Domain9 items

Educator · Influence

Influence

Persuasive marketing, normative misperception, and group pressure that shape young men's sports betting habits.

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Why Influence matters

Decode the Hype

See how ads, social proof, influencers, and peer groups influence gambling attitudes.

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Units in this domain

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Unit · 5 items

Influence Unit

Five teacher-facing items covering ad scale, decoding ads, platform tactics, peer-pressure norms, and refusal scripts.

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  1. 01
    influence · 30m
    The Scale of Gambling Advertising

    Map the scale and reach of gambling advertising in the media young people use, and run a touchpoint audit that makes saturation visible before deconstruction skills land.

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  2. influence · 35m
    Decode the Hype: Reading Sports Betting Ads
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  3. influence · 30m
    Platform Tactics: Algorithms, Affiliates, and Tipsters
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  4. influence · 30m
    Peer Pressure Math: Norms vs Reality
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  5. influence · 30m
    Refusal and Reframing in the Group Chat
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5 items in this unit

Supporting materials

Handouts, references, and guides that pair with this unit.

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Research Source Library

Per-domain citation library covering every claim in the curriculum, with usage guidance for parent, admin, and media conversations. Names the gaps in the source base where they exist.

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Research citations

External academic sources that inform this domain.

  • Lopez-Gonzalez H, Estévez A, Griffiths MD (2018). Controlling the illusion of control: A grounded theory of sports betting advertising in the UK. International Gambling Studies, 18(1), 39–55.

    Grounded-theory analysis of 102 UK sports-betting ads. Operators systematically build narratives that reinforce illusion of control — e.g. live in-game odds, “insider” framing, and personalized props. Explains why sports betting feels like a skill game even though it isn’t.

    Open source

  • Neighbors C, Rodriguez LM, Rinker DV, et al. (2015). Personalized normative feedback for college student gambling: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 83(3), 500–511.

    RCT (n=252) showing PNF significantly reduced college gambling at 3- and 6-month follow-up. Establishes that students systematically overestimate peer gambling and that correcting that misperception changes behavior.

    Open source

  • NCAA (2023). National Study on Sports Wagering Among 18–22-Year-Olds. NCAA Research.

    58% of 18–22-year-olds have engaged in sports betting; 67% of on-campus college students bet, with mobile apps the dominant method. 6% reported losing $500+ in a single day.

    Open source

  • Celio MA, Lisman SA (2014). A personalized normative feedback intervention to reduce college student gambling. Journal of American College Health, 62(3), 154–164.

    RCT (n=136) confirming a single, stand-alone PNF intervention shifts both perceived norms and gambling behavior in college students.

    Open source

  • National Council on Problem Gambling (2024). NGAGE 3.0 — National Survey on Gambling Attitudes and Gambling Experiences.

    Betting weekly or more is identified as one of the strongest predictors of problem gambling. Parlay participation among US sports bettors nearly doubled from 17% (2018) to 30% (2024).

    Open source

  • Fairleigh Dickinson University Poll (Sept 2024). Online Sports Betting Among Young Men.

    Nationally representative poll: 26% of men under 30 bet on sports online in the past year; 10% met problem-gambling criteria — more than triple the 3% national rate.

    Open source

  • NCAA (Jan 2025). Sports Wagering Trends Among Student-Athletes — 5th National Study (n>20,000).

    22% of NCAA male athletes bet on sports in the past year; education programs show a measurable shift in behavior; harassment from bettors is widespread at Division I.

    Open source

  • American Gaming Association (May 2024). State of the States 2024 — The AGA Survey of the Commercial Casino Industry.

    Sports betting revenue grew 446.1% to $11.04B in 2023. State-by-state hold rates show parlays drive a disproportionate share of operator revenue (e.g. NJ 2024: parlays ~27% of wagers, ~72% of sportsbook revenue).

    Open source

  • Newall PWS (2025). Sludge, dark patterns and dark nudges: A taxonomy of online gambling platforms’ deceptive design features. Addiction.

    Three-part taxonomy of deceptive design in online gambling: “sludge” (frictions in withdrawal), “dark patterns” (deceptive UI like high suggested deposits), and “dark nudges” (framing that presents gambling as fun). The reference for naming structural design features in betting apps.

    Open source