Objective: This study describes the experience of pregnancy and childbirth from the perspective of women with opioid use disorder.
Methods: This qualitative study analyzed semi-structured interviews about the prenatal care and birth experience of nine women with opioid use disorder as a sub-analysis of a qualitative study of women with a history of sexual trauma. Transcripts were analyzed using inductive content analysis.
Results: Analysis revealed unique interactions with the healthcare system specific to pregnant women with opioid use disorder. Participants identified pregnancy as a reason to enter and maintain recovery and an increased availability of resources when pregnant. Yet during labor and birth, concerns regarding pain control, child protective services involvement and provider stigma led to negative interactions with the healthcare system.
Conclusion: Pregnant woman with opioid use disorder face unique challenges when seeking care. The perspectives of women with a history of opioid use disorder can inform creation of a harm reduction, non-stigmatizing model of prenatal, labor and birth, and postpartum care.
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http://dx.doi.org/10.1016/j.wombi.2020.01.006 | DOI Listing |
Curr Pain Headache Rep
January 2025
Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA, USA.
Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.
Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.
J Addict Med
January 2025
From the Division of General Internal Medicine, San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA (LWS); San Francisco Department of Public Health, San Francisco, CA (POC); Vital Strategies, New York, NY (KB, DC); Network for Public Health Law, Edina, MN (CSD); and New York University Grossman School of Medicine, New York, NY (CSD).
Stimulant use disorder (StUD) is a rapidly growing concern in the United States, with escalating rates of death attributed to amphetamines and cocaine. No medications are currently approved for StUD treatment, leaving clinicians to navigate off-label medication options. Recent studies suggest that controlled prescription psychostimulants such as dextroamphetamine, methylphenidate, and modafinil are associated with reductions in self-reported stimulant use, craving, and depressive symptoms.
View Article and Find Full Text PDFDrug Alcohol Depend Rep
March 2025
Center to Improve Veteran Involvement in Care, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, United States.
Aim: We examined differences in medications for opioid use disorder (MOUD) receipt between rural and urban veteran patients following initiatives within the US Department of Veterans Affairs (VA) to expand access to MOUD.
Methods: Data for this retrospective cohort study were obtained from the VA Corporate Data Warehouse, which contains national electronic health record data for all VA patients. The analytic sample included all patients diagnosed with OUD from 10/1/2018-9/30/20.
Addiction
January 2025
Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.
Background And Aim: Sedative, hypnotic or anxiolytic use disorders (SHA-UD) are defined by significant impairment or distress caused by recurrent sedative, hypnotic or anxiolytic use. This study aimed to measure trends in the prevalence of SHA-UD diagnoses in adolescent and young adult US Medicaid enrollees from 2001 to 2019.
Design: Annual, cross-sectional study, 2001-2019.
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