Examining Sleep Disturbance Among Sheltered and Unsheltered Transition Age Youth Experiencing Homelessness
Bibliographic record
Abstract
BACKGROUND: The estimated 3.5-million transition age youth (TAY) who experience homelessness in the United States annually are routinely exposed to inadequate sleep environments and other psychosocial risk factors for deficient sleep. Although staying in a shelter versus being unsheltered may facilitate sleep, research suggests that perceived safety wherever one sleeps may be just as important. In this study, which is the first known study to investigate sleep disturbances among TAY experiencing homelessness, we examine associations of sleep disturbances with sheltered status and perceived safety of usual sleep environment. METHODS: We surveyed TAY (aged 18-25) experiencing homelessness in Los Angeles, CA about their sleep, psychosocial health, and living situations. Participants (n=103; 60% sheltered) self-reported sleep disturbances using the Patient-Reported Outcomes Measurement Information System Sleep Disturbance short form, while individual items assessed sheltered status and perceived safety where they usually slept. Regression analyses examined associations of sheltered status and perceived sleep environment safety with sleep disturbance, adjusting for age, sex, race, self-rated health, depression symptoms, serious mental illness, high-risk drinking, and severe food insecurity. RESULTS: Twenty-six percent of participants reported moderate-severe sleep disturbances. Sleep disturbance was not associated with sheltered status, but was positively associated with feeling unsafe in one's sleep environment, depression symptoms, severe food insecurity, and decreased age. CONCLUSIONS: Our findings suggest that sleep disturbances among TAY experiencing homelessness are associated more closely with how safe one feels rather than one's sheltered status. This highlights the importance of providing safe places to live for sheltered and unsheltered TAY.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".