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Habits and Behavioral Complexity – Dynamic and Distinct Constructs
Health Psychology Review
... Phillips and Mullan [7] argue that complexity is an inherent characteristic of behaviors themselves, involving the number of meaningful, separable (e.g., in instigation and execution) and substitutable sub-actions or steps, which may require greater time to prepare and execute intrinsic motivation to form and maintain habits. Contrastingly, Rebar, Rhodes [9] argue that rewards and behavioral complexity are related but distinct constructs, and complexity is not solely a characteristic of the behavior itself but an interaction between the behavior, context (e.g., barriers and facilitators), and actor (e.g., skill level, knowledge acquisition, and cognitive load). Similarly, Kaushal and Rhodes [10] consider behavioral complexity as the perceived difficulty of a behavior, influenced by an individual's self-efficacy, with McCloskey and Johnson [11] agreeing but also considering the time, attention, and planning required to prepare and execute a behavior. ...
... For factors of behavioral complexity, the participants were asked to indicate whether 12 factors of behavioral complexity, as proposed by the literature [7,[9][10][11], were influential or not influential to how complex a behavior is deemed to be (1 = not influential, 2 = influential). Specifically, they were instructed, "Please indicate whether the following factors are influential to how complex a behavior is for the average person to do on a regular basis." ...
... Participants perceived all proposed characteristics as influential to the complexity of a behavior. Researchers have previously speculated that characteristics include the number of steps and motivation required for a behavior [7], supportiveness of the context, an individual's skill, knowledge acquisition and cognitive load [9], perceived difficulty of a behavior, self-efficacy [10], and the time, attention, and planning involved in a behavior [11]. However, this study expands on previous research using data-driven methods to ...
A behavior’s complexity may impact habit formation, with implications for habit-based public health and environmental intervention designs. However, there are varying conceptualizations of behavioral complexity, hindering the synthesis of findings. To develop a unified definition, the aim of this study was to explore perceptions of behavioral complexity and identify behaviors that exemplify aspects of complexity. Participants (N = 225) completed a questionnaire concerning the complexity of various health and environmental behaviors, the importance of complexity characteristics previously identified by researchers (novelty, difficulty, steps, planning, immediacy of reward, time, attention, skill, mental resources, self-efficacy, motivation for a behavior, and supportiveness of the context) and demographics. Participants considered all proposed characteristics to be important. Complex behaviors (e.g., abstaining from smoking and taking insulin shots), compared to simple behaviors (e.g., eating fruit and stretching), are more likely to be true to the previously identified characteristics. Perceived complexity is influenced by several salient characteristics. Results may contribute to a synthesized definition and underpin future research to better identify behavior change techniques to foster habitual behaviors of varying complexity. Hence, researchers, practitioners, and policymakers may identify common barriers and facilitators of behavior to target in interventions. However, further research is required to contextualize the findings.
... They state that behavioral complexity is a process "dependent on context, task and actor" (page 1) that "…is the result of the interaction of the behavior, person, and context; and it varies depending on both between-person and within-person factors, such as skill and knowledge acquisition, demand on working memory, and access to resources" (Page 2). Rebar et al (2022) liken the concept of behavioral complexity to the concept of complexity in the topic of skill acquisition. Certainly we agree that as we become more proficient and practiced and certain tasks, the steps can become relegated to procedural memory or "chunked actions" (Graybiel, 1998), and the procedure becomes less taxing for working memory. ...
... And even if a person becomes practiced (fast) at running 5 kilometers, that will still take more time than it will take them to swallow a pill. Rebar et al. (2022) make the excellent points that there will be individual-and context-specific differences in how difficult it is for an individual to engage in a behavior. We agree that there will certainly be individual differences that influence whether individuals can engage in a behavior and form habits, such as conscientiousness and diurnal preference (Hisler, Phillips, & Krizan, 2017). ...
... The exercise still has meaningfully separable parts (of each instance of behavior), whereas taking a pill does not. Importantly, although Rebar et al (2022) claim that all health behaviors are complex, citing that even taking a pill requires separate actions, such as filling a prescription, we maintain that simple health behaviors do not have meaningfully separable components in each instance of enactment. For example, although taking a medication requires filling a prescription, filling a prescription is not a preparatory step for each instance of taking a pill; it is a separate behavior that is also important for overall adherence and would require its own habit formation process. ...
... Phillips and Mullan [7] argue that complexity is an inherent characteristic of be-54 haviors themselves, involving the number of meaningful, separable (e.g., in instigation 55 and execution) and substitutable sub-actions or steps, which may require greater time to 56 prepare and execute, and intrinsic motivation to form and maintain habits. Con-57 trastingly, Rebar, Rhodes [11] argue that rewards and behavioral complexity are related 58 but distinct constructs, and complexity is not solely a characteristic of a behavior itself, 59 but an interaction between the behavior, context (e.g., barriers and facilitators) and actor 60 (e.g., skill level, knowledge acquisition, cognitive load). Similarly, Kaushal To work towards a unified definition of behavioral complexity, the aim of this study 79 was to explore people's perceptions of the characteristics of complexity, previously pro-80 posed by researchers. ...
... Characteristics of behavioral complexity214 Participants perceived all proposed characteristics as influential to the complexity 215 of a behavior. Researchers have previously speculated that characteristics include the 216 number of steps and motivation required for a behavior [7], supportiveness of the con-217 text, an individual's skill, knowledge acquisition and cognitive load[11], perceived diffi-218 culty of a behavior, self-efficacy [12], and the time, attention and planning involved in a 219 behavior [13]. However, this study expands on previous research using data-driven 220 methods to synthesize and test these ideas to reveal that all characteristics are influen-221 tial. ...
