Why Do Some Women Seem to Have a Thing

Evidence Note: This article integrates peer reviewed findings from developmental neuroscience, neuroendocrinology, reproductive immunology, virology, stress physiology, and public health. Every claim is tied to a cited primary source, and every source is listed in full with its digital object identifier at the end of the article. The Bio-Relational Science framework presented here is an original educational synthesis that translates this body of research into language the general reader can act on.

Abstract

The appearance that some women prefer men who mistreat them is a misreading of attachment-driven behavior. This article argues that what looks like attraction to harmful partners is the predictable output of intermittent reinforcement, trauma bonding, attachment learning, and neurobiological conditioning. Dutton and Painter (1993) tested traumatic bonding theory directly and found that intermittency of abuse and power imbalance predicted the strength of emotional attachment to an abusive partner, with attachment intensifying rather than weakening after separation. The mechanism is now identifiable at the level of single neurons. Fiorillo et al. (2003) showed that dopamine neurons respond most strongly under maximal reward uncertainty rather than under reliable reward, and Anselme et al. (2013) and Robinson et al. (2014) showed that reward uncertainty persistently elevates incentive salience, meaning the unpredictable cue becomes more compelling than the certain one. Social attachment shares substrate with addiction, including dopaminergic reward circuitry and the mu-opioid system required for adult pair bonding (Insel, 2003; Burkett & Young, 2012; Burkett et al., 2011; Herman & Panksepp, 1978). Early maltreatment alters brain structure, function, and connectivity and dysregulates the stress axis, which changes what a nervous system later treats as normal (Teicher et al., 2016; Heim & Nemeroff, 2001; Schore, 2001; Lyons-Ruth et al., 2016). Attachment insecurity is associated with intimate partner violence involvement and with revictimization risk (Velotti et al., 2018; Kuijpers et al., 2011; Widom et al., 2008). Women who return to abusive partners report emotional attachment and hope for change as primary reasons, not a preference for harm (Griffing et al., 2002), and investment model analysis shows that staying tracks investment and constrained alternatives rather than satisfaction (Rusbult & Martz, 1995). The article concludes that this pattern reflects learned relational expectation rather than brokenness or conscious preference, that familiarity is a documented driver of preference independent of quality (Zajonc, 1968), and that what was learned can be retrained (Maier & Seligman, 2016; Turner, 2026).

Keywords: trauma bonding, intermittent reinforcement, reward uncertainty, attachment, attachment insecurity, revictimization, toxic relationships, women’s wellness, relational learning, bio-relational science

Introduction

“Why do some women seem to have a thing for men who treat them badly?”

The question contains its own error. It assumes that a woman who stays in a harmful relationship is expressing a preference, and once that assumption is in place, every explanation that follows is about her character. She likes drama. She has low self-esteem. She is choosing this.

The more accurate explanation is that attachment systems can be trained to misread instability as emotional significance, and that the training follows well-documented rules. What looks like preference is conditioning, and conditioning is not a personality trait.

From a bio-relational perspective, people do not select partners with their minds alone. They respond with nervous systems that learn from repetition, reward, and threat. When affection arrives unpredictably, the system becomes more alert, more invested, and more hopeful each time affection reappears after withdrawal. That is not a flaw in her judgment. It is how reward learning works, and it has been measured in single dopamine neurons (Fiorillo et al., 2003).

The evidence supporting this reframe is stronger than most people realize. Dutton and Painter (1993) tested traumatic bonding theory in women leaving abusive relationships and found that the intermittency of the abuse, not its severity alone, predicted attachment strength. The same literature that documents why people stay also documents what they say about it, and what they say is not that they prefer mistreatment (Griffing et al., 2002).

This article sets out the mechanism, names the biology, and states the consequence. The behavior is real. The interpretation is usually wrong. And the goal is not to shame women for these patterns but to explain why they happen and how they change (Turner, 2026).

Conceptual Framework

Four constructs organize the analysis.

