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1.
Artificial intelligence based prediction of diabetic foot risk in patients with diabetes : a literature review
Lucija Gosak, Adrijana Svenšek, Mateja Lorber, Gregor Štiglic, 2023, pregledni znanstveni članek

Opis: Diabetic foot is a prevalent chronic complication of diabetes and increases the risk of lower limb amputation, leading to both an economic and a major societal problem. By detecting the risk of developing diabetic foot sufficiently early, it can be prevented or at least postponed. Using artificial intelligence, delayed diagnosis can be prevented, leading to more intensive preventive treatment of patients. Based on a systematic literature review, we analyzed 14 articles that included the use of artificial intelligence to predict the risk of developing diabetic foot. The articles were highly heterogeneous in terms of data use and showed varying degrees of sensitivity, specificity, and accuracy. The most used machine learning techniques were support vector machine (SVM) (n = 6) and K-Nearest Neighbor (KNN) (n = 5). Future research is recommended on larger samples of participants using different techniques to determine the most effective one.
Ključne besede: artificial intelligence, machine learning, thermography, diabetic foot prediction, diabetes, diabetes care, diabetic foot, literature review
Objavljeno v DKUM: 27.11.2023; Ogledov: 209; Prenosov: 10
.pdf Celotno besedilo (654,91 KB)
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2.
Innovative nursing care : education and research
znanstvena monografija

Opis: Higher life expectancy on a global level requires complex nursing care as poor education and a lack of knowledge can lead to mistakes. There is a need for nurses who can provide high quality and advanced nursing practice. A mix of well-grounded education and innovative research is needed, where the first provides an understanding of best nursing practice care delivery and the second helps nurses determine best practices and improve nursing care. Provides a current and in-depth picture of actual nursing challenges in education, research, and clinical practice. Helpful in nursing students' education in broader nursing care fields and different approaches in holistic nursing care.
Ključne besede: nursing care, palliative care, dementia, emergencies, triage, education, COVID-19, older people, children, nursing students
Objavljeno v DKUM: 27.11.2023; Ogledov: 209; Prenosov: 11
.pdf Celotno besedilo (1,66 MB)
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3.
Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications : a systematic review of the literature
Lucija Gosak, Kristina Martinović, Mateja Lorber, Gregor Štiglic, 2022, pregledni znanstveni članek

Opis: Aim The aim of this review is to examine the effectiveness of artificial intelligence in predicting multimorbid diabetes-related complications. Background In diabetic patients, several complications are often present, which have a significant impact on the quality of life; therefore, it is crucial to predict the level of risk for diabetes and its complications. Evaluation International databases PubMed, CINAHL, MEDLINE and Scopus were searched using the terms artificial intelligence, diabetes mellitus and prediction of complications to identify studies on the effectiveness of artificial intelligence for predicting multimorbid diabetes-related complications. The results were organized by outcomes to allow more efficient comparison. Key issues Based on the inclusion/exclusion criteria, 11 articles were included in the final analysis. The most frequently predicted complications were diabetic neuropathy (n = 7). Authors included from two to a maximum of 14 complications. The most commonly used prediction models were penalized regression, random forest and Naïve Bayes model neural network. Conclusion The use of artificial intelligence can predict the risks of diabetes complications with greater precision based on available multidimensional datasets and provides an important tool for nurses working in preventive health care. Implications for Nursing Management Using artificial intelligence contributes to a better quality of care, better autonomy of patients in diabetes management and reduction of complications, costs of medical care and mortality.
Ključne besede: artificial intelligence, prediction models, diabetes, prediction of diabetes complications
Objavljeno v DKUM: 03.10.2023; Ogledov: 185; Prenosov: 26
.pdf Celotno besedilo (509,07 KB)
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4.
Digital tools in behavior change support education in health and other students : a systematic review
Lucija Gosak, Gregor Štiglic, Leona Cilar Budler, Isa B. Félix, Katja Braam, Nino Fijačko, Mara Pereira Guerreiro, Mateja Lorber, 2022, pregledni znanstveni članek

