# Designing for Sustained Motivation: A Review of Self-Determination Theory in
Behaviour Change Technologies

Lize Alberts<EMAIL_ADDRESS>Department of Computer Science,
University of OxfordOxfordUK Department of Philosophy, Stellenbosch
UniversityStellenboschZA ,  Ulrik Lyngs<EMAIL_ADDRESS>Department of
Computer Science, University of OxfordOxfordUK and  Kai Lukoff
<EMAIL_ADDRESS>Department of Computer Science and Engineering, Santa Clara
UniversitySanta ClaraCaliforniaUSA

###### Abstract.

Recent years have seen a surge in applications and technologies aimed at
motivating users to achieve personal goals and improve their wellbeing.
However, these often fail to promote long-term behaviour change, and sometimes
even backfire. We consider how self-determination theory (SDT), a metatheory
of human motivation and wellbeing, can help explain why such technologies
fail, and how they may better help users internalise the motivation behind
their goals and make enduring changes in their behaviour. In this work, we
systematically reviewed 15 papers in the ACM Digital Library that apply SDT to
the design of behaviour change technologies (BCTs). We identified 50
suggestions for design features in BCTs, grounded in SDT, that researchers
have applied to enhance user motivation. However, we find that SDT is often
leveraged to optimise engagement with the technology itself rather than with
the targeted behaviour change per se. When interpreted through the lens of
SDT, the implication is that BCTs may fail to cultivate sustained changes in
behaviour, as users’ motivation depends on their enjoyment of the
intervention, which may wane over time. An underexplored opportunity remains
for designers to leverage SDT to support users to internalise the ultimate
goals and value of certain behaviour changes, enhancing their motivation to
sustain these changes in the long term.

Self-Determination Theory, Behaviour Change Technologies, Persuasive
Technologies, Motivational Technologies, mHealth, Digital Commitment Devices,
Wellbeing, Motivation

††copyright: none††price:

##  1\. Introduction

In recent years, there has been a surge in applications (e.g., Duolingo, Calm,
Forest), browser extensions (e.g., Newsfeed Eradicator), and other
technologies (e.g., wearables like FitBit) that are designed to help users
bring about positive behavioural changes in their lives, including losing
weight, gaining new skills, quitting addictions, or developing mindfulness.
These are sometimes referred to under the broader class of persuasive
technologies (Sundar et al., 2012), or the narrower behaviour change apps
(Villalobos-Zúñiga et al., 2021) or mobile health (mHealth) technologies
(Molina et al., 2023). In this paper, we use the term behaviour change
technologies (BCTs) from Hekler et al. (Hekler et al., 2013) to refer to “the
broad array of systems and artifacts developed to foster and assist behavior
change and sustainment” (Hekler et al., 2013, p.3308). These technologies
employ a range of techniques and features (e.g. reminders, rewards,
performance tracking) to motivate, persuade, nudge and otherwise support users
in performing or avoiding certain behaviours.

As of 2021, there are around 350k mHealth (including medical, fitness, and
mental health) apps hosted across different app stores (GVR, 2021), and over
500M people use these to monitor and/or regulate their daily activities
(Villalobos-Zúñiga et al., 2021). Of those, around 55K apps are currently
available on Google Play and 41K on the Apple App Store (with numbers peaking
around the pandemic) (Mikulic, 2022). Other major categories of BCTs include
education apps that motivate learning (which make up the third biggest sector
in the Apple App Store (Curry, 2021)), and digital self-control tools (DSCTs)
like apps or browser extensions that help millions of people limit unwanted
time spent on their devices or online (Lyngs et al., 2019).

However, despite their popularity, BCTs often fail to help individuals bring
about the intended positive changes in the long term (Mustafa et al., 2022;
Harrison et al., 2015). For example, a recent study found that about 53% of
mHealth apps were uninstalled within 30 days of download (Mustafa et al.,
2022). In surveys, aside from lack of desired features, boredom and loss of
motivation are often reported as reasons for behaviour change app abandonment
(Honary et al., 2019). This suggests that initial use is driven by a novelty
effect, but that these technologies lack reliable ways to motivate sustained
use (Mustafa et al., 2022; Schmidt-Kraepelin et al., 2019; Tsay et al., 2020).

Another factor is the severity of enforcement or degree of friction that a BCT
uses to hold users accountable to their goal (Cox et al., 2016; Kim et al.,
2019): too weak and it might be too easy for the user to circumvent the
intervention (e.g., ignoring a reminder sent by the app), too strong and it
might trigger frustration and lead them to abandon the tool completely (e.g.,
blocking a user’s smartphone after a daily usage limit has been hit, with no
override option) (Lukoff et al., 2022). Thus, work on BCTs for helping people
reduce time on distracting websites has found that people typically begin by
setting themselves highly challenging interventions, but often reject
enforcement at the moment of temptation and slip into easier interventions
(Kovacs et al., 2021).

In some cases, a BCT can even backfire, causing the opposite behaviour to what
was intended (e.g. (Lyngs et al., 2020; Erskine et al., 2010; Stibe and
Cugelman, 2016)).111For example, in a study of goal reminders for supporting
self-regulated Facebook use, a participant said the intrusiveness of the
intervention made her want to “stay on just out of spite” (Lyngs et al.,
2020). Such responses could be understood as manifestations of psychological
reactance (Fitzsimons and Lehmann, 2004; McAlaney et al., 2020): unpleasant
motivational arousal to situations that threaten certain behavioural freedoms.
This reactance222A.k.a the “boomerang effect,” or more colloquially, the
“screw you, don’t tell me what to do” effect (Isaac, 2021). may result in
“behavioural backlash,” when a person not only fails to comply with
expectations, but intentionally contradicts them (Fitzsimons and Lehmann,
2004).

Another contributing factor may be the goals and metrics that designers use to
evaluate the success of BCTs. For designers, a primary concern tends to be
maximising engagement with the app, which is not only a straightforward way to
measure success, but is typically also in the interest of the app developer.
In a recent survey of BCTs on the Apple App Store, Villalobos-Zúñiga and
Cherubini (Villalobos-Zúñiga and Cherubini, 2020) found that reminders are the
most popular feature apps use to motivate people to keep to their goals. They
maintain that it is likely overused for specifically that reason: to keep
users returning to the app. As such, more effort may be spent on maximising
engagement with the technology than on facilitating sustained behaviour
change.

This raises some important questions for the design of BCTs, namely: How can
BCTs support sustained behaviour change? How can BCTs help regulate behaviour
without making users feel their autonomy is threatened? What metrics of
success can be used to evaluate user benefit? In this paper, we explore how
self-determination theory (SDT), an evidence-based theory of human motivation,
growth, and wellbeing (Deci and Ryan, 1985; Ryan and Deci, 2000a, b), can be
leveraged to help answer such questions.

SDT has emerged as among the most researched and applied theoretical framework
of human motivation in psychology today (Ryan et al., 2022). It has been
actively and increasingly examined for over four decades, with many of its
central tenets repeatedly evaluated in meta-analyses (Ryan et al., 2022;
Gillison et al., 2019; Ntoumanis et al., 2021). This strong interest in the
theory is partly attributable to its relatively unique focus on the importance
of human autonomy and volition: how environmental factors can either support
or undermine a person’s ability to willingly and proactively pursue a
behaviour in an enduring way (Ryan et al., 2022).

SDT proposes specific factors that affect people’s ability to develop and
sustain motivation for specific behaviours, decreasing their dependence on
support from external sources. On a basic level, the theory maintains that
sources of motivation can be more or less internal (coming from the
individual’s inherent desires to perform the activity) or external (coming
from outside the individual, like fears or rewards or senses of obligation).
According to SDT, whilst interventions based on extrinsic forms of motivation
may work in the short term, they typically fail to sustain motivation in the
long term, or after an intervention has ended (Deci and Ryan, 1985).
Conversely, when motivation becomes internalised, actions can become self-
determined, at which point interventions may no longer be needed, and changes
in behaviour tend to persist (Ryan and Deci, 2017). A major opportunity for
BCTs is to leverage SDT to change the nature of the scaffolding mechanisms
towards more internal regulation of motivation. That is, to help people
internalise the values and goals of the intervention such that they feel less
like it is something they have to do, but rather, something they do
voluntarily as they find it intrinsically enjoyable and/or personally
meaningful. According to subtheories within SDT, this change is facilitated by
the relevant satisfaction of three basic psychological needs (BPNs) that all
humans seem to have: needs for a sense of autonomy, competence, and
relatedness. These need satisfactions provide the essential nutrients for
energising more autonomous forms of regulation, which SDT posits as necessary
mechanisms that underlie long-term changes in behaviour (Ryan and Deci, 2017;
Gillison et al., 2019). By setting out these mechanisms, SDT provides a
framework for developing behaviour interventions, and proposes techniques for
influencing its constructs (Fortier et al., 2012; Gillison et al., 2019;
Ntoumanis et al., 2021; Ryan et al., 2022).

There is strong evidence for the efficacy of SDT-based interventions across
various domains.333This includes physical activity (Edmunds et al., 2008;
Wilson et al., 2006), environmental behaviours (Pelletier and Sharp, 2008),
tobacco addiction (Williams et al., 2009), and healthcare treatment adherence
(Williams et al., 2004)—see (Gillison et al., 2019; Ntoumanis et al., 2021;
Ryan et al., 2022) for meta-analyses of SDT-based intervention studies. As
such, HCI researchers have started to highlight the utility of incorporating
SDT constructs in interface design, and what it may mean to support these
basic needs at different stages of technology adoption (Ballou et al., 2022a;
Peters et al., 2018). For BCTs in particular, a handful of HCI papers have
started to consider how these needs may be supported with design features. To
evaluate how this has been done and what gaps remain for future work,
particularly towards supporting sustained behaviour change, we surveyed
publications in flagship HCI venues with the following research questions:

> (RQ1) Which of SDT’s theories have HCI researchers applied to the design of
> behaviour change technologies?
> (RQ2) What reasons were given for the application of SDT?
> (RQ3) How have SDT-related constructs been translated into design features?
>

For this, we systematically reviewed all papers in the ACM Digital Library
that mention SDT in the abstract, including in our analysis any that apply the
theory towards the design of technologies that have the purpose of helping
individuals change their behaviour in some personally desired way. We drew
inspiration from Tyack and Mekler’s (Tyack and Mekler, 2020) recent review of
how SDT has been applied in HCI in the context of gameplay, which highlights
conceptual gaps and limitations, as well as opportunities for applying the
theory in that space.

Given the breadth of application domains and aims of BCTs, we also consider a
fourth question:

> (RQ4) What contextual factors need to be considered to evaluate whether
> these design features are suitable for different BCTs?

Across the 15 papers we reviewed, we identified 50 design suggestions: 11 for
supporting ‘autonomy’, 22 for ‘competence’, and 17 for ‘relatedness’. We also
identified some common inconsistencies between the broader aims and purpose of
the constructs, as defined by SDT, and how it was translated into design.
Despite SDT’s central aim of supporting integrated forms of motivation, we
found that BCTs tend to utilise it more for the sake of making the technology
as inherently engaging and satisfying as possible, than for offering
scaffolding, information and support for helping users internalise the target
behaviour per se. Whilst most papers consider how to support the basic
psychological needs that SDT postulates (often through gamification tactics
that make doing the tasks more enjoyable), few consider how to help users
internalise the deeper value of the behaviour change and bring it into
congruence with their other goals and values, such that they are intrinsically
motivated to keep pursuing the target behaviours when the intervention ends.

By fostering further reliance on extrinsic forms of motivation, these
technologies are only able to sustain behaviour changes as long as users find
the technology enjoyable and satisfying, which holds several risks. Firstly,
if, for some reason, the users are unwilling or unable to keep using the BCT
(e.g., as it gets discontinued or becomes too expensive), they may no longer
find enjoyment in pursuing the target behaviour. Secondly, if a BCT only makes
the target behaviour enjoyable (e.g., with a satisfying interface design)
without helping users understand and appreciate its ultimate value, their
enjoyment may wane or be replaced by something else they find more enjoyable
(and requires less effort). Moreover, users may be incentivised to perform the
behaviours for the wrong reasons, perhaps undermining the ultimate goal (e.g.,
hacking a step-counter to seem more active, or exercising to the detriment of
their overall health to keep their streak). In many cases, it may be more
desirable for people to internalise their motivation for meeting their
personal goals and knowledge of how to achieve them, such that they no longer
depend on the BCT.

