A Multi-Dimensional Conceptual Framework for Trauma-Informed Practice in Addictions Programming
Bibliographic record
Abstract
Previous research has conceptualized trauma-informed practice in relation to five key values: safety, trust, choice, collaboration, and empowerment. This research identifies key organizational, programmatic, and interpersonal characteristics in community-based residential addictions treatment programming that exemplify each of these principles. Utilizing qualitative research methods, involving open-ended, one to one interviews with clients in residential substance misuse treatment (n = 41), respondents identified the importance of experiencing “safety” in relation to physical safety, confidentiality, reassurance, rule enforcement, and peer relationships. “Trust” was manifested in sharing, staff availability, nonjudgmental interactions, positive relationship dynamics, and caring. “Choice” was articulated in relation to individual needs, participation, opportunities, and focus of efforts. “Collaboration” was characterized in relation to opportunities for feedback, planning, goal setting, specificity, and support. Finally, “empowerment” was characterized by comfort in sharing, trigger management, trauma awareness, and understanding. The findings provide a conceptual framework for a trauma-informed social services organizational practice environment. Findings can inform adaptations to social service delivery processes and programs to become aligned with the values of trauma-informed practice. Future research can build on this framework by testing the study findings with quantitative methods along with replicating current methods in other social service delivery sectors.
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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 | 0.026 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".