Meeting the Needs of Women: Current Treatment Options Available for Women Who Have a History of Physical, Sexual or Emotional Trauma and are Current Substance Users
Bibliographic record
Abstract
There is growing research which describes a strong relationship between early trauma and abuse histories with adult substance abuse. This relationship has often been explained as a coping tool by women who learn to self‐medicate the distress created by abuse. (Eliason, 2006) Although this link has been researched and treatment options explored, counselling services, substance abuse treatment programs and health service programs have only recently come together to address the intersections of past trauma, substance abuse and vulnerability in terms of affecting negative health and treatment outcomes. (Poole & Greaves, 2007) Women with both trauma and substance use issues have had to catalogue their needs and seek separate services, which has often led to incompatible treatment programs. Women who seek out treatment to address issues of sexual trauma may jeopardize their sobriety when strong feelings surface in the counselling process, resulting in a relapse. (Poole & Greaves, 2007) Combining treatments for trauma and substance use may be more effective for clients, and may also be more cost effective in using resources. There is a need for more research to gather additional data and determine the significance and result of treatment outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".