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Personal goals are ubiquitous in everyday life, with people typically pursuing multiple personal goals at any given time. This paper provides a review and synthesis of the vast and varied research on personal goals. A growing body of research shows that goals are best conceptualized as a distinct unit of analysis, with extensive within-person variations in both goal characteristics and attainment. In this paper, we review existing literature on personal goals, examining the process of goal pursuit from start to finish, including goal setting, goal pursuit and selfregulation, and the outcomes associated with attainment and/or failure. We also address the many aspects of personal goal pursuit that are still poorly understood, highlighting directions for future research.
Running head: GOAL PURSUIT
Goal pursuit: Current state of affairs and directions for future research
Marina Milyavskaya
Kaitlyn M. Werner
Carleton University
In press at Canadian Psychology/Psychologie Canadienne
© 2018, Canadian Psychological Association. This paper is not the copy of record and may not
exactly replicate the final, authoritative version of the article. Please do not copy or cite without
authors permission. The final article will be available, upon publication, via its DOI:
Marina Milyavskaya,
Department of Psychology, Carleton University,
Loeb B550, 1125 Colonel By Drive
Ottawa, Ontario, Canada, K1S 5B6
Personal goals are ubiquitous in everyday life, with people typically pursuing multiple personal
goals at any given time. This paper provides a review and synthesis of the vast and varied
research on personal goals. A growing body of research shows that goals are best conceptualized
as a distinct unit of analysis, with extensive within-person variations in both goal characteristics
and attainment. In this paper, we review existing literature on personal goals, examining the
process of goal pursuit from start to finish, including goal setting, goal pursuit and self-
regulation, and the outcomes associated with attainment and/or failure. We also address the
many aspects of personal goal pursuit that are still poorly understood, highlighting directions for
future research.
Keywords: goal pursuit, personal goals, self-regulation, motivation
Goal Pursuit: Current State of Affairs and Directions for Future Research
We all have various goals that we are trying to accomplish – lose 10lbs, stop smoking,
find a new job, be kinder to our partner, or finish that paper by the end of the week. Whether
these pursuits can be attained within a specific time or are on-going tasks that need to be
maintained across our lives, such goals occupy a large portion of our time and mental energy.
Given the centrality of goals in our everyday lives, it is no wonder that goals are studied across a
variety of sub-disciplines, including (but not limited to) social, personality, organizational,
cognitive, health, education, sport, and developmental psychology, as well as allied fields such as
behavioural economics and neuroscience. Within these fields, goals have been studied on a
variety of different levels, from the speed of button presses or problem solving in a lab setting
(e.g., Brandstätter, Lengfelder, & Gollwitzer, 2001; Freitas, Liberman, & Higgins, 2002) to
engagement in specific health behaviours (e.g., Gollwitzer & Oettingen, 1998), educational and
occupational attainment (e.g., Elliot, McGregor, & Gable, 1999), and navigation of broader life
tasks (e.g., Emmons, 1986; Kasser & Ryan, 1996). While this diversity has certainly led to a
variety of notable advancements that help us understand the goal pursuit process, it has also
resulted in a fragmented literature that is difficult to reconcile. Despite this issue, one underlying
notion that seems to be well agreed upon is that people have multiple personal goals that they are
simultaneously motivated to attain. While such goals can be studied at a variety of levels (e.g.,
my goal to lose weight can be linked to my broader value of living a healthy life), this review
predominantly focuses on personal goals that are pursued in an individual’s day-to-day life.
Specifically, we will examine the process of goal pursuit from start to finish, including goal
setting, goal pursuit and self-regulation, and the outcomes associated with attainment and/or
failure. We also address the many aspects of personal goal pursuit that are still poorly
understood, highlighting directions for future research.
Personal Goals
The disparate ways in which goals are studied can also be seen in the proliferation of goal
definitions (see Elliot & Fryer, 2008, for a review). In the present paper, we define a goal as
being a cognitive representation of a desired end state that a person is committed to attain. This
definition highlights three key components. First, cognitive representation refers to the use of a
future-oriented image to make decisions that ultimately guide an individual’s behaviour. This is a
critical distinction to make, as some previous theory and research has equated having a goal with
general behaviour, innate biological responses (e.g., neurons firing; Austin & Vancouver, 1996),
or even going so far as to say, “in some sense, the endpoint of every action, however minute, is a
goal” (Beach, 1985, p. 124). By focusing on mental representations we emphasize that goals are
limited to sentient beings, and exclude more mechanistic functions (e.g., plants orienting towards
sunlight; Elliot & Fryer, 2008). Second, desired end state implies that there is some thing that an
individual wants1 to move toward or attain (whether it is more abstract or concrete). Without this
drive, goals would not have any energy to encourage action or sustain motivation, and instead we
would wander around aimlessly engaging in behaviours without any sense of meaning or
purpose. Finally, we draw on the term commitment to further distinguish between goals and
wishes and/or fantasies (Gollwitzer, 1990). Underlying the term commitment is intent, without
which an individual would not be motivated to move toward the desired end state. Given that we
are specifically interested in personal goals that individuals set and pursue in the course of their
day-to-day lives, we further define personal goals as those explicitly identified and endorsed by
1 Here we refer to “want” as a more general term without assigning any specific motivational
properties (e.g., want-to versus have-to motivation, which we discuss later on).
an individual, as opposed to goals either assumed to exist or explicitly assigned by a researcher
(e.g., solving anagrams in a lab task; broader health goals assumed to exist in health research).
Goals as a Unit of Analysis
One implicit assumption in the existing literature is that goal pursuit unfolds in a similar
way across all goals. This is evident in studies that prime different goals, as the prime is assumed
to facilitate similar behaviour for all people (e.g., priming achievement would lead everyone to
perform better; Custers & Aarts, 2010), or studies that examine one specific goal and draw broad
conclusions about the mechanisms of general goal pursuit (e.g., Bandura & Wood, 1989). The
underlying assumption here is that all people value and pursue the same goals (or types of goals),
therefore leading to similar behavioural responses. One approach to counter this assumption is to
use an idiosyncratic approach, whereby participants are asked about the various goals that they
pursue in their daily lives (e.g., Little, 1983; Emmons, 1989). While this approach starts to move
the field in the right direction, researchers have tended to aggregate across all elicited goals in
order to understand how their aggregated properties influence goal attainment (e.g., Emmons &
King, 1988; Little, 1983; Sheldon & Elliot, 1999). Thus, even though researchers obtain a wealth
of information regarding the specific characteristics for each individual goal (e.g., commitment,
motivation, progress), a lot of this information gets lost. Historically, this approach was in part
due to the complexity of statistical methods required to analyse these goals separately. However,
this is no longer the case, as technological advances have given rise to statistical software
specifically designed to conduct multilevel analyses. That is, since each person typically pursues
multiple goals, these goals can be considered ‘nested’ within the person, with analyses
distinguishing the variability due to differences between people (i.e., how Mark’s goals generally
differ from Julie’s goals), and the variability across one person’s goals (i.e., how Julie’s goals
differ one from one another; Raudenbush & Bryk, 2002).
Based on recent research using this updated nested approach, results consistently suggest
that most of the variance in goal characteristics is at the within-person (goal) level. For example,
studies asking about goal motivation find that approximately 60 to 80% of the variance is at the
within-person level (Holding, Hope, Harvey, Marion Jetten, & Koestner, 2017; Milyavskaya,
Inzlicht, Hope, & Koestner, 2015; Werner, Milyavskaya, Foxen-Craft, & Koestner, 2016).
Similarly, Nurmi and colleagues (2009) found that appraisals of personal goals on multiple
dimensions (such as importance, commitment, meaning) vary predominantly within-person –
only 5-24% of the variation in these appraisals is between individuals, whereas the
overwhelming majority of variance is among goals within the same person. Importantly, research
that examines progress across time also finds that approximately 80 to 95% of the variance in
goal attainment is at the within-person level (Holding et al., 2017; Milyavskaya & Inzlicht, 2017;
Milyavskaya et al., 2015; Werner & Milyavskaya, 2017; Werner et al., 2016). By aggregating
across goals, researchers ignore this variability. Instead, a growing body of research suggests that
the appropriate level of analysis for understanding goal pursuit is at the goal level.
The Process of Goal Pursuit
Research has long distinguished between different phases of goal pursuit, beginning with
Lewin, Dembo, Festinger, and Sears (1944) who differentiated between goal setting and goal
striving. Others have elaborated on this distinction by positing a process of goal pursuit that
changes across time. For example, Little (1983) proposed that personal projects, which are akin
to personal goals, progress through four stages: inception, planning, action, and termination.
