Young men, gaming, and gambling | Research Library

Why young men are described as most at risk, whether that holds up, and how what happens to them reaches everyone else. Updated 2026-10-19.

29 checked findings · 12 measured on young men · 90 leads waiting to be checked

New here? How to read the library · how I check sources · start with the first entry.

Who’s at risk, and why

Among under-30s, 10% of men and 7% of women scored as problem gamblers; across all ages it was 3%

men 18-30: 10% · women under 30: 7% · all respondents: 3% (PGSI 8+)

Measured on young men Measured on: US registered voters; subgroups men 18-30 and women under 30 · 18+; subgroups 18-30 (men), under 30 (women) · USA

What the number is of: Share of each subgroup with PGSI 8+. Overall margin of error +/-3.5 pts; subgroup sizes not published (much wider)

Study type: Poll: live phone (520) and text-to-web (281), 17-20 Aug 2024, n = 801

Source: FDU Poll (2024). 'FDU Poll finds online betting leads to problems for young men.' Fairleigh Dickinson University, 19 Sept 2024 · Checked: press release, 2026-10-05

In young Australian men, more frequent sports betting predicted later problem gambling

OR = 1.63 [95% CI 1.22, 2.20] per one-step increase in frequency ('64% increased odds'; table shows 1.64)

Measured on young men Measured on: Young men in the Ten to Men longitudinal cohort; n = 265 (n = 215 controlling for prior severity) · 18-25 · Australia

What the number is of: Odds of a higher PGSI risk category per one-step rise on a 5-point frequency scale (never / 1-2 a year / few a year / 1-3 a month / weekly+)

Study type: Longitudinal cohort; predictors at Wave 3 (Jul 2020 - Feb 2021), PGSI outcome at Wave 4 (Aug - Dec 2022); ordinal logistic regression

Source: Mancini, Brett, Heirene, Fisher, Nevill & Mitrou (2025). Predicting problem gambling in young men: the impact of sports gambling frequency and internalizing symptoms. J. Gambling Studies 41(3), 1119-1144 · Checked: full text, 2026-10-05

In the same young men, higher anxiety went with LOWER odds of later problem gambling; higher depression with slightly higher odds

Final model (Table 5, step 5): anxiety OR = 0.89 [0.79, 0.99] per point, p = .032 (11% lower odds); depression OR = 1.18 [1.07, 1.30], p = .001 (18% higher). Controlling for prior severity (Table 6): anxiety 0.88 [0.77, 1.00]; depression 1.19 [1.06, 1.35].

Measured on young men Measured on: Same as previous row (Ten to Men, n = 265) · 18-25 · Australia

What the number is of: Odds of higher PGSI risk category per one-point rise in anxiety / depression score

Study type: Same longitudinal model

Among young Swiss men aged 18-24 who had gambled in the past year, 4.4% scored as problem gamblers; that is 2.1% of all the young men surveyed

PGSI 8+: 4.4% of past-year gamblers (n = 1,177); 2.1% of total sample (N = 2,349); moderate-risk (PGSI 3-7) 16.5% of gamblers; 49.8% (n = 1,177) gambled in past 12 months. No CIs reported.

Measured on young men Measured on: Swiss Army conscripts at the mandatory recruitment programme, French-speaking region; all male; n = 2,349 analysed (98.2% response) · 18-24 (mean 20.6) · Switzerland

What the number is of: PGSI 8+ as a share of past-year gamblers (4.4%) and of the whole sample (2.1%)

Study type: Cross-sectional survey, Aug 2023 - Jan 2024, replicating a 2019 survey of the same population; weighted to Swiss age statistics

Source: Tomei, A., Bieri, M., Porchet, C. & Simon, O. (2026). Gambling progression in young adults following online casino-gambling legalization in Switzerland. J. Gambling Studies 42(1):249-263. doi 10.1007/s10899-025-10435-6 · Checked: full text, 2026-10-15

After Switzerland legalised online casinos, problem gambling among young male conscripts who gambled rose slightly from 3.6% (2019) to 4.4% (2023/24), a change the authors call non-significant

3.6% (2019) vs 4.4% (2023/24) of past-year gamblers, PGSI 8+; no test statistic or p-value reported

