Extramarital Relations

Abstract

Extramarital relations is a form of sexual behavior: sexual or romantic involvement with someone other than an established partner. Cognitive psychology treats infidelity not as a moral failing alone but as the outcome of ordinary decision processes operating under temptation, limited self-control, and uncertainty. Whether a person strays is governed less by momentary desire than by a running balance of relationship satisfaction, accumulated investment, and the perceived quality of alternatives — the core of the investment model of commitment. Committed partners defend that balance through motivated cognition, attending less to and devaluing attractive alternatives, while suspicion of a partner's infidelity behaves as a noisy signal-detection judgment in which hits trade off against false alarms. Three demonstrations trace the stay-or-stray decision, inattention to alternatives, and jealousy as detection.

Keywords: extramarital relations, infidelity, commitment, decision-making, attention

People who stray rarely set out to. They describe a gradual slide — attention drifting, an alternative that started to look better than it should, a line crossed before the decision to cross it felt like a decision at all. That phenomenology is the reason extramarital relations repays a cognitive reading. Infidelity is not a single act of will but the visible end of a long chain of smaller computations: how satisfied a partner feels, how much they have sunk into the relationship, how good the alternatives look, how much attention those alternatives are allowed to command, and whether the self-control to override a tempting impulse is available at the moment it is needed.

Framing infidelity this way locates it inside the general science of decision-making rather than sealing it off as a character flaw. The same machinery that governs any choice under temptation — a valuation that weighs a present reward against a longer-term one, an attentional filter that decides which options are even considered, a self-control system that can be depleted or overridden — is what decides whether an attractive alternative becomes an affair (Fincham & May, 2017). And the influence runs both ways: decisions lead to infidelity, and infidelity, once it happens or is suspected, reshapes the decisions that follow it (Thompson, 1983).

What Extramarital Relations Is

Extramarital relations, in the sense indexed by MeSH and used across the behavioral literature, is sexual or romantic involvement with a person other than one's spouse or established partner — a specific form of sexual behavior, the parent descriptor under which the classification files it. The behavioral literature often prefers the broader terms infidelity or extradyadic involvement to cover unmarried as well as married partnerships, and to include emotional as well as sexual involvement. Its social significance is obvious; its cognitive interest is that it forces a decider to resolve a conflict between a tempting immediate option and a valued long-term commitment, using the same resource-limited machinery that governs ordinary choice (Fincham & May, 2017).

Two features make infidelity a revealing case for cognitive psychology. The first is that it is a conflict decision. An attractive alternative offers an immediate reward; the existing relationship offers an accumulated, longer-term one. Which wins is not settled by desire in the moment but by how the two are valued against each other — and that valuation is exactly what the investment model of commitment formalizes, as a balance of satisfaction, investment size, and the quality of alternatives (Rusbult, 1980). The second is that the mind does not wait passively for temptation to arrive. Commitment actively reshapes perception and attention so that alternatives are seen as less attractive and are granted less processing in the first place, a motivated defense of the relationship rather than a neutral readout of what is available (Johnson & Rusbult, 1989; Miller, 1997).

A third feature connects infidelity to perception and threat detection. Partners do not only decide whether to stray; they also try to detect straying in each other, and that detection is a judgment made from noisy, ambiguous cues. Jealousy, on this reading, is the output of an evolved system for inferring a hard-to-observe state — a partner's involvement elsewhere — from imperfect evidence, with all the characteristic errors of any detector working below certainty (Buss et al., 1992; Shackelford & Buss, 1997).

How Extramarital Relations Intersects Cognition

Infidelity touches cognitive psychology at three points, each a different part of the same drama. First, valuation: how a partner weighs the pull of an alternative against the accumulated value of the current relationship, a decision the investment model casts as a balance of satisfaction, investment, and alternatives. Second, attention: how commitment biases what gets noticed and how appealing it looks, so that relationship maintenance is partly an act of motivated attention rather than willpower alone. Third, perception: how a partner detects infidelity from ambiguous cues, a signal-detection problem in social perception that generates jealousy and its errors. Table 1 lays out the three, and the three interactive demonstrations below take them in turn.