Traumatic bonding is the formation of strong emotional attachment through cycles of intermittent abuse and intermittent relief under conditions of power imbalance. Dutton and Painter (1993) operationalized and tested it, finding that intermittency and power differential predicted attachment intensity, and that attachment often rose in the weeks after leaving.

Reward uncertainty is the mechanism that makes intermittency more compelling than consistency. Fiorillo et al. (2003) found that dopamine neurons show maximal sustained activation when reward probability is most uncertain, and Anselme et al. (2013) and Robinson et al. (2014) found that uncertainty persistently increases the incentive salience of the cue that predicts reward.

Attachment and addiction overlap in substrate. Insel (2003) asked whether social attachment is an addictive disorder, Burkett and Young (2012) catalogued the behavioral, anatomical, and pharmacological parallels, and Burkett et al. (2011) showed that mu-opioid receptor activation in the dorsal striatum is necessary for adult social attachment to form.

Relational learning is the durable shaping of expectation by early experience. Teicher et al. (2016) documented the effects of childhood maltreatment on brain structure, function, and connectivity, and Heim and Nemeroff (2001) documented the stress-axis consequences that follow.

The argument is that these four constructs jointly explain a pattern usually explained by character, and that a mechanical explanation is more useful because mechanisms can be interrupted.

Discussion

The premise is wrong, and the correction is mechanical

Start with what the women involved actually report.

Griffing et al. (2002) asked domestic violence survivors why they returned to abusive relationships. The most frequently cited reasons were emotional attachment to the partner and the belief that the partner would change. Preference for mistreatment did not appear, because it is not what is happening.

Rusbult and Martz (1995) analyzed the same question through the investment model and found that staying in an abusive relationship was predicted by high investment, poor alternatives, and economic dependence rather than by satisfaction. Satisfaction was low. Commitment was high. Those two facts coexist when the structural inputs to commitment are present, which is a finding about circumstances rather than about taste.

Dutton and Painter (1993) supplied the mechanism. Among women who had left abusive partners, the intermittency of the abuse predicted attachment strength, and the strength of attachment frequently increased in the period after separation rather than decreasing. Attachment was being produced by the pattern of the relationship, not by its quality.

So the honest correction is this. She is not drawn to bad treatment. She is attached to a person, and the attachment was built by a schedule.

Intermittent reward and the illusion of chemistry

One reason unstable relationships feel compelling is that intermittent reward creates intense emotional spikes. A small gesture of kindness after a period of coldness can feel euphoric because it temporarily resolves distress. The nervous system registers that relief as significant even when the relationship as a whole remains harmful.

This is routinely mistaken for chemistry. In reality, much of it is distress relief, and the two are difficult to distinguish from inside because both produce arousal, focus, and preoccupation.

The physiology explains the confusion. Berridge and Robinson (1998) separated the “wanting” component of reward, driven by dopaminergic incentive salience, from the “liking” component. The two can come apart. A cue can become intensely wanted without the outcome becoming more pleasurable. Applied to relationships, this means a woman can experience escalating pursuit of a partner who is not making her happy, and the escalation is not a sign that she secretly enjoys the treatment. It is the wanting system operating on an unreliable schedule.

Sbarra and Hazan (2008) add the regulatory side, describing how adult attachment involves coregulation of physiological state and how its disruption produces dysregulation rather than simple sadness. When a partner is the source of both dysregulation and its relief, the loop closes on itself.

The more inconsistent the relationship, the more powerful the relief when the partner becomes warm again. That relief creates a cycle of hope, disappointment, craving, and temporary reward. She may stay not because the relationship is nourishing, but because her nervous system has been trained to pursue the next resolution.

Uncertainty is the active ingredient

This is the finding that turns the argument from plausible to demonstrated, and it comes from single-neuron recording rather than from self-report.

Fiorillo et al. (2003) recorded dopamine neurons while varying the probability that a cue would be followed by reward. The phasic response tracked reward prediction error as expected, consistent with Schultz et al. (1997). But a second signal appeared: sustained activation that grew as probability approached fifty percent, meaning the neurons responded most strongly under maximal uncertainty, not under maximal reward.

