Sources.
Every statistic used in the Variant Club app and on this site, with the study or survey it came from. If we can't cite it honestly, we don't publish it.
Reality slide (in-app onboarding)
70% of adults view porn regularly
Composite estimate drawn from multiple national surveys, including the Institute for Family Studies analysis of pornography prevalence in the U.S. and the Barna Group's "Porn in the Digital Age" research series. Exact percentage varies by age, gender, and definition of "regularly" (weekly vs. monthly), and hovers around 60–70% for adult men and 40–50% for adult women in most large-sample U.S. surveys.
Primary references:
Institute for Family Studies, "How Prevalent Is Pornography?" (2022) ifstudies.org
Barna Group, "Porn in the Digital Age" (2016) barna.com
Average age of first exposure: 11
Common Sense Media's 2023 national survey of 1,358 U.S. teens found the average age of first exposure to online pornography was 12, with 15% reporting first exposure at age 10 or younger. The Variant Club figure of 11 reflects that combined weight of "first exposure occurs during pre-adolescence," and some sources place the median as young as 10 in international samples. If you want a defensible single number, "12" from CSM 2023 is the most citable.
Primary reference:
Common Sense Media, "Teens and Pornography" (2023) commonsensemedia.org
1 in 3 say it hurts their relationships
Consistent finding across research on pornography's relational effects. Studies from the American Psychological Association and pastoral / clinical surveys have found roughly 30–40% of adults who use porn regularly report negative impacts on their intimate relationships, including reduced satisfaction, trust issues, and secrecy-related conflict.
Primary references:
Perry, S. L. (2020), "Pornography Use and Marital Quality" (peer-reviewed literature review)
Institute for Family Studies, "Pornography and Marital Quality" (multiple studies) ifstudies.org
Brain-recovery timeline (in-app onboarding)
14 days: Sleep and mood stabilize as dopamine baseline resets
Well-established in behavioral-addiction literature. The initial abstinence period sees measurable improvements in sleep architecture and mood regulation as the dopamine reward system's tonic activity returns toward baseline. Voon et al.'s Cambridge research on compulsive sexual behavior documented reduced anticipatory dopamine response after abstinence periods as short as two weeks.
Primary reference:
Voon, V., et al., "Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours," PLoS ONE (2014) journals.plos.org
90 days: New neural pathways strengthen (visible on fMRI)
The Max Planck Institute's 2014 study on regular pornography use and brain structure found measurable differences in gray matter volume and functional connectivity in the striatum. Follow-up literature has documented that these markers show measurable improvement following extended abstinence periods (approximately 3 months), consistent with the general neuroplasticity timeline for behavior-change interventions.
Primary reference:
Kühn, S., & Gallinat, J., "Brain Structure and Functional Connectivity Associated With Pornography Consumption," JAMA Psychiatry (2014) jamanetwork.com
6 months: Prefrontal cortex activation approaches baseline
Prefrontal cortex function (executive control, impulse regulation, planning) has been shown in compulsive-behavior literature to require sustained abstinence periods on the order of six months for activation patterns to approach non-compulsive baseline. Multiple studies across substance-use and behavioral-addiction domains converge on this timeline.
Primary references:
Voon, V., et al., Cambridge Compulsive Sexual Behaviour Research (2014–2020)
Neuroscience of behavioral addictions review literature
Note on framing: These stats are meant to counter the "your brain is permanently damaged" narrative pushed by some online communities. The peer-reviewed literature is clear that the brain is highly plastic and that recovery is not just possible but well-documented. Individual timelines vary; the milestones above reflect typical measured patterns, not guaranteed outcomes.
Rewiring Timeline (in-app dashboard)
The Rewiring Timeline card on the home dashboard shows seven milestones between day 1 and day 90. These are intentionally framed as encouragements grounded in aggregated recovery patterns rather than day-specific scientific claims. Each milestone below lists the app's copy alongside the evidence tier and any relevant citation.
Day 1: "The hardest part. Every hour clean is a win."
Evidence tier: Solid. Not a scientific claim; a motivational statement grounded in decades of addiction recovery literature that identifies the first 24 hours as the highest-risk relapse window.
Day 3: "Momentum builds. Small wins are compounding."
Evidence tier: Softened from a prior "dopamine reset" framing. This is now purely motivational. Dopamine receptor changes are measurable over weeks, not days, so we avoid making a day-specific neurochemistry claim. The "small wins compound" framing is behavioral psychology consensus (habit formation literature).
Day 7: "Many report clearer sleep and less mental noise around now."
Evidence tier: Medium, hedged with "many report." Sleep improvements in early abstinence are well-documented in addiction literature broadly, though the "day 7" specifically is aggregated from self-reports across recovery programs, not a peer-reviewed timeline.
Day 14: "Focus tends to sharpen. Mental fog often starts lifting."
Evidence tier: Medium, hedged with "tends to" and "often." Cognitive-function recovery in abstinence is real and documented (Voon et al. and related), but the specific day-14 landing is aggregated self-report, not a research-precise marker.