Measured on young men Measured on: Same as N-088; 2019 comparison from Tomei et al. 2022 · 18-24 in 2023/24; the 2019 survey did not include 23-24-year-olds · Switzerland

What the number is of: Share of past-year gamblers scoring PGSI 8+ in each year

Study type: Two cross-sectional surveys of the same recruitment population, 2019 and 2023/24

In a representative sample of young Swiss men in their late twenties, 28.5% had gambled in the past year and 0.8% met the criteria for gambling disorder (2.7% of those who gambled)

Past-year gambling 28.5% (1,526/5,352); DSM-5 GD 4+ criteria: 0.8% of all (41), 2.7% of gamblers

Measured on young men Measured on: C-SURF cohort, young Swiss men enrolled at army recruitment centres (Lausanne, Windisch, Mels); n = 5,352 · mean 28.3 (SD 1.3) · Switzerland

What the number is of: Share of all respondents (0.8%) and of past-year gamblers (2.7%) meeting 4+ of 9 DSM-5 criteria

Study type: Cross-sectional analysis of cohort wave 4, Apr 2019 - Nov 2020

Source: Marmet, S., Studer, J., Wicki, M., Khazaal, Y. & Gmel, G. (2021). Online gambling's associations with gambling disorder and related problems in a representative sample of young Swiss men. Frontiers in Psychiatry 12:703118. doi 10.3389/fpsyt.2021.703118 · Checked: full text, 2026-10-10

Among young Swiss men who gambled, those who mixed online and offline gambling had the most gambling-disorder symptoms, even after accounting for time and money spent

GD criteria vs offline-only: 26-50% online IRR 11.46 [7.67, 17.11] unadjusted; 6.74 [4.39, 10.35] adjusted for time and money gambled

Measured on young men Measured on: Past-year gamblers in the C-SURF sample (n = 1,526) · mean 28.3 · Switzerland

What the number is of: Rate ratio of GD criteria count by share of gambling money spent online, vs offline-only

Study type: Cross-sectional; negative binomial count models

In a Canadian national survey of 15-24-year-olds, 3.3% of young men and 1.1% of young women were moderate-risk or problem gamblers

CPGI moderate-risk or problem: male 3.30%, female 1.10%, all 2.22%; 61.35% gambled in past 12 months

Measured on young men Measured on: Canadian youth in the Canadian Community Health Survey: Mental Health and Well-Being; n = 5,666 · 15-24 · Canada

What the number is of: Share of all youth aged 15-24 scoring moderate-risk or problem on the CPGI (cut-offs not stated on the record)

Study type: National population survey, weighted, bootstrap variance; survey cycle/year not stated on the record (paper published 2007)

Source: Huang, J.-H. & Boyer, R. (2007). Epidemiology of youth gambling problems in Canada: a national prevalence study. Canadian Journal of Psychiatry 52(10):657-665 · Checked: abstract-level (CRDCN record), 2026-10-15

In Sweden, young men aged 16-24 developed a first episode of problem gambling about three times as often as young women, and young people more often than 25-44s

12-month incidence of first episode: males 16-24 3.32% (2.19-5.01), females 16-24 1.14% (0.42-3.07), all 16-24 2.26% (1.52-3.36), 25-44 0.81% (0.41-1.56)

Measured on young men Measured on: Swedish Longitudinal Gambling Study (Swelogs), people with no history of problem gambling at baseline; 4,358 selected aged 16-44 · 16-24 vs 25-44 · Sweden

What the number is of: Incidence proportion of a first episode of problem gambling (PGSI) in the 12 months before follow-up, among those without a prior history

Study type: Prospective population cohort, waves 2008/09 and 2009/10

Source: Froberg, F., Rosendahl, I.K., Abbott, M., Romild, U., Tengstrom, A. & Hallqvist, J. (2015). The incidence of problem gambling in a representative cohort of Swedish female and male 16-24 year-olds, in comparison with 25-44 year-olds. J. Gambling Studies 31(3). doi 10.1007/s10899-014-9450-9 · Checked: abstract, 2026-10-15

Among young men who bet on sports in Ontario and Alberta, 77% saw betting ads every week and 54% saw live-odds ads every week

