Sometimes used interchangeably with self-control (but see distinction made below)
The psychological process by which a person strives to attain valued outcomes. Self-regulation consists of all manner of goal setting and goal pursuit, which can be accomplished through both effortful control of behavior and effortless, automatic, or habitual forms of goal-directed behavior.
Though the term self-regulation has sometimes been equated with self-control, here we use the term self-regulation more broadly to refer to the regulation of one’s behavior and emotions through the process of pursuing one’s goals, including goal setting and both effortful and automatic forms of goal-driven behavior (de Ridder et al. 2012; Fujita 2011). People engage in self-regulation throughout the day, and in many domains (e.g., work, leisure, health, sex, alcohol, tobacco, hygiene, sleep), as a means to reach both short-term and long-term goals (Hofmann et al. 2012). Such instances of everyday self-regulation include (but are not limited to) going to the gym instead of heading home after work, packing a lunch instead of buying one in the cafeteria, and keeping your mouth shut instead of yelling at your boss. Though these behaviors all pertain to different goals (to be healthy, to save money, to remain employed), they are all instances of a situation where regulation of one’s behavior is required to bring about a desired outcome.
As expressed in our definition, self-regulation is intimately related to goals. Goal pursuit first starts with goal setting – that is, selecting which goal(s) to pursue (see Gollwitzer 1990). Once a goal is set, the individual then compares their current state (i.e., where they are at now) to their desired state (i.e., where they would like to be). In the event of a discrepancy, the individual needs to adjust their behavior to get closer to the desired state. This active pursuit of a goal often involves self-control. Self-control consists of the effortful and usually conscious overriding of a proximal impulse or temptation that is in conflict with a distal goal (Carver and Scheier 2011; Milyavskaya and Inzlicht 2017). On the other hand, more automatic forms of goal-directed behavior consist of effortless and often unconscious processes of routinized behaviors in response to environmental cues, such as implementation intentions and habits (Fujita 2011).
Self-Regulation as Goal Pursuit
During the process of goal pursuit, it is important for an individual to establish exactly what it is that they wish to accomplish at a given moment. The first model to differentiate between goal setting and goal striving is the Rubicon model of action phases (Gollwitzer 1990). Whereas goal striving refers to behavior directed toward existing goals, this model further suggests that goal setting answers the question of what goals a person will choose as a function of expected value, desirability, and feasibility. The process that is most often overlooked, however, is how an individual transfers their wishes and desires into more concrete goals. This is particularly important because people have a myriad of wishes and desires to choose from, and so it is up to them to selectively choose which ones to actually implement. This is where the evaluation of the expected value of various options comes into play, as preferences can be established by assessing feasibility (“Do I have the ability and/or resources to attain the desired outcome?” “Is the environment I am in conducive to this goal or will it impede my progress?”) and desirability (“How pleasant are the short-term and long-term consequences?” “Will this goal lead to meaningful experiences and/or desired incentives or rewards?”). Once a goal is chosen (as a function of being both desirable and feasible), the individual is said to have “crossed the Rubicon,” and with their newfound intent, they are able to continue on with the process of goal pursuit (i.e., at this point shifting into goal striving).
An additional factor that contributes to goal setting is the social context or domain in which the goals are situated. Recent research in self-determination theory suggests that the extent to which a social context is supportive of the basic psychological needs for autonomy, competence, and relatedness influences both the types of goals that people pursue (or the “what”) and their underlying reasons (or the “why”) (Milyavskaya et al. 2014). For example, people are more likely to pursue autonomous goals (reflecting personal interest, importance, and meaning) in domains that are perceived as need supportive (Milyavskaya et al. 2014). The kind of goals people set, and their reasons (i.e., motivation) for pursuing them, influences the self-regulatory mechanisms that will later take place in pursuit of these goals. Recent research shows that autonomous goals lead to more automatic, effortless goal pursuit (Milyavskaya et al. 2015; Werner et al. 2016). These findings suggest that motivation plays an important role in how individuals set and pursue goals in their daily lives.
