Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Sep 22;6(9):e39013.
doi: 10.2196/39013.

Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis

Yong-Bin Kang  1 , Anthony McCosker  1   2 , Peter Kamstra  2 , Jane Farmer  2
Affiliations

Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis

Yong-Bin Kang et al. JMIR Form Res. .

Abstract

Background: Resilience is an accepted strengths-based concept that responds to change, adversity, and crises. This concept underpins both personal and community-based preventive approaches to mental health issues and shapes digital interventions. Online mental health peer-support forums have played a prominent role in enhancing resilience by providing accessible places for sharing lived experiences of mental issues and finding support. However, little research has been conducted on whether and how resilience is realized, hindering service providers' ability to optimize resilience outcomes.

Objective: This study aimed to create a resilience dictionary that reflects the characteristics and realization of resilience within online mental health peer-support forums. The findings can be used to guide further analysis and improve resilience outcomes in mental health forums through targeted moderation and management.

Methods: A semiautomatic approach to creating a resilience dictionary was proposed using topic modeling and qualitative content analysis. We present a systematic 4-phase analysis pipeline that preprocesses raw forum posts, discovers core themes, conceptualizes resilience indicators, and generates a resilience dictionary. Our approach was applied to a mental health forum run by SANE (Schizophrenia: A National Emergency) Australia, with 70,179 forum posts between 2018 and 2020 by 2357 users being analyzed.

Results: The resilience dictionary and taxonomy developed in this study, reveal how resilience indicators (ie, "social capital," "belonging," "learning," "adaptive capacity," and "self-efficacy") are characterized by themes commonly discussed in the forums; each theme's top 10 most relevant descriptive terms and their synonyms; and the relatedness of resilience, reflecting a taxonomy of indicators that are more comprehensive (or compound) and more likely to facilitate the realization of others. The study showed that the resilience indicators "learning," "belonging," and "social capital" were more commonly realized, and "belonging" and "learning" served as foundations for "social capital" and "adaptive capacity" across the 2-year study period.

Conclusions: This study presents a resilience dictionary that improves our understanding of how aspects of resilience are realized in web-based mental health forums. The dictionary provides novel guidance on how to improve training to support and enhance automated systems for moderating mental health forum discussions.

Keywords: content moderation; mental health; peer-support forum; resilience dictionary; text analysis; topic modeling.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The 4-phase analysis pipeline that preprocesses forum posts, finds topics, conceptualizes resilience indicators, and builds a resilience dictionary. NMF: nonnegative matrix factorization; POS: parts of speech.
Figure 2
Figure 2
Conceptual illustration of constructing the matrix B by stacking up the matrices of H* generated by the first-layer nonnegative matrix factorization.
Figure 3
Figure 3
Illustration of the 2 steps used to annotate posts with their most relevant resilience indicators. The first step shows how to annotate each post with its most relevant topic from the document-ensemble topic matrix D in equation 1. The second step annotates each post with its most resilience indicators from the outcome of the first step and the mapped outcomes from topics to their most relevant resilience.
Figure 4
Figure 4
Summary of Schizophrenia: A National Emergency (SANE) forum posts in the sample 2018-Q3 to 2020-Q4.
Figure 5
Figure 5
The top 50 terms by word frequency observed from the 48,819 posts.
Figure 6
Figure 6
The 15 generated ensemble topics, where each topic is represented by its top 15 descriptive terms.
Figure 7
Figure 7
Resilience indicattor realizaion in Schizophrenia: A National Emergency (SANE) Australia.
Figure 8
Figure 8
The resilience taxonomy induced from the SANE (Schizophrenia: A National Emergency) Australia posts represented as a treemap that shows the coverage of the concept of each resilience indicator by its rectangle size.
See this image and copyright information in PMC

References

    1. Mental health: strengthening our response. World Health Organization. 2022. Jun 17, [2022-06-17]. https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthe... .
    1. Anderson K, Priebe S. Concepts of resilience in adolescent mental health research. J Adolesc Health. 2021 Nov;69(5):689–95. doi: 10.1016/j.jadohealth.2021.03.035.S1054-139X(21)00167-1 - DOI - PubMed
    1. Moßburger L, Wende F, Brinkmann K, Schmidt T. Exploring online depression forums via text mining: a comparison of Reddit and a curated online forum. Proceedings of the 5th Social Media Mining for Health Applications Workshop & Shared Task; SMM4H '20; June 28, 2020; Barcelona, Spain. 2020. pp. 70–81. https://aclanthology.org/2020.smm4h-1.11 - DOI
    1. Park I, Sarnikar S, Cho J. Disentangling the effects of efficacy-facilitating informational support on health resilience in online health communities based on phrase-level text analysis. Inf Manag. 2020 Dec;57(8):103372. doi: 10.1016/j.im.2020.103372. doi: 10.1016/j.im.2020.103372. - DOI - DOI
    1. Ritchie H. Global mental health: five key insights which emerge from the data. Our World In Data. 2018. May 16, [2021-09-16]. https://ourworldindata.org/global-mental-health .

LinkOut - more resources