Sleep Hygiene Gap Checker

Introduction

Sleep Hygiene Gap Checker helps you work faster by turning raw inputs into a clear result package.

In practice, it checks technical states and reports pass or fail signals so you can make decisions without rebuilding the logic by hand each time.

Use it when you need repeatable output from the same logic, whether you are doing a quick check, preparing a report, or comparing multiple scenarios side by side.

Typical workflow: enter the minimum required fields, run once for a baseline, then adjust one assumption at a time to see how the output changes.

This output is informational and does not replace professional evaluation, diagnosis, or treatment.

Everyday Use and Decision Guide

Start with a plain baseline run before exploring advanced controls. That gives you an anchor result and makes later changes easier to interpret.

In day-to-day use, most people cycle through three moves: set core inputs, compare outcomes, and export a clean snapshot for records or collaboration. The goal is not just getting a number, but understanding what changed and why.

• If you are unsure where to start, fill only the first core field (Preset) and review the baseline output before touching advanced settings.
• If the result swings too much between runs, lock one reference input (Caffeine timing) so comparisons remain fair.
• If a result looks unrealistic, re-check units, percent vs absolute values, and date/time formats before recalculating.
• If you need to share the output, use the built-in copy/download controls after confirming values are complete.

Technical Details

The processing path is deterministic for the same inputs: values are normalized, validated, and then transformed into status fields, evidence fields, and error notes. Invalid entries are constrained or flagged before result rendering.

The workflow runs locally in your browser for normal calculations and formatting.

Inputs and results stay in the browser session unless you choose to copy or download exports.

Detected export paths include CSV, JSON, DOCX outputs. Chart tabs are included for visual comparison.

Step-by-Step Guide

Use this sequence for predictable runs and cleaner comparisons.

1. Review the main form and identify the minimum fields needed for a first run.
2. Enter core inputs: Preset, Caffeine timing, Alcohol timing.
3. Open advanced options only after you confirm the baseline output looks reasonable.
4. Use the primary action controls (Advanced, Gap Findings, Action Queue) and read the summary panel first.
5. Inspect detailed rows or tabs to confirm assumptions, edge cases, and warnings.
6. Copy or download the result set when you are ready to document or share it.

After one complete pass, keep the same baseline and change only one variable per rerun.

Interpreting Results

Read the top summary first, then open detailed rows to confirm how each input contributed to the final output.

When values sit near thresholds, small input edits can flip interpretation labels. Treat boundary results as prompts for a second run rather than final answers.

• Stable/expected: Inputs pass validation, outputs are internally consistent, and guidance suggests normal follow-through.
• Borderline: Values sit close to decision boundaries; re-run with confirmed units and one adjusted assumption.
• Outlier: Inputs or context produce unusual output; inspect warnings and review each field before acting.

Worked Examples

1. Baseline run with Preset
   Input snapshot: Preset: Sample value; Caffeine timing: Sample value; Alcohol timing: Sample value
   Key processing note: Use default advanced settings and run once.
   Final output: You get a stable baseline output you can compare against later runs.
   What this means: This establishes a reference point before optimization.
2. Sensitivity check
   Input snapshot: Preset: Sample value; Caffeine timing: Sample value; Alcohol timing: Sample value; adjust one advanced setting only.
   Key processing note: Re-run and compare summary deltas and warnings.
   Final output: You see which setting most strongly affects the final outcome.
   What this means: This prevents over-tuning multiple variables at once.
3. Share-ready snapshot
   Input snapshot: Preset: Sample value; Caffeine timing: Sample value; Alcohol timing: Sample value
   Key processing note: Confirm result rows, then copy or download exports.
   Final output: Detected export paths include CSV, JSON, DOCX outputs.
   What this means: This creates a portable record for reports or team handoff.

FAQ

Glossary

Endpoint

Target host or URL that gets checked.

Status

Outcome label for a single check step.

Timeout

Maximum wait before a request is marked failed.

Evidence

Returned data used to justify the result.

False negative

A temporary failure even when setup is correct.

Retry window

Later time used to re-check unstable results.