By reviewing papers in the domain of HCI, we were able to understand how
researchers have applied SDT to the design of technological interventions. By
contrast, when SDT is leveraged by papers in other fields (e.g., health),
outcomes are usually reported, but the BCT itself is often described in
insufficient detail to allow for an analysis of design considerations (RQs 3
and 4). One risk we identified is that HCI researchers in this space sometimes
employ design features that relate to the theory by association (e.g.,
understanding relatedness as any form of social interaction), without using
measures to ensure that the features actually support the desired construct
effectively. This is a common pitfall when applying behavioural theories to
technology design more broadly (Michie and Prestwich, 2010; Hekler et al.,
2013; Michie and Johnston, 2012; Roffarello and De Russis, 2023), and has also
been observed in meta-analyses of SDT-based interventions in other domains
(Gillison et al., 2019). This may keep research interventions from achieving
the sustained motivation that the theory promises. Drawing from Hekler et al.
(Hekler et al., 2013) and others, we offer suggestions for research practices
to help ensure that the theory is applied most usefully.

Whereas recent work suggests ways to integrate assessment of SDT’s autonomy
construct when designing wellbeing-supportive technologies (Peters et al.,
2018), we consider implications for supporting user motivation and wellbeing
in the special case of BCTs, where a technology is purposefully designed/used
to support certain desired behavioural changes, and, preferably, in ways that
can be sustained. Our paper also contributes to the growing body of research
in the design and evaluation of BCTs and for HCI researchers interested in
utilising SDT.

In particular, we contribute:

  1. (1)

A systematic review of how SDT has been applied to the design of behaviour
change technologies in HCI, especially regarding claims about supporting core
SDT constructs and facilitating sustained motivation by design;

  2. (2)

An overview of contextual factors that may influence the suitability of SDT-
inspired design features;

  3. (3)

Recommendations for how the HCI community might unlock more of the theory’s
potential, drawing from Hekler et al.’s suggestions for using behavioural
theory in HCI.

##  2\. Self-determination theory

SDT is proposed as an ‘organismic’ metatheory of human
motivation.444Motivation, here, is understood as being moved (inspired,
energised) to act (Ryan and Deci, 2000a). That is, it describes motivation in
terms of its relation to the evolved (human) organism as a whole, rather than
treating it as an isolated phenomenon:

> In essence, SDT attempts to articulate the basic, vital nature of human
> beings— of  how that nature expresses itself, what is required to sustain
> energy and motivation, and how that vital energy is depleted (Ryan and Deci,
> 2017, p.24).

It is based on the observation that people have an innate propensity to be
proactive, creative and self-motivated—striving to grow, learn, master new
skills, and express their talents (Ryan and Deci, 2000b). This natural growth-
tendency is understood in terms of our more general evolved resources for
personality development and behavioural self-regulation. However, this
propensity for self-motivation seems to be sustained only under certain social
and environmental conditions. Under others, people can be passive and
demotivated, rejecting growth (Ryan and Deci, 2000b, a). The importance of
these supporting conditions bears on the particular view of motivation the
theory posits. More than just varying in degree (how much motivation), SDT
describes different types of motivation, pertaining to differences in the
“why”, i.e., the underlying attitudes and reasons that move people to act
(Ryan and Deci, 2000a). Within the six sub-theories of SDT, the BPNs play a
key mediating role between different motivation types.

###  2.1. Types of motivation

The most basic distinction SDT makes is between intrinsic motivation, “doing
something because it is inherently interesting or enjoyable” (Ryan and Deci,
2000a, p.55), and extrinsic motivation, “doing something because it leads to a
separable outcome” (Ryan and Deci, 2000a, p.55). For instance, a child could
practice playing the violin (mainly) because they find it inherently fun and
satisfying to improve their skills, or because of a range of external aims or
pressures (e.g., because their parents force them to, because they want to
impress their friends, because they are afraid of the violin teacher shouting
at them, because they want to achieve a good grade).

Variability in intrinsic motivation is described by one of SDT’s subtheories,
Cognitive Evaluation Theory (CET). According to CET, when someone is
intrinsically motivated to apply themselves in some way, they tend to be at
their most creative, energised and driven. In such cases, not only is the
quality of outcome typically higher, but their motivation for the behaviour
will persist for longer. In contrast, when someone is purely motivated by
extrinsic factors, they may apply themselves with a sense of ambivalence,
boredom and even resentment (Ryan and Deci, 2000a). In its most general form,
CET maintains that the fundamental needs for competence and autonomy are key
factors that distinguish intrinsic and extrinsic motivation: feeling capable
of doing the task, and feeling like one is willingly doing it for personal
reasons. The theory further maintains that both competence and autonomy
satisfactions are necessary for sustaining intrinsic motivation. In addition,
in observing that “intrinsic motivation is most robust in a context of
relational security and can be enhanced by a sense of belonging and
connection” (Ryan and Deci, 2017, p.124), CET suggests that relatedness also
plays a role in intrinsic motivation, especially for activities that involve a
social element.555Several evaluations have reported a comparatively small but
non-significant effect of relatedness satisfaction (Gillison et al., 2019;
Ntoumanis et al., 2021). Ntoumanis et al. (Ntoumanis et al., 2021) suggest
that, whilst relatedness supports “might be useful to support initiation of
change but perhaps not maintain it long-term, particularly if the target
behaviour is complex or does not need to take place alongside other people
(e.g., being regularly physically active, eat healthy)” (Ntoumanis et al.,
2021, p.234). In other domains (e.g., social contexts like work environments)
meta-analytic evidence suggests a more significant effect of relatedness
support (Ntoumanis et al., 2021).

Whilst desirable, an individual will not be intrinsically motivated to perform
just any activity. Ryan and Deci maintain that intrinsic motivation has a lot
to do with the sort of personality and values an individual has: it “exists in
the relation between individuals and activities” (Ryan and Deci, 2000a, p.56),
as individuals may naturally care more easily about certain tasks than others
(e.g., learning a new skill versus doing their taxes). In cases where some
external sources of motivation are required (be it encouragement, deadlines,
or fines), people may still be supported in ways that foster a greater or
lesser sense of willingness and drive. Another subtheory of SDT, Organismic
Integration Theory (OIT), describes four types of motivation within the
broader category of extrinsic motivation (Ryan and Deci, 2000b). These types
differ in their degree of internalisation—the degree to which the behavioural
regulation is experienced as autonomous versus controlled. The key determining
factor here is what is called the perceived locus of causality, i.e., where
the source of regulation is perceived to be (i.e., coming mainly from outside
or within).

The least autonomous form of extrinsic motivation is called external
regulation (doing something purely “to satisfy an external demand or obtain an
externally imposed reward contingency” (Ryan and Deci, 2000a, p.61). A
slightly more autonomous type is introjected regulation, when an activity is
done out of a sense of pressure, typically to “avoid guilt or anxiety, or
attain ego-enhancements or pride” (Ryan and Deci, 2000a, p.62). According to
OIT, both of these types still have an external perceived locus of causality
as the source of motivation is mainly external pressures or incentives.

The remaining two types have more of an internal perceived locus of causality.
The first is identification, i.e., when a person identifies with the personal
importance of a behaviour such that they accept the regulation to come from
within (Ryan and Deci, 2000a). This happens when the outcome of an activity is
required for something that the person deems personally important, e.g.,
filling out an application form for the sake of a job they really want. The
most autonomous type is integrated regulation, which happens when, through a
process of self-examination and bringing regulation’s aims in congruence with
their other needs/values, the regulation has been “fully assimilated into the
self” (Ryan and Deci, 2000a, p.62). Like intrinsic motivation, integrated
forms of motivation lead to behaviours that are volitional and unconflicted,
although they differ from intrinsic motivation in that they remain valued for
their instrumental value to serve some separate goal, rather than pursuing the
activity for its own inherent value (Ryan and Deci, 2017).

These four types of extrinsic motivation fall on a continuum between
amotivation (lacking any intention to act/sense of control) and intrinsic
motivation (as defined above)—see Fig. 1.

Figure 1. Motivation types postulated by SDT, ranging from amotivation (least
autonomous) to intrinsic motivation (most autonomous). Adapted from (Peters et
al., 2018) and (Ryan and Deci, 2000b).

According to OIT, the quality and strength of motivation can increase or
decrease depending on the extent to which a person’s relative need for
autonomy is supported by relevant environmental conditions: it is the key
mediating factor between the different extrinsic motivation types (Ryan and
Deci, 2000a, 2017). As for the other BPNs, they further support the process of
internalisation in different ways. One is by offering justifications for the
importance of valuing a certain behaviour, e.g., understanding why it is
personally meaningful (competence) or that it can bring them closer to people
want to be connected with (relatedness) (Ryan and Deci, 2000a, 2017). Another
is by feeling efficacious concerning it: as if one has the relevant skills to
succeed at it, and it is just the right degree of challenging (competence)
(Ryan and Deci, 2000a, b, 2017). In short, “[t]o fully internalize a
regulation, and thus to become autonomous with respect to it, people must
inwardly grasp its meaning and worth” (Ryan and Deci, 2000a, p.64), which is
generally facilitated by supporting someone’s needs for competence and
relatedness with situational factors (Ryan and Deci, 2017).

However, these factors must be relevant with respect to the given domain or
behaviour, and need satisfactions are implicated differently in each of the
types of regulation within the OIT taxonomy (Ryan and Deci, 2017). For
integration, what is more important than pure need support is facilitating an
internal PLOC towards autonomous, integrated regulation, which relevant need-
supports can help to energise and facilitate (Ryan and Deci, 2017). In their
recent meta-analysis, Ntoumanis et al. (Ntoumanis et al., 2021) found that
changes in autonomous motivation and perceptions of need support were
associated with positive changes in health behaviours, both at the end of the
intervention and at follow-up, but that changes in need-satisfaction per se
were not associated with changes in health behaviours at either time point.
Following Vallerand (Vallerand, 1997), they suggest that autonomous motivation
may mediate the effects of psychological need satisfaction on health
behaviours and people’s ability to sustain them (Ntoumanis et al., 2021).

###  2.2. Relevance for Behaviour Change Technologies

As a theory of human motivation—the different types and how to best support it
with relevant environmental conditions—SDT can help BCT designers create an
environment that enhances the quality of user motivation and their ability to
sustain behaviour change.

In particular, the mini-theory of OIT is a promising theoretical framework to
apply in this context. Whereas CET is useful for describing the factors that
typically contribute to intrinsic motivation, OIT is most useful for
understanding how to support someone to move from more external to internal
sources of motivation—especially for behaviours that are required for goals
they wish to achieve, but they tend to find taxing, unenjoyable or
uninteresting (e.g., maintaining a healthy lifestyle, quitting addictions,
etc.). These are typical reasons why people may choose to adopt BCTs.

It is also worth noting that personal goals often contain elements of both
intrinsic and extrinsic motivation: whilst someone may find playing a sport
inherently satisfying, this does not necessarily apply to all aspects of what
reaching their sport-related goals require (e.g., following a rigorous
training regiment, managing their diet, etc.). Similarly, someone may be
intrinsically motivated to play the violin in an orchestra, but not always to
dedicate hours of their week to practice when they could be doing something
they find more enjoyable. OIT is a useful resource for enhancing people’s
motivation for those aspects of meeting personal goals (as separable outcomes
of behaviour change (Ryan and Deci, 2017)) that they have the most difficulty
keeping to, even if they may find it more or less intrinsically motivating at
different times. As Ryan and Deci explain:

> [With intrinsic motivation,] the “aim” is the spontaneous satisfaction
> experienced while doing the activity. Thus the focus is on present
> experience rather than future goals … With internalized regulation, however,
> the focus is more on future goals or outcomes, for a defining element of
> extrinsic motivation is its instrumental nature, regardless of how
> autonomous one has become with respect to it (Ryan and Deci, 2017,
> p.197-198).

