Individuals Experiencing Homelessness: A Systematic Review of Otolaryngology‐Related Health Needs and Community‐Based Interventions
Bibliographic record
Abstract
OBJECTIVE: Access to and use of physician services is limited for those experiencing homelessness. Homelessness may predispose patients to several Otolaryngology-Head and Neck Surgery (OHNS) health conditions and barriers to care may leave these unaddressed. The aim of this review was to synthesize the literature on OHNS health needs and community-based interventions for patients experiencing homelessness. DATA SOURCES: English literature was searched in MEDLINE, EMBASE, and CINAHL. REVIEW METHODS: Studies were included if they reported on OHNS-related conditions in patients experiencing homelessness and/or interventions related to providing OHNS care to this patient population. RESULTS: Twelve hundred and one articles were screened, and 12 articles were included. Most studies reported on otologic conditions (n = 8) and head and neck-related conditions (n = 6). Nasal trauma, chronic rhinosinusitis, dysphonia, hearing loss, and cancerous/precancerous head and neck lesions were common OHNS conditions reported in this patient population. Identified barriers to care included lack of transportation, financial considerations, and lower health literacy. Three articles on community-based interventions were included. Most of these interventions were single visits to shelters, and ensuring adequate follow-up was identified as a challenge. CONCLUSION: The current literature brings attention to certain OHNS diseases that are prevalent in this unique patient population and identifies unique barriers these patients experience when accessing care. Future studies should focus on further delineating the impact of OHNS diseases in patients experiencing homelessness and screening interventions that can be employed to mitigate the impact of diseases of the head and neck.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".