Table 1

Three Cognitive Problems Behind Extramarital Involvement

Note. The three problems are facets of one situation, not stages in a fixed sequence; a partner values, attends, and perceives continuously and in parallel. MeSH files Extramarital Relations (D005114) under Sexual Behavior (F01.145.802.295) and records no narrower descriptors beneath it, so the organizing structure here is cognitive rather than taxonomic.

Valuation: the stay-or-stray decision

The first cognitive problem is how an attractive alternative gets weighed against the relationship a partner already has. The dominant account is the investment model of commitment, which holds that commitment — and with it the resistance to straying — rises with satisfaction and with the size of what has been invested, and falls with the perceived quality of alternatives (Rusbult, 1980). The decisive move is that satisfaction alone does not determine fidelity. A person can be satisfied yet leave if the alternatives look markedly better and little has been invested; a person can be dissatisfied yet stay if alternatives are poor and investment is high. Commitment, not happiness, is what predicts whether the relationship survives temptation.

Applied to infidelity, the model makes a sharp prediction: extradyadic involvement should track the balance of these forces, not any one of them. Longitudinal work bears this out. Among dating couples, those lower in commitment — because of weaker satisfaction, thinner investment, or more tempting alternatives — were reliably more likely to become involved with someone else, and the quality of alternatives carried independent predictive weight beyond how they felt about the partner (Drigotas et al., 1999). The cognition here is a valuation under conflict: a present, salient reward pitted against a diffuse, accumulated one, resolved by a comparison the decider is only partly aware of making. Demo 1 makes the balance concrete: three sliders set satisfaction, investment, and the quality of alternatives, and a commitment meter crosses a threshold into susceptibility when the leave-force overtakes the stay-force — even with satisfaction held fixed.

Attention: resisting temptation as motivated cognition

The second problem is what keeps a committed partner from being pulled toward attractive others in the first place. The answer is not only willpower in the moment but a standing bias in perception and attention. Committed people spontaneously derogate attractive alternatives — rating them as less appealing than uncommitted people do — a motivated devaluation that protects the relationship by making the outside option look worse than it is (Johnson & Rusbult, 1989). The effect reaches earlier than evaluation, into attention itself: people more committed to a partner pay less visual attention to attractive alternatives, disengaging from them faster, and this inattention predicts relationship stability (Miller, 1997). The bias is automatic rather than strategic, showing up in implicit measures that participants cannot easily control (Maner et al., 2009).

This attentional defense is not costless, and it is not guaranteed. It draws on executive control: when the capacity to override a prepotent impulse is experimentally taxed, romantically involved people become more responsive to attractive alternatives, suggesting that staying faithful partly consumes the same self-regulatory resource as any other act of impulse control (Pronk et al., 2011). Individual differences matter too — avoidantly attached people attend more to alternatives and report more infidelity, as if the relationship-protective bias is weaker in them (DeWall et al., 2011) — and the broader framework treats all of this as motivated cognition that regulates attraction in the service of the current bond (Lydon & Karremans, 2015; McNulty et al., 2018). Demo 2 shows the bias directly: raising commitment shrinks the perceived appeal of five fixed alternatives and withdraws the attention each one commands.

Perception: detecting infidelity as signal detection

The third problem runs in the other direction: not resisting temptation but detecting a partner who has given in to it. A partner's involvement elsewhere is a hidden state that must be inferred from ambiguous evidence — a change in routine, a shift in affection, a cue that may mean everything or nothing. This is a signal-detection problem, and jealousy is the output of the system that solves it. On the evolutionary account, jealousy is an adaptation for detecting threats to a valued relationship, and the cues it weighs are patterned: the classic finding is a sex difference in which cue provokes the sharper response, consistent with the different costs sexual versus emotional infidelity historically imposed (Buss et al., 1992). Whatever the explanation for that patterning, the detection framing is what makes jealousy cognitively tractable.

