OBJECTIVES: The purposes of this study were to develop a Web-based education program, My Child's Safety, which includes patient safety education and information on the diagnosis, treatment, and management for caregivers of children with cancer, and to examine the efficacy of the My Child's Safety program in promoting the caregivers' awareness of patient safety. METHODS: A one-group pre- and post-test design was adopted. The participants were the caregivers of children with cancer and were recruited from one pediatric hemato-oncology unit of a tertiary university hospital in a large metropolitan city of South Korea. They were asked to review the Web-based program for patient safety and then complete questionnaires developed to measure the awareness of patient safety among the caregivers. RESULTS: In the study, the total score of the caregivers' awareness of patient safety had increased significantly after Web-based self-learning patient safety education. Also caregivers' awareness of their right to ask and know about procedures and treatments during hospitalization had increased after the program was used. CONCLUSIONS: The Web-based patient safety education program effectively improved the awareness of patient safety and the awareness of the right to know and ask about procedures and treatments during hospitalization among the caregivers. Family caregivers were less likely to ask healthcare professionals questions related to safety.
Caregivers* ; Child* ; Delivery of Health Care ; Diagnosis ; Education ; Hospitalization ; Humans ; Korea ; Patient Safety ; Pediatrics ; Surveys and Questionnaires

OBJECTIVES: The factors affecting the acceptance of mobile obesity-management applications (apps) by the public were analyzed using a mobile healthcare system (MHS) technology acceptance model (TAM). METHODS: The subjects who participated in this study were Android smartphone users who had an intent to manage their weight. They used the obesity-management app for two weeks, and then completed an 18-item survey designed to determine the factors influencing the acceptance of the app. Three questions were asked pertaining to each of the following six factors: compatibility, self-efficacy, technical support and training, perceived usefulness, perceived ease of use, and behavior regarding intention to use. Cronbach's alpha was used to assess the reliability of the scales. Pathway analysis was also performed to evaluate the MHS acceptance model. RESULTS: A total of 94 subjects participated in this study. The results indicate that compatibility, perceived usefulness, and perceived ease of use significantly affected the behavioral intention to use the mobile obesity-management app. Technical support and training also significantly affected the perceived ease of use; however, the hypotheses that self-efficacy affects perceived usefulness and perceived ease of use were not supported in this study. CONCLUSIONS: This is the first attempt to analyze the factors influencing mobile obesity-management app acceptance using a TAM. Further studies should cover not only obesity but also other chronic diseases and should analyze the factors affecting the acceptance of apps among healthcare consumers in general.
Chronic Disease ; Delivery of Health Care ; Factor Analysis, Statistical ; Intention ; Mobile Health Units ; Obesity* ; Telemedicine ; Weight Loss ; Weights and Measures

PURPOSE: The purpose of this study was to compare the importance and performance of nursing interventions linked to five nursing diagnoses in CVA patients. METHODS: First, total 37 nursing diagnoses were identified from the analysis of 78 nursing records of CVA patients, and then top 5 diagnoses were mapped with nursing interventions. Second, each intervention was compared in terms of importance and performance by 80 nurses working at neurosurgical units from 5 general hospitals. Data were analyzed using mean, SD, and t-test using the SPSS program. RESULTS: Selected the top five nursing diagnoses were Acute Pain, Risk for Disuse Syndrome, Decreased Intracranial Adaptive Capacity, Ineffective Cerebral Tissue Perfusion and Acute Confusion. In general, most of the interventions were scored higher in importance than performance and most of independent interventions were not performed as frequently as it perceived in importance. The interventions which scored high in performance were the interventions ordered by physician or interventions related to medication behavior. CONCLUSION: We identified which nursing interventions should be performed more frequently and more critically important to nursing diagnoses. We recommend further research that enhances the performance of nursing interventions to provide better quality of nursing services to the patients in practice.
Acute Pain ; Cerebrovascular Disorders ; Hospitals, General ; Humans ; Nursing Diagnosis ; Nursing Process ; Nursing Records ; Nursing Services ; Perfusion

