Evidence map›Paper›PMID 38151524›Full record

ArticleScientific reports2023

Leveraging stylometry analysis to identify unique characteristics of peer support user groups in online mental health forums.

Yong-Bin Kang, Anthony McCosker, Jane Farmer

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

3 authors at 2 institutions in 1 country.

Yong-Bin KangAustralian Research Council (ARC) Centre of Excellence for Automated Decision-Making and Society (ADM+S), Swinburne University of Technology, Hawthorn, VIC, 3122, Australia. ykang@swin.edu.au.
Anthony McCoskerAustralian Research Council (ARC) Centre of Excellence for Automated Decision-Making and Society (ADM+S), Swinburne University of Technology, Hawthorn, VIC, 3122, Australia.
Jane FarmerSocial Innovation Research Institute, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia.
Swinburne University of Technology · AUAustralian Research Council · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Online peer support mental health forums provide an effective and accessible form of support, augmenting scarce clinical and face-to-face assistance. However, to enhance their effectiveness, it is essential to understand the unique characteristics of peer support user groups, and how they participate, contribute and communicate in these forums. This paper proposes and tests a novel approach that leverages stylometry analysis to uncover the unique characteristics of peer support user groups in such forums. Our approach identifies how each group empowers and supports other users, and what distinguishes them from others. The analysis shows that emotion-related words are crucial in identifying and distinguishing user groups based on their writing style. Comparative analysis of emotion expressions across user groups also uncovers the significance of emotional content in these forums in promoting mental well-being. Valued 'senior contributors' were more likely than all other groups including trained community guides to use a wide range of both positive and negative emotions in their posts. These findings have significant implications for improving the training of peer-mentors and moderators, scaling forum services, and improving guidelines for emotional expression among peer support users. Our approach presents an objective approach to differentiating the characteristics and communication patterns of valued senior contributors, mentors, and guides, enabling service providers to foster the kinds of communication that supports positive outcomes for distressed users.

Indexed as

CommunicationMental HealthEmotionsHumansInternetMentorsPeer Group

Identifiers

PMID38151524
PMCPMC10752871
OpenAlexW4390263711

What OpenQuestion 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 OpenQuestion graph.