Because the cues are noisy and the states overlap, no suspicion threshold cleanly separates a faithful partner from an unfaithful one. A partner who sets the bar for suspicion low catches more real infidelity but generates corrosive false alarms; one who sets it high avoids false accusations but misses genuine affairs. The errors trade off, exactly as signal-detection theory requires, and the quality of the available cues — how diagnostic they actually are — sets how well any threshold can do (Shackelford & Buss, 1997). A positive detection then feeds into behavior: the vigilance and partner-retention tactics collectively called mate guarding are the output the detector drives, the action side of the same adaptive system. Studies of the cues people treat as signs of a partner's infidelity show that observers do extract real, if imperfect, information from them, which is precisely why both vigilant jealousy and misplaced jealousy are common (Shackelford & Buss, 1997; Selterman et al., 2019). Demo 3 treats suspicion as this detection task: two overlapping cue distributions, a movable suspicion criterion, and hits traded against false alarms as cue diagnosticity varies.

Worked Example

Model the stay-or-stray decision with the investment model to see why satisfaction alone does not predict fidelity. Represent three inputs on a 0–100 scale: relationship satisfaction S, accumulated investment I, and the perceived quality of alternatives A. Let the force pulling toward staying combine satisfaction and investment equally, and the force pulling toward straying be the quality of alternatives:

stay-force = 0.5S + 0.5I,    leave-force = A,    commitment = 50 + (stay-force − leave-force)/2.

Take a partner who is fairly satisfied and well invested but faces only modest alternatives: S = 70, I = 60, A = 30. The stay-force is 0.5 × 70 + 0.5 × 60 = 65, the leave-force is 30, so

commitment = 50 + (65 − 30)/2 = 67.5,

comfortably above the midpoint of 50 at which susceptibility to straying begins. Now hold satisfaction and investment fixed and let a genuinely attractive alternative appear, raising A to 80:

commitment = 50 + (65 − 80)/2 = 42.5,

now below the midpoint, so susceptibility is elevated — without any change in how the partner feels about the relationship. The tipping point is where the leave-force equals the stay-force, i.e. A = 65: below it commitment holds, above it commitment breaks. This is the investment model's central lesson rendered arithmetic: fidelity is governed by a balance, and a sufficiently attractive alternative can tip a satisfied, invested partner into susceptibility while satisfaction stays high (Rusbult, 1980; Drigotas et al., 1999). Demo 1 runs exactly this computation, letting all three inputs vary so the threshold crossing can be watched directly.

Discussion

Reading infidelity as a decision does two useful things. It dissolves the puzzle of the satisfied partner who strays and the dissatisfied one who stays: fidelity is not predicted by satisfaction but by a balance of satisfaction, investment, and alternatives, so both patterns are expected rather than paradoxical (Rusbult, 1980; Drigotas et al., 1999). And it locates extramarital involvement within the general science of self-control and bounded rationality rather than treating it as a sealed-off moral failing: the same motivated attention, impulse control, and valuation-under-conflict that govern dieting, spending, and addiction govern the pull of an attractive alternative (Miller, 1997; Pronk et al., 2011). The practical implication follows directly. Because the relationship-protective bias draws on executive control and on where attention is allowed to settle, conditions that deplete self-regulation or that maximize exposure to attractive, available alternatives should raise risk — which is what the attachment and ecological evidence shows (DeWall et al., 2011; Lydon & Karremans, 2015).

