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The gauge keeps the official ESS total on the original 0 to 24 scale. Use the band and boundary note together with the item review below; the ESS is interpreted as one total daytime sleepiness screen rather than a set of official subscales.
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These are the situations you endorsed most strongly on this run. They are descriptive review cues, not official ESS subscales.
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No situation was endorsed above 0/3 on this run, so there are no higher-scored situations to prioritize.
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ESS is interpreted as one total score. This comparison only shows which situations were more or less endorsed on this run.
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Daytime sleepiness is the tendency to drift toward sleep in ordinary situations when you would rather stay awake. It matters because the setting where dozing happens can change the risk: nodding off while reading is different from nodding off in traffic or during a conversation. This package turns that question into a structured Epworth Sleepiness Scale screen so the pattern is easier to name and review.
The assessment uses eight everyday situations, each rated from 0 to 3 according to your usual chance of dozing. From those responses the package calculates one total score, assigns a severity band, and then builds context summaries that separate passive situations, vehicle-related situations, lying-down rest, and social settings. That layered view makes the result more useful than a single total alone.
A realistic use case is someone who stays alert while talking with people but often feels sleepy while reading, watching TV, or sitting quietly after lunch. The total score may stay in a normal or mildly elevated range, yet the pattern still points to when sleepiness is most likely to appear. That is often the practical question users care about.
The package also adds guidance beyond the raw scale. The gauge summarizes the total score visually, the focus table highlights higher- and lower-scored situations, and the answer table captures each item for later review or export. Those are interpretation aids built on top of the questionnaire result, meant to help reflection and communication.
The boundary is important. This is a screening and self-report reflection tool, not a diagnosis. The score depends on your own estimate of how likely you are to doze in each situation, and it should not overrule safety decisions or professional evaluation when daytime sleepiness is persistent, disruptive, or risky.
The most useful way to answer the scale is to think about usual life, not just one unusually bad or unusually easy day. The wording is about your chance of dozing in each setting, not your momentary tiredness alone. That distinction matters, because someone can feel fatigued without actually tending to fall asleep, and the scale is trying to capture the dozing tendency.
The result should be read in layers. Start with the total score and the severity band. Then look at the situation pattern: are the strongest scores clustered in passive contexts, in vehicle contexts, or around lying down to rest? That second step often explains the result better than the band alone.
The package’s higher- and lower-scored situation lists are helpful because they turn the questionnaire into concrete settings. A moderate total driven by reading, television, and afternoon rest paints a different practical picture than a similar total driven by traffic and passenger travel. The latter deserves much more caution in daily life even if the total score is not the highest possible band.
The answer table is most useful when the result needs to be shared or repeated. It makes it easier to compare how your ratings change over time or to bring the full item pattern into a medical or counseling conversation. The DOCX and CSV exports support that kind of handoff without forcing someone else to reconstruct the score from memory.
Use the band as a signal, not a verdict. Lower scores can still matter if the sleepy situations are safety-sensitive, especially driving-related ones. Higher scores deserve attention, but they still need context from sleep habits, schedules, medications, health conditions, and professional judgement.
The scoring core is straightforward. Each of the eight items accepts a response from 0 to 3. The total score is the sum of those eight values, which gives a possible range from 0 to 24. The package then maps that total into one of five severity bands: Lower Normal, Higher Normal, Mild EDS, Moderate EDS, and Severe EDS, where EDS refers to excessive daytime sleepiness.
The tool also computes context subscores that do not replace the total but help explain it. Passive environments combine items 1, 2, 3, and 7. Vehicle contexts combine items 4 and 8. Rest/lying down uses item 5. Social interaction uses item 6. Those grouped values are turned into bar-style summaries so the result shows not only how much sleepiness is present, but where it tends to show up.
The package’s band thresholds are fixed in code: 0 to 5 for Lower Normal, 6 to 10 for Higher Normal, 11 to 12 for Mild EDS, 13 to 15 for Moderate EDS, and 16 to 24 for Severe EDS. On top of that, the script generates a narrative summary, identifies the highest-scoring situations, marks whether vehicle-related sleepiness raises a driving caution, and adds next-step guidance matched to the band and pattern.
State stays local to the page. Responses are encoded into an eight-character query-backed value named r, using digits 0 to 3 and hyphens for unanswered items. That lets the package restore a session or share a stateful URL, but it also means copied links can expose the response pattern. The package does not need a tool-specific backend to score the questionnaire.
The result surfaces are built from the same response array. The gauge chart displays the total score against the full 0 to 24 span with colored severity segments. The focus table summarizes context subscores, drivers, and pattern cues. The answered-questions table shows every item and chosen response. CSV and DOCX exports are available for the answer table, which makes the structured output easier to save or discuss.
| Band | Score range | How the package frames it |
|---|---|---|
| Lower Normal | 0 to 5 | Low daytime sleepiness under the package's banding rules |
| Higher Normal | 6 to 10 | Upper-normal range worth monitoring in context |
| Mild EDS | 11 to 12 | Mild excessive daytime sleepiness signal |
| Moderate EDS | 13 to 15 | Noticeable excessive daytime sleepiness signal |
| Severe EDS | 16 to 24 | High sleepiness burden with stronger safety and evaluation cues |
| Context group | Items included | Maximum subtotal | Why it helps |
|---|---|---|---|
| Passive environments | 1, 2, 3, 7 | 12 | Shows sleepiness in quieter, low-demand situations |
| Vehicle contexts | 4, 8 | 6 | Highlights sleepiness in traffic or passenger settings |
| Rest / lying down | 5 | 3 | Separates expected rest-related sleepiness from other contexts |
| Social interaction | 6 | 3 | Shows whether alertness slips even during active interaction |
The total score is the starting point, not the whole meaning. A lower band suggests less overall sleepiness under the package's thresholds, while higher bands suggest more daytime sleepiness burden. But the pattern of scores still matters, because one safety-sensitive item can deserve attention even when the total remains moderate.
The context groups are most useful for explaining where the score comes from. A passive-heavy pattern may point to low-stimulation settings as the main problem. A vehicle-heavy pattern deserves more caution because driving and passenger contexts are not interchangeable with reading quietly at home. A high lying-down score may be unsurprising in someone who is already resting, while a high social score suggests sleepiness can break through active engagement.
Treat the package guidance as a prompt for action, not a final answer. If the result is persistent, disruptive, or risky, especially in traffic or work situations, the safest next step is professional evaluation rather than repeated self-scoring.
A user reports higher scores for reading, television, and sitting quietly after lunch, but low scores for talking and stopped traffic. The total score may still move into the higher-normal or mild range, yet the context summary makes it clear that the pattern is concentrated in low-stimulation settings.
Another user reports stronger dozing likelihood while stopped in traffic and while riding as a passenger. Even if the total is not the highest possible band, the vehicle subscore and caution language become more important than the overall number because the real risk is contextual.
A person repeats the questionnaire after improving sleep timing for two weeks. The total score drops and the answer table shows that the biggest change came from passive evening situations rather than from every item equally. That makes the comparison more informative than “the score got better” by itself.
No. The package summarizes self-reported dozing tendency in eight situations. A lower score can still coexist with other sleep complaints or health concerns.
They show where the sleepiness is clustering. Two people can have similar totals with very different patterns and very different practical risks.
The package stores responses in a compact query-backed value, so a copied link can reproduce the response pattern. Treat shared URLs as sensitive.
No. It is a structured screening aid and reflection tool. Diagnosis depends on clinical history, context, and professional assessment.