Barriers to Substance Use Treatment for Individuals with Substance Use Disorders
Bibliographic record
Abstract
Background: Although residential substance use treatment has been shown to improve substance use and other outcomes, most with substance use disorders (SUDs) never seek professional treatment. Much research has been done on the barriers to seeking treatment. However, greater understanding is needed of the similarities and differences in the perceptual barriers to treatment held by clients and staff. Methods: This paper (1) identifies and compares adult client vs. staff perceptions of barriers to substance use treatment, and (2) compares perceptions between an urban vs. rural treatment setting. Secondary analysis of transcripts of semi-structured interviews with clients (n = 61) and staff (n = 37) from a residential substance use treatment program in New York (urban) and in Virginia (rural). Transcriptions of interviews were formally analyzed by two analysts using framework analysis. Results: The major results indicate that personal barriers (83%) were cited more frequently than interpersonal (15%) and structural barriers (24%). Staff were more likely to cite interpersonal barriers (19% vs. 11%) and structural barriers (29% vs. 20%) than were clients. Conclusions: These findings further demonstrate that personal culpability and self-blame are often felt by those with SUDs and this sentiment is often reinforced by treatment providers. Interventions are needed that can reduce the stigma of SUD's, resulting in a shift away from the perception that barriers to treatment exist primarily at the personal level. Trial registration: The Office of Research Subjects Protection at Virginia Commonwealth University (approval #HM15020) and the University Committee on Activities Involving Human Subjects at New York University (approval #FY2016-56) approved the study procedures for the Virginia and New York studies, respectively.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".