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The ongoing transition to the patient-centred healthcare paradigm suggests that patients adopt an active role in managing their health conditions. As a result, the Internet is becoming an important source of health-related information. Internet-based health support groups allow patients to access diverse information relevant to their particular situation by participating in online discussions. The quality of such information may have effects on the patients’ health outcomes. The purpose of the present study was to investigate the effects of knowledge construction in health support group online discussions on perceived information quality, information quality from the perspective of information consumers, and on information integrity, that is, validity from the point of view of the current state of scientific knowledge. It was hypothesised that knowledge construction results in better perceived information quality and in higher information integrity. A health support group online discussion site devoted to weight management was used as a source of data. Quantitative content analysis was used with a discussion thread as a unit of analysis. Based on the findings, the study suggested that moderators of health support group online discussions should promote explicitation or lower level knowledge construction by encouraging clarifications and refinements of health-related recommendations. Moreover, participation of qualified health practitioners is desirable to promote health-related behaviours based on evidence-based knowledge and to expose recommendations that have uncertain or even dangerous effects.

A method for visualizing discussion flow is proposed for analyzing the thread in KGBBS (KeyGraph-based BBS). It is known that group discussion is effective for chance discovery, in which information visualization plays an important role in providing participants with a material to that brainstorm various ideas, opinions, and interpretations. In order to enable online discussion while sharing the same visualized material, KGBBS is proposed based on KeyGraph, which is one of the typical visualization techniques in chance discovery. The aim of this paper is to utilize the result of discussion using KGBBS, by visualizing discussion flow of the thread in KGBBS. The method consists of 2 kinds of visualization techniques — a comment chain diagram to visualize the structure of comment chain, and a visual summary on KeyGraph to visualize concrete transition of topics through successive 2 or 3 comments. The proposed method is applied to actual discussion data, and the analysis results show the combination of both the visualization techniques, making it possible to analyze concrete transition of topics without reading comments in a thread.