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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Feb 20, 2023
Open Peer Review Period: Feb 20, 2023 - Apr 17, 2023
Date Accepted: Apr 11, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis

Swanson K, Ravi A, Saleh S, Weia B, Pleasants E, Arvisais-Anhalt S

Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis

J Med Internet Res 2023;25:e46655

DOI: 10.2196/46655

PMID: 37171873

PMCID: 10221497

The Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: A Content Analysis

  • Karl Swanson; 
  • Akshay Ravi; 
  • Sameh Saleh; 
  • Benjamin Weia; 
  • Elizabeth Pleasants; 
  • Simone Arvisais-Anhalt

ABSTRACT

Background:

The supreme court ruling in Dobbs v Jackson Women’s Health Organization overrules precedents established by Roe v Wade and Planned Parenthood v Casey and allows states to individually regulate access to abortion care services. While many states have passed laws to protect access to abortion services since the ruling, the ruling has also triggered the enforcement of existing laws and creation of new ones that ban or restrict abortion. In addition to denying patients to the full spectrum of reproductive health care, one major concern in the medical community is how the ruling will undermine trust in the patient-clinician relationship by influencing perceptions of the privacy of patient health information.

Objective:

To study the effect of recent abortion legislation on twitter user engagement, sentiment, and expressions of trust in clinicians and privacy of health information.

Methods:

We scraped tweets containing keywords of interest between Jan 1st 2020 – Oct 17th, 2022, to capture tweets posted before and after the supreme court decision. We the trained a Latent Dirichlet Allocation model to select tweets pertinent to the topic of interest and performed a sentiment analysis using a RoBERTa model and a causal impact time series analysis to examine engagement and sentiment. In addition, we used a Word2Vec model to study the terms of interest against a latent trust dimension to capture how expressions of trust for our terms of interest changed over time and used TFIDF to measure to volume of tweets before and after the decision with respect to negative and positive sentiment that map to our terms of interest.

Results:

Our study revealed 1) a transient increase in the number of daily users by 576.86% (95% CI: 545.34% - 607.92%), p < 0.001, tweeting about abortion, healthcare, and privacy of health information post decision; 2) a sustained and statistically significant decrease in the average daily sentiment on these topics by 19.81% (95% CI: 5-22.98%, -16.59%, p , 0.001 post decision ; 3) a decrease in the association of the latent dimension of trust across most clinician related and health information related terms of interest; 4) an increased frequency of tweets with these clinician related and health information related terms and concomitant negative sentiment in the post decision period.

Conclusions:

The study suggests that the Dobbs ruling has consequences for health systems and reproductive healthcare that extend beyond denying patients access to the full spectrum of reproductive health services. The finding of a decrease in expression of trust in clinicians and health information-related terms provides evidence to support advocacy and initiatives that proactively address concerns of trust in health systems and services. Clinical Trial: N/A


 Citation

Please cite as:

Swanson K, Ravi A, Saleh S, Weia B, Pleasants E, Arvisais-Anhalt S

Effect of Recent Abortion Legislation on Twitter User Engagement, Sentiment, and Expressions of Trust in Clinicians and Privacy of Health Information: Content Analysis

J Med Internet Res 2023;25:e46655

DOI: 10.2196/46655

PMID: 37171873

PMCID: 10221497

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