ArticleInnovation in aging2025
The Effects of Risky Behaviors and Social Factors on the Frequency of Fraud Victimization Among Known Victims.
Article in Innovation in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Rational choice and situational convergence: an examination of adolescent cyber victimization from an integrated theoretical perspective.Frontiers in psychology · 2026Article
- Multilevel risk factors for financial fraud in later life: evidence from China.Innovation in aging · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objectives: Routine activity theory (RAT) asserts that a suitable target's exposure to a motivated offender in the absence of capable guardians increases their likelihood of crime victimization. We use these principles to assess the extent to which engaging in risky routine activities-for example, entering sweepstakes drawings, answering unknown calls-is associated with victimization frequency among older adult mass marketing fraud victims across five types of scams: investment fraud, sweepstakes and lottery fraud, romance and family/friend imposter scams, fake products and services, and charity scams. We also examine whether financial and social vulnerability characteristics (loneliness, preference for taking financial risks, financial fragility) are associated with victimization frequency in older adults. Research Design and Methods: A survey was administered to households that the U.S. Postal Inspection Service identified as having recently responded to one or more mail scam solicitations. Respondents answered questions on their behaviors, financial risk preferences, social and demographic characteristics, and number of past-year victimization experiences with 5 types of fraud. Results: As predicted based on RAT, routine activities that increase a target's exposure to motivated offenders are positively associated with fraud victimization frequency, although more frequent online activity was negatively associated with victimization frequency contrary to hypotheses. Precarious financial and emotional states such as financial fragility and loneliness also were associated with greater victimization frequency, and more frequent social engagement and living with others (the presence of capable guardians) had no effect. Discussion and Implications: Target suitability factors such as loneliness, financial fragility, and risky financial preferences and behaviors are associated with a higher frequency of fraud victimization among older adults. Consumer education should include information on reducing risky behaviors that can increase fraud exposure. More frequent social engagement may not be protective. Older adults who are financially fragile and experiencing loneliness require more safeguards.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.