Skip to main content

Uncovering vulnerability to fraud and scams among adult victims in online and offline contexts: A systematic review

Chiara Barbara Dadà ; Laura Colautti ; Alessia Rosi ; Elena Cavallini ; Alessandro Antonietti ; Paola Iannello (2025) — Computers in Human Behavior

What do these research terms mean?
Preprint
A manuscript shared before formal peer review and publication. Check whether a later published version is available.
Dataset
A collection of data or examples for others to inspect or reuse. It can appear in Library search and topic mapping, but RSRC does not use dataset records as evidence in Research Insights.
Dissertation or thesis
Research submitted for an academic degree. This describes its format, not its reliability.
Journal article
An article published in a journal. This label alone does not establish peer review, study quality, or how well the findings apply elsewhere.
Qualitative research
Examines experiences, meanings, or processes, often through interviews or observations. It can explain how something happens without estimating how common it is.
Quantitative research
Uses numerical measurements to describe patterns or test relationships. A relationship between two measurements does not by itself show that one causes the other.
Systematic review
Uses a planned, documented method to find and assess research addressing a question. Its conclusions still depend on the included studies and what the search covered.
Meta-analysis
Statistically combines results from multiple studies. Combining studies does not remove weaknesses in their design or make unlike populations interchangeable.
Not classified
This record has no recognized label in this filter. It does not mean the publication used no method, or that no research exists.

Definitions draw on DataCite resource types; Cochrane review methods; NLM: association and causation. RSRC’s dataset and classification rules are explained in our methodology.

Citation tools


              
              

Transparency

Evidence and review status

This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

Source basis
Downloaded PDF
Source updates
No notice found at last check
AI-generated page content
Yes
Automated checks
Passed
Administrative approval
Yes
Human content review
Not recorded
Subject-matter-expert review
Not recorded
How this was prepared
Source basis

RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.

  • PDF added to RSRC:
Source updates

No incoming update notice was found in the dated Crossref response. Coverage is incomplete, particularly for corrections and expressions of concern; this is not a guarantee that the source is valid or unchanged.

  • Last source-status attempt:
AI-generated page content

AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.

  • Document analysis recorded:
  • Page record updated:
Automated checks

The current, source-bound synopsis passed the recorded versioned publication checks.

  • Checks completed:
View passed checks (3)
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
  • Numerical claims checked against the available source text
  • English-source lexical grounding check
Administrative approval

An authenticated administrator approved the bibliographic record for public Library display. This is not a review of every research claim.

  • Approved for public display:
Human content review

No human review is recorded for the AI-generated content displayed on this page.

Subject-matter-expert review

RSRC has not recorded review of this content by a subject-matter or methods expert.

Review-state definitions
Found a possible error? Request a correction.

Synopsis

The authors conducted a PRISMA-guided systematic review, registered in PROSPERO, of peer-reviewed empirical studies published 2014-2024. Searches of PubMed, PsycINFO, and Scopus were completed in September 2024; reference lists were additionally reviewed. Three investigators screened studies, with independent title/abstract and full-text screening procedures. Fraud victims cannot be treated as a homogeneous group; vulnerability reflects scam type, individual characteristics, and context. The most consistently supported risk factors were low conscientiousness, high impulsivity, reduced cognitive functioning, and social isolation. The review found no consistent risk profile, and context-specific studies limit generalization.

Identified Gaps

Evidence lacks consistent, generalizable fraud-victim risk profiles because fraud types, countries, samples, measures, and contexts vary. The literature disproportionately focuses on older adults, potentially overlooking younger adults’ digital-scam vulnerability. Research rarely establishes which attacks succeed and why, and has limited experimental designs. Studies often assess characteristics after victimization and primarily include victims, leaving susceptibility among un-targeted or non-victimized people less understood. Standardized methods permitting comparisons across fraud types and online/offline contexts are needed.

Methods

PRISMA-guided systematic review, registered in PROSPERO, of peer-reviewed empirical studies published 2014–2024. Searches of PubMed, PsycINFO, and Scopus were completed in September 2024; reference lists were additionally reviewed. Three investigators screened studies, with independent title/abstract and full-text screening procedures. Included studies examined adult victims of specified scams in real or simulated contexts. Thirty-two studies were synthesized by fraud type, individual risk factors, demographics, country, methodology, and sample characteristics. JBI cross-sectional or cohort appraisal tools assessed study quality.

Limitations

The review found no consistent risk profile, and context-specific studies limit generalization. Most included evidence was retrospective and cross-sectional, preventing causal inferences or determination of whether characteristics preceded victimization. Heavy reliance on victimization data may omit susceptible people not yet targeted. Heterogeneous psychosocial measures, outcomes, and methodologies prevented meta-analysis and consistent conclusions. Search keywords may not have covered the full fraud literature, including specific types such as phishing and romance scams; rapidly evolving fraud may also outpace any fixed search strategy.

Future Work

Future studies should use longitudinal designs to distinguish pre-existing predictors from consequences of victimization, and behavioral experiments to reduce survey/interview bias. Research should apply unified designs and standardized measures across fraud types and online/offline settings, include younger as well as older adults, and examine susceptibility among non-victims. It should investigate persuasive strategies (urgency, authority, emotional manipulation) and their links to risk profiles, and expand search terms to capture specific and emerging fraud types.

See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.