Semi-Automatic Creation of Resilience Dictionary for Strengths-based Text Analysis of Online Mental Health Forums (Preprint)

Author:

Kang Yong-BinORCID,McCosker AnthonyORCID,Kamstra PeterORCID,Farmer JaneORCID

Abstract

BACKGROUND

Resilience is an accepted strengths-based concept responding to change, adversity and crisis that involves a range of environmental, social and personal adaptive factors. The concept underpins both personal and community-based preventative approaches to mental health issues and has shaped digital interventions. Online peer-support mental health forums have played a prominent role in enhancing resilience by providing accessible places for sharing lived experiences of mental issues and finding support. Despite the significance and viability of such forums for complementing mental health care, there has been little research on whether and how resilience is realised, hindering service providers’ ability to demonstrate impact.

OBJECTIVE

This paper aims to create a resilience dictionary that reflects the characteristics and realisation of resilience within online mental health peer-support forums. The findings can be used to guide further analysis and inform strengths-based moderation and management of mental health forums.

METHODS

A semi-automatic approach to creating a resilience dictionary is proposed using topic modelling and qualitative content analysis. We present a systematic four-phase analysis pipeline that pre-processes raw forum posts, discovers main themes being discussed in the posts, conceptualises resilience indicators, and resilience dictionary creation. Our approach is applied to online peer-support mental health forums from 2018 to 2020 in SANE Australia, where 70,179 forum post data used by 2,357 users were collected and explored in this study.

RESULTS

The resilience dictionary and taxonomy developed in this study, reveal: (1) how resilience indicators (i.e., “social capital”, “belonging”, “learning”, “adaptive capacity”, and “self-efficacy”) are characterised by themes commonly discussed on the forums; (2) each theme’s top-10 most relevant descriptive terms and their synonyms; and (3) the relatedness of resilience, reflecting a taxonomy of indicators that are more comprehensive (or compound) and indicators that are more likely to facilitate the realisation of others. The study also presents the four-phase analysis pipeline that constructs a resilience dictionary from new forum datasets. Further, this study identifies the resilience indicators “learning”, “belonging” and “social capital” are more commonly realised resilience indicators, and "learning" and "belonging" serve as foundations for the realisation of “self-efficacy” and “adaptive capacity” across the two-year study period.

CONCLUSIONS

This paper presents a resilience dictionary that improves our understanding of how aspects of resilience are realised in online 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.

Publisher

JMIR Publications Inc.

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