77% see sports betting ads weekly; 54% see live odds weekly

Measured on young men Measured on: Men under 30 within a survey of 1,800+ Ontario and Alberta residents who bet on sports in the past 3 months; subgroup n not reported (they are "1 in 5" of the sample) · under 30 · Canada (Ontario, Alberta)

What the number is of: Share of young male sports bettors (past 3 months), not all young men

Study type: Cross-sectional survey; sampling method and dates not reported; not peer-reviewed (fact sheet)

Source: Kim, A. (H.) et al. (TMU, with University of Bristol, Brock University, UMass Amherst, University of Calgary; Greo Evidence Insights). Sports Betting Harm in Young Men: The Impact of Advertising (fact sheet). April 2026 · Checked: full text (fact sheet), 2026-10-18

60% of those young male sports bettors said betting ads influence their betting, and 60% said responsible-gambling ads had not helped them cut down

60% say ads influence their betting; 60% say responsible gambling ads did NOT help reduce betting

What the number is of: Share of young male sports bettors answering each self-report item

Study type: Cross-sectional survey; question wording not reported

Legalising online sports betting in US states raised how often young men who already binge drink do so, by about 10%

~10% increase in binge-drinking frequency at the INTENSIVE margin among young men aged 35 and under; ATT of 0.46 additional binge days. No discernible effect on smoking. BRFSS samples run to 1.1-3.2 million observations depending on outcome.

Measured on young men Measured on: US adults in the Behavioral Risk Factor Surveillance System; young-men subsample aged 35 and under · 35 and under · USA

What the number is of: Binge-drinking FREQUENCY among men who already report binge drinking (intensive margin). It does not show that men who did not binge drink started.

Study type: Difference-in-differences on the staggered state rollout of sports betting laws, with staggered-adoption DID estimators as a robustness check

Source: Dasgupta, K. & Ghimire, K. (2026). Gambling and Substance Use: Early Evidence From Sports Betting Laws. Health Economics Letters. doi 10.1002/hec.70088 · Checked: full text, 2026-10-18

Problem-gambling severity is higher among men and among 18–24s — reported separately

All adults 2.4% (95% CI 1.9–2.8) · of past-12-month gamblers: all 4.0%, men 5.3%, women 2.7%, 18–24s 10.4%

Partly: young or male, not both Measured on: General population; breakdowns are of people who gambled in the past 12 months · 18+; band quoted 18–24 · Great Britain

What the number is of: Of past-12-month gamblers (only 2.4% is of all adults). Sex x age cell NOT published in report text

Study type: Push-to-web official statistics survey, ~20,000 adults, 4 quarterly waves, Jan 2025 – Jan 2026

Source: Gambling Commission. Gambling Survey for Great Britain, Annual Report 2025 (Official Statistics) · Checked: PGSI chapter + full print rendering, agreeing, 2026-09-21

Boys whose friends mostly or all gamble are far more likely to gamble themselves

friends mostly/all gamble: 84% gamble (n = 58) · a few/some friends gamble: 71% (n = 275) · no gambling friends: 17% (n = 338)

Partly: young or male, not both Measured on: US boys · 11-17 · USA

What the number is of: Share who gambled in the past year within each peer band. The 84% is of the 58 boys whose friends MOSTLY OR ALL gamble - not of all boys with any gambling friends

Study type: Cross-sectional online survey of 1,017 US boys 11-17, fielded 9-14 July 2025 by SSRS; weighted; sampling error +/-4.2 pts overall, far wider on the n=58 subgroup

Source: Common Sense Media (2026). Betting on Boys: Understanding Gambling Among Adolescent Boys · Checked: full report PDF, 2026-10-12

Worldwide, men were 3.4 times more likely than women to have a gambling problem, and younger adults 1.51 times more likely than middle-aged adults, reported separately

men vs women 3.4x · young (18-35) vs middle (30-55) 1.51x · older (45-65) 0.80x · global PG prevalence 1.9% (Europe 1.3%, North America 5.3%)

Partly: young or male, not both Measured on: Problem-gambling prevalence samples in 21 studies; 156,249 participants (47.6% male) · Grouped 18-35 / 30-55 / 45-65 (overlapping) · 18 countries (Europe 52%, Asia 19%, Oceania 19%, North America 10%)

