Examining barriers to harm reduction and child welfare services for pregnant women and mothers who use substances using a stigma action framework
Bibliographic record
Abstract
Pregnant women and mothers who use substances often face significant barriers to accessing and engaging with substance use services. A scoping review was conducted in 2019 to understand how stigma impacts access to, retention in and outcomes of harm reduction and child welfare services for pregnant women and mothers who use substances. The forty-two (n = 42) articles were analysed using the Action Framework for Building an Inclusive Health System developed by Canada's Chief Public Health Officer to articulate the ways in which stigma and related health system barriers are experienced at the individual, interpersonal, institutional and population levels. Many articles highlighted barriers across multiple levels, 19 of which cited barriers at the individual level (i.e., fear and mistrust of child welfare services), 18 at the interpersonal level (i.e., familial and relational influence on accessing substance use treatment), 30 at the institutional level (i.e., high organisational expectations on women) and 17 at the population level (i.e., negative stereotypes and racism). Our findings highlight the interconnectedness of stigma and related barriers and the ways in which stigma at the institutional and population levels pervasively influence individual and interpersonal experiences of stigma. Despite a wealth of literature on barriers to treatment and support for pregnant women and mothers who use substances, there has been minimal focus on how systems can address these formidable barriers. This review highlights the ways in which the barriers are connected and identifies opportunities for service providers and policymakers to better support pregnant women and mothers who use substances.
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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 | 0.053 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".