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Empowering interventions to promote sustainable lifestyles: Testing
the habit discontinuity hypothesis in a field experiment
Bas Verplanken
*
, Deborah Roy
Department of Psychology, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
article info
Article history:
Received 25 June 2015
Received in revised form
14 September 2015
Accepted 24 November 2015
Available online 7 December 2015
abstract
This study tested the habit discontinuity hypothesis, which states that behaviour change interventions
are more effective when delivered in the context of life course changes. The assumption was that when
habits are (temporarily) disturbed, people are more sensitive to new information and adopt a mind-set
that is conducive to behaviour change. A field experiment was conducted among 800 participants, who
received either an intervention promoting sustainable behaviours, or were in a no-intervention control
condition. In both conditions half of the households had recently relocated, and were matched with
households that had not relocated. Self-reported frequencies of twenty-five environment-related be-
haviours were assessed at baseline and eight weeks later. While controlling for past behaviour, habit
strength, intentions, perceived control, biospheric values, personal norms, and personal involvement, the
intervention was more effective among recently relocated participants. The results suggested that the
duration of the ‘window of opportunity’was three months after relocation.
©2015 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/)
1. Introduction
Promoting environmentally friendly behaviours is arguably one
of the most difficult behaviour change targets. When people are
asked opinions on environmental issues such as global warming,
many will express concerns and pro-environmental attitudes (e.g.,
Eurobarometer, 2014; Ipsos MORI, 2015; Verplanken &Roy, 2013).
But when asked what the most important issues are today, the
environment usually ends up low in these rankings (e.g., BBC, 2015;
Gallup, 2015). Even if events such as hurricanes, flooding, or
pollution, happen on the doorstep, the environment remains a
distant and nebulous entity for most people (e.g., Lorenzoni,
Nicholson-Cole, &Whitmarsh, 2007, Whitmarsh, 2008). Conse-
quently, as is predicted by construal-level theory of psychological
distance (Trope &Liberman, 2010), mental representations of “the
environment”are not conducive to taking pro-environmental ac-
tion (Spence, Poortinga, &Pidgeon, 2012). Environmental issues
can also be framed as social dilemmas, that is, conflicts between
immediate self-interest and longer-term collective interest, which
also weaken an individual's motivation to act (e.g., Biel &
Thøgersen, 2007; Lorenzoni et al., 2007). Some barriers to pro-
environmental action are straightforward, in particular when
people are restrained in their options, for instance due to inade-
quate public transport or limited financial resources. Gifford (2011)
discussed a variety of psychological barriers to pro-environmental
behaviour, such as judgemental biases, social comparison pro-
cesses, psychological investments in current behaviours, and
mistrust in authorities. In this article we focus on habit as a
particular barrier to change. We will argue that while habits are
hard to break, finding opportunities where existing habits are
temporarily broken may make a behaviour change intervention
more effective.
Many behaviours that are considered as potential targets for
behaviour change in a more sustainable direction, such as trans-
portation, shopping, leisure activities, or water usage, are strongly
habitual. Habits are learned dispositions to repeat past responses
(Wood &Neal, 2007; Wood &Rünger, 2016). These behaviours are
conducted frequently, usually at the same location and time, and
are less guided by conscious intent (e.g., Danner, Aarts, &de Vries,
2008; Gardner, 2009; Ji &Wood, 2007; Neal, Wood, Labrecque, &
Lally, 2012; Ouellette &Wood, 1998; Triandis, 1977; Verplanken,
Aarts, van Knippenberg, &Moonen, 1998; Wood, Quinn, &Kashy,
2002). While the prevalent socio-cognitive models suggest that
control of behaviour is anchored in an individual's motivation or
willpower (e.g., Ajzen, 1991), when habits are forming some of that
control shifts to the environment, that is, to the cues that elicit the
*Corresponding author.
E-mail address: b.verplanken@bath.ac.uk (B. Verplanken).
Contents lists available at ScienceDirect
Journal of Environmental Psychology
journal homepage: www.elsevier.com/locate/jep
http://dx.doi.org/10.1016/j.jenvp.2015.11.008
0272-4944/©2015 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Journal of Environmental Psychology 45 (2016) 127e134
habit (e.g., Neal, Wood, &Drolet, 2013; Neal, Wood, Wu, &
Kurlander, 2011; Orbell &Verplanken, 2010; Wood &Neal, 2007;
Wood, Tam, &Guerrero Witt, 2005). Habits are thus highly auto-
matised behaviours (e.g., Aarts &Dijksterhuis, 2000; Verplanken &
Orbell, 2003), or patterns of behaviour (e.g., Kurz, Gardner,
Verplanken, &Abraham, 2015; Roy, Verplanken, &Griffin, 2015).