Similarly, the Rubicon Model of Action Phases (Gollwitzer, 1990; Heckhausen & Gollwitzer,
1987) proposes that goal pursuit progresses through four distinct, temporally defined phases. In
the predecisional phase, an individual is considering options and evaluating their wishes and
desires. Once an individual generates an intent to pursue a given goal, they “cross the rubicon”
into the preactional phase, where they then decide on the details of how, when, and where they
will pursue the goal. This then leads to the actional phase, where the individual enacts these
plans and engages in activities aimed to attain the desired end state. The actional phase leads to a
concrete outcome (attainment or failure), which then results in a post-actional re-evalution of the
goal and its related actions, thereby serving to guide future goal pursuit.
Although these four phases are theoretically distinguishable, much research has retained
Lewin’s original distinction between goal setting and goal striving. Here, we will focus our
review on these phases of the goal pursuit process, as well as the possible ensuing outcomes
(attainment, abandonment, resetting). Additionally, we propose that the process of goal pursuit is
not always linear, but instead can frequently be cyclical, as goals can be adjusted rather than
attained or abandoned, and the result of either attainment or abandonment often feeds into
decisions regarding new goals.
Goal Setting
In our day-to-day lives we are constantly bombarded with a plethora of potential goal-
related stimuli – so how do people decide what goals to actually pursue? According to past
research, the simple answer to this question is: we pursue what we wish, so long as it is
something that we can realistically expect to attain. In more scientific terms, people decide what
goals they will pursue based on desirability (the value of attaining the goal) and feasibility (the
likelihood that the goal could be attained). These have also been termed value and expectancy
(Wigfield & Eccles, 2000). Together, the multiplicative combination of feasibility/expectancy
and desirability/value has been referred to as ‘expected utility’ (Locke & Latham, 2002), with
potential goals with the highest expected utility adopted as personal goals to be pursued.
Going further back, the wishes, as well as their associated assessments of desirability and
feasibility, must come from somewhere. That is, both the content of the goal itself and the
underlying reasons for setting and pursuing the goal must be grounded in a person’s previous
experiences, as well as current constraints. However, very little research and theory looks at the
origin of goals. In the organizational and sports psychology literatures, goals are often assumed
to be assigned by others (e.g., a supervisor or a coach; Kernan & Lord, 1988), although some
researchers suggest that such assigned goals may be meaningless until they are internalized
(Austin & Vancouver, 1996). Additional research has proposed that our upbringing, personality,
and lay theories of the world influence the content of our goals. For example, research on
parenting has shown that what our parents value and how they relate to us can shape our desires
(e.g., Soenens, et al., 2015). Other research focuses on how personality may shape the nature of
our goals – for example, individuals with a promotion focus would be more likely to set
approach/promotion goals (Higgins, 1998). Give that goals are often domain-specific (i.e.,
academic, work, relationship, etc.), certain characteristics of the domains can also influence the
goals that people set. For example, research finds that a person will set more autonomous goals
in domains where they experience greater satisfaction of the basic psychological needs for
autonomy, competence, and relatedness (compared to other domains; Milyavskaya, Nadolny &
Koestner, 2014). Similarly, our feelings of self-efficacy (both general and domain-specific)
directly influence the feasibility dimension, such that when we experience greater self-efficacy
we feel better able to achieve desired outcomes (Bandura, 1989; Pajares, 1996). Expectancy and
value can also come from previous experiences within a domain or with a goal, promulgating the
cyclical nature of the goal pursuit process. For example, if Jill sets a goal of getting an A in Math
class, but subsequently gets a B, she may revise her expectations the following semester and aim
for a B+ (instead of an A).
Characteristics of Personal Goals. Each goal that a person decides to pursue can be
considered along a number of dimensions, or characteristics (Little, 1983; Little, Salmela-Aro, &
Phillips, 2006). While some researchers are interested in the constellations of such characteristics
(e.g., McGregor & Little, 1998), most of the research that actually examines progress focuses on
one or two features, ignoring others (e.g., McGregor et al., 2006). We now review some of the
most frequently studied characteristics; this list is by no means complete, but represents the most
common features of goals that are examined in the personal goal pursuit literature. Indeed, the
personal projects paradigm identifies a comprehensive variety of 27 characteristics, including
goal importance, enjoyment, commitment, time adequacy, challenge, and difficulty (Little, 1983;
Little et al.,2006). Although discussing all these in detail is outside the scope of this brief review,
we will briefly outline some of them here. For a more detailed discussion, see Austin and
Vancouver (1996) and Fujita and MacGregor (2012).
One important distinction is between abstract and concrete goals (Fujita & MacGregor,
2012). Abstract goals are broader or more general goals (e.g., be less selfish) that typically
involve numerous actions in multiple contexts, and often do not have a concrete end point
signalling that the goal is ‘attained.’ These goals generally encompass one’s broader identity and
values (Kasser & Ryan, 1996, Schwartz, 1992), and, in models where goals are hierarchically
organized, have been proposed to represent the highest levels of the hierarchy (Carver & Scheier,
1982). Concrete goals, on the other hand, are specific actions that are often carried out during a
specific context or time (e.g., go to the gym today), and most importantly, usually (although not
always) have a concrete end point. Another similar characteristic is the degree of specificity,
which has been typically studied in the organizational literature (Locke, Chah, Harrison, &
Lustgarten, 1989). This research frequently finds that more concrete goals are more likely to be
attained (See Locke & Latham, 2002). However, the relation between goal abstraction/specificity
and goal attainment has not been examined for personal goals set and pursued outside of a lab
setting, so it is unknown how generalizable these results are to real-world experiences.
In the organizational literature, Goal Setting Theory (Locke & Latham, 2002, 2013)
further posits that goal difficulty is a key factor in determining performance, such that people put
in more effort and perform better when they pursue difficult yet attainable goals. Although
extensive support for this theory is available (see Locke & Latham, 2002), the research either
uses lab studies (with performance goals such as solving a certain number of anagrams; Erez &
Judge, 2001), and/or goals set by other people (the researcher, boss, or coach). However, it is
unknown whether goal difficulty would similarly affect progress on idiosyncratic personal goals.
Another aspect of personal goals concerns their aim, or the direction toward which a goal
is focused – towards or away from some end state. Approach and avoidance motivation have
been deemed a fundamental component of motivation and behaviour, such that people tend to
move toward positive stimuli and move away from negative stimuli (Elliot, 1999). While
approach and avoidance can be conceptualized at a variety of levels (e.g., personality, neural
underpinnings), at the personal goal level the idea is that people tend to approach desirable end-
states and avoid undesirable end-states. For example, a student may have the goal to do well on
the upcoming test, or to avoid failing it. An extensive body of research indicates that approach
goals are more likely to be attained and lead to a host of positive outcomes (e.g., well-being,
performance) compared to avoidance goals (Elliot, Sheldon, & Church, 1997; Elliot et al., 1999).
However, one recent study using a goal-specific approach and Bayesian analyses found very
strong evidence in support of a null effect for both approach or avoidance motivation on goal
progress (Werner, Milyavskaya, & Koestner, 2017).
Quality of Motivation. One of the most frequently studied features of personal goals is
the person’s motivation for pursuing and attaining the goal. While the amount of motivation an
individual has can partially predict behaviour (Wigfield & Eccles, 2000), there is a qualitative
difference in the types of motivation that one may have. Research in Self-Determination Theory
contrasts autonomous motivation for pursuing a personal goal with controlled motivation (Deci
& Ryan, 2000; Koestner, Otis, Powers, Pelletier, & Gagnon, 2008). Autonomous motivation is
when an individual pursues a goal out of inherent interest or personal importance, whereas
controlled motivation occurs when pursuing a goal for external reasons, such as to please others,
obtain rewards, or avoid guilt or shame. In essence, autonomous goals (also termed self-
concordant; Sheldon & Elliot, 1999) are pursued because it is something that an individual
genuinely wants to do, whereas controlled goals are pursued because they feel they have to
(Milyavskaya et al., 2015). While controlled goals are still likely to be personally set and
endorsed, such pursuits are self-discrepant and do not reflect what the individual truly wants,
thereby resulting in lower quality motivation and detracting from goal attainment. Indeed, a large
body of literature now confirms that autonomous goals are more likely to be attained (see Ryan
& Deci, 2017 for a recent review). However, the role of controlled motivation is less clear: some
studies show a negative effect of controlled motivation on goal attainment, while others show no
effect, and many studies treat autonomous and controlled motivation as a continuum (rather than
as two separate dimensions), making the examination of the distinction more difficult.