A behavior’s complexity may impact habit formation, with implications for habit-based public health and environmental intervention designs. However, there are varying conceptualizations of behavioral complexity, hindering synthesis of findings. To develop a unified definition, the aim of this study was to explore perceptions of behavioral complexity and identify behaviors that exemplify aspects of complexity. Participants (N = 225) completed a questionnaire concerning the complexity of various health and environmental behaviors, the importance of complexity characteristics previously identified by researchers (novelty, difficulty, steps, planning, immediacy of reward, time, attention, skill, mental resources, self-efficacy, and motivation for a behavior, and supportiveness of the context) and demographics. Participants considered all proposed characteristics to be important. Complex behaviors (e.g., abstaining from smoking, taking insulin shots), compared to simple behaviors (e.g., eating fruit, stretching) are more likely to be true to the previously identified characteristics. Perceived complexity is influenced by several salient characteristics. Results may contribute to a synthesized definition and underpin future research to better identify behavior change techniques to foster habitual behaviors of varying complexity. Hence, researchers, practitioners and policymakers may identify common barriers and facilitators of behavior to target in interventions. But further research is required to contextualize the findings.
... skill, knowledge, cognitive load), contextual (e.g. barriers and facilitators) and behavioural factors (Rebar et al., 2023), the perceived difficulty of a behaviour influenced by self-efficacy (Kaushal & Rhodes, 2015), and the time, attention and planning required for a behaviour (McCloskey & Johnson, 2019). Varying definitions may contribute to heterogeneity in behaviour categorisations in studies, and therefore, inconsistent assessments and mixed findings. ...
... Recognising the operation of habits in different action phases can resolve debates around the relevance of habit to complex actions (Gardner & Lally, 2023;Phillips & Mullan, 2023;Rebar et al., 2023). Behavioural complexity refers to the intricacy of executing an action, not instigating it. ...
Habit change is often seen as key to successful long-term behaviour change. Making 'good' behaviours habitual-that is, ensuring a behaviour is prompted automatically on exposure to situational cues, based on cue-response associations learnt through context-consistent repetition-is portrayed as a mechanism for sustaining such behaviours over time. Conversely, disrupting 'bad' habits is expected to terminate longstanding unwanted actions. Yet, some commentators have suggested that the role of habit in real-world behaviour and behaviour change has been overstated. Such critiques highlight a gap between habit theory and the reality of human behaviour 'in the wild'. This state-of-the-field review aims to narrow this gap. Building on a core distinction between habit and habitual behaviour, our review seeks to offer interpretations of habit theory and evidence that will better manage intervention designers' expectations regarding how modifying habit can realistically be expected to promote behaviour change. We emphasise that habit is just one potential influence on behaviour at any given moment, and highlight instances in which habit may dominate over intention, and in which intention may dominate over habit, in determining behaviour frequency. We suggest that, while it may assist behaviour maintenance, habit formation may be neither necessary nor sufficient to sustain real‐world behaviour change. We draw attention to the various ways in which habit may be ‘broken’ (i.e., disrupted), and discern the implications of each habit disruption mechanism for long‐term cessation of unwanted behaviours.
... The kind of research portrayed in this paper is highly sensitive to cultural, economic, and disciplinary differences in workplace settings (Lewis et al., 2021;Li et al., 2023) 11 . Habit formation in complex environments involves an assortment of psychological and social dimensions (Rebar, Rhodes, & Verplanken, 2023) 12 ; changes made in some arenas could have an impact on others. Some modifications of the content and style of AI management systems might be necessary for various audiences and contexts. ...
... These results point to a qualitative distinction where relatively simple behaviors (e.g., taking a daily supplement) can be instigated relatively automatically in the way that habits are typically characterized, whereas support from self-regulation strategies becomes increasingly frequent for increasingly complex behaviors (e.g., exercise, preparing vegetables for dinner), even when the habit to instigate the behaviors is equally strong. Complexity can be defined a priori based on objective features of the behavior, such as the number of separable steps to execute the behavior, or the behavior's temporal duration (Phillips & Mullan, 2022), or, alternatively, as a person's subjective perception of multiple dimensions, such as self-reported challenge, attentional demands, complexity, necessary planning, or duration (Boynton, 2005;Rebar et al., 2023). Inspection of Figure 2 indicates that participants did not always agree with a priori researcher-defined complexity, and participant-rated complexity also varied greatly within each type of behavior. ...
Objective
We tested the hypothesis that complex behaviors are commonly supported by self‐regulation strategies, even when those behaviors are supported by strong instigation habits.
Background
Goal‐directed and habit‐mediated processes arise from separable systems that have been suggested to seldomly interact.
Results
Self‐regulation strategy use was lower for habitually instigated simple behaviors compared to nonhabitually instigated simple behaviors. However, participants' use of self‐regulation strategies increased with the increasing complexity of behaviors, even when complex behaviors were habitually instigated. The difference in the extent of strategy use between habitually and nonhabitually instigated actions was absent when behavioral complexity was particularly high.
Conclusion
These results point to a qualitative distinction—while simple behaviors may progress in a relatively automatic and unthinking manner, complex behaviors receive frequent support from self‐regulation strategies, even if they are instigated habitually.
