Habit and Intention: The Multiple Processes of Behavior ...



Habit and Intention: The Multiple Processes of Behavior Generation in Everyday Life

Wendy Wood Jeffrey M. Quinn

Texas A&M University

Preliminary draft of a chapter to appear in: J. Forgas, W. VonHippel, & K. Williams (Eds.), Sixth annual Sydney Symposium on Social Psychology.

Please do not cite or quote.

Habit and Intention: The Multiple Processes of Behavior Generation in Everyday Life

People seem to believe that much of their behavior is under their own control and that it reflects their intentions and plans. Everyday understanding of the mind-body problem is a pretty straightforward link between cognition, affect, and action (see Wegner, 2002). Thus, acting without thinking would seem to be the stuff of social gaffs and apologies.

Yet, absence of thought about actions may be a common occurrence in everyday life. Behavior can be guided through several processes, and these vary in the amount of attention they require (Heckhausen & Beckmann, 1990; Ouellette & Wood, 1998; Wegner & Bargh, 1998). With novel behavior or behavior in unfamiliar contexts, the uncertainties associated with performance require that people continuously attend to and evaluate new information as it is presented in order to respond appropriately. In contrast, for frequently performed behaviors in stable contexts, behavioral intentions become implicit as individual behaviors come to be incorporated into sequences of multiple actions (Ouellette & Wood, 1998; Wood, Quinn, & Kashy, 2002). Then recurring environmental cues can activate practiced behavior routines in a process that occurs largely outside of people=s awareness (i.e., Aat one extreme...accompanied by a complete mental blank,@ Heckhausen & Beckmann, 1990, p. 38). Thus, given the appropriate contextual cues, behavior can be initiated and performed with minimal, sporadic thought.

In the present chapter, we propose that the implicit processes guiding habit performance can proceed separately from explicitly intentional action. To the extent that these are independent processes, habitual and intentional performance modes will each be affected by a unique set of factors (i.e., in addition to such common factors as a person=s skill set). In addition, the two modes can generate separate, conflicting guides to action, as evidenced by action slips and other unintended behaviors (Hay & Jacoby, 1996; Reason, 1979). These errors illustrate yet another feature of the habitual and intentional systemsBalthough they proceed simultaneously, they also can influence each other in the generation of behavior (see Smith & DeCoster, 2000; Wilson, Lindsey, & Schooler, 2000). Not only can habits interfere with the best laid plans, but also, given sufficient effort and opportunity, the intentional system can override well-practiced behavior.

How Habits Guide Behavior

We define habits as behavioral tendencies to repeat well-practiced acts given stable contextual cues. Repetition of a behavior in a given setting promotes automaticity in the cognitive processing that initiates and controls the response, as the processing comes to be performed quickly, in parallel with other activities, and with the allocation of minimal focal attention (e.g., Posner & Snyder, 1975). Repetition of behavior can yield automaticity when people are intending to achieve some goal or when the repetition is unintended and people are unaware of what they have learned (Squire et al., 1993; see Lippa & Goldstone, 2001, for incidental development of automatic associations). Thus, habits that emerge from intentional repetition could be explicitly represented in memory as goal-action links (Aarts & Dijksterhuis, 2000; Verplankan & Aarts, 1999). Yet, our claim that people are often not aware of their habits and the contexts that trigger them suggests that implicit representations of habits will often not correspond to explicit understanding of behavior.

Stable contexts facilitate the propensity to perform repeated behaviors with minimal cognitive monitoring. Research on transfer of learning and on stimulus generalization have addressed the question of what makes features of stimuli and contexts interchangeable for learning and performance (e.g., Bouton, Nelson, & Rosas, 1999; Proctor & Dutta, 1993). For our purposes, contexts are stable to the extent that they present the same contextual cues integral to performing the response and to the extent that they are similarly conducive to fulfilling an actor=s goals. As Barker and Schoggen (1978) noted in their analysis of the genotype of behavior settings, contexts may vary in superficial attributes but be stable in the features supporting performance. Unstable contexts are ones in which shifts in the supporting environment implicate alternate goals or challenge the smooth initiation, execution, and termination of practiced responses.

How do stable environmental events cue behavior? In classic learning theories, features of the environment directly cue well-practiced behavior through stimulus-response linkages (e.g., Hull, 1943; Spence, 1956). However, more recent models of cognitive processing outline how external events mobilize action by automatically triggering behavioral intentions and action sequences, which then can be implemented with minimal thought (e.g., Bargh & Ferguson, 2000; Heckhausen & Beckman, 1990). With repetition of behavior, intentions become relatively abstract, specifying broad goals, and they become incorporated into sequences of multiple actions (Vallacher & Wegner, 1987). We suggest further that, even for actions that initially may have been explicitly goal-directed, intentions become implicit with repetition. Thus, habitual action sequences are relatively automatically cued by the environment, often outside of awareness, and they do not require motivation, intention, or cognitive capacity.

Memory Systems and Habits

Research in cognitive psychology and the neurobiology of memory systems is consistent with our claim that separate habitual and intentional systems guide behavior. At a cognitive level, habits represent slow-learning systems in which contextual cues, sequences of motor performance, and sometimes behavioral goals are structured in associative memory by similarity of experiences and their repeated contiguity. These learned sequences are then retrieved by a fast, automatic pattern-completion mechanism (see Smith & DeCoster, 2000). The associative processing mode can be contrasted with intentional systems that include rule-based processing and relatively conscious, explicit reasoning that is applied in either a deliberative, systematic manner or a more spontaneous, heuristic way.[i]

Neuropsychological research on memory systems also suggests that habits are associated with a particular memory system. This work has examined patients with brain lesions that yield selective memory impairment or it has used functional neuroimaging techniques to examine activation of brain regions during performance of behavioral tasks (see reviews in Schacter, 1992, 1995). The findings suggest that noncognitive habit and skill memory are linked to a complex of specific brain systems involving the basal ganglia, cerebellum, and motor neocortex (Gabrieli, 1998; Squire, Knowlton, & Musen, 1993). These differ from the systems associated with priming and other forms of nonconscious memory and from the systems involved in declarative, conscious memory for facts and events. Thus, the memory systems involved in habitual responses appear to be separable at a neurological level from those involved in more explicit modes of behavior generation.

In addition, support for our claim that habits are stored as larger action sequences rather than discrete acts was provided by Jog, Kubota, Connolly, Hillegaart, and Graybiel=s (1999) study of the sensorimotor striatum of rats during learning of a maze. Because neuronal responses after successful acquisition emphasized the beginning and the end of the learned procedure, these authors concluded that an action template was developed for the behavioral unit as a whole (i.e., the full maze), and this was triggered by specific contexts at the start and the end of the maze. Thus, habits tend to be integrated into action sequences that are cued as a unit by stable features of the environment.