Relation to Other Goals. Most goals that a person sets are related to other goals,
whether it be a short-term goal set in the service of a broader goal (facilitating), or a goal that
conflicts with another goal (e.g., by competing for time or other resources). Some research that
has examined the degree of conflict or facilitation among pairs of goals finds that people are less
likely to act on goals that actively conflict with other goals (Emmons & King, 1988). Others
have shown that facilitation and interference are not simply two sides of a continuum, but are
instead two separate dimensions. In line with this idea, 2018-04-02 3:50:00 PM find that only
facilitation is related to goal pursuit, while interference is unrelated to goal pursuit, and instead
contributes to lower well-being.
Besides simply looking at the interference among goals, many theories have been
proposed to explain how goals are organized and influence one another. For example, according
to Control Theory (Carver & Scheier, 1982), goals are nested within each other at progressively
more abstract levels of generality, with more abstract goals (i.e., our identity and values) guiding
the standards that we set as our subordinate goals. Most goals that we consciously set and pursue
in our day-to-day lives are at the intermediate levels of the hierarchy. Indeed, most theories (e.g.,
Control Theory, Carver & Scheier, 1982; Goal Systems Theory, Kruglanski et al., 2002) suggest
that goals are organized hierarchically, with short-term goals acting as means in the service of
broader goals. Alternative perspectives, however, highlight different aspects of goal
organization: Cognitive models (e.g., accessibility theory, Higgins, Rholes, & Jones, 1977;
spreading activation theory, Collins & Loftus, 1975) propose that goals, like other cognitive
representations, are organized as a network. Others view goals as sequential, based on the timing
of the goals (e.g., Heckhausen, Wrosch, & Schulz, 2010). While hierarchical theories are the
most prevalent in the literature, they have not been adequately tested outside of the lab. Recent
research also suggests that lay people’s perception of how their own goals are organized are
more in line with the networks and sequential perspectives (Kung & Scholer, 2016).
Goal Pursuit
Once an individual is committed to pursuing a goal, self-regulatory processes take over to
carry out its pursuit. Self-regulation, or the process of working towards a goal, can be viewed as
a discrepancy-reducing feedback loop (Carver & Scheier, 1982). Using the goal as a reference, a
person compares their present state to the desired end state (i.e., “am I on track for my goal?”). If
a discrepancy is detected, the person acts to reduce this discrepancy, thereby engaging in goal-
promoting behaviour. Other than taking direct steps towards the desired end-state (e.g., going to
the gym, eating healthy food, studying for a midterm), people also plan for how they will pursue
the behaviour, monitor progress to ensure that they are on track, and shield against distractions.
Although self-regulation frequently requires effort, the process of goal pursuit can also unfold
automatically, requiring less or no effort. Finally, individuals must navigate multiple goals,
balancing time and resources to pursue multiple goals that invariably influence one another.
Planning. Broader goals (e.g., get an A in biology class) can be broken down into
smaller actions needed to achieve this goal – for example, attend the lecture today or read 20
pages from the textbook this week. These have variously been called steps, subgoals, or means
(e.g., Houser-Marko & Sheldon, 2008; Kruglanski et al., 2002), and are usually more concrete
than the broader goal, but can also be personal goals in their own right. Research has shown that
focusing on such smaller concrete steps can be beneficial, particularly at the start of goal pursuit,
so that each step is viewed as making (relatively) greater progress (Koo & Fishbach, 2012).
One way of breaking down a goal into specific, contextualized actions is by setting
implementation intentions (Gollwitzer, 1999), which are specific if-then plans that serve to
associate a goal-promoting response with a situational cue. For example, ‘if I crave a cigarette,
then I will chew gum instead” or “after class on Tuesdays I will go to the gym”. Because an
individual already has a pre-determined response to a given situation, they do not have to waste
time, energy, or resources coming up with a response in the moment, which helps to shield
against desirable temptations or distractions. Research consistently finds that when people are
asked to make such plans for their goals, they are more likely to attain them (Gollwitzer &
Sheeran, 2006), and that those goals for which a person has a concrete plan are more likely to be
attained (compared to other goals). Although such plans are undoubtedly beneficial, it is still
unclear how frequently people spontaneously set specific implementation intentions.
Monitoring and Adjusting to Feedback. Given the central role of feedback in the self-
regulation process, an important component of goal pursuit is how people obtain and react to
feedback. One way of obtaining feedback is by actively monitoring progress. By identifying
discrepancies between the current and desired states, a person can recognize when they fall short
and more effort is needed. Alternatively, instead of directly monitoring progress towards a goal,
a person can monitor behaviours relevant to the goal (e.g., if the goal is to lose weight, going to
the gym may be a behaviour performed in the service of the goal). A recent meta-analysis found
that interventions that prompt participants to monitor their progress had a small-to-medium effect
(d = .40) on goal attainment, and that monitoring progress more frequently is directly related to
greater goal attainment (Harkin et al., 2016). Furthermore, prompts to monitor outcomes (rather
than behaviours) led to greater goal progress, while monitoring only behaviour (but not outcome)
did not reliably affect goal progress. This research also found that monitoring was more effective
when the information was recorded and when it was made public (Harkin et al., 2016).
In addition to negative feedback signalling that more effort is needed, positive feedback
(i.e., that progress is being made at an acceptable pace) can play a role in goal pursuit (Fishbach,
Eyal, & Finkelstein, 2010). If positive feedback signals that sufficient progress is being made, it
can lead to (temporary) disengagement from goal pursuit and instead enact coasting behaviours
(Carver, 2003). In other words, if an individual is doing a good job in pursuing their goal, they
may start to slowly ease away from the determined pursuit of their goal. Alternatively, positive
feedback can also boost levels of self-efficacy and signal higher levels of commitment (Bandura
& Cervone, 1983). For example, a student envisioning a STEM career who receives positive
praise from her math teacher may think, “maybe I can do well in this subject, maybe math is for
me after all”, thus intensifying her future efforts and eventually leading her to make more
progress on the goal of pursuing a career in STEM. The effects of positive (and negative)
feedback may thus depend on whether the feedback is interpreted as providing information about
commitment or progress; such interpretation depends on the amount of experience that a person
has with a given goal or goal domain. When there is little experience in a goal domain, people
are especially attuned to signals of commitment (e.g. ‘Is this for me? Can I actually do this?’),
whereas with more experience people shift to focus on progress (e.g., ‘How am I doing? What
can I do to do better?’; Fishbach et al., 2010). This is also evident in the type of feedback that
people seek as they progress – when starting on a new goal a person is more likely to seek
positive feedback, but as commitment and expertise become more established they are more
likely to seek more constructive negative feedback related to progress (Finkelstein & Fishbach,
Resisting Temptations. In addition to comparing one’s present state to the desired goal
and enacting behaviours to attain the goal, people must also shield themselves from immediate
tempting desires that threaten goal pursuit. A desire is “an affectively charged motivation toward
a certain object, person, or activity that is associated with pleasure or relief from displeasure”
(Hofmann & Van Dillen, 2012). When a desire conflicts with a longer-term goal, it represents a
temptation that, if indulged, can derail goal pursuit (Hofmann et al., 2012). When desires are
strong, resistance (i.e., effortful self-control) needs to be applied to refrain from indulging in the
desire. The more a desire conflicts with an important goal, the more effortful self-control will
need to be applied, and the more likely that the desire will be successfully resisted (Hofmann et
al., 2012). Some models propose that we (either consciously or unconsciously) evaluate the value
of indulging on one hand and of the broader goal on the other. The result of this valuation
process determines the outcome, as the option with the greatest ‘value’ (across multiple value
sources) is enacted (Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017). Additionally,
experiencing the temptation itself can sometimes remind us of our goals, strengthening the value
of the goals and lessening the value of temptation (Fishbach, Friedman, & Kruglanski, 2003).
Effortless Self-Regulation. An alternative perspective on self-regulation and goal pursuit
is that it can occur automatically (Fitzsimons & Bargh, 2004), effortlessly (Gillebaart & de
Ridder, 2015; Werner et al., 2016), or habitually (Wood & Neal, 2007). That is, instead of
consciously exerting effortful self-control to promote goal-directed behaviour, people frequently
take steps toward their goals in an automatized manner, as a function of responding to situational
cues. Although controversial (see Cesario, 2014), research on goal priming suggests that simply
activating a mental representation of a goal can lead people to act in goal-directed ways (e.g.,
Chartrand & Bargh, 1996). More established research on implementation intentions finds that it
is possible to automatize goal pursuit by linking a behaviour to cues in the environment, such
that the behaviour begins to automatically occur when the cue is encountered. Research has also
shown that people are more likely to set implementation intentions when a goal is autonomous
(Koestner et al., 2002). Goal autonomy has also been linked with more effortless goal pursuit in
a study contrasting effortful (“I tried really hard”) and effortless (“it felt easy and natural to
pursue this goal”) goal pursuit, which found that effortless goal pursuit mediated the link
between autonomy and progress (Werner et al., 2016). That is, autonomous goals are more likely
to be attained precisely because conscious effort is not necessarily required. Research on habits
further finds that when a behaviour is repeatedly paired with a situation, this behaviour continues
to be enacted when the situation is encountered. Goals can direct the formation of good (goal-
promoting) habits by “motivating repetition that leads to habit formation” (Wood & Neal, 2007,
pg. 843). Together, this research provides strong evidence that goal pursuit can unfold
automatically and effortlessly.