This makes OIT potentially very valuable for BCT design, as people typically
adopt a BCT to meet an ultimate separable goal (e.g., losing weight, quitting
smoking, gaining and maintaining a skill), rather than just finding something
new and fun to do. Whereas CET may help designers understand how to make tasks
more intrinsically satisfying and motivating, this is not possible for anyone
for any type of behaviour, and does not necessarily help with doing the
behaviours at the desired specific and persistent frequency to meet a personal
goal (i.e., the why of behaviour change). The acknowledgement and
internalisation of this why—the ultimate value of pursuing the activity—plays
a key role in facilitating integration to more autonomous regulation (Ryan and
Deci, 2017; Davis et al., 2016),666According to Ryan and Deci, integrated
regulation “requires self-reflection and reciprocal assimilation” (Ryan and
Deci, 2000a, p.188), which involves conscious endorsement of the ultimate
value of the behaviour, so as to “ bring a value or regulation into congruence
with the other aspects of one’s self” (Ryan and Deci, 2000a, p.188). and
offers a particular design opportunity. Our work aimed to review how OIT may
have been leveraged for this purpose in BCT design, or whether any of SDT’s
other mini-theories or constructs have been applied, and why.

One of the main challenges for BCTs is supporting long-lasting results, for
which SDT is particularly well-suited. A recent review of the main theories
and models applied in HCI research on behaviour change was focused on this
challenge, and highlighted the potential for, in particular, Dual Process
theory, but made no reference to SDT (Pinder et al., 2018). On this
background, our aim with our review is to provide a useful step towards
exploring the potential of SDT in HCI research to support long-term behaviour
change in service of personal user goals. More than motivation towards
specific outcomes, however, the real strength of SDT lies in the fact that it
treats a person as a whole organism, with particular drives, abilities, needs
and goals, and who can be energised to self-sustain their motivation for
activities they find personally meaningful and thrive under the right
conditions. This supports user-centred design initiatives attempting to
understand the user as a whole person, with needs and interests beyond their
interaction with a given technology (Spiel et al., 2018), and whose overall
well-being matters.

###  2.3. Measures

SDT researchers have developed numerous scales for assessing key constructs of
the theory, including intrinsic and extrinsic motivation, and the three basic
psychological needs. For example, scales that measure internalisation of
extrinsic motivation typically include items that distinguish externally
controlled motivation (e.g. ‘I do X because I might get a reward’) from more
autonomous motivation (e.g. ‘I do X because it’s important to me’). Scales
have been developed for general use (e.g., the Basic Psychological Needs
Satisfaction questionnaire, (Chen et al., 2014)) as well as within specific
domains such as work, exercise or education (Center for Self-Determination
Theory, 2022).

Adaptations for HCI already exist, such as the User Motivation Inventory
(which, in the context of engagement with interactive systems, measures
intrinsic motivation, integrated, identified, introjected, and external
regulation, as well as amotivation, (Brühlmann et al., 2018)), and the Gaming
Motivation Scale (Lafrenière et al., 2012). Measurement of autonomy is likely
to be especially important for HCI research on BCTs, to avoid backfire effects
from well-intentioned intervention. For this purpose, (Peters et al., 2018)
have suggested a number of scale adaptations for spheres ranging from initial
technology adoption (e.g., the extent to which a user’s decision to adopt a
technology is volitional and personally-endorsed) to larger life context
(e.g., how using a technology affects a user’s ability to pursue other
meaningful activities in their life).

##  3\. Review method

Our review aimed to investigate (RQ1) which of SDT’s theories have been
applied in HCI towards BCT design, (RQ2) what reasons were cited for this
application, (RQ3) how SDT-related constructs have been translated into
specific design features/suggestions, and (RQ4) how the suitability of these
design features differs across situations. Our reviewing procedure was loosely
based on the approach taken by Tyack and Mekler (Tyack and Mekler, 2020).

###  3.1. Source Selection

Publications considered for review were drawn from the Association for
Computing Machinery (ACM) Digital Library (the ACM Full-Text Collection), in
order to access a broad range of key venues in HCI.777The ACM Digital Library
(https://dl.acm.org/) is the most comprehensive database of computing and
information technology articles and literature, covering more than 50 peer-
reviewed journals in dozens of computing disciplines. As mentioned earlier, we
focused on HCI venues to get a sense of how HCI researchers have been applying
SDT theory in a technological domain, to evaluate the precedents being set for
interpreting the theory as design features. Whilst there may have been other
relevant work in BCTs in other venues, like psychological journals, HCI has
the greatest explicit focus on design considerations (RQs 3 and 4).
Publications from all years were considered.

###  3.2. Search procedure

We iteratively tested the phrasing of our query to find papers relevant to our
search. Initially, we searched for all papers containing the term “self-
determination” anywhere in the text, which returned 736 results. After going
through the first 146 abstracts, we found that most of the papers mentioned
SDT somewhere in the text without it being central to the aims of the paper.
As we were only interested in papers where SDT is explicitly applied as a lens
or guiding theory, we updated our query to only include publications that
contain “self-determination theory” in the abstract, to ensure the theory is
of central importance. This returned 86 results.

We acknowledge that this may have excluded papers where SDT was used but
referred to by other means (e.g. ‘a popular theory of human motivation’) but
considered this sufficiently unlikely.

###  3.3. Screening criteria

We did not use any exclusion criteria in our screening filters. However, we
manually excluded records that merely described plans for future research.
Thereby, we excluded four posters, two work-in-progress papers, two workshop
proposals, one doctoral consortium paper, and one magazine article, leaving 76
records.

###  3.4. Selection of papers for inclusion in the review

As we were interested in understanding how SDT has been applied towards the
design of BCTs, papers had to satisfy both these conditions: (a) having
substantial relevance to BCTs, (b) using SDT as a lens or guiding theory for
actual system design or for suggesting design implications.

To satisfy (a), papers had to pertain to technologies that have the purpose of
helping individuals change their behaviour in some way that they deem
personally important. For example, we excluded papers where technologies were
meant to help motivate people towards the interest of another party (e.g.
motivating people for crowd work (Posch et al., 2019; Grau et al., 2018;
Naderi et al., 2014)). Moreover, these technologies had to be ones that
individuals are meant to wilfully adopt for personal improvement—e.g., we
excluded papers pertaining to technologies that are intended to be used by
teachers or leaders to help a group reach outcomes, as it was not individually
sought (Behnke et al., 2016; Tolentino and Roleda, 2019; Marques et al.,
2021). However, we decided to include papers where an individual’s goals are
represented by someone close to them (e.g., a BCT adopted by a parent to help
their young child), if the other criteria were satisfied.

To satisfy (b), SDT (or any of its mini-theories) had to be applied
specifically towards the design of a technological intervention, even just as
theoretical suggestions. For example, we excluded papers where SDT was only
mentioned but not applied (e.g., (Korn and Tietz, 2017; Poeller and Phillips,
2022)).

After this step, 15 papers remained—see Fig. 2 for a flowchart of the
inclusion/exclusion procedure. The full list of excluded papers and their
reasons, as well as our analyses of the included papers, are available on the
Open Science
Framework.888https://osf.io/925rn/?view_only=5b8567e524e6416e83ea96fa896948f7

Figure 2. Flowchart of the inclusion/exclusion procedure

###  3.5. Coding procedure

Inspired by Tyack and Meckler (Tyack and Mekler, 2020), papers were coded with
respect to venue, domain, study type (e.g. qualitative, quantitative, mixed),
sample size, study duration, methods used, SDT-related measures used, and
purposes for citing SDT. For our purposes, we also coded papers based on the
user interface (UI) type (e.g., mobile/tablet, wearable, human-robot
interaction); the SDT-related constructs that were employed; how those
constructs were described; which (if any) of SDT’s mini-theories were applied;
how the BCT aimed to encourage sustained motivation. We also coded the
specific claims made about how any BPNs (autonomy, competence, relatedness)
were supported; other claims about how the BCT facilitates an internal
PLOC/autonomous regulation; contextual influencing factors that were
considered; and the paper’s stated novelty or contribution.

During this process, the lead author read through each paper in its entirety,
using different colours to highlight extracts that fit each category. For
design recommendations, the coder appealed to the given authors’ own claims
about the SDT construct they believe it supports, rather than making
inferences based on their understanding of the theory. This involved a
combination of placing direct extracts from the papers under the relevant
headings and making short descriptive summaries. During the next stage, the
same author generated codes to capture patterns in design suggestions for
supporting specific SDT constructs, and wrote some reflections on the
strengths and limitations of each study. The coding spreadsheets are included
as supplementary material.

After this initial phase of analysis, we generated higher-level themes to
capture similarities in the design suggestions made by different papers
(within the respective BPNs they are meant to support), as well as contextual
influencing factors. Whereas most of the generated codes were purely
categorical, placing quotes or summaries of content under its corresponding
category, based on the authors’ own claims, a part of the analysis process was
reflexive (Braun and Clarke, 2019; Clarke et al., 2015), as the coder
interpreted overarching themes, and compared the authors’ description of the
role of each construct with their understanding of Ryan and Deci’s (Ryan and
Deci, 2000a, 2012, b, 2016, 2017; Ryan et al., 2022) evolving description of
the theory and its elements.

Our reviewing procedure followed that of previous systematic reviews in HCI on
interface design and user experience (e.g., (Bargas-Avila and Hornbæk, 2011;
Law et al., 2018; Mekler et al., 2014; Tyack and Mekler, 2020)), and was
guided by Arksey and O’Malley’s (Arksey and O’Malley, 2005) methodological
framework.

##  4\. Results

The following section reports our analysis of the 15 publications we found in
HCI venues that apply SDT towards the design of various forms of BCTs (Table
1). Of these, only eleven were full research papers, while three were extended
abstracts, and one was a late-breaking report. We decided to include all of
these to give a general overview of exploratory work in this area.

Table 1. Papers included in review # |  Authors |  Year |  Title |  ACM Venue |  Application domain |  UI type |  Publication type |  Study type
---|---|---|---|---|---|---|---|---
1 |  Aufheimer et al. |  2023 |  An Examination of Motivation in Physical Therapy Through the Lens of Self-Determination Theory: Implications for Game Design |  CHI |  Physical rehabilitation, Health |  Unspecified |  Full research paper |  qual
2 |  Bomfim & Wallace |  2018 |  Pirate Bri’s Grocery Adventure: Teaching Food Literacy through Shopping |  CHI |  Education, Health |  Mobile |  Extended abstract |  n/a
3 |  Chaudhry et al. |  2022 |  Formative Evaluation of a Tablet Application to Support Goal-Oriented Care in Community-Dwelling Older Adults |  MHCI |  Health, Care |  Tablet |  Full research paper |  qual
4 |  Ferron & Massa |  2013 |  Transtheoretical Model for Designing Technologies Supporting an Active Lifestyle |  CHItaly |  Health, Fitness |  Mobile |  Full research paper |  quant
5 |  Ford et al. |  2012 |  Self-Determination Theory as Applied to the Design of a Software Learning System Using Whole-Body Controls |  OZCHI |  Education |  Organic UI |  Full research paper |  qual
6 |  Jansen et al. |  2017 |  Personas and Behavioral Theories- A Case Study Using Self-Determination Theory to Construct Overweight Personas |  CHI |  Health, Fitness |  Unspecified |  Full research paper |  qual
7 |  Lehtonen et al. |  2019 |  Movement Empowerment in a Multiplayer Mixed-Reality Trampoline Game |  CHI Play |  Health, Fitness |  Organic UI |  Full research paper |  mixed
8 |  Lerch et al. |  2018 |  Understanding Fitness App Usage Over Time: Moving Beyond The Need For Competence |  CHI |  Health,Fitness |  Mobile |  Extended abstract |  quant
9 |  Molina et al. |  2023 |  Motivation to Use Fitness Application for Improving Physical Activity Among Hispanic Users: The Pivotal Role of Interactivity and Relatedness |  CHI |  Health, Fitness |  Mobile |  Full research paper |  mixed
10 |  Putnam et al. |  2017 |  Effects of Commercial Exergames on Motivation in Brian Injury Therapy |  CHI Play |  Health, Physical rehab |  Organic UI |  Extended abstract |  quant
11 |  Saksono et al. |  2020 |  Storywell: Designing for Family Fitness App Motivation by Using Social Rewards and Reflection |  CHI |  Health, Fitness |  Mobile, Wearable |  Full research paper |  qual
12 |  Sinai & Rosenberg-Kima |  2022 |  Perceptions of Social Robots as Motivating Learning Companions for Online Learning |  HRI |  Education |  HRI, PC |  Late-breaking report |  quant
13 |  Van Minkelen et al. |  2020 |  Using Self-Determination Theory in Social Robots to Increase Motivation in L2 Word Learning |  HRI |  Education |  HRI |  Full research paper |  quant
14 |  Villalobos-Zúñiga et al. |  2021 |  Informed Choices, Progress Monitoring and Comparison with Peers: Features to Support the Autonomy, Competence and Relatedness Needs, as Suggested by the Self-Determination Theory |  MobileHCI |  Health, Fitness |  Wearable, Mobile |  Full research paper |  qual
15 |  Yang et al. |  2022 |  Magic Brush: An AI-based Service for Dementia Prevention focused on Intrinsic Motivation |  CSCW |  Health, Care |  Tablet |  Full research paper |  mixed

In terms of user evaluation, the results of 4/15 papers were theoretical:
drawing design implications from an interview with experts (Aufheimer et al.,
2023), an interview with envisioned users (Jansen et al., 2017), watching a
video of someone using the BCT (Sinai and Rosenberg-Kima, 2022), or not
involving any participants (Bomfim and Wallace, 2018). Another two papers drew
implications from surveying existing app users once (Molina et al., 2023;
Lerch et al., 2018). Of the 9/15 papers that tested a novel BCT design with
users, four engaged with the BCT only once (Lehtonen et al., 2019; Putnam et
al., 2017; van Minkelen et al., 2020; Yang et al., 2022). The remaining five
studies were done over the course of 6 sessions (of 90 min each) (Ford et al.,
2012), one month (Villalobos-Zúñiga et al., 2021), 3 months (Saksono et al.,
2020), 6 months (Chaudhry et al., 2022), and two years (Ferron and Massa,
2013) respectively. The maximum sample size was 211, with a median of 35
across studies.

