COVID-19 and pregnant and parenting women who use drugs: exploring the impact of stigmatization on help-seeking behaviour
Bibliographic record
Abstract
Stigma surrounding substance use has been documented as a roadblock to recovery, posing a greater barrier to care for some populations more than others. In particular, pregnant and parenting women are an often overlooked and understudied demographic who could benefit considerably from targeted resources. Though, due to stigma surrounding substance use and motherhood, this demographic is routinely subject to judgement and discrimination resulting in delayed treatment entry. In the midst of the COVID-19 pandemic, issues of access have been compounded by a reduction in services despite heightened mental health struggles caused by prolonged periods of isolation and abrupt changes in lifestyle and environment. The purpose of this study is to understand how stigmatization affects help-seeking behaviour and to explore the impact of COVID-19 on women’s mental health and treatment experiences. Semi-structured telephone interviews were conducted from October 2020-February 2021, with current and past clients of integrated treatment programs in Ontario (n=24). Using an interpretive description approach, data was constructed to identify how stigma is internalized, anticipated, and embodied in the context of help-seeking behaviour, as well as to determine the extent to which the pandemic has interfered with maternal wellbeing. The following themes emerged: (1) stigma and help-seeking (2) COVID-19 and maternal wellness (3) stigma at the structural level: barriers to care and (4) mitigating stigma to enhance help-seeking: facilitating recovery through relationships. This research contributes evidence to a growing body of literature emphasizing the importance of relationships in the recovery process for combatting the effects of stigma and promoting early treatment entry and lends insight into the ways in which pregnant and parenting women with problematic substance use have navigated recovery during COVID-19.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".