One recent perspective on self-regulation as effortful or effortless is the process model of
self-control (Duckworth, Gendler, & Gross, 2016), which proposes that impulses wax and wane
on a cycle comprised of situation, attention, appraisal, and response. Upon encountering a
situation (e.g., a box of cookies sitting out on the kitchen table), a person can direct their
attention towards or away from the temptation (ignore or look at the cookies), appraise the
situation as threatening to a focal goal or as benign, and enact a behavioural response (e.g., eat
the cookies or put them back in the cupboard). To exercise effective self-regulation, a person can
target any of these stages in the cycle. They can select or change the situation so that the
temptation is less likely to be encountered, change their attention, or how they think about the
temptations. Here, the person attempts to shift the value away from the temptation and bolster
the value of the goal-congruent option (Berkman et al., 2017). Finally, if all else fails and the
desire is not diminished, the person must use effortful control (i.e., willpower) to resist.
Growing evidence supports the model’s proposition that applying self-regulatory
strategies earlier in the cycle is more effective and leads to better goal pursuit. Individuals who
are generally more successful at self-regulation (i.e., exhibit high trait self-control; Tangney,
Baumeister, & Boone, 2004) are more likely to report avoiding tempting situations (Ent,
Baumeister, & Tice, 2015), feel less tempted by common temptations (e.g., playing video
games), and have to use their willpower less frequently (Hofmann et al., 2012). More recently,
Milyavskaya and Inzlicht (2018) found that the frequency and strength of temptations that
conflict with personal goals are related to greater goal progress three months later. The
proportion of temptations that are resisted, and the strength of the resistance were completely
unrelated to goal progress. This again provides support for the situation selection perspective on
self-regulation – if you want to attain your goals, set up your environment in such a way as to
reduce temptations. Additionally, research has identified motivation for the goal as having a
direct influence on both the strength and frequency of desire, with autonomous goals less likely
to elicit tempting desires than less autonomous goals (in within-subject analyses; Milyavskaya et
al., 2015).
Pursuing Multiple Goals. People generally have more than one goal that they want to
attain, and so they must use strategies to manage the pursuit of multiple goals. Two alternate
strategies have been identified: sequential and concurrent goal pursuit (Orehek & Vazeou-
Nieuwenhuis, 2013). In sequential goal pursuit, a person focuses on their goals one at a time,
while inhibiting thoughts and cognitions related to other goals (a process known as goal
shielding; Shah, Friedman, & Kruglanski, 2002). Alternatively, a person engages in actions that
can simultaneously lead to progress on multiple goals (e.g., attending a study session with others
can simultaneously help a student’s academic and social goals). Such actions are known as
multifinal (Kruglanski et al., 2002). However, even when a person is pursuing goals sequentially,
they frequently shift their attention from one focal goal to another (Shah et al., 2002). Some
research has examined when and how this occurs, focusing on the role of emotional feedback
and proximity to goal attainment in determining the dynamics of shifting to new goals (Louro,
Pieters, & Zeelenberg, 2007). Specifically, this research found that the positive emotions that
result from making progress on one’s goals, coupled with high expectancy of imminent
attainment, lead to decreased effort on the focal goal and increased efforts towards competing
goals. Conversely, if little progress is being made but the goal is close, people will maintain or
increase effort towards the focal goal.
Goal Attainment, Adjustment, or Disengagement
Despite the arduous pursuit of our goals, the reality is that sometimes things work out and
sometimes they do not. While failing to attain a desired goal is certainly not a pleasant
experience, there are different paths one can take in the event that such an experience occurs. If
the goal is still deemed to be desirable and worth pursuing, people can re-evaluate their goal
and/or alter their strategy to increase the chance of attainment the next time around. Conversely,
if the goal is no longer worthwhile, the person can disengage or abandon the goal entirely in
favour of more fruitful pursuits. This ability to flexibly amend a goal is termed goal adjustment.
Research on goals that is concerned with task performance (Bandura, 1989; Locke &
Latham, 2002) or specific behaviours (e.g., weight loss, Powers, Koestner, & Gorin, 2008)
frequently include specific, objective indicators of goal progress and attainment (e.g., a final
grade, number of puzzles completed, lost weight). These, however, are usually not related to an
individual’s specific goal – for example, if two individuals lost 10lbs, but one had a goal of
losing 10lbs and the other of losing 20lbs, only one attained their goal, although the objective
value of pounds lost is the same. In contrast, most research that examines personal goals uses
subjective goal progress, rather than objective indicators or discrete attainment, as the outcome.
Typically, progress is measured using a Likert scale that assess agreement with items such as “I
have made progress on this goal” (e.g., Koestner et al., 2002, 2008). Some research that has
examined discrete goal status finds that between 26% (for semester long goals) to 40% (for
week-long goals) were attained, 10-12% were failed, and only 4-6% were abandoned; the others
(45-55%) were listed as some progress made (Levine, Werner, Capaldi, & Milyavskaya, 2017).
These studies, however, were conducted with undergraduate students and short-term (week-long)
to medium-term (semester-long) goals, and it is unknown whether similar rates of goal
attainment would be found in other populations and with broader, longer-term goals.
Additionally, goal progress was not examined in conjunction with goal standing, so it is still
unknown if the amount of perceived progress that participants indicate is related to their
standings on these goals. It is also unknown whether progress is perceived to increase or plateau,
or if the total amount of progress made towards a goal can be perceived to decrease over time.
As is described below in the future directions section, a lot more research is needed to better
understand what constitutes successful goal attainment of personal goals.
Consequences of Goal Progress. Research consistently finds that making greater
progress on one’s goals leads to more positive affect and greater well-being (Emmons, 1986;
Sheldon & Elliot, 1999), whereas the opposite is found when less progress is made. Additionally,
making progress on one’s goals has been linked to greater psychological need satisfaction
(Sheldon & Elliot, 1999; Werner & Milyavskaya, 2017). Although some have suggested that this
is especially true when the goals are autonomous (Sheldon & Elliot, 1999), others have shown
that there are only main effects but no interaction between progress and self-concordance, such
that goal progress is generally beneficial (Werner & Milyavskaya, 2017a). Together with other
research on the role of need satisfaction in goal setting (Milyavskaya et al., 2014), this suggests a
reciprocal relationship where greater need satisfaction in a domain leads to more self-concordant
goals that are more likely to be attained, which leads to greater need satisfaction and in turn even
more self-concordant goals. Some evidence for this ‘upward spiral’ has indeed been found
(Sheldon & Houser-Marko, 2001). Similarly, the short-term affective consequences of goal
progress (i.e., feeling good after making some progress) feeds back into the goal pursuit process
(e.g., Louro et al., 2007).
Action Crises and Goal Disengagement. Sometimes, when a goal is no longer
perceived as desirable, feasible, or attainable, individuals disengage from the goal. In the case of
truly unattainable goals, such disengagement is adaptive (Wrosch et al., 2003). Failure to
disengage from an unattainable goal is linked to more intrusive thoughts (van Randenborgh,
Hüffmeier, LeMoult, & Joormann, 2010) and depressive symptoms (Wrosch et al., 2003),
whereas disengagement can be an adaptive self-regulatory strategy with positive benefits (Miller
& Wrosch, 2007; Wrosch et al., 2003). Decisions to disengage are typically preceded by a period
of intrapsychic conflict between continued engagement and disengagement; this conflict is
dubbed an action crisis (Brandstätter, Herrmann, & Schüler, 2013). Although such action crises
do not necessarily lead to goal disengagement since they can be overcome in favour of continued
engagement, the severity of action crises nevertheless relates to lower goal progress (Holding et
al., 2017). Whether this is directly due to greater conscious goal disengagement, or occurs
because both action crises and goal progress are influenced by external factors, such as the
presence of supportive others, is still unknown. Decisions to disengage from a goal can also be
accompanied by decisions to reengage in a new goal. Such goal reengagement has been linked to
positive outcomes, including greater well-being (Ntoumanis, Healy, Sedikides, Smith, & Duda,
2014). However, goal reengagement is often examined as a personality trait, rather than
examining the new goals set by an individual. Therefore, future research is needed to examine
the types of goals that people actually set after goal disengagement, and if these new goals are
different from goals that are failed (e.g., is the goal of the same content, but a lower standard? Or
does a person take an entirely new path?).
