Perceived Need for Care, Help Seeking, and Perceived Barriers to Care for Alcohol Use Disorders in a National Sample
Bibliographic record
Abstract
OBJECTIVE: The aims of this study were to examine the rates and correlates of help seeking, perceived need for care, and perceived barriers to care among people with an alcohol use disorder in a large nationally representative sample. METHODS: Data were drawn from the National Epidemiologic Survey on Alcohol and Related Conditions for persons 18 years and older (N=43,093). Three main groups were defined: people who sought help, people who perceived a need for care but did not seek help, and people who neither perceived a need nor sought help. RESULTS: Almost one-third (N=11,843, or 28%) of survey respondents met DSM-IV criteria for a lifetime alcohol use disorder. Most individuals with an alcohol use disorder (81%) did not report seeking care or perceiving a need for help. Those who were younger, were married, had higher income, had higher education, and did not have an adverse general medical condition were significantly less likely to perceive a need for help or to seek help for an alcohol use disorder. Respondents who did not perceive a need for help or seek it were significantly less likely to have an additional axis I or axis II disorder. CONCLUSIONS: Knowledge of the factors that influence perceived need for help could aid in developing interventions directed toward increasing the rates of help seeking among people with an alcohol use disorder. Regular screening for alcohol use disorders in primary health care settings is recommended.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".