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Evidence explained

Why people get drawn into romance scams

Scammers can exploit a person’s need for connection, tailor their attention, and make a fraudulent relationship difficult to leave. Research links several emotional and personality characteristics with victimization, but it does not establish a reliable checklist for identifying who will be deceived (Whitty, 2013, 2020; Xie & Duan, 2024).

Explanation updated . This can reflect an editorial correction without a new evidence snapshot.

AI-assisted explanation · Automated editorial and source checks. Preparation and review details

Circumstances, tailored approaches, and difficulty leaving

Interpretation. The comparisons below cover social circumstances, romantic beliefs, tailored approaches, and difficulty leaving—not four successive stages. Being approached, believing a relationship, sending money, and remaining involved are distinct outcomes; evidence about one should not be treated as prediction of another (DeLiema & Witt, 2023; Whitty, 2013, 2020).

Circumstances, tailored approaches, and difficulty leaving
FocusWhat the studies showWhat remains uncertain
Social and emotional circumstances Victim and perpetrator interviews

Interviews identified limited social support, insecurity, and low self-esteem as circumstances scammers could exploit (Xie & Duan, 2024).

These themes describe interview participants, not an exhaustive set of characteristics shared by everyone who experiences the scam (Xie & Duan, 2024).

Romantic beliefs Questionnaires and statistical analysis of associations

In Buchanan and Whitty’s two 2013 studies, higher scores on idealization—viewing romantic love as perfect or ideal—were associated with being fooled by scammers (Buchanan & Whitty, 2013).

Interpretation. The findings describe associations in the study samples; they do not establish a reliable screening tool for future victims (Buchanan & Whitty, 2013).

Tailored approaches Linguistic profile analysis

Scammer profiles appeared to appeal to people seeking exclusive relationships who might commit quickly (Lee et al., 2022).

Interpretation. The apparent audience for a profile does not establish which readers actually believed it or sent money (Lee et al., 2022; Whitty, 2020).

Difficulty leaving Participant accounts and proposed explanations

Some participants struggled to end the relationship even after learning it was not genuine (Whitty, 2013).

Interpretation. Descriptions of feeling addicted help convey the experience but do not, by themselves, establish a clinical diagnosis (Whitty, 2013).

Personality findings do not amount to a victim profile

Interpretation. In Buchanan and Whitty’s 2013 research, a set of questions about love at first sight was excluded because participants’ answers were not sufficiently consistent. That matters when interpreting the link with romantic beliefs: the analysis did not cover every belief the researchers tried to measure. Before using such scores for screening, a service would need evidence about predictions for new people (Buchanan & Whitty, 2013).

Interpretation. A 2017 questionnaire study reported associations with scores labeled urgency, sensation seeking, addiction disposition, kindness, and trustworthiness. These are names of questionnaire measures, not diagnoses or judgments about victims’ character. The available excerpts do not explain the questions behind each label, so those associations cannot responsibly be turned into a personality checklist (Whitty, 2017).

A 2020 cyberscam model covering 11,780 respondents detected associations within its sample but explained little of the variation in victimhood. Detecting those associations did not establish useful prediction for new people. The study omitted routine activities—what people regularly do online—and concerned cyberscams generally, not romance scams alone (Whitty, 2020).

Offenders adapt their attention to the person

Xie and Duan’s 2024 study interviewed 18 victims and 13 perpetrators of pig-butchering scams, in which victims may keep depositing money to recover inaccessible apparent profits. The interviews identified limited social support, insecurity, and low self-esteem as recurring themes. This was an exploration of participants’ experiences, not a test comparing people who were deceived with people who resisted (Wang & Zhou, 2022; Xie & Duan, 2024).

Perpetrators described looking for frequent self-criticism and requests for care. They also said that a few conversations helped them decide how to tailor their language. These accounts shift attention from a supposedly fixed weakness in the victim to the offender’s active efforts to identify and exploit a need (Xie & Duan, 2024).

Interpretation. The researchers retained findings only when victim and perpetrator accounts agreed, while acknowledging that their themes did not cover every aspect of susceptibility. An Indian case study adds a related concern: undisclosed relationships left friends and family fewer opportunities to offer advice, check information or intervene before an in-person meeting. These findings support asking whom the person wants involved; they do not show that disclosure would prevent fraud (Verma et al., 2026; Xie & Duan, 2024).

