(magistrsko delo)
Anja Štante (Author), Gregor Štiglic (Mentor), Leona Cilar (Co-mentor)

Abstract

Uvod: Delež starejših od 65 let se v populaciji veča. Napovedi kažejo, da se bo do leta 2100 še povečal. Ena od problematik, ki se pojavlja pri starejših, je upad kognitivnih sposobnosti. Metode: Analizirali smo podatke iz raziskave The Survey of Health, Aging and Retirement in Europe pri valu 6 in 7. Oblikovali smo dve skupini podatkov. V prvo smo uvrstili vse razpoložljive podatke iz držav Evropske unije, v drugo podatke zbrane v Republiki Sloveniji. Analizo podatkov smo izvedli v programskem jeziku R. Z uporabo napovednih modelov smo poskušali napovedati spremembe v vrednosti spremenljivke »razlika v takojšnjem priklicu besed med valoma 6 in 7«. Uporabili smo tri napovedne modele, in sicer multiplo logistično regresijo, Random Forest in Gradient Boosting Machine. Pri dobljenih rezultatih smo primerjali vrednost površine pod krivuljo. Rezultati: Pri evropski populaciji se je kot najboljši napovedni model izkazala multipla logistična regresija z rezultatom pri vrednosti AUC 0,698 (95% IZ: 0,678-0,705). Pri slovenski populaciji se je kot najboljši izkazal Gradient Boosting Machine z rezultati pri AUC 0,698 (95% IZ: 0,663-0,760). Razprava in sklep: Izkazalo se je, da na izhodno spremenljivko vplivajo spremenljivke, ki so že zaznane v drugih študijah. Te so priklic besed pri valu 6, starost in stopnja izobrazbe. Pri evropski populaciji je opazen vpliv spremenljivke samoocena računalniških sposobnosti. Študije s področja kognitivnih sposobnosti pri starejših na območju Republike Slovenije so pomembne, saj se slovenska družba stara.

Keywords

staranje;kognitivni upad;priklic besed;SHARE;napovedni model;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FZV - Faculty of Health Sciences
Publisher: [A. Štante]
UDC: 159.95:159.922.63(043.2)
COBISS: 68315395 Link will open in a new window
Views: 402
Downloads: 63
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: English
Secondary title: Predicting changes of cognitive abilities among older population
Secondary abstract: Introduction: In the population the share of people over 65 years old is increasing. Forecasts suggest that it will increase further by 2100. One of the problems that occurs among the elderly is a decline in cognitive abilities. Methods: We analyzed data from The Survey of Health, Aging and Retirement in Europe through waves 6 and 7. Two data sets were analyzed. In the first one was included data from the European Union, and in the second was included only data from Slovenia. The data analysis was performed in the programming language R. Using predictive models, we tried to predict changes in the variable "difference in the immediate recall of words between waves 6 and 7". We used three prediction models: Gradient boosting machine, multiple logistic regression, and Random Forest. In the obtained results we compared the value of the area under the curve. Results: In the European population, multiple logistic regression proved to be the best predictive model with AUC 0.698 (95% CI: 0.678-0.705). In the Slovenian population Gradient boosting machine proved to be the best with AUC 0.698 (95% CI: 0.663-0,760). Discussion and conclusion: It turned out that the input variable has been influenced by variables already detected in other studies. These are word recall at wave 6, age, and level of education. In the European population the influence of the variable self-assessment of computer skills is noticeable. Due to aging of Slovenian society, studies in the field of cognitive abilities in the elderly are important.
Secondary keywords: aging;cognitive decline;recall;SHARE;predictive model;Aging;Cognitive aging;Staranje;Kognitivno staranje;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za zdravstvene vede
Pages: V, 33 str.
ID: 12875696