Examining the effectiveness of psychological interventions for marginalised and disadvantaged women and individuals who have experienced gender-based violence: protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: Exposure to gender-based violence (GBV) has devastating psychological outcomes for victims/survivors. Particularly in conditions where GBV intersects with multiple forms of oppression, the negative impacts of violence are more challenging to overcome and potential pathways for recovery become less accessible. However, evidence regarding the availability and effectiveness of mental health interventions for GBV survivors from marginalised and disadvantaged communities has yet to be systematically integrated and synthesised. The proposed scoping review will examine the relevant literature regarding the availability and effectiveness of psychological interventions for survivors of GBV from marginalised and disadvantaged backgrounds. This review will (i) document what psychological interventions have been available and empirically established for marginalised and disadvantaged women and individuals with experiences of GBV, (ii) provide a narrative examination of the treatment outcomes of identified interventions regarding their effectiveness and (iii) examine the degree to which GBV interventions in selected sources are designed and applied with a recognition of the social determinants of mental health. METHODS AND ANALYSIS: The search for the proposed scoping review will include five electronic databases: PsycINFO, Scopus, Web of Science, Ovid Medline, and CINAHL. The database search will be completed in June 2022. An additional search will be conducted before the completion of the study in December 2022. The search will target research studies published after 2010. The primary eligibility criterion for study selection is having a focus on psychological interventions for GBV survivors from marginalised and disadvantaged groups. Two reviewers will conduct screening and data extraction. The data will be evaluated to map the treatment outcomes of interventions and their effectiveness. Implications for clinical services will be discussed. ETHICS AND DISSEMINATION: No ethical consideration is foreseen for this scoping review. The dissemination will be done through a publication in a top-tier open access journal and conference presentations.
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 | 0.104 | 0.104 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.020 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.013 |
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".