Loneliness matters, but its role is not settled

A UK pandemic study compared romance-fraud reports to Action Fraud from April 2014–December 2020 with loneliness and internet-use estimates from the Understanding Society survey from January 2017–November 2020. These were the data collection windows, not the duration of anyone’s loneliness or exposure to fraud. Researchers used earlier trends to estimate expected ranges during the pandemic (Buil-Gil & Zeng, 2021).

Only the 16–29 age group showed changes in loneliness outside the study’s predicted range. That does not mean those respondents became fraud victims. The study could not establish causal links between loneliness, internet use, and romance fraud, and it measured loneliness with a single frequency question (Buil-Gil & Zeng, 2021).

Accounts from people with acquired brain injury offer a more personal account: lost friendships and difficulties forming romantic relationships helped make online connection attractive. All participating survivors had severe injuries, however. Their experiences cannot simply be extended to people with milder injuries, and the authors could not establish that the vulnerabilities were unique to brain injury (Gould et al., 2021).

Recognizing deception and leaving are separate problems

Whitty’s explanatory model describes a sunk-cost effect: previous investment can make withdrawal harder. In these accounts, the desired payoff was often the relationship itself rather than money. The model also describes people dismissing contradictory messages to preserve the relationship story they wanted to believe (Whitty, 2013).

The investment version can add another reason to stay. In Wang and Zhou’s analysis, most victims continued putting money into an app when they could not withdraw apparent profits or recover their original investment. They were trying to obtain money they believed was already theirs, not simply pursuing a new opportunity (Wang & Zhou, 2022).

Interpretation. Some participants in Whitty’s research described feeling addicted to the relationship and struggling to cut contact after discovering the deception. This makes recognition an incomplete measure of whether someone has exited a scam. It also suggests that repeating the same factual warning may miss the attachment keeping the person involved (Whitty, 2013).

Reports and repeat incidents need careful interpretation

Complaint counts cannot cleanly identify which groups are most susceptible. An analysis of mass-marketing-scam complaints found that its data mixed three things it could not separate: exposure to fraud, victimization, and willingness to report. A group’s visibility in reports therefore cannot be read directly as its probability of being deceived (DeLiema & Witt, 2023).

Repeat experiences are nevertheless a concern. In one study of catfishing—deceiving someone through a false online identity in a relationship—more than 76% of respondents who reported being catfished said it had happened more than once. That figure describes repeat catfishing in the sample, not repeat financial loss from romance fraud. The authors called for examining behavior before and after victimization to clarify the relationships (Snyder & Golladay, 2024).

What education and support teams can change

Interpretation. These studies can inform the questions teams ask and the situations they explain. They do not establish that a personality checklist, a particular lesson, or a support conversation prevents losses. The following suggestions are practical interpretations, not tested interventions (Whitty, 2013, 2020; Xie & Duan, 2024).

  1. Explain the interaction, not a stereotype

    Use examples showing how an offender notices a need for care and adjusts the conversation. Avoid describing victims simply as lonely, gullible, or unusually trusting. Ask learners to identify the information the offender uses and how the message is tailored, rather than assign the target a personality label (Xie & Duan, 2024).

  2. Ask what makes disengagement difficult

    In support conversations, distinguish uncertainty about the scam from difficulty giving up the relationship or hoped-for money. Ask what the person fears losing by leaving, rather than assuming continued contact means they have not understood the evidence (Wang & Zhou, 2022; Whitty, 2013).

  3. Measure the outcome you actually mean

    When evaluating a risk assessment or educational program, separate contact with a scammer, belief in the relationship, payment, and continued involvement. Ask whether the study measured behavior before victimization or only afterward, and whether its outcome was catfishing or financial fraud (Snyder & Golladay, 2024; Whitty, 2020).

Before adopting a vulnerability checklist

Does the checklist predict deception or financial loss in people like those you serve, or does it merely describe people who have already reported harm? If the evidence supports only description, use it to open a conversation about circumstances—not to decide who is safe or who deserves attention (DeLiema & Witt, 2023; Whitty, 2020; Xie & Duan, 2024).

About the evidence

This explanation draws on selected sources from RSRC’s full synthesis. The full research record, its source list and version history remain available below.

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Scope, preparation and limitations

Codex edited and reviewed this explanation from synthesis version 90. Changed passages were checked against preserved source excerpts; passing source checks were reused for unchanged passages. The editorial judgments are recorded as Codex review, not a new API grading run. They assess communication, not reader-test results or scientific certainty. No human or expert content review of this explanation is recorded.

