Motivation and emotion/Book/2025/Motivational dimensional model of affect

Motivational dimensional model of affect
What is the motivational dimensional model of affect and what are its implications?

Overview

Figure 1. Are emotions just feelings? Scenario Alex is getting ready for two big occasions. On Monday, Alex is on a creative project and is not stressed perhaps slightly bored. This low-arousal positive state facilitates wide reflection and brainstorming. On Tuesday, Alex has an imminent interview for a job. Now the feeling is stronger thrilled but apprehensive too and attention constricts to likely questions and responses. Both situations are accompanied by generally positive affect, but cognitive focus and behavioural reactions vary. This demonstrates the motivational dimensional model of emotion: feelings differ not just along valence (pleasant, unpleasant) or arousal (high, low), but also along motivational intensity, and this determines if attention constricts or dilates and if behaviour be exploratory or action oriented.

The motivational dimensional model of affect (MDMA) looks at emotions as more than just “good” or “bad” feelings. It accounts for them in terms of valence (pleasant-unpleasant), motivational direction (approach-avoidance), and motivational strength (the force of the urge to do something). The model regards emotions as adaptive systems: they energise behaviour with varying levels of emergency and goal orientation and form the way we concentrate, think, and react to the world.

Practical problem:

Why does it matter? Knowing how emotions direct attention and motivation applies with a broad brush. In academies, it can account for why certain moods foster creativity and others refine focus. In workplaces, it can help us understand how emotional states influence productivity and collaborative work. Clinically, it provides a framework for devising improved strategies for emotion regulation in anxiolytic or depressive illness.

Key concepts:

• Valence: the emotional tone (pleasant vs unpleasant).
• Motivational direction: whether an emotion pushes someone toward (approach) or away from (avoidance) a goal.
• Motivational intensity: the strength or urgency of that motivational drive.

This perspective helps resolve a puzzle in emotion science: why emotions that feel equally pleasant or unpleasant sometimes lead to opposite behaviours. According to MDMA for instance, anger and fear are both negative, high-arousal emotions, but they differ in action. Anger tends to activate approach behaviour (e.g., confronting a problem), whereas fear initiates avoidance behaviour (e.g., escaping danger) (Carver & Harmon-Jones, 2009; Gable & Harmon-Jones, 2010). In a similar way, low-level states like contentment or mild sadness broaden focus of attention and invite flexibility, whereas high-level states like desire or fear narrow focus and prepare for quick action.

Table 1. Key dimensions of the motivational dimensional model of affect

Valence	Motivational Direction	Motivational Intensity	Example Emotions	Likely Outcome
Positive	Approach	Low	Contentment, relaxation	Broad attention, flexibility
Positive	Approach	High	Desire, excitement	Narrow focus, goal pursuit
Negative	Avoidance	Low	Sadness, fatigue	Withdrawal, broad reflection
Negative	Avoidance	High	Fear, disgust	Narrow focus, avoidance
Negative	Approach	High	Anger	Confrontation, goal pursuit

Table 1 demonstrates how the motivational dimensional model of affect (MDMA) categories emotions using three key dimensions: valence (pleasant vs. unpleasant), motivational direction (approach vs. avoidance), and motivational intensity (low vs. high). By combining these dimensions, the model helps explain why emotions that seem similar in valence or arousal can still lead to very different patterns of thought and behaviour. For example, both fear and anger are negative and high in arousal, but fear typically promotes avoidance, whereas anger often energises approach.

Focus questions How does the MDMA extend or differ from categorical and dimensional models? How does motivational intensity influence attention, memory, and categorisation? What neural and physiological systems underlie approach and avoidance motivation? How do individual differences and context shape intensity effects? How can the MDMA be applied in mental health, education, productivity, and social behaviour? What are the model’s limitations, and where should future research go?

Theoretical framework

One of the primary puzzles in psychology has been to make sense of how emotions are catagorised and can be explained over the years. Scientists have proposed competing frameworks for what emotions are and how they come to exist and what they serve as purposes. Each would appear to offer a distinct way of conceptualising affect, some in terms of universals or categories others in the form of dimensions, and more recent theories still in terms of motivation and action. The development of this sequence also explains how the motivational dimensional model of affect evolved and why it was formulated and how it extends but goes beyond earlier approaches.

