Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder
The study objective was to identify distinct profiles of pregnant persons with opioid use disorder (PP-OUD) using cluster analysis and examine difference in substance use patterns between profiles. We examined data from 104 PP-OUD ≤ 32 weeks of gestation who were recruited into a behavioral health c...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-06-01
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| Series: | Addictive Behaviors Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352853223000068 |
| _version_ | 1797804611529080832 |
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| author | Elizabeth Charron Ziji Yu Brad Lundahl John Silipigni Akiko Okifuji Adam J. Gordon Jacob D. Baylis Ashley White Kristi Carlston Walitta Abdullah Benjamin Haaland Elizabeth E. Krans Marcela C. Smid Gerald Cochran |
| author_facet | Elizabeth Charron Ziji Yu Brad Lundahl John Silipigni Akiko Okifuji Adam J. Gordon Jacob D. Baylis Ashley White Kristi Carlston Walitta Abdullah Benjamin Haaland Elizabeth E. Krans Marcela C. Smid Gerald Cochran |
| author_sort | Elizabeth Charron |
| collection | DOAJ |
| description | The study objective was to identify distinct profiles of pregnant persons with opioid use disorder (PP-OUD) using cluster analysis and examine difference in substance use patterns between profiles. We examined data from 104 PP-OUD ≤ 32 weeks of gestation who were recruited into a behavioral health clinical trial at two academic medical centers. We used Partitioning Around Medoids analysis to identify clusters and explored patterns of substance use and substance use treatment between clusters using bivariate statistical tests and regression methods. We identified two distinct clusters of participants, including ‘Group A’ (n = 68; 65.4 %) and ‘Group B’ (n = 36; 34.6 %). Group A had fewer members who were not employed (38 % vs 58 %) and incarcerated (3 % vs 8 %) compared to Group B. Group A compared with Group B included more members with: a history of overdose (72 % vs 50 %); anxiety (85 % vs 25 %); ≥moderate pain (76 % vs 22 %); ≥moderate depression (75 % vs 36 %); ≥moderate drug use severity (94 % vs 78 %); and, more days of cannabis (mean: 6.2 vs 2.3 days), stimulant (mean: 4.5 vs 1.3 days), and injection heroin (mean: 1.3 vs 0 days) use in the past 30 days (P < 0.05 for all comparisons). Clusters of PP-OUD differed with respect to sociodemographic characteristics, mental health conditions, and substance use patterns. More research is needed to confirm identified profiles and assess treatment outcomes associated with cluster membership. |
| first_indexed | 2024-03-13T05:39:48Z |
| format | Article |
| id | doaj.art-aa9b76773d8247e3945e2049d08c11d6 |
| institution | Directory Open Access Journal |
| issn | 2352-8532 |
| language | English |
| last_indexed | 2024-03-13T05:39:48Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Addictive Behaviors Reports |
| spelling | doaj.art-aa9b76773d8247e3945e2049d08c11d62023-06-14T04:33:34ZengElsevierAddictive Behaviors Reports2352-85322023-06-0117100484Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorderElizabeth Charron0Ziji Yu1Brad Lundahl2John Silipigni3Akiko Okifuji4Adam J. Gordon5Jacob D. Baylis6Ashley White7Kristi Carlston8Walitta Abdullah9Benjamin Haaland10Elizabeth E. Krans11Marcela C. Smid12Gerald Cochran13Department of Health Promotion Sciences, Hudson College of Public Health, University of Oklahoma, Schusterman Center, Tulsa, OK, United States; Program of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States; Corresponding author at: Department of Health Promotion Sciences, Hudson College of Public Health, University of Oklahoma, Tulsa Schusterman Center, 4502 E. 41st Street, Tulsa, OK 74135, United States.Program of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United StatesCollege of Social Work, University of Utah, Salt Lake City, UT, United StatesDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, United StatesDepartment of Anesthesiology, University of Utah School of Medicine, Salt Lake City, UT, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States; Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, UT, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United StatesDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, United StatesDepartment of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, United StatesDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, United States; Center for Perinatal Addiction Research, Education and Evidence-based Solutions (Magee CARES), Magee-Womens Research Institute, Pittsburgh, PA, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States; Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, University of Utah Health, Salt Lake City, UT, United StatesProgram of Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United StatesThe study objective was to identify distinct profiles of pregnant persons with opioid use disorder (PP-OUD) using cluster analysis and examine difference in substance use patterns between profiles. We examined data from 104 PP-OUD ≤ 32 weeks of gestation who were recruited into a behavioral health clinical trial at two academic medical centers. We used Partitioning Around Medoids analysis to identify clusters and explored patterns of substance use and substance use treatment between clusters using bivariate statistical tests and regression methods. We identified two distinct clusters of participants, including ‘Group A’ (n = 68; 65.4 %) and ‘Group B’ (n = 36; 34.6 %). Group A had fewer members who were not employed (38 % vs 58 %) and incarcerated (3 % vs 8 %) compared to Group B. Group A compared with Group B included more members with: a history of overdose (72 % vs 50 %); anxiety (85 % vs 25 %); ≥moderate pain (76 % vs 22 %); ≥moderate depression (75 % vs 36 %); ≥moderate drug use severity (94 % vs 78 %); and, more days of cannabis (mean: 6.2 vs 2.3 days), stimulant (mean: 4.5 vs 1.3 days), and injection heroin (mean: 1.3 vs 0 days) use in the past 30 days (P < 0.05 for all comparisons). Clusters of PP-OUD differed with respect to sociodemographic characteristics, mental health conditions, and substance use patterns. More research is needed to confirm identified profiles and assess treatment outcomes associated with cluster membership.http://www.sciencedirect.com/science/article/pii/S2352853223000068Cluster analysisOpioid use disorderPerinatalPregnancySubstance use |
| spellingShingle | Elizabeth Charron Ziji Yu Brad Lundahl John Silipigni Akiko Okifuji Adam J. Gordon Jacob D. Baylis Ashley White Kristi Carlston Walitta Abdullah Benjamin Haaland Elizabeth E. Krans Marcela C. Smid Gerald Cochran Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder Addictive Behaviors Reports Cluster analysis Opioid use disorder Perinatal Pregnancy Substance use |
| title | Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| title_full | Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| title_fullStr | Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| title_full_unstemmed | Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| title_short | Cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| title_sort | cluster analysis to identify patient profiles and substance use patterns among pregnant persons with opioid use disorder |
| topic | Cluster analysis Opioid use disorder Perinatal Pregnancy Substance use |
| url | http://www.sciencedirect.com/science/article/pii/S2352853223000068 |
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