Opis: Due to the increased prevalence of chronic diseases, behavior changes are integral to self-management. Healthcare and other professionals are expected to support these behavior changes, and therefore, undergraduate students should receive up-to-date and evidence-based training in this respect. Our work aims to review the outcomes of digital tools in behavior change support education. A secondary aim was to examine existing instruments to assess the effectiveness of these tools. A PIO (population/problem, intervention, outcome) research question led our literature search. The population was limited to students in nursing, sports sciences, and pharmacy; the interventions were limited to digital teaching tools; and the outcomes consisted of knowledge, motivation, and competencies. A systematic literature review was performed in the PubMed, CINAHL, MEDLINE, Web of Science, SAGE, Scopus, and Cochrane Library databases and by backward citation searching. We used PRISMA guidelines 2020 to depict the search process for relevant literature. Two authors evaluated included studies using the Mixed Methods Appraisal Tool (MMAT) independently. Using inclusion and exclusion criteria, we included 15 studies in the final analysis: six quantitative descriptive studies, two randomized studies, six mixed methods studies, and one qualitative study. According to the MMAT, all studies were suitable for further analysis in terms of quality. The studies resorted to various digital tools to improve students’ knowledge of behavior change techniques in individuals with chronic disease, leading to greater self-confidence, better cooperation, and practical experience and skills. The most common limitations that have been perceived for using these tools are time and space constraints.
Ključne besede: digital tools, didactics, noncommunicable diseases, chronic diseases, behavior change support education, health science
Objavljeno v DKUM: 28.09.2023; Ogledov: 204; Prenosov: 12
.pdf Celotno besedilo (460,18 KB)
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5.
The KIDSCREEN-27 scale: translation and validation study of the Slovenian version
Leona Cilar Budler, Majda Pajnkihar, Ulrike Ravens-Sieberer, Owen Barr, Gregor Štiglic, 2022, izvirni znanstveni članek

Opis: Background: There are many methods available for measuring social support and quality of life (QoL) of adolescents, of these, the KIDSCREEN tools are most widely used. Thus, we aimed to translate and validate the KIDSCREEN-27 scale for the usage among adolescents aged between 10 and 19 years old in Slovenia. Methods: A cross-sectional study was conducted among 2852 adolescents in primary and secondary school from November 2019 to January 2020 in Slovenia. 6-steps method of validation was used to test psychometric properties of the KIDSCREEN-27 scale. We checked descriptive statistics, performed a Mokken scale analysis, parametric item response theory, factor analysis, classical test theory and total (sub)scale scores. Results: All five subscales of the KIDSCREEN-27 formed a unidimensional scale with good homogeneity and reliability. The confirmatory factor analysis showed poor fit in user model versus baseline model metrics (CFI = 0.847; TLI = 0.862) and good fit in root mean square error (RMSEA = 0.072; p(χ2) < 0.001). A scale reliability was calculated using Cronbach's α (0.93), beta (0.86), G6 (0.95) and omega (0.93). Conclusions: The questionnaire showed average psychometric properties and can be used among adolescents in Slovenia to find out about their quality of life. Further research is needed to explore why fit in user model metrics is poor.
Ključne besede: social support, adolescent, psychometrics, factor analysis, quality of life
Objavljeno v DKUM: 23.08.2023; Ogledov: 195; Prenosov: 19
.pdf Celotno besedilo (1,77 MB)
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6.
Emotional intelligence among nursing students: findings from a longitudinal study
Leona Cilar Budler, Lucija Gosak, Dominika Vrbnjak, Majda Pajnkihar, Gregor Štiglic, 2022, izvirni znanstveni članek

