Petrič Gregor, Cugmas Marjan, Petrič Rok, Atanasova Sara
Faculty of Social Sciences, University of Ljubljana, Ljubljana, Slovenia.
Institute of Oncology, Ljubljana, Slovenia.
Digit Health. 2023 Feb 20;9:20552076231155681. doi: 10.1177/20552076231155681. eCollection 2023 Jan-Dec.
Informational social support is one of the main reasons for patients to visit online health communities (OHCs). Calls have been made to investigate the objective quality of such support in the light of a worrying number of inaccurate online health-related information. The main aim of this study is to conceptualize the Quality of Informational Social Support (QISS) and develop and test a measure of QISS for content analysis. A further aim is to investigate the level of QISS in cancer-related messages in the largest OHC in Slovenia and examine the differences among various types of discussion forums, namely, online consultation forums, online support group forums, and socializing forums.
A multidimensional measurement instrument was developed, which included 20 items in a coding scheme for a content analysis of cancer-related messages. On a set of almost three million posts published between 2015 and 2019, a machine-learning algorithm was used to detect cancer-related discussions in the OHC. We then identified the messages providing informational social support, and through quantitative content analysis, three experts coded a random sample of 403 cancer-related messages for the QISS.
The results demonstrate a good level of interrater reliability and agreement for a QISS scale with six dimensions, each demonstrating good internal consistency. The results reveal large differences among the social support, socializing, and consultation forums, with the latter recording significantly higher quality in terms of accuracy (M = 4.48, < .001), trustworthiness (M = 4.65, < .001), relevance (M = 3.59, < .001), and justification (M = 3.81, = .05) in messages providing informational social support regarding cancer-related issues.
This study provides the research field with a valid tool to further investigate the factors and consequences of varying quality of information exchanged in supportive communication. From a practical perspective, OHCs should dedicate more resources and develop mechanisms for the professional moderation of health-related topics in socializing forums and thereby suppress the publication and dissemination of low-quality information among OHC users and visitors.
信息性社会支持是患者访问在线健康社区(OHC)的主要原因之一。鉴于大量不准确的在线健康相关信息令人担忧,人们呼吁对这种支持的客观质量进行调查。本研究的主要目的是对信息性社会支持质量(QISS)进行概念化,并开发和测试一种用于内容分析的QISS测量方法。另一个目的是调查斯洛文尼亚最大的OHC中与癌症相关信息的QISS水平,并研究各种类型的讨论论坛之间的差异,即在线咨询论坛、在线支持小组论坛和社交论坛。
开发了一种多维测量工具,其中包括一个用于对与癌症相关信息进行内容分析的编码方案中的20个项目。在2015年至2019年发布的近300万个帖子中,使用机器学习算法在OHC中检测与癌症相关的讨论。然后,我们识别出提供信息性社会支持的信息,并通过定量内容分析,三位专家对403条与癌症相关信息的随机样本进行QISS编码。
结果表明,一个具有六个维度的QISS量表具有良好的评分者间信度和一致性,每个维度都具有良好的内部一致性。结果显示,社会支持、社交和咨询论坛之间存在很大差异,就提供有关癌症相关问题的信息性社会支持的信息而言,后者在准确性(M = 4.48, <.001)、可信度(M = 4.65, <.001)、相关性(M = 3.59, <.001)和合理性(M = 3.81, =.05)方面的质量明显更高。
本研究为研究领域提供了一个有效的工具,以进一步调查在支持性沟通中交换的信息质量不同的因素和后果。从实际角度来看,OHC应该投入更多资源,并为社交论坛中与健康相关主题的专业审核制定机制,从而抑制低质量信息在OHC用户和访客中的发布和传播。