LISTEN: lived experiences of Long COVID: a social media analysis of mental health and supplement use

The findings contribute to a better understanding of the complex nature of Long COVID and inform the development of comprehensive, patient-centered care strategies addressing both physical and mental health needs.

Authors

Institutions

Publication Details

Journal
Frontiers in Big Data
Published
2025-06-18
DOI
https://doi.org/10.3389/fdata.2025.1539724
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

LISTEN: lived experiences of Long COVID: a social media analysis of mental health and supplement use

Cecilia Vindrola‐Padros, Hương Giang Lê, Sigrún Eyrúnardóttir Clark, Sam Martin et al.
Frontiers in Big Data
Long-Term Effects of COVID-19
article

LISTEN: lived experiences of Long COVID: a social media analysis of mental health and supplement use

Cecilia Vindrola‐Padros, Hương Giang Lê, Sigrún Eyrúnardóttir Clark, Sam Martin, Samantha Vanderslott, Clair L. Firth, Norha Vera San Juan, Abinaya Chandrasekar, Maya Janse Van Rensburg
article en

Abstract

The findings contribute to a better understanding of the complex nature of Long COVID and inform the development of comprehensive, patient-centered care strategies addressing both physical and mental health needs.

Frontiers in Big DataVol. 8
Oxford BioMedica (United Kingdom) (GB), University College London (GB)
UK Research and Innovation, Medical Research Council
Openalex Percentile: Top 78%
Long-Term Effects of COVID-19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.