Intentions and Habits Guide Behavior

Despite the strong evidence of the separate cognitive and neurological processes associated with habitual and nonhabitual behavior, the standard behavior prediction models in social psychology have focused on explicit, intentional guides to action (see Eagly & Chaiken, 1993). According to the best-known such model, the theory of planned behavior (and its precursor, the theory of reasoned action), behavior is a function of behavioral intentions; these intentions in turn reflect attitudes toward a behavior, perceptions of normative pressures, and perceptions of efficacy to perform a behavior (Ajzen, 1987, 1999; Fishbein & Ajzen, 1984). Research that has measured the relevant cognitions and then used these to predict behavior has provided strong support for such models (see meta-analytic reviews by Armitage & Conner, 2000; Randall & Wolff, 1994; Sheppard, Hartwick, & Warshaw, 1988). However, this evidence of predictive power does not necessarily speak to the cognitive and affective mechanisms through which behavior is generated.2

Predictive models, like laws, are Ageneral summaries of the way things happen...and are deduced from observations of specific things happening...processes, on the other hand, are the intermediary events that explain why things happened as they did@ (Gilbert, 1998, p. 103). Developing the theory of reasoned action to address process, Fazio (1990; Fazio & Olson, 2003) proposed that the theory holds primarily when people are highly motivated and have sufficient opportunity to deliberate about their intentions and behavior. When motivation and opportunity are limited and when attitudes are strong and automatically activated in memory, then people respond in a more spontaneous fashion and their attitudes and perceptions of social norms directly guide action. Although Fazio=s depiction of spontaneous action can be faulted for providing little insight into the relevant mechanisms (e.g., how do the automatically-activated attitudes toward a target direct specific behaviors, see Eagly & Chaiken, 1993), the model is noteworthy for addressing the dynamics of intention-behavior processes.

To extend predictive models to consider the dynamic impact of habits, Ouellette and Wood (1998) conducted a meta-analytic synthesis of the conditions under which behavior reflects conscious intentions versus habits. Specifically, habitual repetition should occur when a behavior has been performed with sufficient frequency in a stable contextBas should be the case with behaviors such as drinking coffee and wearing sealtbelts. In contrast, intentions should be a guide primarily when a behavior is novel or performed in an unstable contextBas with behaviors such as getting a flu shot or donating blood (Triandis, 1977). The top panel of the path model in Figure 1 displays the findings for studies in the synthesis that examined behaviors that could be performed frequently. As anticipated, people who had established habits for these behaviors simply repeated their past behavior and were minimally influenced by their stated intentions. The bottom panel in Figure 1 displays the findings for studies that examined behaviors that occur only a few times a year, and typically in unstable contexts. With these behaviors, people were likely to carry out their intentions, and the frequency with which they had performed the action in the past had little effect. This overall pattern of findings suggests that when people have sufficient opportunity to form habits, behavior is not a function of conscious intentions.

Additional demonstration that habit and intention provide separate guides to behavior has been provided by research that has examined behavior prediction for people with and without habits in a given behavioral domain (e.g., Albarracin, Kumkale, & Johnson, 2002; Ferguson & Bibby, 2002; Ouellette & Wood, Study 2). For example, in a study of car use, Verplanken, Aarts, van Knippenberg, and Moonen (1998) found that people who used their cars frequently and thus had established a driving habit did not base their travel decisions on their intentions to driveBinstead, they repeated their past behavior. In contrast, people who used their cars less often were guided by their intentions regarding mode of transport. Thus, habitual and explicit intentional processes appear to provide separate guides to behavior, and these guides interact in their effects such that intentions have minimal influence when habits have been formed.

Despite the independent effects of habit and intention on past behavior, people=s judgments of these factors appear to be linked. For example, in both of the path models in Figure 1, intention is correlated with past behavior. This relation could reflect a tendency for people to practice to habituation intended behaviors as well as a tendency for people to infer their intentions from their past behavior (e.g., reasoning, AI did it in the past, I will probably do it in the future@). Inference of intention from past behavior should occur especially when people are uncertain of their intentions (see Bem, 1972), a circumstance that is likely when behavior emerges from implicit processes. Thus, the relation between intention and frequency of past behavior plausibly reflects a variety of factors unrelated to the processes through which habits guide behavior.

Is past behavior a valid measure of habit? The evidence that behavior is generated through multiple processes does not challenge models of explicit intention so much as complement them by suggesting that implicit processes also guide behavior. Yet, a recurring question from the perspective of prediction models is whether frequent behavior in stable contexts reflects habit or some other variable that might already be represented in the model (e.g., Ajzen, 2001).

Participant reports of past performance frequency have been the standard measure of naturally-occurring habits (e.g., Ronis, Yates, & Kirscht, 1989; Triandis, 1977). Similarly, manipulations of frequent performance in stable contexts have been the standard procedure to establish strong habits in the laboratory (e.g., Hay & Jacoby, 1996; Shiffrin & Schneider, 1977). These two paradigms converge in suggesting that the processes guiding behavior are automatized with frequent practice, especially when the practice occurs in stable contexts (Schneider & Shiffrin, 1977; Wood, Quinn, & Kashy, 2002).3

Furthermore, suggesting that performance frequency effects cannot easily be dismissed as proxies for other, nonmeasured variables, habits have been found to maintain their predictive impact in designs that control for a variety of additional factors (e.g., attitude accessibility, self-concept, perceived behavioral control; Ouellette & Wood, 1998). Additional reassurance is provided by the pattern of effects associated with habits; although main effect findings that past behavior predicts future behavior would be vulnerable to explanation through nonhabitual factors, the interactive effects of habit and intention that emerge in specific conditions (see Figure 1, also Verplanken et al., 1998) are not easy to explain in terms other than automaticity.

The accuracy of people=s reports of their past behavior is limited by their ability to assess such information. Research has successfully estimated habituation from people=s reports of the frequency of a variety of everyday actions (e.g., bike and car travel, exercise, reading a newspaper, eating junk food; Verplanken & Aarts, 1999; Wood, Tam & Witt, 2003). Yet, the extent to which people accurately attend to, remember, and report past behavior frequency depends on a number of factors, including their retrieval strategy. Specific instances of behavior may not be accessible in memory for people who perform behaviors routinely, and instead of relying on episodic recall they may generate estimates of frequency and context stability from their understanding of the rate at which they perform an act (e.g., reading the newspaper every morning would be extrapolated to seven times per week, Menon, Raghubir, & Schwarz, 1995). Because these retrospective reporting strategies can be influenced by a number of factors (e.g., questionnaire design, Schwarz, 1990), they are best paired with alternate measures that are less reliant on estimation and recall. Diary methods in which people provide contemporaneous reports of their activities can potentially assess frequency of behaviors that may otherwise escape recall. For example, event-contingent reporting requires people only to recognize and tally instances of performance, and thereby provides a measure of frequency that is not especially susceptible to biases associated with retrieval and estimation strategies.