Anselme et al. (2013) tested the behavioral consequence and found that reward uncertainty enhanced incentive salience attribution, measured as sign-tracking toward the predictive cue. Robinson et al. (2014) showed the effect persisted even after uncertainty was removed, meaning early uncertainty left a durable elevation in how compelling the cue remained.

Read together, these results say something specific about hot-and-cold relationships. Uncertainty is not a tolerated cost of the relationship. Uncertainty is the thing amplifying the pull. A partner who is reliably affectionate generates a smaller dopaminergic signal than one who might be. That is not a moral fact about anyone involved. It is the operating characteristic of the system that assigns motivational weight.

This is why the advice to simply recognize that he is inconsistent so often fails. Recognition operates on the evaluative system. The inconsistency is operating on the motivational one.

The addiction comparison is often used loosely. The literature supports it specifically.

Insel (2003) posed the question directly in Physiology and Behavior and concluded that social attachment recruits the same reward pathways implicated in substance dependence, including dopaminergic projections to the nucleus accumbens. Burkett and Young (2012) then catalogued the behavioral, anatomical, and pharmacological parallels between social attachment, love, and addiction across a comprehensive review, including tolerance, withdrawal, craving, and relapse analogues.

The opioid system is central. Herman and Panksepp (1978) found that morphine alleviated separation distress while naloxone intensified it, establishing the opioid basis of attachment-related distress. Burkett et al. (2011) then showed that mu-opioid receptor activation in the dorsal striatum is necessary for adult social attachment to form in monogamous prairie voles. Blocking those receptors prevented partner preference formation. Machin and Dunbar (2011) reviewed the broader brain opioid theory of social attachment.

Fisher et al. (2010) completed the picture on the human side, finding that romantic rejection activated regions associated with reward, addiction, craving, and emotion regulation.

So the withdrawal a woman feels when an unreliable partner pulls away is not metaphorical. It is running on the opioid and dopamine systems that mediate attachment and dependence, and that is why willpower performs poorly against it.

Trauma bonding and self-blame

Trauma bonding explains why people remain attached to partners who mistreat them. In a trauma bond, affection, apology, fear, and power imbalance combine to produce intense attachment that is difficult to exit. The bond is strengthened not by safety but by repeated cycles of harm and relief (Dutton & Painter, 1993).

Self-blame develops inside this pattern with near-perfect reliability. A woman may conclude that if she were more attractive, calmer, more patient, or more compliant, he would treat her better. That interpretation gives the illusion of control, and it obscures the real problem, which is that the relationship is structured to keep her working for approval. The issue is not her inadequacy. The issue is that the relationship has taught her to earn what should have been freely given.

Maier and Seligman (2016) provide the mechanism behind the psychological collapse that accompanies this. Revisiting fifty years of learned helplessness research with neuroscience, they reframed the core finding: the animal does not learn helplessness, it fails to learn control, and passivity is the default state that persists when control is not detected. Prolonged uncontrollability produces the passivity rather than any defect in the organism.

Applied here, a woman in an unpredictable relationship is not failing to act because she is weak. She is in an environment engineered, whether deliberately or not, to prevent the detection of control. Her behavior is what the research predicts from anyone in that environment.

Why knowing does not equal leaving

The most common form of self-blame is the observation that she saw the warning signs and stayed anyway. This is treated as proof of irrationality. It is better understood as proof that insight and motivation run on different systems.

Berridge and Robinson (1998) established that incentive salience operates independently of conscious evaluation of outcome quality. Fiorillo et al. (2003), Anselme et al. (2013), and Robinson et al. (2014) established that uncertainty amplifies it. None of those processes consult the person’s stated assessment of the relationship.

Spielmann et al. (2013) documented an additional force across six studies. Fear of being single predicted settling for less responsive and less compatible partners, in both experimental and longitudinal designs. Fear of being single does not just lower standards at the start. It reinterprets evidence already in hand.

