Agreement Among Subjective, Objective, and Collateral Measures of Insomnia in Postwithdrawal Recovering Alcoholics
Bibliographic record
Abstract
The level of agreement among objective, subjective, and collateral assessments of insomnia was examined in 56 recovering alcoholics. Participants underwent a multimodal sleep assessment protocol consisting of sleep logs, actigraph recordings, questionnaires, and collateral reports of insomnia severity. All sleep measures confirmed moderate to severe insomnia in the study sample. Over 1 week of simultaneous sleep log and actigraph recording, the average disagreement between methods ranged from 16 min for sleep onset latency to 1 hr for wake time after sleep onset. Interrater agreement for the severity of insomnia symptoms using the Sleep Impairment Index was poor for subject-clinician, subject-collateral, and collateral-clinician rating pairs (intraclass correlation coefficients < .35). In general, recovering alcoholics' self-reported sleep reflected a greater severity of insomnia symptoms than did the actigraph and collateral measures. Given that such high levels of disagreement can occur in individual participants, researchers are advised to use a combination of sleep measures to assess insomnia in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".