Habits and Other Forms of Automaticity

Automating behaviors into habits yields abstract, implicit intentions that guide sequences of behaviors, the performance of which is largely cued by the environment outside of awareness. It is unclear at present whether this automaticity in behavior performance is associated with automaticity in judgments about behavior. According to Verplanken and Aarts (1999), habits correspond to scripts, or cognitive structures that develop with repeated experience to represent people=s understanding of stereotyped sequences of action in well-known situations (see Schank & Abelson, 1977). In this view, habits are represented in memory as goal-behavior links that are automatically activated to guide performance. In line with the idea that habits are guided by automatically-accessed judgments, Ajzen (2001), suggested that even Afamiliar behaviors that have become automatic as a result of frequent performance...are..guided by spontaneous attitudes and intentions@ (p. 109). In support of these ideas, Aarts and his colleagues (Aarts & Dijksterhuis, 2000; Aarts, Verplankan, & van Knippenberg, 1994, as cited in Verplanken & Aarts, 1999) have demonstrated that, when a relevant goal is activated (e.g., going to the grocery store), people are faster at accessing attitudes and intentions for a behavior (e.g., to ride a bike) when they previously had developed a habit than when they had not. In this view, automaticity in habit performance is guided by automaticity in judgment.

Yet, there is reason to believe that habits will not always correspond with scripted or automatically-accessed judgments about behavior. As Abelson (1981) noted, Athe difference between a script and a habit is that a script is a knowledge structure, not just a response program@ (p. 722). Differences between explicit understandings and actual behavior emerge because habits can be generated outside of awareness, independent of explicit intentions (see Figure 1). Extrapolating from these findings, it seems likely that response times to report these intentions (see Aarts & Dijksterhuis, 2000) also will not be a reliable indicator of implicit, habitual behavior.

This idea that people=s reports of their intentions may not correspond to the implicit intentions that guide habits echoes the often-found dissociations between explicit and implicit cognitive constructs in research on stereotyping and other judgments (Fazio & Olson, 2003). Automaticity in judgments about behavior, although not always in line with automaticity in behavior performance, are worth investigation in their own right. For example, automaticity in judgment may emerge when habits can be clearly labeled by self and others and when these labels are used frequently in everyday interactionBas with consistent travel model choices (e.g., Aarts & Dijksterhuis, 2000). Furthermore, automatically accessed judgments can guide behavior through spontaneous processes and use of heuristic rules that are explicit but not deliberative (e.g., impulse buying in which people reason, AI like it, I=ll buy it,@ Verplanken & Herabadi, 2001).

To better understand the automatic processes guiding habits, it is useful to compare habits with other forms of environmentally-cued responses, especially implementation intentions. Such intentions are a form of planning that facilitates goal attainment by specifying Athe when, where, and how of goal-directed responses@ (Brandstätter, Lengfelder, & Gollwitzer, 2001, p. 947; see also Gollwitzer, 1999). People form implementation intentions by explicitly linking performance of a desired act with contextual features that signify an opportunity for performance (i.e., Awhen x occurs, I will perform behavior y.@). Like habits, such plans of action elicit immediate and efficient responses when people encounter relevant environmental cues. However, implementation intentions likely require some intentional inference. People may consciously monitor the environment for the target event or the event=s occurrence may automatically trigger the previously-formed intentions (McDaniel & Einstein, 2000). In contrast, habits seem to proceed largely outside of awareness and are not initiated by recognition of an intention (Ouellette & Wood, 1998).

Priming also is worth discussing in relation to habits. Priming can automatically generate behavior when relevant goals and constructs (e.g., a trait, a group stereotype) become accessible through use or exposure. For example, exposure to words related to the stereotype of the elderly appears to induce behavior consistent with that stereotype (e.g., walking slowly or exhibiting poor memory; Bargh, Chen, & Burrows, 1996; Dijksterhuis, Bargh, & Miedema, 2000). Similarly, Ahot@ emotional reactions can emerge automatically when exposure to appetitive or aversive stimuli automatically triggers impulsive approach or avoidance behaviors that are not mediated by the actor=s conscious intentions (Metcalfe & Mischel, 1999; Chen & Bargh, 1999). These priming effects and emotional reactions are similar to habits in that actions involve minimal awareness, intention, and control. However, unlike habits, in which contextual cues tend to elicit immediately a specific behavior to which they have become linked through repeated practice, priming effects may occur with a single exposure to relevant stimuli and can encompass a variety of behaviors relevant to the target construct (e.g., walking speed, memory performance). In addition, priming sometimes has relatively long-term behavioral effects that continue independent of the initial context (e.g., if primed goals are not satisfied, Bargh & Chartrand, 1999).

In sum, the mechanisms guiding habits are the stable contextual features that directly and automatically trigger well-practiced action sequences (Ouellette & Wood, 1998). Relevant psychological processes, such as attitudes toward behavior, goals, and intentions, that may initially intervene between contextual cues and behavior become implicit through repeated performance. Research on automaticity of judgments about behavior, on implementation intentions, and on priming effects all provide important insight into the many facets of automaticity, but these alternate processes do not map directly onto the mechanisms guiding habits.4

Thought about Habitual Behavior

The differences between explicit intentional and implicit habitual processes should be apparent in people=s everyday experiences of their behavior. Given that the processes guiding habits occur largely outside of awareness, people should not typically have to think about their behavior during habit performance. They should be freed-up to consider other issues such as past experiences or future plans. To test this idea, Wood, Quinn, and Kashy (2002) conducted two diary investigations in which college students reported once per hour on what they were thinking, what they were doing, and how they were feeling. The reported behaviors that were performed almost daily and usually in the same context were considered to be habits, whereas those performed less often or in varying contexts were not considered to be habits.

Suggesting that habits are guided by implicit processes outside of awareness, participants= thoughts tended not to correspond with their behaviors during habit performance. Specifically, participants= thoughts wandered from their behavior when performing habits almost 60% of the time. In contrast, participants= thoughts when performing nonhabits typically concerned their behavior and were focused elsewhere only about 35% of the time. Assuming that thought about behavior-irrelevant factors is an indicator of the limited, sporadic conscious processing guiding actions, habit performance appears to have been guided by relatively automatic processing. Furthermore, the finding that participants thought about habitual behavior about 40% of the time suggests that the habitual mode of behavior regulation is best characterized by minimal or sporadic cognitive monitoring, and not by the complete absence of thought.5

This automaticity in habit performance was not only found with simple acts that could be performed with minimal thought (e.g., typing, cooking), but also was apparent with complex acts that required on-line monitoring and tailoring to ongoing input (e.g., studying, conversing with others). That is, complex acts were performed with less behavior-relevant thought, and presumably greater automaticity, given frequent practice in stable contexts. It may be that with practice people form expectations about the general form and content of this input and develop standard patterns of response that reduce the amount of thought required. This is perhaps illustrated in the stereotypic interaction between long-married couples at breakfast, in which a conversation can be maintained despite the inattention of one partner who has learned to respond appropriately to pauses while reading the newspaper.