Le and Agnew (2003) confirmed meta-analytically that commitment is driven by satisfaction, investment size, and quality of alternatives. Two of those three can hold commitment in place while satisfaction collapses. Rusbult and Martz (1995) demonstrated exactly that pattern in abusive relationships.

So the mind may know better while the body remains engaged with the cycle. That is not a contradiction in her. It is an accurate description of how the two systems are built.

Why bad treatment can feel familiar

Familiarity is one of the strongest and least examined drivers of preference.

Zajonc (1968) demonstrated the mere exposure effect, showing that repeated exposure to a stimulus increases liking for it independent of any positive outcome associated with it. Preference follows exposure. It does not require that the exposure be good.

This is why early relational environments matter so much. If a woman’s early environment included emotional inconsistency, conditional affection, criticism, or neglect, those patterns register later as normal rather than as alarming. Schore (2001) documented how secure attachment relationships shape right brain development, affect regulation, and infant mental health, and in a companion paper the same year documented how early relational trauma shapes those systems differently.

Porges (2007) supplies the sharpest concept here. The polyvagal perspective describes how the autonomic nervous system continuously evaluates environmental cues for safety below the level of conscious awareness. What the system treats as a safety cue is shaped by history. A calm, consistent partner does not automatically read as safe to a system calibrated on inconsistency.

This is why peaceful relationships can feel boring or even suspicious. If chaos has been normalized, calm may feel unfamiliar enough to be misread as absence of chemistry, while a hot-and-cold partner feels magnetically compelling because the emotional pattern is recognizable.

That recognition is not destiny. It is learning. And what was learned can be unlearned.

Early maltreatment changes the hardware

Her original article said the brain can become habituated to instability. The imaging literature says it more strongly than that.

Teicher et al. (2016) reviewed the effects of childhood maltreatment on brain structure, function, and connectivity in Nature Reviews Neuroscience and documented alterations across threat detection, reward processing, emotion regulation, and self-referential networks. Lyons-Ruth et al. (2016) found that disorganized attachment in infancy predicted greater amygdala volume in adulthood, a prospective link across decades.

Heim and Nemeroff (2001) documented the endocrine consequence, reviewing preclinical and clinical evidence that childhood trauma alters the hypothalamic-pituitary-adrenal axis and increases vulnerability to mood and anxiety disorders in adulthood.

Widom et al. (2008) traced the behavioral outcome. In a prospective study following documented cases of childhood victimization into adulthood, childhood victimization predicted lifetime revictimization across multiple forms. Widom et al. (2014) confirmed the prospective link to intimate partner violence victimization specifically.

These findings support her framework rather than complicating it. A nervous system calibrated by early adversity is not making bad choices from a neutral starting position. It is operating with altered threat detection, altered reward processing, and an altered stress axis. That is a physiological condition, and it is exactly why willpower-based advice underperforms.

Attachment insecurity raises risk, and it is not a character flaw

Attachment theory adds explanatory power without adding blame.

Velotti et al. (2018) conducted a systematic review of intimate partner violence and attachment and found consistent associations between attachment insecurity, both anxious and avoidant, and involvement in intimate partner violence as victim or perpetrator. Kuijpers et al. (2011) found that attachment, anger, and related regulatory factors predicted revictimization risk in intimate partner violence, and in a companion analysis examined victims’ own influence on revictimization patterns.

Mikulincer and Shaver (2019) describe the mechanism generally: attachment orientations shape emotion regulation strategies, with anxious orientation producing hyperactivation of attachment behavior under threat. Simpson and Rholes (2017) reviewed adult attachment and stress in romantic relationships and reached compatible conclusions.

Hyperactivation is the key term. Under threat of loss, an anxiously attached person’s attachment system increases proximity seeking rather than decreasing it. A partner who periodically withdraws is therefore generating, not reducing, attachment behavior. The withdrawal functions as an activation cue.

This means the widely repeated advice that she should feel less attached when he treats her badly is asking her attachment system to do the opposite of what it is built to do under those precise conditions.