Goal Adjustment. Research on this latter stage of the goal process mostly focuses on
goal attainment and disengagement, but little is known about how people shift their goals. For
example, does there come a time when the student decides that it is not realistic to obtain an A in
the course, so her goal shifts to obtaining a B+? Some theoretical work discusses such shifts as
recalibrations of the reference value in the feedback loop underlying self-regulation (Carver &
Scheier, 2002) but little empirical work has examined how these shifts occur during actual goal
pursuit. Given that the timescale of goal pursuit varies greatly depending on the goal itself and its
abstraction level, some goals may be adjusted on a daily basis (e.g., my goals for what I plan to
accomplish this week shift fluidly based on how much I accomplish on any given day and new
tasks that arise), while for other goals months or even years may pass before a person readjusts a
goal (e.g., a couple may unsuccessfully try to have a child for many years before deciding to
adopt). Alternatively, some goals may become ‘frozen’, where no progress is made yet
individuals do not give up on the goal (Davydenko, Werner, & Milyavskaya, 2017). Research at
the appropriate time scales is needed to understand the fluidity of goal adjustment.
Role of Others
Although goal pursuit is often studied as an individual endeavour, other people in our
lives are usually inextricably involved in our goal pursuits. A great deal of research in this area
has examined the support that goal pursuers receive from other people in their lives –
predominantly romantic partners and friends, but also colleagues, supervisors, parents, teachers,
coaches, and health care providers. Research has found that support from all these sources can
benefit goal pursuit (e.g., Jakubiak & Feeney, 2016), and that responsive support is particularly
beneficial (Feeney, 2004). A great deal of research has specifically focused on autonomy
support, which occurs when the support provider acknowledges the person’s feelings, listens to
their perspective, encourages choice, and refrains from control or pressure (Grolnick & Ryan,
1989; Koestner et al., 2012). Using a variety of methods including daily diary, longitudinal, and
experimental studies, research consistently shows that such support is related to better goal
attainment for a variety of personal goals. Such autonomy support has been distinguished from
directive support where the partner provides encouragement and guidance by making
suggestions and problem solving. In research that compares the two directly, autonomy support
is associated with greater internalization of goals and greater goal progress, while directive
support has either no effect or a small negative effect (Koestner et al., 2012; Koestner et al.,
2015). A separate line of research has distinguished between visible and invisible support
(Bolger, Zuckerman, & Kessler, 2000), finding that invisible support led to better goal progress
over the course of a year (Girme, Overall, & Simpson, 2013). Although distinct, these two lines
of research (autonomous vs. directive, invisible vs. visible support) share many similarities, and
future research can determine whether they tap into similar underlying behaviours and influence
goal pursuit through similar mechanisms.
In addition to helping close others pursue their own goals, people sometimes set goals for
close others – for example, a woman who wants her husband to lose weight, or a father who
wants his daughter to succeed in school. Such vicarious goals can influence how these
individuals support the goal pursuer, and the ultimate outcome of the goal (Carbonneau &
Milyavskaya, 2017). Given that often times people know the goals that others have for them,
some research has found that the mere thought of these others can influence goal setting and
pursuit (Fitzimons & Bargh, 2003; Shah 2003). For example, in one study, participants who were
primed with ‘father’ performed better on an academic task when they reported that their father
valued such tasks and when they were close to their father (Shah 2003). Many of these studies,
however, have used very small sample sizes, and caution is warranted. Additionally, whether this
research, which often uses broader general goals such as ‘achievement’, translates to
idiosyncratic personal goals is still unknown.
Close others can also be instrumental to our goal pursuit, helping us to attain our goals -
for example, if I have the goal of losing weight but my partner is the one who goes grocery
shopping and refrains from buying junk food. People can typically identify who these
instrumental others are for each goal, and, as described above, the type of support that these
instrumental others provide can shape goal pursuit. Recently, the disparate research on how
others help with goal pursuit has been formalized into transactive goal dynamics theory, which
describes the interdependent nature of goal pursuit and “conceptualizes two or more
interdependent people as one single self-regulating system” (Fitzsimons, Finkel, & vanDellen,
Future Directions
Research on goal pursuit comes from many research areas, including social, personality,
organizational, cognitive, and developmental psychology. While leading to many new insights,
this has also resulted in a preponderance of theories and research to explain specific aspects of
goal pursuit. One of the priorities in this literature would be to develop more cohesive models
that incorporate the multiple aspects of goal pursuit outlined above. Although models have been
developed to examine some aspects of goal pursuit (e.g., the progression of goals through
temporal stages, Gollwitzer, 1990; dealing with multiple goals, Neal, Ballard, & Vancouver,
2017; self-control, Kotabe & Hofmann, 2015; self-regulation, Wilkowski & Ferguson, 2016),
there is no single model that can incorporate and address all of these components. A
comprehensive model would include predictions about goal selection and goal setting, the
process of goal pursuit and self-regulation, managing multiple goals in real-time, and decisions
to alter or abandon a goal.
One key direction in creating a unified model is a better understanding of the
characteristics, both of the person and of the goal, that actually influence goal pursuit. Although
there are many theories and papers that look at various characteristics in isolation (e.g., how does
motivation predict goal progress? How do implementations predict goal progress?), few
researchers ever attempt to integrate these theories (see Webb & Sheeran, 2005). This results in a
fragmented field. Furthermore, some of the constructs that have been suggested to play a role in
goal pursuit may be the same construct under different names. By including multiple measures
into one study, researchers can examine how these relate to each other, and determine unique and
strongest predictors of goal pursuit.
Reconciling Trait Approaches with Goal-Specific Approaches
A critical inconsistency in the goal literature is that self-regulation is often studied at a
trait level, while most of the variance in goal attainment is at the goal level. Indeed, traits such as
conscientiousness and trait self-control have been consistently linked with beneficial self-
regulatory outcomes (see de Ridder, Lensvelt-Mulders, Finkenauer, Stok, & Baumeister, 2012).
It would thus seem that conscientious individuals are generally better at attaining their goals. But
how can this be reconciled with the large within-person variation in personal goal attainment? If
only about 5-20% of the variance is at the between person level, this means that any individual
difference would contribute very little to overall goal attainment. This may be the reason why the
effects of trait self-control on outcomes are generally small. However, there may be a way that
individual traits affect the goals that people set, thereby influencing goal-specific outcomes. For
example, perhaps people with higher levels of trait self-control generally set better goals, such
that progress on even one of those goals translates into broad success. Alternatively, there may
be many ways to be ‘successful’ despite not attaining some personal goals. Individual differences
may relate to how flexible people are in changing and resetting goals and in finding multiple
means to pursue the same broader goals.
It may also be the case that the studies that focus on traits and general success use a
proscriptive, societally accepted definition of success (e.g., earning more money, receiving more
education); this may not necessarily be the same as attaining one’s personal goals, as not all
people may strive for these ‘successes’. Much more research is needed to reconcile these trait
and goal-specific perspectives. Studies can directly examine, for example, whether trait self-
control influences the types of goals that people set, whether more conscientious people are
pursuing more (or fewer) goals simultaneously, and whether these individual differences relate to
more flexible goal pursuit. Future research can also examine possible predictors of variability,
such that, for example more conscientious individuals may have less variability in goal
attainment across their goals than someone who is less conscientious.
Validating Instruments
Some of the problems with research on personal goal pursuit comes from measures that
are used to assess the numerous constructs of interest. For example, in the personal projects
paradigm, participants rate various characteristics for each goal (e.g., difficulty, importance,
commitment) using one item per characteristic (e.g., Nurmi et al., 2009). Similarly, research on
goal pursuit uses one item to assess effort, and two to three items to assess progress (e.g.,
Sheldon & Elliot, 1999; Werner et al., 2016). Although this is often necessary to keep the
surveys to a reasonable length (especially since participants are reporting on multiple goals), it
often precludes the possibility of using statistical analysis to ensure construct validity.
As an example of this issue, there is an outstanding question of whether goal motivation
is best conceptualized as a continuum or as two separate dimensions. Conceptually, self-
concordance is supposed to be one dimension along a continuum (Deci & Ryan, 2000), with a
score frequently calculated by subtracting controlled motivation from autonomous motivation.
