Concerns have been raised over the experiences of violence such as domestic violence (DV) and intimate partner violence (IPV) during the COVID-19 pandemic. Social media such as Reddit represent an alternative outlet for reporting experiences of violence where healthcare access has been limited. This study analyzed seven violence-related subreddits to investigate the trends of different violence patterns from January 2018 to February 2022 to enhance the health-service providers’ existing service or provide some new perspective for existing violence research. Specifically, we collected violence-related texts from Reddit using keyword searching and identified six major types with supervised machine learning classifiers: DV, IPV, physical violence, sexual violence, emotional violence, and nonspecific violence or others. The increase rate (IR) of each violence type was calculated and temporally compared in five phases of the pandemic. The phases include one pre-pandemic phase ( Phase 0, the date before February 26, 2020) and four pandemic phases ( Phases 1–4) with separation dates of June 17, 2020, September 7, 2020, and June 4, 2021. We found that the number of IPV-related posts increased most in the earliest phase; however, that for COVID-citing IPV was highest in the mid-pandemic phase. IRs for DV, IPV, and emotional violence also showed increases across all pandemic phases, with IRs of 26.9%, 58.8%, and 28.8%, respectively, from the pre-pandemic to the first pandemic phase. In the other three pandemic phases, all the IRs for these three types of violence were positive, though lower than the IRs in the first pandemic phase. The findings highlight the importance of identifying and providing help to those who suffer from such violent experiences and support the role of social media site monitoring as a means of informative surveillance for help-providing authorities and violence research groups.

Systematic analysis of interview data can provide important insights into how young people experience and interpret their emotions. Both human-led qualitative (e.g., thematic analysis) and machine-driven quantitative (e.g., natural language processing [NLP]) analytical approaches are available, but their solutions are rarely compared. Interview responses by 57 neurodivergent adolescents to questions about their emotions, previously analysed using reflexive thematic analysis (RTA), were submitted to Topic Modelling (TM). Topic labels were developed in collaboration with neurodivergent co-researchers to ground their meaning in the lived experience of neurodivergent communities. Topics were mapped to RTA themes or subthemes to examine their proximities. Topic-based cluster analysis was used to identify participant groupings with similar topic distributions. TM revealed 10 interpretable and meaningful emotion-related topics – some closely overlapping with and others differing from the RTA themes. TM topics differentiated the young people’s emotional experiences at school from those in other settings. TM and RTA resulted in overlapping and different insights into the meaning of neurodivergent young people’s accounts of their emotions. Our findings demonstrate the potential use of TM in interview analysis and might suggest a potential complementarity between the TM topics and RTA themes, to be further explored using more advanced algorithms and a more sophisticated NLP implementation.

Nasopharyngeal carcinoma (NPC) remains a major endemic disease in parts of Asia especially Southern China and Southest Asia, the risk factors of which are distinct from other head and neck cancers. Antidiabetic drugs have been proposed to reduce the risk of NPC. The associations between sodium–glucose cotransporter 2 inhibitors (SGLT2I) versus dipeptidyl peptidase-4 inhibitors (DPP4I) and the risks of NPC and head and neck cancer among patients with type 2 diabetes mellitus (T2DM) remain unknown. This was a population-based cohort study including patients with T2DM treated with either an SGLT2I or a DPP4I between January 1, 2015, and December 31, 2019, in Hong Kong. Propensity score matching (1:1 ratio) was performed using the nearest neighbor search. Multivariable Cox regression was applied to identify significant predictors. The primary outcome was new-onset NPC and other head and neck cancers. We found that patients with T2DM were treated with either an SGLT2I or a DPP4I between January 1, 2015, and December 31, 2019, in Hong Kong. This cohort included 75,884 patients with T2DM, among whom 28,778 patients were on an SGLT2I and 47,106 patients were on a DPP4I. After matching (57,556 patients), 106 patients developed NPC and 50 patients developed head and neck cancer. Compared with DPP4Is, SGLT2Is were associated with lower risks of NPC (HR, 0.41; 95% confidence interval, 0.21–0.81) but not of head and neck cancer (HR, 1.00; 95% confidence interval, 0.26–3.92) after adjustments. The association remained consistent in different risk models, matching approaches, and sensitivity analysis. In conclusion, this study provided real-world evidence that SGLT2Is were associated with lower risks of NPC but not of head and neck cancer when compared with DPP4Is among patients with T2DM, whereas their biological effects need future confirmation. Prevention Relevance: This study provided real-world evidence that SGLT2Is were associated with lower risks of NPC but not of head and neck cancer when compared with DPP4Is among patients with T2DM. SGLT2Is should be considered before DPP4Is about the risks of NPC in regions with high prevalence of NPC.