Two cautions keep the account honest. First, the decision framing describes the cognitive machinery, not the moral weight; naming the heuristic that chose is not the same as excusing the choice, and the machinery operates within relationships whose norms and injuries are real. Second, prediction remains humbling. Infidelity is patterned and partly forecastable from personality, attachment, and relationship variables, but even the best contemporary models, trained on a wide battery of predictors, explain a limited share of the variance and locate much of their signal in relationship-level rather than individual-level factors (Buss & Shackelford, 1997; Vowels et al., 2022). The cognition is tractable; the forecast is not yet precise (Fincham & May, 2017).

Current Directions

The most active front is predictive modeling. Applying explainable machine learning to a broad battery of self-report predictors, recent work ranked the variables that actually carry signal about infidelity — relationship satisfaction, desire, and commitment-related measures dominating over demographic ones — while confirming that even the strongest model leaves much of the behavior unexplained (Vowels et al., 2022). A second front revisits why people stray rather than merely who does, mapping the distinct motivations for extradyadic involvement — from dissatisfaction and neglect to situational opportunity and simple desire for variety — and asking how these motivations map onto the valuation and attentional mechanisms above (Selterman et al., 2019). A third develops the attention-and-control account into something interveneable, asking whether the relationship-protective biases in attention and evaluation can be strengthened deliberately, and whether their failure under cognitive load offers a causal handle on temptation (McNulty et al., 2018; Pronk et al., 2011). The question uniting them is whether fidelity is better supported by changing the balance a partner faces or by protecting the automatic cognition that defends the relationship when deliberate control is unavailable.

Common Misconceptions

People only stray when they are unhappy in their relationship.

Satisfaction is only one of three forces. The investment model predicts — and longitudinal data confirm — that a satisfied, happy partner can still become susceptible when attractive alternatives appear and little has been invested, because commitment, not happiness, governs fidelity (Rusbult, 1980; Drigotas et al., 1999).

Resisting an affair is purely a matter of willpower and moral character.

Much of the defense is automatic and cognitive: committed people attend less to attractive alternatives and devalue them without trying. That bias draws on executive control, so when self-regulation is depleted, even committed people become more responsive to alternatives (Miller, 1997; Maner et al., 2009; Pronk et al., 2011).

Jealousy is irrational and simply a sign of insecurity.

Jealousy is better understood as the output of a detection system working from noisy cues. Suspicion trades hits against false alarms exactly as signal-detection theory requires; because genuine and innocent behavior overlap, both vigilant and misplaced jealousy are expected, not evidence that the system is malfunctioning (Buss et al., 1992; Shackelford & Buss, 1997).

Whether someone will cheat is obvious in advance.

Infidelity is patterned and partly predictable from personality, attachment, and relationship variables, but even the best machine-learning models leave much of it unexplained and place most of their predictive weight on relationship-level factors rather than stable individual traits (Buss & Shackelford, 1997; Vowels et al., 2022).

Glossary

Attention.

The selective allocation of limited processing to some cues over others; committed partners direct it away from attractive alternatives, a key part of the cognitive defense of a relationship (Miller, 1997).

Commitment.

The psychological attachment to and intention to maintain a relationship; in the investment model it rises with satisfaction and investment and falls with the quality of alternatives, and it predicts resistance to infidelity (Rusbult, 1980).

Decision-making.

The process of selecting among options by weighing their values; infidelity is treated here as a valuation under conflict between a present alternative and an accumulated relationship.

Derogation of alternatives.

The motivated tendency of committed people to rate attractive alternative partners as less appealing than uncommitted people do, protecting the relationship by devaluing the outside option (Johnson & Rusbult, 1989).

Executive control.

The self-regulatory capacity to override a prepotent impulse; staying faithful partly consumes it, so depleting it raises responsiveness to attractive alternatives (Pronk et al., 2011).

Extradyadic involvement.

Sexual or emotional involvement with someone outside an established couple; the behavioral literature's broader term for infidelity, covering unmarried as well as married partnerships (Selterman et al., 2019).

Extramarital relations.

The MeSH-indexed behavior of sexual or romantic involvement with a person other than one's spouse or established partner; treated here as a decision under temptation.