Other research, however, frequently finds that these dimensions are uncorrelated (or positively
correlated), showing that while autonomous motivation is consistently related to positive goal
outcomes, controlled motivation is either negatively or unrelated to progress. This seems to
suggest that a better approach is to examine the two types of motivation separately (Koestner et
al., 2002). Conversely, a recent large meta-analysis of the motivation scales suggests that people
do indeed experience different types of motivation to different degrees of self-determination,
providing evidence in favour of the continuum approach (Howard, Gagné, & Bureau, 2017).
However, this meta-analysis focused on behavioural regulation using established scales of
motivation, with multiple items per motivation type. Future research would greatly benefit from
examining whether a dichotomous or continuum approach is most suitable for personal goals.
The problem, however, is that the typical assessment of goal motivation in longitudinal goal
research uses one item per motivation type (intrinsic, integrated, introjected, and extrinsic, and
sometimes identified; 4 or 5 items total), so that more complex factor analyses are impossible.
One aspect of goal pursuit that is often overlooked is the idea that goals can unfold over
many different timescales – some goals can be accomplished in a few days, while others take
months or even years, and others are constantly ongoing and must be maintained. With the
exception of values and life goals (which require active maintenance), different timescales are
used interchangeably and often treated in the same manner (e.g., a week-long goal may be
compared to a month-long goal). Future research is needed to understand whether the process of
goal pursuit is the same for goals on different timescales, especially since broader goals are
frequently broken down into smaller goals that are pursued over a shorter time (e.g., a month-
long goal can be broken down into both weekly and daily goals). For research to understand the
process of goal pursuit, these timescales need to be taken into account. This is especially
important for investigating goal adjustment, as well as other questions concerning the possible
fluctuation in goal-relevant variables, such as abstraction, motivation, and even progress.
Considering the timescale over which goal pursuit unfolds is necessary to properly design
studies that can provide valid information on the various aspects of goal pursuit. Currently, even
those studies on personal goal pursuit that include multiple assessment to examine process and
outcomes vary greatly in the frequency and delay of assessments, ranging from asking about
progress daily (Wilkowski & Ferguson, 2016), weekly (Werner & Milyavskaya, 2017a), by
semester (Sheldon & Kasser, 2001), or yearly (Duckworth, Peterson, Matthews, & Kelly, 2007),
often without any justification for why those frequencies were selected. Additionally, some goals
might have specific ‘turning points’ – for example, receiving their midterm grade may prompt
the student to re-evaluate their goal for their end-of semester grade, and a successful competition
may lead an athlete to set a higher goal for a subsequent competition (Donovan & Williams,
2003). Given that such turning points are likely highly idiosyncratic for separate goals,
researchers need to carefully consider the frequency of measurements in their studies to capture
such variations. Assessments that are too close together will likely miss the longer-term
consequences of goal pursuit (e.g., whether the goal is attained) for more abstract goals, but
those assessments that are too far apart will miss the opportunity for detecting important shifts in
goal adjustment and the progression of smaller sub-goals. One possible technique that could be
especially useful in goal research is measurement-burst designs (Sliwinski, 2008), which consist
of combining intensive repeated-measures assessments with longer term (e.g., weekly, monthly)
assessments to examine both fine-grained and longer-term variability in goal pursuit.
What Constitutes Successful Goal Pursuit?
Despite the extensive literature on goals, what constitutes successful goal pursuit is not
completely clear. That is, are we as researchers interested in determining whether some progress
is made (and if so, how much progress is meaningful), or if a goal is attained? No research has
directly examined how these are related. One reason may be that objective indicators for most
idiosyncratic goals are difficult to determine. As described above, one benefit in subjective
assessments is that they are the same across goals, so that within-person analyses can be
conducted. How this would look like for objective measures is unclear – that is, can a goal such
as ‘lose 10 lbs’ be compared with a goal of ‘earning an A’, even though objective indicators for
both are available? Future research is needed on both objective and subjective goal attainment to
triangulate what constitutes ‘successful’ goal pursuit. This can then be used as an outcome
criterion to test models of goal pursuit. The eventual aim would be to develop and test predictive
models, where researchers could use the characteristics of a person’s goals to accurately predict
actual goal progress.
Goals as Networks
Very little research on personal goals has considered them in the broader context of other
goals that people are simultaneously pursuing. Although some research has examined how goals
facilitate or conflict with other goals (Emmons & King, 1988; Riediger & Freund, 2004), the
implications of such conflict or facilitation for how a person actually juggles these goals in their
daily life has not been examined. Additionally, even though research has identified sequential
and concurrent strategies of goal pursuit (Orehek & Vazeou-Nieuwenhuis, 2013), the focus has
been on goal planning using lab studies, and so it is unclear how this actually occurs naturally in
idiosyncratic goal pursuit in daily life. Future research thus needs to consider not only the pursuit
of specific goals, but also how these goals relate to one another. With the popularization of
statistical techniques such as network analysis, it could be especially interesting to examine goals
as networks in order to better understand how they relate to (or conflict with) one another. For
example, do people have separable clusters of goals (where some goals are relatively
independent, or only linked to one long-term goal), or do many of the goals cluster together? Are
there individual differences that can predict how goals are organized? How does the structure of
the network affect goal attainment? Using a network approach for the study of goal pursuit can
pave the way for new insights on goal setting and pursuit.
Overall, there is a rich literature on goal pursuit stemming from many areas in
psychology. This brief review focused on personal goals and the cycle of goal pursuit, while
unfortunately ignoring some other aspects of goal pursuit (e.g., goal automaticity; Aarts &
Dijksterhuis, 2000). Indeed, a complete review of the literature could fill numerous books.
Nevertheless, this brief review highlights some key aspects of goal pursuit research: Goals are
best conceptualized as a distinct unit of analysis, with extensive within-person variations in both
goal characteristics and attainment. Numerous characteristics of goals have been identified as
contributing to successful goal pursuit; however, this literature remains scattered and a more
comprehensive model is needed to integrate these disparate findings. Future research can focus
on understanding the interplay between goals and individual differences, how goals relate to each
other, and how people set, pursue, readjust, and juggle multiple goals both in their day-to-day
lives and over longer courses of time.
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... Research on goals and goal dimensions has shown that goal dimensions have important effects on outcomes like goal attainment (Milyavskaya & Werner, 2018;Sheldon & Elliot, 1998) and the psychological well-being of the person who pursues the goal (Hennecke & Brandstätter, 2017;Klug & Maier, 2015;Little, 2020). A look at this literature, however, also reveals a large degree of heterogeneity with regard to how relevant constructs are named and measured. ...
... These concepts all refer to mid-level goals, that is goals that are narrower than abstract general values or worldviews (Royce & Powell, 1983), but still guide people's behavior over extended periods of time ranging from weeks to decades (Atherton et al., 2021). Second, there are several different terms in use to describe self-reported properties of goals, for example goal characteristics (Milyavskaya & Werner, 2018), goal appraisals , or goal cognitions (Karoly & Ruehlman, 1995). We will here adopt Austin and Vancouver's (1996) terminology by using the term "goal dimensions" for characteristics on which goals vary. ...
... Goals are a central construct in the analysis of human motivation, and their characteristics or dimensions have been shown to affect the goal pursuer's experience and success in achieving them (Little et al., 2014;Milyavskaya & Werner, 2018;Sheldon & Elliot, 1998). To measure goal dimensions, researchers commonly use self-report items asking participants to rate their goals on various dimensions of interest, e.g., their commitment, value, or expectancy (Emmons, 1986;Little, 1983). ...
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Goals represent a central construct in the analysis of human motivation. How people appraise their own goals on various quantitative dimensions, like commitment or difficulty, predicts important outcomes like goal attainment and psychological well-being. Unfortunately, however, there appears to be little agreement in the literature on how to best measure goal dimensions. To get an overview of current measurement practices, we conducted a systematic literature review that yielded 693 publications including 1,166 different terms for goal dimensions and 3,244 reported items. Up to 79 different items were found to indicate single goal dimensions and 80% of scales consisted of one item, which mostly asked for the term of the goal dimension name. We further extracted 358 different item facets, that is, different meaning-bearing terms (e.g., "engrossed" or "deeply involved"). 28% of item facets were found only once in individual items and 52% of item facets were used to measure more than one goal dimension. We find that for 42% of items, sources were not reported or items were created ad hoc. Hence, we recommend being cautious of jingle fallacies when comparing similar goal dimensions across publications and being cautious of jangle fallacies when comparing different goal dimensions. We advocate considering construct validity and content validity more thoroughly in the development of goal dimension items and enhancing transparency in reporting of study items. Furthermore, we advocate factor analysis methodology to narrow down the abundance of goal dimension terms and developing parsimonious and comprehensive theories of goal dimensions.