The full synthesis preserves 27 publication records and 122 evidence statements. These counts do not establish the number of independent studies or the strength of a finding. Practical implications are editorial interpretations, with limitations explained alongside the evidence.

RSRC methodology
Sources cited in this explanation (12)

Links open the publication record or original work. Journal access may vary.

  1. Buchanan, T., & Whitty, M. T. (2013). The online dating romance scam: causes and consequences of victimhood. Psychology, Crime & Law, 20(3), 261–283. https://doi.org/10.1080/1068316x.2013.772180
  2. Buil-Gil, D., & Zeng, Y. (2021). Meeting you was a fake: investigating the increase in romance fraud during COVID-19. Journal of Financial Crime, 29(2), 460–475. https://doi.org/10.1108/jfc-02-2021-0042
  3. DeLiema, M., & Witt, P. (2023). Profiling consumers who reported mass marketing scams: demographic characteristics and emotional sentiments associated with victimization. Security Journal, 37(3), 921–964. https://doi.org/10.1057/s41284-023-00401-5
  4. Gould, K. R., Carminati, J.-Y. J., & Ponsford, J. L. (2021). “They just say how stupid I was for being conned”. Cyberscams and acquired brain injury: A qualitative exploration of the lived experience of survivors and close others. Neuropsychological Rehabilitation, 33(2), 325–345. https://doi.org/10.1080/09602011.2021.2016447
  5. Lee, K. F., Chan, M. Y., & Mohamad Ali, A. (2022). Self and desired partner descriptions in the online romance scam: a linguistic analysis of scammer and general user profiles on online dating portals. Crime Prevention and Community Safety, 25(1), 20–46. https://doi.org/10.1057/s41300-022-00169-7
  6. Snyder, J. A., & Golladay, K. (2024). More Than Just a “Bad” Online Experience: Risk Factors and Characteristics of Catfishing Fraud Victimization. Deviant Behavior, 1–21. https://doi.org/10.1080/01639625.2024.2416071
  7. Verma, S., Gujarathi, P., & Lazarus, S. (2026). Romance Fraud in India: A Qualitative Study of Online–Offline Transitions in the Digital Dating Ecosystem. Journal of Economic Criminology, 100248. https://doi.org/10.1016/j.jeconc.2026.100248
  8. Wang, F., & Zhou, X. (2022). Persuasive Schemes for Financial Exploitation in Online Romance Scam: An Anatomy on Sha Zhu Pan (杀猪盘) in China. Victims & Offenders, 18(5), 915–942. https://doi.org/10.1080/15564886.2022.2051109
  9. Whitty, M. T. (2013). The Scammers Persuasive Techniques Model: Development of a Stage Model to Explain the Online Dating Romance Scam. British Journal of Criminology, 53(4), 665–684. https://doi.org/10.1093/bjc/azt009
  10. Whitty, M. T. (2017). Do You Love Me? Psychological Characteristics of Romance Scam Victims. Cyberpsychology, Behavior, and Social Networking, 21(2), 105–109. https://doi.org/10.1089/cyber.2016.0729
  11. Whitty, M. T. (2020). Is There a Scam for Everyone? Psychologically Profiling Cyberscam Victims. European Journal on Criminal Policy and Research, 26(3), 399–409. https://doi.org/10.1007/s10610-020-09458-z
  12. Xie, Z., & Duan, Z. (2024). “Why did I fall for it?” Exploring internet fraud susceptibility in the pig butchering scam. Security Journal, 38(1). https://doi.org/10.1057/s41284-024-00457-x
Full synthesis and revision history

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Across the reviewed evidence, susceptibility to relationship-based online scams is best characterized as interactional and context-dependent. Loneliness after divorce or bereavement, delayed marriage, and searching for life change are suggested pathways to emotional attachment or deception, rather than established individual predictors of victimization. Scammers harvest personal information from dating apps and social media to identify targets, then use staged grooming that includes small “testing-the-water” gift or request strategies and escalation of requests. Cognitive and motivational processes documented as contributors to sustained engagement and difficulty exiting fraudulent relationships include sunk-cost effects (with the relationship itself often the desired end), near-win events (for example, anticipated reunions thwarted by a sudden emergency), and cognitive dissonance, whereby victims dismiss contradictory information to preserve the desired narrative (Grace Carvalho Fernandes et al., 2023; Kim & Seo, 2019; Wang & Zhou, 2022; Whitty, 2013a, 2013b).

