The Theory of Reasoned Action, developed by Martin Fishbein and Icek Ajzen, is a psychological model that explains how our attitudes and social influences shape our intentions and, in turn, our behavior. In simple terms, it suggests that people do things because they intend to, and those intentions come from what they personally believe about the behavior and what they think others expect of them. It’s a key theory for understanding decision-making in health, relationships, and everyday life.
Key Takeaways
- Definition: The Theory of Reasoned Action (TRA) explains how people’s intentions lead to their behaviors, emphasizing that actions are guided by rational thought rather than impulse. Developed by Martin Fishbein and Icek Ajzen, it focuses on the link between beliefs, intentions, and actions.
- Components: The theory highlights two main factors that shape behavioral intentions — personal attitudes toward the behavior and perceived social pressures, known as subjective norms. Together, these predict whether someone is likely to act.
- Process: TRA proposes that behavior starts with intention, which is formed through evaluating outcomes and considering others’ expectations. If both attitude and social approval align, the person is more likely to follow through.
- Applications: The model is widely used in health campaigns, marketing, and social psychology to predict actions such as exercising, quitting smoking, or purchasing products. It helps design interventions that change beliefs to shift behavior.
- Limitations: TRA assumes people have full control over their actions, which isn’t always true in real-life situations. This led to the development of the Theory of Planned Behavior, which adds perceived behavioral control as a third factor.
Formally, the TRA is a mathematical (expectancy-value) model as well as a psychological theory, closely related to the Theory of Planned Behavior.
Theoretical Origins
The TRA, along with its later version, the Theory of Planned Behavior (TPB), belongs to a group of ideas known as social cognition models.
These models suggest that our actions are guided by what we believe about a behavior, how we think others will view it, and the social situations we’re in.
This way of thinking is closely related to social learning theory, developed by psychologists like Albert Bandura, which emphasizes how our thoughts and social environment work together to shape behavior.
Origins and Early Development
The Theory of Reasoned Action was created by Martin Fishbein and Icek Ajzen.
Their early publications appeared in the late 1960s and early 1970s, notably, Fishbein’s work in 1967 and joint papers by Ajzen and Fishbein around 1970.
These studies laid the foundation for modern research into attitudes, intentions, and decision-making.
Commitment to Goals
A key idea behind TRA is that people are more likely to commit to a goal when they believe it is both worthwhile and achievable.
This idea comes from early motivation research, summarized in the simple formula:
Commitment = Value of the goal × Expectation of success
This idea captures how motivation and belief combine to shape our intentions and behavior.
How the Model Works
The Theory of Reasoned Action has four main terms: Belief, Attitude, Subjective Norms, and Intention (Fishbein and Ajzen, 1975):
1. Behavioral Intention
Your intention is basically your plan or motivation to do something – it’s the best single predictor of whether you’ll actually do it.
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It shows how much effort you’re willing to put in.
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The stronger your intention, the more likely you’ll act on it.
For example, if you’re determined to start exercising three times a week, that intention is a strong sign you probably will.
However, your intention depends on two things: how you feel about exercising (your attitude) and what others think about it (the subjective norm).
In short:
If people have time to think about their choices, their intentions are usually the best clue to what they’ll actually do.
2. Attitude Toward the Behavior
Your attitude toward a behavior is your personal evaluation of it – whether you think it’s good, bad, enjoyable, or worthwhile.
This attitude is shaped by two things:
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Outcome beliefs – what you think will happen if you do it (e.g., “If I quit smoking, I’ll be healthier” or “If I quit smoking, I might gain weight.”)
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Outcome value – how much those outcomes matter to you (e.g., “Being healthier is really important to me.”)
The theory shows that specific attitudes (e.g., “I plan to use birth control pills in the next two years”) are better predictors of behavior than vague, general ones (e.g., “I support birth control”).
3. Subjective Norms (Social Pressure)
Subjective norms refer to the social pressure you feel about a behavior – what you think the important people in your life believe you should do.
This depends on two parts:
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Beliefs about others’ opinions – what you think people close to you (like parents, friends, or partners) expect of you.
