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Abstract: The Perceived Inventory of Technological Competency as Caring in Nursing (PITCCN) questionnaire has been designed to measure technological competency as caring in nursing practice. It incorporates the use of technology with the fundamental principles of caring that are central to nursing. As there were no psychometrically sound instruments to quantify the concept of technological competency as caring in the Slovene language, we adapted the English version of the questionnaire to the local environment. The goal was to assess the level of psychometric properties of the PITCCN investigated in Slovene hospitals. Methods: Content validity was conducted with eight experts and quantified by the content validity index (CVI) and the modified Cohen’s kappa index. Face validity was assessed through discussions with participants from the target culture in the pilot study. To assess construct validity and internal consistency, a cross-sectional research methodology was used on a convenience sample of 121 nursing personnel from four hospitals. Principal component analysis (PCA) was used to examine construct validity, while Cronbach’s alpha and adjusted item-total correlations were used to measure internal consistency. Results: The content and face validity of PITCCN were adequate. The scale validity index (S-CVI) was 0.97. Cronbach’s α was 0.92, and subscale reliabilities ranged from 0.810 to 0.925. PCA showed four components, which explained more than 73.49% of the variance. Conclusions: The Slovenian version of PITCCN (PITCCN_SI) has good psychometric properties.
Keywords: technology, caring, reliability, validity, psychometric properties
Published in DKUM: 28.03.2025; Views: 0; Downloads: 3
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Abstract: Publikacija "Napredne kvantitativne raziskovalne metode v zdravstveni negi" daje študentom zdravstvene nege in medicinskim sestram znanje in spretnosti za razlago različnih statističnih metod na njihovem področju, kar lahko izboljša spretnosti uporabnikov pri zbiranju, analizi in razlagi rezultatov iz klinične prakse ter tako prispeva k izboljšanju kakovosti zdravstvene oskrbe. Vsebuje podrobna navodila za uporabo programa IBM SPSS in izvajanje statističnih analiz, ki jih morajo medicinske sestre poznati pri svojem delu, saj pri vsakodnevnem delu s pacienti uporabljajo in ustvarjajo podatke. Glavni cilj zdravstvene nege pacientov je zagotavljanje kakovostne in na dokazih temelječe zdravstvene nege, zato so medicinske sestre dolžne slediti najnovejšim raziskavam in dokazom ter jih uporabljati pri svojem delu. Znanje, pridobljeno v tej knjigi, lahko medicinskim sestram pomaga tudi pri boljšem razumevanju in interpretaciji predhodno objavljenih rezultatov ter s tem pri kritični presoji veljavnosti in zanesljivosti rezultatov, ki jih bodo uporabljale v klinični praksi.
Keywords: quantitative analysis, statistics, IBM SPSS, reliability, validity, data analysis
Published in DKUM: 28.01.2025; Views: 0; Downloads: 17
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Abstract: Background: Although the internet facilitates access to a wide range of knowledge and evidence, overuse among young people is associated with lower wellbeing and psychosomatic symptoms. The aim of this cross-sectional study is to explore the relationship between internet use, mental wellbeing, and psychosomatic symptoms among university students in Slovenia. Methods: We used correlation matrix plots to identify correlated symptoms and multivariate logistic regression to analyze the relationship between the time spent on the internet or computer and psychosomatic symptoms controlling for gender. Symptoms were measured using the Health Behavior of School Children scale. Results: Out of 464 students, the majority (64.7%, n = 300) were healthcare students and 35.3% (n = 164) were computer science students. Among somatic symptoms, headaches were associated with more time spent on the computer (r = −0.17, p < 0.001) and were significantly more prevalent in computer science students compared to health science students (χ2(1) = 8.52, p = 0.004). Time spent using the internet for spare time activities was associated with lower nervousness (r = 0.15, p = 0.005). Conclusions: Computer science students reported more frequent psychological symptoms compared to health science students and less somatic symptoms.
Keywords: psychological symptoms, somatic symptoms, technology use, wellbeing, university students
Published in DKUM: 27.11.2024; Views: 0; Downloads: 3
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Abstract: Background: Retention of adult basic life support (BLS) knowledge and skills after professional training declines over time.To combat this, the European Resuscitation Council and the American Heart Association recommend shorter, more frequent BLS sessions. Emphasizing technology-enhanced learning, such as mobile learning, aims to increase out-of-hospital cardiac arrest (OHCA) survival and is becoming more integral in nursing education. Objective: The aim of this study was to investigate whether playing a serious smartphone game called MOBICPR at home can improve and retain nursing students’ theoretical knowledge of and practical skills in adult BLS. Methods: This study used a randomized wait list–controlled design. Nursing students were randomly assigned in a 1:1 ratio to either a MOBICPR intervention group (MOBICPR-IG) or a wait-list control group (WL-CG), where the latter received the MOBICPR game 2 weeks after the MOBICPR-IG. The aim of the MOBICPR game is to engage participants in using smartphone gestures (eg, tapping) and actions (eg, talking) to perform evidence-based adult BLS on a virtual patient with OHCA. The participants’ theoretical knowledge of adult BLS was assessed using a questionnaire, while their practical skills were evaluated on cardiopulmonary resuscitation quality parameters using a manikin and a checklist. Results: In total, 43 nursing students participated in the study, 22 (51%) in MOBICPR-IG and 21 (49%) in WL-CG. There were differences between the MOBICPR-IG and the WL-CG in theoretical knowledge (P=.04) but not in practical skills (P=.45) after MOBICPR game playing at home. No difference was noted in the retention of participants’ theoretical knowledge and practical skills of adult BLS after a 2-week break from playing the MOBICPR game (P=.13). Key observations included challenges in response checks with a face-down manikin and a general neglect of safety protocols when using an automated external defibrillator. Conclusions: Playing the MOBICPR game at home has the greatest impact on improving the theoretical knowledge of adult BLS in nursing students but not their practical skills. Our findings underscore the importance of integrating diverse scenarios into adult BLS training.
Keywords: serious smartphone game, adult basic life support, teaching, games, gaming, education, nurses, nursing, educational, mHealth, mobile health, applications, smartphones, randomized controlled trial, technology-enhanced learning, life support, knowledge retention, practical
Published in DKUM: 27.11.2024; Views: 0; Downloads: 3
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Abstract: Background: Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients’ behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. Objective: This review aims to present the most-used visualization techniques to estimate CVD risk. Methods: In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. Results: We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing–related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). Conclusions: On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health’s effectiveness in improving CVD outcomes is limited.
Keywords: cardiovascular disease prevention, risk factors, visual analytics, visualization, mobile phone, PRISMA
Published in DKUM: 26.11.2024; Views: 0; Downloads: 8
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