###  4.1. Application domains

We identified two primary domains of application for BCTs, with some overlap.
The most prominent was health, which pertained to 12/15 of the papers, and the
other was education (4/15). Health was coupled with the subcategories of
fitness (7/15), physical rehabilitation (2/15), and care (2/15), and once with
education (i.e., food/nutrition literacy).

###  4.2. UI types

In total, the 15 papers developed and/or evaluated six different types of
interfaces, again with some overlap (e.g., software that can either be
implemented on different devices, or BCTs that involve multiple devices at
once). The types were mobile, wearable, tablet, PC, HRI, and Organic UI. While
some applications may have been compatible with multiple devices (e.g. mobile
phones, tablets, laptops, PCs), we did not make such inferences ourselves. We
used mobile to refer to applications that were described as primarily intended
for mobile phones, and tablet when the application utilised tablet features
(e.g., drawing on the screen with a stylus). We used PC when the tool
specifically required a large screen and/or keyboard typing (e.g., some
educational programs). We used HRI (human-robot interaction) to refer to BCTs
that involved social interaction with a robot, and organic UI for interfaces
that involved users’ whole bodies (e.g., as in certain exercise games).

Mobile was the most prominent UI type (4/15), followed by organic UI (3/15),
whereas wearable, tablet, PC, and HRI were each explored in 2/15 papers
respectively. Two papers were implementation-neutral/did not specify a
specific UI type.

###  4.3. Which of SDT’s theories and constructs were applied (RQ1)

Of the reviewed papers, only 3/15 explicitly mentioned the mini-theories they
applied, although all employed constructs from specific mini-theories. 13/15
employed the BPNs (as put forward in Basic Psychological Needs Theory, BPNT),
of which one only used the relatedness construct (Saksono et al., 2020). 11/15
employed intrinsic vs extrinsic motivation (as put forward in CET), and 5/15
employed the different motivation types of the autonomy-control continuum
(combining CET with OIT) (Aufheimer et al., 2023; Ferron and Massa, 2013;
Jansen et al., 2017; Villalobos-Zúñiga et al., 2021; Molina et al., 2023). One
paper employed constructs drawn from the Intrinsic Motivation Inventory (Ryan
et al., 1983) instead of the BPNs (Putnam et al., 2017) , and one employed
self-determination as a construct instead of intrinsic motivation (Chaudhry et
al., 2022).

Of those that mentioned the application of specific mini-theories, all three
said they used BPNT (Aufheimer et al., 2023; Lerch et al., 2018; van Minkelen
et al., 2020), although Aufheimer et al. (Aufheimer et al., 2023) combined it
with OIT, and Van Minkelen et al. (van Minkelen et al., 2020) combined it with
CET.

####  4.3.1. How was the role of the constructs in facilitating autonomous
regulation described?

Most papers offered a short description of the BPNs (14/15), and one employed
them without summarising what each need means/entails (Bomfim and Wallace,
2018).999The format of the paper was an extended abstract, which may explain
the oversight.

Several papers explained that satisfying these BPNs is required for/can
facilitate the internalisation of motivation (Bomfim and Wallace, 2018;
Saksono et al., 2020; Lerch et al., 2018), the behaviour (Lerch et al., 2018;
Aufheimer et al., 2023, p.2), or the performance of an activity (Molina et
al., 2023). Several others maintained that satisfying the BPNs will enhance
(Putnam et al., 2017; Ford et al., 2012; Jansen et al., 2017; Yang et al.,
2022), maintain (van Minkelen et al., 2020), or increase (Sinai and Rosenberg-
Kima, 2022; Jansen et al., 2017) intrinsic motivation: e.g., “When these three
needs are met, intrinsic motivation is expected to increase” (Sinai and
Rosenberg-Kima, 2022, p.1045). One simply stated that satisfying the needs is
necessary for “optimal function and growth” (Lehtonen et al., 2019, p.23), and
another that it leads to self-determination (Villalobos-Zúñiga et al., 2021).

As to how the internalisation process works, some understood it as a matter of
likelihood: the more of the BPNs are satisfied, the greater the chance that
motivation will fall on the more autonomous side of the continuum (Molina et
al., 2023; Jansen et al., 2017), e.g.,: “If all three of these basic
psychological needs are sufficiently met, intrinsic motivation to lead a
healthy lifestyle is probably high” (Jansen et al., 2017, p.2128). Others
maintained that moving along the continuum happens over time, as a
staged/gradual process—either by satisfying the needs (Saksono et al., 2020;
Yang et al., 2022), or “by providing personalized feedback to people with
different motivational levels or at different stages of the behavior change
process” (Ferron and Massa, 2013, p.2). The latter argued that, thereby, a
person may finally “reach” intrinsic motivation: “[SDT is a] theory describing
behavioral change as a gradual process starting from motivation … toward
increasing levels of internal regulation, finally reaching intrinsic
motivation” (Ferron and Massa, 2013, p.1).

In defining the BPNs, descriptions seemed generally consistent with how Ryan
and Deci (Ryan and Deci, 2000b, 2017) describe them. However, only rarely
(5/15) were the particular roles of the constructs described in terms of how
they might facilitate the integration process from more external to internal
sources of motivation, as OIT describes (Ryan and Deci, 2000b, 2017). For
competence in particular, several summaries may be construed as overly
reductive through that lens: e.g., defining competence simply as “the self-
perceived ability to learn new things and receive feedback” (van Minkelen et
al., 2020, p.370); as having mastery over challenging tasks (Lehtonen et al.,
2019, p.23) ; as a feeling of confidence in one’s ability (Molina et al.,
2023; Saksono et al., 2020; Putnam et al., 2017; Jansen et al., 2017; Yang et
al., 2022); or as a feeling of effectance from receiving positive feedback
(Sinai and Rosenberg-Kima, 2022; Yang et al., 2022). In contrast, only five
papers (Aufheimer et al., 2023; Molina et al., 2023; Villalobos-Zúñiga et al.,
2021; Bomfim and Wallace, 2018; Putnam et al., 2017) engaged with role of
competence support to facilitate “higher-order reflection” on the person’s
values, goals, and purposes (an essential part of the integration process
(Ryan and Deci, 2017)), more than simply feeling sufficiently challenged or
confident due to receiving positive feedback. This could be because most
papers drew the constructs from BPNT or SDT in general, rather than, at least
explicitly, considering the particular role the constructs play in the mini-
theories in facilitating the internalisation of regulation. It could also be
because the remaining (10/15) papers only employed constructs from CET (i.e.,
extrinsic vs intrinsic motivation), rather than OIT’s different motivation
types, and the process of moving between them.

###  4.4. Reasons for applying SDT (RQ2)

All of the reviewed papers suggested sustained motivation as a potential
benefit of applying SDT. Some described it in terms of enhancing motivation
for a given behaviour (Lehtonen et al., 2019; Bomfim and Wallace, 2018; Ferron
and Massa, 2013; Jansen et al., 2017), increasing engagement with the BCT
(Aufheimer et al., 2023; Lerch et al., 2018; Saksono et al., 2020; Ford et
al., 2012; Yang et al., 2022), improving the quality of their experience with
the BCT (Sinai and Rosenberg-Kima, 2022), or supporting users’ sense of self-
determination or empowerment (Aufheimer et al., 2023; Bomfim and Wallace,
2018; Chaudhry et al., 2022; Villalobos-Zúñiga et al., 2021). Holistic
benefits like promoting users’ overall well-being (Aufheimer et al., 2023;
Chaudhry et al., 2022; Lerch et al., 2018) or supporting a healthy lifestyle
(Jansen et al., 2017; Ferron and Massa, 2013; Saksono et al., 2020) were also
mentioned.

Most papers referred to “intrinsic motivation” as a part of the defining aim
of employing SDT (10/15), as opposed to the integrated regulation of a
specific goal or value of a behaviour (3/15) (Saksono et al., 2020; Aufheimer
et al., 2023; Molina et al., 2023). This owes to the fact that, as mentioned,
rather than describing motivation as a movement between different types or
orientations to motivation, constructs from CET and OIT were often conflated.
As such, intrinsic motivation was sometimes understood as something that is
already present and merely increases (Jansen et al., 2017; Ford et al., 2012;
Sinai and Rosenberg-Kima, 2022; Putnam et al., 2017; Yang et al., 2022): “SDT
proposes that intrinsic motivation of the users of a system such as Stomp is
enhanced by meeting three key needs” (Ford et al., 2012, p.147), or “When
these three needs are met, intrinsic motivation is expected to increase”
(Sinai and Rosenberg-Kima, 2022, p.1045). One paper acknowledged the different
types of motivation on the autonomy-control continuum, but argued that all of
those in the extrinsic category in OIT will fail to sustain long-term
behaviour change: “SDT introduces a control–autonomy continuum … from
amotivation (or absence of intention to act) to external regulation (to obtain
a reward) to introjected regulation (to avoid guilt) to identification
(accepted external regulation) to integration (self-determined action).
Additionally, the SDT explains that these … extrinsic motivation types can
urge a person to behave a certain way in the short-term but will fail to
maintain the behavior over more extended periods.” (Villalobos-Zúñiga et al.,
2021, p.2).

Application aims were typically phrased in terms of sustained usage of the
intervention (e.g., increasing/enhancing the “motivation to use a health app”
(Saksono et al., 2020, p.1) or “strengthening user engagement” (Ford et al.,
2012, p.149)), rather than promoting the activity that the BCT promotes
outside of the intervention (making exercise more inherently motivating, e.g.,
by helping users internalise its value to their lives). Even when the aims
were explicity stated as motivating users to engage in healthy behaviours, it
was implied that this would be done via motivating them to use the BCT, rather
than helping them internalise the value of the activity per se. For example:
“the satisfaction of the basic needs through the use of technology of
technology should result in intrinsic motivation to use the fitness App”
(Molina et al., 2023, p.4). Only one paper made explicit mention of helping
users sustain positive behaviours in their lives beyond the BCT (Bomfim and
Wallace, 2018). That is, to “develop an understanding of the nutritional
benefits of foods … [in order to] learn and internalize content to maintain
their outside the game” (Bomfim and Wallace, 2018, p.1-6). In this vein, one
paper made it explicit that enhancing engagement with the app can have the
effect over time of helping them engage in the target behaviour, even if it
will not necessarily enhance their intrinsic motivation for the behaviour
itself (Molina et al., 2023): “Importantly, behavior is not always driven by
intrinsic motivation (e.g., using fitness Apps due to sheer pleasure). In
fact, behavior related to PA [physical activity] is mostly driven by extrinsic
motivational factors … Integrated regulation is the nearest to intrinsic
motivation and is desired for the sustained use of fitness Apps. Sustained use
of the device could result in long-term PA adherence.” (Molina et al., 2023,
p.3-4). Two papers considered the BCT as a supplementary tool for in-person
therapy, and argued that, thus, applying SDT to the BCT will only partly help
sustain their motivation (Aufheimer et al., 2023).