What the number is of: Ratio of problem-gambling prevalence: men vs women (all ages); young vs middle-aged (both sexes)

Study type: Systematic review and random-effects meta-analysis

Source: Dellosa & Browne (2024). The influence of age on gambling problems worldwide: a systematic review and meta-analysis of risk among younger, middle-aged, and older adults. J. Behavioral Addictions · Checked: abstract, 2026-10-19

In Great Britain, which age group looks most at risk depends on who you count: across all adults the highest problem-gambling rate was among 25-34s, but among people who gambled it was 18-24s

PGSI 8+, 2023. ALL ADULTS (base 9,633): 25-34 highest at 5.2%, declining to 0.2% at 75+. PAST-YEAR GAMBLERS (base 5,790): 18-24 9.1%, 25-34 8.4%, 35-44 4.8%, 45-54 3.7%, 55-64 0.8%, 65-74 1.4%, 75+ 0.4%. Men 3.3% vs women 1.8% (all adults).

Partly: young or male, not both Measured on: Adults 18+ in Great Britain; 9,633 participants (5,790 past-year gamblers), unweighted · 18+, in 10-year bands from 18-24 · Great Britain

What the number is of: Share scoring PGSI 8+ among all adults vs among past-12-month gamblers; sex and age reported separately, no sex x age figure in the text

Study type: Official statistics survey (GSGB), 2023 annual report

Source: Gambling Commission (2024). Gambling Survey for Great Britain: annual report 2023 (official statistics), section 'Problem Gambling Severity Index'. Published 25 July 2024 · Checked: full section text plus Figure 16 chart values (web report), 2026-10-15

In Australia, the share of men who bet on sports rose from 5.9% to 9.3% between 2015 and 2022, and rose fastest among men aged 18-44

Men: 5.9% (2015) -> 9.3% (2022), a 57.6% relative rise (about 3.4 percentage points); men 18-44: rise of 62-66% (relative; underlying percentages not given)

Partly: young or male, not both Measured on: Australians in the HILDA household panel (~17,000 followed yearly); analysis sample size not reported · All adult men; band 18-44 reported as a range · Australia

What the number is of: Share of all men who bet on sports in each year

Study type: National household panel survey; gambling module 2015, 2018, 2022; author analysis

Source: Botha, F. (2025-03-12). The rate of sports betting has surged more than 57%, and younger people are betting more. The Conversation. doi 10.64628/AA.hh3ywmsqr (author's analysis of HILDA 2015, 2018, 2022) · Checked: full text (author's article), 2026-10-18

Gambling problems predict later loneliness; loneliness does not predict later gambling problems (within-person)

problems→loneliness β = 0.069, p = .007 · loneliness→problems β = 0.001, p = .971 · escape→problems β = 0.077, p = .047

Measured on: General-population adults who gambled at least monthly, not problem gamblers; Norstat panel; 54.58% male · 18–75; mean 51.85 (SD 13.97); younger participants lost to attrition · Finland

What the number is of: Within-person standardized paths; analytic n = 612 of 1,530 at T1

Study type: Longitudinal RI-CLPM, 5 waves, Apr 2021 – May 2023

Source: Hagfors, Kaakinen, Savolainen, Vepsäläinen & Oksanen (2025). Lonely gamble. J. Behavioral Addictions 14(2), 972-981 · Checked: full text (PMC), 2026-09-21

Loot boxes are rare among games but near-universal in exposure: the few titles carrying them are the ones everyone plays

16.2% of games (75 of 463) · 71.2% of players playing a game with them (week of 16–22 Apr 2019)

Measured on: Concurrent players of the 463 most-played Steam games · Not reported (platform counts) · Global Steam

What the number is of: 71.2% = share of players; 16.2% = share of games

Study type: Longitudinal observational, 3,319 days, Mar 2010 – Apr 2019

Source: Zendle, Meyer & Ballou (2020). The changing face of desktop video game monetisation. PLOS ONE 15(5) e0232780 · Checked: full text (PMC + publisher), 2026-09-10

In the largest meta-analysis of gambling prevalence, 2.8% of adult men who gambled were problem gamblers against 1.2% of adult women, with sex and age reported separately and never combined

Adults who gambled in the past 12 months: any-risk 14.2% (9.6-19.7), women 10.9% (9.5-12.6), men 17.9% (16.2-19.9); problematic 2.8% (1.9-3.9), women 1.2% (0.8-1.7), men 2.8% (2.2-3.6). Adolescents, problematic by sex (k=8, ranges not pooled): boys 4.7-14.5%, girls 0.5-4.9%. Whole-population adults: 46.2% gambled, 8.7% any-risk, 1.41% problematic.

