Evidence mapPaperPMID 39983050Full record

ArticleJMIR formative research2025

Investigating Reddit Data on Type 2 Diabetes Management During the COVID-19 Pandemic Using Latent Dirichlet Allocation Topic Modeling and Valence Aware Dictionary for Sentiment Reasoning Analysis: Content Analysis.

Meghan Nagpal, Niloofar Jalali, Diana Sherifali, Plinio Morita, Joseph A Cafazzo

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Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Meghan NagpalInstitute of Health Policy, Management, & Evaluation, Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 4th Floor, Toronto, ON, M5T 3M6, Canada, 1 416 978 4326, 1 416 978 7350.ORCID 0000-0002-5290-8809
Niloofar JalaliSchool of Public Health & Health Systems, University of Waterloo, Kitchener, ON, Canada.ORCID 0000-0002-7356-0573
Diana SherifaliSchool of Nursing, McMaster University, Hamilton, ON, Canada.ORCID 0000-0002-4423-3848
Plinio MoritaInstitute of Health Policy, Management, & Evaluation, Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 4th Floor, Toronto, ON, M5T 3M6, Canada, 1 416 978 4326, 1 416 978 7350.ORCID 0000-0001-9515-6478
Joseph A CafazzoInstitute of Health Policy, Management, & Evaluation, Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 4th Floor, Toronto, ON, M5T 3M6, Canada, 1 416 978 4326, 1 416 978 7350.ORCID 0000-0002-3114-4440

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Type 2 diabetes (T2D) is a chronic disease that can be partially managed through healthy behaviors. However, the COVID-19 pandemic impacted how people managed T2D due to work and school closures and social isolation. Moreover, individuals with T2D were at increased risk of complications from COVID-19 and experienced worsened mental health due to stress and anxiety. Objective: This study aims to synthesize emerging themes related to the health behaviors of people living with T2D, and how they were affected during the early stages of the COVID-19 pandemic by examining Reddit forums dedicated to people living with T2D. Methods: Data from Reddit forums related to T2D, from January 2018 to early March 2021, were downloaded using the Pushshift API; support vector machines were used to classify whether a post was made in the context of the pandemic. Latent Dirichlet allocation topic modelling was performed to identify topics of discussion across the entire dataset and a subsequent iteration was performed to identify topics specific to the COVID-19 pandemic. Sentiment analysis using the VADER (Valence Aware Dictionary for Sentiment Reasoning) algorithm was performed to assess attitudes towards the pandemic. Results: From all posts, the identified topics of discussion were classified into the following themes: managing lifestyle (sentiment score 0.25, 95% CI 0.25-0.26), managing blood glucose (sentiment score 0.19, 95% CI 0.18-0.19), obtaining diabetes care (sentiment score 0.19, 95% CI 0.18-0.20), and coping and receiving support (sentiment score 0.34, 95% CI 0.33-0.35). Among the COVID-19-specific posts, the topics of discussion were coping with poor mental health (sentiment score 0.04, 95% CI -0.01 to0.11), accessing doctor and medications and controlling blood glucose (sentiment score 0.14, 95% CI 0.09-0.20), changing food habits during the pandemic (sentiment score 0.25, 95% CI 0.20-0.31), impact of stress on blood glucose levels (sentiment score 0.03, 95% CI -0.03 to 0.08), changing status of employment and insurance (sentiment score 0.17, 95% CI 0.13-0.22), and risk of COVID-19 complications (sentiment score 0.09, 95% CI 0.03-0.14). Overall, posts classified as COVID-19-related (0.12, 95% CI 0.01-0.15) were associated with a lower sentiment score than those classified as nonCOVID (0.25, 95% CI 0.24-0.25). This study was limited due to the lack of a method for assessing the demographics of users and verifying whether users had T2D. Conclusions: Themes identified from Reddit data suggested that the COVID-19 pandemic significantly influenced how people with T2D managed their disease, particularly in terms of accessing care and dealing with the complications of the virus. Overall, the early stages of the pandemic negatively impacted the attitudes of people living with T2D. This study demonstrates that social media data can be a qualitative data source for understanding patient perspectives.

Indexed as

COVID-19Diabetes Mellitus, Type 2Health BehaviorSocial MediaHumansPandemicsSARS-CoV-2attitudesCOVID-19diabetesdiabetes mellitusDMhealth behaviorhealth knowledgepandemicspatient-generated health dataperspectivepracticeself-managementsocial mediaT2DM

Identifiers

PMID39983050
PMCPMC11870598

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.