Understanding factors that might contribute to sustained moderate‐to‐vigorous intensity physical activity (MVPA) after the initial start of participation is important. The purpose of this study was to examine the changes in PA habit and identity, two constructs purported to drive behavioral maintenance, among parents of young (< 13 years of age) children participating in a PA intervention across 3 months. Parents (team sport n = 58; individual PA n = 60; control n = 66) completed measures of PA habit, PA identity, and self‐reported MVPA at baseline, and post‐randomization at 6 weeks and 3 months. Identity and habit showed an increase across time, and these changes interacted with group condition assignment. Identity increased for participants in the team sport condition and was significantly different from a stable profile among those assigned to the control condition. Participants in the individual PA condition increased identity from 6 weeks to 3 months. Habit had a more attenuated change across time, with participants in the team sport condition showing an increase from 6 weeks to 3 months compared with the other conditions. The findings contribute to our understanding of maintenance processes and represent the first exploration of how involvement in team sport might shape subsequent habit and identity development.
Background
. Forming a habit - i.e., a cue-behaviour association learned through repeated performance - has been proposed to promote behaviour maintenance, but some commentators have questioned whether simple cue-behaviour associations can direct complex actions. This paper addresses this issue by drawing on a proposed distinction between 'habitual instigation', whereby habit automatically prompts the impulse to initiate an action episode, and 'habitual execution', whereby habit automates performance of sub-actions involved in that episode. Theory predicts that frequency should be determined by habitual instigation, but not habitual execution, irrespective of complexity. This study examined the influence of habitual instigation and execution on the frequency of four behaviours ranging in complexity.
Method
. A sample of 173 participants, recruited via an online platform, completed questionnaire measures of perceived complexity, and instigation and execution habit, for four behaviours expected to vary in complexity (checking one's phone, drinking sugary drinks, using social media, using public transport). Of these, 118 participants self-reported behaviour frequency one week later. ANOVAs compared complexity perceptions across behaviours, and multivariate regressions modelled effects of instigation and execution habit on behaviour.
Results
. Drinking sugary drinks was rated the simplest behaviour, followed by phone-checking, and using social media. Using public transport was rated most complex. Across behaviours, instigation-behaviour correlations tended to be stronger than execution-behaviour correlations, and instigation habit predicted behaviour but execution did not.
Conclusion
. Instigation habit regulated performance frequency of simple and complex behaviours alike. While complexity may be an important consideration when developing new habits, it is less relevant to the relationship between established habits and behaviour. Interventions should promote instigation habits to maintain even complex behaviours.
Behavioural theories, predictions, and interventions should be relevant to complex, real-world health behaviours and conditions. Habit theory and habit formation interventions show promise for predicting and promoting, respectively, longer-term behaviour change and maintenance than has been attained with theories and interventions focused only on deliberative behavioural factors. However, the concept of habit has largely been treated as uniform across different types of behaviours. In this conceptual review, we contend that the definitional aspects of habit differ at a conceptual level for simple versus more complex behaviours, with ramifications for prediction, promotion, and measurement of habits. Specifically, habits are defined as direct context-response associations learned through repeatedly rewarded responding-but what is meant by "response" and "reward" depends upon the complexity of the behaviour. We review literature that suggests (1) responses in complex habits have separable and substitutable components (vs a single and static, unitary component) and (2) rewards for complex habits are necessarily continued and intrinsic (vs temporary and extrinsic, respectively). We discuss some empirical and theoretical questions raised by these issues around behavioural complexity and habit. Lastly, we outline the ramifications of these issues for habit measurement (habit strength and habit formation) via self-report and objective measures.
A clear rationale can be made for promoting long-term regular physical activity (PA), yet despite some attempts to operationalize “maintenance,” no robust definition has been agreed upon, beyond arbitrary time frames of regular PA. This has likely impaired the advancement of theory and practice. The purpose of this critical narrative review was to first overview the conception of maintenance and co-requisite theoretical constructs in theories used in PA research. Our subsequent aims were to engage in a critical analysis of this literature to propose a working definition of PA maintenance followed by recommendations for future research. Relevant behavioral theories were parsed for references to maintenance or maintenance-specific constructs and constructs most likely associated with maintenance were overviewed from a recent systematic review. Based on this information, we suggest PA maintenance be operationalized as a process marked by a shift in the mechanisms of action determining behavioral performance, that engender greater perceived behavioral enactment efficiency. We suggest that maintenance should not be considered an absolute state of behavioral performance (e.g., a stage), as some constructs that were critical to behavioral performance during initiation will still be critical during PA continuation. Based on this definition, we propose a method of falsifiability hypothesis testing of theoretical constructs that may determine the maintenance process. Finally, the review concludes with suggestions for future research using this operationalization of maintenance including measure development, tests of latency to reach the peak maintenance process, validating constructs critical to determining maintenance, exploration of the contextual and individual moderators of maintenance formation, and the development of an omnibus dynamic model of initiation, continuation, and maintenance in PA behavior change.
Objective: Conceptual models of addiction highlight self-efficacy and motivation as key variables important during a smoking quit attempt; however, recent research has primarily focused on self-efficacy. Given the importance of motivation in these models, a clearer understanding of the effects of motivation during a smoking quit attempt is needed. Method: This study utilized ecological momentary assessment (EMA) to investigate the dynamic effects of motivation and self-efficacy early in a quit attempt. Participants were 356 smokers (45% male; 34% African American, 33% non-Hispanic White, 33% Latino). Participants completed EMAs of motivation, self-efficacy, and smoking for 4 days prequit through 1 week postquit, and returned for a follow-up assessment at 4 weeks postquit. Trajectory parameters of motivation and self-efficacy (mean, slope, and volatility) were analyzed in separate and combined regression models to predict smoking outcomes. Results: Prequit results showed that parameters of motivation and self-efficacy were not associated with smoking on quit day. Postquit analyses revealed that participants with lower mean levels of motivation and self-efficacy were more likely to smoke at the end of Week 1. Moreover, individuals with decreasing levels of motivation over the first week of their quit attempt were more likely to be smoking at the end of Week 4. Conclusions: These findings highlight the need to incorporate dynamic measures of motivation in smoking research. Furthermore, the results underscore the value of utilizing EMA methods and trajectory parameters to gain a more nuanced understanding of the dynamic effects that key mechanisms have on smoking during a quit attempt.