The Cybernetic Model
After setting a goal, it is up to the individual to regularly assess his or her goal progress. Control theory (or cybernetic theory; Carver and Scheier 1982) was one of the first theories to try to explain control processes, in a more general manner. The model centers on discrepancy-reducing (or negative) feedback loops, with the first stage of focusing on the input function, whereby the individual assesses the present condition (Carver and Scheier 1982). This present condition is then compared to a desired or ideal condition through a comparator mechanism. If the individual detects a discrepancy, he or she then enacts a behavior to reduce the discrepancy. This is called the output function, which changes the present condition. Another feedback loop is then set in motion to compare the new present condition to the desired one (Carver and Scheier 1982).
In the context of goal pursuit, discrepancy-reducing loops occur over multiple iterations, and as such allow individuals to monitor their goal progress. In the case where an individual is making satisfactory progress, he or she will continue on with pursuing the goal, as no discrepancy is detected and therefore no significant adjustment is required. However, if current progress is unsatisfactory, a discrepancy between current goal progress and the desired goal state is detected. The individual thus enacts a behavior to reduce the discrepancy and ultimately attain the desired goal (Carver and Scheier 2011). For example, if a student has the goal to have a 3.5 GPA, he or she will constantly compare the present condition of his or her grades to the desired condition. If the student’s grades start to deteriorate, he or she will then notice a discrepancy and choose to enact a new behavior to reduce it (e.g., studying more for the next exam). This premise is operating under the assumption that most long-term goals cannot actually be “attained” and consequently require active maintenance until they are no longer valuable or commitment wanes (either in general or when a competing goal takes precedence). Throughout the goal pursuit phase, it is important that individuals periodically monitor the progress they are making toward their goal (Carver and Scheier 1982; Gollwitzer 1999).
Progress monitoring is particularly important because challenges are frequently encountered throughout goal pursuit. Specifically, it is quite common to experience temptations that conflict with a long-term goal (Hofmann et al. 2012). Temptations have a strong hedonic incentive value and are usually accompanied by a strong urge to satisfy the temptation. They can be activated by stimuli in the environment, such as walking by an ice cream shop, or by internal triggers (e.g., thirst). Temptations are aimed at short-term gratification, and their value decreases when the physical and/or temporal proximity to the tempting stimuli is reduced (Hofmann et al. 2009). Temptations are mostly impulsive, automatic processes that operate outside of conscious awareness. Overriding these temptations, on the other hand, requires deliberate and effortful control (Hofmann et al. 2009). Because temptations usually interfere with long-term goals, such effortful control is necessary for effective self-regulation.
Effortful Goal Pursuit
As described above, the effortful control of behavior in goal pursuit is the “effortful inhibition of an immediately gratifying behavior or impulse” (Milyavskaya and Inzlicht 2017, p. 2). It typically implies a deliberate process, by which the individual inhibits undesirable responses that come in conflict with a set goal.
Baumeister and Heatherton (1996) were among the first to try to explain the self-control mechanism that people may use when faced with temptations. They conceptualized Carver and Scheier’s (1982) feedback loop as “one internal process overriding another” (Baumeister and Heatherton 1996, p. 2) and asked the question of what enables such overriding to occur. Their answer was a strength model, in which one’s strength to override a temptation must be greater than the strength of the impulse or temptation. This led to the elaboration of the resource model, which has become one of the most prominent models of self-control. The resource model posits that self-control is an inner capacity that relies on a limited internal resource or energy. The central tenet of this model is that repeatedly engaging in self-control depletes this limited inner resource, subsequently leading to a state of ego depletion (Baumeister and Heatherton 1996). For example, if someone repeatedly resists the temptation of spending money on clothing while passing boutiques during a walk in town, this same person will later fail at resisting junk food due to having depleted their self-control resource. This prediction has been repeatedly tested, mainly using a sequential task paradigm, and shows that exerting self-control on a first task impairs the ability to do so on a second one (Hagger et al. 2010). However, recent debates about the magnitude of the effect (Hagger et al. 2010), an inability to replicate one of the paradigms in a large-scale preregistered replication effort across many labs (Hagger et al. 2016), and the absence of evidence of a plausible resource (see Milyavskaya and Inzlicht 2017 for review) have resulted in the development of newer models of self-control.