PURPOSE: The purpose of this study was to compare the importance and performance of nursing interventions linked to five nursing diagnoses in CVA patients. METHODS: First, total 37 nursing diagnoses were identified from the analysis of 78 nursing records of CVA patients, and then top 5 diagnoses were mapped with nursing interventions. Second, each intervention was compared in terms of importance and performance by 80 nurses working at neurosurgical units from 5 general hospitals. Data were analyzed using mean, SD, and t-test using the SPSS program. RESULTS: Selected the top five nursing diagnoses were Acute Pain, Risk for Disuse Syndrome, Decreased Intracranial Adaptive Capacity, Ineffective Cerebral Tissue Perfusion and Acute Confusion. In general, most of the interventions were scored higher in importance than performance and most of independent interventions were not performed as frequently as it perceived in importance. The interventions which scored high in performance were the interventions ordered by physician or interventions related to medication behavior. CONCLUSION: We identified which nursing interventions should be performed more frequently and more critically important to nursing diagnoses. We recommend further research that enhances the performance of nursing interventions to provide better quality of nursing services to the patients in practice.
Acute Pain ; Cerebrovascular Disorders ; Hospitals, General ; Humans ; Nursing Diagnosis ; Nursing Process ; Nursing Records ; Nursing Services ; Perfusion

OBJECTIVES: The purpose of the study was to develop and evaluate a clinical-guideline-based smartphone application ('app') for obesity management. METHODS: Obesity-related knowledge and functional requirements were extracted from clinical practice guidelines, a literature review, and consultations with experts. The extracted knowledge was used to design obesity-management algorithms, and the functions of the developed app are presented through a use case diagram and activity diagrams. The database and user interface were designed and then an app was developed. The proficiency and efficiency of the algorithm were evaluated using scenarios, while the user interface was assessed using a mobile heuristics evaluation tool, with its usability determined using the Post-Study System Usability Questionnaire. RESULTS: In total, 131 obesity-related knowledge statements and 11 functions for the app were extracted, and 5 algorithms (comprising 1 main algorithm and 4 subalgorithms) were developed. The database comprised 11 tables and 41 screens. The app was developed using the Android SDK platform 4.0.3, JDK 1.7.0, and Eclipse. The overall proficiency and efficiency scores of the algorithm were 88.0 and 69.1, respectively. In heuristics tests, 57 comments were made, and the mean usability score was 3.47 out of 5. Thirteen usability problems were identified by the heuristics and usability evaluations. CONCLUSIONS: The app developed in this study might be helpful for weight management because it can provide high-quality health information and intervention without spatial or temporal constraints. However, the clinical effectiveness of this app still requires further investigation.
Mobile Health Units ; Obesity* ; Referral and Consultation ; Telemedicine ; Weight Loss ; Surveys and Questionnaires

No abstract available.
Epidermal Cyst* ; Melanins*

OBJECTIVES: This study developed a diabetes self-management mobile application based on the information-motivation-behavioral skills (IMB) model, evidence extracted from clinical practice guidelines, and requirements identified through focus group interviews (FGIs) with diabetes patients. METHODS: We developed a diabetes self-management (DSM) app in accordance with the following four stages of the system development life cycle. The functional and knowledge requirements of the users were extracted through FGIs with 19 diabetes patients. A system diagram, data models, a database, an algorithm, screens, and menus were designed. An Android app and server with an SSL protocol were developed. The DSM app algorithm and heuristics, as well as the usability of the DSM app were evaluated, and then the DSM app was modified based on heuristics and usability evaluation. RESULTS: A total of 11 requirement themes were identified through the FGIs. Sixteen functions and 49 knowledge rules were extracted. The system diagram consisted of a client part and server part, 78 data models, a database with 10 tables, an algorithm, and a menu structure with 6 main menus, and 40 user screens were developed. The DSM app was Android version 4.4 or higher for Bluetooth connectivity. The proficiency and efficiency scores of the algorithm were 90.96% and 92.39%, respectively. Fifteen issues were revealed through the heuristic evaluation, and the app was modified to address three of these issues. It was also modified to address five comments received by the researchers through the usability evaluation. CONCLUSIONS: The DSM app was developed based on behavioral change theory through IMB models. It was designed to be evidence-based, user-centered, and effective. It remains necessary to fully evaluate the effect of the DSM app on the DSM behavior changes of diabetes patients.
Blood Glucose Self-Monitoring ; Diabetes Mellitus ; Focus Groups ; Heuristics ; Humans ; Life Cycle Stages ; Methyltestosterone ; Mobile Applications* ; Mobile Health Units ; Self Care* ; Telemedicine