Until recently, most studies investigating the acute relationships between affective and physical feeling states and physical activity were conducted in controlled laboratory settings, whose results might not translate well to everyday life. This review was among the first attempts to synthesize current evidence on the acute (e.g., within a few hours) relationships between affective and physical feeling states and physical activity from studies conducted in free-living, naturalistic settings in non-clinical populations. A systematic literature search yielded 14 eligible studies for review. Six studies tested the relationship between affective states and subsequent physical activity; findings from these studies suggest that positive affective states were positively associated with physical activity over the next few hours while negative affective states had no significant association. Twelve studies tested affective states after physical activity and yielded consistent evidence for physical activity predicting higher positive affect over the next few hours. Further, there was some evidence that physical activity was followed by a higher level of energetic feelings in the next few hours. The evidence for physical activity reducing negative affect in the next few hours was inconsistent and inconclusive. Future research in this area should consider recruiting more representative study participants, utilizing higher methodological standards for assessment (i.e., electronic devices combined with accelerometry), reporting patterns of missing data, and investigating pertinent moderators and mediators (e.g., social and physical context, intensity, psychological variables). Knowledge gained from this topic could offer valuable insights for promoting daily physical activity adoption and maintenance in non-clinical populations.
Reasoned action approaches have primarily been applied to understand exercise behaviour for the past three decades, yet emerging findings in unconscious and Dual Process research show that behavior may also be predicted by automatic processes such as habit. The purpose of this study was to: (1) investigate the behavioral requirements for exercise habit formation, (2) how Dual Process approach predicts behaviour, and (3) what predicts habit by testing a model (Lally and Gardner in Health Psychol Rev 7:S137-S158, 2013). Participants (n = 111) were new gym members who completed surveys across 12 weeks. It was found that exercising for at least four bouts per week for 6 weeks was the minimum requirement to establish an exercise habit. Dual Process analysis using Linear Mixed Models (LMM) revealed habit and intention to be parallel predictors of exercise behavior in the trajectory analysis. Finally, the habit antecedent model in LLM showed that consistency (β = .21), low behavioral complexity (β = .19), environment (β = .17) and affective judgments (β = .13) all significantly (p < .05) predicted changes in habit formation over time. Trainers should keep exercises fun and simple for new clients and focus on consistency which could lead to habit formation in nearly 6 weeks.
Physical activity is regulated by controlled processes, such as intentions, and automatic processes, such as habits. Intentions relate to physical activity more strongly for people with weak habits than for people with strong habits, but people's intentions vary day by day. Physical activity may be regulated by habits unless daily physical activity intentions are strong. University students (N = 128) self-reported their physical activity habit strength and subsequently self-reported daily physical activity intentions and wore an accelerometer for 14 days. On days when people had intentions that were weaker than typical for them, habit strength was positively related to physical activity, but on days when people had typical or stronger intentions than was typical for them, habit strength was unrelated to daily physical activity. Efforts to promote physical activity may need to account for habits and the dynamics of intentions.
Objective:
Sedentary behavior is a health risk but little is known about the motivational processes that regulate daily sedentary behavior. This study was designed to test a dual-process model of daily sedentary behavior, with an emphasis on the role of intentions and habits in regulating daily sedentary behavior.
Method:
College students (N = 128) self-reported on their habit strength for sitting and completed a 14-day ecological momentary assessment study that combined daily diaries for reporting motivation and behavior with ambulatory monitoring of sedentary behavior using accelerometers.
Results:
Less than half of the variance in daily sedentary behavior was attributable to between-person differences. People with stronger sedentary habits reported more sedentary behavior on average. People whose intentions for limiting sedentary behavior were stronger, on average, exhibited less self-reported sedentary behavior (and marginally less monitored sedentary behavior). Daily deviations in those intentions were negatively associated with changes in daily sedentary behavior (i.e., stronger than usual intentions to limit sedentary behavior were associated with reduced sedentary behavior). Sedentary behavior also varied within people as a function of concurrent physical activity, the day of week, and the day in the sequence of the monitoring period.
Conclusions:
Sedentary behavior was regulated by both automatic and controlled motivational processes. Interventions should target both of these motivational processes to facilitate and maintain behavior change. Links between sedentary behavior and daily deviations in intentions also indicate the need for ongoing efforts to support controlled motivational processes on a daily basis.