Infidelity.

A breach of a relationship's agreed exclusivity, sexual or emotional; the end point of a chain of valuation, attention, and self-control processes rather than a single act of will (Fincham & May, 2017).

Investment model.

The account of commitment as rising with satisfaction and investment size and falling with the quality of alternatives; its balance predicts whether a relationship survives temptation (Rusbult, 1980).

Jealousy.

The emotional output of a system for detecting threats to a valued relationship; modeled as a signal-detection judgment from noisy cues, with characteristic hits and false alarms (Buss et al., 1992).

Mate guarding.

Behavior aimed at preventing a partner's infidelity or defection, from vigilance to displays of commitment; the behavioral complement to jealousy's detection function (Shackelford & Buss, 1997).

Quality of alternatives.

The perceived desirability of partners available outside the current relationship; the leave-force of the investment model, and the input that attention and derogation act to suppress (Rusbult, 1980).

Relationship maintenance.

The set of mostly automatic processes — inattention to alternatives, derogation, positive illusions — through which a committed partner sustains a relationship against competing attractions (Maner et al., 2009; McNulty et al., 2018).

Satisfaction level.

How rewarding a relationship feels relative to expectations; one input to commitment, but on its own a poor predictor of fidelity without investment and alternatives (Rusbult, 1980).

Signal detection theory.

The framework for deciding whether a signal is present in noise; here, the model of how a partner infers infidelity from ambiguous cues, trading hits against false alarms (Shackelford & Buss, 1997).

Social perception.

The reading of other people's states and dispositions from their behavior; in infidelity it supplies both the perception of attractive alternatives and the detection of a partner's straying.

Key Researchers

David M. Buss

(University of Texas at Austin, Department of Psychology). Established the evolutionary account of jealousy as an evolved mechanism for detecting threats to a relationship, and documented the sex-patterned cue weighting that frames infidelity detection as an adaptive perception problem. ORCID · Faculty page · Wikipedia

Frank D. Fincham

(Florida State University, Family Institute and Department of Psychology). Synthesized the cognitive and motivational antecedents of infidelity in romantic relationships, situating extradyadic involvement within the broader science of relationship processes. ORCID · Google Scholar · Faculty page

Jon K. Maner

(Florida State University, Department of Psychology). Demonstrated the implicit cognition of relationship maintenance, showing that committed individuals automatically disengage attention from attractive alternatives as a defense that operates below deliberate awareness. ORCID · Google Scholar · Faculty page

James K. McNulty

(Florida State University, Department of Psychology). Showed that attentional and evaluative biases away from attractive alternatives help people avoid infidelity, linking automatic cognition to relationship outcomes over time. Google Scholar · Faculty page

Caryl E. Rusbult

(VU University Amsterdam; previously University of North Carolina at Chapel Hill). Developed the investment model of commitment, which explains why satisfaction, investment, and the quality of alternatives together — not satisfaction alone — predict whether a relationship resists infidelity. Wikipedia · Wikidata

Todd K. Shackelford

(Oakland University, Department of Psychology). Mapped the cues people treat as signs of a partner's infidelity and the mate-guarding responses they provoke, framing partner monitoring as an adaptive detection problem. Google Scholar · Faculty page · Wikipedia

Frequently Asked Questions

How does decision-making lead to infidelity in relationships?

Infidelity is the end point of a valuation under conflict rather than a single lapse. The investment model treats the choice to stay or stray as a balance between a stay-force — relationship satisfaction plus accumulated investment — and a leave-force, the perceived quality of available alternatives. When an attractive alternative raises the leave-force past the stay-force, commitment drops below the threshold at which susceptibility rises, even if satisfaction has not changed. Longitudinal studies confirm that lower commitment, whether from thin investment or tempting alternatives, reliably predicts extradyadic involvement, which is why fidelity is better forecast by the balance of these forces than by happiness alone.

