The Hooked in 2025 survey by Casinos Blockchain offers a window into the realities of modern digital and behavioral addictions.

Drawing on quantitative responses from 1000 participants – primarily U.S. adults – this research explores platform-specific usage, spending habits, demographic risks, psychological “hooks,” and the evolving impact on health and industry.

The findings paint a picture of a society deeply intertwined with screens and habit-forming technologies, with distinct patterns by age, platform, and lifestyle.

The most addictive platforms: where attention flows

YouTube stands out as the most habit-forming platform in 2025, according to user engagement metrics. Nearly every respondent (95%) used YouTube, with almost one in five reporting daily usage of 5+ hours. About a third checked the platform more than ten times a day—numbers unmatched by any other service. One 45–54-year-old female participant described using YouTube “10+ times daily” for over five hours, the survey’s most extreme single-platform use.

Facebook and Instagram follow closely, with 80%+ usage rates and 12–14% of users spending over five hours daily—typically in many brief sessions. Facebook slightly edged out Instagram for frequency, but Instagram saw similar total engagement hours, especially among younger users.

TikTok’s grip is strong: about three-quarters use the platform, with nearly 20% opening it more than 10 times daily, and over 10% exceeding 5 hours of daily use. One 25–34-year-old male described “5+ hours” each on both TikTok and YouTube, underscoring a reality where users cycle between multiple high-engagement platforms.

Other services such as Twitter (now X), online gaming, gambling, and 18+ content platforms showed lower intensity but notable frequency for some. For example, 14% played online games 10+ times a day (often brief sessions), and 11% of gamblers checked betting sites 10+ times daily. Overall, video and social media apps dominate both frequency and total time spent, revealing their unrivaled potential for habit formation.

Most addictive behavior types

When comparing broad categories, social media clearly leads in addictive engagement.

Participants spend far more time on social networking apps than on gaming or gambling. In fact, many respondents use multiple social media apps, resulting in an average of ~7.5 hours per day combined on social platforms – vs roughly 1–1.5 hours on gaming or gambling activities.

The typical participant reported checking some form of social media about 20 times per day (median ~18–19 total social app opens) – far higher than the ~3 daily sessions for games or ~2 for gambling.

Younger users especially might cycle through TikTok, Instagram, YouTube, etc., contributing to this high combined screen time.

Looking at self-reported addictiveness: 83% of respondents selected “social media” as an addictive habit they engage in, compared to about 61% for gaming and only 29% for online gambling.

This suggests that social media is not only more widely used but also more widely perceived as habit-forming. The data on time spent reinforces this – a large share spend multiple hours scrolling feeds or watching videos daily, whereas relatively few spend that much time playing video games or placing bets online.

It’s worth noting that gaming can be very engaging for a subset (some gamers do play for many hours straight), but in aggregate, gaming sessions were less frequent and shorter per day than social media sessions.

Gambling showed the lowest daily engagement on average; however, those who do gamble often exhibit compulsive patterns (e.g. checking betting apps frequently in short bursts).

User money spending patterns: where the Most Money Flows

Survey data on self-reported spending indicates that users spend the most money on online subscriptions and gambling, as well as on alcohol, compared to other habit categories. When asked about monthly spending on various items, a majority of respondents reported keeping expenditures low (under $30) in most categories, but there were notable exceptions:

• Subscription services (e.g. streaming, fan platforms): This category saw the highest average spend. Many people subscribe to multiple services – about 54% spent at least $30/month on subscriptions, and ~16% spent over $50. This suggests that streaming platforms, premium content (and services like OnlyFans) are significant recurring expenses for a good portion of users.
• Online gambling: While most (70%) spend under $30 on gambling monthly, a sizable minority spends heavily. About 17% of respondents spent over $50 per month on gambling (including ~7% spending “More than $100” monthly). This indicates that the gambling industry gains substantial revenue from a smaller group of high-spending users.
• Alcohol: Real-life substance use also showed up in spending. Around 15% reported spending above $50 per month on alcohol. The majority (65%+) kept alcohol spending under $30, but the presence of some high spenders highlights that alcohol sales take a financial toll for a segment of users similar to gambling.
• Video games: Spending on PC games was moderate, with only ~6% spending over $50 monthly. Mobile game purchases were even lower – nearly 90% spent less than $30 on mobile games, and only ~3% exceeded $50. Despite the stereotype of costly microtransactions, most mobile gamers in this survey did not spend much money (perhaps playing free-to-play without buying extras).
• Social apps: Direct spending on social media apps was minimal – only ~3% spent beyond $50. This implies that aside from indirect costs (time/attention or data), social networks aren’t extracting large direct payments from most users in this sample. Their monetization is likely via ads rather than user purchases.

