Help-seeking among pregnant and parenting women who use drugs: Mitigating stigma through relationships
Bibliographic record
Abstract
BACKGROUND: Pregnant and parenting women who use drugs experience high rates of stigma when navigating the health care system, due to the gendered impacts of punitive drug policies and assumptions that conflate substance use with an inability to parent. There is a lack of research examining how stigma uniquely impacts pregnant and parenting women who use drugs, particularly with regards to self-efficacy and motivations to access health and social services, and other personal experiences of help-seeking processes. This study explores how stigma is internalized, anticipated, and embodied in the context of help-seeking, among pregnant and parenting women who use drugs. METHODS: Semi-structured telephone interviews were conducted from October 2020-February 2021 with current and past clients of integrated treatment programs in Ontario, designed for women who are pregnant and parenting young children (n = 24). Participants were asked to reflect upon their service experiences prior to COVID-19. RESULTS: Applying an interpretive description approach, the following themes emerged: (1) stigma and avoidance of help-seeking (2) stigma at the structural level: barriers to care and (3) mitigating stigma to enhance help-seeking: facilitating recovery through relationships. CONCLUSION: Expressions of judgement have negative impacts on self-esteem and can foster internalized stigma, while disclosure of substance use in motherhood can threaten to damage interpersonal relationships. At the same time, supportive relationships can buffer against stigma-related harms. Service invisibility and implicit bias within the medical community further deter help-seeking, with negative past experiences compounding mistrust of the system. To promote conditions that are supportive of help-seeking and healthy outcomes for this population, compassion and empathy are critical.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".