This comes with a degree of ‘tunnel vision’, that is, a lack of choice
awareness, superficial decision making, and little interest in new
information, even if decision makers are explicitly asked to make
deliberate choices (Aarts, Verplanken, &van Knippenberg, 1997;
Verplanken, Aarts, &van Knippenberg, 1997).
The features which thus characterise habit elack of conscious
intent, a shift of behavioural control from willpower to cues, and
‘tunnel vision’eare making existing habits resistant to change and
thus do not bode well for behaviour change interventions. How-
ever, it is not always possible to execute a habit. Circumstances may
arise or contexts may change which limit or block a habit, perhaps
temporarily, and thus require considering alternative courses of
action (e.g., Jones &Ogilvie, 2012). For instance, Fujii, G€
arling, and
Kitamura (2001) studied the effects of a temporary freeway
closure on commuters. While habitual car users were likely to take
a longer route rather than switching to a more efficient public
transport option, some car users did try public transport and,
finding out they had overestimated the travel time, continued to do
so during the freeway closure. Brown, Werner, and Kim (2003)
observed how car users switched to a light-rail option due to
temporary parking shortages, and for some this remained a long-
run choice maintained by the positive experiences. Verplanken,
Walker, Davis, and Jurasek (2008) found that university em-
ployees who had recently moved house and were concerned about
the environment were commuting more sustainably than those
who were equally concerned, but had not relocated, suggesting that
the relocation might have temporarily activated important envi-
ronmental values (cf., Gatersleben, Murtagh, &Abrahamse, 2014;
Verplanken &Holland, 2002).
These studies suggest that when habits are broken, this may
create a “window of opportunity”for behaviour change. Change
may occur spontaneously, for instance by discovering better op-
tions than the old habits, as supposedly was the case in the studies
cited above. But this window may also be used strategically to
promote behaviour change. Behaviour change interventions may
thus be more effective when delivered in the context of major habit
disruptions, such as those related to life course changes. This has
been put forward as the habit discontinuity hypothesis (Bamberg,
2006; Verplanken et al., 2008; Walker, Thomas, &Verplanken,
2015). Major discontinuities may involve transitions to new pha-
ses in life (e.g., from education to a job), geographical or physical
changes (e.g., residential or work-related relocations), or changes in
the environment where habits are executed (e.g., infrastructural
changes). Such discontinuities may force people to renegotiate
ways of doing things, create a need for information to make the
new choices, and a mind-set of being ‘in the mood for change’.
Interventions that capitalise on these conditions may thus be more
effective compared to interventions under default conditions.
A number of studies have investigated the effects of behaviour
change interventions that were intentionally delivered in the
context of a discontinuity. Bamberg (2006) provided residents who
recently had relocated with a 1-day free public transport ticket and
information about the available public transport services. The
intervention induced a significant increase in the use of public
transport compared to a control group of relocated residents who
did not receive an intervention. Thøgersen (2012), in a secondary
analysis of an intervention study in which participants were given a
free one-month public transport pass, found that the intervention
was only effective among participants who had recently moved
house or work place. Walker et al. (2015) followed workers of an
organisation which had relocated and initiated a sustainable travel
plan in the wake of it, and demonstrated how old habits decayed
and new habits established.
While the studies cited in the previous paragraph produced
results that are in line with the habit discontinuity hypothesis, they
did not provide a test whether the discontinuity itself had a distinct
role. In other words, these studies demonstrated that interventions
delivered in the wake of a discontinuity were effective, but did not
contrast the effects with a default condition in which participants
did not go through a discontinuity. The present study aimed to
provide such a test in a field experiment in a middle-large city in
the east of England. The study included participants who had,
versus had not, recently relocated, as well as an intervention versus
no-intervention control group in both segments. The intervention
consisted of face-to-face interviews and the provision of informa-
tion about sustainable choices. The outcome consisted of self-
reported frequencies of twenty-five environmentally relevant be-
haviours, which were assessed at baseline and eight weeks later.
The hypothesis was tested that higher frequencies of behaviour are
reported in the intervention versus control group eight weeks later,
but that this effect is stronger when participants had recently
relocated.
