The Impact of Linguistic Signals on Cognitive Change in Support Seekers in Online Mental Health Communities: Text Analysis and Empirical Study

被引:0
|
作者
Li, Min [1 ]
Gu, Dongxiao [1 ]
Li, Rui [1 ]
Gu, Yadi [2 ]
Liu, Hu [3 ]
Su, Kaixiang [1 ]
Wang, Xiaoyu [4 ]
Zhang, Gongrang [1 ]
机构
[1] Hefei Univ Technol, Sch Management, 193 Tunxi Rd, Hefei 230009, Peoples R China
[2] Univ Shanghai Sci & Technol, Ctr Mental Hlth Educ, Shanghai, Peoples R China
[3] Southeast Univ, Sch Management, Nanjing, Peoples R China
[4] Anhui Univ Tradit Chinese Med, Affiliated Hosp 1, Hefei, Peoples R China
基金
中国国家自然科学基金;
关键词
mental health; online communities; cognitive change; signaling theory; text analysis; NATURAL-LANGUAGE USE; SOCIAL SUPPORT; CONSTRUAL-LEVEL; COMMUNICATION; DISTRESS; EMPATHY; MEDIA; TIES;
D O I
10.2196/60292
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: In online mental health communities, the interactions among members can significantly reduce their psychological distress and enhance their mental well-being. The overall quality of support from others varies due to differences in people's capacities to help others. This results in some support seekers' needs being met, while others remain unresolved. Objective: This study aimed to examine which characteristics of the comments posted to provide support can make support seekers feel better (ie, result in cognitive change). Methods: We used signaling theory to model the factors affecting cognitive change and used consulting strategies from the offline, face-to-face psychological counseling process to construct 6 characteristics: intimacy, emotional polarity, the use of first-person words, the use of future-tense words, specificity, and language style. Through text mining and natural language processing (NLP) technology, we identified linguistic features in online text and conducted an empirical analysis using 12,868 online mental health support reply data items from Zhihu to verify the effectiveness of those features. Results: The findings showed that support comments are more likely to alter support seekers' cognitive processes if those comments have lower intimacy (beta(intimacy)=-1.706, P <.001), higher positive emotional polarity (beta (emotional_polarity) =.890, P <.001), lower specificity (beta (specificity) =-.018, P <.001), morefirst-person words (beta (first-person) =.120, P <.001), more future- and present-tense words (beta (future-words) =.301, P <.001), and fewer function words (beta (linguistic_style) =-.838, P <.001). The result is consistent with psychotherapists' psychotherapeutic strategy in offline counseling scenarios. Conclusions: Our research contributes to both theory and practice by proposing a model to reveal the factors that make support seekers feel better. The findings have significance for support providers. Additionally, our study offers pointers for managing and designing online communities for mental health.
引用
收藏
页数:16
相关论文
共 16 条
  • [1] An analysis of cognitive change in online mental health communities: A textual data analysis based on post replies of support seekers
    Gu, Dongxiao
    Li, Min
    Yang, Xuejie
    Gu, Yadi
    Zhao, Yu
    Liang, Changyong
    Liu, Hu
    INFORMATION PROCESSING & MANAGEMENT, 2023, 60 (02)
  • [2] Mental Health Support and its Relationship to Linguistic Accommodation in Online Communities
    Sharma, Eva
    De Choudhury, Munmun
    PROCEEDINGS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018), 2018,
  • [3] Why Do Users of Online Mental Health Communities Get Likes and Reposts: A Combination of Text Mining and Empirical Analysis
    Liu, Jingfang
    Kong, Jun
    HEALTHCARE, 2021, 9 (09)
  • [4] The Impact of Online and Offline Social Support on the Mental Health of Carers of Persons with Cognitive Impairments
    Yi, Eun-Hye Grace
    Adamek, Margaret E.
    Hong, Michin
    Lu, Yvonne
    Wilkerson, David
    JOURNAL OF GERONTOLOGICAL SOCIAL WORK, 2023, 66 (07): : 888 - 907
  • [5] Effect of writing style on social support in online health communities: A theoretical linguistic analysis framework
    Jiang, Shan
    Liu, Xuan
    Chi, Xiaotong
    INFORMATION & MANAGEMENT, 2022, 59 (06)
  • [6] UNINTENDED EMOTIONAL EFFECTS OF ONLINE HEALTH COMMUNITIES: A TEXT MINING-SUPPORTED EMPIRICAL STUDY
    Zhou, Jiaqi
    Zhang, Qingpeng
    Zhou, Sijia
    Li, Xin
    Michael Zhang, Xiaoquan
    MIS QUARTERLY, 2023, 47 (01) : 195 - 226
  • [7] Moments of Change: Analyzing Peer-Based Cognitive Support in Online Mental Health Forums
    Pruksachatkun, Yada
    Pendse, Sachin R.
    Sharma, Amit
    CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2019,
  • [8] Does Use of Health Language Improve Social Support Outcome? Linguistic Analysis of Online Health Communities
    Jiang, Shan
    AMCIS 2020 PROCEEDINGS, 2020,
  • [9] Misinformation in Italian Online Mental Health Communities During the COVID-19 Pandemic: Protocol for a Content Analysis Study
    Bizzotto, Nicole
    Morlino, Susanna
    Schulz, Peter Johannes
    JMIR RESEARCH PROTOCOLS, 2022, 11 (05):
  • [10] Consequences of Gift Giving in Online Health Communities on Physician Service Quality: Empirical Text Mining Study
    Peng, Li
    Wang, Yanan
    Chen, Jing
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (07)