Tested the hypothesis that self-motivation through proximal goal setting serves as an effective mechanism for cultivating competencies, self-percepts of efficacy, and intrinsic interest. 40 children (7.3–10.1 yrs of age) who exhibited gross deficits and disinterest in mathematical tasks pursued a program of self-directed learning under conditions involving either proximal subgoals, distal goals, or no goals. Results of the multifaceted assessment provide support for the superiority of proximal self-influence. Under proximal subgoals, Ss progressed rapidly in self-directed learning, achieved substantial mastery of mathematical operations, and developed a sense of personal efficacy and intrinsic interest in arithmetic activities that initially held little attraction for them. Distal goals had no demonstrable effects. In addition to its other benefits, goal proximity fostered veridical self-knowledge of capabilities as reflected in high congruence between judgments of mathematical self-efficacy and subsequent mathematical performance. Perceived self-efficacy was positively related to accuracy of mathematical performance and to intrinsic interest in arithmetic activities. (25 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Abstract
Cognitive load theory has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance. The theory assumes a limited capacity working memory that includes partially independent subcomponents to deal with auditory/verbal material and visual/2- or 3-dimensional information as well as an effectively unlimited long-term memory, holding schemas that vary in their degree of automation. These structures and functions of human cognitive architecture have been used to design a variety of novel instructional procedures based on the assumption that working memory load should be reduced and schema construction encouraged. This paper reviews the theory and the instructional designs generated by it.
"Food deserts," areas characterized by poor access to healthy and affordable food, may contribute to social and spatial disparities in diet and diet-related health outcomes. However, the extent to which food deserts exist is debated. We review the evidence for the existence of food deserts in socioeconomically disadvantaged areas.
We conducted a systematic review of primary, quantitative, observational studies, published in English or French, that used geographic or market-basket approaches in high-income countries. The literature search included electronic and hand searches and peer-reviewed and grey literature from 1966 through 2007. We also contacted key researchers to identify other studies. We analyzed the findings and quality of the studies qualitatively.
Forty-nine studies in 5 countries met inclusion criteria; the amount and consistency of the evidence varied by country. These studies were a mix of geographic and market-basket approaches, but the methodologic quality of studies and completeness of reported findings were mixed. We found clear evidence for disparities in food access in the United States by income and race. Findings from other high-income countries were sparse and equivocal.
This review suggests that food deserts exist in the United States, where area-level deprivation compounds individual disadvantage. Evidence for the existence of food deserts in other high-income nations is weak.
Pioneering work in the 1940s and 1950s suggested that the concept of 'chunking' might be important in many processes of perception, learning and cognition in humans and animals. We summarize here the major sources of evidence for chunking mechanisms, and consider how such mechanisms have been implemented in computational models of the learning process. We distinguish two forms of chunking: the first deliberate, under strategic control, and goal-oriented; the second automatic, continuous, and linked to perceptual processes. Recent work with discrimination-network computational models of long- and short-term memory (EPAM/CHREST) has produced a diverse range of applications of perceptual chunking. We focus on recent successes in verbal learning, expert memory, language acquisition and learning multiple representations, to illustrate the implementation and use of chunking mechanisms within contemporary models of human learning.
To illustrate the differing thoughts and emotions involved in guiding habitual and nonhabitual behavior, 2 diary studies were conducted in which participants provided hourly reports of their ongoing experiences. When participants were engaged in habitual behavior, defined as behavior that had been performed almost daily in stable contexts, they were likely to think about issues unrelated to their behavior, presumably because they did not have to consciously guide their actions. When engaged in nonhabitual behavior, or actions performed less often or in shifting contexts, participants' thoughts tended to correspond to their behavior, suggesting that thought was necessary to guide action. Furthermore, the self-regulatory benefits of habits were apparent in the lesser feelings of stress associated with habitual than nonhabitual behavior.
The present model outlines the mechanisms underlying habitual control of responding and the ways in which habits interface with goals. Habits emerge from the gradual learning of associations between responses and the features of performance contexts that have historically covaried with them (e.g., physical settings, preceding actions). Once a habit is formed, perception of contexts triggers the associated response without a mediating goal. Nonetheless, habits interface with goals. Constraining this interface, habit associations accrue slowly and do not shift appreciably with current goal states or infrequent counterhabitual responses. Given these constraints, goals can (a) direct habits by motivating repetition that leads to habit formation and by promoting exposure to cues that trigger habits, (b) be inferred from habits, and (c) interact with habits in ways that preserve the learned habit associations. Finally, the authors outline the implications of the model for habit change, especially for the self-regulation of habit cuing.
Background
Previous research suggests that there is a bidirectional relationship between incidental affect (i.e., how people feel in day-to-day life) and physical activity behavior. However, many inconsistencies exist in the body of work due to the lag interval between affect and physical activity measurements.
Purpose
Using a novel continuous-time analysis paradigm, we examined the temporal specificity underlying the dynamic relationship between positive and negative incidental affective states and moderate-to-vigorous physical activity (MVPA).
Methods
A community sample of adults (n = 126, Mage = 27.71, 51.6% Male) completed a 14-day ambulatory assessment protocol measuring momentary positive and negative incidental affect six times a day while wearing a physical activity monitor (Fitbit). Hierarchical Bayesian continuous-time structural equation modeling was used to elucidate the underlying dynamics of the relationship between incidental affective states and MVPA.
Results
Based on the continuous-time cross-effects, positive and negative incidental affect predicted subsequent MVPA. Furthermore, engaging in MVPA predicted subsequent positive and negative incidental affect. Incidental affective states had a greater relative influence on predicting subsequent MVPA compared to the reciprocal relationship. Analysis of the discrete-time coefficients suggests that cross-lagged effects increase as the time interval between measurements increase, peaking at about 8 h between measurement occasions before beginning to dissipate.
Conclusions
The results provide support for a recursive relationship between incidental affective states and MVPA, which is particularly strong at 7–9 hr time intervals. Future research designs should consider these medium-term dynamics, for both theory development and intervention.