To assess whether these findings regarding thought about behavior hold up across age, Quinn and Wood (2003) collected data from a community sample (age range 17-79, M = 34.3, SD = 13.9). Once again, participants tended to think about their behavior when they performed nonhabits, and to think about issues unrelated to their actions during habit performance. While performing habits, participants= thoughts strayed from their behavior more than 50% of the time, compared to only about 40% of the time while performing nonhabits. Interestingly, this relationship between thoughts and behavior did not vary with participants= age, and the diary reports of individuals of various age groups showed a similar proportion of habitual behaviors (M = 47%). However, age did have one clear effect: Older people tended to think about what they were doing with greater frequency than younger participants. Because older participants= also indicated that their behavior was more important than did younger participants, we speculate that age-related increases in thought about behavior reflect the increases in responsibility and interpersonal interdependence that occurred within the age ranges in our sample.

Cognitive consistency. Habits are not only associated with lesser amounts of thought about behavior, but also they are associated with less coherent thought about behavior. When people do not use intentional reasoning, they do not have to think about the cognitive antecedents of intention (e.g., attitudes, norms) and in ways that organize these factors into a coherent guide to action. Inconsistencies could then emerge over time in the various components as each is affected individually by experience and other factors. Inconsistencies would also be expected for habits that develop as side-effects of other behaviors (see, e.g., Lippa & Goldstone, 2001) because unintended behaviors are not likely to be the product of a coherent train of thought to begin with.

Cognitive inconsistencies in the explicit cognitive reasoning components associated with habitual behavior have been found in both meta-analytic and primary research on condom use (Albarracin, Kumkale, & Johnson, 2002; Trafimow, 2000). That is, for people who use condoms habitually, intentions are not well-integrated with attitudes and subjective norms, whereas for people who use condoms in a nonhabitual manner, intentions are more closely linked to these other factors. Additional evidence of cognitive inconsistencies in the determinants of intention has been found in research on everyday behaviors such as reading the newspaper and watching TV (Wood, Tam, & Witt, 2003). That is, attitudes toward these behaviors, subjective norms, and perceptions of behavioral control do not cohere as closely to intentions when people perform the behaviors habitually as when they do so nonhabitually. Thus, across a variety of domains, habits have been found to be associated with inconsistent patterns of thought about behavior.

These demonstrations of the lack of coherence in the explicit cognitive reasoning components of action provide compelling evidence that habits are not guided by such thought. If habits were guided by thought about intentions and its cognitive antecedents, then people should have had many opportunities to develop a coherent cognitive structure with respect to action. Instead, however, people=s thoughts about habits are not well-organized and, for example, they might report that they dislike a behavior but also that they intend to perform it. This lack of coherence is understandable given that habits are guided by implicit systems that do not implicate conscious intentional processes.

Habits and Intentions Separately Guide Behavior: Evidence from Action Errors

One implication of the dissociation between habitual and explicitly intentional behavior is that the two modes can generate separate guides to action. These two guides correspond when people intend to do what comes habitually. The differences between the systems become evident when they conflict, as occurs when habits intrude on intentional action in the form of Aaction slips@ (Hay & Jacoby, 1996; Heckhausen & Beckmann, 1990; Reason, 1979).

Habit intrusions or slips correspond to well-practiced action sequences that belong to some activity other than the one intended. Diary research has revealed that action slips in everyday life occur largely when people are distracted or preoccupied by something other than their immediate behavior; the intruding actions tend to be ones people have engaged in recently and frequently, and ones that share locations, movements, and objects with the intended actionBso that the environment then cues practiced yet unintended behaviors (Reason, 1979, 1984; Reason & Lucas, 1984). To explain these deviations between action and intention, researchers have postulated multiple systems guiding action (e.g., Heckhausen & Beckmann, 1990). For example, Reason (1984) proposed that action slips emerge from the relatively independent actions of a cognitive store of learned action sequences and an intentional system that identifies goals and ways of achieving themBcoinciding with the current contents of consciousness.

Studies of habit-induced errors in memory performance in laboratory settings have similarly demonstrated that habitual patterns and conscious recollection can contribute independently to performance (e.g., Caldwell & Masson, 2001; Hay & Jacoby, 1996; Jacoby, Yonelinas, & Jennings, 1997; Yonelinas & Jacoby, 1995). For example, Jacoby and colleagues established habits through the repeated pairing of stimulus words and then in a memory task directed participants to give habit-inconsistent responses to word-pair fragments. Errors in this paradigm represent failures to override the habitual pairings. Such slips were found to increase when conscious control was reduced by, for example, distracting participants during test performance. Interestingly, Jacoby and colleagues derived estimates of the degree of cognitive controlBfrom comparing error rates on habit-inconsistent trials with those on trials on which participants tried to respond habitually, and these proved to vary independently of estimates of habitual responding.

In general, studies of action slips highlight the potentially conflicting outcomes of intentional and habitual processes and thereby support the premise that these represent separate systems guiding behavior. Yet, this research also demonstrates how these systems interact. Specifically, habitual errors tend to occur when conscious control is reduced because people are preoccupied or distracted. Furthermore, the habitual errors that occur may be foreshadowed by intended actions, in that the errors tend to share movements and objects with intended actions.

Habits and Intentions Separately Guide Behavior: Evidence of the Separate Determinants of Action

Some of the strongest evidence for the separate systems guiding behavior comes from the unique factors that influence each. That is, characteristic sets of factors influence the potency of habits and the potency of intentions, and these thereby determine the extent to which each systems influences behavior.

Determinants of controlled, intentional processes. The strength of controlled, intentional processes depends largely on people=s ability and motivation to develop and implement intentions (Fazio, 1990). The research we have considered in this chapter so far suggests that in daily life, people=s motivation and ability is typically not sufficient to override most habitual, automatic responses. That is, the typical form of the interaction between habitual and intentional guides to action has been a pattern in which intentions have a minimal effect when habits are present to guide behavior (see Figure 1, also Verplankan et al., 1998). The circumscribed effect of intentions is understandable given that motivational control appears to be a limited resource and to be easily depleted by small acts of self-regulation (Baumeister, Muraven, & Tice, 2000). Additionally, ability to control practiced behavior patterns can be limited by lack of knowledge about behaviorBas illustrated by the initial step in many behavior modification programs of gathering information about a problematic behavior (e.g., keeping a food diary to identify eating habits). Assuming such limits on motivation and ability do not influence habitual responding, everyday habits will often run-off uninterrupted, even when they conflict with explicit intentions.

Experimental evidence that controlled but not habitual responding is limited when ability is reduced comes from Jacoby and colleagues= work that we mentioned in the prior section on action errors (see summary in Kelley & Jacoby, 2000). In this research, intentional recollection but not habits was impaired by (a) aging and the associated reduction in cognitive ability, (b) distractions that divided people=s attention from their response, and (c) time limits that reduced the opportunity to respond. Thus, a variety of cognitive deficits impair intentional but not habitual responding.

In addition to being uniquely vulnerable to fluctuations in ability and motivation, the intentional system is likely to yield more fluid dispositions than the habitual one. This is because changes in intention do not derive from such slow-moving factors as repetition in stable contexts (see Smith & DeCoster, 2000), but shift more rapidly with changes in logical reasoning as well as with spontaneous influences. Thus, in predictive models, intentions are a function of evaluations of behavior, subjective norms, and perceived control (Ajzen, 2002). A vivid demonstration that intentions but not habits are responsive to new information was provided by Ferguson and Bibby=s (2002) investigation of the determinants of blood donation. Donors with little experience, whose behavior was intentionally guided, became discouraged from future donation when their fellow donors fainted. Presumably, their intentions became less favorable with this powerful demonstration of negative consequences. However, participants who had donated with sufficient frequency in the past to establish a habit continued to donate, undeterred by the plight of fellow donors. Presumably, such negative outcomes did not influence habitual guides to action.

