
negative intervention effect (d = -.68) on yearly goal com-
mitment. Participants in the intervention condition decreased
more strongly on commitment to their yearly goal than par-
ticipants in the control condition. At follow-up, there was
no intervention effect, meaning that goal commitment of
participants in the intervention condition did not decrease
further after T4 compared to participants in the control con-
dition. However, the difference between the two conditions
compared to baseline remained relevant (d = -.64).
At 3-months follow-up, there were trends towards signifi-
cant positive intervention effects on future orientation and
on self-efficacy. In both conditions, the observed scores of
future orientation decreased immediately after the interven-
tion. However, at follow-up, participants in the intervention
condition showed a small increase in future orientation com-
pared to baseline, whereas participants in the control con-
dition still reported a small decrease on this outcome. The
intervention effect (d = .09) was small based on the criteria
of Cohen as well as based on the mean effect size distribu-
tions of universal interventions (Tanner-Smith etal., 2018).
On self-efficacy, participants in the intervention condition
seemed to improve slightly more than participants in the
control condition. This effect (d = .12) would be interpreted
as small based on Cohen’s criteria, though small to moder-
ated based on the mean effect size distributions of universal
interventions targeting self-concept outcomes (25th percen-
tile d = .06 and 50th percentile d = .17; Tanner-Smith etal.,
2018).
Intervention Effects After Each Module
After the first module, a positive effect on vividness of the
future self emerged. Participants in the intervention condi-
tion had a clearer and more vivid image of their future self

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Table 1 Descriptive statistics (M and SD) of the proximal and distal outcomes at baseline, during the intervention, immediately after the intervention, and at three months follow-up per condi-
tion
T1 = Baseline, T2 and T3 = Interim measurements, T4 = Post measurement, T5 = 3-Months follow-up
Intervention condition Control condition
T1 T2 T3 T4 T5 T1 T2 T3 T4 T5
M (SD)M (SD)M (SD)M (SD)M (SD)M (SD)M (SD)M (SD)M (SD)M (SD)
Proximal outcomes
Future self-identification
Vividness 3.24 (1.49) 3.83 (1.31) 3.95 (1.42) 3.83 (1.45) 3.68 (1.46) 3.50 (1.42) 3.77 (1.34) 3.82 (1.38) 3.77 (1.36) 3.64 (1.39)
Valence 6.59 (1.62) 6.49 (1.29) 6.39 (1.29) 6.45 (1.35) 6.37 (1.47) 6.73 (1.14) 6.61 (1.26) 6.51 (1.14) 6.59 (1.18) 6.62 (1.10)
Relatedness 3.76 (1.11) 3.83 (1.11) 4.05 (1.07) 4.16 (1.07) 4.11 (1.23) 3.94 (1.03) 3.95 (1.06) 4.08 (0.99) 4.20 (1.10) 4.13 (1.06)
Future orientation 2.95 (0.53) 2.86 (0.53) 2.98 (0.54) 3.11 (0.53) 3.08 (0.49) 3.09 (0.47)
Self-defeating behavior 4.89 (1.73) 4.39 (1.82) 4.31 (1.83) 3.77 (2.25) 4.78 (2.27) 4.16 (1.78) 3.81 (1.77) 3.65 (1.93) 3.52 (1.96) 4.53 (1.85)
Weekly goal achievement 3.42 (0.79) 3.23 (0.92) 3.47 (0.86) 3.39 (0.76) 3.36 (0.80) 3.38 (0.96)
Monthly goal achievement 3.41 (0.83) 3.29 (0.91) 3.38 (0.96) 3.25 (0.99)
Yearly goal commitment 5.96 (0.54) 5.34 (0.88) 5.28 (1.17) 6.05 (0.58) 5.81 (0.74) 5.73 (0.84)
Impulsiveness 2.22 (0.40) 2.22 (0.35) 2.19 (0.41) 2.14 (0.43) 2.14 (0.44) 2.12 (0.40)
Distal outcomes
Psychosocial wellbeing 3.57 (0.51) 3.53 (0.52) 3.43 (0.55) 3.56 (0.52) 3.46 (0.59) 3.55 (0.48) 3.59 (0.45) 3.54 (0.49) 3.60 (0.48) 3.61 (0.41)
Self-efficacy 2.93 (0.35) 2.97 (0.34) 2.99 (0.39) 2.85 (0.32) 2.88 (0.32) 2.87 (0.36)
Self-esteem 2.86 (0.46) 2.84 (0.47) 2.79 (0.51) 2.85 (0.41) 2.83 (0.45) 2.88 (0.44)
Academic achievement 7.26 (0.65) 7.18 (0.70)

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Table 2 Estimated regression coefficients of the outcomes per time point regressed on condition in the autoregressive path models and effect sizes per outcome and time point
Significant findings emphasized in bold, Trend towards significant findings emphasized in bold italics, T1 = Baseline, T2 and T3 = Interim measurements, T4 = Post measurement,
T5 = 3-Months follow-up, Only a subsample of outcomes was assessed at interim measurements, Positive effect sizes indicate changes in the desired direction (i.e., an increase in positive out-
comes and a decrease in negative outcomes)
a Variable had no baseline so Cohen’s d is calculated without baseline correction
T1 T2 T3 T4 T5 Cohen’s d
B(SE)p B(SE)p B(SE)p B(SE)p B(SE)pT1-T2 T1-T3 T1-T4 T1-T5
Proximal outcomes
 Future self-identification
  Vividness -.26(.22) .242 .27(.13) .040 .01(.11) .931 -.01(.11) .897 -.01(.16) .965 .22 .27 .22 .21
 Valence -.14(.21) .492 -.03(.14) .834 -.07(.12) .584 -.08(.15) .590 -.08(.16) .621 .01 .01 .00 -.08
 Relatedness -.19(.16) .249 .04(.12) .723 -.02(.10) .816 .04(.10) .687 -03(.14) .817 .06 .14 .13 .15
 Future orientation -.17(.08) .036 -.06(.04) .164 .07(.04) .072 -.11 .09