Physical distancing remains an important initiative to curb COVID‐19 and virus transmission more broadly. This exploratory study investigated how physical distancing behaviour changed during the COVID‐19 pandemic and whether it was associated with identity with virus transmission avoidance and physical distancing habit strength. In a longitudinal, multinational study with fortnightly repeated‐assessments, associations and moderation effects were considered for both overall (person‐level means) and occasion‐specific deviations in habit and identity. Participants (N = 586, M age = 42, 79% female) self‐reported physical distancing behavioural frequency, physical distancing habit strength, and identity with avoiding virus transmission. Physical distancing followed a cubic trajectory, with initial high engagement decreasing rapidly before increasing again near study end. Physical distancing was associated with both overall and occasion‐specific virus transmission avoidant identity and physical distancing habit strength. People with strong virus transmission avoidant identity engaged in physical distancing frequently regardless of fluctuations in habit strength. However, for those with weaker virus transmission avoidant identity, physical distancing was strongly aligned with fluctuations in habit strength. To enhance engagement in physical distancing, public health messaging might fruitfully target greater or more salient virus‐transmission avoidance identity and stronger physical distancing habit.
Efforts to guide peoples’ behavior toward environmental sustainability, good health, or new products have emphasized informational and attitude change strategies. There is evidence that changing attitudes leads to changes in behavior, yet this approach takes insufficient account of the nature and operation of habits, which form boundary conditions for attitude-directed interventions. Integration of research on attitudes and habits might enable investigators to identify when and how behavior change strategies will be most effective. How might attitudinally driven behavior change be consolidated into lasting habits? How do habits protect the individual against the vicissitudes of attitudes and temptations and promote goal achievement? How might attitudinal approaches aiming to change habits be improved by capitalizing on habit discontinuities and strategic planning? When and how might changing or creating habit architecture shape habits directly? A systematic approach to these questions might help move behavior change efforts from attitude change strategies to habit change strategies.
Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Skin cancer is highly burdensome, but preventable with regular engagement in sun protective behaviors. Despite modest effectiveness of sun-protective behavior promotional efforts thus far, rates of engagement in sun-protective behaviors remain low. More is needed to understand motivation for using sunscreen, wearing sun-protective clothing, and seeking shade. This study tested whether the links of intention and habit strength with behavior differed between sun-protective behaviors. It was hypothesized that sun protective behaviors would be predicted by both habit and intention and that intention-behavior associations would be weaker for people with stronger habits. Participants residing in Queensland, Australia (N = 203; 75.96% female; M age = 37.16 years, SD = 14.67) self-reported their intentions and habit strength about sun-protective behavior for the next 7 days. Participants were followed-up 7 days later to self-report their sun-protective behavior. Multilevel modeling, accounting for nesting of multiple behaviors within-person, revealed that habit moderated the intention strength – behavior association and this moderation effect did not differ as a function of which behavior was being predicted. People with strong or moderate habit strength tended to act in line with their intentions; however, for people with very weak habits (2 SD < M), there was less alignment between their intention and behavior. These findings suggest that habit plays a facilitative role in the implementation of strong sun protective behavior intentions. Interventions should consider how to encourage intention and habit to enhance sun-protective behaviors and reduce the burden of skin cancer from sun exposure.
Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.1903380 .
Objectives
This study examined the impact of the COVID‐19 lockdown on the physical activity (PA) of UK adults and potential motivational determinants of such behaviour.
Design and methods
A survey was conducted with 1,521 UK adults recruited through Prolific.co in early June 2020. Along with demographic information, questions assessed current PA, changes in PA modalities (i.e., overall, around the home, for transport, in the workplace, in the local neighbourhood, at recreation/sport facilities) related to the lockdown, and beliefs about capabilities, opportunities, and motivations according to the COM‐B model. A series of logistic regressions were constructed to examine associations between shifts in the PA modalities and the COM‐B components.
Results
The majority of respondents (57%) had either maintained or increased their levels of PA during the COVID‐19 lockdown. However, the proportion meeting PA guidelines (31%) was low and engagement in sedentary‐related behaviour for both work and leisure increased substantially during the lockdown. The components of the COM‐B model were associated with shifts in PA. In particular, physical opportunity (odds ratios ranging from 1.14 to 1.20) and reflective motivation (odds ratios ranging from 1.11 to 1.25) appeared to be the most consistent predictors of behaviour.
Conclusions
If UK adults believed they had the physical opportunity and were motivated, they were more likely to have maintained or increased their PA during the COVID‐19 lockdown. However, the majority of adults are not meeting the UK guidelines on PA and the prevalence of PA is substantially lower than national surveys prior to the pandemic.
Statement of contribution
What is already known on this subject? The COVID‐19 pandemic has significantly disrupted the daily routines of citizens globally.
Engagement in physical activity appears to have declined as a result of the requirement to self‐isolate and stay in place.
The COM‐B model of behaviour change is a useful framework for identifying the correlates and determinants of behaviour.
What does this study add? Though most UK adults maintained or increased their engagement in physical activity during the COVID‐19 pandemic, the majority did not meet recommended guidelines.
Reflective processes and physical opportunity were the primary predictors of change in physical activity.