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Motivation to comply – how much you care about meeting those expectations.
For instance, someone might not personally like the idea of dieting, but if their friends and family strongly encourage it – and they value those opinions – they may still form the intention to diet.
Putting It All Together
The TRA suggests that your attitude (how you feel about the behavior) and your subjective norm (social expectations) combine to shape your intention, which in turn predicts your behavior.
Research shows:
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Attitudes and subjective norms are strongly linked to intentions (around 0.67 correlation).
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Intentions and actual behavior are moderately linked (around 0.53–0.62 correlation).
This means the theory explains intentions well. It does not guarantee follow-through. Time, opportunity, or confidence can still get in the way.
Sheppard, Hartwick, and Warshaw (1988) ran the definitive early test.
Aim: to establish TRA’s predictive validity across the accumulated literature, including situations the theory was not designed for.
Method: a meta-analysis of 87 studies (156 separate tests) computing average correlations for two paths: attitude and norm to intention, and intention to behavior.
Results: attitude and subjective norm together predicted intention strongly (R ≈ 0.66). Intention predicted behavior more modestly (R ≈ 0.53).
Conclusion: TRA predicts well within, and somewhat beyond, its intended domain. The weak link stays intention-to-behavior. Belief-to-intention predicts far more reliably. As a meta-analysis, this evidence sits high in the hierarchy, though it pools mostly cross-sectional, self-report correlations.
A Worked Example
Consider a student deciding whether to exercise three times a week for the next month. Each belief is rated from -3 (very unlikely or very bad) to +3 (very likely or very good).
Attitude toward the behavior: each belief is multiplied by its evaluation.
- "Will improve my fitness": +3 belief × +3 evaluation = +9
- "Will improve my mood": +2 × +2 = +4
- "Will take up study time": +2 × -2 = -4
Added together, the attitude score totals +9 points.
Subjective norm: each normative belief is multiplied by motivation to comply.
- "My partner thinks I should": +3 belief × +2 motivation = +6
- "My GP thinks I should": +3 × +1 = +3
Added together, the norm score also totals +9 points.
If attitude carries somewhat more weight than the norm for this person, the resulting intention score is strongly positive, raising the probability the person actually exercises. Weakening any single belief lowers the intention, and the predicted behavior, in turn.
Each of these terms is often treated by behavioral scientists as a factor in an equation intended to predict human behavior. As such, they are all related — factors that ultimately contribute to behavior.
Fishbein and Ajzen (1975), who originated the theory of reasoned action, created a diagram to describe the relationship between the main components of their model.
Attitudes, norms, and perceived control each lead to intentions — the readiness to do a behavior. These intentions can then lead, albeit imperfectly, to behaviors.
After Fishbein and Ajzen’s (1975) original behaviors, other scientists have attempted to better group and explain the background factors that lead to the behavioral, normative, and control beliefs that lead to attitude, subjective norms, and perceived behavioral control, respectively.
These environmental factors could include the following:
- Personal factors: traits, locus of control, emotions, and health concerns.
- Demographic factors: Age, gender, race, ethnicity, education, income, and religion.
- Environmental factors: diagnosis, stress, and media exposure.
Health Applications
Peer Influence and Addiction
Neighbors, Foster, and Fossos (2013) outlined several models of addiction. One was built on the Theory of Reasoned Action and its successor, the Theory of Planned Behavior.
The norm they describe is narrower than usual. It concerns only what a person’s valued others think about that person’s own behavior, not behavior in general.
Consider an adolescent who believes people who matter to them would disapprove of smoking. Their intention to smoke should weaken. That should make them less likely to actually smoke.
This narrows TRA’s subjective norms twice over. They concern only people who matter to the individual, and only that person’s own behavior, not behavior in general (Neighbors, Foster, & Fossos, 2013).
This may seem like a small distinction. It matters in practice. The theory does not ask how much someone’s friends approve of smoking in general.
It asks how much they approve of that person’s own smoking in particular.
For instance, parents with moderate or favorable views on marijuana legalization may still disapprove of marijuana use by their own child (Neighbors, Foster, & Fossos, 2013).