In general, then, intentions are influenced by a unique set of factors that appear to have lesser effects on habits. Specifically, the impact of intention is impaired by limits in people=s ability and motivation, and intentions are likely to shift more rapidly than habits and change as a function of new information.

Determinants of habitual processes. The separate nature of habitual and intentional systems is also suggested by the unique set of factors that influence performance of habits. Our definition of habits as repeated behavior in stable contexts identifies the two factors that should most strongly affect strength of habitual responding. Indeed, in laboratory settings, greater repetition in stable contexts has been found to yield stronger automatic, habitual memory responses, whereas practice does not appear to have the same degree of facilitative effects on conscious memory use (Kelley & Jacoby, 2000). Regarding stability of the supporting context, when contexts change people can not longer mindlessly repeat past actions, and automatic habitual performance is interrupted. In contrast, acts guided by intentions should typically be unaffected by context changes (i.e., except when motivation or opportunity are affected).

To test these ideas about context changes, Wood, Tam, and Witt (2003, Study 1) examined the newspaper-reading and exercising behavior of college students transferring to a new university. These students were of interest because transferring schools can disrupt the context supporting such everyday behaviors. Several weeks before the transfer and several weeks after, students reported on their habits, intentions, and aspects of the performance context. As expected, when the transfer brought about changes in context, students= habits were disrupted. Then, they apparently were forced to follow more thoughtful guides to behavior. For example, for reading the newspaper, an important supporting context was whether students= roommate(s) read a paper. A change in the roommates= behaviorBeither a shift to a roommate who read a daily paper or a shift to one who did not, appeared to disrupt the smooth performance of reading habits. Then, students= behavior no longer followed the habit they had established at their former school, and instead their behavior came in line with their intentions to read the paper. In contrast, participants with a newspaper-reading habit at their old school whose roommates= behavior was stable across the transfer maintained their behavior regardless of their explicit intentions. Finally, for students without an established habit, behavior closely followed from intentions. Thus, the overall pattern of findings revealed that disruptions in environmental support for behavior blocked the automatic performance of habits but did not affect the extent to which intentions influenced behavior.

Changes in the contextual cues supporting habits impede efficient repetition and focus people on their intentions because negotiating such changes requires thought. Evidence that thinking about behavior yields a shift from the habitual to intentional modes of performance comes from research by Wood, Tam, & Witt (2003, Study 2). At the beginning of the study, all students reported on their past behavior. Then, in one experimental condition, students wrote a short paragraph explaining their intentions for an everyday activity (e.g., exercising, watching TV, reading the newspaper), and gave an overall rating of their intentions for that behavior. After three weeks, students were recontacted and their behavior was assessed. For students who had previously established habits for these behaviors, thought about intentions increased the correspondence between intentions and future behavior. Students without habits were relatively unaffected by thought, and continued to be guided by their intentions before and after the manipulation. Thus, when people with habits were encouraged to thoughtfully re-evaluate their intentions, these new intentions emerged as guides to behavior. In combination, Wood et al.=s (2003) studies suggest that changes in the context supporting habits render behavior a function of intentions because such changes instigate thought and encourage people to use intentions as behavior guides.

Habits and the Self

The mode used to guide behavior has a variety of implications for self-related processes. Habits can be considered to be part of people=s goal attainment and self-regulatory systems, yielding predictable outcomes with considerable efficiency. In this capacity, habits are important components of self-systems. Yet, people do not necessarily incorporate habitual behavior into their self-concepts. Because habitual modes of performance involve minimal thought and are not guided by intention, to the actor, habits may not appear to implicate the self.

Self-regulation. The efficiency that emerges from acting without thinking has important self-regulatory benefits, given that decision-making about even a single behavior can impair people=s ability to direct subsequent actions (Baumeister et al., 1998; Baumeister et al., 2000). Economic models frame efficiency in terms of saving decision costs, given that habits enable people to avoid costs of individual choice and responsibility, including gathering and processing information and weighing outlay against input (Lindbladh & Lyttkens, 2002).

Evidence of that the efficiency of habit performance yields self-control benefits emerged in Wood, Quinn, & Kashy=s (2002) diary study of everyday behavior. Their participants reported lesser stress and feelings of being overwhelmed and out of control when engaged in habitual than nonhabitual behaviors. It is also interesting to note that the deliberation associated with a single nonhabitual behavior increased feelings of stress, but that performing multiple nonhabits simultaneously did not lead to further increments in stress levels. Thus, the benefits of habits emerged during normal activity levels and were not limited to those times when especially high demands were placed on people=s behavior, as when they were deliberating about multiple behaviors simultaneously.

Given these self-regulatory benefits of automating behavior, it is perhaps no surprise that people perform about half of their behaviors in everyday life without thinking about them (Quinn & Wood, 2003; Wood, Quinn, & Kashy, 2002). Although this estimate is considerably lower than prior speculations that around ninety-five percent of daily acts are performed automatically (see Bargh & Chartrand, 1999), even our lower estimate renders a picture of people as relatively detached from their ongoing activityBat least half of the time.

The value of habitual behavior to conserve decision-making resources should be especially evident when people are working to achieve effort-intensive goals. When people have to deliberate about behavior, they should be less able to allocate thought and effort to achieve effortful long-term goals. In support of this prediction, Witt and Wood (2003) found that people engaged in a 14-week exercise program to improve their physical fitness were more likely to achieve their fitness goals by the end of the program if their other top goals and strivings during that period required minimal thought to accomplish. These findings suggest that devoting minimal thought to activities in one domain allows people to succeed with other, more attention-demanding activities in other domains. In general, structuring life around a core of habits can be beneficial to goal pursuit because it allows people to Abranch out@ and accomplish additional goals.

Emotion. Mode of behavior performance has implications for emotional experience as well as for the contents of consciousness. Specifically, diary assessments of everyday behavior revealed that habits were associated with less intense emotions than nonhabits (Wood et al., 2002). This pattern could reflect Frijda=s (1988) laws of emotion, in which Acontinued pleasures wear off; continued hardships lose their poignancy@ (p. 353). From this perspective, people adapt psychologically and physiologically to the emotion-inducing aspects of repeated actions in repeated contexts in a way that reduces emotional intensity. In addition, the lesser intensity emotions associated with habits can be explained by Mandler=s (1975) theory of mind and emotion. In this view, emotions arise when the interruption of one=s plans and organized behavior sequences generates arousal (i.e., of the autonomic nervous system) and initiates an interpretation of the interruption that implicates particular emotions. Because infrequently performed behaviors and behaviors in unstable contexts are plausibly more likely than habitual behaviors to encounter difficulties and interference, nonhabitual behaviors are more likely to be associated with emotions. Finally, from the perspective of Carver and Scheier=s (1998, 1999) cybernetic model of self-regulation, emotions emerge from discrepancies between people=s behavior or related outcomes and their goals and self-standards. Specifically, emotions emerge from changes in the rate at which behaviors and outcomes are meeting or failing to meet self-goals. Although Carver and Scheier offer few speculations about the factors that might lead people to recognize such discrepancies and thus to experience emotion, it seems plausible that people will attend more to discrepancies when deliberating about behavior than when acting habitually. In sum, a variety of theoretical perspectives can account for people=s less intense emotions when engaged in habitual than nonhabitual behavior.