Measured on: Adults and adolescents in 366 representative samples across 68 countries; mean age 29.7 · adults vs adolescents only · 68 countries and territories

What the number is of: The 2.8% / 1.2% are CONDITIONAL on having gambled in the past 12 months, not shares of the whole population

Study type: Systematic review and meta-analysis of representative survey studies; random-effects meta-regressions

Source: Tran, L.T., Wardle, H., Colledge-Frisby, S., Taylor, S., Lynch, M., Rehm, J., Volberg, R., Marionneau, V., Saxena, S., Bunn, C., Farrell, M. & Degenhardt, L. (2024). The prevalence of gambling and problematic gambling: a systematic review and meta-analysis. The Lancet Public Health 9(8), e594-e613 · Checked: full text, 2026-10-15

Across two decades of studies, more exposure to gambling advertising went with more gambling behaviour, a weaker link with intentions, and an uncertain one with attitudes; almost every study was a snapshot, so cause is unproven

Pooled mean r: behaviour .24 (range -.08 to .68, ~23 studies); intentions .05 (small, significant); attitudes .40 (2 studies, 95% CI -.17 to .77)

Measured on: Mixed: adults and adolescents in the included studies; Australia, Canada, US, UK, Germany, Norway and others · Mixed (adolescents to adults) · Multiple

What the number is of: Correlation between ad exposure and each outcome

Study type: Critical and meta-analytic review of studies since 1999; random-effects models; almost all included studies cross-sectional

Source: Bouguettaya, A., Lynott, D., Carter, A., Zerhouni, O., Meyer, S., Ladegaard, I., Gardner, J. & O'Brien, K.S. (2020). The relationship between gambling advertising and gambling attitudes, intentions and behaviours: a critical and meta-analytic review. Current Opinion in Behavioral Sciences 31:89-101. doi 10.1016/j.cobeha.2020.02.010 · Checked: full text (author manuscript), 2026-10-18

An umbrella review of 8 systematic reviews covering 74 studies concluded the evidence consistently supports a causal relationship between gambling advertising exposure and gambling, with a dose-response effect and more evidence of impact on children and young people

8 systematic reviews; 74 unique primary studies

Measured on: Whatever the 74 underlying studies sampled; not a young-men review · includes children and young people · multiple

What the number is of: n/a - a synthesis, not a prevalence estimate

Study type: Systematic umbrella review; included reviews assessed with AMSTAR 2

Source: McGrane, E., Wardle, H., Clowes, M., Blank, L., Pryce, R., Field, M., Sharpe, C. & Goyder, C. (2023). What is the evidence that advertising policies could have an impact on gambling-related harms? A systematic umbrella review of the literature. Public Health 215, 124-130 · Checked: abstract, 2026-10-19

Television advertising during live World Cup broadcasts influenced how often people bet and whether they bet at all, in a higher-risk group

no effect sizes read from the abstract

Measured on: Self-reported gambling data, higher-risk population group · not stated in abstract · United Kingdom

What the number is of: Frequency of bets placed and probability of placing a bet

Study type: Quasi-experiment during the 2022 football World Cup; linear, count, propensity-score and inverse-probability-weighted matching models

Source: McGrane, E. (2025). What is the impact of restrictions on television gambling advertising during live sport? An investigation using quasi-experimental and econometric methods. PhD thesis, University of Sheffield · Checked: abstract, 2026-10-19

The people around them

About 4.7 people are affected for every person with problem gambling, once double-counting across shared families and friends is corrected; the widely cited 'six others' overstates it at population level

~4.7 affected others per person with problem gambling · low- and moderate-risk gamblers = 70% of harm 'vectors' · nearly 1 in 4 affected others are themselves at-risk gamblers