####  4.4.1. How the BCT aims to encourage sustained motivation

We also analysed papers in terms of their claims regarding how the BCT might
encourage sustained motivation. This was often stated as the outcome of
satisfying one or more BPN in some way (13/15), as it enhances (Saksono et
al., 2020), stimulates (van Minkelen et al., 2020), strengthens (Yang et al.,
2022) or increases (Sinai and Rosenberg-Kima, 2022) users’ intrinsic
motivation; supports their sense of self-determination (Villalobos-Zúñiga et
al., 2021; Chaudhry et al., 2022); or makes the BCT more enjoyable (Ferron and
Massa, 2013; Lehtonen et al., 2019; Yang et al., 2022) (e..g, ‘trying to make
users experience sensory pleasure’ (Ferron and Massa, 2013, p.4). Chaudhry et
al. (Chaudhry et al., 2022) also suggested avoiding common reasons for
abandonment (e.g., a lack of trust and familiarity with the BCT), and
supporting re-engagement. In the context of exergames, 3/15 papers also
suggested that building user confidence, in particular, will motivate
sustained use (Putnam et al., 2017; Lerch et al., 2018; Lehtonen et al.,
2019). In the context of therapy, 2/15 papers maintained that making BCTs more
engaging will not sustain motivation as well as in-person therapy on its own,
but can facilitate the process (Aufheimer et al., 2023; Putnam et al., 2017).

###  4.5. How SDT was applied to inform design decisions (RQ3)

Beyond the description of SDT and its concepts, the meanings of the relevant
constructs were further evidenced in how they were translated into design
requirements and operationalised in measures. In analysing the reviewed work,
we distinguished between claims about supporting each of the BPNs by design,
and claims about facilitating an internal PLOC/autonomous regulation, as both
are important for internalising motivation (Ntoumanis et al., 2021; Ryan and
Deci, 2017, 2000b). Finally, we discuss the use of any SDT-related measures in
validating the different design suggestions.

Regarding supporting the BPNs, competence received the most treatment (13/15),
followed by relatedness (12/15) and autonomy (10/15)—see Fig.3.

Figure 3. Design suggestions for supporting users’ three basic psychological
needs (Ryan and Deci, 2000b) in behaviour change technologies

####  4.5.1. Supporting autonomy by design

We captured the range of design suggestions for supporting user ‘autonomy’
with the themes supply choice in task/outcome, supply choice in means, enhance
UX/usability, afford ability to voice, and tailor features to individual
differences. The 11 codes underlying these themes, and their prevalence across
papers, are shown in Fig.3.

Supply choice in task/outcome: Multiple papers suggested that the need for
autonomy could be supported by increasing the user’s degree of choice over the
tasks they completed, and/or the outcomes they achieved. We captured these
under the codes agency in goal setting in 3/15 papers, task options (2/15),
and dynamic goal-setting (1/15). Agency in goal-setting ranged from allowing
users to set their own goals (e.g., their weekly step-goal (Villalobos-Zúñiga
et al., 2021)), to selecting their own goals from an example goal list
(Chaudhry et al., 2022). Giving users full autonomy over their goals was
considered more appropriate in some contexts than others. For instance, in
expert interviews, Aufheimer et al. found that physical therapy is often “a
space devoid of meaningful provision of autonomy” (Aufheimer et al., 2023,
p.13) as patients do not possess the relevant expert knowledge, but maintained
that they should still be involved in “meaningful and collaborative goal-
setting” with therapists. Task options referred to features that offer the
user some choice over how they want to execute the task, either by giving
options to choose from (e.g., do you want to do X or Y? (Sinai and Rosenberg-
Kima, 2022) or allowing them to manipulate some small aspect of the format of
the task without changing the nature of the task (van Minkelen et al., 2020).
Finally, dynamic goal-setting referred to allowing users to adjust and update
their goals over time (Chaudhry et al., 2022).

Supply choice in means captured suggestions for offering some degree of
freedom in how tasks/outcomes were done/achieved. This included the codes
customisation (5/15), flexible means (3/15), user-initiated engagement (1/15),
and no time restrictions (1/15). Customisation included allowing users to help
shape the content of the program (Yang et al., 2022) and offering means for
users to specify their unique needs and preferences—either from pregiven
options (Bomfim and Wallace, 2018; Molina et al., 2023), or through more
qualitative means like motivational interviewing (Chaudhry et al., 2022) or
manually calibrating the BCT to individual traits and abilities. Flexible
means referred to giving the user a task or action plan that they are free to
implement according to their needs, circumstances and abilities (Chaudhry et
al., 2022; Lehtonen et al., 2019; Yang et al., 2022). Illusion of choice in
games referred to a suggestion for gamifying a physical therapy task plan such
that users have an “illusion of autonomy” even if outcomes were set (Aufheimer
et al., 2023). Finally, no time restrictions meant allowing users to take the
time they want to complete a task (Yang et al., 2022).

Enhance UX/usability: Two papers argued that autonomy could be supported by
making the interface more intuitive and easy to use. The code usable UI (2/15)
included the suggestion that an interface that’s easy to navigate will allow
users to freely exercise their options (Molina et al., 2023), as well as the
suggestion that a whole-body interface that allows users to behave in
intuitive (organic) ways will likewise support their autonomy (Ford et al.,
2012).

Afford ability to voice: This theme captured a suggestion for giving users a
degree of autonomy by allowing them to voice their experience with the BCT.
The code feedback options (1/15) referred to a suggestion for offering options
for users to give feedback on how they found a task (van Minkelen et al.,
2020). In particular, “the need for autonomy was also supported by presenting
a green smiley which the child could press to start the lesson, and a red
smiley which the child could press to indicate he/she had not understood the
instruction” (van Minkelen et al., 2020, p.371).

Tailor features to individual differences: Finally, this theme captured a
suggestion for incorporating considerations of SDT support in user-centred
design methodology. The code tailored autonomy support (1/15) referred to a
suggestion that designers should anticipate variations users’ needs for
autonomy at the design stage (captured as nuances in persona descriptions), so
as to include appropriate features, whatever they may be, tailored to
different users’ relative needs for autonomy support (Jansen et al., 2017).

####  4.5.2. Supporting competence by design

We captured 20 codes relating to suggestions for supporting user ‘competence’.
We discuss these under the themes adjusting difficulty, giving validation,
offering incentives, improving self-knowledge, improving task knowledge,
increasing user involvement, enhancing UX/usability, and tailor features to
individual differences.

Adjusting difficulty: This theme captured suggestions that related to making
tasks either more difficult or easier, or merely appear as such, so that users
feel competent executing them. It included the codes auto-adjust difficulty
(2/15), exaggerate user abilities (2/15), tailored goal-setting (1/15), and
challenging tasks (1/15). Auto-adjust difficulty was an implementation of the
idea in SDT that challenges should neither be too difficult nor too easy, and
so it should adjust according to what users are able to achieve (Bomfim and
Wallace, 2018; Ford et al., 2012). Exaggerate user abilities refers to making
users feel more powerful by apparently increasing their abilities, such as by
showing them a simulated version of themselves with exaggerated performance
(Lehtonen et al., 2019), or digitally enhancing things they produce (Yang et
al., 2022). Tailored goal-setting meant adjusting goals based on the user’s
recent performance (Villalobos-Zúñiga et al., 2021), and challenging tasks
just meant to make tasks extra challenging to be more motivating (Lehtonen et
al., 2019).

Giving validation: Several papers suggested making users feel validated in
their efforts as a way to support their sense of competence. This theme
captured the codes positive feedback (4/15), encouragement (3/15), periodic
feedback (1/15). Positive feedback included references to giving constructive
feedback to users, either depending on whether or not they succeeded (Sinai
and Rosenberg-Kima, 2022; van Minkelen et al., 2020), or regardless: “the
virtual assistant gives positive feedback to the image that the user draws
regardless of the user’s performance. The positive feedback can increase the
competence … of users even if they are not good at drawing” (Yang et al.,
2022, p.6). Encouragement was suggested to help users not feel incompetent
when they struggle (Sinai and Rosenberg-Kima, 2022; van Minkelen et al., 2020;
Villalobos-Zúñiga et al., 2021)). For instance: “It seems like the answer is
wrong, but I know you can do it. You just need some more time to think about
it” (Sinai and Rosenberg-Kima, 2022, p.1046). Finally, periodic feedback was
the suggestion of offering users a weekly report giving feedback on their
achievements/progress that week (Chaudhry et al., 2022).

Offering incentives captured suggestions for supporting users’ needs for
competence by offering them some incentive to keep on track with their goals.
This included rewards (3/15), gamification (2/15), and negative
rewards/warnings (1/15). Rewards referred to offering some form of virtual
rewards(Chaudhry et al., 2022; Ferron and Massa, 2013; Ford et al., 2012))
whilst negative rewards/warnings referred to virtual indicators of a lack of
progress (Chaudhry et al., 2022). Gamification techniques were suggested to
make tasks more engaging (for being both challenging and rewarding) (Putnam et
al., 2017; Ferron and Massa, 2013).

Improving self-knowledge: Some papers suggested that competence can be
supported by helping users notice things regarding their progress and choices.
This captured the codes prompt reflection (3/15),  self-monitoring (3/15), and
progress tracking (2/15). Prompt reflection refers to showing information or
adding some level of friction to prompt users to reflect on things like the
impact of their past goals (Chaudhry et al., 2022), how contextual factors may
have affected their progress (Villalobos-Zúñiga et al., 2021), or giving them
a chance to change their decisions (Bomfim and Wallace, 2018). Self-monitoring
refers to showing information to help users monitor their past
achievements/goals they have already reached (Aufheimer et al., 2023; Chaudhry
et al., 2022; Lerch et al., 2018), while progress tracking refers to showing
information to help users see how far they are from reaching their current
goal(s) (Chaudhry et al., 2022; Villalobos-Zúñiga et al., 2021).

Improving task knowledge: There were a few suggestions for supporting
competence by helping users better understand what they are asked to do. This
included the codes informed decisionmaking (4/15), guided goal-setting (2/15),
explain value (2/15), explain recommendations (1/15), and semi-automated goal
tracking (1/15). Informed decisionmaking had to do with offering users more
information with options, such as what they can expect from choosing a given
option (Yang et al., 2022; Villalobos-Zúñiga et al., 2021), what its
particular benefits are (Bomfim and Wallace, 2018) or why a given option may
be relevant to the user in particular (Chaudhry et al., 2022). Guided goal-
setting meant offering users help with setting their personal goals, either
through an example goal list (Chaudhry et al., 2022) or suggest adaptable
goals to each individual’s ability level (Villalobos-Zúñiga et al., 2021,
p.9). Explain value refers to showing information on why certain tasks or
goals are meaningful or useful, so as to help users internalise their value
(Bomfim and Wallace, 2018; Putnam et al., 2017). Explain recommendations meant
explaining why recommendations are relevant to the particular user (Chaudhry
et al., 2022). Finally, semi-automated goal tracking was suggested as a way to
minimize burden on the user whilst still affording them a level of autonomy
(Chaudhry et al., 2022).

Increasing user involvement: One paper suggested that competence can be
supported by letting a user play an active role in the BCT’s mechanism for
motivating them. The code manual reminders (1/15) captured the idea that users
would feel more competent if they set their task reminders themselves (in an
app) (Chaudhry et al., 2022).

Enhancing UX/usability: One paper suggested that users would feel more
competent if the interface is easy to use. The code usable interfacecaptured
the idea of improving the usability of the platform overall, such that users
have a greater sense of efficacy when using it (Lerch et al.,
2018).101010Whereas Fordd et al. (Ford et al., 2012) suggested that usability
supports user autonomy, Lerch et al. (Lerch et al., 2018) suggested it
supports user competence. We report on how the authors employed the tactics.

Tailor features to individual differences: Finally, three papers suggested
individual differences may determine how competence is best supported. This
captured the codes tailored motivation tactics (2/15), and participatory
design (1/15). Papers that advocated tailored motivation tactics suggested
that the most useful/effective tactics for supporting user competence depend
on contextual factors like the stage of adoption users are at (i.e., whether
they just starting on a goal or already making progress (Ferron and Massa,
2013), or their personality (Jansen et al., 2017). Participatory design meant
involving end-users in the interface’s design (particularly visualising their
progress) such that it is easy for them to understand (Chaudhry et al., 2022).

####  4.5.3. Supporting relatedness by design

We generated 17 codes relating to suggestions for supporting user
‘relatedness’, captured under the themes interaction with conversational
agent, user connectedness, interaction with external people, interaction with
human expert, considerate gesture from interface, and tailor featues to
individual differences.

