Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums

Kushner, Taisa; Sharma, Amit

doi:10.1145/3366423.3380056

Cited by 17 publications

(13 citation statements)

References 28 publications

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“…Furthermore, our system was reported to assist the support providers by assisting them to learn how to react empathetically. Considering that such an empathetic reaction is a key to thriving OMHCs [19], we could see the feasibility of extending our work to long-term deployment settings. However, considering that some participants worried if our community setting might only be filled with monotonous, emotionally empathetic reactions, it is would also be beneficial to diversify the type of reactions (e.g., supporting energetic reactions) to enrich the community environment.…”

Section: Discussion and Limitationmentioning

confidence: 99%

“…For such OMHCs to thrive and individuals to improve mental health (e.g., reducing depression/anxiety), it is known that active sharing (e.g., sharing experiences, expressing emotions, and restructuring maladaptive cognition) are particularly crucial [19,20,23,30,33,34]. Specifically, previous works suggested that people were more satisfied when their received support matches the needed support [41,42], in the form of informational or emotional support.…”

Section: Related Work 21 Online Mental Health Communitymentioning

confidence: 99%

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Exploring the Effects of AI-assisted Emotional Support Processes in Online Mental Health Community

Shin,

Park,

Kim

et al. 2022

Preprint

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Section: Discussion and Limitationmentioning

confidence: 99%

Section: Related Work 21 Online Mental Health Communitymentioning

confidence: 99%

Exploring the Effects of AI-assisted Emotional Support Processes in Online Mental Health Community

Shin,

Park,

Kim

et al. 2022

Preprint

View full text Add to dashboard Cite

“…The communication between these support-seekers and providers usually happened in the posted threads created by the seekers, with text as the conversational medium [28,56,67]. Previous research has suggested that participating in the communication in OMHCs could improve members' mental health [34,46,57,58,61,64,68]. For example, Rains et al conducted a meta-analysis of computer-mediated support groups and found that long-term participation in such communities was associated with less depression, greater quality of life, and improved self-efficacy in managing their health conditions [61].…”

Section: Benefits Of Online Mental Health Communitiesmentioning

confidence: 99%

Effects of Support-Seekers’ Community Knowledge on Their Expressed Satisfaction with the Received Comments in Mental Health Communities

Peng

Yang

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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Online mental health communities (OMHCs) are prominent resources for improving people's mental wellbeing. An immediate cue of such improvement is support-seekers' satisfaction expressed in their replies to the received comments. However, the comments that seekers find satisfying may change with their community knowledge, e.g., measured by tenure and posting experience in that community. In this paper, we first model the amount of satisfaction conveyed in the support-seekers' replies to the received comments. Then we quantitatively examine how seekers' expressed satisfaction is affected by their community knowledge, sought and received support in an OMHC. Results show that support-seekers with more posting experience generally display less contentment to the received comments. Compared to newcomers, higher tenured members express less satisfaction when receiving informational support. We also found that support matching positively predicts seekers' satisfaction regardless of their community knowledge. Our findings have implications for OMHCs to satisfy support-seekers through their community knowledge. CCS CONCEPTS• Human-centered computing → Empirical studies in collaborative and social computing.

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“…For specialized OMHC platforms such as Talklife or 7Cups, recent studies have examined positive outcomes over a sample of users (Baumel et al 2018) or over a single thread or bursts of conversation (Kushner and Sharma 2020, Pruksachatkun et al 2019; Pendse et al 2019). We extend this research by focusing on long-term changes in one’s mental health over a large sample of individuals and retrospectively finding the most relevant causes.…”

Section: Background and Related Workmentioning

confidence: 99%

Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities

Saha

Sharma

2020

Preprint

Self Cite

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Online mental health communities enable people to seek and provide support, and growing evidence shows the efficacy of community participation to cope with mental health distress. However, what factors of peer support lead to favorable psychosocial outcomes for individuals is less clear. Using a dataset of over 300K posts by ∼39K individuals on an online community TalkLife, we present a study to investigate the effect of several factors, such as adaptability, diversity, immediacy, and the nature of support. Unlike typical causal studies that focus on the effect of each treatment, we focus on the outcome and address the reverse causal question of identifying treatments that may have led to the outcome, drawing on case-control studies in epidemiology. Specifically, we define the outcome as an aggregate of affective, behavioral, and cognitive psychosocial change and identify Case (most improved) and Control (least improved) cohorts of individuals. Considering responses from peers as treatments, we evaluate the differences in the responses received by Case and Control, per matched clusters of similar individuals. We find that effective support includes complex language factors such as diversity, adaptability, and style, but simple indicators such as quantity and immediacy are not causally relevant. Our work bears methodological and design implications for online mental health platforms, and has the potential to guide suggestive interventions for peer supporters on these platforms.

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Bursts of Activity: Temporal Patterns of Help-Seeking and Support in Online Mental Health Forums

Cited by 17 publications

References 28 publications

Exploring the Effects of AI-assisted Emotional Support Processes in Online Mental Health Community

Exploring the Effects of AI-assisted Emotional Support Processes in Online Mental Health Community

Effects of Support-Seekers’ Community Knowledge on Their Expressed Satisfaction with the Received Comments in Mental Health Communities

Causal Factors of Effective Psychosocial Outcomes in Online Mental Health Communities

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