While the resource model emphasized the interplay between two systems, namely, impulses or temptations, that required overriding and a resource that could override these impulses, Hofmann et al. (2009) posit that self-control can be understood as a three-part system (dispositions and situations, impulsive thoughts, and reflective thoughts) in which some dispositions and situations can influence whether impulsive or reflective thoughts will “win” and determine the behavioral output (Hofmann et al. 2009). On the one hand, the impulsive system generates impulsive behavior as a function of associative clusters forming in one’s long-term memory. These clusters may be created or strengthened through temporal or spatial co-activation of (a) a stimulus, (b) an affective reaction, and (c) behavioral schemas. Once formed, these clusters can be instantly activated by perceptual clues in one’s environment or by triggering one’s inner homeostatic processes (e.g., hunger, thirst). On the other hand, the reflective system is responsible for higher-order mental operations, such as executive functions, putting together strategic plans for goal pursuit, and inhibiting impulses or habits. Thus, the reflective system includes more conscious, deliberate processes that allow for greater control over the more unconscious impulsive system. While both systems have the potential to influence behavior, the actual direction of one’s behavior is ultimately determined by situational and dispositional boundaries (e.g., self-control resources, cognitive capacity, working memory capacity; Hofmann et al. 2009).
The process model (Inzlicht and Schmeichel 2012) brings the three-part system one step further by offering an explanation for the mechanics of the interplay between the different systems. As an alternative to the resource model, the process model states that initial self-control exertion leads to self-control failure at a second time point by (a) generating motivational shifts away from self-control and toward self-gratification and (b) generating attentional shifts away from cues that indicate the need for control toward cues that indicate reward (Inzlicht and Schmeichel 2012). In refining these ideas, the more recent shifting priorities model (Milyavskaya and Inzlicht 2017) posits that the decision to exert self-control is based on “numerous inputs reflecting the relative value of both indulgence and restraint” or valuation (Berkman et al. 2015, p. 6). In other words, individuals in a self-control dilemma weigh the pros and cons of the possible alternatives (e.g., giving in to temptation or indulgence vs. resisting). According to this model, attention serves to bring the self-control dilemma into conscious awareness, while both attention and motivation (i.e., the reasons why people pursue goals; Deci and Ryan 2000) affect the valuation of each alternative. The shifting priorities model provides an explanation for the decline in self-control over time by suggesting that a first instance of self-control shifts the value of exerting effort as well as the value of indulging away from self-control and toward temptations.
Automatic Goal Pursuit
Individuals have a limited capacity to process and respond consciously to their environments (e.g., Bargh and Chartrand 1999). As a result, people often rely on cognitive procedures that require minimal conscious effort, intention, monitoring, or resources to do so. The same can be said about self-regulation – though effortful self-control is useful to consciously control one’s behavior to override impulses and temptations, it is more efficient for this regulation of behavior to require less conscious effort (Fujita 2011).
Research confirms that goals can be put in motion automatically and can unconsciously guide behavior (Aarts and Dijksterhuis 2000; Fishbach et al. 2003). This automatization of goal-directed behaviors can occur in response to environmental cues, as some features of the environment can automatically activate associated goals (Bargh et al. 2001). For example, walking past a bank can automatically prime one’s goal to save money. Studies show that unconsciously priming goal-specific cues increases goal-directed behavior (e.g., Bargh et al. 2001). However, there are different ways in which goals can be primed (Shah 2005). Instrumental goal priming occurs when specific means (e.g., settings, individuals, activities, behaviors) become associated with a specific goal. The relation is a functional one (degree of facilitation), and its increasing strength means increasing the likelihood that encountering the means will automatically activate the goal. On the other hand, interpersonal goal priming occurs when other individuals influence the goals that one chooses to pursue. In this case, the stronger and closer the relationship, the higher likelihood that one will consider the other’s input and goals (Shah 2005).
Such automatic goal priming can also come about through temptation-goal associations. Fischbach and colleagues (2003) argue that as a result of repeatedly exerting self-control, facilitative links form between the temptations and the distal goal with which they come in conflict, such that the subsequent display of a temptation cue activates the goal it would compromise. For example, if one repeatedly resists drinking alcohol, eventually the sight of alcohol paraphernalia has the potential to automatically activate the goal to remain sober. Given that such links would be overlearned, they would require few cognitive resources. This goal priming might bring the threat into conscious awareness and lead to the exertion of more effortful self-control (Fishbach et al. 2003).
