{{ interpretationLead }}
| # | Domain | Component | Score | Profile role | Action focus |
|---|---|---|---|---|---|
| {{ row.rankLow }} | {{ row.name }} | {{ row.component }} | {{ row.scoreText }} | {{ row.profileRole }} | {{ row.note }} |
Scoring note: {{ scoringMethodNote }}
Ranks the eight domains from lowest to highest so the main watchpoints are obvious before you inspect item-level answers.
A radar view of the eight domain scores after each item has been aligned to the same 0 to 100 direction.
Shows how far each domain sits above or below your own mean so strongest anchors and largest gaps are easy to compare.
PCS is built here from Physical Functioning, Role-Physical, Pain, and General Health.
MCS is built here from Emotional Well-being, Role-Emotional, Social Functioning, and Energy / Fatigue.
Use this table for the ranked 0 to 100 domain scores, within-tool priorities, and exportable comparison rows.
| Domain | Component | Score | Band | Vs mean | Priority | Guidance |
|---|---|---|---|---|---|---|
| {{ row.name }} | {{ row.component }} | {{ row.scoreText }} | {{ row.bandLabel }} | {{ row.deltaText }} | {{ row.priorityLabel }} | {{ row.note }} |
Each answered item stays tied to its source domain so repeat runs are easier to compare later.
| # | Domain | Item | Response |
|---|---|---|---|
| {{ answer.id }} | {{ answer.domain }} | {{ answer.text }} | {{ answer.answer }} |
The payload mirrors this tool’s transparent domain-profile logic so the same comparison frame is easy to reuse later.
Health-related quality of life is a structured way to describe how physical functioning, pain, energy, mood, and social life are affecting day-to-day living. It matters because people can feel broadly "not quite right" without having a single lab number or diagnosis explain where the strain is showing up. This package uses the RAND SF-12 item set to turn that broad picture into a shorter, trackable profile.
The survey covers 12 questions and asks you to anchor most answers to the past four weeks. Once all items are answered, the package transforms the responses into eight domain scores on a 0 to 100 scale, then derives an overall mean plus simplified physical and mental summary scores. That gives you a fast snapshot of where functioning looks steadier and where it appears more pressured.
A realistic use case is comparing two check-ins taken weeks apart. Someone whose bodily pain and role-physical scores improve after rehabilitation may see the physical side move up while emotional and energy scores remain relatively flat. Another person may show the opposite pattern, with stable movement but lower energy and emotional well-being during a stressful month.
The result surface is built for reflection rather than diagnosis. The summary badges highlight the mean, physical component summary (PCS), mental component summary (MCS), balance label, strongest domain, and lowest domain. Below that, the package generates focus-versus-strength tables, next-step suggestions, a radar profile, a domain bar chart, and a full answer table you can export.
The important caution is that this is not the official norm-based SF-12 scoring workflow used in every research setting. The code uses item transforms to 0 to 100, averages them within eight domains, and then computes package-defined PCS and MCS averages from four domains each. That makes the output easy to read and compare within this package, but it should not be treated as a direct substitute for every published SF-12 scoring method or as a clinical diagnosis.
The most important practical choice is consistency. Answer with the same recall frame for every item, because mixing "how I felt this morning" with "how the month has gone overall" makes the profile harder to interpret. The tool already prompts you to use the past four weeks unless a question states otherwise, and that is the safest way to keep repeat runs comparable.
Read the result in layers. Start with the mean score and the PCS versus MCS badges. Then look at the strongest and lowest domains. After that, use the focus-versus-strength table and next-step guidance to see whether the profile is broadly balanced or whether one area is doing most of the damage. The charts help with pattern recognition, but the ranked domains usually explain the result faster than the visuals alone.
The profile is most useful for change detection and conversation prompts, not for proving that something is medically wrong or psychologically wrong. If pain, energy, or emotional well-being scores stay low across repeated check-ins, the value is in seeing that pattern clearly enough to discuss it or plan around it. If one run looks unusually poor, the best next step is often a second check under calmer conditions rather than over-interpreting a single reading.
Privacy deserves attention too. The package keeps the response state in a compact URL parameter so you can reload the same answers on the same device. That is convenient for continuity, but it also means a copied link can carry sensitive response patterns. Treat shared URLs and exported answer tables as personal data, even though the scoring itself stays in the browser.
When you want to compare runs, focus on direction and spread rather than perfection. A five-point lift in one weak domain can matter more than a stable overall mean. The summary is most informative when it helps you ask, "Which part of daily functioning moved, and what changed around it?" rather than "Did I pass or fail?"
