Perspectives on research and health of individuals with lived experience of opioid use in pregnancy
Bibliographic record
Abstract
Opioid use in Canada has been on the rise over the past two decades, and many individuals who use opioids are of child-bearing age. Although significant research exists on the effects of opioid use in pregnancy for both the pregnant individual and the child, few studies to date have engaged individuals with lived experience of opioid use in pregnancy to determine research priorities that are important to this population. From November 2022 to August 2023, twelve interviews were conducted with individuals who have used opioid in pregnancy. Participants were given space to share their story and questioned on research priorities that were meaningful to them. Data were coded and analyzed with Dedoose, using a hermeneutic phenomonelogical framework. Relative to personal experience and research guidance shared by birth parents, five themes were identified: 1) addiction and mental health; 2) impact of Child and Family Services; 3) lack of knowledge within the healthcare system; 4) stigmatizing interactions with the health care system; and 5) recommendations for future research. Individuals articulated the need for positive, trusting, and non-judgemental relationships between researchers, health care practitioners, and patients with opioid-affected pregnancies. Participants expressed the need for detailed information on best practices in opioid use and pregnancy, resources available to parents, and short and long-term effects of opioid use in pregnancy. Majority of participants expressed a desire for further clinical and social research on opioid-affected pregnancies. Future research and health care interactions with individuals with opioid-affected pregnancies must be founded in principles of non-judgemental care, harm reduction, relationship-building and reducing stigma.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".