... Research on goals and goal dimensions has shown that goal dimensions have important effects on outcomes like goal attainment (Milyavskaya & Werner, 2018;Sheldon & Elliot, 1998) and the psychological well-being of the person who pursues the goal (Hennecke & Brandstätter, 2017;Klug & Maier, 2015;Little, 2020). A look at this literature, however, also reveals a large degree of heterogeneity with regard to how relevant constructs are named and measured. ...
... These concepts all refer to mid-level goals, that is goals that are narrower than abstract general values or worldviews (Royce & Powell, 1983), but still guide people's behavior over extended periods of time ranging from weeks to decades (Atherton et al., 2021). Second, there are several different terms in use to describe self-reported properties of goals, for example goal characteristics (Milyavskaya & Werner, 2018), goal appraisals , or goal cognitions (Karoly & Ruehlman, 1995). We will here adopt Austin and Vancouver's (1996) terminology by using the term "goal dimensions" for characteristics on which goals vary. ...
... Goals are a central construct in the analysis of human motivation, and their characteristics or dimensions have been shown to affect the goal pursuer's experience and success in achieving them (Little et al., 2014;Milyavskaya & Werner, 2018;Sheldon & Elliot, 1998). To measure goal dimensions, researchers commonly use self-report items asking participants to rate their goals on various dimensions of interest, e.g., their commitment, value, or expectancy (Emmons, 1986;Little, 1983). ...
... This is important for at least three reasons. First, there are no studies evaluating the psychometric proprieties of a self-report measure that subsumes a broad range of goal characteristics that have previously been shown to be related to outcome variables such as goal achievement, motivational quality, real-world behaviors, and well-being (Milyavskaya & Werner, 2018). Additionally, not all extant measures for individual measures have been validated. ...
... Their reliability and validity are, in some cases, limited by a small number of items and missing empirical evidence for the correlation to latent variables (Milyavskaya & Werner, 2018). The specificity of measures to a particular context is an additional limitation when comparing effects (e.g., comparing the impact of avoidance goals in educational, organizational, and personal goals). ...
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How motivated a person is to pursue a goal may depend on many different properties of the goal, such as how specific it is, how important it is to the person, and how actionable it is. Rigorously measuring all of the relevant goal characteristics is still very difficult. Existing measures are scattered across multiple research fields. Some goal characteristics are not yet covered, while others have been measured under ambiguous terminology. Other conceptually related characteristics have yet to be adapted to goals. Last but not least, the validity of most measures of goal characteristics has yet to be assessed. The aim of this study is to: a) integrate, refine, and extend previous measures into a more comprehensive battery of self-report measures, the Goal Characteristics Questionnaire (GCQ), and b) investigate its evidence of validity. In two empirical studies, this paper provides evidence for the validity of the measures regarding their internal structure, measurement invariance, and convergence and divergence with other relevant goal-related measures, such as the motivation, affect, and the dimensions of Personal Project Analysis. The results show that our goal characteristic dimensions have incremental validity for explaining important outcomes, such as goal commitment and well-being. It concludes with practical recommendations for using the GCQ in research on goal-setting and goal-pursuit, and a discussion about directions for future studies.
... Past research suggests that most of the variance in goal progress is at the goal level (i.e., within-person; see ref. 90 , for an overview), perhaps explaining the few associations between individual differences and goal attainment. Besides self-control, agreeableness was also positively related to goal progress, and neuroticism negatively related to progress (at 2 out of the 3 follow-ups). ...
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Self-regulation has been studied across levels of analysis; however, little attention has been paid to the extent to which self-report, neural, and behavioral indices predict goal pursuit in real-life. We use a mixed-method approach (N = 201) to triangulate evidence among established measures of different aspects of self-regulation to predict both the process of goal pursuit using experience sampling, as well as longer-term goal progress at 1, 3, and 6-month follow-ups. While self-reported trait self-control predicts goal attainment months later, we observe a null relationship between longitudinal goal attainment and ERPs associated with performance-monitoring and reactivity to positive/rewarding stimuli. Despite evidence that these ERPs are reliable and trait-like, and despite theorizing that suggests otherwise, our findings suggest that these ERPs are not meaningfully associated with everyday goal attainment. These findings challenge the ecological validity of brain measures thought to assess aspects of self-regulation. Self-regulation helps people to achieve their goals, and has been studied across modalities. Here, the authors present longitudinal evidence suggesting that common neural and behavioral measures of self-regulation derived from laboratory tasks do not predict everyday goal pursuit.
... Our findings suggest that even people who have personality traits that make them well-suited for goal disengagement generally may struggle to disengage from specific goals that they harbour little autonomous motivation to disengage from and feel perpetually conflicted about. Indeed, our focus on goal-specific disengagement is in line with a growing body of research suggesting that a significant level variance for understanding goal characteristics and outcomes tends to be at the level of the goal (Holding et al., 2017;Milyavskaya & Werner, 2018). ...
When people hit roadblocks with their personal goals, goal disengagement is an adaptive response associated with improved mental and physical health. However, people can have trouble letting go of goals, even when pursuing them is problematic. We introduce a motivational model of goal disengagement by proposing that having autonomous motivation to disengage (a sense of truly identifying with the decision) as opposed to controlled motivation to disengage (feeling forced to let go) allows for people to make greater progress disengaging from specific goals, and prevents people getting stuck in an “inaction crisis” where they feel torn between disengaging further or re-adopting the goal. Using prospective longitudinal designs, we tracked the goal disengagement of personal goals in university students (Study 1, N = 510) and a general adult sample of Americans (Study 2, N= 446), finding that autonomous motivation for goal disengagement facilitated making disengagement progress. This work expands our understanding of the role of autonomous motivation throughout a goal’s lifecycle and helps integrate different theoretical frameworks on goal motivation and self-regulation.
... Our findings suggest that even people who have personality traits that make them well-suited for goal disengagement generally may struggle to disengage from specific goals that they harbour little autonomous motivation to disengage from and feel perpetually conflicted about. Indeed, our focus on goal-specific disengagement is in line with a growing body of research suggesting that a significant level variance for understanding goal characteristics and outcomes tends to be at the level of the goal (Holding et al., 2017;Milyavskaya & Werner, 2018). ...
Full-text available
When people hit roadblocks with their personal goals, goal disengagement is an adaptive response associated with improved mental and physical health. However, people can have trouble letting go of goals, even when pursuing them is problematic. We introduce a motivational model of goal disengagement by proposing that having autonomous motivation to disengage (a sense of truly identifying with the decision) as opposed to controlled motivation to disengage (feeling forced to let go) allows for people to make greater progress disengaging from specific goals, and prevents people getting stuck in an “inaction crisis” where they feel torn between disengaging further or re-adopting the goal. Using prospective longitudinal designs, we tracked the goal disengagement of personal goals in university students (Study 1, N = 510) and a general adult sample of Americans (Study 2, N= 446), finding that autonomous motivation for goal disengagement facilitated making disengagement progress. This work expands our understanding of the role of autonomous motivation throughout a goal’s lifecycle and helps integrate different theoretical frameworks on goal motivation and self-regulation.
... Goals can be conceptualized as a 'cognitive representation of a desired end state that a person is committed to attain' (Milyavskaya & Werner, 2018;p. 164). ...
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The action crisis represents the decisional conflict between persisting in pursuing a goal and giving it up. In the current study, the results of adaptation of the Action crisis scale to Slovak are presented across 11 subsamples and 1507 participants. The confirmatory factor analysis indicated that the original structure with 6 items does not provide an acceptable fit. The network analysis further showed that the most problematic item related to rumination was not stable and was connected to only one other node. Thus, a revised solution with five and four items was proposed (S-ACRISS R). In order to corroborate the convergent validity, a nomological network with 13 theoretically derived variables was examined. The results of the mini meta-analysis established the expected pattern of relationships with variables covering areas such as individual differences, motivation, goal-related cognitions, goal-related affect as well as variables associated with the process of goal attainment.
... The goal-related constructs, articulated in frameworks under such rubrics as "middlelevel-units" [1], "characteristics adaptations" [2], or "personal concerns" [3], have become, in the last few decades, key personal factors in explaining and regulating behavior [4][5][6]. Indeed, from contemporary approaches, besides the basic tendencies represented by traits [2], plans, intentions, and purposes are the raw material of knowledge for a personality psychology that is interested in both personal (as well as collective) well-being and the exploration of the dynamics that underlie behavior. ...
