defrag. — a screen time and life-balance calculator
{showFinder &&defrag. walks users through nine sequential steps. The order is deliberate — each step builds the context needed for the next. No step is skippable, but every value can be adjusted at any time.
- About You — age, first device age, smartphone age (adults), parent toggle, daily obligations (sleep, school/work, hygiene, chores, meals, commute).
- Invest Your Time — what the user wants to spend time on (organized activities, interests, protected screen sessions as a budget).
- Your Day With Screens — weekday personal screen hours, weekend screen hours, phone habit checkboxes that feed the filler model, daily pickup count.
- Design Your Screen Time — choose which categories of personal screens count toward the intentional budget (social, streaming, gaming, etc.) and assign frequency/duration per session.
- The Reveal — lifetime dot grid, waking percentage, protected brain time hero stat, pac-man animation revealing screen dots, free-time percentage, 24-hour clock.
- Protected Brain Time — dedicated pitch for the PBT concept, adaptive text by threshold, Great Divide comparison bars.
- Your Possibilities — three levers (pickups, screen goal, filler contexts) in a cockpit panel; live reclaimed-years counter.
- Your Plan — ideal day summary, defragged bubble chart, "What this adds up to" stats, strategies + counterweights accordions, downloadable HTML plan.
- The Bigger Picture — meta scaling: one person → family → classroom → school → university → city → US → world. Closes with "The future belongs to the curious."
defrag. uses six age brackets to pre-fill obligation and screen time defaults. When you move the age slider, all values update automatically. You can adjust any slider to match your reality — the defaults anchor the conversation in real data.
| {h} | ))}|
|---|---|
| {label} | {vals.map((v, j) => ({v} | ))}
1-hour floor on totalIdeal. If a user
hasn't built an intentional screen budget in Step 4 (Design Your Screen Time),{" "}
effectiveAdjScrH
{" "}
falls back to{" "}
max(totalIdeal, 1)
. This prevents the Plan page from reporting "0h screens" — a number that's almost
never realistic and would make the reclaimed-years math look absurd.
{" "}? adjScrH
{" "}: max(totalIdeal, 1)
Seniors retirement blend. For users under 65 whose lifetime grid extends past 65, retirement-phase segments blend the user's intentional screen budget with the Seniors bracket default (5.5h/day). This reflects the empirical reality that retirees' screen time converges toward the population average regardless of pre-retirement habits — the workplace discipline that kept screens in check disappears.
Both choices are design decisions, not empirical constants. The 1h floor is a guardrail against degenerate outputs; the retirement blend keeps the lifetime projection honest for users who might otherwise assume their current screen habits will hold across a 40-year horizon.
Step 3 ("Your Day With Screens") asks "Where does your phone show up?" — a set of checkboxes for contexts where phone use happens during other activities (morning, getting ready, commute, at school/work, after school, meals, caregiving, bedtime). Each checked context adds a{" "} base minute estimate, scaled by pickup intensity.
This captures filler screen time — the phone checks during meals, the scrolling before bed, the morning scroll that never feels like "screen time." These minutes are controllable but rarely counted. Age-appropriate categories are shown (e.g., "After school" for under-18, "Caregiving" for adults 25+).
fillerMinutes = sum of (FILLER_ESTIMATES[context] × pkpScale)
{" "}for each checked context
defrag. uses a three-layer screen model : Required (school/work device hours) | Filler (phone habit checkboxes, scaled by pickups) | Intentional (chosen personal screens). Controllable = Filler + Intentional — the number that matters for the Reveal. On the Possibilities page, users can uncheck filler contexts to "protect" those windows, and adjust the pickup slider to see how reducing phone checks reduces filler time.
Weekdays and weekends have different obligation profiles. School/work, homework, commute, and teen jobs apply Monday–Friday only. defrag. computes separate free time values and averages them for lifetime projections.
{" "}+ commute + caregiving + teenJobDailyH
weekendOblig = sleep + hygiene + chores + meals + caregiving
avgFreeTime = (5 x weekdayFree + 2 x weekendFree) / 7
avgSH = (5 x weekdaySH + 2 x weekendSH) / 7
Pie charts and the 24-hour clock use weekday values. Lifetime projections, the life grid, and free-time screen intensity all use weekly averages (avgSH, avgFreeTime) so weekday and weekend patterns are both reflected. The WeekPlan in Step 8 ("Your Plan") zeroes school/work and commute on Saturday and Sunday.
