Dataset Information

Impact of Education on School Nurses' Knowledge of Inflammatory Bowel Disease.

ABSTRACT:

Background/aims

School nurses' knowledge of inflammatory bowel disease (IBD) has not been evaluated. We aimed to investigate school nurses' knowledge of IBD and determine whether education could improve this knowledge.

Methods

School nurses were invited to complete self-reported questionnaires on IBD. Then, IBD specialists from tertiary referral hospitals provided a 60-minute lecture with educational brochures on two occasions, with a 3-month interval. Within 6 months after the educational interventions, school nurses were asked to complete the same IBD questionnaire via e-mail.

Results

Among 101 school nurses who were invited to participate, 54 nurses (53.5%) who completed two consecutive questionnaires were included in this study (median age, 45 years; range, 25 to 59 years; 100% female); 11.1% and 7.4% of the study participants had no knowledge regarding ulcerative colitis and Crohn's disease, respectively. They had heard of IBD most frequently from doctors (33.3%), followed by internet sources (25.9%). After 6 months, the number of nurses who could explain IBD to students with over 30% confidence increased from 24 (44.5%) to 42 (77.8%) (p＜0.001). Most nurses (81.5%) reported that the educational intervention was helpful for managing students with abdominal pain or diarrhea. The number of students who received IBD-related welfare services from the Daegu Metropolitan Office of Education doubled when compared with the corresponding number during the prior educational year.

Conclusions

There is room for improvement in school nurses' knowledge of IBD. A systematic educational program on IBD should be implemented for these nurses.

SUBMITTER: Kim ES

PROVIDER: S-EPMC6346995 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (Il10-/-) with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition. RESULTS:Wild-type (WT) and Il10-/- mice were exposed to whole body irradiation of 7?Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24?h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (p <?0.001, FDR?<?10%) after radiation exposure in Il10-/- and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and Il10-/- mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in Il10-/- mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and Il10-/- after irradiation. CONCLUSIONS:Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers.