Running Head: THINK AHEAD BEFORE YOU REGULATE

Think ahead before you regulate: A focus on future consequences predicts choices of
and beliefs about strategies for the down-regulation of negative emotions

Catherine N. M. Ortner, Leah Chadwick, and Alexis M. Wilson

Department of Psychology, Thompson Rivers University, 805 TRU Way, Kamloops,
BC, V2C 0C8

Corresponding Author: C. Ortner, Tel. 250 828 5497, cortner@tru.ca

This is a post-peer-review, pre-copyedit version of an article published in Motivation
and Emotion. The final authenticated version is available online at:
http://dx.doi.org/10.1007/s11031-018-9705-3

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Abstract
Considering future consequences predicts many self-regulatory behaviors. Moreover,
emotion regulation choices often involve trade-offs between immediate hedonic benefits
and future well-being and mental health. We propose that focusing on future
consequences may also predict emotion regulation choices. We examined whether
people who consider future consequences of their actions are more likely to choose
adaptive strategies and less likely to choose maladaptive strategies (Study 1) and
whether people believe that adaptive and maladaptive strategies have differential shortand long-term consequences (Study 2). In Study 1, consideration of future consequences
was related to choosing more adaptive and fewer maladaptive strategies for regulating
negative emotions. In Study 2, participants believed that adaptive strategies are more
effective in the short-term than in the long-term and that maladaptive strategies are
more effective in the long-term than in the short-term. Moreover, commonalities in
favored strategies were observed across the two studies. Taken together, the findings
suggest that trait future time focus plays a significant role in emotion regulation
preferences and that people have some knowledge about the varied temporal
consequences of different strategies.

Keywords: emotion regulation; consideration of future consequences; future time focus;
well-being

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Think ahead before you regulate: A focus on future consequences predicts choices of
and beliefs about strategies for the down-regulation of negative emotions
The way in which people regulate their emotions has important consequences
for their mental health and well-being (Aldao, Nolen-Hoeksema, & Schweizer, 2010;
Gross & John, 2003; Nelis, Quoidbach, Hansenne, & Mikolajczak, 2011). Therefore, in
order to experience well-being and avoid psychopathology, people presumably need to
consider the long-term effects of their emotion regulation choices. People vary in their
tendency to consider the future consequences of their actions (Strathman, Gleicher,
Boninger, & Edwards, 1994) and considering future consequences predicts selfregulatory behaviors (Joireman & King, 2016), in addition to well-being (Azizli,
Atkinson, Baughman, & Giammarco, 2015). However, the association between
consideration of future consequences and emotion regulation choices has received
limited attention to date.
Consideration of future consequences
Consideration of future consequences (CFC) refers to the extent to which people
incorporate future outcomes in their decisions when determining a course of action
(Strathman et al., 1994). CFC predicts a host of outcomes that come about through
effective self-regulation, including exercise, healthy eating, reduced problematic
drinking, and academic performance (Joireman & King, 2016; Joireman, Shaffer,
Balliet, & Strathman, 2012; Joireman, Strathman, & Balliet, 2006; McKay, Cole, &
Percy, 2015; McKay, Percy, & Cole, 2013; Peters, Joireman, & Ridgway, 2005).
Furthermore, a rich, broader literature supports the role of future time focus in selfregulation more generally. For example, in the domain of academic achievement, Miller
and Brickman (2004) proposed that proximal self-regulation is driven in part by the
valuation of distal future goals. This assertion is supported by research showing that

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holding distal future goals is associated with making more mid-range goals and also
with the uptake of proximal self-regulation strategies, such as those that might facilitate
learning (Tabachnick, Miller, & Relyea, 2008).
Several other temporal constructs have been proposed, including time
perspective (Zimbardo & Boyd, 1999), temporal distancing (Bruehlman-Senecal,
Ayduk, & John, 2016), and temporal focus, (Shipp, Edwards, & Lambert, 2009).
However, CFC differs from these constructs in that it focuses specifically on the extent
to which people consider immediate versus future outcomes of their actions when
making decisions (Joireman & King, 2016). On the other hand, time perspective, as
assessed by the Zimbardo Time Perspective Inventory (ZTPI), comprises five sub-scales
that assess different aspects of temporal orientation, such as holding a negative or
positive view of the past. Only the future subscale of the ZTPI reflects a measure of
behavior that involves working towards future goals, and is therefore most closely and
positively associated with CFC (Zimbardo & Boyd, 1999). Temporal distancing, which
involves the tendency to consider negative experiences from a future timepoint, is only
weakly correlated with CFC (Bruehlman-Senecal et al., 2016). In addition, CFC
correlates with, but is distinct from, a number of other psychological constructs, such as
conscientiousness, optimism, and delay of gratification (Joireman & King, 2016).
Few studies have explored the connection between CFC and well-being (Azizli
et al., 2015). Research on the related construct of future time perspective (Zimbardo &
Boyd, 1999) suggests that striving towards future goals is associated with higher life
satisfaction, happiness, and positive affect, as well as lower negative affect (Boniwell,
Osin, Linley, & Ivanchenko, 2010; Stolarski & Matthews, 2016; Zhang, Howell, &
Stolarski, 2013).
Emotion regulation

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People recruit a variety of strategies to maintain, enhance, or diminish their
emotional experience, expression, and physiology (Gross & Thompson, 2007). For
example, reappraisal reduces negative feelings by changing one’s thoughts about an
emotional situation (Richards & Gross, 1999). In contrast, rumination involves
repetitive thoughts about a negative event and tends to prolong or even augment
negative feelings (Pedersen et al., 2011). People also regulate positive emotions. For
example, positive mental time travel—remembering a positive event that has
occurred—maintains positive feelings. In contrast, fault-finding—looking for negative
aspects of a positive situation—reduces positive feelings (Quoidbach, Berry, Hansenne,
& Mikolajczak, 2010). How we regulate our emotions is connected to physiological
responding and mental health, including anxiety, depression, substance use, and wellbeing. Strategies that have a positive association with psychopathology and
physiological responding (e.g., rumination) have been deemed maladaptive and those
with a negative association with psychopathology and physiological responding (e.g.,
reappraisal), have been deemed adaptive (Aldao et al., 2010; DeSteno, Gross, &
Kubzansky, 2013; Nelis, Quoidbach, et al., 2011; Quoidbach et al., 2010; Tamir, 2009).
Researchers have challenged the distinction between maladaptive and adaptive
strategies, noting that the utility of each strategy varies according to context (NaragonGainey, McMahon, & Chacko, 2017; Philippot, 2013). Flexible application of several
different kinds of strategies, dependent on the situation, may be most adaptive (Aldao,
Sheppes, & Gross, 2015; Bonanno & Burton, 2013; Bonanno, Papa, Lalande, Westphal,
& Coifman, 2004). However, the adaptive/maladaptive distinction has been a useful
guide in the development of some self-report measures of emotion regulation and
maintains its predictive utility (e.g., Nelis et al., 2011).
Consideration of future consequences and emotion regulation

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Given that CFC is broadly related to self-regulatory behaviors, and that both
future time focus and effective emotion regulation predict well-being, it follows that
thinking about the future consequences of one’s behaviors may guide effective emotion
regulation, particularly in the face of negative events. Specifically, people who consider
future consequences may employ adaptive strategies to a greater extent than
maladaptive strategies, in the service of achieving long-term well-being. In addition,
specific strategies (whether adaptive or maladaptive) vary in their immediate and
delayed consequences (Gross, 2015). Some strategies have immediate hedonic benefits,
resulting in decreased negative affect, but do little to change feelings or are even
detrimental in the long-term. For example, attention reorientation (shifting attention
away from a negative stimulus towards a neutral or positive stimulus), rapidly decreases
negative affect but increases it after a delay, relative to other strategies (Kross & Ayduk,
2008). Also, avoidance of negative thoughts and experiences is associated with
psychopathology in the long-term (Aldao et al., 2010). Some other strategies are
beneficial in the long-term, but are effortful to implement or require tolerating
unpleasant feelings in the short-term. For example, reappraisal is associated with
positive mental health outcomes in the long-term, but is relatively effortful to execute,
placing demands on working memory, selective attention, and goal maintenance in the
short-term (Goldin, McRae, Ramel, & Gross, 2008; Kalisch, 2009; Ortner, Zelazo, &
Anderson, 2013; Sheppes & Meiran, 2007). Acceptance of unpleasant feelings is also
associated with reduced psychopathology (Aldao et al., 2010), but acceptance does not
diminish unpleasant feelings in the short-term, and so they must be tolerated, at least
initially (Ellis, Vanderlind, & Beevers, 2013). Thus, individuals who do not focus on
the long-term benefits of emotion regulation (i.e., those low in CFC) may avoid the use
of strategies that entail effortful control or the need to tolerate negative feelings, in spite

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of the potential long-term benefits of these strategies. In contrast, those who can
prioritize the future consequences of their regulatory efforts (i.e., those high in CFC)
should be more willing to use strategies that provide delayed benefits.
For regulation of emotions to positive events, the expected association with CFC
might be less clear. Strategies to maintain or even enhance positive emotions might not
have differential immediate and future benefits. Savoring (for example by focusing
one’s attention on the present moment, engaging in positive future mental time travel, or
telling others about positive experiences) is associated with greater positive affect in
response to positive events in the short-term, and higher life satisfaction in the longterm (Erisman & Roemer, 2010; Quoidbach et al., 2010; Quoidbach, Wood, &
Hansenne, 2009). On the basis of these findings, one might expect the associations
between CFC and emotion regulation preferences during positive events to be weak or
even non-existent.
There is limited research on the association between future time focus and
emotion regulation. One study found a small negative association between consideration
of future consequences and expression suppression (concealing behavioral expressions
of emotion), but no correlation with reappraisal (Bruehlman-Senecal et al., 2016). Also,
people who score high, compared to low, on CFC respond differently to emotionally
evocative events, reporting lower aggression, particularly when the consequences of
their behaviors are delayed (Joireman, Anderson, & Strathman, 2003). They also report
less regret and self-blame when they consider how they can learn from their experience
after a negative event (Boninger, Gleicher, & Strathman, 1994). Furthermore, when
asked to focus on a long-term regulatory goal, participants preferred reappraisal over
distraction compared to when asked to focus on a short-term regulatory goal (Sheppes et