The effects were controlled for key determinants of environ-
mental behaviour at baseline; past behaviour, habit strength,
behavioural intention, perceived behavioural control, biospheric
values, personal norms, and personal involvement (e.g., Steg, van
den Berg, &de Groot, 2014; Steg &Vlek, 2009). Past behaviour
obviously served as benchmark for change. Existing habit strength
was included, as this might influence the resistance to change
(Lewin, 2008/1946). Intention and perceived control represented
the most proximal predictors of behaviour in the theory of planned
behaviour (e.g., Ajzen, 1991), and thus covered the motivation to
behave environmentally friendly and the perceived ability to do so,
respectively. Biospheric values, personal norms, and personal
involvement represented broader motivational, normative and
identity-related factors which have been found related to related to
pro-environmental behaviour and behaviour change (e.g.,
G€
ockeritz et al., 2010; Sparks &Shepherd, 1992; Stern, 1992;
Thøgersen &
€
Olander, 2002; Verplanken &Holland, 2002;
Whitmarsh &O'Neill, 2010).
2. Method
2.1. Participants and design
Participants were recruited among residents of Peterborough, a
city in the east of England with approximately 186,000 citizens. A
total of 1612 individuals were cold-contacted at the doorstep; 800
(49.6%) were willing to participate in the study.
1
Half of the par-
ticipants were known to have relocated within the previous 6
months (“movers”). These households had been identified through
property websites and contacts with developers who had been
active in the recruitment areas. The remaining 400 participants
were recruited from the same areas (“non-movers”). Movers and
non-movers were matched on house size (number of bedrooms),
home ownership, recycling facilities, and access to public transport.
Participants were assigned to an intervention or a control con-
dition. In order to avoid neighbours being assigned to different
1
Given the fact that participants were cold-contacted, and that participation
involved a relatively lengthy first session on the doorstep, we considered this
percentage as rather favourable. Participants were not systematically probed for
reasons for non-participation.
B. Verplanken, D. Roy / Journal of Environmental Psychology 45 (2016) 127e134128
conditions, a clustered randomisation procedure was applied, in
which geographical units were designated as intervention and
control areas, respectively.
The study comprised two measurements (T1 and T2, respec-
tively), which were approximately eight weeks apart. The mea-
surements consisted of questionnaires, which were handed out
upon recruitment and sent by post, respectively. From the original
800 participants at T1, a total of 521 (65%) submitted a completed
questionnaire at T2. The final sample contained 330 females (63%)
and 191 males (37%). Ages ranged from 19 to 85 years, M ¼41 years.
Participants received a £10 cash voucher and a lottery ticket for a
£250 a prize draw for submitting the final T2 questionnaire.
The study received approval from the Ethics Committee in the
authors' department.
2.2. Procedure and the intervention
The field work (recruitment, delivery of the intervention and
data collection) was conducted by the Peterborough Environment
City Trust. This organisation had developed an intervention to
promote sustainable behaviours among residents who had recently
relocated. This intervention was adapted and delivered in the
intervention condition. Participants in the control condition only
completed the T1 and T2 questionnaires.
The intervention consisted of a Personal Interview; a selection of
sustainable items (“Sustainable Goodie Bag”); tailored and general
information (“Green Directory”); a Newsletter. The intervention
was targeted at a wide range of environmentally relevant behav-
iours, including water conservation, waste reduction, reducing car
use, and saving gas and electricity. The intervention contained
individualised as well as generic information. Multiple motives
were addressed, which concerned ecological values such as pre-
serving natural resources, as well as individual benefits such as
financial savings (cf., Steg, Bolderdijk, Keizer, &Perlaviciute, 2014;
Whitmarsh, 2009). The individualised information was tailored in
the Personal Interview, and partly tailored in the Green Directory,
which also contained generic information. The Sustainable Goodie
Bag and the Newsletter conveyed generic information.
2.2.1. Personal Interview
Upon agreement to participate, participants were asked to fill
out a questionnaire, which formed the T1 baseline assessment. The
project assistant then conducted a personal interview. The re-
sponses provided in the questionnaire were used as the basis for
this conversation. The purpose of the interview was to identify
behaviours the interviewees were interested in changing, potential
barriers to change, and possible solutions. The project assistants
were trained to use one or more of the following intervention tools:
(1) addressing perceived obstacles and barriers, such as lack of
information or skills; (2) providing details of obtaining financial
benefits, for example by saving water, electricity, gas or fuel; (3)
emphasising long-term environmental benefits for humans and the
environment; (4) setting and committing to behavioural goals; (5)
emphasising a “green identity”; (6) emphasising pro-
environmental injunctive and descriptive norms; (7) enhancing
or maintaining engagement with and attention to the ecological
agenda. The project assistants kept notes of which behaviours were
addressed specifically during the interview.
2.2.2. “Sustainable Goodie Bag”
Participants were offered a free re-usable shopping bag con-
taining sustainable products. The bag contained eco-washing
liquid, vegetable and flower seeds, a bus timetable, a shower
timer, and a set of brochures on environmentally friendly choices.
