Selective attention to sleep in heavy and light social drinkers
Bibliographic record
Abstract
Introduction: Espie et al. (2006) propose a route into primary psychophysiological insomnia (PI) along the attention-intention-effort pathway which focuses on the inhibition of sleep-wake automaticity. A contributing factor to this is selective attention to sleep (alongside explicit intention to sleep and effort in the sleep engagement process). Previous research has established selective attention to sleep in PI by demonstrating altered attentional processing of sleep stimuli in PI compared to normal sleepers. With alcohol dependent individuals, who have also developed insomnia, having a 60% relapse rate compared to 30% in those without insomnia (Brower et al. 2001), understanding sleep in this population is relevant to both alcohol dependence research as well as research into development and maintenance of insomnia. \n \nMethod: An ICB flicker paradigm was employed to investigate \nwhether selective attention to sleep was present along the alcohol consumption spectrum. A between subjects design was used to analyse responses of heavy (more than 20 units per week) and light (less than 10 units per week) social drinkers obtained from a computer task presenting images of sleep salient, alcohol salient and neutral images. \n \nResults: We found a significant effect of stimulus type (sleep, alcohol or neutral) but no main effect of alcohol consumption (heavy or light). A significant interaction was found between sleep (poor or normal) and alcohol consumption. On further analysis, it was found that those poor sleepers who consumed higher levels of alcohol were \nsignificantly faster at identifying the sleep salient stimulus compared to poor sleepers who consumed lower amounts of alcohol. \n \nConclusion: This study suggests that poor sleepers who consume higher amounts of alcohol show an attentional bias towards sleep compared to normal sleepers, irrespective of alcohol consumption level, and poor sleepers who consume lower levels of alcohol. Further research is called for to understand the underlying mechanism behind the selective attention in this particular group and whether this effect is mediated by the individuals’ relationship with alcohol or sleep profile.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".