Another way in which automatic self-regulation develops is through habits. Habits can be defined as “links between a goal and actions that are instrumental in attaining this goal” (Aarts and Dijksterhuis 2000, p. 54). Indeed, infrequent or unfamiliar goals prompt individuals to consider several possible actions before choosing the best one, which implies that the action will not be performed immediately. On the other hand, when a goal is familiar and regularly pursued, there is an opportunity for associations to form between the goal and the frequently performed actions. Such associations emerge through frequent co-activation of the goal and a corresponding action, usually an action that has been shown to lead to goal achievement, and generally in the same context. The more frequently these co-activations occur, the stronger the habit becomes. Once habits are established, goal activation can automatically elicit the associated habitual behavior. Habits thus allow an individual to perform goal-directed actions in a mindless, automatic way. However, the activation of the goal is a necessary condition to the automatic unfolding of the habit (Aarts and Dijksterhuis 2000), which can occur as a function of environmental cues, as previously discussed.
In addition to the frequency and consistency of association between goals and actions, Gollwitzer (1999) has shown that implementation intentions can be used as a form of automatic self-regulation. Implementation intentions are created by labeling a specific if (or when)-then contingency between an environment or situation and a plan of action (e.g., if/when I am offered a soda, then I will ask for water). By doing so, a mental association is generated between the specific situational cue (soda) and the suitable goal-directed behavior (drinking water, which is in line with the goal to be healthy). Then, when such situations arise in the future, the preset behavior will be immediately and automatically performed (Gollwitzer 1999). Implementation intentions can be used to plan for anticipated temptations that may distract an individual from attaining their goal and can thus help one stay on track by actively avoiding them (Gollwitzer 1999). Because the individual already has a prepared response to an expected temptation, the self-control dilemma does not require the individual’s conscious attention, thus facilitating a more automatic or habitual response (Gollwitzer 1999). Further evidence that implementation intentions lead to more automatic responses stems from the findings that goal-directed behaviors can be efficient under heavy cognitive load and are enacted faster when the stimulus is subliminal (for an overview of the mechanisms of implementation intentions, see Gollwitzer and Sheeran 2006).
Individual Differences in Self-Regulation
While self-regulation is often goal specific and situational, there are also individual differences that affect self-regulatory success and failure. For example, although many factors such as goal strength, motivation, current mood, etc., may affect whether a person purchases a cupcake even though it conflicts with their goal to eat healthy, some people are more likely to frequently cave in to buying the cupcake, whereas others are rarely fazed by such a treat. Such individual differences may occur as a function of varying personality traits, biological processes, and cognitive functions. In this final section, we describe some of these individual difference factors that can influence self-regulation, including trait self-control, conscientiousness, behavioral approach and inhibition systems, and working memory (for a more extensive review, see Carver 2005).
From a personality perspective, it is important to note that there are dispositional differences in the ability to engage in different self-regulatory processes across multiple domains (e.g., academic, health, relationships). One such difference, termed trait self-control, is thought to represent a difference in the general ability to override impulses (de Ridder et al. 2012). Indeed, a recent meta-analysis found a small-to-medium effect size for measures of trait self-control predicting positive behavioral outcomes in a variety of life domains (de Ridder et al. 2012). In other words, this review provided evidence for the long-standing assumption that being able to successfully control one’s behavior is associated with a wide array of positive outcomes, whereas the lack of self-control often leads to undesirable responses.
In an attempt to explain the mechanism underlying dispositional self-control, Adriaanse and colleagues (2014) explored the role of automatic behavior. In a daily diary study examining habits and eating behaviors, they found that people high in trait self-control were more likely to have weaker unhealthy snacking habits, which in turn predicted lower consumption of unhealthy snacks throughout the week (Adriaanse et al. 2014). These findings suggest that people high in trait self-control are not necessarily better in regulating their behavior because they are better able to resist temptations; rather, they are more successful because they develop more adaptive habits (Adriaanse et al. 2014). Thus, a key conclusion from this evidence is that people high in trait self-control are better at setting up their environment in a way that is conducive to successful regulation, which ultimately translates into the successful attainment of one’s goals.
While self-control can be dispositional in and of itself, it is also the case that other well-known personality factors influence self-regulation. Drawing from the Five Factor Model of Personality (i.e., the “Big Five”), conscientiousness has been associated with positive self-regulation. Conscientiousness refers to the tendency to follow socially prescribed norms and rules and engage in impulse control to do so, to plan ahead, to be goal driven, and to be able to delay gratification. Conscientiousness has been shown to play an important role in the regulation of temptations, specifically regarding behaviors associated with impulse versus restraint (Carver 2005). For example, people high in conscientiousness are more likely to consider future consequences when choosing their behavior (Strathman et al. 1994). While other traits from the Big Five may also play an arguably smaller role in the process of self-regulation (e.g., agreeableness, neuroticism), for the sake of brevity, they are not discussed here (cf. Carver 2005).
