دورية أكاديمية
Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study.
| العنوان: | Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study. |
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| المؤلفون: | Wu D; Department of Integrated Information Technology, University of South Carolina, Columbia, SC, United States., Shead H; Department of Mathematics, Augusta University, Augusta, GA, United States., Ren Y; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, United States., Raynor P; College of Nursing, University of South Carolina, Columbia, SC, United States., Tao Y; Department of Information Systems and Business Analytics, Loyola Marymount University, Los Angeles, CA, United States., Villanueva H; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, United States., Hung P; Arnold School of Public Health, University of South Carolina, Columbia, SC, United States., Li X; Arnold School of Public Health, University of South Carolina, Columbia, SC, United States., Brookshire RG; Department of Integrated Information Technology, University of South Carolina, Columbia, SC, United States., Eichelberger K; School of Medicine Greenville, University of South Carolina, Greenville, SC, United States.; Prisma Health, Greenville, SC, United States., Guille C; College of Medicine, Medical University of South Carolina, Charleston, SC, United States., Litwin AH; School of Medicine Greenville, University of South Carolina, Greenville, SC, United States.; Prisma Health, Greenville, SC, United States., Olatosi B; Arnold School of Public Health, University of South Carolina, Columbia, SC, United States. |
| المصدر: | Journal of medical Internet research [J Med Internet Res] 2024 Sep 20; Vol. 26, pp. e53171. Date of Electronic Publication: 2024 Sep 20. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: <2011- > : Toronto : JMIR Publications Original Publication: [Pittsburgh, PA? : s.n., 1999- |
| مواضيع طبية MeSH: | Substance-Related Disorders*/psychology , Substance-Related Disorders*/epidemiology , Social Media*/statistics & numerical data, Humans ; Female ; Pregnancy ; Disclosure/statistics & numerical data ; Perinatal Care/statistics & numerical data |
| مستخلص: | Background: According to the Morbidity and Mortality Weekly Report, polysubstance use among pregnant women is prevalent, with 38.2% of those who consume alcohol also engaging in the use of one or more additional substances. However, the underlying mechanisms, contexts, and experiences of polysubstance use are unclear. Organic information is abundant on social media such as X (formerly Twitter). Traditional quantitative and qualitative methods, as well as natural language processing techniques, can be jointly used to derive insights into public opinions, sentiments, and clinical and public health policy implications. Objective: Based on perinatal polysubstance use (PPU) data that we extracted on X from May 1, 2019, to October 31, 2021, we proposed two primary research questions: (1) What is the overall trend and sentiment of PPU discussions on X? (2) Are there any distinct patterns in the discussion trends of PPU-related tweets? If so, what are the implications for perinatal care and associated public health policies? Methods: We used X's application programming interface to extract >6 million raw tweets worldwide containing ≥2 prenatal health- and substance-related keywords provided by our clinical team. After removing all non-English-language tweets, non-US tweets, and US tweets without disclosed geolocations, we obtained 4848 PPU-related US tweets. We then evaluated them using a mixed methods approach. The quantitative analysis applied frequency, trend analysis, and several natural language processing techniques such as sentiment analysis to derive statistics to preview the corpus. To further understand semantics and clinical insights among these tweets, we conducted an in-depth thematic content analysis with a random sample of 500 PPU-related tweets with a satisfying κ score of 0.7748 for intercoder reliability. Results: Our quantitative analysis indicates the overall trends, bigram and trigram patterns, and negative sentiments were more dominant in PPU tweets (2490/4848, 51.36%) than in the non-PPU sample (1323/4848, 27.29%). Paired polysubstance use (4134/4848, 85.27%) was the most common, with the combination alcohol and drugs identified as the most mentioned. From the qualitative analysis, we identified 3 main themes: nonsubstance, single substance, and polysubstance, and 4 subthemes to contextualize the rationale of underlying PPU behaviors: lifestyle, perceptions of others' drug use, legal implications, and public health. Conclusions: This study identified underexplored, emerging, and important topics related to perinatal PPU, with significant stigmas and legal ramifications discussed on X. Overall, public sentiments on PPU were mixed, encompassing negative (2490/4848, 51.36%), positive (1884/4848, 38.86%), and neutral (474/4848, 9.78%) sentiments. The leading substances in PPU were alcohol and drugs, and the normalization of PPU discussed on X is becoming more prevalent. Thus, this study provides valuable insights to further understand the complexity of PPU and its implications for public health practitioners and policy makers to provide proper access and support to individuals with PPU. (©Dezhi Wu, Hannah Shead, Yang Ren, Phyllis Raynor, Youyou Tao, Harvey Villanueva, Peiyin Hung, Xiaoming Li, Robert G Brookshire, Kacey Eichelberger, Constance Guille, Alain H Litwin, Bankole Olatosi. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.09.2024.) |
| فهرسة مساهمة: | Keywords: Twitter; perinatal care; polysubstance use; pregnant care; prenatal care; sentiment analysis; social media |
| تواريخ الأحداث: | Date Created: 20240920 Date Completed: 20240920 Latest Revision: 20240920 |
| رمز التحديث: | 20240921 |
| DOI: | 10.2196/53171 |
| PMID: | 39302713 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1438-8871 |
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| DOI: | 10.2196/53171 |