Uncovering the Complexity of Perinatal Polysubstance Use Disclosure Patterns on X: Mixed Methods Study (Preprint)
Authors: Wu Dezhi , Shead Hannah , Ren Yang , Raynor Phyllis , Tao Youyou , Villanueva Harvey , Hung Peiyin , Li Xiaoming , Brookshire Robert G , Eichelberger Kacey , Guille Constance , Litwin Alain H , Olatosi Bankole 
Published: September 2024

BACKGROUND

According to the <i>Morbidity and Mortality Weekly Report</i>, 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 &gt;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 <i>alcohol and drugs</i> identified as the most mentioned. From the qualitative analysis, we identified 3 main themes: <i>nonsubstance</i>, <i>single substance</i>, and <i>polysubstance,</i> and 4 subthemes to contextualize the rationale of underlying PPU behaviors: <i>lifestyle</i>, <i>perceptions of others’ drug use</i>, <i>legal implications</i>, and <i>public health</i>.

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 <i>alcohol and drugs</i>, 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.