Interestingly, the most prominent theme here was relate to conversational
agent, rather than connecting users with other people. This included the codes
interaction with embodied agent (3/15), reminders from digital assistant
(1/15), proximity to embodied agent (1/15), support from digital agent (2/15),
and interaction with voice-based agent (1/15). The code interaction with
embodied agent referred to suggestions to let users engage in human-like
social interactions with a social robot, whether for care, encouragement and
support (Sinai and Rosenberg-Kima, 2022; van Minkelen et al., 2020) or merely
for assistance (Chaudhry et al., 2022). It was also suggested that receiving
reminders from digital assistant (i.e., a virtual AI agent (Chaudhry et al.,
2022)) would make users feel more related, as would receiving guidance from
digital agent (e.g., feedback such as“You did a great job” and “I love the
picture.” (Yang et al., 2022), or personalised suggestions and help (Molina et
al., 2023)). Under interaction with voice-based agent, Yang et al. used a
celebrity voice as a digital assistant of a virtual therapist: “Several
studies have shown that not only do people often feel connected and involved
with celebrities and others appearing in the media but the sense also
develops” (Yang et al., 2022, p.5). Finally, proximity to embodied agent
referred to the suggestion that a social robot’s mere presence is enough
support a sense of relatedness (van Minkelen et al., 2020).

Relate to other users: Several papers suggested supporting relatedness by
encouraging users to connect with other users in some regard. This included
the codes multi-user interface (2/15), encourage cooperation (3/15), encourage
peer comparison (2/11), encourage group competition (1/15). Multi-user
interface referred to exergames that require multiple players so as to make
players feel more connected (Ford et al., 2012; Lehtonen et al., 2019).
Encourage cooperation referred to suggestions for encouraging users to
collaborate with other users, either by tasks that require cooperation(Ford et
al., 2012; Saksono et al., 2020), or by visualising data of user achievements
in collaborative ways (Molina et al., 2023). Encourage peer comparison meant
features for showing the progress/achievements of similar users (Ferron and
Massa, 2013; Villalobos-Zúñiga et al., 2021). However, in finding this to
backfire, (Villalobos-Zúñiga et al., 2021) suggested encourage group
competition as an alternative (i.e., letting users compete in teams to forge a
sense of comradery).

Relate to external people: Suggestions here pertained to encouraging users to
relate to other (non-user) people in the world. This included the codes
utilise existing connections (2/15), global connectedness (1/15), and embed
interface in natural social context (1/15). Utilise existing connections
referred to suggestions for features that encouraging users to reach out to
their existing friends or family (Sinai and Rosenberg-Kima, 2022; van Minkelen
et al., 2020). Global connectedness applied to a suggestions for informing the
user about broader initiatives that partake in similar behaviours, so as to
foster a sense of community (Bomfim and Wallace, 2018). Finally, embed
interface in natural social context was the suggestion that playing a mixed-
reality exergame in a natural social setting will encourage social
interaction, and, hence, support relatedness (Lehtonen et al., 2019).

Interaction with human expert: This captured suggestions regarding the
importance of human actors (particularly in the context of care/therapy) for
supporting people’s sense of relatedness. This included the codes human
assistance (1/15) and human judgment (1/15). The code human assistance
referred to a suggestion that physical therapy games should only be considered
a supplementary technology to human-led therapy, as “the human relationship
between therapist and patient serves as a source of enjoyment and comfort that
should be respected and supported by technical interventions” (Aufheimer et
al., 2023, p.13). Similarly, Chaudry et al. suggested that human judgment
should be used to help personalise goal suggestions, and that doing so will
support user relatedness in some way: “collected information [about user
needs, values and preferences] is sent to the care manager’s portal, who is
then able to send goal suggestions to the participants’ app (relatedness)”
(Chaudhry et al., 2022, p.6).

Considerate gesture from interface: Two papers suggested that interfaces that
perform supportive humanlike social gestures to foster a sense of relatedness.
It contained the codes address user by name (1/15) (van Minkelen et al., 2020)
and ask about user mood (1/15) (Yang et al., 2022). Ask about user mood
referred to the idea of asking a user how they feel that day so as to maintain
“healthy emotional conditions” (Yang et al., 2022, p.5).

Finally, tailor features to individual differences captured a suggestion that
the appropriate relatedness supporting features may depend on the user. It
contained the code tailored relatedness support (1/15), which described a
suggestion to anticipate variations users’ needs for relatedness at the design
stage so as to determine which approach(es) are most suitable (Jansen et al.,
2017).

####  4.5.4. Facilitating an internal perceived locus of causality/autonomous
regulation by design

Beyond supporting the BPNs, 10/15 papers considered how to support an internal
PLOC/autonomous regulation by design. Here we included any claims about
facilitating the internalisation process towards greater self-determination,
without mention of supporting a specific need (even if they may implicitly
relate to one).

Suggestions here included creating space in which patients can be involved in
meaningful goal-setting (Aufheimer et al., 2023); helping users internalise
content (Bomfim and Wallace, 2018); allowing increasing users’ awareness of
their progress (Chaudhry et al., 2022; Ferron and Massa, 2013; Villalobos-
Zúñiga et al., 2021); providing tailored feedback at different stages of the
process (Ferron and Massa, 2013); by identifying specific behavioural
variables of different users in the design stages (Jansen et al., 2017);
promoting interaction with other users (Molina et al., 2023); helping the user
feel valued and appreciated (van Minkelen et al., 2020); clearly communicate
the BCT’s value (Putnam et al., 2017); and extending the frequency of
satisfying (Saksono et al., 2020) or educational (Bomfim and Wallace, 2018)
moments over time.

####  4.5.5. Measures used

Of all the papers we reviewed, only 4/15 used full validated SDT-related
scales to measure SDT-related constructs (i.e., the Ubisoft Perceived
Experience Questionnaire (UPEQ) (Lehtonen et al., 2019); the Technology-based
Experience of Need Satisfaction questionnaire (Peters et al., 2018); the
Balanced Measure of Psychological Needs (BMPN) scale (Sheldon and Hilpert,
2012); and the Perceived Intrinsic Motivation (PIM) Questionnaire (Sinai and
Rosenberg-Kima, 2022). Another 2/15 papers used shortened versions of existing
scales: a reduced (Italian) version of the Sport Motivation Scale (Ferron and
Massa, 2013), and a shortened version of the Intrinsic Motivation Inventory
(IMI) scale (Putnam et al., 2017). (Yang et al., 2022) measured intrinsic
motivation with three statements developed by (Davis et al., 1992).

Some papers (3/15) did not use SDT-related scales or questionnaires, but still
based their data analysis on the theory. This included using SDT to inform
interview topics/code participant responses (Jansen et al., 2017), asked
researchers familiar with SDT to evaluate app features through an SDT lens
(Villalobos-Zúñiga et al., 2021), or made their own scale for measuring
participants’ level of engagement with a task (van Minkelen et al., 2020).

4/15 papers used no SDT-related measures (Bomfim and Wallace, 2018; Chaudhry
et al., 2022; Ford et al., 2012; Saksono et al., 2020). Instead, these papers
based the design of a BCT or prototype on SDT, but either did not test it with
users (Bomfim and Wallace, 2018) or measured constructs of user
experience/satisfaction unrelated to SDT (Chaudhry et al., 2022; Saksono et
al., 2020). One paper observed children engaging with an exercise game for 90
minutes and made inferences about its ability to support users’ BPNs without
asking users directly (Ford et al., 2012).

###  4.6. Contextual determining factors (RQ4)

Given the breadth of domains and behaviours for which BCTs can be designed,
there is some variation in how and to which extent it makes sense to support
each of the three BPNs. Moreover, other theories like the transtheoretical
model of behaviour change (Prochaska and Velicer, 1997) suggest that different
groups of people will vary in their needs and the interventions that
effectively support them. In our review, we found some acknowledgement of
factors that may affect the contextual suitability of certain design features
and motivation mechanisms.

One contextual factor that was raised was the relative stage of behaviour
change that an individual was in, e.g., whether they are only just adopting a
new behaviour or trying to sustain it (Ferron and Massa, 2013). According to
Ferron and Massa (Ferron and Massa, 2013), new adopters may require more
extrinsic motivation (e.g., gamification techniques) and more education,
whereas users at the later stage may benefit from “other incentives that
leverage their intrinsic motivation to a healthy and active lifestyle” (Ferron
and Massa, 2013, p.5). Another paper considered individual differences,
arguing that designers should “create complex, yet engaging and highly
realistic personas that make [variations in] users’ basic psychological needs
explicit” (Jansen et al., 2017, p.2127). Related to this was age: some papers
dealt with determining the appropriate features for users that have diminished
autonomy like children (Saksono et al., 2020; Ford et al., 2012; van Minkelen
et al., 2020), or other special requirements like older adults (Chaudhry et
al., 2022). Chaudry et al.(Chaudhry et al., 2022) found that their
participants (adults ¿55) found the use of ‘negative rewards’/warnings
motivating, contrary to findings with younger participants (Consolvo et al.,
2008). In the context of exergames for brain injury therapy, (Putnam et al.,
2017) found that males had significantly higher intrinsic motivation scores
than females, which they took to suggest that therapists ‘may need to scaffold
their female patients more in exergame therapies” (Putnam et al., 2017, p.56).
However, given the relatively small sample sizes of studies (n=between 5 and
211), and the particular conditions of each study, the generalisability of
these findings are questionable.

Regarding cultural differences, Molina et al. (Molina et al., 2023)
investigated the experience of Hispanic users of fitness apps. They maintain
that most studies testing the efficacy of mHealth technologies have been
conducted with a predominantly white population, and fail to adequately
address the needs of non-white communities: “Hispanics can view PA as ‘a waste
of time,’ hold different norms regarding weight and body shape, and value
social support with close family ties and obligations. Such culture-specific
values may detract Hispanics from engaging with fitness Apps for improving PA’
(Molina et al., 2023, p.1). To address this, they argue that customisation
options should not just account for personal information like age or gender,
but also to the user’s norms, values, and worldviews, which can diverge even
within a given cultural group. They also emphasise that the particular
implementation and embodiment of features matter.

Another consideration was domain: Aufheimer et al. (Aufheimer et al., 2023)
maintained that, in applications that require some level of expert regulation
(e.g., healthcare), it may not be in users’ best interests to give them as
much control as in other domains (e.g., fitness), but that a sense of autonomy
could still be supported through collaborative goal-setting, and games with
some illusion of freedom towards predefined outcomes. Lerch et al. (Lerch et
al., 2018) also highlight the importance of external contextual factors, as
factors like no longer finding exercise necessary or getting a gym membership
can also contribute to app abandonment, and so it may not necessarily mean the
BCT was not effective in its purpose.

##  5\. Discussion

Self-determination theory (SDT), an evidence-based theory of human motivation
and growth, is one of the major motivational theories in mainstream psychology
(Gillison et al., 2019; Ntoumanis et al., 2021; Ryan et al., 2022), and has
recently gained popularity in HCI (Ballou et al., 2022b; Peters et al., 2018).
It is particularly useful for understanding factors that either support or
undermine an individual’s ability to sustain their self-determination to
engage in certain behaviours, which we believe may usefully guide BCT
designers in facilitating sustained behaviour change. To explore this
opportunity, we systematically reviewed 15 HCI papers that employ SDT
specifically towards the design of BCTs to explore (RQ1) which of SDT’s
theories have been applied in HCI towards BCT design, (RQ2) what reasons were
cited for this application, (RQ3) how SDT-related constructs have been
translated into specific design features/suggestions, and (RQ4) what
contextual factors affect the suitability of these design features for
different BCTs.

Whilst SDT has gained popularity in multiple areas in HCI—especially games
research—we found that its application towards enhancing user motivation in
the context of behaviour change (at least in the HCI community) is still
relatively sparse. Our review of papers in the ACM Digital Library containing
‘self-determination theory’ in the abstract returned 84 results. Of these,
only 15 were research papers that leveraged the theory to make design
suggestions for technologies towards helping individuals change their
behaviour in some personally-desired way. All of these papers used key
constructs from SDT (such as intrinsic motivation and the basic psychological
needs for autonomy, competence, and relatedness) as a basis for proposing
design guidelines for BCTs, in a range of application domains.

