Analysis of the evolution of COVID-19 disease understanding through temporal knowledge graphs.

The COVID-19 pandemic highlighted two critical barriers hindering rapid response to novel pathogens. These include inefficient use of existing biological knowledge about treatments, compounds, gene interactions, proteins, etc. to fight new diseases, and the lack of assimilation and analysis of the fast-growing knowledge about new diseases to quickly develop new treatments, vaccines, and compounds. Overcoming these critical challenges has the potential to revolutionize global preparedness for future pandemics. Accordingly, this article introduces a novel knowledge graph application that functions as both a repository of life science knowledge and an analytics platform capable of extracting time-sensitive insights to uncover evolving disease dynamics and, importantly, researchers' evolving understanding. Specifically, we demonstrate how to extract time-bounded key concepts, also leveraging existing ontologies, from evolving scholarly articles to create a single temporal connected source of truth specifically related to COVID-19. By doing so, current knowledge can be promptly accessed by both humans and machines, from which further understanding of disease outbreaks can be derived. We present key findings from the temporal analysis, applied to a subset of the resulting knowledge graph known as the temporal keywords knowledge graph, and delve into the detailed capabilities provided by this innovative approach.

Preliminary effectiveness study of the Cope Notes digital mental Health program.

BACKGROUND: Cope Notes is a subscription-based EMI that uses Short Message Service (SMS) technology to deliver daily text messages that promote hope, reduce stigma, and encourage coping and the use of positive psychology strategies. AIM: We aimed to evaluate the preliminary effectiveness of Cope Notes, a brief ecological momentary intervention (EMI). METHODS: We conducted a longitudinal study where participants (N = 64) completed measures of depression, anxiety, perceived stress, coping, emotional intelligence, label avoidance, attitudes towards treatment-seeking, and readiness for change before the intervention, 1 month post-intervention, and 2 months post-intervention. This study includes mixed repeated measures ANOVAs to analyze over time. RESULTS: Findings show that participants with severe depression experienced a significant decrease in anxiety and depressive symptoms, and perceived stress (p < .001) and showed a significant increase in emotional intelligence at 1 month post-intervention. Participants with mild to moderate depression experienced a significant increase in overall coping and problem-focused coping. CONCLUSIONS: While further investigation of Cope Notes' feasibility and acceptability is warranted, these findings support that the Cope Notes EMI holds promise as a low-cost, impactful mental health solution for populations with limited access to care and those experiencing self-stigma preventing help-seeking.

Characterizing User Experiences With an SMS Text Messaging-Based mHealth Intervention: Mixed Methods Study.

BACKGROUND: Limited access to mental health care services due to provider shortages, geographic limitations, and cost has driven the area of mobile health (mHealth) care to address these access gaps. Reports from the Cohen Veterans Network and National Council for Behavioral Health show that in states where mental health care is more accessible, 38% of people still do not receive the care they need. mHealth strategies help to provide care to individuals experiencing these barriers at lower cost and greater convenience, making mHealth a great resource to bridge the gaps. OBJECTIVE: We present a mixed methods study to evaluate user experiences with the mental mHealth service, Cope Notes. Specifically, we aimed to investigate the following research questions: How do users perceive the service in relation to stigma, impact of the intervention, and perceived usefulness? How do users rate the Cope Notes service and SMS text messaging along various dimensions of acceptability? What is the relationship between Cope Notes SMS text message ratings, user personality, and coping strategies? What are user perspectives of leveraging ubiquitous sensing technologies to improve delivery and provide tailored content? METHODS: We performed qualitative interviews with Cope Notes users (N=14) who have used the service for at least 30 days to evaluate their experiences and usefulness of the service. These interviews were coded by 2 raters (SLK and JL), and the interrater reliability was calculated with SPSS (IBM Corp) at 61.8%. In addition, participants completed quantitative measures, including a user experiences survey, personality inventory (Big Five Inventory-10), and coping assessment (Brief Coping Orientation to Problems Experienced). RESULTS: We derived 7 themes from our qualitative interviews: Likes or Perceived Benefits, Dislikes or Limitations, Suggested Changes, Stigma or Help Seeking, Perceptions of Ubiquitous Sensing, Cultural Sensitivity, and Alternative mHealth Resources. Exploratory analyses between acceptability ratings of Cope Notes and personality factors showed statistically significant positive relationships between seeing oneself as someone who is generally trusting and acceptability items, the most significant being item 7 (I fully understood the sentiment behind Cope Notes Messages) with (rs(10)=0.82, P=.001). We also found statistically significant relationships between acceptability and Brief Coping Orientation to Problems Experienced items, with the strongest positive correlation between participants strongly endorsing coping by accepting the reality that an event has happened and acceptability item 7 (rs(8)=0.86, P=.001). CONCLUSIONS: Our study found that Cope Notes subscribers appreciate the service for reframing their mental wellness with statistically significant correlations between personality and acceptability of the service. We found that some users prefer a more personalized experience with neutral to positive reactions to a potential companion app that continuously monitors user behavior via smartphone sensors to provide just-in-time interventions when users need it most.