Emotional states and life transitions as proximal vulnerability conditions

The reviewed literature identifies loneliness and life transitions as possible contexts for emotional receptivity to online relationships. One paper suggests attachment associated with loneliness after divorce, bereavement, or delayed marriage; another presents seeking life improvement as a condition that may facilitate deception. These descriptions do not establish elevated individual selection or engagement risk, or intentional offender timing around such transitions. A systematic review describes loneliness as a significant risk factor, citing research that combined romance-fraud reports with separate survey estimates of loneliness and internet use. In that research, only respondents aged 16–29 showed loneliness significantly above predicted pre-COVID trends; this is not itself an individual-level test of scam susceptibility. A qualitative study in India adds a distinct social mechanism: when relationships remained undisclosed, others had fewer opportunities to offer advice, verify information, or intervene before an offline meeting. This finding concerns online–offline transitions and does not demonstrate that disclosure prevents fraud or financial loss (Buil-Gil & Zeng, 2021; Grace Carvalho Fernandes et al., 2023; Kassem & Carter, 2023; Kim & Seo, 2019; Verma et al., 2026).

One study analysed reports of romance fraud to Action Fraud (April 2014–December 2020) together with Understanding Society longitudinal survey estimates of loneliness and internet use (January 2017–November 2020), and operationalised loneliness using a single frequency measure rather than the 20‑item UCLA loneliness scale (Buil-Gil & Zeng, 2021).

Public profiles, online routines, and target selection

Corpus and qualitative analyses show offenders harvest publicly available profile cues and routine online behaviour to identify and prioritise targets. Reported signals include disclosed relationship status, photos, occupation, family information, and visible patterns of online engagement—information used to assess emotional state, financial ‘juiciness’, and availability (Faber, 2024; Huang et al., 2015; Lee et al., 2022; Wang & Zhou, 2022).

Offender‑perspective and corpus work further report deliberate persona tailoring and profiling (for example creating accounts geared to middle‑aged divorced women) and use of platform affordances (friending on Facebook; profile narratives) to increase exposure to potential victims, indicating that platform practices and public disclosures materially shape selection (Huang et al., 2015; Lee et al., 2022; Toma, 2016).

Grooming sequences and proximate mechanisms sustaining engagement

A consistent set of qualitative and corpus studies documents staged grooming sequences: early trust building and emotional intimacy, ‘test‑the‑water’ small requests, near‑win events or early apparent returns (especially in romance‑investment variants), and stepwise escalation of demands. Empirical and offender‑perspective work reports that initial compliance with small requests or apparent small returns frequently increases later compliance via commitment and sunk‑cost dynamics (Wang & Zhou, 2022; Whitty, 2013a, 2013b; Xie & Duan, 2024).

Complementary findings describe cognitive‑motivational processes observed in victim accounts: near‑win events that encourage continued investment, and cognitive dissonance processes whereby victims sustain a preferred narrative and dismiss contradictory information—mechanisms that qualitative studies identify as helpful for explaining persistence and repeat engagement (Whitty, 2013b).

Dispositional and cognitive correlates: evidence and limits

Several empirical studies measured dispositional traits (for example romantic beliefs, impulsivity, locus of control, neuroticism, and related constructs) and reported associations with self‑reported susceptibility or victimhood in particular samples. One study found higher romantic‑belief scores predicted being fooled in its sample, and larger panel work measured impulsivity and neuroticism alongside demographic controls (Buchanan & Whitty, 2013; Whitty, 2017, 2020).

The reviewed work documents limited granularity in analysis—vulnerability to different scam types is often considered together rather than separately—and reports measurement of dispositional traits and demographics (impulsivity, locus of control, neuroticism, age, gender, education) (Buchanan & Whitty, 2013; Whitty, 2020).

Population‑specific vulnerability pathways

Qualitative and administrative evidence identified vulnerabilities among people with acquired brain injury (ABI), including cognitive impairment and ‘scam blindness,’ which participants reported could increase susceptibility to cyberscams. Participants also associated romance scams with feelings of boredom or loneliness and with trusting or generous personalities. These findings come from a sample of survivors with severe ABI and may not generalize to people with mild or moderate ABI or to different impairment profiles (Gould et al., 2021).

Older‑adult studies recurrently report social isolation, widowhood or bereavement, and emotional vulnerability among targeted older victims; other sources identify younger adults (for example 25–34 in one national statistic) as an exposed high‑loss group in some contexts, particularly where romance baiting is combined with investment narratives. In a study of fifty convicted online romance-fraud offenders, the predominance of female victims prompted the authors to recommend awareness campaigns tailored to women on dating platforms. That case-based observation does not establish greater susceptibility among women in the general population or demonstrate that such campaigns are effective (Cross, 2023; Pope & Seto, 2026; Soares & Lazarus, 2024).

