Gambling type preferences, psychological distress and hazardous alcohol use among young Finns
Bibliographic Data
| ID | 21727140 |
|---|---|
| Authors | Kalle Lind (0000-0003-0238-3837, Finnish Institute for Health and Welfare, corresponding author), Tanja Grönroos (0000-0001-9888-9300, Finnish Institute for Health and Welfare), Johanna Järvinen-Tassopoulos (0000-0003-0839-1205, Finnish Institute for Health and Welfare), Tiina Latvala (0000-0002-6921-386X, Finnish Institute for Health and Welfare), Jukka Kontto (0000-0003-3899-9852, Finnish Institute for Health and Welfare), Anne H Salonen (0000-0002-4693-0110, Finnish Institute for Health and Welfare) |
| Year | 2026 |
| Pages | 1-16 |
| Publication date | 2026-06-29 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Addiction Research & Theory (JOURNAL) |
| Journal identifiers | ISSN: 1476-7392 • E-ISSN: 1606-6359 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/16066359.2026.2693271 |
| OpenAlex | W7166590502 |
| Language | EN |
| References cited | 53 |
Background: Adolescence and early adulthood are periods of heightened vulnerability to gambling harm, financial strain, and mental health problems. Although overall gambling participation has declined among young people in Finland, those aged 20–29 remain overrepresented among individuals experiencing at-risk or problem gambling.Methods: This study uses combined data from the nationally representative Finnish Gambling 2019 and 2023 surveys (2019: N = 3,994; 2023: N = 5,977) to examine gambling behavior among younger respondents. Latent class analysis (LCA) was conducted separately for all respondents and those under age 30 to identify subgroups based on patterns of gambling-type engagement.Results: Among participants under 30, a four-class solution emerged. ‘Mainstreamers’ (36.6%) typically played scratch cards, weekly lotteries, and electronic gaming machines (EGMs). ‘Young omnivores’ (21.5%) engaged in multiple product types and showed associations with at-risk/problem gambling (OR 6.49), hazardous alcohol use (OR 2.00), and a lower likelihood of being female (OR 0.05). ‘Midstreamers’ (22.0%) mainly played scratch cards and EGMs and showed no elevated risk indicators. ‘Moderate mixed’ (19.9%) engaged moderately in EGMs, offshore, and private gambling and were associated with hazardous alcohol use (OR 2.60).Conclusions: These findings demonstrate distinct gambling profiles among young adults and highlight the need for targeted prevention and intervention strategies
Alcohol · Distress · Mental health · Psychological distress · Substance use · Young adult · Gambling Behavior and Treatments · Impact of Technology on Adolescents · Substance Abuse Treatment and Outcomes
Statistical Power Analysis for the Behavioral Sciences
Maturation of the adolescent brain
Prevalence of Adolescent Problem Gambling
Adolescent Maturity and the Brain
Specification Tests for the Multinomial Logit Model
PoLCA
Understanding gambling related harm
Early risk and protective factors for problem gambling
The Audit Alcohol Consumption Questions (Audit-C) An Effective Brief Screening Test for Problem Drinking
The new life stage of emerging adulthood at ages 18–29 years
Gambling, Delinquency, and Drug Use During Adolescence
The influence of age on gambling problems worldwide
A brief report on dysregulation of positive emotions and impulsivity
The Prevalence of Problem Gambling Among U.S. Adolescents and Young Adults
Is adolescence a time of heightened risk taking? An overview of types of risk-taking behaviors across age groups
Wanna Bet? Investigating the Factors Related to Adolescent and Young Adult Gambling
Player Preferences and Social Harm
Beginning gambling
Using administrative register data for adjusting non-response bias in the finnish gambling harms survey
Factors contributing to psychological distress in the working population, with a special reference to gender difference
Way to Play
Influences on gambling during youth
Sports Betting Motivations Among Young Men
Performance of a Five-Item Mental Health Screening Test
Latent Class Modeling with Covariates
Latent Class Analysis
| Citation velocity | historical |
|---|---|
| Highly cited | No |