Purpose: As industries develop rapidly, the risk of heavy metals pollution and exposure in the environmentand food is increasing. Even the slightest amount of heavy metals can be harmful to the human body, especiallyin newborn babies. This study aimed to estimate the heavy metals content in breast milk and identifyrelated factors. Methods: Thirty-nine lactating mothers admitted to the postpartum care center in Changwon city betweenJuly 15 and September 20, 2019 were recruited. Barium, cadmium, cobalt, nickel, and lead concentrationsin breast milk were measured using an inductively coupled plasma-optical emission spectrometer. Collecteddata were analyzed using independent t-test, 1-way analysis of variance, Mann-Whitney U-test,Kruskal-Wallis test, and Pearson correlation coefficients. Results: The average concentration of heavy metals in breast milk (mg/kg) were as fellow: barium, 3.68±1.29; cadmium, 0.03±0.06; cobalt, 0.10±0.19; nickel, 0.22±0.27; and lead, 0.13±0.26. There was a significantdifference between lead concentration and monthly household income (t=2.46, p=0.019). Therewas a difference between a family history of diabetes and hypertension and barium concentration (t=1.97,p=0.056) and between smoking history and nickel concentration (t=-1.95, p=0.058), but they were notstatistically significant. A significantly positive correlation was observed between cobalt and cadmiumconcentrations (r=0.93, p<0.001), and a significant negative correlation was observed between nickel andcadmium concentrations (r=-0.40, p=0.010) and cobalt concentration (r=-0.46, p=0.003). In addition,lead concentration showed a significant negative correlation with age (r=-0.39, p=0.013). Conclusions Guidelines for safe levels of heavy metals concentrations in breast milk need to be establishedand lactating mothers should consider the risk factors related to heavy metals poisoning such as dietaryintake, smoking, and alcohol consumption.

This study explored the experiences of pregnant women with depressed mood participating ina group cognitive behavioral therapy (CBT) program using video communication, based on Beck’s cognitive theory.Methods: The participants were six pregnant women out of 13 women who had participated in an 8-session group CBT program using video communication for women with depressed mood (EdinburghPostnatal Depression score of ≥9). Data were collected from February 20 through March 25, 2021. Indepth individual interviews were conducted through a video conferencing platform at 1 month post-baseline. Thematic analysis was done.Results: Three themes, 10 subthemes, and 38 concepts were derived from experiences of participating inthe 4-week group CBT program (twice a week). The first theme, entitled “continuing realization” hadsubthemes of “a negative and instable self,” “a selfish judgment that excludes others,” and “a strong beliefin self-control.” The second theme, entitled “attempt to change for restoration” had subthemes of “shift torational thinking,” “freedom from suppressed beliefs,” “tolerance of other people,” and “courage for self-expression.” The third theme, entitled “departure for a positive life,” had subthemes of “emotional healing,”“faith in oneself,” and “reestablishing the criteria for happiness.”Conclusion: Pregnant women with depressed mood expressed that continuing realizations and attemptsto change supported their transition toward a positive direction of healing. Thus, they were able to changetheir distorted thinking into rational thinking through CBT using video communication. These findingssupport the use of group CBT using video communication with pregnant women who have depressedmood.

Electronic Health Records (EHRs)-based surveillance systems are being actively developed for detecting adverse drug reactions (ADRs), but this is being hindered by the difficulty of extracting data from unstructured records. This study performed the analysis of ADRs from nursing notes for drug safety surveillance using the temporal difference method in reinforcement learning (TD learning).