Categorical and dimensional models

Early theories treated emotion as a set of independent, biologically based categories. Categorical theories suggested a limited number of fundamental emotions such as anger, fear, sadness, joy, disgust, and surprise that are distinct and universally recognised across cultures (Ekman 1992). This strategy is common sense and grounded in evidence on facial expression, but it is also inflexible. It finds it hard to make sense of 'mixed emotions', cultural variations, and why states of different emotions could give very different actions.

Dimensional models, which conceptualised emotion not in terms of categorical entities that had to be completely homogeneous across individuals (as they would have to be if these categories were parallels for basic emotions), but instead as emotions present on continuous axes. For example, affect can be rendered in a two dimensional space consisting of valence (pleasant, unpleasant) and arousal (high, low) as per Russell’s circumplex model (1980). This model describes the basic structure of human emotional experience, but it is limited.

Approach avoidance traditions

Motivational theories closed this gap by focusing on the direction of action. Gray’s reinforcement sensitivity theory distinguished between the Behavioural Activation System (BAS), responding to reward and eliciting approach behaviour, and the Behavioural Inhibition System (BIS), responding to danger and eliciting avoidance (Gray, 1987). These systems account for why particular emotions energise pursuit and others urge caution. The BIS/BAS scales (Carver & White, 1994) are used to measure differences between people on these tendencies. This framework does not capture variation in intensity well, however. Mild worry and overwhelming fear are both avoidance states, but they differ dramatically in how strongly they press for action.

The motivational dimensional model of affect

The motivational dimensional model of affect expands earlier approaches by incorporating a third dimension: motivational intensity the strength of action tendencies in addition to valence and direction (Gable & Harmon-Jones, 2010). This addition helps explain why emotions that appear similar on other dimensions can have very different cognitive and behavioural consequences:

• High-intensity approach (e.g., desire, determination) narrows attention and increases persistence
• Low-intensity approach (e.g., contentment, amusement) broadens perspective and fosters creativity
• High-intensity avoidance (e.g., fear, disgust) narrows focus for rapid threat detection
• Low-intensity avoidance (e.g., sadness, fatigue) reduces immediate action but may promote reflection

Campbell and colleagues (2021) who demonstrated that while motivational intensity and valence tend to be correlated, they differ in important ways for emotions like sadness, anger, and amusement. This conclusion illustrates that intensity is not simply a synonym for valence, but a distinct and useful construct. Recurrent contentiousness highlights the challenges of accurately measuring intensity, but also underscores its value for elucidating the functional effect of emotions on thought and behaviour.

Key insight Previous theories of emotion each captured part of the puzzle categorical models mapped universals, dimensional models charted affective space, and approach–avoidance frameworks illuminated motivational direction. MDMA integrates these threads and pushes them forward, by adding motivational intensity, MDMA accounts for not only whether, people move toward or away from stimuli, but also the force with which they do so. This helps us to better understand why emotionally similar emotions of valence or arousal can still give rise to dramatically different pattens of thought and action.

Empirical research evidence

Attention and cognitive scope

Motivational intensity shapes attentional scope. High intensity approach states (e.g., desire, determination) narrow focus to goal relevant details, whereas low intensity states (e.g., contentment, amusement) broaden attention to wider context (Gable & Harmon-Jones, 2010). These effects are often tested with global and local tasks, showing that intensity not valence predicts attentional scope (Domachowska, Heitmann, & Deutsch, 2016; Gable & Harmon-Jones, 2016). A meta-analysis of approach avoidance tasks further indicates that biases to approach positives and avoid negatives depend on task design, suggesting context shapes emotional action tendencies (Phaf, Mohr, Rotteveel, & Wicherts, 2014). Example, classroom active breaks reset attention (Watson et al., 2021), and research on academic emotions shows motivational intensity can either drive persistence or broaden engagement depending on context (Loderer, Pekrun, & Lester, 2020). Together, these results highlight that attention is a clear domain where motivational intensity exerts context sensitive effects.

Memory, categorisation and higher cognition

These attentional shifts affect memory and higher-order thinking. High-intensity states direct encoding toward central, goal-relevant details, often at the cost of peripheral information, which supports persistence and accuracy in structured tasks. Low-intensity states broaden categorisation and associative thinking, allowing more flexible connections between ideas. This pattern reflects Fredrickson’s broaden-and-build theory , which suggests positive emotions expand cognitive scope and build lasting resources (Fredrickson, 2001). Positive affect can widen attentional selection and enhance creative problem solving (Rowe, Hirsh, & Anderson, 2007), while studies show that motivational intensity combined with resilience predicts stronger academic achievement in English as a foreign language learners (Yang & Wang, 2021). Motivational intensity, then, shapes not only immediate attention but also how information is processed for long term learning.