The role of peace

The most important goal in relational healing is helping the nervous system recognize peace as desirable. A healthy bond does not require endless proving, emotional whiplash, or chronic uncertainty. It provides consistency, accountability, and safety.

The research supports treating this as a trainable physiological outcome rather than as an attitude adjustment. Coan and Sbarra (2015) describe social baseline theory, in which proximity to reliable social partners reduces the metabolic and neural resources the brain devotes to threat monitoring. Coan et al. (2006) demonstrated it directly: holding a partner’s hand under threat attenuated neural threat response, with the effect strongest in higher-quality relationships. Reliable presence lowers baseline vigilance.

Sbarra and Hazan (2008) describe attachment as coregulation of physiological state, which reframes what stability provides. A steady partner is not merely pleasant company. He is an external regulator, and the regulation has measurable outputs in cortisol, sleep, and cardiovascular function.

So peace initially feels less dramatic than chaos, and that is expected. The dopaminergic signal is smaller under certainty (Fiorillo et al., 2003). But the regulatory benefit is larger, and it accumulates. When the body learns that stability is not emptiness, attraction patterns begin to shift.

What retraining actually requires

The practical program follows from the mechanism rather than from motivation.

It requires exposure to consistency long enough to recalibrate. Zajonc (1968) showed that preference follows exposure, which cuts both ways: if familiarity built the current pattern, familiarity can build a different one. Coan and Sbarra (2015) indicate what to expect during the adjustment, as threat monitoring does not drop the moment circumstances improve.

It requires interrupting uncertainty rather than tolerating it. Because uncertainty is the amplifier, reducing contact with the unpredictable cue matters more than deciding to care less about it (Anselme et al., 2013; Robinson et al., 2014).

It requires restoring detected control. Maier and Seligman (2016) identified the failure to detect control as the operative variable, which means small, reliably effective actions are not trivial. They address the actual mechanism.

It requires expecting withdrawal and planning for it. Attachment disruption runs on opioid and dopaminergic systems, so the acute period after leaving resembles withdrawal, including the counterintuitive finding that attachment can intensify immediately after separation (Dutton & Painter, 1993; Fisher et al., 2010; Herman & Panksepp, 1978). Knowing that the spike is expected and time limited prevents reading it as evidence that leaving was wrong.

And it requires structural support rather than insight alone, given that investment, constrained alternatives, and economic dependence are documented drivers of staying (Rusbult & Martz, 1995; Le & Agnew, 2003).

Relation to Bio-Relational Science

Bio-Relational Science holds that relational outcomes are produced by biology, attachment history, and behavior acting together. This question is the framework’s clearest demonstration, because the popular explanation fails on all three counts at once.

The popular explanation locates the cause in a woman’s character. The framework locates it in a schedule of reinforcement operating on a nervous system with a history. Those are different claims with different predictions and different remedies. If the cause is character, the remedy is self-criticism. If the cause is conditioning, the remedy is changing the conditions.

Every layer of the framework is supported. Biology: reward uncertainty amplifies incentive salience, and attachment shares substrate with dependence (Fiorillo et al., 2003; Burkett & Young, 2012; Burkett et al., 2011). History: early maltreatment alters threat detection, reward processing, and the stress axis, and predicts revictimization prospectively (Teicher et al., 2016; Heim & Nemeroff, 2001; Widom et al., 2008). Behavior: intermittency predicts attachment strength, and investment and alternatives predict staying (Dutton & Painter, 1993; Rusbult & Martz, 1995).

The framework’s commitment in this case is to refuse the character explanation while still describing the pattern accurately. A woman is not choosing harm, and she is also not helpless. She is in a learned state with identifiable inputs, and the inputs can be changed.

Turner (2026) develops this in And That’s Why Men Like Virgins, tracing how silence about the biology of bonding leaves women interpreting a conditioning process as a personal failing, and how that misinterpretation keeps them inside it. The present analysis extends that argument with the reward-uncertainty, attachment-addiction, maltreatment, and revictimization literatures.