Measured on: Not reported in abstract: a reconciliation of published reports from gamblers and affected others · Not reported · Not reported in abstract

What the number is of: Affected people per person with problem gambling, population level

Study type: Network model reconciling gambler and affected-other reports, with clustering correction

Source: Browne, Tulloch & Woodbright (2026). From 'Six Others' to Edge Conservation: a network reconciliation of gambling harm to others. J. Gambling Studies. doi 10.1007/s10899-026-10521-3 · Checked: abstract, 2026-10-05

The wider system

Legalising sports betting was followed by more bankruptcies, slightly lower credit scores and more debt collections

July 2024 version: average credit score in legalising states down ~0.3%; in online-access states bankruptcy filing up 'roughly 28%', elsewhere stated as 25-30% vs pre-treatment. The bankruptcy ATT is 0.03 PERCENTAGE POINTS, so the 25-30% is relative to a very small base.

Partly: young or male, not both Measured on: US consumers in the University of California Consumer Credit Panel · all adults; subgroups include men under 45 by county income · USA

What the number is of: Changes in consumer credit outcomes, not gambling behaviour. The bankruptcy figure is a relative increase on a 0.03pp absolute effect

Study type: Difference-in-differences on the staggered state rollout of legal sports betting after the 2018 Supreme Court ruling; 38 states at the time of this version

Source: Hollenbeck, Larsen & Proserpio (2024). The Financial Consequences of Legalized Sports Gambling. SSRN 4903302; American Institute for Boys and Men (2025). How sports betting can harm young men · Checked: full text (July 2024 version), 2026-10-18

The UK whistle-to-whistle ban cut gambling advertising around live football but was associated with an increase in advertising around live horse racing, which the restriction does not cover

no effect sizes read from the abstract

Measured on: UK television advertising and scheduling data · United Kingdom

What the number is of: Presence of advertising on television, not gambling behaviour

Study type: Quasi-experimental and econometric analysis of advertising and scheduling data

What helps

Most treatment-seeking patients who self-excluded on Sweden's national register gambled anyway

41 of 60 (68%) · of those, unlicensed sites 68% (28/41) · borrowed identity or land-based venues 22%

Measured on: Treatment-seeking patients at one regional gambling-disorder unit (Region Skåne, Malmö); 76% men · Adults 18+; not reported · Sweden

What the number is of: 41 of the 60 patients who had self-excluded (60 = 81% of 74 with data)

Study type: Retrospective chart review, Jan–Sep 2021

Source: Spelpaus self-exclusion breach study (Region Skåne). 85 included / 74 complete · Checked: full text, 2026-08-31

In GambleAware's tracking of its 'Bet Regret' campaign aimed at younger male sports bettors, 38% of the audience said they try to 'tap out' of their betting app before placing a bet

Tap out before betting: 38% of campaign audience; 53% of higher-risk bettors intending to cut down; 17% actively use tapping out to cut down; campaign recognition averaged 60% (75% in highest-risk band)

Measured on: The campaign's target audience in an Ipsos MORI tracking study (younger male sports bettors, per the campaign aim); sample size and ages not stated in this document · not reported in this document · Great Britain

What the number is of: Share of the tracked campaign audience reporting each behaviour

Study type: Repeated tracking survey; self-report; no baseline or comparison group reported

Source: GambleAware (2021-06-04). GambleAware publishes Safer Gambling Campaign Bet Regret summary (announcement PDF) · Checked: full text (announcement PDF), 2026-10-18

Why we check

Britain's national gambling survey reaches young men poorly: 4% of responding males were aged 18-24, against 11% of the male adult population

Unweighted, 2023 annual report: males 18-24 were 4% of responding males vs 11% of the GB male adult population; females 18-24 were 7% of responding females vs 10%. Address-level response rate 19% (target 22%). Across six published waves the male figure runs 4-6% vs 11%.

