Material hardship and secure firearm storage: findings from the 2022 behavioral risk factor Surveillance System
Bibliographic record
Abstract
BACKGROUND: Firearm secure storage is an important public health practice due to its potential impact on reducing the incidence of accidental injuries, suicides, and thefts. Yet, there is limited research on how economic conditions might shape firearm storage patterns. METHODS: This study explores the relationship between material hardship and firearm secure storage among firearm-owning households. Data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS) were analyzed, including responses from 7,197 firearm-owning adults in California, Minnesota, Nevada, and New Mexico. Multinomial logistic regression models assessed the relationship between levels of material hardship and storage practices, adjusting for demographic and socioeconomic factors. RESULTS: Among respondents, 14.3% reported firearms were stored, loaded and unlocked. Compared to respondents experiencing no hardships, those experiencing three or more material hardships incurred a 183% higher risk of storing firearms in an unsecured manner (Relative Risk Ratio = 2.828, 95% CI = 1.286, 6.220). CONCLUSION: This study highlights an association between greater material hardship and unsecured firearm storage. These findings emphasize the need for public health interventions that address economic barriers to safe firearm storage, potentially reducing firearm-related injuries and deaths among individuals experiencing material hardship.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".