Convergent Validity of Suffering and Quality of Life as Measured by The Hidradenitis Suppurativa Quality of Life
Bibliographic record
Abstract
Abstract Background Hidradenitis suppurativa (HS) is a painful chronic, recurrent inflammatory skin disease with great impact on health‐related quality of life (HRQOL). Recently, Hidradenitis SuppuraTiva cORe outcomes set International Collaboration (HISTORIC) established HRQOL as a core domain set for HS clinical trials and developed the Hidradenitis Suppurativa Quality of Life (HiSQOL) as a validated outcome measurement instrument. Objectives To provide further convergent validity of HiSQOL by comparing it to Dermatology Life Quality Index (DLQI) and Pictorial Representation of Illness and Self Measure‐Revised 2 (PRISM‐R2). Methods In this cross‐sectional study, 103 participants completed HiSQOL, PRISM‐R2 and DLQI. PRISM‐R2 is an instrument designed to measure suffering and reports the two measures, Illness Perception Measure (IPM) and Self‐Illness Separation (SIS). Correlation analyses were performed including a sub‐analysis for a subgroup of patients with high scores in the HS‐specific domains of HiSQOL. Results A very strong correlation was found between HiSQOL and DLQI (ρ = 0.93, P < 2.2 × 10−16, (95% CI: 0.89;0.95)), and moderately strong correlations were found between HiSQOL and SIS (ρ = −0.73, P < 2.2 × 10−16, (95% CI: −0.81; −0.62)) and DLQI and SIS (ρ = −0.70, P < 2.2 × 10−16, (95% CI: −0.79; −0.59)). IPM was positively associated with HiSQOL and DLQI and negatively with SIS. Conclusions HiSQOL is a valid measure of quality of life for HS patients, and we suggest that HiSQOL can be used as a measure of suffering as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".