2.2.3. “Green Directory”
An information booklet was sent out shortly after the Personal
Interview. Information for each participant was selected on the
basis of their expressed interest and/or lack of awareness of issues
during the Personal Interview. The Directory also provided generic
information by referring to websites on howto live sustainably, and
emphasised both environmental as well as the financial benefits of
saving resources.
2.2.4. Newsletter
Participants received twice a Newsletter from the Peterborough
Environment City Trust. The Newsletters contained a variety of
information about sustainable solutions and provided links to
relevant websites.
2.3. Assessments
Behaviours were assessed both at T1 and T2, while all other
measures were taken at T1.
2.3.1. Relocation status
Participants were asked how long ago they had moved to their
current address. This was recorded in terms of weeks, months, and/
or years. The time participants lived at the current address varied
from one week to 32 years. A variable indicating relocation status
was constructed by applying a log transformation on the numberof
weeks participants had lived at their current address.
2.3.2. Behaviours
Participants were asked how frequently they had performed
twenty-five environmentally relevant behaviours during the last
year (T1). These items were presented again eight weeks later (T2)
with reference to the same time frame. The choice of behaviours
was informed by behavioural goals formulated by the UK Depart-
ment for Environment, Food, and Rural Affairs (Defra, 2008). The
behaviours broadly covered the domains of water (e.g., taking less
than 10 min in the shower; using the toilet dual flush), waste (e.g.,
using re-usable shopping bags; using leftover food for other meals),
transportation (e.g., walking or cycling short journeys; ecologically
friendly driving), and energy use (e.g., turning down the heating;
washing clothes at cooler temperatures).
2
Frequencies of per-
forming these behaviours were reported on 5-point scales, which
were labelled “never”(1), “seldom”(2), “sometimes”(3), “often”
(4), “always”(5), respectively. Because the internal reliabilities of
the four behavioural domains were unacceptable (i.e., Cronbach
Alpha <0.50), the twenty-five behaviours were aggregated. Cron-
bach Alpha for the collective behaviours was 0.77 and 0.84 for the
T1 and T2 assessments, respectively. For each participant the be-
haviours were thus averaged into a T1 and T2 aggregated behaviour
index, respectively. High scores indicate high frequencies.
2.3.3. Habit strength
Habit strength was assessed by a shortened version of the Self-
Report Habit Index (SRHI; Verplanken &Orbell, 2003). In order to
keep the response load within acceptable limits, the SRHI was
applied to the four behavioural domains, which were labelled as,
“Using less water”,“Producing less waste”,“Reducing the car less
for short journeys”, and “Reducing gas and electricity use”,
respectively. Foreach of these categories six items from the original
2
The study originally included seven more behaviours. However, these were
discarded, for instance due to too little variance at T1 (e.g., almost everyone re-
ported to switch off lights and to use fully loaded washing machines), not owning a
device (e.g., a water butt), or a lack of facilities (e.g., a car sharing scheme).
B. Verplanken, D. Roy / Journal of Environmental Psychology 45 (2016) 127e134 129
twelve items contained in the SRHI were presented, Each set of
items started with the stem “[Behaviour X] is something …”, which
was followed by the six items; “…I do frequently”,“…I do auto-
matically”,“…I do without thinking”,“…that is part of my daily
routine”,“…is typically me”, and “…I have been doing for a long
time”. The items were chosen such that the key features of habit
(the experience of repetition and automaticity) were represented
(Orbell &Verplanken, 2015). Responses were reported on 5-point
scales labelled as “strongly disagree”(1), “disagree”(2), “unde-
cided”(3), “agree”(4), “strongly agree”(5), respectively. Cronbach
Alpha for the four behavioural domains varied between 0.96 and
0.97. Across all items Cronbach Alpha was 0.94. For each participant
the SRHI responses were averaged into an aggregated habit index.
High scores indicate strong habits.
2.3.4. Behavioural intentions
For each of the four main behavioural categories participants
were presented with three intentions, e.g., “In the next six months I
intend to conserve water”;“I expect that I will conserve water in
the next six months; “I am not really intending to conserve water in
the next six months”(reverse scored). Responses were reported on
5-point scales, which were labelled “strongly disagree”(1),
“disagree”(2), “undecided”(3), “agree”(4), “strongly agree”(5),
respectively. Cronbach Alpha for the four behavioural domains
varied between 0.75 and 0.82. Across all items Cronbach Alpha was
0.86. For each participant the behavioural intention responses were
averaged into an aggregated intention index. High scores indicate
strong intentions.
