Popular media misinformation on neonatal abstinence syndrome, 2015-2021.

Health communication Misinformation Substance use

Journal

The International journal on drug policy
ISSN: 1873-4758
Titre abrégé: Int J Drug Policy
Pays: Netherlands
ID NLM: 9014759

Informations de publication

Date de publication:
16 Feb 2024
Historique:
received: 21 06 2023
revised: 22 12 2023
accepted: 28 01 2024
medline: 18 2 2024
pubmed: 18 2 2024
entrez: 17 2 2024
Statut: aheadofprint

Résumé

As the overdose crisis unfolded, narratives mischaracterizing neonatal abstinence syndrome (NAS) as "addicted babies" with echoes to the "crack babies" panic proliferated in mainstream media. his study examines NAS misinformation dynamics and characteristics over a seven-year period. Based on a comprehensive query, Media Cloud was used to compile mainstream media content relating to NAS between 2015 and 2021. Articles were redundantly coded on key parameters such as speakers represented, publication source, and scientific accuracy. Of the 348 articles meeting search criteria, 264 (76 %) featured misinformed narratives, 70 (20 %) featured informed narratives, and 14 (4 %) featured both informed and misinformed content. Most frequent misinformation elements related to misrepresentation of babies as "addicted" at birth and exaggeration of NAS symptomatology and long-term harms. Least represented voices were people most affected, with just 11 (2 %) featuring mothers who used opioids prepartum. Since misinformation contributes to punitive legal responses and harms patient care, efforts to prevent, monitor, and address inaccurate and stigmatizing narratives are essential to improving policy and practice.

Sections du résumé

BACKGROUND BACKGROUND
As the overdose crisis unfolded, narratives mischaracterizing neonatal abstinence syndrome (NAS) as "addicted babies" with echoes to the "crack babies" panic proliferated in mainstream media. his study examines NAS misinformation dynamics and characteristics over a seven-year period.
METHODS METHODS
Based on a comprehensive query, Media Cloud was used to compile mainstream media content relating to NAS between 2015 and 2021. Articles were redundantly coded on key parameters such as speakers represented, publication source, and scientific accuracy.
RESULTS RESULTS
Of the 348 articles meeting search criteria, 264 (76 %) featured misinformed narratives, 70 (20 %) featured informed narratives, and 14 (4 %) featured both informed and misinformed content. Most frequent misinformation elements related to misrepresentation of babies as "addicted" at birth and exaggeration of NAS symptomatology and long-term harms. Least represented voices were people most affected, with just 11 (2 %) featuring mothers who used opioids prepartum.
DISCUSSION CONCLUSIONS
Since misinformation contributes to punitive legal responses and harms patient care, efforts to prevent, monitor, and address inaccurate and stigmatizing narratives are essential to improving policy and practice.

Identifiants

pubmed: 38367328
pii: S0955-3959(24)00026-4
doi: 10.1016/j.drugpo.2024.104341
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104341

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare no conflicts of interests.

Auteurs

Katie McCreedy (K)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States. Electronic address: mccreedy.k@northeastern.edu.

Aanchalika Chauhan (A)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States.

Gabriel Holder (G)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States.

Sunyou Kang (S)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States.

Eric Reinhart (E)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States.

Leo Beletsky (L)

Bouve College of Health Sciences, Northeastern University, Boston, MA, United States.

Classifications MeSH