Figure 2. Brain stucture

Neural and physiological correlates

At the neural level, motivational intensity appears in asymmetrical cortical activity. Frontal EEG studies link approach motivation to greater left-frontal activation and avoidance motivation to greater right frontal activity (Harmon-Jones & Gable, 2018; Reznik & Allen, 2017). Meta-analyses suggest these effects are small and context-dependent, making EEG asymmetry more of a situational marker than a stable trait (Kuper, Käckenmester, & Wacker, 2019).

Neurochemical evidence adds to this picture, where approach states rely on dopamine-driven reward circuits such as the nucleus accumbens, while avoidance states engage the amygdala and insula for threat detection and defense (Knutson & Greer, 2008). Physiological studies show how rapidly these systems act seeing another person’s emotion can shift posture, trigger approach avoidance reactions, and change preferred interpersonal distance in real time (Lebert, Vergilino-Pérez, & Chaby, 2024). Together, these findings highlight how motivational intensity and direction are rooted in coordinated neural and bodily processes.

Emotion regulation and well being

Motivational intensity plays a key role in emotion regulation. Stronger emotions are more likely to trigger deliberate regulation efforts, which are linked to better psychological health (Gutentag et al., 2024). Classic models highlight the type of strategy such as reappraisal versus suppression as central to outcomes (Gross, 1998), but newer work shows that the effort invested matters too: daily studies find that regulation intensity predicts well-being more strongly than frequency alone (Wenzel & Rowland, 2025). Meta analyses add that maladaptive strategies like rumination and suppression predict poorer outcomes, while adaptive approaches such as reappraisal buffer against distress and psychopathology (Aldao, Nolen-Hoeksema, & Schweizer, 2010). Overall, motivational intensity not only drives the need for regulation but also shapes how effective regulation is in supporting resilience.

Individual differences and boundary conditions

Motivational intensity varies across people and contexts. Sensitivity in the behavioural activation (BAS) and inhibition (BIS) systems shapes approach and avoidance tendencies. Individuals high in BAS are more responsive to rewards, while those high in BIS are more sensitive to threats (Carver & White, 1994; Gray & McNaughton, 2000). Clinical research shows that depression is associated with reduced approach motivation (Kasch, Rottenberg, Arnow, & Gotlib, 2002), while anxiety involves heightened avoidance and vigilance (Barlow, 2000; Bijttebier, Beck, Claes, & Vandereycken, 2009). These tendencies can change, as interventions such as behavioural activation help restore functional levels of motivation. Personality also plays a role: extraversion relates to stronger approach states, while neuroticism predicts stronger avoidance motivation (Allen, Coan, & Nazarian, 2004). Although large-scale reviews show weak and inconsistent links between EEG asymmetry and personality (Kuper, Käckenmester, & Wacker, 2019; Reznik & Allen, 2018), traits such as openness and conscientiousness influence how motivational intensity is expressed. The Big Five framework therefore complements the MDMA.

Developmental, cultural, and biological factors provide further boundary conditions. Adolescents often show heightened approach motivation and greater risk taking due to immature regulatory systems (Steinberg, 2008), while older adults prioritise emotional meaning and regulation (Carstensen, 2006). Cross cultural research suggests that in collectivist settings, motivational intensity is shaped by social harmony goals, altering how emotions such as anger are expressed (Mesquita & Walker, 2003). Biological influences also matter. Dopamine related polymorphisms such as DRD4 and COMT contribute to variability in reward sensitivity and novelty seeking, though effects are modest and context dependent (Munafo, Yalcin, Willis-Owen, & Flint, 2008; Savitz & Ramesar, 2004). Hormonal reactivity adds another layer, as high cortisol responses under stress predict reduced approach behaviour and altered regulation in anxiety prone individuals (Klaassens et al., 2005; Meyer et al., 2023). Taken together, these findings highlight that motivational intensity develops through the interaction of dispositional, developmental, cultural, and biological processes.