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al., 2014). These findings suggest that a future time focus influences the ways in which
people respond to and recover from negative emotionally evocative events.
Study 1
Does CFC predict more adaptive emotion regulation overall, as well as the use
of specific adaptive and maladaptive strategies? Although the evidence suggests a link
between CFC and emotion regulation, we could find no published studies examining
this association using a measure of emotion regulation that assesses an array of adaptive
and maladaptive strategies in response to both positive and negative emotional events.
The aim of Study 1 was, first, to examine whether the consideration of future
consequences predicts more adaptive emotion regulation choices overall, particularly
for negative emotional events. Prior researchers have advocated for behavior-specific
measures of CFC (Dassen, Houben, & Jansen, 2015; van Beek, Antonides, &
Handgraaf, 2013), so we included both a general and domain-specific measure. The
domain-specific measure was adapted from the general CFC measure (Strathman et al.,
1994) and referred to considering future consequences for feelings, rather than future
consequences in general. We used this feelings-specific measure to test our hypotheses,
but its development was not the primary focus of this research. Second, we tested
whether future time focus was associated with the endorsement of specific adaptive and
maladaptive emotion regulation strategies. Finally, given limited previous work on the
association between CFC and well-being, we examined this association using a broad
battery of well-being measures.
Method
Participants
Participants were 209 undergraduate students from introductory psychology
courses at Thompson Rivers University in Kamloops, BC. The university’s Research

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Ethics Board approved the study. Participants gave informed consent and received 2%
bonus credit towards their grade.
After elimination of random responders, 182 participants remained in the final
sample, of which 133 identified as female, 45 as male, and two as “other” (no response:
n = 2). The mean age was 19.30 years (SD = 2.60). Participants were white (n = 138),
Asian (n = 8), First Nations (n = 9), Hispanic (n = 2), black (n = 2), Indian (n = 2),
Middle Eastern (n = 1), mixed ethnicity (n = 16), or other (n = 2) (no response: n = 2).
Measures
Consideration of Future Consequences Scale (CFCS; Strathman et al.,
1994). The CFCS comprises 12 items assessing the propensity to consider the future
outcomes of one’s actions (e.g., “I consider how things might be in the future, and try to
influence those things with my day to day behavior”). Participants responded on a scale
from 1 (not at all like me) to 5 (very much like me). Reliability was high (α = .81) in the
current sample. Prior researchers have advocated for domain-specific measures of CFC
(Dassen et al., 2015; van Beek et al., 2013), so we also adapted the CFCS to focus on
feelings (CFCS-Feelings). The CFCS-Feelings emphasized feelings as outcomes of
one’s actions (e.g., “I consider how I might feel in the future, and try to influence those
feelings with my day to day thoughts and behavior”). Reliability was high (α = .87).
Zimbardo Time Perspective Inventory (ZTPI; Zimbardo & Boyd, 1999).
The ZTPI assesses five dimensions relating to time perspective. For the purposes of the
current study, we focused on the future dimension (ZTPI-F), which comprises 13 items
(e.g., “I believe that a person’s day should be planned ahead each morning,”) to which
participants rated their agreement on a scale from 1 (very untrue) to 5 (very true).
Reliability was high (α = .81). We excluded the other subscales of the ZTPI from our

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analyses because they show considerable content overlap with the emotion regulation
items.
Emotion Regulation Profile Revised (ERP-R; Nelis et al., 2011). The ERP-R
is a broad measure of emotion regulation choices, tapping into people’s choices of four
adaptive and four maladaptive strategies for each of the down-regulation of negative
emotions and the up-regulation of positive emotions. The ERP-R comprises nine
negative and six positive scenarios. For each negative scenario, participants identified
which of four adaptive strategies (situation modification (e.g., getting help from a friend
to prepare for a presentation), attention reorientation (e.g., thinking about a happy
memory), positive reappraisal (e.g., looking for the positive in a situation), and emotion
expression (e.g., sharing emotions)) and four maladaptive strategies (learned
helplessness (e.g., doing nothing to improve a situation), rumination (e.g., focusing on
negative thoughts), substance abuse (e.g., using alcohol to escape a situation), and
acting out (e.g., yelling when angry)) they would use. Similarly, for each positive
scenario, participants identified which of four adaptive strategies (behavioral display
(expressing positive emotions non-verbally), savoring the moment (focusing attention
on the experience), capitalizing (e.g., telling a friend about the experience), and positive
mental time travel (e.g., remembering past positive events)) and four maladaptive
strategies (inhibition of emotion expression (e.g., suppressing one’s expression of
positive emotions), fault-finding (looking for problems with the situation), inattention
(engaging in other, negative, mental activities, such as worrying), and negative mental
time travel (thinking about the event while focusing on external attributions or negative
thoughts about the future)) they would use. Participants selected as many strategies as
they wished for each scenario. Each adaptive strategy selection was credited +1 point
and each maladaptive strategy selection was credited -1 point. The measure yields

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scores for regulation of negative emotions and regulation of positive emotions
(computed by summing the adaptive and maladaptive points for negative scenarios and
positive scenarios), with higher scores reflecting more use of adaptive relative to
maladaptive strategies. We also summed scores for adaptive strategies and maladaptive
strategies, for positive and negative scenarios separately (savoring, dampening, focus
change, and stuck negative, respectively), such that higher scores reflected more choice
of those regulatory approaches. In other words, savoring reflects the selection of the
four adaptive strategies across the six positive scenarios; dampening reflects the
selection of the four maladaptive strategies across the six positive scenarios; focus
change reflects the selection of the four adaptive strategies across the nine negative
scenarios; and stuck negative reflects the selection of the four maladaptive strategies
across the nine negative scenarios. We also computed a score reflecting total choice of
each strategy. The decision to compute scores both for choice of adaptive and
maladaptive strategies, as well as for each strategy separately, was based on prior
research finding differential associations between adaptive versus maladaptive strategy
use and mental health and well-being as well as between individual strategies and
measures of well-being (Aldao et al., 2010; Quoidbach et al., 2010).
In the current sample, reliability was good (for up-regulation of positive
emotions, α = .81, and for down-regulation of negative emotions, α = .78).
Well-being measures. We used a battery of tests (Huta & Ryan, 2010) to assess
life satisfaction (α = .84) (Satisfaction With Life Scale (SWLS); Diener, Emmons,
Larson, & Griffin, 1985), vitality (α = .91) (Bostic, Mcgartland, & Hood, 2011),
meaning in life (α = .87) (Huta & Ryan, 2010), positive and negative affect (α = .87 and
α = .77, respectively) (E. Diener & Emmons, 1984), elevating experiences (α = .85)
(Huta & Ryan, 2010), self-esteem (one item) (Huta & Ryan, 2010), experience of

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meaning (α = .87) (Huta & Ryan, 2010), self-connectedness (Huta & Ryan, 2010), and
carefreeness (α = .73) (Huta, 2012). Following Huta and Ryan (2010), positive affect,
negative affect, elevating experiences, self-connectedness, and carefreeness items were
intermixed in a single measure whereby participants rated the extent to which they
typically feel each state on a scale from 1 (not at all) to 7 (extremely).
Depression Anxiety Stress Scales (DASS-21; Henry & Crawford, 2005). To
assess mental health symptoms, participants completed the DASS-21 (short form).
Respondents rated how much each of 21 statements (seven for each of depression,
anxiety, and stress) applied to them over the past week (e.g., “I felt that I had nothing to
look forward to”—depression), on a scale from 0 (did not apply to me at all) to 3
(applied to me very much). We computed a mean DASS score, for which reliability was
high (α = .92).
Conscientious Responders Scale (CRS; Marjanovic, Struthers, Cribbie, &
Greenglass, 2014). The CRS consists of instructional items embedded amongst other
items in a questionnaire to identify non-conscientious responders. Five items (e.g., “To
respond to this question, please choose option number five, ‘slightly agree’”) were
scored as correct (1) or incorrect (0). Participants scoring a total of 0, 1, or 2, out of a
possible 5, were considered random responders and were omitted from the analyses
(Marjanovic et al., 2014). Based on this criterion, 18 participants (8.6%) were identified
as random responders, a proportion similar to random responding rates found in other
undergraduate samples surveyed with the CRS (e.g., Marjanovic, Holden, Struthers,
Cribbie, & Greenglass, 2015; Marjanovic et al., 2014) and similar validity measures
(see Meade & Craig, 2012).
Balanced Inventory of Desirable Responding-Short Form (BIDR; Hart,
Ritchie, Hepper, & Gebauer, 2015). Participants completed the short form of the

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BIDR, which includes eight items assessing each of impression management (IM) and
self-deceptive enhancement (SDE) (e.g., “It’s hard for me to shut off a disturbing
thought”). Following Hart et al. (2015), items were scored using continuous, rather than
dichotomous, scoring. Given the content overlap between some of the SDE items and
emotion regulation, we only used the IM subscale (α = .63). BIDR-IM scores correlated
positively with the future factor focus score (computed below), r = .17, p = .022, and
with ERP-down regulation of negative emotions, r = .27, p < .001, but not with any
other measures, all p’s > .11.
Demographic information. Participants reported their age, gender, and
ethnicity.
Procedures
Participants completed the questionnaires in groups of approximately 10 to 25
students. Questionnaire order was counterbalanced, with the ERP-R either preceding or
following the other measures (which were always in a fixed order). Participants
completed the demographic information last.
Results
Preliminary analyses
Table 1 shows descriptive statistics for the ERP-R, CFCS, CFCS-Feelings, ZTPI-F, and
measures of well-being.
Data reduction
Because the CFCS, CFCS-Feelings, and ZTPI-F likely tap into a similar
construct, we conducted factor analysis to derive a single factor representing futureoriented thinking, to be used in subsequent analyses. We conducted a principal axis
factor analysis on the three scale scores, with oblique rotation (direct oblimin; no
rotation was applied because only one factor was extracted). The Kaiser-Meyer-Oklin

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measure of sampling adequacy was adequate, KMO = .656, and KMOs for all three
variables were .613 or higher. Only one factor had an eigenvalue greater than 1, and it
explained 74.10% of the variance. Visual inspection of the scree plot further supported a
single factor solution, with factor loadings of .89, .89, and .57, for CFCS, CFCSFeelings, and ZTPI-F, respectively, suggesting a factor representing trait future focus.
Given that the three scales clustered on one factor, we used future focus factor scores
for trait future focus in subsequent correlational analyses.
We also conducted factor analysis to derive factors for the scales assessing wellbeing (SWLS, vitality, positive affect, negative affect, carefreeness, elevating
experience, experience of meaning, self-esteem, and self-connectedness). A principal
axis factor analysis of the scale scores with oblique rotation (direct oblimin) indicated
KMO = .869, with no KMOs for individual variables below .823. Two factors had
eigenvalues above 1, and the two factors explained 59.79% of the variance, with
carefreeness, negative affect, positive affect, and self-esteem, loading onto one factor,
and elevating experiences, experience of meaning, and self-connectedness loading onto
a second factor. Vitality and SWLS both loaded onto both factors (see Table 2 for factor
loadings). For simplicity of interpretability, we named these two factors Hedonic wellbeing and Eudaimonic well-being (notwithstanding recent debates about the validity of
the distinction between two forms of well-being, see Biswas-Diener, Kashdan, & King,
2009). We used factor scores for the two factors in our correlational analyses.
Correlations between consideration of future consequences and emotion regulation
We conducted Pearson correlation coefficients to assess the relationship between
future focus factor scores (based on the factor analysis described above) and scores for
down-regulating negative emotions and up-regulating positive emotions on the ERP-R.
Correlations are shown in Table 3.

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Future focus was significantly associated with down-regulation of negative
emotions. That is, participants with high future time focus reported more adaptive
regulation of negative emotions than participants with low future time focus. To
ascertain whether these associations were driven by the use of adaptive strategies,
maladaptive strategies, or both, we examined relations with stuck negative and focus
change. Although the correlation coefficients were small, future focus factor scores
predicted greater use of focus change strategies and less use of stuck negative strategies,
r = .24, p = .001, and r = -.22, p = .003, respectively.
For up-regulation of positive emotions, there were no significant associations
between savoring and dampening and future focus factor scores, both r’s < .10, p’s >
.27.
Finally, in an exploratory fashion, we examined associations between future
focus factor scores and specific regulatory strategies. Given the lack of associations
with positive emotion regulation described above, we focused on the strategies for
negative emotion regulation. Future focus was positively associated with reappraisal, r
= .21, p = .005, situation modification, r = .261, p < .001, and negatively associated
with acting out, r = .18, p = .02, and learned helplessness, r = .21, p = .004.. All other
associations were small (r’s < .135) and not significant.
Correlations between consideration of future consequences, emotion regulation,
and measures of well-being
We computed Pearson correlation coefficients between future time focus
measures and well-being, and between emotion regulation and well-being (Tables 3 and
4).
Future focus was negatively associated with the hedonic factor score but
positively associated with the eudaimonic factor score (Table 3). Thus, having a higher

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future focus predicted lower hedonic well-being, but higher eudaimonic well-being
scores. There was no association of future focus with the DASS. Regulation of negative
emotions and positive emotions were both associated with hedonic and eudaimonic
factor scores, as well as with the DASS, with more adaptive regulation of positive and
negative emotions predicting greater well-being and lower depression, anxiety, and
stress (Table 4).
Discussion
Study 1 was designed to examine the relation between trait-level thinking about
the future consequences of one’s behavior and emotion regulation choices and wellbeing. Overall, a future time focus predicted a more adaptive pattern of emotion
regulation: people who considered the future consequences of their actions were more
likely to select adaptive strategies (such as reappraisal and situation modification) and
less likely to select maladaptive strategies (such as acting out) when down-regulating
negative emotions. Future time focus also predicted well-being and, replicating past
work, emotion regulation choices were connected to well-being and mental health
(Nelis, Quoidbach, et al., 2011). Notably, thinking about the future consequences of
one’s actions was not reliably associated with choices of emotion regulation strategies
for positive emotion scenarios. However, while the current study was well-powered to
detect moderate associations (for r = .30, the required sample size to achieve power =
.95 is N = 115), it was underpowered to detect weak associations (for r = .10, the
required sample size to achieve power = .95 is N =1077). However, the results suggest
that if future focus does predict regulation of positive emotions, the association is weak.
The results extend previous research suggestive of an association between CFC
and responses to emotionally evocative situations (Boninger et al., 1994; BruehlmanSenecal et al., 2016; Joireman et al., 2003). A key strength of the current work over

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previous studies was that we assessed participants’ choices of a broad array of both
adaptive and maladaptive emotion regulation strategies in response to both negative and
positive scenarios.
The association between future time focus factor scores and eudaimonic wellbeing was moderate and positive. In addition, high future time focus weakly predicted
lower hedonic well-being. One consideration is that too extreme of a focus on the future
may reduce people’s enjoyment of present moment experiences and even result in
negative outcomes (e.g., workaholism) (Boniwell et al., 2010). Perhaps flexibly
considering both immediate and future outcomes of one’s behaviors would be
associated with optimal emotion regulation and well-being. Such a perspective
coincides with other work showing a relation between a balanced time perspective
(computed from scores from all sub-scales of the ZTPI) and well-being measures
(Boniwell et al., 2010; Zhang et al., 2013). We did not compute balanced time
perspective in the current study because there is considerable content overlap between
the other ZTPI sub-scales and emotion regulation items, which would likely inflate the
size of the correlations with emotion regulation. Future work could explore alternative
ways to measure flexibility in consideration of the immediate and future outcomes of
one’s behaviors to determine if flexibility, rather than a future focus alone, would be a
better predictor of emotion regulation and well-being.
Study 2
Study 1 suggested an association between the extent to which people consider
the future consequences of their behaviors and their reported emotion regulation
choices. However, we do not know if people might choose to use more adaptive
strategies because they are actually aware of the differential short- and longer-term
consequences of their regulatory choices. Therefore, in Study 2 we sought to determine

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to what extent people recognize that putatively adaptive and maladaptive strategies
differ in their immediate and future consequences. In one previously published study,
participants instructed to focus on either immediate or delayed consequences showed
differential preferences for distraction and reappraisal (Sheppes et al., 2014), suggesting
that people hold beliefs that different strategies have differential immediate and delayed
benefits. However, that study focused on only two strategies. In Study 2, we asked
participants to rate either the immediate or future effectiveness of eight different
strategies, both adaptive and maladaptive.
In Study 2, participants read the same scenarios as in Study 1 and were asked to
focus on either the immediate or future impacts of each strategy on their feelings. They
rated the effectiveness of each strategy, providing a more sensitive measure of beliefs
about regulatory outcomes than a binary variable of use/not use for each strategy.
Because we found reliable associations between thinking about future consequences and
regulation of negative emotions, but not positive emotions, in Study 1, Study 2 included
only negative scenarios. This approach also alleviated participant burden by reducing
the number of scenarios and strategies to which they were required to respond.
We predicted that participants would rate adaptive strategies as more effective in
the future than immediately, and maladaptive strategies as more effective immediately
than in the future.
Method
Participants
Participants were 80 students from introductory psychology courses at
Thompson Rivers University in Kamloops, BC. The research was approved by the
university Research Ethics Board. Participants gave informed consent and received 2%
bonus credit towards their grade. The mean age was 21 years (SD = 5.95). Fifty-six

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participants identified as female and 23 as male (no response: n = 1). Participants were
white (n = 64), black (n = 4), Hispanic (n = 3), First Nations (n = 2), Indian (n = 1),
Asian (n = 1), or mixed ethnicity (n = 4) (no response: n = 1).
Measures
Emotion Regulation Profile-Adapted. We adapted the original ERP-R (Nelis,
Quoidbach, et al., 2011) described above to assess the perceived effectiveness of each
response for each negative scenario. Specifically, participants rated how much better or
worse they thought each response would make them feel on a scale from 1 to 9 (1 =
much worse, 5 = no change, and 9 = much better).
Demographic information. Participants reported their age, gender, and
ethnicity.
Procedure
Participants were tested in groups of approximately 10 to 25 students. They were
randomly assigned to either the immediate or future focus condition. Participants in the
immediate focus condition were instructed to “…indicate what will be the immediate
impact of that response on your feelings. Don’t be concerned with the long-term effects
of that response. Rather, think about whether that response will make you feel
immediately better or worse.” Participants in the future focus condition were instructed
to “indicate what will be the long-term impact of that response on your feelings. Don’t
be concerned with the immediate or short-term effects of that response. Rather, think
about whether that response will make you feel better or worse in the long-term, later
that day and beyond.” After making the ratings, participants provided demographic
information.
Results
To test whether perceived effectiveness varied according to time focus

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(immediate or future) and strategy type (adaptive and maladaptive), we conducted a
mixed 2 x 2 ANOVA. The dependent variable was perceived effectiveness, collapsing
across the four specific adaptive strategies and collapsing across the four specific
maladaptive strategies. Overall, participants believed that adaptive strategies were more
likely to make them feel better than maladaptive strategies, F(1, 78) = 564.70, p < .001,
ηp2 = .88. There was no significant effect of focus, F(1, 78) = 0.48, p = .49, ηp2 = .006.
The main effect of strategy type was qualified by an interaction between strategy type
and time focus, F(1, 78) = 7.68, p = .007, ηp2 = .09. Participants rated adaptive
strategies as more effective in the future (M = 6.74, SD = 0.78) than immediately (M =
6.42, SD = 0.59), t(78) = 2.04, p = .022, d = .46, and maladaptive strategies as more
effective immediately (M = 3.54, SD = 0.72) than in the future (M = 3.09, SD = 0.82),
t(78) = 2.56, p = .006, d = .57 (applying the Bonferroni adjustment for multiple
comparisons, α = .05/2 = .025).
In order to test which strategies were driving these differences, we conducted
exploratory t-tests to assess differences in effectiveness ratings between the immediate
and future focus conditions for each strategy separately. Given the exploratory nature of
these analyses and the large number of t-tests conducted, we used two-tailed tests and
also applied the Bonferroni correction to use a more conservative alpha, α = .05/8 =
.006. For adaptive strategies, the effect was significant for positive reappraisal, only,
t(78) = 3.94, p < .001, d = 0.89, indicating that participants expected positive reappraisal
to be more effective in the future than immediately. For maladaptive strategies, the
effect was significant for substance use, t(78) = 4.05, p < .001, d = 0.92, and acting out,
t(78) = 3.05, p = .003, d = 0.69, indicating that participants expected both substance use
and acting out to be more effective immediately than in the future. In sum, for adaptive
strategies, the perceived effectiveness of reappraisal drove the higher ratings for future

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versus immediate focus. For maladaptive strategies, the perceived effectiveness of
substance use and acting out drove the higher ratings for immediate versus future focus.
Discussion
In Study 2, we tested the effects of time focus (immediate or future) on
perceived effectiveness of emotion regulation strategies. The results lend support to the
conclusions from Study 1, suggesting that people have some knowledge about the
differential immediate and delayed consequences of different strategies. In Study 2,
adaptive strategies were perceived to be more effective for improving feelings overall.
Moreover, people believed that adaptive strategies would be more likely to make them
feel better in the future than immediately, but that maladaptive strategies would be more
likely to make them feel better immediately than in the future. These effects did not
hold across all specific strategies. Rather, for adaptive strategies, positive reappraisal
was believed to have greater future than immediate benefits. For maladaptive strategies,
it was primarily acting out and substance abuse that were believed to have more
immediate than future benefits. Given the exploratory nature of these strategy-level
analyses, these results should be interpreted with caution. Furthermore, while Study 2
was adequately powered to detect large effects (for d = 0.80 and power = .95, a sample
size of N = 70 is required), it was underpowered to detect small to medium effects.
Therefore, further research is needed to ascertain beliefs about the differential
immediate and future consequences of specific regulatory strategies.
General discussion
Together, Studies 1 and 2 show that people’s emotion regulation preferences are
guided in part by the extent to which they consider the future consequences of their
behaviours and also that people believe that strategies differentially achieve immediate
versus future changes in feelings. In Study 1, future time focus correlated positively

