Evidence map›Paper›PMID 41622293›Full record

ArticleInjury epidemiology2026

Examining disparities in harmful reporting on community firearm violence in Philadelphia television news reports.

Jessica H Beard, Evan L Eschliman, Jennifer Midberry, Leah E Roberts, Anita Wamakima, Kallie Palm, Siena Wanders, Tyrone Muns, Jim MacMillan, Christopher N Morrison

Abstract read
In one paragraph

Article in Injury epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jessica H BeardDivision of Trauma Surgery and Surgical Critical Care, Department of Surgery, Temple University Hospital, Philadelphia, PA, USA. jessica.beard@tuhs.temple.edu.
Evan L EschlimanDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Jennifer MidberryKlein College of Media and Communication, Temple University, Philadelphia, PA, USA.
Leah E RobertsDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
Anita WamakimaDivision of Trauma Surgery and Surgical Critical Care, Department of Surgery, Temple University Hospital, Philadelphia, PA, USA.
Kallie PalmLewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Siena WandersLewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Tyrone MunsLewis Katz School of Medicine at Temple University, Philadelphia, PA, USA.
Jim MacMillanPhiladelphia Center for Gun Violence Reporting, Philadelphia, PA, USA.
Christopher N MorrisonDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.

Funding

Substance Abuse Epidemiology Training Program (SAETP) at Columbia UniversityT32DA031099 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEBORAH S HASIN, Silvia Saboia Martins · 2012 to 2026
$6.1M
Examining Racial and Spatial Disparities in Harmful News Media Reporting on Community Firearm ViolenceR21MD019088 · NIMHD · TEMPLE UNIV OF THE COMMONWEALTH · PI BEARD, JESSICA H · 2023 to 2024
$452k
Individuals' Longitudinal Risks for Firearm Violence Perpetration and VictimizationK18HD117390 · NICHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MORRISON, CHRISTOPHER NEIL · 2024 to 2024
$348k
NICHD NIH HHS K18 HD117390NIDA NIH HHS T32 DA031099NIMHD NIH HHS R21 MD019088
6 · The paper itself

Abstract

backgroundNews coverage of community firearm violence (CFV) can cause multilevel harm. We aimed to quantify the frequency and severity of harmful CFV news content and examine how victim, shooting event, and place-based characteristics relate to harmful CFV reporting.

methodsWe performed a quantitative media content analysis of a random sample of CFV clips aired on Philadelphia local television news in 2021 using a novel codebook. We matched clips to shooting victims in the Philadelphia Police Department dataset and used shooting event location to obtain place-based characteristics from American Community Survey data. Generalized structural equation models evaluated associations between victim demographics, shooting event, and place-based characteristics (Group I), news coverage characteristics (Group II), and either composite harmful CFV reporting scores or specific harmful reporting elements determined by a prior modified Delphi process (Group III).

resultsAmong 394 individuals covered in 303 clips, the mean (SD) individual-level harmful CFV reporting score was 15.2 (4.38) out of 29. Episodic framing (i.e. reporting lacking systematic context) (93.9%) was the most common harmful content element and perpetrator mugshot (4.8%) was least common element. Graphic and/or explicit content was present in 30.3% of clips. Individuals having more than one clip and longer total focus time had higher harmful reporting scores, while individuals involved in fatal shootings, having longer total clip length, and having a follow-up story had lower scores. Black, adult, victims in non-fatal shootings and people shot in areas with a higher proportion of Black residents were more likely to have news coverage containing graphic and/or explicit content.

conclusionsHarmful CFV reporting is pervasive, and the severity of harm is associated with news coverage characteristics. Disparities in specific harmful CFV content elements may further exacerbate existing health inequities. Journalists should modify CFV reporting practices to minimize harm.

Indexed as

Firearm injuryFirearm violenceFramingJournalismMediaNews reporting

Identifiers

PMID41622293
PMCPMC12952156

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.