Partly: young or male, not both Measured on: Adults 18+ in Great Britain responding to the GSGB; unweighted sample composition · 18-24 vs all adults · Great Britain

What the number is of: Share of RESPONDENTS of each sex who were 18-24, against that group's share of the population

Study type: Official statistics survey, push-to-web; unweighted sample profile against population benchmarks

Source: Gambling Commission (2024). Gambling Survey for Great Britain: annual report 2023, Response to the survey · Checked: full section text (web report), 2026-10-15

Numbers that don’t hold up

Figures that circulate in AI search summaries and shared posts, traced back as far as we could.

“Young men 18-30: 10% problem gambling vs 3% of the general population”
The numbers come from a real 2024 US poll, but the comparison is wrong. The 3% is everyone, all ages. Among under-30s it was 10% of men and 7% of women.
“Young men are 3.4 times more likely than women to gamble at a problem level”
Real, but about men and women of all ages, from a 2024 meta-analysis of 21 studies. It reports younger adults separately and never measures young men as a group, and the gap narrows in North America.
“Young men at risk are twice as likely to have anxiety and 2.5 times as likely to have depression”
We couldn't find a source for these figures. The one study we found that followed young men over time saw higher anxiety go with lower odds of later problem gambling, and depression with slightly higher odds.
“The highest-risk period is ages 16 to 22”
No research source found. It appears on a treatment provider's web page with no citation.
“84% of boys who gamble report that their friends also gamble”
Turned around, and narrower than it sounds. The survey found that among boys whose friends mostly or all gamble, 84% gamble themselves, against 17% of boys with no gambling friends. That 84% rests on 58 boys out of 1,017.
“An average of 5 to 10 people are negatively affected by each compulsive gambler”
The research version is the widely cited 'six others'. A 2026 analysis that corrects for the same people being counted twice puts it nearer 4.7, with the harm concentrated in families.
“Many young men use gambling as a way to escape or numb underlying anxiety or depression”
Half right at best. In the one study we found that followed young men over time, higher anxiety went with lower odds of later problem gambling; depression went with higher odds.
“Many young men view gambling as the only viable shortcut to financial mobility when savings and career paths feel out of reach”
Presented as a finding, but the only thing behind it is a YouTube video. It may well be true; nobody has shown it.
“In a Canadian national survey of 15-24-year-olds, 3.3% of young men and 1.1% of young women were moderate-risk or problem gamblers”
This figure is real, but it comes from a Canadian survey published in 2007 and is often quoted without its date.
“77% of young men are exposed to betting advertisements on a weekly basis”
Right number, wrong population: the 77% is of young men who already bet on sports, not of all young men.

What we’re checking next

One question a week, in this order. Each answered question becomes a journal entry with its sources.

Are young men actually most at risk? What does the data show when sex and age are measured together? (answered 2026-10-10 · raw/coaching/research/briefs/2026-10-10-Q1-are-young-men-most-at-risk.md)
What pulls them in, and why now? The phone, always-on apps, sports-betting ads (the games get their own block, Q8–Q11) (answered 2026-10-18 · raw/coaching/research/briefs/2026-10-17-Q2-what-pulls-them-in.md)
Do loot boxes lead to gambling, or just travel with it? The gaming–gambling bridge: does paying for random rewards cause later gambling, or do the same people do both? (open)
Skins, esports and in-game betting: how does playing turn into wagering? Tradable items, skin gambling sites, betting on matches (open)
What does watching gambling do? Streamers gambling on stream, casino content on gaming platforms, betting influencers (open)
Are free 'social casino' games a rehearsal for the real thing? Play-money slots and poker inside games and apps (open)
Do young men gamble because other routes to financial mobility feel closed? Precarity, side-hustle culture, betting and trading as the 'only shortcut' (open)
Does "handle it yourself" keep it hidden? Masculine norms and help-seeking (open)
Loneliness first, or gambling first, in young people? (open)
What does someone who bets or trades with limits actually do differently, and what does it protect? (open)
Who else gets hurt, and how? Partners, parents, children, friends (open)
What does being open about it do for trust? (open)
What does it cost beyond the household? Work, debt, crime, health services, public spending (open)
Which safeguards actually work? Deposit and loss limits, self-exclusion, cooling-off tools (open)

If gambling is costing you or someone close to you more than it should, the US National Problem Gambling Helpline is free and confidential: call or text 1-800-MY-RESET (1-800-697-3738), or chat at ncpgambling.org.