ArticleBMC psychiatry2022
Mental health-related communication in a virtual community: text mining analysis of a digital exchange platform during the Covid-19 pandemic.
Article in BMC psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review.JMIR mental health · 2024Pooled it
- Text mining method to unravel long COVID's clinical condition in hospitalized patients.Cell death & disease · 2024Article
- Korean adolescents' coping strategies on self-harm, ADHD, insomnia during COVID-19: text mining of social media big data.Frontiers in psychiatry · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVirtual communities played an important role in mental health and well-being during the Covid-19 pandemic by providing access to others and thereby preventing loneliness. The pandemic has accelerated the urge for digital solutions for people with pre-existing mental health problems. So far, it remains unclear how the people concerned communicate with each other and benefit from peer-to-peer support on a moderated digital platform.
objectiveThe aim of the project was to identify and describe the communication patterns and verbal expression of users on the inCLOUsiv platform during the first lockdown in 2020.
methodsDiscussions in forums and live chats on inCLOUsiv were analysed using text mining, which included frequency, correlation, n-gram and sentiment analyses.
resultsThe communication behaviour of users on inCLOUsiv was benevolent and supportive; and 72% of the identified sentiments were positive. Users addressed the topics of 'corona', 'anxiety' and 'crisis' and shared coping strategies.
conclusionsThe benevolent interaction between users on inCLOUsiv is in line with other virtual communities for Covid-19 and the potential for peer-to-peer support. Users can benefit from each other's experiences and support each other. Virtual communities can be used as an adjuvant to existing therapy, particularly in times of reduced access to local health services.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.