Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, United States.
Department of Psychiatry, Columbia University, New York, NY, United States.
J Med Internet Res. 2022 Jan 11;24(1):e31175. doi: 10.2196/31175.
Hikikomori is a form of severe social withdrawal that is particularly prevalent in Japan. Social media posts offer insight into public perceptions of mental health conditions and may also inform strategies to identify, engage, and support hard-to-reach patient populations such as individuals affected by hikikomori.
In this study, we seek to identify the types of content on Twitter related to hikikomori in the Japanese language and to assess Twitter users' engagement with that content.
We conducted a mixed methods analysis of a random sample of 4940 Japanese tweets from February to August 2018 using a hashtag (#hikikomori). Qualitative content analysis included examination of the text of each tweet, development of a codebook, and categorization of tweets into relevant codes. For quantitative analysis (n=4859 tweets), we used bivariate and multivariate logistic regression models, adjusted for multiple comparisons, and estimated the predicted probabilities of tweets receiving engagement (likes or retweets).
Our content analysis identified 9 codes relevant to tweets about hikikomori: personal anecdotes, social support, marketing, advice, stigma, educational opportunities, refuge (ibasho), employment opportunities, and medicine and science. Tweets about personal anecdotes were the most common (present in 2747/4859, 56.53% of the tweets), followed by social support (902/4859, 18.56%) and marketing (624/4859, 12.84%). In the adjusted models, tweets coded as stigma had a lower predicted probability of likes (-33 percentage points, 95% CI -42 to -23 percentage points; P<.001) and retweets (-11 percentage points, 95% CI -18 to -4 percentage points; P<.001), personal anecdotes had a lower predicted probability of retweets (-8 percentage points, 95% CI -14 to -3 percentage points; P=.002), marketing had a lower predicted probability of likes (-13 percentage points, 95% CI -21 to -6 percentage points; P<.001), and social support had a higher predicted probability of retweets (+15 percentage points, 95% CI 6-24 percentage points; P=.001), compared with all tweets without each of these codes.
Japanese tweets about hikikomori reflect a unique array of topics, many of which have not been identified in prior research and vary in their likelihood of receiving engagement. Tweets often contain personal stories of hikikomori, suggesting the potential to identify individuals with hikikomori through Twitter.
蛰居现象是一种严重的社会退缩形式，在日本尤为普遍。社交媒体帖子提供了对心理健康状况公众看法的深入了解，也可以为识别、接触和支持难以接触的患者群体（如受蛰居影响的个体）提供策略。
本研究旨在确定与日语中的蛰居相关的 Twitter 内容类型，并评估 Twitter 用户对这些内容的参与度。
我们使用 2018 年 2 月至 8 月期间的一个随机 #hikikomori 标签对 4940 条日语推文进行了混合方法分析。定性内容分析包括对每条推文的文本进行检查、开发代码本以及将推文分类为相关代码。对于定量分析（n=4859 条推文），我们使用了双变量和多变量逻辑回归模型，进行了多次比较调整，并估计了推文获得参与（点赞或转发）的概率。
我们的内容分析确定了 9 个与蛰居相关的代码：个人轶事、社会支持、营销、建议、污名、教育机会、避难所（ibasho）、就业机会和医学与科学。关于个人轶事的推文最常见（在 4859 条推文中，2747 条，占 56.53%），其次是社会支持（902 条，占 18.56%）和营销（624 条，占 12.84%）。在调整后的模型中，被编码为污名的推文点赞的预测概率较低（减少 33 个百分点，95%CI-42 至-23 个百分点；P<.001）和转发（减少 11 个百分点，95%CI-18 至-4 个百分点；P<.001），个人轶事的转发预测概率较低（减少 8 个百分点，95%CI-14 至-3 个百分点；P=.002），营销的点赞预测概率较低（减少 13 个百分点，95%CI-21 至-6 个百分点；P<.001），社会支持的转发预测概率较高（增加 15 个百分点，95%CI 6-24 个百分点；P=.001），而不是所有没有这些代码的推文。
日本关于蛰居的推文反映了一系列独特的主题，其中许多主题在之前的研究中没有被发现，并且它们获得参与的可能性也不同。推文通常包含蛰居者的个人故事，这表明通过 Twitter 识别蛰居者的可能性。