Applications

Emotion regulation and goal pursuit and productivity

Regulating motivational intensity is essential for balancing urgency with flexibility where Motivational intensity is the heart of both emotion regulation and goal pursuit. Intensity states have the potential to energise rapid action but are risky for narrow focus, whereas low intensity states give a broader perspective and foster adaptability. For example, mindfulness, paced breathing, or cognitive reappraisal can reduce intensity to facilitate flexible responding (Fredrickson, 2001; Gross, 1998). If motivation is low, goal imagery, hyped music, or short deadlines can be used to increase intensity. On the other hand, Effort on regulation predicts well being better than frequency alone does (Wenzel & Rowland, 2025), and higher emotional intensity tends to predetermine strategy use in a ruminative direction rather than an appraisal direction (Kozubal, Szuster, & Wielgopolitan, 2023). These processes directly influence productivity. Low intensity positive emotions like calm or laughter broaden focus and foster creativity, whereas high-intensity emotions like determination narrow focus and fortify persistence (Gable & Harmon-Jones, 2010; Rowe, Hirsh, & Anderson, 2007). Scheduling work to align with these processes for a starting point of low intensity states to encourage idea generation and a change to high intensity ones for detailed execution which is likely to improve both individual and group outcome.

Mental health, education and group behaviour

Disruptions in motivational intensity are associated with a variety of psychological distresses. Depression is typically defined by low approach motivation, to be redressed by rewarding activities (Kasch, Rottenberg, Arnow, & Gotlib, 2002). Anxiety represents increased avoidance motivation, and can be treated with exposure treatment that systematically decreases avoidance and facilitates corrective learning (Barlow, 2000). Addictions often involve hyperapproach motivation, and thus require treatments to reduce reward seeking and augment regulatory control (Bijttebier, Beck, Claes, & Vandereycken, 2009). Intensity checking may also give the clinician useful information to provide tailoring treatment (Wenzel & Rowland, 2025). Similar processes also occur in the classroom. Approach emotions like curiosity, joy, and pride widen attention and long focus, whereas avoidance states like test anxiety they narrow early on  focus and lower performance (Pekrun, Elliot, & Maier, 2009). Classroom techniques using introductoons of low intensity positive states with humour or quiet starts and moderate high intensity states to keep focus going have improved learning. Active breaks also show how varying physiological intensity returns focus and enhances achievement (Watson et al., 2021). At a group level, motivational intensity also impels group behaviour. High level approach emotions such as anger will engage protest and advocacy, whereas avoidance emotions such as fear will inhibit partcipating (Carver & Harmon-Jones, 2009; van Zomeren, Leach, & Spears, 2012). Efficacy and hope fortify mobilisation by turning intrinsic motivation to collaborative action, and there is evidence showing viewing others emotions directly changes posture, initiates approach-avoidance behaviour, and alters interpersonal distance in real time (Lebert, Vergilino-Pérez, & Chaby, 2024). In combination, these results show how motivational intensity shapes resilience, learning, and group action in various settings.

How motivation shapes attention and brain Activity Scenario: Alex, a Year 9 student, is revising for a science test. At first, Alex feels calm and mildly curious, a low intensity approach state. In this mode, attention is broad: Alex notices patterns in the diagrams and makes connections across topics. Brain activity reflects this openness, with balanced frontal activation supporting flexible thinking. As the test approaches, Alex becomes determined to master key formulas. This shift into a high intensity approach state narrows attention. Now, Alex focuses sharply on the details, blocking out distractions. Neuroscientific research suggests that such states are accompanied by greater activity in the left frontal cortex and dopamine-rich circuits that support goal pursuit. Takeaway Alex’s experience illustrates how motivation shapes cognition and brain function. Low-intensity states broaden scope for exploration and integration, while high intensity states sharpen focus for detail and accuracy together optimising learning when balanced.

Future research and limitations

The Motivational Dimensional Model of Affect (MDMA) has deepened our understanding of how motivation shapes thought, emotion, and behaviour, but the research base is uneven. By going beyond traditional two dimensional accounts of affect, the model highlights the functional role of motivational direction and intensity. Yet there are clear challenges. Measurement is one of the biggest. Many studies use stand-ins such as arousal ratings or incentive cues, which can blur the distinction between intensity, valence, and arousal (Gable & Harmon-Jones, 2010). The model also overlaps with existing frameworks like the Circumplex Model and the Broaden and Build theory, but direct comparisons are rare. Moving forward, researchers need validated tools and experimental designs that can tease apart intensity from other factors and clarify how MDMA connects with or diverges from other models. Physiological methods such as pupillometry, heart rate variability, and mobile EEG show promise in capturing motivational intensity with greater accuracy and in real time.

