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Addictive behaviors

July 22, 2026 · via Europe PMC

Changes in gambling behaviors among young adults in Rhode Island, 2022-2024.

Rosenthal SR, Torres JN, Lyons ME, Silva S.

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Overall gambling participation among Rhode Island young adults was stable from 2022 to 2024, but those who gambled engaged in more types, including sports betting, slots, and app-based gambling.

What was studied

Repeated cross-sectional data from the Rhode Island Young Adult Survey in 2022 (n=1,022) and 2024 (n=1,008) among 18-25-year-olds.

Key findings

  • No significant change in overall gambling participation
  • Among gamblers, increases in sports betting (AOR 1.65), casino slots (AOR 2.99), other slots (AOR 2.30), and app-based gambling (AOR 2.14)
  • Number of gambling types endorsed increased (IRR 1.28)
  • Positive BBGS screens more common but not significant after adjustment

Clinical relevance

This suggests clinicians may consider screening young adults for gambling, especially mobile and sports betting, as engagement diversifies.

Who should care

Psychiatry

Limitations

Repeated cross-sectional surveys from one state; self-report.

Young adult gamblers are diversifying into sports betting and apps, a possible emerging risk.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Background

The rapid expansion of legalized sports betting and mobile gambling in the U.S. has transformed how gambling is accessed and experienced. Young adults are particularly vulnerable to these changes; however, limited research has examined how gambling behaviors are shifting across multiple modalities during periods of expanding gambling availability.

Methods

We analyzed repeated cross-sectional data from the Rhode Island Young Adult Survey (RIYAS) collected in 2022 (n = 1,022) and 2024 (n = 1,008) among individuals aged 18-25 years. Outcomes included past-year participation in specific gambling behaviors, positive BBGS (Brief Biosocial Gambling Screen) screens, and overall gambling involvement measured as the number of gambling types endorsed. Multivariable logistic regression models estimated adjusted odds ratios for differences in individual gambling behaviors between survey waves, and Poisson/zero-inflated Poisson models estimated differences in gambling involvement.

Results

Gambling participation did not differ significantly between 2022 and 2024. However, among individuals reporting gambling, participation increased in several activities, including lottery tickets (AOR = 1.36, 95 % CI: 1.01-1.83), raffle gambling (AOR = 1.40, 95 % CI: 1.05-1.88), sports betting (AOR = 1.65, 95 % CI: 1.07-2.56), casino slot machines (AOR = 2.99, 95 % CI: 2.10-4.27), other slot machines (AOR = 2.30, 95 % CI: 1.23-4.33), and app-based gambling (AOR = 2.14, 95 % CI: 1.38-3.32). The number of gambling types endorsed increased (IRR = 1.28, 95 % CI: 1.16-1.41). Positive BBGS screens were more common in 2024 but not statistically significant after adjustment.

Conclusions

Findings suggest while overall gambling participation remained stable, engagement across multiple and mobile-based gambling activities increased between survey waves, potentially signaling emerging risk. Increasing diversification and digitalization of gambling behaviors requires continued surveillance and public health strategies addressing emerging gambling environments.

DOI

10.1016/j.addbeh.2026.108804

PMID

42497732

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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