Self-defeating behavior .73(.26) .006 .11(.22) .610 .30(.22) .175 -.30(.25) .227 .09(.28) .746 .08 .04 .27 .27
Weekly goal achievement1.02(.12) .838 -.15(.12) .211 .12(.13) .373 .04 -.15 .10
Monthly goal achievement1-.05(.12) .697 .07(.14) .594 .04 .04
Yearly goal commitment -.10(.08) .255 -.36(.11) .001 -.09(.14) .523 -.68 -.64
Impulsiveness .08(.06) .199 .02(.03) .633 -.02(.04) .665 .00 -.02
Distal outcomes
Psychosocial wellbeing .01(.07) .864 -.09(.05) .102 -.06(.06) .290 .01(.06) .904 -.10(.07) .155 -.16 -.27 -.12 -.35
Self-efficacy .08(.05) .101 .02(.04) .659 .09(.05) .078 .03 .12
Self-esteem .01(.07) .888 -.02(.04) .570 -.06(.05) .261 .00 -.23
Academic achievementa.08(.10) .464 .12

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than participants in the control condition. The effect size
(d = .22) was small based on the criteria of Cohen, but mod-
erate based on the mean effect size distribution of universal
interventions targeting self-concept outcomes (50th percen-
tile d = .17; Tanner-Smith etal., 2018). No other effects
emerged on the other outcomes during the intervention (see
Table2).
Discussion
As the integration of technology, in particular smartphone
apps, in interventions is growing, there is a need for evi-
dence-based intervention apps and knowledge about effec-
tive translation of theories of change into technological fea-
tures. The present study evaluated a prototype of the FutureU
app. Our purpose was, firstly, to investigate the potential of
this specific intervention app to generate intervention effects
and, secondly, to examine whether the modules successfully
translated theories of change into app features. Our results
indicated both negative and positive intervention effects.
More specifically, there was a large negative effect on goal
commitment immediately after the intervention, which
remained relevant at follow-up. Furthermore, there were
small to moderate positive effects on vividness of the future
self (after the first intervention module), future orientation
(at follow-up), and self-efficacy (at follow-up). We conclude
from these findings that the FutureU app has potential, but
also that there is a need to 1) further develop and optimize
it, and 2) examine its potential among other populations than
university students.
The negative effect on goal commitment could potentially
be explained by imagination of the future self as well as by
the study design. When participants set their goal for the
year, they may have fantasized about their desired future
and did not consider their expectations of success, thus the
feasibility of the goal, when setting it. During the interven-
tion, they were asked to imagine their future when their goal
is obtained and subsequently identify which obstacles cur-
rently stand in their way of obtaining this goal (i.e., MCII
used in module 3 of the intervention), posing to themselves
the question whether their desired future can be realized.
For some participants this may have triggered the thought
that their goal is not attainable, which may have reduced
their motivation to pursue this goal and, as a consequence,
they may have lost their commitment to it (Oettingen etal.,
2005). Another explanation relates to the design of the study.
Participants set a goal for the year at the start of the inter-
vention and reported their commitment to this goal over a
period of time. During the intervention participants con-
templated their future and who they want to be(come). This
contemplation may have affected the way they think about
their future self and clarified their vision of the future. Given
that the way people think about and identify with their future
self can affect their personal goals (Peetz & Wilson, 2008),
participants’ goals may have changed during the interven-
tion, resulting in reduced commitment to their previously
set goals. To test this hypothesis, future research could focus
on potential changes in long-term goals during and after an
intervention aimed at stimulating future orientation.
The (trend towards) positive effects on vividness of the
future self, future orientation, and self-efficacy signal the
potential of the FutureU app. In particular, the effects on
vividness and future orientation are promising as these are
key outcomes of the intervention. Vividness plays an impor-
tant role in both future self-identification and EFT (Rösch
etal., 2021) and was hypothesized to play a pivotal role in
establishing intervention effects. The increase in future ori-
entation, albeit modest, implies that, after interacting with (a
representation of) the future self, participants became more
willing to give up something in the present to obtain benefits
in the future, thought more about future consequences of
their actions, and made more plans for the future (Steinberg
etal., 2009) – characteristics of future-oriented thinking.