To evaluate the progress and remaining opportunities regarding research in
this area, we were interested in understanding how exactly SDT was leveraged:
the aims for which the theory was applied, how the roles of the theory’s
constructs were understood, and how this guided the design approach and
evaluation of the BCTs. We identified two overarching domains of application:
health (subsuming fitness, physical rehabilitation and care), and education.
This involved a range of different interface types: from mobile apps, to
human-robot interaction, to wearables (or some combination).

All papers made design suggestions for supporting at least one of the basic
psychological needs that SDT proposes, with most of the focus on ‘competence’.
In our analysis, we generated themes to capture patterns in design solutions
that have been proposed across BCT domains and interface types. We also
identified other claims about supporting an internal PLOC/autonomous
regulation by design, and some contextual factors that may affect the relative
suitability of design solutions.

###  5.1. How SDT can help BCTs facilitate sustained motivation change

From our analysis, we identified two primary ways in which SDT has been
applied to the design of BCTs, revealing subtly different conceptions about
the (a) ultimate aim of BCTs, and (b) how they may help users achieve
sustained behaviour change. Approaches may also implicitly contain some
combination, although this distinction was not typically acknowledged.

The first is understanding a BCT as something that makes certain target
behaviours more intrinsically enjoyable, and hence motivating. In this case,
the theory was typically applied to making the tool/platform/tasks afford
users a certain amount of autonomy, competence, and/or relatedness, such that
they find using the BCT engaging, sufficiently challenging, and encouraging.
In this case, the idea is that sustained motivation may be achieved by making
users want to do the target behaviour more, via the BCT (e.g., by gamifying
the doing of the task), and hence, as long as they volitionally choose to use
the BCT for its intrinsic enjoyment, they will be engaging in the target
behaviour. In this case, the SDT mini-theories of CET and BPNT were, mostly
implicitly, applied as theoretical frameworks.

The second is understanding BCTs as a tool for helping users achieve specific
personal goals, where the aim is helping users reflect on, and internalise the
value of changing their behaviour in some personally-desired way. By
internalising the value of the behaviour change—prompting users to reflect on
what they wish to achieve with the BCT, and bringing it into congruence with
their other goals and values—the idea is that they may become more self-
determined to do things that are instrumentally important to them, but that
they do not necessarily find intrinsically motivating (e.g., wanting to change
their lifestyle/behaviours for finding it personally important and meaningful,
rather than because they know they have to). In this case, sustained behaviour
change is achieved by enhancing the quality of a person’s motivation for doing
the target behaviour, such that they might eventually no longer even require
external scaffolds like a BCT to feel motivated. In this case, the SDT mini-
theory of OIT was—again, mostly implicitly—applied to help users move towards
integrated regulation of the ultimate outcomes/goals they aim to reach through
the BCT.

Of the two approaches, the first was taken by the vast majority (10/15) of
reviewed papers. Whilst both have potential utility, we believe that the
latter may be more effective/appropriate for promoting sustained motivation in
many, if not most, contexts of BCTs, for reasons outlined below.

On the one hand, increasing a user’s inherent enjoyment of a BCT (e.g.,
through gamification or social scaffolds) may well increase their willingness
to use the intervention long-term, thereby helping them, in effect, perform
the target behaviour more. However, this may be less effective or sustainable
as a behaviour change approach than internalising the value of the behaviour
per se. Firstly, technologies like apps tend to have limited shelf-lives, or
are subject to changes (e.g., many apps start to require paid subscriptions in
order for the company to stay profitable). If a user’s motivation entirely
depends on their enjoyment of the BCT, but they are no longer able, or
willing, to use it due to external factors beyond their control, it could mean
that they stop engaging with the target behaviour entirely.

Secondly, just because a BCT, like an exergame, motivates users to do some
version of a target behaviour (e.g., jumping on a trampoline), it does not
necessarily mean that engaging in the behaviour it encourages as much as
possible is appropriate or sufficient for meeting their ultimate personal goal
with the behaviour change (e.g., becoming fit or healthy, or losing weight).
As Lerch et al.’s (Lerch et al., 2018) findings suggest, there are sometimes
valid, and even important, reasons why people may want to stop using a BCT
like a fitness app, e.g., deciding to get a gym membership instead, or feeling
sufficiently motivated to meet their exercise goals in other ways than the BCT
supports. In a similar vein, Spiel et al. (Spiel et al., 2018) critique
fitness trackers for embedding the assumption that “more steps equals more
health”, regardless of other factors that may be required for a healthy
lifestyle. One possible consequence of gamifying the doing of a ‘healthy’
behaviour as such, without helping users understand the value and importance
of performing the behaviour in the right way, at the right frequency, or
adapting their approach based on their changing needs, is that people may
start to “hack” the game for rewards rather than caring about whether or not
the exercise was done correctly. This may include waiting for the timer to run
out without exercising for the sake of getting points, or waving one’s arm to
increase steps in a wearable step counter.

Moreover, as the path of least resistance, such shortcuts may make users lose
interest in the app over time, as they find it too easy to avoid doing
behaviours in more effortful, goal-directed ways. Similarly, users might start
pursuing the proxy behaviour at the cost of their overall health (e.g.,
running too far and too frequently), as they are incentivised to maximise
their engagement with the app, rather than being regulated by the requirements
of meeting a specific personal goal. Finally, as mentioned earlier, intrinsic
motivation is not something that is always present but merely increases or
decreases, as several reviewed papers claimed. Instead, it is a specific type
of motivation that individuals can have towards certain behaviours for certain
reasons, which cannot necessarily be elicited for any target behaviour (Ryan
and Deci, 2000a, 2017). Some behaviours are simply less inherently enjoyable
than others, and even if one can make a target behaviour more enjoyable (e.g.,
with a BCT gamifying the process of stopping an addiction), this will only be
effective as long as using the BCT is comparatively more enjoyable than
engaging in the behaviour it is trying to avoid (e.g., enjoying being
supported in not drinking more than drinking), which is a tall order. Ryan and
Deci (Ryan and Deci, 2000b) also highlight this risk:

> Yet, however promising the serious games and gamification movements sound,
> their promise has not always yielded desired results. Many educational,
> training-focused, and health-related games are transparently extrinsic in
> their focus. Moreover, when such educational and training-focused games are
> expected to compete for players’ attention against actual games … they will
> typically lose because the way they are designed leaves them less
> interesting and need satisfying. Similarly, simply adding game elements to a
> workplace or learning task will not typically be sufficient to enhance
> motivation, particularly if the activity is not already intrinsically
> interesting (Ryan and Deci, 2017, p.529-530).

Thus, we believe that applying OIT to help people internalise the value and
importance of appropriately performing the target behaviour would be more
conducive to self-determined, sustained motivation towards personal goals,
than merely encouraging increased and sustained BCT use in line with CET or
BPNT. As Ryan and Deci (Ryan and Deci, 2017) explain:

> Numerous studies in varied behavioral domains and using various assessment
> strategies indicate that more autonomous and self- concordant motivation is
> associated with greater behavioral persistence, as specified in OIT’s
> Proposition IV. Clearly, when people more fully internalize the value and
> importance of a behavior or domain, they are more likely to maintain
> relevant behaviors and beliefs than when they engage in such behaviors for
> more controlled reasons. One result of this is a higher probability of
> actually achieving the goals people pursue (Ryan and Deci, 2017, p.213).

We believe that this gap poses a great opportunity for BCT designers to
utilise SDT towards meeting personal goals that require difficult or laborious
tasks that users may not easily find intrinsically motivating (or at least not
as strongly as compared to not doing it).

One can imagine various probable reasons why promoting increased BCT
engagement, rather than promoting people’s independent pursuit of behaviour
change, is the more common aim in HCI research. For one, companies typically
benefit financially from increased and sustained user engagement with the BCT.
If this happens to promote healthy behaviours and lifestyle choices in the
users, it can seem like a win-win situation. It is also easier to measure
success through people’s BCT use statistics than if they were to stop using
the BCT, and this use data can also be useful to learn more about human
behaviour, as well as how to keep improving and adapting BCT design. Moreover,
it may be that there is simply more of a precedent in using gamification or
other UX-enhancement tactics in interface design than applying theoretical
constructs in more OIT-consistent ways. As only five of the reviewed papers
regarded user studies that endured longer than a single use, of which only
three endured longer than a month, it is hard to know whether CET-consistent
approaches actually succeed in effectively sustaining behaviour change as
intended.

###  5.2. How SDT-related constructs were translated into design features

####  5.2.1. Design features to support users’ basic psychological needs

Across the reviewed papers, we generated 50 themes representing design
suggestions for supporting one of the basic psychological needs posited by
SDT: 11 for supporting ‘autonomy’, 22 for ‘competence’, and 17 for
‘relatedness’. These themes showed some overlap with those identified by
Villalobos-Zúñiga and Cherubini’s (Villalobos-Zúñiga and Cherubini, 2020)
review of features related to SDT in behaviour change apps: particularly,
customisation and (tailored/guided) goal-setting for supporting autonomy;
rewards, self-monitoring and activity(/progress) tracking for supporting
competence, and peer comparison and group competition to support relatedness.

How exactly all the features were implemented varied between domains and
technologies, as did the extent to which they convincingly seemed to support
the BPN in a theory-consistent way. Similar to what Tyack and Mekler (Tyack
and Mekler, 2020) found in the use of SDT for gameplay, papers were sometimes
“frought with dubious (and often uncited) claims as to how individual game
[BCT] elements relate to SDT concepts” (Tyack and Mekler, 2020, p.9): e.g.,
that supporting the three BPNs, in some way, will increase intrinsic
motivation. Even if features apparently associate with a given construct,
e.g., relatedness (having a “warm and caring” interaction with a social
robot), few evaluated its validity or justified it in terms of its relation to
the broader theory or mini-theories. Even if pleasant, is not necessarily true
that interaction with a robot would satisfy relatedness in the same way as
connections to other people (e.g., feeling a part of a group, improving one’s
social status, making a loved one happy) might, or that it will effectively
motivate the user for the target behaviour. Similarly, merely including a
feature that gives users a level of control over some aspect of the interface,
e.g., being able to choose between two options, does not necessarily mean that
one’s quality of motivation for the behaviour the app supports will increase.
This would all have to be evaluated with valid empirical measures, as we
discuss in section 5.4. This shortcoming is not limited to HCI research,
however. In their meta-analysis of SDT-based interventions, Gillison et al.
(Gillison et al., 2019) identified similar limitations across disciplines that
leveraged SDT for health behaviour interventions.111111Gilllison et al. argue
that insights into the efficacy of interventions that leverage SDT is “limited
by poor specification of the intervention techniques employed (i.e.,
investigators may state that they provided an autonomy supportive environment
without stating how they did so), and by a lack of information about the
impact of specific techniques on the mediators of change proposed within SDT
(e.g., need support and motivation); that is, it is often assumed techniques
will have the hypothesised impact on mediators without this being explicitly
tested.”(Gillison et al., 2019, p.111).

More than just implementing any one feature with a high degree of fidelity to
the theory, designers should also consider interaction effects—whether any one
feature will be sufficient for supporting the BPN in question, and whether
supporting any one BPN will be as effective in a given context without
supporting any others. Hekler et al. suggested this as another potential
pitfall of applying behavioural theories in HCI: “By focusing on individual
constructs rather than whole frameworks, however, an HCI researcher might
inadvertently design a system based on constructs that do not work
independently but only in tandem with other constructs” (Hekler et al., 2013,
p.3309). This point is further unpacked by Villalobos-Zúñiga and Cherubini:

> We suggest three open questions: (i) It is still unclear whether providing
> support for only one, or two of the basic needs can yield positive effects
> on a user’s motivation. (ii) … we do not know whether implementing multiple
> features that support the same BPN would actually increase the overall
> positive effect, or be detrimental towards supporting self-determined action
> towards the target activity. (iii) … It is not clear whether a particular
> combination of supports for the three basic needs would be better suited to
> help users with varying levels of intrinsic motivation (measured at the
> onset of the intervention) (Villalobos-Zúñiga and Cherubini, 2020, p.20).

