Background: In recent years, women’s fertility desire has attracted increasing attention in China. Objective: This study aims to detect attitudes toward giving birth among young female users on Douban, a very popular Chinese social media platform. Methods: A total of 2634 valid posts from 2489 users discussing the topic “What does childbirth mean to a woman” on Douban were crawled and retained for analysis. We utilized content and thematic analysis methods to capture users’ concepts of childbirth. Results: The findings reveal that a significant majority of users conveyed generally neutral (1060/2634, 40.24%) or negative (1051/2634, 39.90%) attitudes toward childbirth, while only about one-fifth of users expressed positive (523/2634, 19.86%) sentiments. Notably, posts with negative attitudes garnered more replies and likes, and the proportion of posts expressing negativity exhibited fluctuations over time. Health risk (339/2634, 12.87%) emerged as the most frequently cited aspect of childbirth cost, with subjective happiness and the fulfillment of mental needs identified as primary benefits. Surprisingly, only a minimal number of posts (10/2634, 0.38%) touched upon the traditional objective benefits of raising children for old-age care. Thematic analysis results suggest that discussions about fertility on social media platforms might contribute to an exaggerated perception of health risks among women. Additionally, a lack of knowledge about childbirth was observed, partially attributable to longstanding neglect and avoidance of communication on these matters, likely influenced by traditional cultural biases. Moreover, there is a prevailing assumption that women should naturally sacrifice themselves for childbirth and childcare, influenced by the idealization of the female figure. Consequently, women may harbor hesitations about having a baby, fearing the potential loss of their own identity in the process. Conclusions: The results indicate a shift in the perception of childbirth among modern Chinese women over time, influenced by their increasing social status and the pursuit of self-realization. Implementing strategies such as public education on the health risks associated with pregnancy and delivery, safeguarding women’s rights, and creating a supportive environment for mothers may enhance women’s willingness to undergo childbirth. International Registered Report Identifier (IRRID): RR2-10.2196/preprints.50468

Background: The phenomenon of cyberbullying is becoming increasingly severe, and many studies focus on the negative psychological impacts of cyberbullying survivors. However, current survey methods cannot provide direct and reliable evidence of the short-term psychological effects of cyberbullying survivors, as it is impractical to measure psychological changes before and after such an unpredictable event in a short period. Objective: This study aims to explore the psychological impacts of cyberbullying on survivors during the pericyberbullying period, defined as the critical time frame surrounding the first cyberbullying incident, encompassing the psychological changes before, during, and after the event. Methods: We collected samples from 60 cyberbullying survivors (experimental group, 94/120, 78% female) and 60 individuals who have not experienced cyberbullying (control group, matched by sex, location, and number of followers) on Sina Weibo, a social media platform developed by Sina Corporation. During the pericyberbullying period, we retrospectively measured psychological traits 3 months before and after the first cyberbullying incident for both groups. Social media data and predictive models were used to identify survivors’ internal psychological traits, including happiness, suicide risk, personality traits, and moral perceptions of the external environment. Network analysis was then performed to explore the interplay between cyberbullying experiences and psychological characteristics. Results: During the pericyberbullying period, survivors exhibited significantly reduced happiness (t59=2.14; P=.04), marginally increased suicide risk, and significant changes in the Big 5 personality traits, including decreased conscientiousness (t59=2.27; P=.03), agreeableness (t59=2.79; P=.007), and extraversion (t59=2.26; P=.03), alongside increased neuroticism (t59=–3.42; P=.001). Regarding moral perceptions of the external environment, survivors showed significant increases in communicative moral motivation (t59=–2.62; P=.011) and FairnessVice (t59=–2.20; P=.03), with a marginal rise in PurityVice (t59=–1.88; P=.07). In contrast, the control group exhibited no significant changes during the same time frame. Additionally, network analysis revealed that beyond cyberbullying experiences, core psychological characteristics in the network were neuroticism, conscientiousness, and Oxford Happiness. Conclusions: By leveraging noninvasive retrospective social media data, this study provides novel insights into the short-term psychological impacts of cyberbullying during the pericyberbullying period. The findings highlight the need for timely interventions focusing on enhancing survivors’ happiness, reducing suicide risk, adjusting personality traits, and rebuilding moral cognition to mitigate the negative effects of cyberbullying.

The global COVID-19 pandemic may significantly affect the experiences of death and bereavement. This study aimed to learn from recent outbreaks of infectious diseases and further understand their impacts on bereavement. We obtained psychological status scores for 32 individuals bereaved due to COVID-19 and 127 individuals bereaved due to non-COVID-19 causes using the online ecological recognition (OER) approach. Next, a sentiment analysis and independent sample t-test were performed to examine the differences between these two groups. The results indicated that the individuals bereaved due to COVID-19 were more insecure and more preoccupied with the grief of the moment than those bereaved due to non-COVID-19 reasons, while the latter group had higher depression scores than the former group. This study can guide policy-makers and clinical practitioners to provide more targeted and sustainable post-bereavement support for both bereaved groups during the COVID-19 period.

Background: Positive mental health is arguably increasingly important and can be revealed, to some extent, in terms of psychological well-being (PWB). However, PWB is difficult to assess in real time on a large scale. The popularity and proliferation of social media make it possible to sense and monitor online users’ PWB in a nonintrusive way, and the objective of this study is to test the effectiveness of using social media language expression as a predictor of PWB. Objective: This study aims to investigate the predictive power of social media corresponding to ground truth well-being data in a psychological way. Methods: We recruited 1427 participants. Their well-being was evaluated using 6 dimensions of PWB. Their posts on social media were collected, and 6 psychological lexicons were used to extract linguistic features. A multiobjective prediction model was then built with the extracted linguistic features as input and PWB as the output. Further, the validity of the prediction model was confirmed by evaluating the model's discriminant validity, convergent validity, and criterion validity. The reliability of the model was also confirmed by evaluating the split-half reliability. Results: The correlation coefficients between the predicted PWB scores of social media users and the actual scores obtained using the linguistic prediction model of this study were between 0.49 and 0.54 (P<.001), which means that the model had good criterion validity. In terms of the model’s structural validity, it exhibited excellent convergent validity but less than satisfactory discriminant validity. The results also suggested that our model had good split-half reliability levels for every dimension (ranging from 0.65 to 0.85; P<.001). Conclusions: By confirming the availability and stability of the linguistic prediction model, this study verified the predictability of social media corresponding to ground truth well-being data from the perspective of PWB. Our study has positive implications for the use of social media to predict mental health in nonprofessional settings such as self-testing or a large-scale user study.