2.3.5. Perceived behavioural control
For each behavioural category participants were presented with
three items assessing perceived behavioural control (e.g., “I would
find it easy to conserve water”;“Cutting back on my water con-
sumption would not be hard to do”;“I don't really know how I
could conserve water”ereverse scored). Responses were reported
on 5-point scales, which were labelled “strongly disagree”(1),
“disagree”(2), “undecided”(3), “agree”(4), “strongly agree”(5),
respectively. Cronbach Alpha for the four behavioural domains
varied between 0.63 and 0.77. Across all items Cronbach Alpha was
0.82. For each participant the perceived behavioural control re-
sponses were averaged into an aggregated perceived control index.
High scores indicate strong perceptions of control.
2.3.6. Personal norms
For each behavioural category participants were presented with
three items assessing personal norms with respect to the envi-
ronment (e.g., “Conserving water is something that everyone
should do”;“Because of my values and principles, I feel it is
important to try and conserve water”;“I feel a moral obligation to
save water for the sake of the environment”). Responses were re-
ported on 5-point scales, which were labelled “strongly disagree”
(1), “disagree”(2), “undecided”(3), “agree”(4), “strongly agree”(5),
respectively. Cronbach Alpha for the four behavioural domains
varied between 0.78 and 0.84. Across all items Cronbach Alpha was
0.91. For each participant the personal norm responses were aver-
aged into an aggregated personal norm index. High scores indicate
strong personal norms.
2.3.7. Biospheric values
Biospheric values were assessed by four items taken from De
Groot and Steg (2008). Respondents rated the importance of “Pre-
venting pollution: protecting natural resources”,“Respecting the
earth: harmony with other species”,“Unity with nature: fitting into
nature“, and “Protecting the environment: preserving nature”in
terms of the extent to which they were “a guiding principle in their
lives”. The response scale used was ‘‘not at all important”(1) to “of
supreme importance”(5).’Cronbach Alpha was 0.91. For each
participant the responses were averaged. High scores indicate
strong values.
2.3.8. Personal involvement
Personal involvement was assessed by eight items, which were
developed for the present study. The items covered emotional
involvement (e.g., “I feel anxious about what climate change will do
to us”), interest in the environment (e.g., “There are more impor-
tant things to worry about than the environment”- reverse scored),
and empowerment (e.g., “I feel that I can really make a contribution
to a better environment”). Responses were reported on 5-point
scales, which were labelled “strongly disagree”(1), “disagree”(2),
“undecided”(3), “agree”(4), “strongly agree”(5), respectively.
Cronbach Alpha was 0.81. For each participant the responses were
averaged into a personal involvement index. High scores indicate
strong personal involvement.
3. Results
All variables were screened on distribution normality, and were
found satisfactory. Skewness and kurtosis values were
between 0.05 and þ0.05 for all variables, except personal
involvement, for which these values were 0.98 and 1.50, respec-
tively, suggesting some degree of deviation from normality.
In Table 1 means, standard deviations, and correlations of the
behaviour indices at T1 and T2 and the determinants of behaviour
at T1 are presented. All determinants assessed at T1 were statisti-
cally significantly correlated with the behaviour indices. The cor-
relations were as can be expected on the basis of the literature, that
is, in the range of 0.30e0.40.
3.1. Testing the habit discontinuity hypothesis
In order to test the main hypothesis, a multiple regression
analysis was conducted. Behaviour at T2 was regressed on age, sex,
behaviour at T1, the determinants of behaviour at T1 (habit,
intention, perceived control, biospheric values, personal norm, and
personal involvement), the intervention, relocation status, and the
intervention x relocation status interaction. The intervention was
coded as 1 (control group) and þ1 (intervention group), and
relocation status was z-transformed before calculating the inter-
action term. The adjusted R-square was 0.46, Cohen's f
2
¼0.85. The
variance inflation factors varied from 1.02 to 2.28, indicating that
there were no multicollinearity problems. Details of the analysis are
presented in Table 2.
While all determinants at T1 correlated statistically significantly
with behaviour at T2, only behaviour at T1, habit, and personal
involvement retained statistically significant regression weights.
Unsurprisingly, the main effect of relocation status was non-
significant. The intervention effect was statistically significant,
suggesting the intervention was effective in changing behaviour in
a sustainable direction. Importantly, this effect was qualified by a
statistically significant intervention x relocation status interaction,
beta ¼0.08, t ¼2.37, p <.02.
