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RESEARCH PRODUCT

Assessing competence: The European survey on aging protocol (ESAP)

Georg RudingerConstanza PaulJadwiga CharzewskaRocío Fernández-ballesterosAndrea DrusiniJ.j.f. SchrootsLeopold RosenmayrEino HekkinnenMaría Dolores Zamarrón

subject

GerontologyAdultLongitudinal studyAgingPsychometricsmedia_common.quotation_subjectHealth StatusIntelligencePilot ProjectsStructural equation modelingSurveys and QuestionnairesPersonalityHumansInterpersonal RelationsMental CompetencyCompetence (human resources)Life Stylemedia_commonAgedAged 80 and overSuccessful agingAnthropometryAge FactorsSDG 10 - Reduced InequalitiesAnthropometryMiddle AgedExploratory factor analysisEuropeSocioeconomic FactorsPhysical Fitness/dk/atira/pure/sustainabledevelopmentgoals/reduced_inequalitiesGeriatrics and GerontologyPsychologyPsychosocialPersonality

description

<i>Objectives:</i> The main goal of this research project was to translate and adapt the European Survey on Ageing Protocol (ESAP) to 7 European countries/cultures. This article presents preliminary results from the ESAP, the basic assessment instrument of EXCELSA (European Longitudinal Study of Aging). <i>Methods:</i> 672 individuals aged 30–85, selected through quota sampling (by age, gender, education and living conditions), participated in this study, with 96 subjects from each of the 7 European countries. The basic research protocol for assessing competence and its determinants was designed to be administered in a 90-min in-home face-to-face interview. It contains a series of questions, instruments, scales and physical tests assessing social relationships and caregiving, mental abilities, well-being, personality, mastery and perceived control, self-reported health, lifestyles, anthropometry, biobehavioral measures and sociodemographic variables. <i>Results:</i> 84% of ESAP measures are age-dependent and 75% of them discriminate between education levels. Minor differences were found due to gender, and between people living in rural and urban areas. Exploratory factor analysis yielded 10 factors accounting for 67.85% of total variance, one of which was identified as cognitive and physical ‘competence’. This factorial structure was tested across countries through concordance coefficients. Finally, using structural equation modeling, our data were fitted into a model of competence. When the sample was split into younger groups (aged 30–49 years) and older ones (50 and more years), the same model was appropriate for our data. <i>Discussion:</i> The results are discussed in accordance with other findings on psychosocial, biophysical and sociodemographic components of competence, and also in accordance with theories on competence and successful aging.

10.1159/000079132http://web.ebscohost.com/ehost/pdfviewer/pdfviewer?hid=11&sid=556d35ff-5067-4311-a546-be1ab93b3b74@sessionmgr13&vid=1