Breakfast Consumption
One of the most popular applications of the theory of reasoned action is to assess the probability that a group of people will follow a particular health behavior.
One study attempts to see if the theory of reasoned action would increase breakfast consumption among students in a secondary school in Iran (Hosseini et al., 2015).
To do so, the researchers implemented an informational program that intended to promote breakfast consumption.
Students then filled out a questionnaire before and after the intervention. The first part of this questionnaire concerned knowledge about breakfast consumption, and the second, components of the Theory of Reasoned Action’s factors.
According to the data, subjective norms were the best predictor of breakfast consumption (Hosseini et al., 2015). This included whether someone believed others around them ate breakfast, and whether they thought important others in their life wanted them to.
Fast Food Consumption
Marketers have also used the theory of reasoned action to describe a wide variety of behaviors, such as the consumption of automobiles, banking services, computer software, coupons, detergents, and soft drinks.
Researchers Richard P. Bagozzi, Nancy Wong, Shuzo Abe, and Massimo Bergami tested the theory across cultures, studying fast food consumption in the United States, Italy, China, and Japan.
Subjective norms shaped choices when people ate with friends, but not when they ate alone. This held regardless of whether someone’s culture was individualistic or collectivist.
The researchers found that subjective norms tended to influence decisions when eating with friends, but not alone, regardless of the level of individualism or collectivism in one’s culture.
However, the impact of attitudes, subjective norms, and past behavior on intentions was greater for Americans than for Italians, Chinese, or Japanese people.
In general, there was more explainable variance in behavior for Western than Eastern cultures (Bagozzi, Wong, Abe, & Bergami, 2000)
TRA’s predictive power reaches beyond these single studies. Meta-analyses confirm attitudes and subjective norms also predict intentions for condom use (Albarracín, Johnson, Fishbein, & Muellerleile, 2001) and physical activity (Hagger, Chatzisarantis, & Biddle, 2002). In both areas, intention again predicts actual behavior only moderately.
Technology Acceptance
TRA is the theoretical ancestor of the Technology Acceptance Model (TAM), one of the most widely used frameworks in information-systems research.
Davis (1989) adapted reasoned-action logic to technology use. He replaced TRA’s general belief structure with two specific beliefs: perceived usefulness and perceived ease of use.
Aim: to build and validate belief measures that carry reasoned action into technology adoption.
Method: Davis tested two six-item scales across two studies of 152 users and several application programs. He related them to current and predicted future usage.
Results: both scales were highly reliable (α ≈ 0.98 for usefulness, 0.94 for ease of use). Perceived usefulness correlated more strongly with usage (r ≈ 0.63 current, 0.85 predicted) than did ease of use (r ≈ 0.45 and 0.59).
Conclusion: Usefulness carries the most weight. Both domain-specific beliefs carry the reasoned-action pathway into technology adoption. The evidence is cross-sectional and self-reported, but careful scale validation made TAM one of the most replicated specializations of TRA.
Limitations
The TRA can be seen as a blueprint for a bridge that connects thoughts to actions.
The main critique is that this blueprint only works perfectly if the bridge is short (a simple, fully controllable action) and built in ideal conditions (perfectly rational deliberation).
Real-world complexity strains this blueprint. It lacks components like Perceived Behavioral Control, and supports like implementation planning, needed to reliably support complex human behavior.
1. Limited to Volitional (Controllable) Behavior
The most significant limitation of the original TRA is its restriction to fully volitional behaviors. These are actions entirely under a person’s conscious control.
- Inapplicability to Non-Volitional Actions: Many important behaviors, like addiction or negotiating condom use, are not fully under a person’s control.
- Need for Expansion: Ajzen (1985, 1991) added Perceived Behavioral Control (PBC) to address this gap, creating the Theory of Planned Behavior (TPB).
2. The Intention-Behavior Gap
A consistent critique applied to the TRA (and often to its successor, the TPB) is the significant drop in predictive ability when moving from intention to actual behavior.