One implication of the limited emotional responses associated with habitual behavior is that, when people do experience emotions during habit performance, the emotions are likely to be linked to their thoughts rather than their behavior (Wood et al., 2002). Because habits require minimal explicit thought, people are able to entertain unrelated concerns, and the intruding thoughts may themselves be highly emotionally charged. Thus, when performing behaviors habitually, people report that their emotions sometimes are associated with their actions and sometimes with their unrelated thoughts. In contrast, the emotions associated with nonhabitual behaviors emerge from action over thought.

This general pattern in which habit-related emotions are low in intensity and elicited by thoughts could have implications for broader lifestyle patterns. We speculate that people whose lives are characterized by large proportions of habitual behavior can find that their emotional experiences become dull and subdued over time. Much like Thurber=s (1942) character, Walter Mitty, they may find that their own ruminations and fantasies are the primary source of their emotions rather than their immediate behavioral experiences.

Understanding of the self. In contrast to the marked role of habits in self-regulation and emotion, habitual behavior likely has few implications for people=s self-concepts. Given the low intensity emotions and lack of thought associated with habits, people are unlikely to believe that habits reflect their values, desires, or preferences. To the extent that people do not consciously guide habits, these behaviors may be viewed as imposed by situational factors rather than the self (see Wegner & Wenzlaff, 1996). These ideas were supported by the diary reports of everyday behavior in Wood et al. (2002). In general, participants judged their habits as relatively uninformative about the self and relatively unimportant to attaining personal goals. Furthermore, the causal mechanisms responsible for habits were not readily apparent to participantsBhabits were rated as less likely than nonhabits to arise from internal causes or from external causes such as the situation or the circumstance. The one exception to this overall pattern is that people reported experiencing lesser pride and worse feelings about the self when they engaged in habitual than nonhabitual behavior. Thus, habitual behaviors proved to be, at best, unrelated to participants= self-concepts and at worst, associated with negative aspects of the self.

People=s negative spin on habitual behavior can be understood as part of the dissociation between the implicit intentions that guide habits and people=s explicit intentions and goals. This dissociation is easy to understand when habits were not originally intended and emerged, for example, as side-effects of other intended actions; then explicit intentions may never have been formed for that behavior. Yet, even when habits were initially intended, the guiding intentions that become implicit may differ from explicit intentions, because explicit reasoning processes are more sensitive to shifts in goal structures, capabilities, and available opportunities (Smith & DeCoster, 2000). This reasoning bears some resemblance to Wilson, Lindsey, and Schooler=s (2000) analysis of dual attitudes, in which people access and rely on implicit attitudes except when motivated and able to override these with their explicit attitudes.

In daily life, the disconnection between habitual behavior and the self has a number of implications. For example, if people do not see themselves as especially responsible for their habits, they may not believe that they have sufficient efficacy to change such acts. Also, goals achieved through routinized activity may not be a strong source of pride. Thus, for example, healthy lifestyle decisions that become routinized as part of one=s daily behavior may not yield a sense of personal accomplishment because the behavior does not appear to be volitional.

Conclusion and Summary of Functions of Habituating Behavior

In the present chapter we have argued that behavior can be guided through relatively separate habitual and intentional processes. For frequently performed behaviors in stable contexts, behavioral intentions become implicit and recurring environmental cues can activate practiced behavior routines in a process that occurs largely outside of people=s awareness. Thus, habitual behavior can be initiated and performed without intention.

Our evidence that the implicit processes guiding habit performance can proceed separately from explicitly intentional action was drawn from several sources. First, research in cognitive psychology and the neurobiology of memory systems has identified automatic, habitual systems that appear to guide behavior relatively independently from conscious, controlled processes. Additionally, habits and intentions appear to be independent predictors of future behavior when considered jointly in a research design. Specifically, intentions generally have minimal impact on everyday behavior when habits have been formed. Furthermore, studies of action slips have demonstrated that habitual and intentional performance modes can generate separate, conflicting guides to action. In addition, separate sets of factors appear to influence each performance system, with motivation and ability influencing the more fluid intentional system and practice and stable contextual cues influencing habit performance. Finally, we reported the results of diary studies of everyday life that demonstrate the characteristic patterns of thought, emotion, and self-beliefs associated with each performance mode.

Overall, we outlined a highly textured picture of the benefits and costs associated with the mode of behavior performance. The cognitive economy and performance efficiency of habits potentially frees people to engage in other thoughtful activities such as rumination about past events and planning for future ones. Also, habit performance is not likely to deplete self-regulatory resources in the same way as deliberative behavior and this may allow people to conserve regulatory strength. Yet, these potential benefits co-occur with clear disadvantages of automating behavior.

The disadvantages to habituating behavior outlined in this chapter include (a) subdued emotions associated with behaviorBhabits have an insulating quality that reduces the immediacy of emotional experience, (b) minimal experience of pride in habits, (c) the perception that habits are not self-relevant and not useful in attaining personal goals, and (d) a slow-changing system that may not be sufficiently responsive to fluctuations in the relevant stimuli (e.g., Fazio, Ledbetter, & Towles-Schwen, 2000; Verplanken & Aarts=s, 1999, habitual mind-sets). In general, these varying benefits and costs of automating behavior highlight the importance of strategically using habits in daily life to accomplish tasks efficiently with minimal stress and yet still enact desired behaviors and maintain a sense of personal involvement and emotional engagement in ongoing experience.

References

Aarts, H., & Dijksterhuis, A. (2000). Habits as knowledge structures: Automaticity in goal-directed behavior. Journal of Personality and Social Psychology, 78, 53-63.

Abelson, R. P. (1981). Psychological status of the script concept. American Psychologist, 36, 715-729.

Ajzen, I. (1987). Attitudes, traits, and actions: Dispositional prediction of behavior in personality and social psychology. In L. Berkowitz (Ed.) Advances in experimental social psychology (pp. 1-63). San Diego, CA: Academic Press.

Ajzen, I. (2002). Residual effects of past on later behavior: Habituation and reasoned action perspectives. Personality and Social Psychology Review, 6, 107-122.

Albarracin, D., Kumkale, G. T., & Johnson, B. T. (2002). Influences of population and methodological factors on reasoning in condom use: A meta-analysis. Manuscript under review.

Bargh, J. A., & Chartrand, T. L. (1999). The unbearable automaticity of being. American Psychologist, 54, 462-479.