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with adaptive down-regulation of negative emotions (especially reappraisal and
situation modification) and negatively with maladaptive down-regulation of negatives
emotion (especially acting out). In Study 2, prompting people to focus on future rather
than immediate changes in feelings resulted in higher perceived effectiveness for
adaptive strategies (especially for reappraisal), and lower perceived effectiveness for
maladaptive strategies (especially for acting out and substance abuse). Thus, we
observed some overlap between the types of strategies that people who consider future
consequences prefer to employ and people’s beliefs about the immediate and future
benefits of different regulatory strategies.
Although the strategy-specific analyses were exploratory, the findings mesh
with the research literature showing enduring benefits of adaptive strategies like
reappraisal (Denson, Moulds, & Grisham, 2012; Gutentag, Halperin, Porat, Bigman, &
Tamir, 2016; Ray, Wilhelm, & Gross, 2008; Thiruchselvam, Blechert, Sheppes,
Rydstrom, & Gross, 2011) and situation modification (Billings & Moos, 1981; DixonGordon, Aldao, & De Los Reyes, 2014; Schäfer, Naumann, Holmes, Tuschen-Caffier,
& Samson, 2017; Schutte, Manes, & Malouff, 2009). The findings also converge with
research illustrating the potentially detrimental consequences of substance use (Single,
Rehm, Robson, & Truong, 2000) and learned helplessness (Bargai, Ben-Shakhar, &
Shalev, 2007; C. I. Diener & Dweck, 1978). In addition, the findings are consistent with
prior research suggesting that although acting out is not an effective way to decrease
negative feelings, people do tend to believe that it reduces angry feelings (Bushman,
2002; Bushman, Baumeister, & Phillips, 2001).
Notably, participants expected attention reorientation to be equally effective in
the short- and long-term, in spite of research evidence that its benefits are short-lived
(Denson et al., 2012; Kross & Ayduk, 2008; Thiruchselvam et al., 2011). People might

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not be aware of the limited benefits of distraction, though this seems unlikely, given that
other research has shown that when given the choice to use distraction or reappraisal,
people are more likely to choose distraction when given short-term, rather than longterm, regulatory goals (Sheppes et al., 2014). Rather, it may be that the effects of
distraction are modulated by other, contextual variables, such as personality, event
significance, or stimulus intensity (cf. Sheppes & Gross, 2011). Furthermore, it is
important to consider that people typically do not use a single emotion regulation
strategy in isolation (Heiy & Cheavens, 2014). Using distraction may lay the
groundwork for the use of other strategies that are more effective in the long-term.
For the other emotion regulation strategies assessed—emotion expression,
rumination, and expression suppression—there was also no clear-cut association with
CFC and no effect of the immediate/future focus manipulation. Perhaps these strategies
are not differentially effective in the short- versus the long-term. Indeed, rumination
maintains negative feelings (Aldao et al., 2010; Clancy, Prestwich, Caperon, &
O’Connor, 2016; Denson et al., 2012; Schäfer et al., 2017). Expression suppression has
been found to be maladaptive in the short- and long-term (Cameron & Overall, 2017;
Chervonsky & Hunt, 2017). Social sharing of feelings (emotion expression) appears to
be beneficial both in the short- and long-term (Cameron & Overall, 2017; DixonGordon et al., 2014; Lepore, 1997; Lepore, Ragan, & Jones, 2000).
Limitations and future research
We report preliminary findings of a connection between a future time focus and
emotion regulation choices. Our results open up several avenues for subsequent
research. First, in our studies, participants reported their choices of and beliefs about a
limited number of responses to several scenarios. Given that we found a relationship
between future focus and emotion regulation in these contrived instances, the effect may

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be even stronger in real life situations when people are actually required to regulate
their emotions. However, people’s self-reported preferences in the current study may
not correspond with their actual regulatory behaviors: they may just be responding
according to what they believe is best in a situation, not what they would actually do.
Nonetheless, the ERP-R has good validity both in correlational and experimental studies
(Nelis, Kotsou, et al., 2011; Nelis, Quoidbach, et al., 2011). Future work should
examine how both trait-level CFC and experimentally-manipulated future focus relate
to emotion regulation choices in the face of experienced emotion-eliciting events (cf.
Sheppes et al., 2014). Furthermore, ecological momentary assessment could assess how
both trait-level and state-level time focus predict emotion regulation choices in
everyday life.
Second, future work should examine how other contextual variables, such as
goals, personality, and stimulus characteristics, interact with CFC to impact emotion
regulation choices in real-world situations. For example, people prefer reappraisal over
distraction when emotional events are of low intensity, and vice versa under conditions
of high intensity (Sheppes et al., 2014; Sheppes, Scheibe, Suri, & Gross, 2011). This
effect may be moderated by CFC, such that those who consider the future consequences
of their behaviors are even more likely to choose reappraisal under conditions of low
intensity, given reappraisal’s more favorable outcomes for long-term changes in affect.
Such hypotheses could be tested both in laboratory settings and using ecological
momentary assessment.
A third direction pertains to the use of the CFCS in this work. Although the
original, 12-item CFCS appeared to be unidimensional (Strathman et al., 1994), recent
research has differentiated between immediate and future concerns (CFC-14; Joireman
et al., 2012). Distinguishing between concern for immediate versus future consequences