Implications for Women’s Wellness and Bio-Relational Education

Women’s wellness education should treat this pattern as a relational learning issue rather than a character flaw. Women who repeatedly form attachments to harmful partners are not careless or foolish. They are operating with nervous systems trained by experience to treat intensity and uncertainty as signals of significance.

Five teaching priorities follow.

Teach the mechanism, not the moral. Intermittency amplifies attachment, and that has been shown in the abuse literature and at the level of dopamine neurons (Dutton & Painter, 1993; Fiorillo et al., 2003). A woman who understands that uncertainty is the amplifier has a target. A woman told she has poor judgment has nothing.

Teach that insight does not produce release. Incentive salience does not consult conscious evaluation, which is why identifying warning signs and still staying is expected rather than shameful (Berridge & Robinson, 1998; Spielmann et al., 2013).

Teach withdrawal as a predictable phase. Attachment disruption engages opioid and dopaminergic systems, and attachment can spike after separation rather than easing (Herman & Panksepp, 1978; Fisher et al., 2010; Dutton & Painter, 1993). Women who are warned about this are less likely to read the spike as proof they made a mistake.

Teach that calm requires recalibration time. Threat monitoring does not reset on decision. Reliable presence lowers it gradually, and the initial flatness of a steady relationship is a physiological adjustment rather than an absence of compatibility (Coan & Sbarra, 2015; Porges, 2007).

Teach structural assessment alongside emotional insight. Investment, alternatives, and economic dependence predict staying, which means practical resources belong in the intervention rather than only in the aftermath (Rusbult & Martz, 1995).

For educators and clinicians, the implication is that “why do you keep choosing him?” is the wrong question. A better one is “what has your nervous system learned to recognize as love?” That shift moves the work from blame to mechanism, and mechanisms can be changed.

Conclusion

Some women appear to have a thing for men who treat them badly because nervous systems can be conditioned to mistake instability for connection, and the conditioning follows rules that have been measured rather than guessed.

Intermittency predicts attachment strength in women leaving abusive relationships (Dutton & Painter, 1993). Reward uncertainty maximizes dopaminergic signaling and persistently elevates the pull of the cue that predicts reward (Fiorillo et al., 2003; Anselme et al., 2013; Robinson et al., 2014). Attachment shares reward and opioid machinery with dependence, which is why separation produces withdrawal rather than relief (Insel, 2003; Burkett & Young, 2012; Burkett et al., 2011). Early adversity alters the systems that decide what counts as safe (Teicher et al., 2016; Schore, 2001; Porges, 2007). And what women themselves report is emotional attachment and hope, not a taste for mistreatment (Griffing et al., 2002).

None of that means a woman is broken, defective, or doomed. It means her bonding system has been trained by experience, and training is reversible in principle because the inputs are identifiable. Failure to detect control is the operative deficit, not weakness, and detected control can be rebuilt (Maier & Seligman, 2016).

A bio-relational approach restores the proper frame. The goal is not to find the next emotional high. The goal is to build relationships that feel like safety, reciprocity, and peace, and to give the body long enough with steadiness to recognize it as the real thing.

References

Anselme, P., Robinson, M. J. F., & Berridge, K. C. (2013). Reward uncertainty enhances incentive salience attribution as sign-tracking. Behavioural Brain Research, 238, 53-61. https://doi.org/10.1016/j.bbr.2012.10.006

Berridge, K. C., & Robinson, T. E. (1998). What is the role of dopamine in reward: Hedonic impact, reward learning, or incentive salience? Brain Research Reviews, 28(3), 309-369. https://doi.org/10.1016/S0165-0173(98)00019-8

Burkett, J. P., & Young, L. J. (2012). The behavioral, anatomical and pharmacological parallels between social attachment, love and addiction. Psychopharmacology, 224(1), 1-26. https://doi.org/10.1007/s00213-012-2794-x