Bargh, J. A., Chen, M., & Burrows, L. (1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71, 230-244.

Bargh, J. A., & Ferguson, M. J. (2000). Beyond behaviorism: On the automaticity of higher mental processes. Psychological Bulletin, 126, 925-945.

Bargh, J. A., Gollwitzer, P. G., Lee-Chai, A., Barndollar, K., & Trotschel, R. (2001). The automated will: Nonconscious activation and pursuit of behavioral goals. Journal of Personality and Social Psychology, 81, 1014-1027.

Barker, R. G., & Schoggen, P. (1978). Measures of habitat and behavior output. In R. G. Barker & assoc. (Ed.), Habitats, environments, and human behavior: Studies in ecological psychology and eco-behavioral science from the Midwest Psychological Field Station, 1947-1972 (pp. 229-244). San Fransciso: Jossey-Bass.

Baumeister, R. F., Bratslavsky, E., Muraven, M., & Tice, D. M. (1998). Ego depletion: Is the active self a limited resource? Journal of Personality and Social Psychology, 74, 1252-1265.

Baumeister, R. F., Muraven, M., & Tice, D. M. (2000). Ego depletion: A resource model of volition, self-regulation, and controlled processing. Social Cognition, 18, 130-150.

Bem, D. J. (1972). Self-perception theory. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 6, pp. 1-62). San Diego, CA: Academic Press.

Bouton, M. E., Nelson, J. B., & Rosas, J. M. (1999). Stimulus generalization, context change and forgetting. Psychological Bulletin, 125, 171-186.

Brandstätter, V., Lengfelder, A., & Gollwitzer, P. M. (2001). Implementations intentions and efficient action. Journal of Personality and Social Psychology, 81, 946-960.

Caldwell, J. I., & Masson, M. E. (2001). Conscious and unconscious influences of memory for object location. Memory and Cognition, 29, 285-295.

Carver, C. S., & Scheier, M. F. (1998). On the self-regulation of behavior. New York: Cambridge University Press.

Carver, C. S., & Scheier, M. F. (1999). Themes and issues in the self-regulation of behavior. In R. S. Wyer (Ed.,), Perspectives on behavioral self-regulation: Advances in social cognition Volume XII (pp. 1-106). Mahwah, NJ: Erlbaum.

Chen, M., & Bargh, J. A. (1999). Consequences of automatic evaluation: Immediate behavioral predispositions to approach or avoid the stimulus. Personality and Social Psychology Bulletin, 25, 215-224.

Dijksterhuis, A., Bargh, J. A., & Miedema, J. (2000). Of men and mackerels: Attentions and automatic behavior. In H. Bless & J. P. Forgas (Eds.), Subjective experience in social cognition and behavior (pp. ). Philadelphia: Psychology Press.

Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich.

Fazio, R. H. (1990). Multiple processes by which attitudes guide behavior: The MODE model as an integrative framework. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 23, pp. 75-109). San Diego, CA: Academic Press.

Fazio, R. H., Ledbetter, J. E., & Towles-Schwen, T. (2000). On the costs of accessible attitudes: Detecting that the attitude object has changed. Journal of Personality and Social Psychology, 78, 197-210.

Fazio, R. H., & Olson, R. H. (2003). Implicit measures in social cognition research: Their meaning and use. Annual Review of Psychology, 54, 297-327.

Ferguson, E., & Bibby, P. A. (2002). Predicting future blood donor returns: Past behavior, intentions, and observer effects. Health Psychology, 21, 513-518.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Frijda, N. H. (1988). The laws of emotion. American Psychologist, 43, 349-358.

Gabrieli, J. D. E. (1993). Cognitive neuroscience of human memory. Annual Review of Psychology, 49, 87-115.

Gilbert, D. T. (1998). Ordinary personology. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 2, pp. 89-150). Boston: McGraw-Hill.

Goldberg, L. R. (1992). The development of markers for the big 5 factor structure. Psychological Assessment, 4, 26-42.

Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54, 493-503.

Greve, W. (2001). Traps and gaps in action explanation: Theoretical problems of a psychology of human action. Psychological Review, 108, 435-451.

Hay, J. F., & Jacoby, L. L. (1996). Separating habit and recollection: Memory slips, process dissociations, and probability matching. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 1323-1335.

Heckhausen, H., & Beckmann, J. (1990). Intentional action and action slips. Psychological Review, 97, 36-48.

Hull, C. L. (1943). Principles of behavior: An introduction to behavior theory. New York: Appleton-Century-Crofts.

Jacoby, L. L., Yonelinas, A. P., & Jennings, J. M. (1997). The relation between conscious and unconscious (automatic) influences: A declaration of independence. In J. D. Cohen & J. W. Schooler (Eds.), Scientific approaches to consciousness (pp. 13-47). Mahwah, NJ: Erlbaum.

James, W. (1890). The principles of psychology (Vol. 2). New York: Holt.

Jog, M. S., Kubota, Y., Connolly, C. I., Hillegaart, V., & Graybiel, A. M. (1999). Building neural representations of habits. Science, 286, 1745-1749.

Kelley, C. M., & Jacoby, L. L. (2000). Recollection and familiarity: Process-dissociation. In E. Tulving & F. I. M. Craik (Eds.), The Oxford handbook of memory (pp. 215-228). New York: Oxford University Press.

Langer, E. J. (1989a). Mindfulness. Reading, MA: Addison-Wesley.

Langer, E. J. (1989b). Minding matters: The consequences of mindlessness-mindfulness. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 22, pp. 137-173). Orlando, FL: Academic Press.

Lindbladh, E., & Lyttkens, C. H. (2002). Habit versus choice: The process of decision-making in health-related behaviour. Social Science & Medicine, 55, 451-465.

Lippa, Y., & Goldstone, R. L. (2001). The acquisition of automatic response biases through categorization. Memory & Cognition, 29, 1051-1060.

Logan, G. D. (1988). Toward an instance theory of automatization. Psychological Review, 95, 492-527.

Mandler, G. (1975). Mind and emotion. New York: Wiley.

McDaniel, M. A., & Einstein, G. O. (2000). Strategic and automatic processes in prospective memory retrieval: A multiprocess framework. Applied Cognitive Psychology, 14, S127-S144.

Menon, G., Raghubir, P., & Schwarz, N. (1995). Behavioral frequency judgments: An accessibility-diagnosticity framework. Journal of Consumer Research, 22, 212-228.

Metcalfe, J., & Mischel, W. (1999). A hot/cool analysis of delay of gratification: Dynamics of willpower. Psychological Review, 106, 3-19.

Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124, 54-74.

Pashler, H. (1994). Dual-task interference in simple tasks: Data and theory. Psychological Bulletin, 116, 220-244.

Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition: The Loyola symposium (pp. 55-85). Hillsdale, NJ: Erlbaum.

Proctor, R. W., & Dutta, A. (1993). Do the same stimulus-response relations influence choice reactions initially and after practice? Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 922-930.

Quinn, J. M., & Wood, W. (2003). Habits across the lifespan. Manuscript in progress.

