Women's obstetric and reproductive health care discourse in online forums: Perceived access and quality pre- and post-Affordable Care Act

Williams, Serena; Dhillon, Soneet

doi:10.1016/j.ypmed.2019.04.013

Cited by 2 publications

(2 citation statements)

References 25 publications

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“…The ACA provides a variety of evidence-based preventative services to females with no out-of-pocket cost to women who have certain health plans which has the potential for improvement in health outcomes. [24][25][26][27][28] Williams previously reported that having insurance influences support for the ACA and Macabe reported that individuals who experienced a change in health insurance coverage where their coverage was changed unfavorably were more likely to disapprove of the ACA. [11,16] We found no statistical difference in support for the ACA based on a change in coverage.…”

Section: Discussionmentioning

confidence: 99%

Public perception of the United States’ Affordable Care Act

Molla

Bacon-Baguley²,

DeVuyst-Miller³

et al. 2019

IJH

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Background/Objective: Implementation of the Affordable Care Act (ACA) in the US has given opportunity to obtain health insurance for thousands who were previously uninsured. Many believe that the ACA is an improvement over previous insurance, while others view it as making health care more costly. The purpose of this study was to survey individuals regarding knowledge and perceptions of the ACA.Methods: Researchers in public health, physician assistant studies, pharmacy and medical education developed a survey to assess the impact of the ACA. The survey included demographic questions and statements which assessed ACA support, and perspectives of the ACA’s impact on pharmaceutical and medical coverage and personal out of pocket costs. A convenience sampling was used to recruit participants at a public venue in an urban setting.Results: Demographics of the 179 surveyed include: median age 31 years; 84% Caucasian; 37% married; 58% completed a minimum of four years of college; and 45% with income exceeding $50,000. 13 (7%) were uninsured before the ACA, and 8 (4%) after. 130 (73%) had prescription coverage before the ACA with 107 (60%) reported no change in coverage, 22 (12%) better coverage, and 21 (12%) less coverage after the ACA. An association for ACA support was found based on political affiliation with more Democrats than Republicans supporting the ACA (p < .001). 71 (71%) who support the ACA, reported insurance did not improved after the ACA.Conclusions: These findings identify that in a sample of upper middle class individuals, a majority support the ACA despite a lack of improvement in their own insurance indicating that personal sacrifice for the general population is occurring.

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Section: Discussionmentioning

confidence: 99%

Public perception of the United States’ Affordable Care Act

Molla

Bacon-Baguley²,

DeVuyst-Miller³

et al. 2019

IJH

View full text Add to dashboard Cite

show abstract

“…The data mining and sentiment analysis of social media, especially web-based medical discussion forums, can provide a fast and effective way to better understand patients' attitudes, expectations, and experiences [18], which can better guide patient-centric care [20]. The literature shows that health care professionals can, with the sentiment analysis of web-based medical forums, discover new outlooks of patient issues and recurrent complications related to specific treatment uses and drugs [19,21,22] and administrative burden and access to care [23]. By analyzing forum posts, physicians can further understand patients' attitudes and experiences and assess their needs and concerns, which can result in better patient-centric care [24].…”

Section: Introductionmentioning

confidence: 99%

Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions

Nguyen¹,

Trinh²,

Wang³

et al. 2021

J Med Internet Res

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Background Clinical data in social media are an underused source of information with great potential to allow for a deeper understanding of patient values, attitudes, and preferences. Objective This tutorial aims to describe a novel, robust, and modular method for the sentiment analysis and emotion detection of free text from web-based forums and the factors to consider during its application. Methods We mined the discussion and user information of all posts containing search terms related to a medical subspecialty (oculoplastics) from MedHelp, the largest web-based platform for patient health forums. We used data cleaning and processing tools to define the relevant subset of results and prepare them for sentiment analysis. We executed sentiment and emotion analyses by using IBM Watson Natural Language Understanding to generate sentiment and emotion scores for the posts and their associated keywords. The keywords were aggregated using natural language processing tools. Results Overall, 39 oculoplastic-related search terms resulted in 46,381 eligible posts within 14,329 threads. Posts were written by 18,319 users (117 doctors; 18,202 patients) and included 201,611 associated keywords. Keywords that occurred ≥500 times in the corpus were used to identify the most prominent topics, including specific symptoms, medication, and complications. The sentiment and emotion scores of these keywords and eligible posts were analyzed to provide concrete examples of the potential of this methodology to allow for a better understanding of patients’ attitudes. The overall sentiment score reflects a positive, neutral, or negative sentiment, whereas the emotion scores (anger, disgust, fear, joy, and sadness) represent the likelihood of the presence of the emotion. In keyword grouping analyses, medical signs, symptoms, and diseases had the lowest overall sentiment scores (−0.598). Complications were highly associated with sadness (0.485). Forum posts mentioning body parts were related to sadness (0.416) and fear (0.321). Administration was the category with the highest anger score (0.146). The top 6 forum subgroups had an overall negative sentiment score; the most negative one was the Neurology forum, with a score of −0.438. The Undiagnosed Symptoms forum had the highest sadness score (0.448). The least likely fearful posts were those from the Eye Care forum, with a score of 0.260. The overall sentiment score was much more negative before the doctor replied. The anger, disgust, fear, and sadness emotion scores decreased in likelihood, whereas joy was slightly more likely to be expressed after doctors replied. Conclusions This report allows physicians and researchers to efficiently mine and perform sentiment analysis on social media to better understand patients’ perspectives and promote patient-centric care. Important factors to be considered during its application include evaluating the scope of the search; selecting search terms and understanding their linguistic usages; and establishing selection, filtering, and processing criteria for posts and keywords tailored to the desired results.

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Women's obstetric and reproductive health care discourse in online forums: Perceived access and quality pre- and post-Affordable Care Act

Cited by 2 publications

References 25 publications

Public perception of the United States’ Affordable Care Act

Public perception of the United States’ Affordable Care Act

Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions

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