AI Article Synopsis
- Depression affects over 280 million people worldwide, but many struggle with undiagnosed or untreated cases due to stigma and lack of awareness.
- Social media, particularly X (formerly Twitter), can be utilized to monitor signs of depression, with a study analyzing 246,637 tweets from diagnosed users to identify themes related to their experiences before and after diagnosis.
- Machine learning techniques, like logistic regression and support vector machines, were employed to differentiate between tweets from depressed and non-depressed users, highlighting the potential of Twitter data in tracking depression and understanding symptom changes and coping strategies.
Article Abstract
Depression affects over 280 million people globally, yet many cases remain undiagnosed or untreated due to stigma and lack of awareness. Social media platforms like X (formerly Twitter) offer a way to monitor and analyze depression markers. This study analyzes Twitter data 90 days before and 90 days after a self-disclosed clinical diagnosis. We gathered 246,637 tweets from 229 diagnosed users. CorEx topic modeling identified seven themes: causes, physical symptoms, mental symptoms, swear words, treatment, coping/support mechanisms, and lifestyle, and conditional logistic regression assessed the odds of these themes occurring post-diagnosis. A control group of healthy users (284,772 tweets) was used to develop and evaluate machine learning classifiers-support vector machines, naive Bayes, and logistic regression-to distinguish between depressed and non-depressed users. Logistic regression and SVM performed best. These findings show the potential of Twitter data for tracking depression and changes in symptoms, coping mechanisms, and treatment use.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11624259 | PMC |
| http://dx.doi.org/10.1038/s44184-024-00107-5 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Lifestyle and Health Behavior Changes in the COVID-19 Pandemic: A Role for Mental Health Symptoms and Diagnosis and Daily Life Difficulties During Lockdown in Lebanon.
Behav Med
January 2025
Clinical Research Institute, Department of Internal Medicine, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.
Several studies report significant changes in lifestyle habits during the COVID-19 pandemic, yet results are largely heterogeneous across populations. We examined changes in lifestyle and health behaviors during the first COVID-19 lockdown in Lebanon and assessed whether mental and physical health indicators and outbreak- and lockdown-related factors are related to these changes. Data come from a cross-sectional online survey (May-June 2020) which assessed changes in smoking, alcohol, diet, eating behavior, physical activity, sleep hours, sleep satisfaction, social media use, self-rated health, and life satisfaction ( = 494).
View Article and Find Full Text PDFMolecular switch of the dendrite-to-spine transport of TDP-43/FMRP-bound neuronal mRNAs and its impairment in ASD.
Cell Mol Biol Lett
January 2025
PhD Program in Medical Neuroscience, Taipei Medical University, Taipei, Taiwan (R.O.C.).
Background: Regulation of messenger RNA (mRNA) transport and translation in neurons is essential for dendritic plasticity and learning/memory development. The trafficking of mRNAs along the hippocampal neuron dendrites remains translationally silent until they are selectively transported into the spines upon glutamate-induced receptor activation. However, the molecular mechanism(s) behind the spine entry of dendritic mRNAs under metabotropic glutamate receptor (mGluR)-mediated neuroactivation and long-term depression (LTD) as well as the fate of these mRNAs inside the spines are still elusive.
View Article and Find Full Text PDFBiased attention allocation in major depressive disorder: A replication and exploration of the potential effects of depression history.
J Affect Disord
January 2025
School of Psychological Sciences, Tel Aviv University, Tel-Aviv, Israel. Electronic address:
Background: Increased attention allocation to negative-valenced information and decreased attention allocation to positive-valenced information have been implicated in the etiology and maintenance of depression. The Matrix task, a free-viewing eye-tracking attention assessment task, has shown corroborating results, coupled with adequate reliability. Yet, replication efforts are still needed.
View Article and Find Full Text PDFStudying the Digital Intervention Engagement-Mediated Relationship Between Intrapersonal Measures and Pre-Exposure Prophylaxis Adherence in Sexual and Gender Minority Youth: Secondary Analysis of a Randomized Controlled Trial.
J Med Internet Res
January 2025
Department of Community Health Sciences, Boston University, Boston, MA, United States.
Background: Improving adherence to pre-exposure prophylaxis (PrEP) via digital health interventions (DHIs) for young sexual and gender minority men who have sex with men (YSGMMSM) is promising for reducing the HIV burden. Measuring and achieving effective engagement (sufficient to solicit PrEP adherence) in YSGMMSM is challenging.
Objective: This study is a secondary analysis of the primary efficacy randomized controlled trial (RCT) of Prepared, Protected, Empowered (P3), a digital PrEP adherence intervention that used causal mediation to quantify whether and to what extent intrapersonal behavioral, mental health, and sociodemographic measures were related to effective engagement for PrEP adherence in YSGMMSM.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!