Opis: Emotional intelligence is an important factor for nursing students’ success and work performance. Although the level of emotional intelligence increases with age and tends to be higher in women, results of different studies on emotional intelligence in nursing students vary regarding age, study year, and gender. A longitudinal study was conducted in 2016 and 2019 among undergraduate nursing students to explore whether emotional intelligence changes over time. A total of 111 undergraduate nursing students participated in the study in the first year of their study, and 101 in the third year. Data were collected using the Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF) and Schutte Self Report Emotional Intelligence Test (SSEIT). There was a significant difference in emotional intelligence between students in their first (M = 154.40; 95% CI: 101.85–193.05) and third year (M = 162.01; 95% CI: 118.65–196.00) of study using TEIQue-SF questionnaire. There was a weak correlation (r = 0.170) between emotional intelligence and age measuring using the TEIQue-SF questionnaire, and no significant correlation when measured using SSEIT (r = 0.34). We found that nursing students’ emotional intelligence changes over time with years of education and age, suggesting that emotional intelligence skills can be improved. Further research is needed to determine the gendered nature of emotional intelligence in nursing students.
Ključne besede: emotional intelligence, nursing, students, caring experience, TEIQue-SF, SSEIT
Objavljeno v DKUM: 23.08.2023; Ogledov: 225; Prenosov: 28
.pdf Celotno besedilo (798,48 KB)
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7.
Vpliv kakovosti delovnega okolja zaposlenih v zdravstveni negi na tveganje za pojav sindroma izgorelosti
Katja Godec, 2023, magistrsko delo

Opis: Uvod: Zdravstvena nega spada med poklice, ki so v večji meri izpostavljeni obremenitvam ter imajo visoko stopnjo ogroženosti za sindrom izgorelosti. Obremenitve, kot so stres, težki in agresivni pacienti na delovnem mestu, postajajo vse intenzivnejše in pogosto vodijo v nekakovostno delovno življenje in posledično v proces izgorevanja. Namen zaključnega dela je ugotoviti, kako zaposleni v zdravstveni negi doživljajo delovno okolje ter v kolikšni meri kakovost delovnega okolja vpliva na tveganje za pojav sindroma izgorelosti. Metode: Empirični del zaključnega dela temelji na kvantitativni metodologiji. Kot instrument za raziskovanje sta bila uporabljena anketna vprašalnika za oceno kakovosti delovnega okolja (WRQoL) in oceno stopnje izgorelosti (BAT). Raziskava je potekala med zaposlenimi v zdravstveni negi na sekundarni ravni v eni izmed slovenskih bolnišnic. Podatki so bili analizirani s pomočjo deskriptivne statistike z uporabo programa IBM SPSS Statistics 28.0. Rezultati: Stopnja poklicne izgorelosti pri medicinskih sestrah se je v naši raziskavi izkazala za nizko, vendar so udeleženci navedli visoko stopnjo stresa na delovnem mestu. Kakovost delovnega okolja medicinskih sester je bila na zmerni ravni. Ugotovljeno je bilo, da obstaja statistično pomembna povezava med kakovostjo delovnega okolja in tveganjem za pojav sindroma izgorelosti (p < 0,001). Razprava in zaključek: Nezadovoljstvo z delom vodi do večje stopnje nekakovostnega delovnega življenja in povečanega tveganja za nastanek pojava izgorelosti, kar posledično vpliva na kakovost zdravstvene nege. Rešitev k zmanjševanju izgorelosti zaposlenih v zdravstveni negi in k njeni prepoznavnosti vidimo v povečanju ozaveščanja o sindromu izgorelosti.
Ključne besede: izgorelost, medicinska sestra, kakovost delovnega okolja
Objavljeno v DKUM: 10.08.2023; Ogledov: 533; Prenosov: 121
.pdf Celotno besedilo (991,87 KB)

8.
Uporaba mobilnega zdravja in mobilnega učenja za samoobvladovanje sladkorne bolezni tipa 1 pri otrocih in mladostnikih
Nives Morčič, 2023, diplomsko delo

