The European Portuguese version of the insomnia severity index
Bibliographic record
Abstract
Summary Insomnia is the most prevalent sleep complaint, but remains largely an unidentified public health issue. The Insomnia Severity Index (ISI) is a brief self‐report questionnaire to assess insomnia, long‐established both in clinical and research settings. The present study aimed to analyse the reliability, validity, and accuracy of the ISI European Portuguese version. After the translation protocol, 1,274 participants (65.54% female), with a mean (SD, range) age of 37.52 (16.82, 18–95) years, completed the ISI. This sample included 250 patients with insomnia from a Sleep Medicine Centre, presenting a diagnosis of insomnia disorder (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; International Classification of Sleep Disorders, Third Edition), and 1,024 individuals from the community. A group of 30 patients with obstructive sleep apnea (OSA) was also recruited. Cronbach’s α was 0.88 (internal consistency), and corrected item‐total correlations ranged from 0.56 to 0.83. An exploratory factor analysis (oblique rotation) revealed a two‐factor solution for both clinical and community samples. The ISI total score significantly differentiated insomnia disorder, no insomnia, and OSA subgroups with a large effect size (η 2 = 0.42). The correlation between ISI and Pittsburgh Sleep Quality Index supported concurrent validity (0.82), and discriminant validity was confirmed by a moderate correlation between ISI and Beck Depression Inventory Second Edition (0.32). The area under the curve was 0.88, and the optimal cut‐off to detect clinical insomnia was 14 (82.1% sensitivity, 79.5% specificity). In conclusion, the Portuguese version of the ISI is a reliable and valid measure of insomnia in clinical and non‐clinical populations. Our present study also contributes to relevant data for the international literature regarding the cut‐off score of the scale for the detection of clinical insomnia.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".