Subscription content and gambling are the areas where users tend to pour the most money, with alcohol not far behind. These industries benefit financially from user habits: nearly one in six users is a high-spender on streaming or betting. By contrast, gaming and social media see relatively low direct spending per user (though gaming companies may profit through a smaller number of whales, and social platforms via advertising).

Addiction by age group

Younger adults reported the highest digital addiction levels, while middle-aged groups showed more gambling/alcohol involvement. Breaking down responses by age:

• 18–24 year olds (Gen Z): This youngest group logs enormous screen time. They averaged around 7–8 hours of social media per day, with some even higher (median ~5.5 hours) – reflecting constant mobile engagement. Tellingly, over 70% of 18–24s said they have felt addicted to a digital activity. They also had the highest rate of seeking help (more on that below). However, they reported relatively low involvement with alcohol or gambling – only ~12.5% checked “Alcohol” as an addiction category, and 25% checked “Online gambling,” which is lower than older groups. This suggests digital platforms are the primary habit loop for the youngest cohort, more so than substances.
• 25–34 year olds: This group also had extremely high screen time – in fact the highest combined social media use (~10 hours/day on average across platforms). Over half (56%) felt addicted digitally. They balanced digital and real-world vices: about one-third flagged gambling or alcohol as issues. Their gambling participation was higher than Gen Z (53% use online gambling sites), and ~34% acknowledged gambling as an addictive habit【29†】. This group may be at a life stage of peak digital engagement (multiple apps, work and personal screen use), but some are also engaging in gambling and drinking at notable rates.
• 35–44 year olds: Interestingly, the 35–44 group showed the highest incidence of gambling and alcohol addiction reports. About 42% selected “Online gambling” and a similar 42% “alcohol” as habits of concern– the highest of any age segment for those categories. Many in this group likely have more disposable income for betting or drinking, and perhaps higher stress levels, leading to those behaviors. Their digital use remained high (7+ hours social media daily on average), but only ~38% felt addicted to digital platforms – significantly less than the younger groups. This could be due to greater awareness or simply different self-perception, but it suggests that mid-life respondents see gambling and alcohol as equal or greater concerns than Facebook or TikTok.
• 45–54 year olds: The oldest group in the survey had the lowest digital usage and addiction feelings. They averaged ~6 hours on social media (still substantial), and only ~28% felt addicted to digital tech. They were also the least likely to use online gambling sites (only ~47% did) and very few (14%) identified gambling as an issue. About 30% noted alcohol as a habit. Overall, this group’s risk profile skewed lower for digital addiction and slightly lower for gambling, though a portion still reported struggles with alcohol.

Younger respondents (teens and 20s) are heavily at risk of digital addictions (huge screen times and self-acknowledged dependency), whereas 30s–40s respondents show more multi-faceted addictions – mixing digital habits with gambling and alcohol. The oldest adults 45+ in this sample were comparatively less impacted on all fronts (possibly due to more balanced use or cohort effects). These age trends highlight how digital-native generations are experiencing addiction differently: the youngest are “hooked” mainly on screens, while those in their 30s and 40s juggle both online and traditional addictions.

Habit-forming platform features (what hooks users)

Survey respondents gave insight into why certain apps are so habit-forming – pointing to specific features and “hooks” that create strong habit loops. The most cited engagement drivers were:

• Rewards and bonuses: Gamified reward systems were the top factor, cited by 57% of respondents as keeping them hooked. This includes things like points, virtual rewards, winning streaks, or bonus content. Many users – even those referring to social media – relate to the idea of reward mechanisms (for example, the dopamine hit of a “like” or upvote can function as a reward). One respondent explicitly noted “Rewards or bonuses” as a feature that drew them in, alongside frequent notifications.
• Notifications: The second most common hook (about 48% selecting it) was push notifications. Constant alerts from apps prompt users to return even when they didn’t plan to. This spans across platforms: social apps notify about tags or messages, games about missions or sales, gambling apps about new odds or outcomes. It creates a loop of reactive checking. Several participants who “almost always” lose track of time indicated that relentless notifications pull them back in repeatedly.
• Personalised content feeds: Around one-third (32%) highlighted personalised content – algorithmic feeds and recommendations – as a factor in their habit loop. Infinite scrolling feeds on TikTok, Instagram, or YouTube (the “For You” page, tailored video suggestions, etc.) are designed to serve each user’s interests, making it hard to put down. This was reflected in responses: for instance, a user might blame “personalized content” for often spending too long on an app. It’s the classic “rabbit hole” effect – the app knows what you like and keeps showing more.
• Live updates and real-time interaction: About 26% cited live updates (e.g. constantly refreshing news feeds, live game scores, stock prices, or social news) as a hook. The fear of missing out on something happening right now can compel frequent checking. This factor is particularly relevant to Twitter (fast news), sports betting (odds updates), and real-time games.
• Social pressure and competition: A smaller portion noted social pressure (10%) and leaderboards or rankings (8%) as drivers. These mechanics are common in fitness apps, games, or even social streaks (Snapchat streaks, for example). A competitive leaderboard or the pressure to respond to friends can create a sense of obligation that keeps users coming back daily, though these were less universally cited than the reward/notification loop.

Notably, only a few (about 10%) said “None of the above” – implying most people do recognize some designed hook that gets them. In summary, apps that combine frequent rewards, push notifications, and AI-tailored content have the strongest habit loops.

A platform like TikTok, for instance, hits all three: endless personalized videos (content), intermittent likes/comments (rewards), and frequent alerts.

Games and gambling apps leverage rewards and leaderboards, while social networks lean on notifications and personalized feeds. The survey data confirms that these elements are very effective at capturing user attention (often against the user’s own intentions).

Mental health treatment costs and help-seeking

Despite high addiction rates, only about 19% of all respondents have sought online help for digital overuse. Gen Z leads the way (33% of 18–24s have searched for support), followed by Millennials (22%), those aged 35–44 (19%), and just 9% of 45–54s.

There is broad willingness to use free therapy/support apps, but regular usage of screen-time tools is still limited.

Younger users are more aware and proactive, but a gap remains in resources and uptake, especially among older demographics.

Business profits from addiction

The profits generated from addictive behaviors are staggering. Tech companies dominate, with Meta (Facebook/Instagram) projected to generate $180 billion in 2025, YouTube $39B, and TikTok $27B. Gambling is a $110B+ industry, and global alcohol sales top $1.7–2.1 trillion/year.

Streaming and gaming also profit from recurring habits and microtransactions. Even though direct payments for social media are low, time and attention are converted into billions in advertising revenue.

Global financial losses from major addictions

The cost to society from addiction is immense:

• Digital addiction: ~$3 trillion/year (mainly from lost productivity and indirect economic output)
• Alcohol: ~$1.5–2 trillion/year (healthcare, accidents, chronic illness)
• Gambling: ~$500–600 billion/year (mostly direct personal losses among a smaller segment)

Although user spending on digital platforms is modest, the aggregate cost of lost productivity, mental health treatment, and economic displacement is unmatched.

Mapping Risk and Responsibility

The data paints a stark picture: social media remains the most widely used and addictive platform, fueled by infinite scroll, notifications, and hyper-personalized content. Gambling, while less commonly used, inflicts the most severe individual losses. Alcohol and streaming subscriptions continue to draw substantial user spending.

Gen Z emerges as both the most digitally addicted and the most proactive in seeking help. Meanwhile, people in their 30s and 40s are at highest risk for multi-addiction – balancing screen dependency with gambling and alcohol.

Most users don’t limit themselves to just one addictive behavior. Instead, they combine social, gaming, gambling, and more, creating complex “multi-addiction” profiles. As platforms double down on behavioral design to maximize engagement, the cost to society grows – not only in dollars, but in time, attention, and well-being.

Ellen Diamond, a psychology graduate from the University of Hertfordshire, has a keen interest in the fields of mental health, wellness, and lifestyle.