While the components of the TRA (attitudes and subjective norms) correlate strongly with intention, their correlation with the actual performance of behavior is noticeably weaker.
- Intention-Behavior Gap: Sheeran’s (2002) review documents this shortfall directly: attitudes and norms predict intention strongly, but intention predicts actual behavior only moderately (r ≈ 0.53–0.62).
- Experimental Evidence: Webb and Sheeran’s (2006) meta-analysis found that experimentally changing intention by a medium-to-large amount produced only a small-to-medium change in behavior.
- Need for "Action" Variables: The gap has spurred research into concepts like Implementation Intentions, concrete "when, where, and how" plans that help bridge intention to action.
3. Oversimplification of Human Decision-Making (The Rational Agent)
The TRA, as a social cognition model, assumes that individuals are generally rational decision makers who deliberately weigh the perceived implications of their actions before making a decision.
This strong assumption about human rationality has been subject to criticism in psychology generally, as well as specific limitations within the model:
- Neglect of Affective Variables: The model focuses on cognitive factors like beliefs and norms, often failing to capture emotional (affective) influences on behavior.
- Bounded Rationality: People try to weigh costs and benefits rationally, but limited memory, time, and attention prevent them from being fully rational decision-makers.
- Automatic, Non-Conscious Processes: Many behaviors happen quickly and unintentionally, outside conscious awareness. By focusing only on reasoned action, TRA overlooks this automatic side of behavior.
4. Methodological and Structural Issues
The way the TRA defines and measures its components also presents limitations:
- Lack of Causal Specificity: Support for the intention-behavior link relies heavily on cross-sectional studies, which cannot separate cause from effect over time.
- Neglect of Reciprocal Relationships: The TRA assumes attitudes shape behavior, but behavior can also reshape attitudes afterward. This reciprocal path is not part of the model.
- Issue of Specificity: A more specific attitude predicts a behavior better, but measuring subjective norms is trickier. It depends on whether researchers assess individually salient beliefs or generalized modal beliefs.
Contemporary Research
Since 2015 the reasoned-action tradition has kept being tested. The picture is now more precise, mostly through meta-analyses of the RAA (the model’s modern, more granular successor).
McEachan et al. (2016) ran the highest-value test.
Aim: to compare the RAA’s paired subcomponents (e.g., experiential vs instrumental attitude) as predictors of intention and behavior.
Method: a meta-analysis of correlational tests of every subcomponent, with regressions predicting intention and behavior.
Results: capacity (a self-efficacy-like facet) and experiential (affective) attitude showed the largest correlations with intention. Descriptive norms, not the classic subjective norm, best predicted behavior.
Conclusion: the RAA’s constructs predict health behavior, but their weights are markedly unequal. The affective side of attitude and self-efficacy-like control do most of the work.
A second meta-analysis pushes further. Hagger, Polet, and Lintunen (2018) added past behavior to the model using meta-analytic structural equation modeling. Including past behavior weakened the model’s paths, especially the direct intention-to-behavior link, suggesting habitual, non-conscious processes play a real part in health behavior.
Theory of Reasoned Action vs. Theory of Planned Behavior
The theory of reasoned action has some limitations. One of these is a significant risk of confounding between attitudes and norms.
This happens because attitudes can often be reframed as norms and norms as attitudes.
For example, someone who has the attitude that kale is good for them may simply be reflecting a subjective norm of a group of influential friends, family, doctors, and social media influencers who believe that kale is healthy.
The theory of planned behavior attempts to resolve these limitations through the idea of perceived behavior control (LaCaille, 2020).
The Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB) are closely related social cognition models used to explain and predict deliberate human behavior.
The TRA served as the foundational model, and the TPB represents its expansion and improvement to address specific limitations of the original theory.
The primary difference between the TRA and the TPB lies in the inclusion of a third, critical conceptual component in the TPB: Perceived Behavioral Control (PBC).