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The appraisal of goal-related constructs, generally, and of personal projects (PP) in particular, is one of the most solid research paths with regard to subjective well-being and health. In the last few years, the appraisal of PP has been linked to such problems as excessive alcohol and marijuana use, but no study has been conducted in the field of compulsive buying (CB). In this study, using Little’s personal-projects-analysis (PPA) methodology, the differences in university students were analyzed in both broad domains (meaning, structure, community, efficacy, and stress) and specific appraisal dimensions in groups with low (n = 293), moderate (n = 191), and high (n = 41) compulsive-buying propensities. The results confirm that the high-propensity group presented the highest significant levels in the domain of stress and the lowest in efficacy, meaning, and structure. As to appraisal dimensions, the group with a high propensity to CB attained statistically lower appraisals in the dimensions of importance, enjoyment, self-identity, absorption, control, time adequacy, progress, and outcome of their projects; the appraisal of the level of stress, difficulty, and conflict increased as the level of involvement in CB increased. These findings have major implications for the design of prevention and intervention programs for this behavioral problem.
There are many ways in which researchers ask participants about their personal goals or projects, yet findings are subsequently considered interchangeable. This study experimentally tested whether different ways of asking participants about their goals elicits different goals and impacts reports of goal progress. Undergraduate participants (N = 285) were assigned to one of three conditions (personal projects, personal goals, open-ended goals), listed an unlimited number of goals they were currently pursing, rated each goal on a series of goal characteristics, and six weeks later reported on their goal progress. Results indicated that participants reported significantly more goals in the personal project condition than in the other two conditions, and that these goals were rated as less difficult. Overall, the present study provides further insight into the effects of the elicitation methods employed in goal pursuit research.
While research bore out a reliable relationship between moral identity and moral behavior, it has not addressed potential undermining effects of moral identity on moral behavior. This paper offers an integrative framework for conceptualizing such effects. Within this framework, moral identity is defined as a goal that allows for different forms of goal pursuit. The moral identity goal can vary along three axes: prevention versus promotion orientation, external versus internal motivation, and low versus high level of abstraction. It is argued that (a) prevention orientation fosters moral disengagement, (b) external motivation promotes moral hypocrisy, and (c) a less abstract representation of the moral identity goal allows for moral licensing. These undermining effects can be overcome by promotion-oriented, internally motivated and more abstract moral identity goals.
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Self-determination theory proposes a multidimensional representation of motivation comprised of several factors said to fall along a continuum of relative autonomy. The current meta-analysis examined the relationships between these motivation factors in order to demonstrate how reliably they conformed to a predictable continuum-like pattern. Based on data from 486 samples representing over 205,000 participants who completed 1 of 13 validated motivation scales, the results largely supported a continuum-like structure of motivation and indicate that self-determination is central in explaining human motivation. Further examination of heterogeneity indicated that while regulations were predictably ordered across domains and scales, the exact distance between subscales varied across samples in a way that was not explainable by a set of moderators. Results did not support the inclusion of integrated regulation or the 3 subscales of intrinsic motivation (i.e., intrinsic motivation to know, to experience stimulation, and to achieve) due to excessively high interfactor correlations and overlapping confidence intervals. Recommendations for scale refinements and the scoring of motivation are provided.
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In the present study, we examined whether personal standards and self-critical perfectionism differentially related to how people attributed their success and failures in pursuing their personal goals. In two studies (Ns = 185 and 240), participants set three week-long (Study 1) and semester-long (Study 2) goals, and at the end of the week or semester answered questions about goal status, internal and external attributions, and likelihood to reset the goal. Mulitlevel analyses showed that self-critical perfectionism was related to attributing goal attainment to external sources; this was not the case for failure or abandonment. Conversely, personal standards perfectionism was related to attributing failure more to external sources. Overall, these results highlight differences in how perfectionism influences the use of the self-serving bias.
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Self-control is often conceived as a battle between “hot” impulsive processes and “cold” deliberative ones. Heeding the angel on one shoulder leads to success; following the demon on the other leads to failure. Self-control feels like a duality. What if that sensation is misleading, and, despite how they feel, self-control decisions are just like any other choice? We argue that self-control is a form of value-based choice wherein options are assigned a subjective value and a decision is made through a dynamic integration process. We articulate how a value-based choice model of self-control can capture its phenomenology and account for relevant behavioral and neuroscientific data. This conceptualization of self-control links divergent scientific approaches, allows for more robust and precise hypothesis testing, and suggests novel pathways to improve self-control.
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Do we have the necessary perceptual abilities to set goals that are congruent with our own values and needs? In a prospective study, participants (n=185) identified three goals that they planned to pursue throughout the week. For each goal they then rated their motivation for pursuing it and made predictions about the extent to which goal attainment would satisfy their needs for autonomy, competence, and relatedness. One week later, participants rated their progress on each goal, as well as the actual need satisfaction they experienced. Using Bayesian analysis, we found support for our (null) hypothesis that participants predicted that their goals would satisfy their psychological needs, irrespective of goal self-concordance. While people sometimes overestimated need satisfaction, we found that people who pursued more self-concordant goals actually benefited more from their pursuits, both compared to others who pursued less concordant goals and among their own goals.
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This research examined the types of eating regulation goals that women have for themselves as well as for their romantic partner, and how these relate to their interpersonal style toward their partner, and to their partner’s psychological and relational well-being. Participants were 131 heterosexual couples. Results show that the eating regulation goals that women have for their partner (health or appearance oriented) reflect the type of goals that they personally pursue. Furthermore, women who have health-focused eating goals for their partner are perceived as more autonomy-supportive, which is associated with the partner’s report of higher relationship quality. Conversely, women who have appearance-focused eating goals for their partner are more likely to be perceived as controlling, which negatively predicts the partner’s psychological and relational well-being. These results attest to the importance of considering women’s personal eating regulation goals for a better understanding of the type of goals they have for their partners and how these relate to their partners’ well-being and relationship quality.
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Self-regulation is the dynamic process by which people manage competing demands on their time and resources as they strive to achieve desired outcomes, while simultaneously preventing or avoiding undesired outcomes. In this article, we review the current state of knowledge regarding the process by which people manage these types of demands. We review studies in the organizational, cognitive, social psychology, and human factors literatures that have examined the process by which people (a) manage task demands when working on a single task or goal; (b) select which tasks or goals they work on, and the timing and order in which they work on them; and (c) make adjustments to the goals that they are pursuing. We review formal theories that have been developed to account for these phenomena and examine the prospects for an integrative account of self-regulation that can explain the broad range of empirical phenomena examined across different subdisciplines within psychology. Expected final online publication date for the Annual Review of Organizational Psychology and Organizational Behavior Volume 4 is March 21, 2017. Please see for revised estimates.
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Objective: Action crises describe the intrapsychic conflicts individuals experience when they feel torn between further goal pursuit and goal disengagement. The present investigation introduces autonomous and controlled motivation as independent predictors of action crisis severity, beyond known personality level predictors (action orientation), and novel personality level predictors (neuroticism and conscientiousness). Method: Using a multi-wave prospective longitudinal design and multilevel modeling (MLM) we followed students pursuing 3 personal goals across an academic semester (N = 425 undergraduates, 76% female, 57% Caucasian, Mage = 20.2, SD =2.3). In two follow-up surveys, participants reported on the severity of their action crises, goal progress, and symptoms of depression. Results: Results suggest that autonomous motivation shields individuals from experiencing action crises, while controlled motivation represents a risk factor for developing action crises beyond personality level predictors. Furthermore, MLM revealed that autonomous motivation is a significant predictor of action crisis severity at both the within- and between person levels of analysis. Action crises mediate both the relationship between autonomous motivation and goal progress, and the relationship between controlled motivation and symptoms of depression. Conclusions: The implications of these findings for the prevention of action crises and motivation research are discussed. This article is protected by copyright. All rights reserved.
Self-control is typically viewed as a key ingredient responsible for effective self-regulation and personal goal attainment. This study used experience sampling, daily diary, and prospective data collection to investigate the immediate and semester-long consequences of effortful self-control and temptations on depletion and goal attainment. Results showed that goal attainment was influenced by experiences of temptations rather than by actively resisting or controlling those temptations. This study also found that simply experiencing temptations led people to feel depleted. Depletion in turn mediated the link between temptations and goal attainment, such that people who experienced increased temptations felt more depleted and thus less likely to achieve their goals. Critically, results of Bayesian analyses strongly indicate that effortful self-control was consistently unrelated to goal attainment throughout all analyses.