Moreover, it is important to consider how effects may evolve: whether
apparently effective supports for any given need may wane or even have a
negative effect over time.121212Ryan and Deci emphasise the importance of
follow-up studies, as “SDT expects that careful use of external controls can
produce behavior change in the short term … But the more important and
penetrating issue concerns the persistence of that behavior change … when the
controls were no longer in effect … and it is here that the autonomy support
and resulting internalization and integration of behavioral regulations are so
crucial.” (Ryan and Deci, 2017, p.207-208). We, therefore, echo Hekler et
al.’s suggestion that designers should treat any proposed design features for
supporting SDT constructs as hypotheses that require additional testing, and
that the gap between theory and a concrete design should be bridged for every
new technology (Hekler et al., 2013, p.3310), given potentially significant
contextual differences. In the next section, we collate our findings of some
of such contextual factors that may affect the suitability of certain design
features for different BCTs.

####  5.2.2. Design features to support autonomous regulation

Beyond supporting specific BPNs, we also identified design suggestions for
facilitating an internal perceived locus of causality/autonomous regulation,
such that users may internalise motivation for the target behaviour.

Here we identified suggestions for creating space in which patients can be
involved in meaningful goal-setting; helping users internalise content;
allowing increasing users’ awareness of their progress; providing tailored
feedback at different stages of the process; by identifying specific
behavioural variables of different users in the design stages; promoting
interaction with other users; helping the user feel valued and appreciated;
clearly communicate the BCT’s value; and extending the frequency of satisfying
or educational moments over time.

As in the case of the BPNT supporting features above, the relative suitability
of such suggestions will likely vary between domains and implementations. The
most robust approach would be to apply a specific mini-theory as a theoretical
framework (in this case, OIT) as a basis for understanding (a) the role that a
given SDT construct plays in the theory, and how it may be most meaningfully
operationalised in the given context. Moreover, validated SDT measures should
be applied to evaluate the construct validity of a given operalisation in a
given implementation.

###  5.3. Gaps and limitations in existing work

Similar to Tyack and Mekler’s (Tyack and Mekler, 2020) finding of the use of
SDT in HCI games research, we found that the majority of papers engage with
SDT in a limited manner, rarely mentioning the mini-theories that give SDT-
related constructs their operational definitions. As such, the meaning and
role of constructs were sometimes described in ways that were overly
simplistic or not wholly theory-consistent. Drawing from Hekler et al. (Hekler
et al., 2013), we discuss these in terms of some typical risks of applying
behavioural theories in technology design.

For one thing, only four papers used complete validated SDT-related scales to
measure SDT-related constructs, while another two used shortened versions.
However, most papers used no validated SDT-related scales or questionnaires.
Instead, they did one of three things: either they used an understanding of
the theory as an interpretative lens (e.g., creating their own scale or coding
qualitative data in terms of the SDT constructs they seem to support), or they
measured constructs of user experience/satisfaction unrelated to SDT, or did
no user evaluation. Whilst using the theory as an interpretative lens for
analysing data is a valid approach, and fits well within the tradition of
theory-driven qualitative methods in HCI and the social sciences, there are
methods to lower the risk of confirmation bias, which have not been followed
in the reviewed work. One option suggested by Hekler et al. (Hekler et al.,
2013) is having a preformulated coding manual that contains “likely responses
in user feedback that would indicate that the technology was having or not
having a theoretically postulated effect” (Hekler et al., 2013, p.3311-3312)
Otherwise, it is too easy for researchers to subconsciously interpret anything
that participants say as vaguely related to the constructs of SDT. This risk
is even greater given the level of generality of SDT as a metatheory,131313A
metatheory has the highest level of generality of behavioural theories, and
identifies “broad ‘levels’ of inter-related associations and factors of
influence on a behavior of interest” (Hekler et al., 2013, p.3308) which means
that there is a lot of ambiguity in how constructs may be operationalised, and
translating it into design guidelines and features requires a great deal of
conceptual work.

This is one of the ‘common pitfalls’ of applying a behavioural theory from
psychology in HCI, as outlined by Hekler et al. (Hekler et al., 2013). Another
common pitfall is “picking only some constructs from a theory and thus losing
the potency of the full conceptual framework for designing a system” (Hekler
et al., 2013, p.3312), which we also noticed in our review. That is, whilst
all of the reviewed papers employed SDT-related constructs like
extrinsic/intrinsic motivation and the three BPNs, few papers described these
terms of the relevant mini-theories that describe them—also echoing Tyack and
Mekler’s (Tyack and Mekler, 2020) finding. Related to this, we also found that
a third common pitfall applied: “using selective constructs from a theory but
making claims that are related to the full theory” (Hekler et al., 2013,
p.3312). There was a tendency in the reviewed papers to confuse or selectively
combine constructs from two of its subtheories, CET and OIT. As mentioned,
some papers described intrinsic motivation as something that is always present
and increases or decreases with better support of the BPNs, rather than a
specific type of motivation, as the theory maintains. Instead, the theory
describes a process of internalisation/integration that occurs as the reasons
underlying an action become internalised and brought into congruence with
one’s other values. A related second point is that supporting either autonomy,
competence and relatedness in an interface—in some form or other—sometimes
appeared to be taken as sufficient to catalyse intrinsic motivation. As Hekler
et al. (Hekler et al., 2013) maintain, translating constructs from a
psychological theory into design features—especially a metatheory with such a
great degree of generality—requires a great deal of conceptual and formative
work, as it leaves space for much ambiguity. For example, autonomy does not
necessarily just mean “more choice, somewhere”, and what constitutes the right
amount of choice and the right kind of things to choose from should be
carefully explored with each new implementation, and in consideration of other
contextual factors like the domain, differences in needs between individuals
or groups, and for a given user over time.

Despite SDT’s central aim of supporting sustained and integrated forms of
motivation, we found another limitation in that reviewed HCI papers tend to
utilise it more for the sake of making BCTs engaging and satisfying (drawing
from OIT and BPNT), rather than offering scaffolding, information and support
for helping users internalise the target behaviour per se (in line with OIT).
Whilst the former may help motivate users to use the BCT in the short term,
the fact that motivation depends so much on the intervention (and the
encouragement/feedback/incentives it provides) means that its source is still
primarily extrinsic, and hence their ability to sustain motivation for the
target behaviour itself, independently of the intervention, is not supported.
This approach lacks a meaningful provision of autonomy in not encouraging
users to internalise/integrate the personal value of the target behaviour.
Hence, once the novelty effect or users’ ‘intrinsic motivation’ to engage with
the BCT wanes, if the latter was even achieved, users may not have the same
personal investment/motivation in continuing with either the BCT or the
behaviour. For encouraging more sustained behaviour change, beyond BCT
dependence, we suggest drawing from OIT as a potentially fruitful solution to
explore in future work.

Apart from choosing an appropriate theory, we now propose some general
guidance for operationalising SDT constructs in interface design, drawing from
Hekler et al.’s (Hekler et al., 2013) suggestions for applying behavioural
theories in HCI.

###  5.4. Future opportunities: designing for sustained motivation

Robustly applying SDT to the design of BCTs involves understanding the
appropriate aims and metrics that relate to the theory, as well as the
appropriate methods for translating its constructs into design features. We
briefly consider each of these below.

####  5.4.1. Appropriate aims

A limitation we noticed in existing work, is that researchers tend to assume
that the (implicit) ultimate aim of applying SDT to BCT design should be to
get users to engage more with the technology, rather than leveraging the power
of the theory for helping people internalise target behaviours to the point of
becoming self-regulated. A particular value of SDT is its ability to help
designers give people the tools and support they need to reach this point of
self-sufficiency, instead of simply making the intervention mechanisms less
controlling or more fun. For lasting results, it might be preferable not to
limit tasks to the interaction with the technology, especially if the activity
has the potential of being rewarding and valuable in itself (e.g., exercising
or developing mindfulness). In such cases, the aim should be to encourage
users to gain as much as possible autonomous control over their regulation
such that they eventually do not need the intervention anymore. This may
involve empowering them with information about how and why the target
behaviour is important, and knowledge about how to help themselves
(competence) as well as letting them become active participants in their self-
regulation in their lives outside of the technology (relatedness). If
gamification strategies are used, it may be helpful to find ways of gamifying
self-sufficiency (i.e., gaining knowledge about the value and purpose of the
target behaviour, and skills regarding performing it appropriately without
guidance), not just the “doing of” a given target behaviour (e.g., assuming
that more steps equal better health (Spiel et al., 2018)).

####  5.4.2. Appropriate methods and metrics for translating constructs into
design features

Another limitation we noticed, was finding robust (and theory-consistent) ways
to test and validate design features that aim to support users in aims such as
the above (in accounting for relevant SDT-related constructs), avoiding common
errors like confirmation bias and issues of construct validity.

Although the designed purpose of most BCTs is to effectively motivate changes
in user behaviour, the lack of resources in HCI for conducting large-scale
(and long-term) randomised controlled trials (RCTs) means that this is rarely
demonstrated (Hekler et al., 2013). Of our reviewed papers, only three studies
lasted longer than a month, of which none were RCTs. For more robust studies,
Hekler et al. suggest a few suitable approaches for theory-driven study
designs in HCI research. One approach is mediational/path and moderation
analyses, which aim to account for variations in relevant variables like how a
BCT works (i.e., the mediating variables: which of its features drive
behavioural change) and for whom or under what circumstances it works best
(i.e., moderating variables like individual/group and situational
differences). According to Helker et al., understanding key mediator variables
within guiding theories like SDT can “allow HCI researchers to both support
these constructs in their designs and to assess them in their evaluations
instead of solely relying on more distal outcomes such as behaviors” (Hekler
et al., 2013, p.3311). Another suggested approach, mentioned earlier, is using
theory to help evaluate qualitative data, e.g., testing whether a technology
is operating according to the relevant theoretical mechanisms by formulating
“a priori expectations of likely responses in user feedback that would
indicate that the technology was having or not having a theoretically
postulated effect” (Hekler et al., 2013, p.3312)—see Grimes and Grinter
(Grimes and Grinter, 2007) for an example. This contrasts with the more
deductive approach that was sometimes taken in our reviewed work, i.e., using
thematic analysis to code participant observation/interview data in terms of
the constructs they seem related to.

Beyond validating causal links between specific features and the relevant
constructs, researchers in the social sciences and HCI have developed and
validated several measures for measuring SDT-related constructs like BPN
satisfaction in different domains (see Peters et al.(Peters et al., 2018) for
an overview), which few of the reviewed work utilised. Here, it is also
important to consider which (combination of) scales are most appropriate for a
given context (e.g., measures for evaluating motivation/BPN support in therapy
differs from evaluating it in fitness), as well as when (and how frequently)
to evaluate the BCT’s effectivity, as motivation levels/quality may fluctuate
and wane over time (e.g., when the novelty effect wears off, or if a user
fails to assimilate and integrate a regulation). This may require adapting
supporting features or motivational approaches.

##  6\. Limitations and future work

Our review was limited to publications in HCI venues, which may have excluded
potentially relevant research in related fields (e.g., psychology, healthcare,
education) that applied SDT to BCT design. We expect that the risks of
validity and bias that Hekler et al. (Hekler et al., 2013) describe would be
lower in social scientific studies in fields like psychology, where the focus
is more on evaluating effect sizes with RCTs than on interface design. As our
focus was more on the latter, and we wanted to survey the precedents being set
in the HCI community, we limited our scope to records in the ACM Digital
Library.

As our review included late-breaking reports and extended abstracts, it may be
the case that some apparent limitations in understanding or applying SDT were
due to constraints related to the paper format. We decided to still include
those formats as this is still a relatively new/exploratory research area for
HCI and we wanted to give a broad overview of all the initial approaches to
applying SDT in this domain, as it may pave the way for future research
avenues.

Our suggestion for applying the SDT mini-theory of OIT to BCT design is
theoretical and has not been explored in practice/with end-users. This is
something we aim to look at in future work.

##  7\. Conclusion

In our review of 15 HCI papers that apply SDT to the design of behaviour
change technologies (BCTs), we described themes in how HCI researchers have
translated core SDT constructs into design features, and highlighted some
opportunities for future work aiming to further encourage sustained behaviour
change. We identified some limitations in how the theory has been understood
and applied (e.g., to enhance users’ motivation to use a technology rather
than supporting users in internalising the regulation towards becoming more
self-determined). We also highlighted risks of confirmation bias and bad
construct validity in cases where the theory was applied in an HCI context
without taking appropriate cautionary measures in the study design. In doing
so, we explore how the HCI community might unlock more of the theory’s
potential and better support sustained motivation with BCTs. Our work
contributes to discourse on designing wellbeing-supportive technologies, as
well as the growing body of research in the design and evaluation of BCTs and
for HCI researchers interested in utilising SDT.

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