Skip to main content

The effect of true crime docuseries on romance fraud reporting to the police

Stephany Grant ; David Buil-Gil (2025) — Crime Science

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

The record is approved for public display, but a complete historical administrator action is not recorded.

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 study analyzed monthly UK data from April 2014 to January 2024. It combined Action Fraud romance-fraud reports, releases of five high-engagement TV portrayals, LexisNexis article counts, and UK Google Trends searches. GEE Poisson time-series models with AR(1) correlation estimated associations while controlling for trend, seasonality, and COVID-19 lockdowns; Negative Binomial models served as a sensitivity analysis. Dirty John, Love Fraud, and The Puppet Master were associated with statistically significant increases in reported romance fraud of 6%, 24%, and 9%, respectively. News article volume and Google search volume did not significantly moderate the association between docuseries and reported romance fraud. The design estimates temporal associations rather than demonstrating that viewing caused reporting.

Identified Gaps

The study identifies limited evidence on the mechanisms through which media portrayals affect reporting. It also leaves unclear which program content or themes distinguish portrayals associated with increased reporting, and whether comparable effects occur for other crime types.

Methods

The study analyzed monthly UK data from April 2014 to January 2024. It combined Action Fraud romance-fraud reports, releases of five high-engagement TV portrayals, LexisNexis article counts, and UK Google Trends searches. GEE Poisson time-series models with AR(1) correlation estimated associations while controlling for trend, seasonality, and COVID-19 lockdowns; Negative Binomial models served as a sensitivity analysis.

Limitations

The design estimates temporal associations rather than demonstrating that viewing caused reporting. TV-program selection was restricted to releases with over 1,000 IMDb reviews, using reviews as a proxy for audience engagement because precise viewing figures were unavailable. The outcome captures reports to Action Fraud, not all victimization or reporting pathways. The authors also note that the explanation based on case outcomes is difficult to prove.

Future Work

Test which specific messages or themes within TV programs increase reporting; assess whether true-crime docuseries on other crimes also increase reporting; and survey fraud victims to identify mechanisms linking media portrayals to reporting.

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