Here is a detailed comparison of the differences:
1. Scope of Behavior Explained
The most substantial difference is the type of behavior each theory is designed to explain:
| Feature | Theory of Reasoned Action (TRA) | Theory of Planned Behavior (TPB) |
|---|---|---|
| Behaviors Covered | Volitional Behavior, meaning actions that are entirely under the person’s control. | Non-Volitional Behavior and deliberate behaviors in general. |
| Limitation/Improvement | The TRA was limited because much behavior, such as addictive behaviors (e.g., smoking) or complex social negotiations (e.g., negotiating condom use), is not completely volitional. | The TPB was developed to improve the model’s ability to address non-volitional behavior. |
2. The Core Components (Determinants of Intention)
Both models assert that intention is the best predictor of deliberate behavior, and this intention is determined by predictive factors.
| TRA Component | TPB Component | Difference Explained |
|---|---|---|
| Attitude toward the Specific Behavior | Attitude toward the Specific Behavior | Both models retain this element, which is the person’s specific attitude toward the behavior, not their general attitude. |
| Subjective Norms | Subjective Norms | Both retain this element, which accounts for perceived social pressure—beliefs about how important others view the behavior. |
| (Not Included) | Perceived Behavioral Control (PBC) | The TPB includes PBC, which is defined as a person’s belief that they have control over their own behavior in certain situations, even when facing barriers. |
3. Role of Perceived Behavioral Control (PBC)
The introduction of Perceived Behavioral Control (PBC) is the defining feature of the TPB.
- Definition: PBC is how easy or difficult people believe a behavior will be. It resembles self-efficacy, the belief you can master a situation and produce a good outcome.
- Influence on Intention and Behavior: PBC directly influences intention, and can also predict behavior directly when perceptions of control are accurate.
- Empirical Success: Adding PBC made the TPB more successful than the TRA at predicting behavioral change; PBC correlates with intention at around 0.71.
4. Predictive Power
While both models show strong predictive power for intentions, the TPB offers an incremental improvement in predictive success due to the inclusion of PBC:
- Intention Prediction: Attitudes and social norms correlate highly with intention under the TRA (about 0.67); the TPB’s added variables explain 40-50% of intention’s variance.
- Behavior Prediction: TRA’s intention-behavior correlation runs 0.53-0.62; TPB variables explain 19-38% of behavior’s variance. Both models predict intention far better than behavior itself, a gap that motivates concepts like Implementation Intentions.
References
Bagozzi, R. P., Wong, N., Abe, S., & Bergami, M. (2000). Cultural and situational contingencies and the theory of reasoned action: Application to fast food restaurant consumption. Journal of consumer psychology, 9 (2), 97-106.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
Fishbein, M. (1979). A theory of reasoned action: some applications and implications.
Hale, J. L., Householder, B. J., & Greene, K. L. (2002). The theory of reasoned action. The persuasion handbook: Developments in theory and practice, 14 (2002), 259-286.
Hosseini, Z., Gharghani, Z. G., Mansoori, A., Aghamolaei, T., & Nasrabadi, M. M. (2015). Application of the theory of reasoned action to promoting breakfast consumption. Medical journal of the Islamic Republic of Iran, 29, 289.
LaCaille, L. (2020). Theory of reasoned action. Encyclopedia of behavioral medicine, 2231-2234.
Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and social psychology Bulletin, 18 (1), 3-9.
Montano, D. E., & Kasprzyk, D. (2015). Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. Health behavior: Theory, research and practice, 70 (4), 231.
Neighbors, C., Foster, D. W., & Fossos, N. (2013). Peer influences on addiction. Principles of addiction: Comprehensive addictive behaviours and disorders, 1, 323-331.
Rossi, A. N., & Armstrong, J. B. (1999). Theory of reasoned action vs. theory of planned behavior: Testing the suitability and sufficiency of a popular behavior model using hunting intentions. Human Dimensions of Wildlife, 4 (3), 40-56.
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 (3), 325-343.
Vallerand, R. J., Deshaies, P., Cuerrier, J. P., Pelletier, L. G., & Mongeau, C. (1992). Ajzen and Fishbein’s theory of reasoned action as applied to moral behavior: A confirmatory analysis. Journal of personality and social psychology, 62 (1), 98.