The scope of research also remains limited. Most studies have focused on attentional scope, leaving areas such as memory, decision making, problem solving, and creativity less explored (Harmon-Jones, Gable, & Price, 2013). Positive emotions have received disproportionate attention, while the role of high and low intensity negative states like fear, sadness, or disgust is less understood, even though emerging findings show important differences (Threadgill & Gable, 2019). Individual differences and boundary conditions are another gaps. Personality traits, developmental stage, and cultural context likely shape how motivational intensity operates (Carver & White, 1994; Steinberg, 2008; Carstensen, 2006; Mesquita & Walker, 2003). Questions of ecological validity remain as well, since much of the evidence comes from short, controlled lab tasks that may not reflect daily life (Kuppens et al., 2013). Neural evidence such as frontal EEG asymmetry lends some support to the model but findings are mixed and still debated (Harmon-Jones, 2017; Reznik & Allen, 2017). Future research should make greater use of ecological momentary assessment, longitudinal studies, and interventions like mindfulness, active breaks, or goal priming to test the model in real world settings. New technologies such as wearable sensors and mobile EEG also offer opportunities to link neural and physiological markers with everyday motivational dynamics. By combining laboratory precision with naturalistic and applied approaches, researchers can better establish the boundaries of MDMA and strengthen its practical value.

Conclusion

The Motivational Dimensional Model of Affect (MDMA) expands emotion theory by emphasising not only valence and arousal but also the intensity and direction of motivational forces. Research shows that motivational intensity shapes attention, memory, neural and physiological activity, regulation, and individual differences. High intensity states tend to narrow focus, while low intensity states broaden scope, helping explain why emotions sometimes support flexible thinking and at other times sharpen detail-oriented processing. The model also offers valuable applied insights: in education, calm curiosity supports creativity while urgency drives focused work; in clinical settings, it distinguishes low motivational drive in depression from heightened avoidance in anxiety or excessive approach in addiction; and in group contexts, it explains how emotional intensity can mobilise or restrain collective behaviour.

Despite its promise, the model faces challenges. Measurement limitations, overemphasis on positive affect, and a lack of ecological validity remain obstacles. Future research should develop more precise tools, investigate underexplored domains, and test the model in real-world settings. By doing so, MDMA can advance theory and improve practice across learning, therapy, work, and social life. Emotions are not only about whether they feel good or bad, but about how strongly they drive action. Recognising motivational intensity reveals why emotions sometimes broaden our horizons and at other times sharpen our focus, offering a clearer lens for understanding and improving human behaviour.

See also

• Motivation impairment (Wikipedia)
• Emotional self-regulation (Book chapter, 2013)
• Motivation intensity (Wikiversity)

References

Campbell, N. C., Dawel, A., Edwards, M., & Goodhew, S. C. (2021). Does motivational intensity exist distinct from valence and arousal? Emotion. Advance online publication. https://doi.org/10.1037/emo0000945

Carver, C. S., & Harmon-Jones, E. (2009). Anger is an approach-related affect: Evidence and implications. Psychological Bulletin, 135(2), 183–204. https://doi.org/10.1037/a0013965

Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319

Domachowska, I., Heitmann, C., & Deutsch, R. (2016). Motivational intensity modulates global–local processing: Evidence from Navon tasks. Motivation and Emotion, 40(6), 902–913. https://doi.org/10.1007/s11031-016-9570-8

Ekman, P. (1992). An argument for basic emotions. Cognition & Emotion, 6(3–4), 169–200. https://doi.org/10.1080/02699939208411068

Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218–226. https://doi.org/10.1037/0003-066X.56.3.218

Gable, P. A., & Harmon-Jones, E. (2010). The motivational dimensional model of affect: Implications for breadth of attention, memory, and cognitive categorization. Cognition & Emotion, 24(2), 322–337. https://doi.org/10.1080/02699930903378305

Gable, P. A., & Harmon-Jones, E. (2016). The motivational dimensional model of affect: Implications for breadth of attention, memory, and cognitive categorisation. Frontiers in Psychology, 7, 1029. https://doi.org/10.3389/fpsyg.2016.01029

Gray, J. A. (1987). The psychology of fear and stress (2nd ed.). Cambridge University Press.

Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271

Gutentag, T., Kalokerinos, E. K., Millgram, Y., Garrett, P. M., Sobel, R., & Tamir, M. (2024). Motivational intensity in emotion regulation. Personality and Social Psychology Bulletin. Advance online publication. https://doi.org/10.1177/01461672241273273

Harmon-Jones, E. (2017). On the role of asymmetric frontal cortical activity in approach and withdrawal motivation: An updated review. Psychophysiology, 55(1), e12879. https://doi.org/10.1111/psyp.12879

Harmon-Jones, E., & Gable, P. A. (2018). On the role of asymmetrical frontal cortical activity in approach and withdrawal motivation: An updated review of the evidence. Psychophysiology, 55(1), e12879. https://doi.org/10.1111/psyp.12879

Harmon-Jones, E., Gable, P. A., & Price, T. F. (2013). Does negative affect always narrow and positive affect always broaden the mind? Current Directions in Psychological Science, 22(4), 301–307. https://doi.org/10.1177/0963721413481353

Klaassens, J. H., van Noorden, M. S., Giltay, E. J., van Pelt, J., van Veen, T., & Zitman, F. G. (2005). Effects of intranasal administration of cortisol on approach–avoidance behavior. Psychoneuroendocrinology, 30(7), 665–677. https://doi.org/10.1016/j.psyneuen.2005.02.012

Knutson, B., & Greer, S. M. (2008). Anticipatory affect: Neural correlates and consequences for choice. Philosophical Transactions of the Royal Society B: Biological Sciences, 363(1511), 3771–3786. https://doi.org/10.1098/rstb.2008.0155

Kuper, N., Käckenmester, W., & Wacker, J. (2019). Resting frontal EEG asymmetry and personality traits: A meta-analysis. Psychophysiology, 56(11), e13405. https://doi.org/10.1111/psyp.13405

Kuppens, P., Tuerlinckx, F., Russell, J. A., & Barrett, L. F. (2013). The relation between valence and arousal in subjective experience. Psychological Bulletin, 139(4), 917–940. https://doi.org/10.1037/a0030811

Meyer, A., Hajcak, G., Torpey, D., Kujawa, A., Kim, J., Bufferd, S., Carlson, G. A., & Klein, D. N. (2023). Vulnerability to anxiety differently predicts cortisol reactivity in healthy youth. Journal of Affective Disorders, 335, 153–161. https://doi.org/10.1016/j.jad.2023.04.002

Phaf, R. H., Mohr, S. E., Rotteveel, M., & Wicherts, J. M. (2014). Approach, avoidance, and affect: A meta-analysis of approach–avoidance tendencies in manual reaction-time tasks. Frontiers in Psychology, 5, 378. https://doi.org/10.3389/fpsyg.2014.00378

Reznik, S. J., & Allen, J. J. B. (2017). Frontal asymmetry as a moderator and mediator of emotion. Biological Psychology, 128, 89–97. https://doi.org/10.1016/j.biopsycho.2017.07.001

Reznik, S. J., & Allen, J. J. B. (2018). Frontal asymmetry as a moderator and mediator of emotion. Biological Psychology, 136, 13–21. https://doi.org/10.1016/j.biopsycho.2018.05.010

Rowe, G., Hirsh, J. B., & Anderson, A. K. (2007). Positive affect increases the breadth of attentional selection. Proceedings of the National Academy of Sciences, 104(1), 383–388. https://doi.org/10.1073/pnas.0605198104

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. https://doi.org/10.1037/h0077714

Savitz, J. B., & Ramesar, R. S. (2004). Genetic variants implicated in personality: A review of the evidence and new research. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 124B(1), 1–19. https://doi.org/10.1002/ajmg.b.20017

van Zomeren, M., Leach, C. W., & Spears, R. (2012). Protesters as passionate economists: A dynamic dual pathway model of collective action. Personality and Social Psychology Review, 16(2), 180–199. https://doi.org/10.1177/1088868311430835

Watson, A., Timperio, A., Brown, H., Hesketh, K. D., Macdonald, D., & Craike, M. (2021). Active school breaks and students’ attention: A systematic review with meta-analysis. Brain Sciences, 11(6), 675. https://doi.org/10.3390/brainsci11060675

Yang, S., & Wang, W. (2021). The role of academic resilience, motivational intensity, and their relationship in EFL learners’ academic achievement. Frontiers in Psychology, 12, 823537. https://doi.org/10.3389/fpsyg.2021.823537

External links

• The motivational dimensional model of affect (Research Gate)
• Assessing the Motivational Dimensional Model of emotion–cognition interaction (ScienceDirect)
• Emotion Regulation (National Library of Medicine)