Baseline Sleep Diary Collection
Two weeks of logged bed times reveal a low sleep-efficiency pattern.
- 9.0 h: Typical baseline time in bed (self-selected, unregulated)
- 5.6 h: Typical baseline sleep time (fragmented across the night)
- ~62%: Typical baseline efficiency (sleep ÷ time in bed)
- 14 days: Diary logging period (minimum before titration starts)
Why the app starts with a diary
Two weeks of nightly logs anchor the algorithm to real behavior.
Insomnia often means lying awake in bed, not lacking sleep drive.
What the diary captures
Bedtime, wake time, awakenings, and estimated minutes actually asleep.
The core problem it exposes
Extra time in bed trains the brain to associate bed with wakefulness.
Initial Time-in-Bed Restriction
The prescribed window shrinks to roughly match average sleep time.
- ATS + 0.5h: Initial window formula (average total sleep, buffered)
- 5.0 h: Minimum allowed window (safety floor, never lower)
- 6.1 h: Typical week-1 window (down from 9.0 h baseline)
- ↑ sleep drive: Expected short-term effect (mild sleep debt builds)
How the app sets the first window
It takes average diary sleep time, adds a small buffer, and caps low.
Why restriction feels counterintuitive
Less time in bed initially raises pressure to fall asleep fast.
A tighter window consolidates fragmented sleep into one solid block.
Guardrails built into the app
A hard floor prevents the window from ever dropping below five hours.
Sleep Efficiency Calculation
Every morning the app computes efficiency from last night's data.
- TST ÷ TIB: Efficiency formula (total sleep ÷ time in bed)
- > 85%: Expansion threshold (widen the window next week)
- < 80%: Restriction threshold (narrow the window further)
- 80–85%: Hold zone (window stays unchanged)
The nightly calculation
Sleep time is divided by time in bed and expressed as a percentage.
Why a weekly average is used
One rolling week smooths out single bad nights before deciding.
A single low-efficiency night never triggers an algorithm change.
What the app shows the user
A simple gauge and a one-line weekly summary of the trend.
Weekly Window Titration Algorithm
Each week the algorithm expands, holds, or restricts the window.
- +15–30 min: Expansion step size (when efficiency exceeds 85%)
- −15 min: Restriction step size (when efficiency drops below 80%)
- 6–8: Typical weeks to stabilize (per published protocols)
- 8.5 h: Upper window cap (rarely exceeded even late)
The decision rule
Above 85% expand, below 80% restrict, in between hold steady.
Why adherence changes the curve
Skipping the prescribed window slows or stalls the whole process.
Consistent adherence is the single biggest driver of faster titration.
Automation versus a human therapist
The app applies the same rule every week without judgment fatigue.
Optimized, Consolidated Sleep Window
A stable window now delivers consistently high sleep efficiency.
- ≥ 88%: Final efficiency target (sustained across nights)
- 7.2–7.8 h: Typical final window (individualized end point)
- ↓ ~60%: Wake-after-sleep-onset drop (versus baseline diary)
- Week 8: Program completion (maintenance phase begins)
What "optimized" means here
The window matches true sleep need, not habit or anxious over-time.
Maintaining the gains
The app shifts from titration mode to a lighter monitoring mode.
Relapse often starts with quietly creeping bedtimes — the app watches for it.
Beyond the app alone
Sleep restriction pairs with stimulus control for durable results.