In order to inspect the nature of the interaction, simple slope
analyses were conducted at the mean minus one standard devia-
tion of relocation status, the mean, and the mean plus one standard
deviation, respectively. The dependent variable was the behaviour
index at T2, controlled for the behaviour index at T1 and the de-
terminants. These analyses revealed that the intervention was most
effective when participants had relocated relatively recently. The
slopes showed a statistically significant effect of the intervention on
behaviour change at the mean minus one standard deviation of
B. Verplanken, D. Roy / Journal of Environmental Psychology 45 (2016) 127e134130
relocation status, beta ¼0.20, p <.001, 95% CI between 0.08 and
0.32, and at the mean, beta ¼0.09, p <.04, 95% CI between 0.01 and
0.18, while there was no significant effect at the mean plus one
standard deviation, beta ¼0.01, 95% CI between 0.14 and 0.11.
Because part of the information provided during the interven-
tion was individualised, the multiple regression was re-run with
the behavioural composites of participants in the intervention
condition being replaced by composites of only the behaviours that
were specifically addressed during the Personal Interview. Using
these tailored scores, the results were very similar to those reported
above, and included again the statistically significant intervention x
relocation status interaction, beta ¼0.08, t ¼2.43, p <.02.
3.2. Investigating the ‘window of opportunity’
Tentatively, we investigated the actual time frame during which
the intervention was most effective after participants had relo-
cated. In other words, given that a habit discontinuity effect was
present, how wide was this ‘window of opportunity’? While relo-
cation status had been log-transformed in the previous analyses, in
this case the raw number of weeks since relocation was used. As
half of the total sample was recruited to have relocated within the
previous 6 months, the sample was split as closely as possible into
quartiles, i.e., participants who relocated less than 3 months pre-
viously, 3e6 months, 6e200 months and over 200 months,
respectively. In Fig. 1 the mean behaviour composite scores at T1
and T2 in the intervention and control conditions are graphically
presented for the four groups. The figure also provides the test of
the intervention effect in each group.
3
This breakdown suggests
that the intervention was effective during the first three months
after relocation, after which no effects could be detected.
4. Discussion
This study tested the hypothesis that an intervention delivered
in the wake of a major discontinuity (residential relocation) is more
effective than if the intervention is delivered under default condi-
tions. The rationale behind the hypothesis is that when old habits
are temporarily disturbed, people may be more sensitive to new
information and adopt a mind-set that is conducive to behaviour
change. The results of the study gave support to this hypothesis.
While controlling for baseline levels of past behaviour, habit
strength, intentions, perceived control, biospheric values, personal
norms and personal involvement, and pitted against a no-
intervention control group, participants who received an inter-
vention and had recently relocated reported more change eight
weeks later on a composite of twenty-five environment-relevant
behaviours compared to participants who had not recently relo-
cated. Although other studies have produced results that were in
line with the habit discontinuity hypothesis (Bamberg, 2006;
Brown et al., 2003; Fujii et al., 2001; Jones &Ogilvie, 2012;
Thøgersen, 2012; Verplanken et al., 2008; Walker et al., 2015), the
field experimental design of the present study provided a more
rigorous test of the hypothesis. Unlike the above mentioned
studies, which were either correlational and/or included samples in
which all participants had been subjected to a discontinuity of
some sort, the present study was thus able to demonstrate the ef-
fect of the discontinuity per se.
There are a number of caveats to consider. The effect size of the
extent to which relocation boosted intervention effects was small.
More than anything else, the results should be considered as ‘proof
of concept’. Two conditions made the present test very conserva-
tive. The first is that for an individual participant not all behaviours
Table 1
Bivariate correlations between behaviour and T1 and T2 and determinants at T1.
MSD2345678
1. Behaviour index T1 3.15 0.57 0.34 0.30 0.29 0.28 0.35 0.33 0.62
2. Habit T1 3.65 0.73 0.34 0.39 0.31 0.45 0.30 0.40
3. Intention T1 3.89 0.66 0.66 0.34 0.57 0.45 0.32
4. Perceived control T1 3.51 0.66 0.36 0.44 0.39 0.30
5. Biospheric values T1 3.73 0.83 0.51 0.45 0.30
6. Personal norms T1 4.24 0.64 0.49 0.38
7. Personal involvement T1 3.45 0.61 0.41
8. Behaviour Index T2 3.13 0.54
Note: N ¼521. All correlations are statistically significant at p <.001.
Table 2
Multiple regression predicting behaviour at T2.
B SE B Beta t Semi-partial correlation
Age 0.00 0.00 0.07 2.04* 0.07
Sex 0.00 0.04 0.00 0.06 0.00
Behaviour index T1 0.45 0.04 0.48 12.89*** 0.42
Habit T1 0.11 0.03 0.15 3.79*** 0.12
Intention T1 0.03 0.04 0.03 0.64 0.02
Perceived control T1 0.01 0.04 0.01 0.16 0.01
Biospheric values T1 0.00 0.03 0.00 0.11 0.00
Personal norms T1 0.03 0.04 0.04 0.84 0.03
Personal involvement T1 0.17 0.04 0.17 4.31*** 0.14
Relocation status 0.00 0.01 0.01 0.30 0.01
Intervention 0.04 0.02 0.07 2.14* 0.07
Relocation status x intervention 0.04 0.02 0.08 2.37* 0.08
Note: N ¼521. * ¼p<.05; *** ¼p<.001.