Approach (BAS) and Avoidance (BIS) Systems
Shifting toward a more biopsychological perspective, a distinction has been made between approach and avoidance-based motive systems that underlie affect and behavior (Gray 1994). The behavioral approach system (BAS) is an appetitive system that serves to activate or facilitate action and is often attuned to rewards and goal achievement. Using a stoplight analogy, this system would serve as the green light or the “go” system. Because of this system’s affiliation with the dopaminergic reward system in the brain (via the ventral tegmental area of the midbrain in the anticipation of rewards and the mesial prefrontal cortex after the receipt of rewards), positive outcomes (e.g., positive affect) emerge when it is activated (Carver 2005). Conversely, the red light or “stop” system is the behavioral inhibition system (BIS). Activated in the face of threat or novelty, this avoidance system triggers negative affect (e.g., anxiety) and encourages an individual to withdraw in order to avoid punishment and reduce the negative affect. From a biological perspective, research shows that responses to threat are associated with the activation of the right anterior cortex, indicating this area as the root of avoidance motivation (Carver 2005).
As with the aforementioned concept of trait self-control and the Big Five personality characteristics, there are dispositional differences in the extent to which these approach and avoidance motive systems influence behavioral activity. Specifically, individuals lower in approach tendencies (i.e., having a less reactive BAS) are less likely to engage in impulsive behaviors than those higher in approach (i.e., having a more reactive BAS) (Carver, 2005; Gray 1994). This is likely because temptations often have high intrinsic value (e.g., Milyavskaya and Inzlicht 2017) and so those with a more reactive BAS will respond in a way that allows them to achieve that immediate reward, even at the sake of impeding progress on their more distal goal. However the reverse is true for BIS – those higher in avoidance (i.e., a more reactive BIS) are less likely to engage in impulsive behaviors than individuals with lower avoidance tendencies (i.e., a less reactive BIS) (Carver 2005; Gray 1994). This is likely because if an individual is faced with temptation, the individual with a more reactive BIS will be driven to avoid the negative consequences associated with impulsive behaviors that can impede their goal progress.
As previously described, the dual systems perspective of self-regulation emphasizes the interplay between the reflective (i.e., controlled) and impulsive (i.e., automatic) systems. Expanding this work, Hofmann and colleagues (2008) drew from the cognitive literature to argue that individual differences in working memory capacity enable the extent to which consciously controlled processes can override automatic or habitual responding. In other words, individuals with greater working memory are more likely to be successful in enacting controlled, goal-directed behavior, whereas those with a lower working memory capacity are more likely to make a decision without considering alternative responses (for a review, see Barrett et al. 2004).
To directly examine the role of working memory capacity in self-regulation, Hofmann et al. (2008) conducted three studies examining whether individual differences in working memory differentially influence the impulsive and reflective systems in the domains of sexuality, eating behavior, and anger expression. Across all domains, results consistently suggested that individuals with lower working memory capacity were more likely to rely on automatic processes than individuals with greater working memory capacity. For example, within the eating behavior domain, automatic attitudes toward candy resulted in greater liking and consumption, but only for individuals with lower working memory capacity. Similar patterns were also found in the other domains. Overall, these findings suggest that it is also important to take into consideration the different cognitive conditions that influence the extent to which an individual relies on more automatic (e.g., habitual) versus consciously controlled (e.g., planning) processes when faced with temptations that require self-regulation.
In this entry, we provided a brief overview of both past and current perspectives on self-regulation. While there has yet to be a consensus on what self-regulation really is, here we take the stance that self-regulation goes beyond the classic idea of effortful self-control. Instead, we present a series of contemporary theories and models that build on these fundamental ideas by arguing that attention should be paid to the interplay between conscious control processes (i.e., effortful self-control) and more automatic (e.g., effortless, habitual) processes. Evidence for this proposition is further provided by research on individual differences from a wide array of perspectives, including personality, biopsychology, and cognition.
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