Burkett, J. P., Spiegel, L. L., Inoue, K., Murphy, A. Z., & Young, L. J. (2011). Activation of mu-opioid receptors in the dorsal striatum is necessary for adult social attachment in monogamous prairie voles. Neuropsychopharmacology, 36(11), 2200-2210. https://doi.org/10.1038/npp.2011.117

Coan, J. A., & Sbarra, D. A. (2015). Social baseline theory: The social regulation of risk and effort. Current Opinion in Psychology, 1, 87-91. https://doi.org/10.1016/j.copsyc.2014.12.021

Coan, J. A., Schaefer, H. S., & Davidson, R. J. (2006). Lending a hand: Social regulation of the neural response to threat. Psychological Science, 17(12), 1032-1039. https://doi.org/10.1111/j.1467-9280.2006.01832.x

Dutton, D. G., & Painter, S. (1993). Emotional attachments in abusive relationships: A test of traumatic bonding theory. Violence and Victims, 8(2), 105-120. https://doi.org/10.1891/0886-6708.8.2.105

Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003). Discrete coding of reward probability and uncertainty by dopamine neurons. Science, 299(5614), 1898-1902. https://doi.org/10.1126/science.1077349

Fisher, H. E., Brown, L. L., Aron, A., Strong, G., & Mashek, D. (2010). Reward, addiction, and emotion regulation systems associated with rejection in love. Journal of Neurophysiology, 104(1), 51-60. https://doi.org/10.1152/jn.00784.2009

Griffing, S., Ragin, D. F., Sage, R. E., Madry, L., Bingham, L. E., & Primm, B. J. (2002). Domestic violence survivors’ self-identified reasons for returning to abusive relationships. Journal of Interpersonal Violence, 17(3), 306-319. https://doi.org/10.1177/0886260502017003005

Heim, C., & Nemeroff, C. B. (2001). The role of childhood trauma in the neurobiology of mood and anxiety disorders: Preclinical and clinical studies. Biological Psychiatry, 49(12), 1023-1039. https://doi.org/10.1016/S0006-3223(01)01157-X

Herman, B. H., & Panksepp, J. (1978). Effects of morphine and naloxone on separation distress and approach attachment: Evidence for opiate mediation of social affect. Pharmacology Biochemistry and Behavior, 9(2), 213-220. https://doi.org/10.1016/0091-3057(78)90167-3

Insel, T. R. (2003). Is social attachment an addictive disorder? Physiology and Behavior, 79(3), 351-357. https://doi.org/10.1016/S0031-9384(03)00148-3

Kuijpers, K. F., van der Knaap, L. M., & Winkel, F. W. (2011). Risk of revictimization of intimate partner violence: The role of attachment, anger and violent behavior of the victim. Journal of Family Violence, 27(1), 33-44. https://doi.org/10.1007/s10896-011-9399-8

Le, B., & Agnew, C. R. (2003). Commitment and its theorized determinants: A meta-analysis of the investment model. Personal Relationships, 10(1), 37-57. https://doi.org/10.1111/1475-6811.00035

Lyons-Ruth, K., Pechtel, P., Yoon, S. A., Anderson, C. M., & Teicher, M. H. (2016). Disorganized attachment in infancy predicts greater amygdala volume in adulthood. Behavioural Brain Research, 308, 83-93. https://doi.org/10.1016/j.bbr.2016.03.050

Machin, A. J., & Dunbar, R. I. M. (2011). The brain opioid theory of social attachment: A review of the evidence. Behaviour, 148(9-10), 985-1025. https://doi.org/10.1163/000579511X596624

Maier, S. F., & Seligman, M. E. P. (2016). Learned helplessness at fifty: Insights from neuroscience. Psychological Review, 123(4), 349-367. https://doi.org/10.1037/rev0000033

Mikulincer, M., & Shaver, P. R. (2019). Attachment orientations and emotion regulation. Current Opinion in Psychology, 25, 6-10. https://doi.org/10.1016/j.copsyc.2018.02.006