The hero stat of The Reveal. Protected brain time is the number of waking minutes per day where your brain is not processing someone else's content — no screens, no audio, no external input. This is when original thought, daydreaming, and self-reflection happen.
protectedMinutes = max(0, wakingMinutes - schoolH×60
{" "}- commute×60 - caregivingMin - teenJobDailyH×60
{" "}- fillerMinutes - sH×60 - audioMinutes)
The Reveal shows what reducing phone pickups to 25/day would do to protected brain time. This recalculates filler screen time using the same formula but with a reduced pickup scale factor.
reducedFiller = same sum, scaled by reducedPkpScale
reducedProtected = max(0, wakingMin - schoolH×60 - commute×60
{" "}- caregivingMin - teenJobDailyH×60
{" "}- reducedFiller - sH×60 - audioMin)
protectedGain = reducedProtected - protectedMinutes
25 pickups/day is chosen as a realistic reduction target — roughly one per waking hour. Average is 185×/day (Reviews.org 2026). Each pickup averages ~30 seconds of screen exposure (Oulasvirta et al., 2012). The pickup-to-filler scaling model (pkpScale = pickups / 185, clamped 0.5–1.8) is a defrag. model, not empirically validated — it provides a directional estimate, not a precise measurement.
Adults see a birth-to-78 dot grid showing their entire life — past and future. Past segments are estimated using age-appropriate sleep, school, work, and screen time averages. Future segments use the existing computeGridSegs projection. A "you are here" marker shows the user's current position in life.
Kids and teens (under 22) see the original remaining-life-only grid with the "tap to reveal screen time" toggle, since their past is minimal relative to what's ahead.
The Reveal branches into two pathways based on controllable screen time — filler + intentional, not required school/work.
isLightUser = controllableH {"<"} 2.5
Pathway A ({"<"} 2.5h): "You're
protecting something rare" — affirming framing. The Reveal shows a celebration
card with the user's real stats highlighted in teal, plus a{" "}
counterfactual panel comparing current
protected brain time and free-time screen percentage against what would happen if
screen time drifted to the next age bracket's national average (kids→5h,
tweens→7h, teens→8h, adults→5h). Protected Brain Time text adds age-specific
affirmation. The trajectory card in Possibilities reframes from "three paths" to
"what you're protecting — and what drift would cost."
Pathway B (≥ 2.5h): "Here's the gap" —
gap-focused framing + filler vs intentional breakdown.
The 2.5h threshold is a design choice for framing, not a clinical cutoff.
defrag. estimates total screen time from age 2 to the user's current age using a three-era model. The ramp target is{" "} total daily screen hours (personal + work/school devices) — not just personal use.
Era 1 (Pre-internet): TV-only baseline by age. Era 2 (Desktop internet):{" "} Baseline + gradual bump (max +1.5h, growing at 0.2h/year) for AOL, email, early web. Era 3 (Smartphone): Logarithmic ramp from desktop level to current total screen hours.
Era 3: piecewise ramp — early years reach ~40% of target,
{" "}last 5-7 years accelerate quadratically to current level
{" "}dailyH = desktopLevel + (totalScrH - desktopLevel) × t
| {h} | ))}|
|---|---|
| {label} | {vals.map((v, j) => ({v} | ))}
For users age 22+, the hero stat shows total lifetime screen years: past screen time (computed from age 2 to current age using the whole-life screen history model) plus future projected screen time. Kids and teens see only remaining years, since their past screen time is relatively small.
futureScreenYears = (statScrH / 24) × yearsRem
totalLifetimeScreenYears = pastScreenYears + futureScreenYears
The lifetime dot grid represents{" "} remaining months of life from the user's current age to age 78 (CDC NCHS 2022 estimate of 77.5 years). Each dot = 1 month, 1 row = ~1 year (14 columns). Dots are colored by category using phase-weighted averages across four life stages. For adults 22+, a full-life grid (birth to 78) is shown with a "you are here" marker.
| {h} | ) )}|
|---|---|
| {phase} | {vals.map((v, j) => ({v} | ))}
For each category, the lifetime average is computed as a weighted mean across phases:
School years run from current age to 18 (extended by college: +2 for community, +1.5 for trade, +4 for university). Work years run from school end to 65. Screen time uses the weekly average (avgSH), which accounts for weekend extra hours. defrag. does not assume behavior change in the baseline projection.
{r.summary}
Most screen time interventions start with a number — "no more than 2 hours" — and work backward. The research suggests this approach has low durability. Externally imposed limits trigger reactance (Brehm, 1966), are abandoned once removed, and don't build the internal reasoning that drives lasting change.
defrag. inverts this. Users start by mapping what they actually want their time to contain — sleep, obligations, interests, relationships. The screen time question comes after the rest of the day is filled in. The number the user arrives at is self-derived, grounded in their own stated values. This aligns with self-determination theory (Deci & Ryan, 1985), which identifies autonomy, competence, and relatedness as the core drivers of intrinsic motivation and durable behavior change.
The tool also avoids pathologizing. It does not call any amount of screen time "addictive" or label users as having a problem. The framing is economic: time is a finite resource, allocation is a choice, and the question is whether the current allocation matches stated priorities. This approach is consistent with media balance frameworks (Common Sense Media, American Academy of Pediatrics Family Media Plan).