Randall, D. M., & Wolff, J. A. (1994). The time-interval in the intention-behavior relationship: Meta-analysis. British Journal of Social Psychology, 33, 405-418.

Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., & Congdon, R. T. (2001). HLM5: Hierararchical linear and nonlinear modeling. Chicago: Scientific Software International.

Reason, J. (1979). Actions not as planned: The price of automatisation. In. G. Underwood & R. Stevens (Eds.), Aspects of consciousness, Vol. 1: Psychological Issues (pp. 67-89). London: Academic Press.

Reason, J. (1984). Absent-mindedness and cognitive control. In J. E. Harris & P. E. Morris (Eds.), Everyday memory: Actions and absent-mindedness (pp. 113-132). London: Academic Press.

Reason, J., & Lucas, D. (1984). Using cognitive diaries to investigate naturally occurring memory blocks. In J. E. Harris & P. E. Morris (Eds.), Everyday memory: Actions and absent-mindedness (pp. 53-70). London: Academic Press.

Ronis, D. L., Yates, J. F., & Kirscht, J. P. (1989). Attitudes, decisions, and habits as determinants of repeated behavior. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 213-239). Hillsdale, NJ: Erlbaum.

Schacter, D. L. (1992). Understanding implicit memory: A cognitive neuroscience approach. American Psychologist, 47, 559-569.

Schacter, D. L. (1995). Implicit memory: A new frontier for cognitive neuroscience. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 815-824). Cambridge, MA: MIT Press.

Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals and understanding: An inquiry into human knowledge structures. Hillsdale, NJ: Erlbaum.

Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127-190.

Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search and attention. Psychological Review, 84, 1-66.

Schwarz, N. (1990). Assessing frequency reports of mundane behaviors: Contributions of cognitive psychology to questionnaire construction. In C. Hendrick & M. S. Clark (Eds.), Review of personality and social psychology: Research methods in personality and social psychology (Vol. 11, pp. 98-119). Newbury Park, CA: Sage.

Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325-343.

Smith, E. R., & DeCoster, J. (2000). Dual-process models in social and cognitive psychology: Integration and links to underlying memory systems. Personality and Social Psychology Review, 4, 108-131.

Spence, K. W. (1956). Behavior theory and conditioning. New Haven: Yale University Press.

Squire, L. R., Knowlton, B., & Musen, G. (1993). The structure and organization of memory. Annual Review of Psychology, 44, 453-495.

Thurber, J. (1942). My world - and welcome to it. New York: Harcourt, Brace, & Co.

Trafimow, D. (2000). Habit as both a direct cause of intention to use a condom and as a moderator of the attitude-intention and subjective norm-intention relations. Psychology and Health, 15, 383-393.

Triandis, H. C. (1977). Interpersonal behavior. Monterey, CA: Brooks/Cole.

Vallacher, R. R., & Wegner, D. M. (1987). What do people think they=re doing: Action identification and human behavior. Psychological Review, 94, 3-15.

Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behavior: Is habit an empty construct or an interesting case of goal-directed automaticity? In W. Stroebe & M. Hewstone (Eds.), European Review of Social Psychology (Vol. 10, pp. 101-134). Chichester, UK: Wiley.

Verplanken, B., Aarts, H., van Knippenberg, A., & Moonen, A. (1998). Habit versus planned behaviour: A field experiment. British Journal of Social Psychology, 37, 111-128.

Verplanken, B., & Herabadi, A. ( 2001). Individual differences in impulse buying tendency: Feeling and no thinking. European Journal of Personality, 15, S71-S83.

Wegner, D. M. (2002).The illusion of conscious will. Cambridge, MA: MIT Press.

Wegner, D. M., & Bargh, J. A. (1998). Control and automaticity in social life. In D. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (4th ed., Vol.1, pp. 446-496). Boston: McGraw-Hill.

Wegner, D. M., & Wenzlaff, R. M. (1996). Mental control. In E. T. Higgins & A. W. Kruglanski (Eds.), Social psychology: Handbook of basic principles (pp. 466-492). New York: Guilford.

Wilson, T. D., Lindsey, S., & Schooler, T. Y. (2000). A model of dual attitudes. Psychological Review, 107, 101-126.

Witt, M., & Wood, W. (2003). Goal success as a function of people=s limited capacity for thought. Manuscript in progress.

Wood, W., Quinn, J. M., & Kashy, D. (2002). Habits in everyday life: The thought and feel of action. Journal of Personality and Social Psychology, 83, 1281-1297.

Wood, W., Tam, L., & Witt, M. (2003). Habitual behaviors and vulnerability to changes in context and thought. Manuscript in progress.

Yonelinas, A. P., & Jacoby, L. L. (1995). Dissociating automatic and controlled processes in a memory-search task: Beyond implicit memory. Psychological Research, 57, 156-165.

Figure Caption

Figure 1. Path diagrams from Ouellette and Wood (1998) depicting the prediction of behavior from intention and past behavior. The top panel reports findings for behaviors performed monthly or less often and in changing contexts (e.g., getting flu shots, mamograms). The bottom panel reports findings for behaviors that could be performed daily or weekly and that often occur in stable contexts (e.g., drinking coffee, wearing seatbelts).

***p < .001

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[i]. Although Smith and DeCoster=s (2000) discussion of dual-mode analyses emphasized cognitive reasoning and thus differentiated between deliberative versus simpler, heuristic modes of thought, we have here extended their distinction to contrast intentional versus habitual modes of performance.

2. The predictive form of the model also has been challenged. In a philosophically-oriented critique, Greve (2001) noted the model=s failure to explain how cognitive states generate behavior, along with its tautological definition of actions and intentions (i.e., because actions are logically dependent on intentions in the model, intentions cannot be an independent cause of actions). Greve (2001) concluded that the theory of planned behavior identifies the contents of consciousness (e.g., beliefs, desires, values, norms) on which intentions are based, and thus is more appropriately labeled the Atheory of planning of behavior@ (p. 445).

3. Reanalysis of the thought protocols provided by participants in Wood, Quinn, and Kashy=s (2002) diary research revealed that, among participants reporting that they performed an action frequently, those who also reported that they performed the act in the same context almost every time indicated thinking about their behavior less (i.e., 44% thought about their behavior) than participants who reported that they performed the act in varying contexts (50% thought about their behavior).

4. In addition, the construct of mindlessness differs from habit. As Langer (1989a, 1989b) cautioned, although both involve relatively effortless, invariant behavior, habits are more closely linked to behavioral response. In contrast, mindlessness reflects a general mental state of the organism as a whole (Langer, 1989b).

5. To ensure that the differential thought was not artifactual and emerged because, for example, habitual behaviors were less interesting or easier to perform than nonhabitual ones, Wood et al. (2002) selected a few behaviors (e.g., driving a car) and compared habitual and nonhabitual performance within these behavioral domains. These within-domain findings revealed that, like the results reported in the text, greater thought was directed to nonhabitual than habitual acts.

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.12 ***

.62 ***

.40

Future Behavior

Past Behavior

Intention

.45 ***

.27 ***

.70

Future Behavior

Past Behavior

Intention

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