Social isolation and firearm secure storage in the USA: results from the 2022 BRFSS
Bibliographic record
Abstract
BACKGROUND: Firearm secure storage (ie, storing firearms unloaded and locked) is recommended to reduce unintentional injuries and suicides. However, the relationship between psychological states, such as social isolation, and firearm secure storage practices is under-researched. METHODS: Data are from 7136 individuals with firearms in their households from the 2022 Behavioral Risk Factor Surveillance System. Multinomial logistic regression was used to explore the relationship between social isolation and firearm storage. RESULTS: Among respondents, 71.6% reported storing firearms unloaded, 14.2% stored firearms loaded and locked and 14.2% stored firearms loaded and unlocked. Most respondents reported feeling 'never' (40.7%) or 'rarely' (33.3%) socially isolated, with 18.7% reporting 'sometimes', 4.3% 'usually' and 3.0% 'always' feeling socially isolated. Covariate-adjusted multinomial logistic regression analysis revealed that respondents who felt 'always' socially isolated had an over threefold greater risk of storing firearms loaded and unlocked (relative risk ratio=3.733, 95% CI 1.443 to 9.662, p=0.007) compared with unloaded. CONCLUSION: Results suggest a link between feelings of social isolation and unsecured firearm storage. Public health strategies should address both firearm safety education and the underlying issue of social isolation.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".