Family burden among US adults experiencing secondhand harms from alcohol, cannabis or other drugs
Bibliographic record
Abstract
Background: Family burden has not been studied in relation to alcohol and other drug harms from others. We adapted a family burden scale from studies of caring for those with mental health conditions for use in the US Alcohol and Drug Harm to Others Survey (ADHTOS). We investigated associations between a seven-item summative burden scale and different types of harms attributed to someone else’s use of alcohol, cannabis, or another drug: (a) being assaulted/physically harmed; (b) having family/partner problems; (c) feeling threatened or afraid; and (d) being emotionally hurt/neglected due to others’ substance use. Methods: A survey of adults aged 18 years and over conducted between October 2023 and July 2024 (n = 8,311), involved address-based sampling (n = 3,931 including 193 mail-backs) and web panels (n = 4,380), oversampling Black (n = 951), Latinx (n = 790) and sexual or gender minority (SGM) respondents (n = 309). Data from seven items on types of burdens experienced from other people’s alcohol or drug use were provided by those harmed by someone else’s alcohol or drug use and were used to create a burden scale. Analyses used negative binomial regression on burden sum adjusting for covariates, such as age, gender, race and ethnicity, marital status and years of education. Results: The single factor burden scale showed good internal consistency (α = .91). Components assessing being emotionally drained/exhausted and family friction/arguments were endorsed by 38–39% of participants; finding stigma of the other’s substance use upsetting was affirmed by 33%. Fewer endorsed feeling trapped in caregiving roles (22%), problems outside the family (26%), neglect of other family members’ needs (16%), and having to change plans (14%). In adjusted regression models, seven of eight harm exposures were significantly associated with burden scores. Discussion: People reported substantial burden from others’ use of alcohol, cannabis, and other drugs. Family support interventions and policy remedies to mitigate these burdens are needed.
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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 | 0.001 |
| 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".