Opis: Uporaba mobilnih aplikacij na pametnih telefonih predstavlja potencial za izboljšanje urejenosti sladkorja v krvi in s tem zmanjšanje dolgoročnih zapletov bolezni pri otrocih in mladostnikih s slabo nadzorovano sladkorno boleznijo tipa 1. Namen zaključnega dela je raziskati vpliv uporabe mobilnega zdravja ter mobilnega učenja na samoobvladovanje sladkorne bolezni tipa 1 pri otrocih in mladostnikih.
Ključne besede: otroci, sladkorna bolezen tipa 1, mobilno zdravje, samooskrba
Objavljeno v DKUM: 13.07.2023; Ogledov: 257; Prenosov: 52
.pdf Celotno besedilo (1,24 MB)

9.
International Scientific Conference "Research and Education in Nursing" : Book of Abstracts, June 19th 2023, Maribor, Slovenia
2023

Opis: University of Maribor Faculty of Health Sciences celebrates the 30th anniversary of its founding. In honoring this occasion, we are organising the lnternational Scientific Conference "Research and Education in Nursing". It will be held on June 19th 2023 in Maribor and will include the most recent findings of domestic and foreign researchers in nursing and other healthcare fields. The conference aims to explore advances in nursing and health care research as well as research-based education, in the Slovenian and international arena. Furthermore, it will provide an opportunity far practitioners and educators to exchange research evidence, models of best practice and innovative ideas.
Ključne besede: higher education, nursing, health sciences, conference, research
Objavljeno v DKUM: 19.06.2023; Ogledov: 292; Prenosov: 32
.pdf Celotno besedilo (4,11 MB)
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10.
Korelacija med hipertenzijo in biološko starostjo in analiza njunega vpliva na smrtnost
Urša Deban, 2023, magistrsko delo

Opis: Uvod: Povišan krvni tlak oziroma hipertenzija je pomemben dejavnik tveganja srčno-žilnih in ledvičnih obolenj. Biološko starost lahko izračunamo na podlagi klinično merljivih parametrov. Metode: Z namenom analize korelacije med hipertenzijo in biološko starostjo in njuno povezanostjo s smrtnostjo smo analizirali podatke iz podatkovne zbirke NHANES, ki vsebuje podatke o zdravstvenem stanju ameriških prebivalcev. Iz podatkovne zbirke NCHS pa smo pridobili podatke o smrtnosti. Izračunali smo biološko starost in analizirali statistično pomembnost razlik v krvnem tlaku in biološkem staranju med različnimi demografskimi skupinami. Z modelom logistične regresije smo primerjali napovedno moč krvnega tlaka in staranja na smrtnost. Paciente smo razdelili v tri skupine glede na hipertenzivni status ter primerjali statistične parametre med njimi. Rezultati: Zaznali smo nizko korelacijo med krvnim tlakom in kronološko ter biološko starostjo, statistično pomembne razlike v biološkem staranju, ter krvnim tlakom in spolom. Ugotovili smo statistično pomembne razlike med nekaterimi, ne pa vsemi rasami. V analizi skupine hipertenzivnih pacientov nekatere razlike med demografskimi skupinami zbledijo. Izmed vseh testiranih spremenljivk se je kot najmočneje povezana s smrtnostjo pokazala ocena biološke starosti na podlagi krvnih meritev. Razprava in zaključek: Rezultati raziskave izpostavljajo pomen biološke starosti pri nastanku hipertenzije, nakazujejo razlike v krvnem tlaku med demografskimi skupinami in pomen biološke starosti pri oceni tveganja smrtnosti.
Ključne besede: hipertenzija, krvni tlak, biološko staranje, smrtnost, logistična regresija
Objavljeno v DKUM: 22.05.2023; Ogledov: 307; Prenosov: 69
.pdf Celotno besedilo (1,32 MB)

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