Sleep, anxiety and fatigue in family members of patients admitted to the intensive care unit: a questionnaire study
Bibliographic record
Abstract
INTRODUCTION: Family members of critically ill patients often experience increased incidence of physical and mental health issues. One of the first ways family members suffer is by losing sleep. The purpose of this study is to understand sleep quality, levels of fatigue and anxiety, and factors contributing to poor sleep in adult family members of critically ill patients. METHODS: A questionnaire was designed to evaluate sleep, fatigue and anxiety during the intensive care unit (ICU) admission. We incorporated three validated instruments: General Sleep Disturbance Scale (GSDS), Beck Anxiety Index (BAI) and Lee Fatigue Scale (NRS-F). Adult family members of patients in ICU for more than 24 hours were approached for questionnaire completion. Patient demographics were recorded. RESULTS: The study population consisted of 94 respondents, (49.1 ± 12.9 years, 52.7% male); 43.6% were children and 21.3% were spouses of ICU patients. Sleep quality was rated as poor/very poor by 43.5% of respondents, and good/very good by 15.2%. The most common factors contributing to poor sleep were anxiety (43.6%), tension (28.7%) and fear (24.5%). Respondents' most common suggestions to improve sleep were more information regarding the patient's health (24.5%) and relaxation techniques (21.3%). Mean GSDS score was 38.2 ± 19.3, with 58.1% of respondents experiencing moderate to severe sleep disturbance. Mean BAI was 12.3 ± 10.2, with 20.7% of respondents experiencing moderate to severe anxiety. Mean NRS-F was 3.8 ± 2.5, with 57.6% of respondents experiencing moderate to high fatigue. Family members who spent one or more nights in the hospital had significantly higher GSDS, BAI and NRS-F scores. The patient's Acute Physiology and Chronic Health Evaluation (APACHE) II score at survey completion correlated significantly with family members' GSDS, BAI and NRS-F. CONCLUSION: The majority of family members of ICU patients experience moderate to severe sleep disturbance and fatigue, and mild anxiety.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".