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might enhance our understanding of the connection with emotion regulation. For
example, people may be more likely to act out angrily either because they are concerned
with immediate consequences, or because they are not concerned with future
consequences, or both. Similarly, choice of reappraisal may be driven by a lack of
concern with immediate consequences, a heightened concern for future consequences,
or both. Furthermore, Joireman and King (2016) identified at least four different
mechanisms by which CFC may be connected to self-regulatory behaviors. Uncovering
which of these mechanisms are involved in guiding emotion regulation is important not
just from a theoretical standpoint, but also for enabling the development of interventions
to facilitate healthy emotion regulation. For example, according to the awareness model
(Joireman & King, 2016), the effect of CFC on behavior is mediated by an awareness of
the consequences of one’s actions. If the awareness model holds, it would favor
interventions that emphasize training increased awareness of emotion regulation choices
and their outcomes. Other mechanisms would suggest that other types of interventions
are more likely to be effective.

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26

Acknowledgements
This work was supported by the Social Sciences and Humanities Research
Council of Canada [grant number 430-2014-00626]. The authors thank Allister Grapes
for his assistance with data collection.

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27

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Table 1. Descriptive statistics for consideration of future consequences, regulation of
negative and positive emotions, and measures of well-being.
M

SD

CFCS

42.00

6.72

CFCS-Feelings

40.96

7.52

ZTPI-F

3.55

0.60

5.79

8.01

Focus change

14.07

5.89

Stuck negative

7.87

5.31

Regulation of positive emotions

8.05

7.02

Savouring

13.00

5.46

Dampening

3.00

3.86

Life satisfaction

22.09

6.10

Vitality

3.85

1.20

Positive affect

4.83

1.02

Negative affect

3.41

1.08

Carefreeness

3.64

0.95

Elevated

3.86

0.89

Self-connected

5.04

1.02

Self-esteem

4.00

1.53

Meaning

5.01

1.18

DASS Mean

3.30

1.91

Future thinking

Regulation of negative emotions

Well-being

Note. CFCS = Consideration of Future Consequences Scale; ZTPI-F = Zimbardo Time
Perspective Inventory Future subscale. Focus change = adaptive strategies for
regulation of negative emotions (positive reappraisal, attention reorientation, emotion
expression, situation modification); stuck negative = maladaptive strategies for
regulation of negative emotions (rumination, acting out, substance abuse, learned
helplessness); savouring = adaptive strategies for regulation of positive emotions
(behavioural display, savouring the moment, capitalizing, positive mental time travel);

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dampening = maladaptive strategies for regulation of positive emotion (inhibition of
emotion expression, fault finding, inattention, negative mental time travel). DASS =
Depression Anxiety Stress Scales.

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Table 2. Factor loading for well-being items
Factor 1

Factor 2

Carefreeness

.781

-.083

Negative affect

-.729

.080

Positive affect

.586

.285

Vitality

.472

.440

Self-esteem

.405

.212

Life satisfaction

.404

.334

Elevated

-.080

.816

Meaning

.025

.688

Self-connected

.053

.481

Note. Factor loadings > .3 appear in bold.

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Table 3. Pearson’s correlations between future focus and regulation of positive and
negative emotions, well-being, and DASS.

Regulation of negative emotions

Future focus
factor score
.31**

Regulation of positive emotions

.10

Hedonic

Eudaimonic

DASS

.34**

.27**

-.32**

.27**

.35**

-.22**

Well-being
Hedonic factor score

-.21**

Eudaimonic factor score

.37**

DASS-Mean

-.05

Note. * p < .05 (one-tailed) ** p < .01 (one-tailed). Focus change = adaptive strategies
for regulation of negative emotions (positive reappraisal, attention reorientation,
emotion expression, situation modification); stuck negative = maladaptive strategies for
regulation of negative emotions (rumination, acting out, substance abuse, learned
helplessness); savouring = adaptive strategies for regulation of positive emotions
(behavioural display, savouring the moment, capitalizing, positive mental time travel);
dampening = maladaptive strategies for regulation of positive emotion (inhibition of
emotion expression, fault finding, inattention, negative mental time travel); DASS =
Depression Anxiety Stress Scales.

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Table 4. Pearson’s correlations among regulation of positive and negative emotions,
well-being, and DASS.
Eudaimonic
factor score
.27**

DASS

Regulation of negative emotions

Hedonic
factor score
.34**

Regulation of positive emotions

.27**

.35**

-.22**

-.32**

Note. * p < .05 (one-tailed) ** p < .01 (one-tailed). DASS = Depression Anxiety Stress
Scales.

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Figure 1. Perceived effectiveness ratings (1 = much worse, 5 = no change, 9 = much
better) for adaptive (Panel A) and maladaptive (Panel B) strategies, by immediate and
future focus. Attn Reor = attention reorientation; Reapp = reappraisal; Sit mod =
situation modification; Expr = emotion expression; Rumin = rumination; Act out =
acting out; Subst = substance use; Helpless = learned helplessness.

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