The application of artificial intelligence (AI) in nursing care has surfaced as a revolutionary method for improving the quality and efficiency of patient care. Examining AI-driven care plans could yield valuable insights for improving nursing care. A pretest-posttest quasi-experimental study with 43 participants compared manual and AI-generated care plans in performance expectancy, effort expectancy, user satisfaction, and efficiency, before and after the intervention. AI-driven care plans were produced through www.careplans.com in line with NANDA taxonomy. Participants were selected consecutively and completed a self-administered questionnaire. Data analysis was conducted using R (v4.1.2), utilizing the Wilcoxon signed-rank test for paired data. Results were illustrated in box plots, with differences deemed significant at P- values <.05. Care plans generated by AI consistently demonstrated superior performance compared to those developed manually across all evaluated criteria. The median scores for AI-generated plans were 91.67%, 93.75%, 91.67%, and 92.86% in perceived efficiency. In contrast, the manually written plans achieved scores of 58.33%, 56.25%, 50%, and 45%, respectively. Wilcoxon signed-rank test indicated that these differences were statistically significant ( P < .001). Utilising efficient AI-generated care plans enhances nursing care, allowing for the reallocation of time saved to focus on direct patient care.
Electronic health records (EHRs) can improve data access, care coordination, data integrity, and protections for privacy and confidentiality, yet adoption in resource-constrained settings is uneven. This cross-sectional mixed-methods study examined factors associated with nurses’ comfort using EHRs in Botswana’s clinics and health posts. We surveyed 193 nurses across 53 facilities within 8 district health management teams. Closed-ended survey responses were analyzed descriptively in SPSS 26, while responses to one open-ended question were analyzed in NVivo 15 as an exploratory qualitative component. Individual factors reported in relation to comfort using EHRs included computer self-efficacy, EHR knowledge, familiarity, frequency of use, and prior technology-related training. Technology characteristics linked to comfort using EHRs were perceived accessibility, usability, efficiency, and enhancements to privacy and confidentiality, whereas limited access, software and hardware issues, difficulty of use, and workflow inefficiencies were linked to discomfort using EHRs. At the organizational level, availability of training was the only factor that fostered comfort using EHRs, while lack of institutional training, weak EHR support and maintenance, inadequate infrastructure, and understaffing were prominent sources of discomfort using EHRs. These findings highlight the need for continuous training, reliable infrastructure, and sufficient staffing to reduce discomfort using EHRs and strengthen nurses’ comfort using EHRs and sustained EHR use in resource-constrained settings.
Socioeconomic deprivation has been associated with depression, and previous studies have demonstrated an association between family relationship satisfaction and depression. However, there is a lack of consensus regarding whether family relationship satisfaction can moderate the association between socioeconomic deprivation and depression. This study examined the longitudinal association between socioeconomic deprivation and depression and tested whether family relationship satisfaction and benefits from the Basic Livelihood Security System moderated this association. Data from the Korea Welfare Panel Study were used, including 7867 Korean adults followed over a five-year period from 2017 to 2021. Correlation analysis and generalized estimating equations were conducted to examine whether family relationship satisfaction and Basic Livelihood Security System benefits moderated the association between socioeconomic deprivation and depression. Socioeconomic deprivation was significantly associated with higher depressive symptoms, whereas family relationship satisfaction was significantly associated with lower depressive symptoms. The interaction between socioeconomic deprivation and family relationship satisfaction was significant (B = -0.174, Wald chi(2) = 37.662, p < 0.001), indicating that family relationship satisfaction moderated this association. Although receipt of Basic Livelihood Security System benefits was significantly associated with depression, the interaction between socioeconomic deprivation and benefit receipt was not significant (B = 0.135, Wald chi(2) = 2.506, p = 0.113). These findings highlight the importance of considering both socioeconomic conditions and family relationship resources when examining factors associated with depressive symptoms among socioeconomically disadvantaged adults.
Patients with colorectal cancer or severe abdominal trauma often require a stoma and must master the self-care necessary to prevent peristomal skin complications. In this study, we developed and evaluated a mobile health (mHealth) app, called The Stoma Self-Care App, to facilitate self-care knowledge and skill acquisition alongside clinical monitoring in patients with ostomy. The app was developed following the 6 stages of the System Development Life Cycle: planning, design, development, testing, deployment, and maintenance. To evaluate usability, the app was tested in 23 patients over 4 weeks, who then completed a self-administered satisfaction questionnaire. The final version of the mHealth app received favorable clinical appraisals, with the average satisfaction score being 4.85/5.0. The findings demonstrated good usability and high user satisfaction among a small sample of patients with ostomy, indicating that the app was well accepted and easy to use. Overall, this study describes a systematic, user-centered approach to developing a mHealth app for ostomy self-care and provides preliminary evidence supporting its usability and acceptability. The app’s systematic development and high user acceptance support the feasibility of a user-centered development approach for mHealth applications in ostomy care. Further studies involving larger and more diverse patient populations are warranted to evaluate the app’s effectiveness and broader applicability.