Taken together, our findings seem to support the theo-
retical framework of the FutureU intervention: Creating a
vivid and clear vision of the future self can increase people’s
propensity to favor the needs and wants of the future self
over those of the present self. In the same line of reasoning,
as people’s identification with their future self strengthens,
they may also see the future self as a role model who suc-
cessfully overcame obstacles in life, which, in turn, increases
feelings of competence to effectively deal with stressors,
i.e., self-efficacy (Scholz etal., 2002). The next step for
future research is to test these potential mechanisms by ana-
lyzing whether vividness of the future self and future self-
identification function as mediators in the intervention for
cultivating future orientation and self-efficacy.
The effect on vividness of the future self emerged after
the first intervention module, which tentatively suggests
that the theories of change used in this module were suc-
cessfully translated into technological features. Perhaps the
intervention can be optimized by incorporating features of
the first module into the other two modules or by referring
back to the first module’s features in the other modules. The
first module was based on theories about exposure to the
future self (McMichael etal., 2022) and personality change
over time (Thielmann & De Vries, 2021; Yeager, 2017). We
translated these theories into app features by creating an ava-
tar of the future self, presenting an animated video clip with
psychoeducation about personality, and having participants
fill out both a personal profile and a personality profile of
their future self. It remains to be determined whether the
effect on vividness was established by all these features in
conjunction or only by a subset of these features. For future
research, it would be interesting to test the effectiveness of

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the app features used in the first module separately in order
to unravel which features were (particularly) effective. This
could also further inform intervention theory, translation of
theory into technology, and the development of other inter-
vention apps.
Strengths andLimitations
The findings of the present study should be interpreted in
light of several strengths and limitations. First, prior to con-
ducting this pilot RCT, the app had been thoroughly user-
tested and iterated on the basis of informal small-scale pilot
studies (see Mertens etal., 2022). Other strengths are the
relatively large sample size and multiple measurement points
allowing us to evaluate the intervention effects in detail.
A limitation of the study is that the sample consisted
solely of university students who were mainly female.
Although we specifically targeted this population of rela-
tively young people, it limits the generalizability of our find-
ings to other populations. Additionally, students received
compensation for their participation in the study. Even
though the compensation regarded completion of the ques-
tionnaires and not engagement with the intervention or for
achieving goals, this may nevertheless have affected our
results. Furthermore, as each intervention module was based
on multiple theories of change that were translated into mul-
tiple technological features, we were unable to unravel the
specific feature or (combination of) features that established
the intervention effects after a module. In addition, not all
outcomes could be assessed during the intervention, since
we focused on outcomes that could reasonably change within
a week. This limited our ability to analyze and explain the
negative intervention effect on goal commitment after the
intervention. It would be interesting for future research to
examine whether this effect was related to specific interven-
tion modules or whether it may have had an other explana-
tion such as changed goals.
Conclusion
In conclusion, the FutureU app prototype carries promise
for stimulating young people’s future orientation, though
further iterations are necessary to boost intervention effects.
The positive intervention effects were in line with the future
self-framework on which the intervention is based. The next
step is to further develop the FutureU app, examine its work-
ing mechanisms, and test it among different populations.
Furthermore, our findings suggest that our attempt to trans-
late theories of exposure to the future self and personality
change over time into technological features was successful
as vividness of the future self increased after the module
based on these theories. Our study constitutes a first step
into studying how theories of change addressing vividness
of the future self can be translated into smartphone app fea-
tures. This knowledge can be used for the development of
smartphone-based interventions focusing on a broad range
of outcomes, as future self-identification has been shown
to be relevant for various domains, including delinquency,
lifestyle, and savings.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s11121- 023- 01609-y.
Acknowledgements The authors thank Orb Amsterdam (www.
orbam sterd am. com) for programming the FutureU app and their
helpful suggestions.
Authors’ Contributions JLvG obtained funding for the study and con-
ceptualized the intervention. All authors contributed to the intervention
content and study design. EM wrote the draft of the manuscript. All
authors critically revised the manuscript. All authors read and approved
the final manuscript.
Funding The study is financially supported by the ERC Consolidator
Grant (Grant Number 772911-CRIMETIME).
Availability of Data and Materials Data that support the findings of
this study are openly available in the Center for Open Science Online
Supporting Information at https:// osf. io/ 9jbrp/
Declarations
Ethics Approval This study was performed in line with the principles
of the Declaration of Helsinki. Ethical approval for conducting this
RCT is obtained from the independent Ethics Board of the Institute of
Education and Child Studies at Leiden University (ECPW2021-320).
Clinical Trial Registration The trial is registered in the Netherlands Trial
Register (number: NL9671) on 16 August 2021.
Consent to Participate Informed consent was obtained from all indi-
vidual participants included in the study.
Competing Interests The authors declare that they have no competing
interests.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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