Multi-source heterogeneous blockchain data quality assessment model for enterprise business activities.

Blockchain-based applications are becoming more and more widespread in business operations. In view of the shortcomings of existing enterprise blockchain evaluation methods, this paper proposes a multi-source heterogeneous blockchain data quality evaluation model for enterprise business activities, so as to achieve efficient evaluation of business activity information consistency, credibility and value. This paper proposes a multi-source heterogeneous blockchain data quality assessment method for enterprise business activities, aiming at the problems that most of the data in enterprise business activities come from different data sources, information representation is inconsistent, information ambiguity between the same block chain is serious, and it is difficult to evaluate the consistency, credibility and value of information. The method firstly proposes an entity information representation method based on the Representation learning for fusing entity category information (CEKGRL) model, which introduces the triad structure of related entities in blockchain, then associates them with enterprise business activity categories, and carries out similarity calculation through contextual information to achieve blockchain information consistency assessment. After that, a trustworthiness characterization method is proposed based on information sources, information comments, and information contents, to obtain the trustworthiness assessment of the business. Finally, based on the information trustworthiness characterization, a value assessment method is introduced to assess the total value of business activity information in the blockchain, and a blockchain quality assessment model is constructed. The experimental results show that the proposed model has great advantages over existing methods in assessing inter-block consistency, intra-block activity information trustworthiness and the value of blockchain.

Effect of Humanistic Pain Management in Postpartum Women after Cesarean Delivery Based on Active Pain Assessment and Visual Analog Scale.

Objective: To explore the effect of humanistic pain management based on active pain assessment and the visual analog scale in postpartum women after cesarean delivery. Methods: We selected 100 postpartum women who underwent cesarean delivery in Xuzhou Maternity and Child Health Care Hospital from April to December 2021 and divided the postpartum women into a management group and a conventional group, with 50 cases in each group. The conventional group was given routine pain management, while the management group was given humanistic pain management based on active pain assessment and visual analog scale score. The quality of pain management, sleep quality, unhealthy emotion, maternal comfort, breastfeeding rates, and patient compliance in the 2 groups were compared. Results: The most severe degree of pain, the least degree of pain, the frequency of moderate and severe pain, and the influence of pain on sleep were lower in the management group than in the conventional group. The Pittsburgh Sleep Quality Index score was lower and the Self-Rating Anxiety Scale and the Self-Rating Depression Scale scores were higher in the management group than in the conventional group. In addition, the comfort scores for the second day and the third day after delivery were higher in the management group than in the conventional group. The breastfeeding rate and patient compliance were higher in the management group than in the conventional group. Conclusion: Humanistic pain management based on active pain assessment and the visual analog scale can improve the quality of maternal pain management, the quality of sleep, and maternal comfort, ameliorate maternal adverse emotions, and promote breastfeeding and patient compliance.

Is It Safe for Me to Get It? Factors Influencing COVID-19 Vaccination Decision-Making among Postpartum Women Who Are Black and Hispanic in Deep South.

BACKGROUND: COVID-19 vaccination is vital for ending the pandemic, yet safety concerns persist among pregnant and postpartum women, especially those who are Black and Hispanic. This study aims to explore factors that influence postpartum women's vaccination decision-making during pregnancy and postpartum through women's lived experiences and maternal care providers' (MCPs) observations. METHODS: From January to August 2022, we conducted semi-structured interviews with postpartum women who are Black and Hispanic and with MCPs. Participants were recruited from obstetric and pediatric clinics in South Carolina and had given birth in 2021. Thematic analysis was employed for data analysis. RESULTS: The study involved 19 Black and 20 Hispanic women, along with 9 MCPs, and revealed both barriers and facilitators to COVID-19 vaccination. The factors that influence pregnant and postpartum women's decision about COVID-19 vaccine uptake included: 1) awareness of health threats associated with COVID-19 vaccines, 2) vaccine availability and accessibility, 3) vaccine-related knowledge and exposure to misinformation, 4) concerns regarding pre-existing health conditions and potential side effects of COVID-19 vaccines, 5) emotional factors associated with vaccination decision-making processes, 6) concerns about the well-being of infants, 7) cultural perspectives, and 8) encouragement by trusted supporters. CONCLUSION: The findings suggest that reliable information, social support, and trusted MCPs' advice can motivate COVID-19 vaccination among pregnant and postpartum women who are Black and Hispanic. However, barriers such as misinformation, mistrust in the health care system, and fears of potential side effects impede vaccination uptake. Future interventions should address these barriers, consider health disparities, involve trusted MCPs, and initiate conversations about vaccines to promote vaccination among these populations.