Porges, S. W. (2007). The polyvagal perspective. Biological Psychology, 74(2), 116-143. https://doi.org/10.1016/j.biopsycho.2006.06.009

Robinson, M. J. F., Anselme, P., Fischer, A. M., & Berridge, K. C. (2014). Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues. Behavioural Brain Research, 266, 119-130. https://doi.org/10.1016/j.bbr.2014.03.004

Rusbult, C. E., & Martz, J. M. (1995). Remaining in an abusive relationship: An investment model analysis of nonvoluntary dependence. Personality and Social Psychology Bulletin, 21(6), 558-571. https://doi.org/10.1177/0146167295216002

Sbarra, D. A., & Hazan, C. (2008). Coregulation, dysregulation, self-regulation: An integrative analysis and empirical agenda for understanding adult attachment, separation, loss, and recovery. Personality and Social Psychology Review, 12(2), 141-167. https://doi.org/10.1177/1088868308315702

Schore, A. N. (2001). Effects of a secure attachment relationship on right brain development, affect regulation, and infant mental health. Infant Mental Health Journal, 22(1-2), 7-66. https://doi.org/10.1002/1097-0355(200101/04)22:1<7::AID-IMHJ2>3.0.CO;2-N

Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593-1599. https://doi.org/10.1126/science.275.5306.1593

Simpson, J. A., & Rholes, W. S. (2017). Adult attachment, stress, and romantic relationships. Current Opinion in Psychology, 13, 19-24. https://doi.org/10.1016/j.copsyc.2016.04.006

Spielmann, S. S., MacDonald, G., Maxwell, J. A., Joel, S., Peragine, D., Muise, A., & Impett, E. A. (2013). Settling for less out of fear of being single. Journal of Personality and Social Psychology, 105(6), 1049-1073. https://doi.org/10.1037/a0034628

Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17(10), 652-666. https://doi.org/10.1038/nrn.2016.111

Turner, D. R. (2026). And that’s why men like virgins: How biology and silence keep good girls in the dark. VirtualVillageMom Publishing.

Velotti, P., Beomonte Zobel, S., Rogier, G., & Tambelli, R. (2018). Exploring relationships: A systematic review on intimate partner violence and attachment. Frontiers in Psychology, 9, 1166. https://doi.org/10.3389/fpsyg.2018.01166

Widom, C. S., Czaja, S. J., & Dutton, M. A. (2008). Childhood victimization and lifetime revictimization. Child Abuse and Neglect, 32(8), 785-796. https://doi.org/10.1016/j.chiabu.2007.12.006

Widom, C. S., Czaja, S., & Dutton, M. A. (2014). Child abuse and neglect and intimate partner violence victimization and perpetration: A prospective investigation. Child Abuse and Neglect, 38(4), 650-663. https://doi.org/10.1016/j.chiabu.2013.11.004

Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of Personality and Social Psychology, 9(2, Pt. 2), 1-27. https://doi.org/10.1037/h0025848

About the Author

Donna R. Turner, Ed.S., MPH, CHES, HSMI, CDVA is the founder of the Center for Bio-Relational Health (CBRH) and the developer of the Bio-Relational Science educational framework. Her work integrates educational psychology, public health, neuroscience, reproductive biology, and relationship science to improve health literacy and relationship decision-making.

A Certified Health Education Specialist (CHES), Turner has spent more than two decades developing educational programs that translate complex scientific research into practical knowledge for the public. Her research interests include pair bonding, neuroendocrinology, reproductive health, human papillomavirus (HPV), stress physiology, and evidence-based relationship education.

She is the author of And That’s Why Men Like Virgins: How Biology & Silence Keep Good Girls in the Dark, the inventor of a patent-pending over-the-counter HPV sperm testing technology, and the creator of the Truth Talk relationship education series.

Learn more about the Center for Bio-Relational Health, explore additional Featured Articles, browse the Relationship Question Library for practical, evidence-informed answers grounded in Bio-Relational Science, or explore the app for free relationship lessons and unlock Ask Donna René for personalize guidance to your relationship questions.

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