3
In this case the behaviour scores were not controlled for demographics and
determinants. If the significant covariates presented in Table 1 are used to control
for the analyses in the subgroups, the results are similar, i.e., a statistically signif-
icant effect of the intervention for participants who relocated within the previous
three months, F(1,142) ¼8.19, p <.01, and non-significant effects in the three
remaining groups, F(1,116) ¼0.27, F(1,112) ¼0.31, and F(1,141) ¼0.49, respectively.
B. Verplanken, D. Roy / Journal of Environmental Psychology 45 (2016) 127e134 131
were relevant, and only a selection of these were addressed in the
Personal Interview. Secondly, the discontinuity effect was
controlled for major determinants of behaviours, that is, past
behaviour, habit, perceived behavioural control, and a set of moti-
vation variables, which, as can be expected, explained most of the
variance in T2 behaviour. The test of the discontinuity effect was
thus confined to the mere additional contribution of relocation.
The discontinuity effect was evident when using the highest
level of aggregation of behaviour and the corresponding aggregates
of habit, intention, perceived control and personal norm.
4
First, the
intervention was partly tailored, and thus focused on different
behaviours for different participants, which provided a compelling
argument for aggregation. Second, aggregation makes sense from a
reliability point of view. In a seminal paper, Weigel and Newman
(1976) showed that when single behavioural criteria were aggre-
gated into an overall behavioural index, this measure correlated
0.62 with a general environmental attitude measure, compared to
an average of 0.29 when single criteria were used. While that paper
focused primarily on the issue of attitude-behaviour consistency, it
demonstrated that, in line with the principles of test theory,
combining multiple indicators provides a more reliable instrument.
In order to provide the most rigorous test of the discontinuity ef-
fect, we thus also aggregated the behaviour-specific determinants
(habit, intention, perceived control, personal norm) at the highest
level. A fair question can be posed about the psychological meaning
of these aggregates, as these do not have one-to-one connections to
specific behaviours. Our view is that, if anything else, the aggre-
gates might be considered as behavioural, motivational, and
normative representations of higher order sustainability or
ecological values. One of our reviewers suggested that the aggre-
gated habit variable might capture variation in self-identity, in this
case a “green”identity (e.g., Sparks &Shepherd, 1992; Stern, 1992;
Thøgersen &
€
Olander, 2002; Verplanken &Roy, 2013; Whitmarsh &
O'Neill, 2010), which would thus also elucidate why habit retained
a significant regression weight (Table 2). The latter suggested that
variations in existing habit strength modulated behaviour change
over and above the discontinuity effect.
While the results undoubtedly have theoretical significance, the
practical implications are limited unless circumstances are found or
created under which larger effect sizes can be realised. The latter
may be accomplished in a variety of ways. For instance, larger effect
sizes can be expected when interventions focus on single or small
sets of behaviours (e.g., recycling, eco-driving, saving water; e.g.,
Abrahamse, Steg, Vlek, &Rothengatter, 2005). Effect sizes may in-
crease by selecting and/or combining treatments. On the basis of a
meta-analysis of 253 intervention studies in the domain of pro-
environmental behaviours, Osbaldiston and Schott (2012) found
that interventions that included cognitive dissonance, goal setting,
social modelling and the use of prompts showed the largest effect
sizes. Combining such tools with a discontinuity approach may thus
lead to more powerful interventions. Finally, interventions may be
more effective when these are carried forward by groups or com-
munities which generate social support (e.g., Abrahamse et al.,
2005; Staats, Harland, &Wilke, 2004; Weenig &Midden, 1991).
Interventions and behaviour change cannot be seen in isolation
from wider systems in which they occur (e.g., Hawe, Shiell, &Riley,
2009; Lewin, 2008/1946). A ‘system’may be defined by
geographical location, such as a residential area. This comes with an
infrastructure and bundles of behaviours, such as driving children
to school or shopping in that area. Relocation thus unfreezes such
patterns. It is therefore interesting to focus on relatively large-scale
discontinuities, which are confined to a specific location and time
frame, such as when a new residential area is being built. These
situations provide easy access to relatively large groups of resi-
dents, who are all undergoing the same life course change in the
same time period. Other ‘systems’may be culturally defined, such
as social practices, for instance those involving hygiene or leisure
activities (e.g., Kurz et al., 2015; Reckwitz, 2002; Shove, Pantzar, &
Watson, 2012). Social practices also involve infrastructures and
bundles of habits, and are empowered with a shared meaning (e.g.,
hygiene standards). When individuals move into a new phase, such
as a transition from school to work, starting a family or entering
retirement, the habits defined by a social practice are subject to
change, and may thus be interesting targets for interventions.