Why do committed people pay less attention to attractive alternatives?

Because commitment recruits an automatic, relationship-protective bias in attention and evaluation. Research shows that more committed people disengage their gaze from attractive alternatives faster and rate those alternatives as less appealing than uncommitted people do — a motivated derogation that makes the outside option look worse than it is. The bias appears on implicit measures that are hard to control deliberately, so it is better described as a standing cognitive defense than as conscious effort. Its function is to keep tempting alternatives from being fully processed in the first place, lowering the leave-force before any decision to stray is reached.

What is the investment model of commitment and how does it predict infidelity?

The investment model holds that commitment to a relationship rises with satisfaction and with the size of what has been invested, and falls with the perceived quality of alternatives. Its central claim is that satisfaction alone does not determine fidelity: a satisfied partner can become susceptible when alternatives are attractive and investment is low, while a dissatisfied partner can stay when alternatives are poor and investment is high. Because commitment reflects this balance, it predicts resistance to infidelity better than satisfaction does, and longitudinal research on dating couples finds that the quality of alternatives carries independent predictive weight for later extradyadic involvement.

Can jealousy be understood as a signal-detection problem?

Yes. A partner's infidelity is a hidden state that must be inferred from ambiguous cues, so suspicion behaves exactly like detecting a signal in noise. Setting the suspicion threshold low catches more genuine infidelity but produces costly false alarms; setting it high avoids false accusations but misses real affairs. The two errors trade off, and because faithful and unfaithful behavior overlap, no threshold eliminates both. Evolutionary accounts add that jealousy is an adaptation for this detection, with cue weighting patterned by the historically different costs of sexual versus emotional infidelity, which is why both vigilant and misplaced jealousy are common.

How does infidelity affect future relationship decision-making?

The influence runs in both directions. Decisions about satisfaction, investment, and attention lead to infidelity, and the outcome — an affair, or merely the suspicion of one — feeds back to reset the balance that governs later decisions. Discovery lowers trust and satisfaction, raising the perceived value of leaving; suspicion recalibrates the detection threshold, often toward hypervigilance that generates further false alarms. Because each outcome updates the inputs to the next valuation, infidelity is less a discrete event than a perturbation of an ongoing decision system, reshaping commitment and monitoring for a long time afterward.

How do perception and attention protect a relationship from temptation?

Perception and attention form the first line of defense, acting before deliberate self-control is needed. Committed partners automatically grant attractive alternatives less attention and perceive them as less appealing, so the pull of an alternative is dampened at the input stage rather than resisted at the decision stage. This perceptual-attentional guard draws on executive control, which means it can fail: when self-regulatory resources are depleted, the bias weakens and even committed people attend more to alternatives. Protecting a relationship is therefore partly a matter of managing exposure and cognitive load, not willpower in the moment alone.

Does staying faithful depend on self-control and executive function?

In part, yes. Experimental work shows that when the capacity to override a prepotent impulse is taxed, romantically involved people become more responsive to attractive alternatives, indicating that fidelity consumes the same self-regulatory resource as other acts of impulse control. Individual differences reinforce the point: people higher in avoidant attachment attend more to alternatives and report more infidelity, as if the relationship-protective bias is weaker in them. This does not reduce fidelity to willpower, since much of the defense is automatic, but it explains why temptation is hardest to resist precisely when self-regulation is stretched.

Can infidelity be predicted from cognitive and relationship variables?

Partly, but the forecast is far from precise. Applying explainable machine learning to a broad battery of self-reported predictors, recent research found that relationship variables — satisfaction, desire, and commitment-related measures — outrank demographic ones in predicting infidelity, yet even the strongest model leaves much of the behavior unexplained. The signal lies more in the state of the relationship than in stable individual traits, consistent with the investment model's emphasis on a changeable balance of forces. Infidelity is thus patterned and partly predictable, but not reliably foreseeable from any fixed profile of a person.

References

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