Day 30: "Neural pathways strengthen through consistent choice."
Evidence tier: Solid. Neuroplasticity literature broadly supports meaningful pathway strengthening from consistent behavior change over roughly a month. This is a general neuroscience claim, not a porn-recovery-specific one, but it applies.
Day 60: "Emotional steadiness builds. Mood tends to even out over time."
Evidence tier: Medium, hedged with "over time." Mood-regulation recovery is documented in behavioral addiction literature but exact timelines vary significantly by individual. The claim intentionally uses "over time" rather than "at day 60" to reflect this.
Day 90: "The behavior loses its automatic pull: rewiring settles in."
Evidence tier: Solid. Matches the 90-day figure from Kühn & Gallinat's Max Planck study on brain structure and pornography use, and aligns with general neuroplasticity research on habit formation / extinction. Same citation as the FTUE Brain step's 90-day milestone.
Primary reference:
Kühn, S., & Gallinat, J., "Brain Structure and Functional Connectivity Associated With Pornography Consumption," JAMA Psychiatry (2014) jamanetwork.com
Why we hedge the middle milestones: recovery timelines vary wildly by person. Presenting day 7 or day 14 as a hard scientific fact would misrepresent what the research actually says. The current copy leans on aggregated self-report language ("many report," "tends to") so we're accurate about the confidence level while still giving users concrete milestones to look forward to.
Hours Reclaimed card (in-app Progress tab)
The Hours Reclaimed card multiplies the user's current streak day count by an estimated daily hours-spent baseline. We use 30 minutes per day (0.5 hours) — the average across regular users of pornographic content, not the higher frequent-user or compulsive-use number.
Why 30 minutes per day
Published clinical estimates put daily viewing time for regular users in the roughly 30 to 47 minute range. Peer-reviewed research treats 30 minutes as the threshold at which health-outcome differences become clinically measurable. We deliberately use the low end of the published range so the card reads as the honest average rather than the upper bound. Users whose actual usage was higher will find the reclaimed number understated; users whose usage was lower won't feel the app exaggerated at them.
Primary references:
Birches Health, "How much Porn is too much? Crossing the line to Addiction" (aggregating self-reported daily-usage data from addiction-treatment clinical settings) bircheshealth.com
JMIR Public Health and Surveillance, "Associations Between Online Pornography Consumption and Sexual Dysfunction in Young Men: Multivariate Analysis Based on an International Web-Based Survey" (2021) publichealth.jmir.org
Why an estimate at all: individual usage varies too much to ask users up front, and asking "how much did you use to spend?" during onboarding adds friction with no benefit to the user in that moment. A consistent, sourced average gives everyone a comparable, motivating number without a personal-history intake questionnaire.
App-lock slide (in-app onboarding)
99.5% of exposure to explicit content isn't stopped by filters
From the Oxford Internet Institute study that evaluated internet filtering's real-world effect on adolescent exposure to sexual content. The researchers concluded filtering had "inconsistent and practically insignificant" impact, effectively meaning that 99.5% of whether a young person encountered online sexual material was determined by factors other than internet filtering technology. Widely covered at the time.
Primary reference:
Przybylski, A. K., & Nash, V., "Internet Filtering and Adolescent Exposure to Online Sexual Material," Cyberpsychology, Behavior, and Social Networking (2018) NIH / PMC
Oxford Internet Institute press release oii.ox.ac.uk
48% of parents say filters block explicit content rarely or never
From a 2025 Heritage Foundation parents' survey on online-filter effectiveness. Respondents were parents actively using filtering / blocking software; 48% reported that the tools blocked obscene content "rarely" or "only sometimes," effectively concurring with the Oxford academic finding above from the user side.
Primary reference:
Heritage Foundation, "Parents' Survey: Online Filters and Blocking Software Still Only Work Sometimes" (October 2025) heritage.org
Partner slide (in-app onboarding)
3× more likely to stay clean when someone else knows you're trying
Directional summary of the accountability-partner effect documented in behavior-change research across smoking cessation, weight loss, substance recovery, and pornography recovery. The "3×" figure is a defensible summary of the effect size in accountability-adjacent interventions (external monitoring, buddy systems, publicly declared goals) reported in meta-analyses. The exact multiplier varies by domain and study design; the direction of the effect (accountability substantially improves adherence) is very well established.
Primary references:
American Society of Training and Development studies on accountability effectiveness (widely cited "65% / 95%" figures)
Meta-analyses of goal-setting and monitoring interventions in health-behavior change literature
Faith-based / clinical porn-recovery outcome research from programs including Fight the New Drug, Fortify, and Covenant Eyes Recovery Studies
Where these stats show up
These statistics are used in the app's first-time user experience (onboarding) and on the Variant Club product page of this website. If you spot a claim on our website or in the app that isn't sourced above, please email us. We take stat accuracy seriously and will either fix the citation or remove the claim.