Habit discontinuities may also be considered from a stage model
perspective (e.g., Bamberg, 2013; Dahlstrand &Biel, 1997;
Gollwitzer, 1990; Prochaska &Velicer, 1997). Stage models of
behaviour change distinguish a motivational phase and a volitional
or execution phase. The motivational phase is characterised by
deliberation, prioritising goals, and forming intentions. In the
volitional phase goals and intentions are subsequently enacted. One
of the issues in these models is why, how, and when an individual
moves from a motivational to a volitional phase. A habit
Fig. 1. Breakdown of T1 and T2 mean behavioural composite scores into four relocation status groups and tests of the intervention effect.
4
When the analyses were conducted on disaggregated indices and respective
determinants, the intervention x relocation status interactions were in the same
direction, but were statistically significant for transport-related behaviours,
marginally significant for waste-related behaviours, and nonsignificant for water-
and energy-related behaviours. Similarly to the aggregated analyses, the effects
were confined the first three months after relocation.
B. Verplanken, D. Roy / Journal of Environmental Psychology 45 (2016) 127e134132
discontinuity may be conducive to instigating such a transition, and
may thus facilitate the transition from contemplation to action (e.g.,
Gollwitzer, 1990; Holland, Aarts, &Langendam, 2006). A prereq-
uisite is that a motivation to adopt the new behaviours is present in
the first place, which needs to be genuine and self-related in order
to have the potential to translate into action (e.g., Bamberg, 2006;
Verplanken &Holland, 2002; Walker et al., 2015; Whitmarsh &
O'Neill, 2010).
The present study has a number of limitations. An obvious
limitation is that behaviours were assessed by means of self-
reports, which are vulnerable to social desirability and consis-
tency biases. We opted for investigating a broad spectrum of be-
haviours. This put constraints on the types of measurements that
were feasible. However, even if the self-reports contained a degree
of bias, this cannot explain why a habit discontinuity effect was
found. In other words, it is difficult to argue that biases would be
stronger among those who recently relocated. The choice for
breadth (many behaviours) also put restrictions on the assessments
of behaviour-specific determinants (habit, perceived control,
intention, personal norm), which could only be measured at the
level of behaviour category (e.g., saving water). This introduced a
lack of correspondence. Another limitation was that we had no a-
priori foundation for defining what exactly a “recent”relocation is,
and the chosen cut-off period of six months was arguably arbitrary.
This points to a wider issue with respect of discontinuity hypoth-
esis, namely the question what determines the size of what we
referred to as the ‘window of opportunity’, and the time when
discontinuity effects can be expected to occur (cf., Jones &Ogilvie,
2012). A disruption is a temporary condition, and once a person has
settled into the new situation, old habits may easily be re-activated
(e.g., Walker et al., 2015; Wood &Rünger, 2016; Wood et al., 2005).
The present results suggest that in this case the ‘window’was
approximately three months wide. It can be argued that the dy-
namics of a discontinuity effect may not be confined to a period
after the event itself. For instance, in the case of relocations, be-
haviours such as more efficient commuting may be the very reason
for a relocation. The window of opportunity may thus open before
the actual discontinuity takes place.
5. Conclusion
Prevalent models of behaviour and behaviour change may lead
to the suggestion that people change attitudes and behaviour only
if the alternatives offered are sufficiently convincing or beneficial.
This leaves the context in which interventions are delivered out of
the equation, and reflects a rather static view of human behaviour.
The habit discontinuity approach focuses on contexts in which
people are undergoing life course changes. Those moments of
change, when minds and behaviours temporarily unfreeze, may
provide precious opportunities for adopting healthier and more
sustainable lifestyles.
Acknowledgements
The authors wish to thank the Peterborough Environment City
Trust, and in particular Rachel Huxley, Janine Starling, Karen Law-
rence and Selena West, for conducting the field work of this study;
the Sustainable Lifestyles Research Group (SLRG), and in particular
Gemma Birkett, Ian Christie and Tim Jackson, for their support; Ian
Walker and Wendy Wood for insightful comments on an earlier
draft of this article. This research was supported by a grantfrom the
Department for Environment, Food, and Rural Affairs (Defra), UK,
grant number RMP 5687, and additional funding from the Eco-
nomic and Social Research Council and the Scottish Government.
The funders had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
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