Regular moderate and vigorous intensity physical activity has numerous health benefits, yet low participation rates. Research of the determinants of physical activity and subsequent interventions has primarily focused on deliberative motivational and self-regulatory processes. In this chapter, we overview the current evidence and conception of physical activity habit formation and focus on how more recent research may overcome its past controversial nature among physical activity scientists. Observational evidence is clearly supportive of a relationship between self-reported habit and physical activity, even after controlling for motivational and self-regulatory processes. A more recent separation between the phases (initiation, execution) of physical activity has helped delineate where habit may determine physical activity. Furthermore, separations among different concepts of intention (decision, strength) may help improve our understanding of how deliberative motivation and habit interact and co-determine behavior. While intervention research of habitual physical activity is scarce, early results suggest attending to specific conditions (contextual repetitions, cues, scripts) can expedite and improve the likelihood of habit formation. We conclude the chapter with a discussion of areas for future research including how individual differences may facilitate or impede physical activity habit formation, the potential role of oppositional behavioral habits in physical inactivity, and habitual physical activity among special populations. Full text available at: http://hdl.handle.net/1828/15577
TItis volume is the first effort to compile representative work in the emerging research area on the relationship of disability and physical environment since Barrier-Free Environments, edited by Michael Bednar, was published in 1977. Since that time, disability rights legislation like the Americans, with Disabilities Act in the United States, the worldwide growth of the independent-living move ment, rapid deinstitutionalization, and the maturation of functional assessment methodology have all had their impact on this research area. The impact has been most noticeable in two ways-fostering the integration of environmental vari ables in rehabilitation research and practice, and changing paradigms for environ mental interventions. As the contributions in this volume demonstrate, the relationship of disabil ity and physical environment is no longer of interest primarily to designers and other professionals concerned with managing the resources of the built environ ment. The physical environment has always been recognized as an important variable affecting rehabilitation outcome. Until recently, however, concepts and tools were not available to measure its impact in clinical practic~ and outcomes research. In particular, lack of a theoretical foundation that integrated environ ment with the disablement process hampered development of both research and clinical methodology. Thus, the physical environment received little attention from the mainstream rehabilitation research community. However, this situation is changing rapidly.
Objectives:
The primary purpose of this study was to investigate how habit strength in a preparatory and performance phase predicts exercise while accounting for intention. The secondary purpose was to determine the strength of potential habit antecedents (affective judgement, perceived behavioural control, consistency, and cues) in both exercise phases.
Design:
This was a prospective study with measures collected at baseline and week 6.
Methods:
Participants (n?=?181) were a sample of adults (18-65) recruited across nine gyms and recreation centres who completed baseline and follow-up questionnaires after 6?weeks.
Results:
Intention (? = .28, p = .00) and habit preparation (? = .20, p = .03), predicted exercise, and change of exercise with coefficients of ? = .25, (p = .00) and ? = .18, (p = .04), respectively, across 6 weeks but not habit performance (p>.05).
Conclusions:
This study highlighted the distinction between the two phases of exercise and the importance of preparatory habit in predicting behaviour. Focusing on a consistent preparatory routine could be helpful in establishing an exercise habit. Statement of contribution What is already known on this subject? A recent meta-analysis found habit to correlate r?=?.43 with behaviour (Gardner, de Bruijn, & Lally, ). Verplanken and Melkevik () propose that habit in exercise should be measured in separate components. Phillips and Gardner () interpreted this as habitual instigation (thought) to exercise and execution. What does this study add? Extended pervious work and identified two distinct behavioural phases (preparation and performance) for exercise. Habit model revealed that temporal consistency was the strongest predictor in both phases of exercise. Intention and habit of preparatory behaviour predicted exercise fluctuations in gym members.
To illustrate the differing thoughts and emotion's involved in guiding habitual and nonhabitual behavior, 2,. diary studies were conducted in which participants provided hourly reports of their ongoing experiences. When participants were engaged in habitual behavior, defined as behavior that had been performed almost daily in stable contexts, they were likely to think about issues unrelated to their behavior, presumably because they did not have to consciously guide their actions. When engaged in nonhabitual behavior,or actions performed less often or :in shifting contexts; participants' thoughts tended to correspond to their behavior, suggesting that thought was necessary to guide action. Furthermore, the self-regulatory, benefits of habits were apparent in the lesser feelings of stress associated with habitual,. than nonhabitual behavior.
Objectives:
'Habit' is a process whereby situational cues generate behaviour automatically, via activation of learned cue-behaviour associations. This article presents a conceptual and empirical rationale for distinguishing between two manifestations of habit in health behaviour, triggering selection and initiation of an action ('habitual instigation'), or automating progression through subactions required to complete action ('habitual execution'). We propose that habitual instigation accounts for habit-action relationships, and is the manifestation captured by the Self-Report Habit Index (SRHI), the dominant measure in health psychology.
Design:
Conceptual analysis and prospective survey.
Methods:
Student participants (N = 229) completed measures of intentions, the original, non-specific SRHI, an instigation-specific SRHI variant, an execution-specific variant, and, 1 week later, behaviour, in three health domains (flossing, snacking, and breakfast consumption). Effects of habitual instigation and execution on behaviour were modelled using regression analyses, with simple slope analysis to test habit-intention interactions. Relationships between instigation, execution, and non-specific SRHI variants were assessed via correlations and factor analyses.
Results:
The instigation-SRHI was uniformly more predictive of behaviour frequency than the execution-SRHI and corresponded more closely with the original SRHI in correlation and factor analyses.
Conclusions:
Further, experimental work is needed to separate the impact of the two habit manifestations more rigorously. Nonetheless, findings qualify calls for habit-based interventions by suggesting that behaviour maintenance may be better served by habitual instigation and that disrupting habitual behaviour may depend on overriding habits of instigation. Greater precision of measurement may help to minimize confusion between habitual instigation and execution. Statement of contribution What is already known on this subject? Habit is often used to understand, explain, and change health behaviour. Making behaviour habitual has been proposed as a means of maintaining behaviour change. Concerns have been raised about the extent to which health behaviour can be habitual. What does this study add? A conceptual and empirical rationale for discerning habitually instigated and habitually executed behaviour. Results show habit-behaviour effects are mostly attributable to habitual instigation, not execution. The most common habit measure, the Self-Report Habit Index, measures habitual instigation, not execution.