The package builds eight domain scores: General Health, Physical Functioning, Role-Physical, Pain, Role-Emotional, Emotional Well-being, Energy / Fatigue, and Social Functioning. Each item response is transformed to a 0 to 100 scale so higher values always represent better functioning. Some items are reverse-coded in the implementation to keep that direction consistent, including the general-health item, the downhearted-and-blue item, and the social-functioning interference item.
After transformation, each domain score is the arithmetic mean of its mapped items, rounded to one decimal place. The package then computes a simple overall mean across the eight domains. PCS is the mean of Physical Functioning, Role-Physical, Pain, and General Health. MCS is the mean of Emotional Well-being, Role-Emotional, Social Functioning, and Energy / Fatigue. The balance label is set to Balanced profile when the absolute PCS-MCS gap is under four points, otherwise the higher side is called out.
Interpretation bands are also package-defined. A score of 75 or above is labeled high, 50 to 74.9 is moderate, and anything below 50 is treated as lower and worth attention. The next-step suggestions are generated from those scores and from the lowest domains. For example, low pain, energy, or social-functioning results trigger different follow-up suggestions, and wide spread between high and low domains increases the emphasis on narrowing the weakest area first.
| Domain | Question IDs | Item count | Coding note |
|---|---|---|---|
| General Health | 1 | 1 | Reverse-coded |
| Physical Functioning | 2, 3 | 2 | Forward-coded |
| Role-Physical | 4, 5 | 2 | Forward-coded |
| Pain | 6 | 1 | Forward-coded |
| Role-Emotional | 7, 8 | 2 | Forward-coded |
| Emotional Well-being | 9, 10 | 2 | Item 10 reverse-coded |
| Energy / Fatigue | 11 | 1 | Forward-coded |
| Social Functioning | 12 | 1 | Reverse-coded |
| Rule | Threshold or behavior | Why it matters |
|---|---|---|
| Band labels | High at 75+, moderate at 50 to 74.9, lower below 50 | Turns the raw numbers into faster summary language |
| Balance label | PCS and MCS within 4 points counts as balanced | Flags whether physical and mental summaries are moving together |
| Domain grouping | High domains are 60+, middle 40 to 59, low below 40 | Drives the highlight counts and the strengths versus focus summary |
| Response persistence | 12-character response state stored in URL parameter r |
Makes repeat viewing convenient, but copied links can expose answers |
The overall mean tells you how the full profile is trending, but it is only the entry point. The domain spread and the highest-versus-lowest domains explain whether the profile is evenly moderate, sharply split, or broadly strong. A moderate mean with one very weak domain often deserves more attention than the headline number suggests.
PCS and MCS are best read as package summaries rather than universal SF-12 norms. A stronger PCS with a weaker MCS suggests the physical side of daily life is holding up better than mood, energy, social, or emotional role areas. The reverse pattern suggests physical limitations are weighing more heavily than the mental side.
Low scores are signals for reflection, not verdicts. A weak pain score does not diagnose a pain disorder, and a weak emotional-well-being score does not diagnose depression. The right interpretation is that the package is pointing to parts of functioning that may deserve closer attention, better self-management, or a conversation with a qualified professional.
Someone answers all 12 questions and gets mid-range PCS and MCS values that sit within four points of each other. The balance label is therefore Balanced profile. Even so, the focus table may still flag Energy / Fatigue as the weakest area, which is a useful reminder that balance does not mean every domain is equally strong.
After rehabilitation, a person may see Pain and Physical Functioning rise while Energy / Fatigue remains low. The bar chart makes that split obvious, and the next-step panel is likely to emphasize gradual conditioning plus routines that support energy and recovery rather than treating the improved physical scores as the whole story.
A user takes the survey at the start and end of a stressful month. The second run shows lower Emotional Well-being and Role-Emotional scores even though General Health and Pain barely move. That pattern is more useful than the overall mean alone because it tells you which part of life changed and what kind of follow-up might help.
No. The package uses its own transparent 0 to 100 transforms, domain averages, and simplified PCS and MCS summaries. It is useful for internal comparison, but it is not a drop-in replacement for every published SF-12 scoring workflow.
The response pattern is stored in the URL parameter r. That makes repeat viewing convenient, but copied links can also expose your answers.
It means that area of functioning looks weaker relative to the package's 0 to 100 scale. It is a prompt for attention, not a diagnosis.
The package is most reliable for within-person reflection and repeated check-ins. Cross-person comparison is much harder because context, baseline health, and interpretation all differ.