- All defaults are population averages. Individual variation is high — defaults are starting points, not prescriptions.
- Screen time is not monolithic. Educational, creative, and social screen use have different wellbeing profiles than passive consumption. defrag. distinguishes required vs. personal screens but does not subdivide personal screen quality.
- Lifetime projections assume current behavior continues unchanged — a deliberate choice to make the status quo legible, not a prediction.
- Life expectancy anchor (78, CDC NCHS 2022) uses U.S. national average. It varies significantly by race, income, sex, and geography — masking a ~10-year gap between income quintiles.
- Day walkthrough filler estimates are based on option ranges (e.g., "5–10 minutes" mapped to 8m), not precise measurements. Actual filler time may be higher or lower.
- Protected brain time assumes audio-occupied time (podcasts, music during routines) is not "protected" — some users may reasonably disagree.
- The 2.5h screen intensity threshold is a design choice for framing, not a clinical cutoff.
- Whole-life screen history uses estimated baselines and a logarithmic ramp model — directional, not precise.
She's a teenager. Smart, curious, connected. One evening I asked her how much time she thought she'd spent on her phone that day. She guessed about two hours. Her screen time report said six and a half.
That gap — between what we think we're doing and what we're actually doing — stopped me. But what happened next mattered more.
I pulled out a blank piece of paper. We sat down together and I walked her through the math. Her sleep. School. Homework. The things she actually wanted to do — basketball, reading, time with friends. One by one, we filled in what mattered. Then we looked at what was left.
On her own, without me telling her a number, she landed on about one to two hours of screens a day. Her answer. Her reasoning. Her choice.
That piece of paper became the first draft of this project. defrag. is the tool I wished I'd had — and the conversation I think every family deserves to have.
When a hard drive gets fragmented, storage is scattered everywhere — the system slows, space disappears, nothing runs cleanly. Defragmenting reorganizes it. You get back capacity you didn't know you'd lost.
That's what this tool is for. Not restriction. Reorganization. Reclaiming the cognitive space that screens have quietly occupied — so there's room again for the things that actually build a life.
Most screen time conversations start with the screen. defrag. starts somewhere else: with your ideal day. What you actually want to do with your time. What matters to you.
Once you've mapped that — your sleep, your commitments, your interests, your chosen balance — the screen time picture becomes clear on its own. Not as a verdict. As information.
AI is not the enemy. Cognitive displacement is. {" "} The answer isn't restriction — it's capacity-building. That's the lens this tool is built on.
Researchers studying behavior change have found something counterintuitive: telling people data isn't enough. Charts, statistics, and expert recommendations rarely move behavior in lasting ways. What works is letting people see it, manipulate it, and arrive at their own conclusions.
Researchers at Arizona State University were working on water conservation. They built an interactive model — a system of dials representing agriculture, pools, landscaping, residential and commercial use. Instead of telling people what to do, they let them explore the numbers themselves. Turning the dials. Watching the consequences. People who engaged with the model made more meaningful and lasting changes than those who simply received information.
That insight is the foundation of defrag. Instead of telling you how much screen time is too much, the tool lets you build your own ideal day first — your sleep, your values, your interests — and then see the gap yourself. The number you arrive at is yours. That's what makes it stick.
defrag. is grounded in the Singh et al. JAMA Pediatrics 2026 study — the largest longitudinal study of its kind, following 100,991 Australian adolescents across grades 4–12 over three years. The study found a U-shaped association between after-school social media use and wellbeing: moderate use was associated with the best outcomes across happiness, optimism, life satisfaction, emotional regulation, and cognitive engagement. Both the highest use and complete non-use were associated with poorer wellbeing, with effects varying significantly by age and sex. For girls, high use was most harmful in middle adolescence (grades 7–9). For boys, no use became increasingly associated with poor wellbeing from grade 9 onward — suggesting that social isolation, not just heavy use, is a risk.
Rebecca Guglielmo is a digital literacy advocate, researcher, author, and speaker focused on the intersection of adolescence, technology, and learning. A Common Sense Educator with more than a decade of experience working with students, families, and schools, she has developed AI policy, guidelines, and digital citizenship programming designed to protect deep learning while preparing students to use digital media and artificial intelligence with intention.
She is the author of Half Life Gone — a book about how a quarter century of screens, algorithms, and AI has displaced the cognitive space humans need to think, create, remember, and become themselves.
defrag. is part of Prompt-Ed — a professional development and digital literacy resource suite for educators and families.
The Ethical Tech Lab is a student-facing program that takes these ideas further — an Ethics Bowl-style tournament where students analyze real digital dilemmas, debate policy, and develop their own positions on technology, AI, and the future. Built for grades 5–8, it turns passive screen time awareness into active critical thinking.
"Technology doesn't steal time. It occupies the time we haven't yet decided to protect."