Cognitive load theory (CLT) is one of the most important theories in educational psychology, a highly effective guide for the design of multimedia and other learning materials. This edited volume brings together the most prolific researchers from around the world who study various aspects of cognitive load to discuss its current theoretical as well as practical issues. The book is divided into three parts. The first part describes the theoretical foundations and assumptions of CLT, the second discusses the empirical findings about the application of CLT to the design of learning environments, and the third part concludes the book with discussions and suggestions for new directions for future research. It aims to become the standard handbook in CLT for researchers and graduate students in psychology, education, and educational technology.
The triarchic theory of human intelligence provides a broader basis for understanding intelligence than do many, if not most theories of intelligence. The theory is called “triarchic” because it consists of three parts. The first part relates intelligence to the internal world of the individual, specifying the mental mechanisms that lead to more or less intelligent behaviour. This part of the theory specifies three kinds of mental processes that are instrumental in learning how to do things, planning what things to do and how to do them, and in actually doing the things. The second part of the theory specifies at what point in a persons’ experience with tasks or situations intelligence is most critically involved in handling of those tasks or situation In particular, this part of the theory emphasises the roles of dealing with novelty and of automatising mental processing in intelligence. The third part of the theory relates intelligence to the external world of the individual, specifying three kinds of macroprocesses — adaptation, selection and shaping — that characterise intelligent behaviour in the everyday world. This part of the theory thus emphasises the role of environmental context in determining what constitutes intelligent behaviour in a given milieu.
The contributions in this special issue have been discussed with regard to the management of CL. In summary, the majority of the contributions investigate the worked example effect in order to reduce ECL. Furthermore, a new way of external management by artificially reducing ICL is discussed as well as the recent trend of managing an increase in GCL so as to redirect the learners' attention. This special issue highlights the crucial role of adequate design of computer-based learning environments which should rely on the recommended CLT-design principles. Finally, it was suggested to not only consider the external management of CL but also learners' internal management strategies. Thus, in order to further develop CLT the question of how learners really deal with CL should be addressed with the help of process analysis in future research. Finally, an important conceptual differentiation should be emphasised, which has neither been discussed in this special issue nor in other CLT-studies. With respect to learning criteria, one may distinguish studies that aim at short term learning performance and studies that aim at long term skill development and competence acquisition. Earlier research mainly investigated ECL-reduction with short time learning periods focusing on learning performance measures within one task. In contrast, more recent work is increasingly studying complex skill development based on several problem tasks. In my opinion for short term learning performance the classical ECL-reduction effects (e.g., split-attention, redundancy, modality) appear to be more significant, whereas for long term skill development deeper elaboration processing induced by external GCL-management and/or effective internal management seem more effective measures. Future research on CLT also needs to consider this conceptually driven distinction.
Objective
Two studies were conducted with the aim of closing the intention–behaviour gap for sunscreen use and sun protection behaviours by examining the influence of self-regulatory capacity on the prediction of sunscreen use (Study 1) and self-regulatory capacity and habit on sun protection behaviours (Study 2).
Design
Studies were conducted online. Participants completed questionnaires and cognitive measures and then reported behaviour one week later.
Main Outcome Measures
Questionnaires measuring intention and cognitive tasks measuring self-regulatory capacity were administered to 209 university students. One week later, participants reported behaviour. In Study 2, questionnaires measuring intentions, and habit and cognitive tasks measuring self-regulatory capacity were administered to 178 university students who reported behaviour one week later.
Results
Intention accounted for 7.1% of variance in sunscreen use, no measures of self-regulation accounted for variance in behaviour or moderated the intention–behaviour gap (Study 1). Intention, self-regulatory capacity and habit accounted for 56.1% of variance in sun protection behaviours (Study 2). Intention, self-regulatory ability and habit predicted behaviour, while habit moderated the intention–behaviour gap.
Conclusion
Interventions aimed at increasing sun protection behaviours should take into account level of intention, self-regulatory capacity and habit. Individuals may benefit from habit formation strategies and self-regulation training.
Habits are automatic behavioural responses to environmental cues, thought to develop through repetition of behaviour in consistent contexts. When habit is strong, deliberate intentions have been shown to have a reduced influence on behaviour. The habit concept may provide a mechanism for establishing new behaviours, and so healthy habit formation is a desired outcome for many interventions. Habits also however represent a potential challenge for changing ingrained unhealthy behaviours, which may be resistant to motivational shifts. This review aims to provide intervention developers with tools to help establish target behaviours as habits based on theoretical and empirical insights. We discuss evidence-based techniques for forming new healthy habits and breaking existing unhealthy habits. To promote habit-formation we focus on strategies to initiate a new behaviour, support context-dependent repetition of this behaviour, and facilitate the development of automaticity. We discuss techniques for disrupting existing unwanted habits, which relate to restructuring the personal environment and enabling alternative responses to situational cues.
Cognitive skill acquisition is acquiring the ability to solve problems in intellectual tasks, where success is determined more by subjects' knowledge than by their physical prowess. This review considers research conducted in the past ten years on cognitive skill acquisition. It covers the initial stages of acquiring a single principle or rule, the initial stages of acquiring a collection of interacting pieces of knowledge, and the final stages of acquiring a skill, wherein practice causes increases in speed and accuracy.