Repeat victimization and routine behaviours

Multiple large surveys and complaint‑based studies document high rates of repeat victimization in catfishing and related relationship‑based deception: more than three‑quarters of catfishing respondents in two large samples reported being victimized more than once, with many reporting multiple incidents (Golladay & Snyder, 2025; Snyder & Golladay, 2024).

Qualitative survivor accounts and survey analyses report that information overload and mental exhaustion led some participants to overlook warning signs or act without adequate reflection. Authors recommend future research that prospectively measures behaviors before and after catfishing to clarify temporal relationships to victimization, and that includes broader online-application user groups, additional risk factors, and varied recall periods (Cazanis et al., 2025; Snyder & Golladay, 2024).

Methodological patterns, limitations, and evidence gaps

The evidence requires distinguishing explanatory accounts from population-level estimates of susceptibility. A psychoanalytic case account interprets catfishing in relation to rejection and marginalized identity, but does not establish population-level risk. A complaint-data study explicitly states that exposure, victimization, and the propensity to report to a federal agency cannot be separated analytically; demographic patterns in those complaints therefore cannot establish which groups are most susceptible. Research on catfishing also calls for further investigation of repeat victimization rather than treating its relationship with catfishing as fully explained (DeLiema & Witt, 2023; Golladay & Snyder, 2025; Knafo, 2021).

Several evidence records explicitly call for specific research actions supported in the reviewed material: testing whether flow or addiction constructs help explain delayed recognition and exit difficulty; prospective measurement of behaviors around catfishing to clarify temporal order; improved measurement of loneliness and social-isolation constructs; and targeted research on psychological vulnerabilities that may be exploited by AI-enhanced emotional manipulation. A study of female Facebook users in Malaysia also proposes using its questionnaire for future comparisons of knowledge and protective practices across sociodemographic groups. This is a research agenda, not a completed demographic vulnerability ranking or a validated prediction of victimization (Abidin et al., 2018; Buil-Gil & Zeng, 2021; Gauci & Vella, 2026; Snyder & Golladay, 2024; Whitty, 2013b).

Knowledge and protective practices: outcome limits

Among female Facebook users in Malaysia, knowledge and protective-practice measures differed significantly between respondents whose family members, acquaintances, or friends had previously been victims of love scams (205 respondents) and those without that history (404). The preserved excerpt does not specify the direction of either difference. These findings concern knowledge and practices in a particular platform and population sample, not demonstrated reductions in victimization or financial loss (Abidin et al., 2018).

References

This AI-assisted synthesis is based on reviewed evidence records. It may contain errors or omissions. Follow the publication and DOI links, consult the original works, and make your own judgment about the evidence.

Revision history

  1. Version 90

    Current public version

    Incremental evidence update. A small update is warranted. Distinguish suggested emotional vulnerability from demonstrated risk, add the findings on relationship disclosure and knowledge/protective-practice differences with their outcome and sampling limits, and recognize sociodemographic comparisons as future research rather than established vulnerability rankings. Remove the synthetic-persona citation from the methodological synthesis. The central conclusion against a reliable victim checklist...

    • Publications: 27 (+2)
    • Evidence statements: 122 (+4)
    • Cited sources: 27 (+2)

    Sources added: Examining fifty cases of convicted online romance fraud offenders; Knowledge and Protective Practice Towards Love Scam Among Female Facebook Users in Malaysia; Romance Fraud in India: A Qualitative Study of Online–Offline Transitions in the Digital Dating Ecosystem.

    Sources removed: Synthetic Dialogue Dataset for Romance Scam Detection.

  2. Version 89

    Automated claim-level support repair round 1, correcting 5 passages from synthesis version 88.

  3. Version 88

    Automated evidence-grounded revision attempt 1. Initial version.

    • Publications: 25 (-5)
    • Evidence statements: 118 (-24)
    • Cited sources: 25 (-5)

    Sources removed: Adult attachment and online dating deception: a theory modernized; Factors of susceptibility to online romance scam in Malaysia: unraveling the complex pathways; Modelling the modus operandi of online romance fraud: Perspectives of online romance fraudsters; The Effects of Risky Behaviors and Social Factors on the Frequency of Fraud Victimization Among Known Victims; and 1 more.

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