Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
Medientyp:
E-Artikel
Titel:
Development of a frailty index from the Dutch public health monitor 2016 and investigation of its psychometric properties: a cross-sectional study
Beteiligte:
Kleinenberg-Talsma, Nanda;
van der Lucht, Fons;
Jager-Wittenaar, Harriët;
Krijnen, Wim;
Finnema, Evelyn
Erschienen:
Springer Science and Business Media LLC, 2023
Beschreibung:
<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Background</jats:title>
<jats:p>Frailty in older adults is an increasing challenge for individuals, health care organizations and public health, both globally and in The Netherlands. To focus on frailty prevention from a public health perspective, understanding of frailty status is needed. To enable measurement of frailty within a health survey that currently does not contain an established frailty instrument, we aimed to construct a frailty index (FI) and investigate its psychometric properties.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>We conducted a cross-sectional study using data from the Dutch Public Health Monitor (DPHM), including respondents aged ≥ 65 years (n = 233,498). Forty-two health deficits were selected based on literature, previously constructed FIs, face validity and standard criteria for FI construction. Deficits were first explored by calculating Cronbach’s alpha, point-polyserial correlations, and factor loadings. Thereafter, we used the Graded Response Model (GRM) to assess item difficulty, item discrimination, and category thresholds.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Cronbach’s alpha for the 42 items was 0.91. Thirty-seven deficits showed strong psychometric properties: they scored above the cutoff values for point-polyserial correlations (0.3) or factor loadings (0.4) and had moderate to very high discrimination parameters (≥ 0.65). These deficits were retained in the scale. Retaining the deficits with favorable measurement properties and removing the remaining deficits resulted in the FI-HM37.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>The FI-HM37 was developed, an FI with 37 deficits indicative of frailty, both statistically and conceptually. Our results indicate that health monitors can be used to measure frailty, even though they were not directly designed to do so. The GRM is a suitable approach for deficit selection, resulting in a psychometrically strong scale, that facilitates assessment of frailty levels using the DPHM.</jats:p>
</jats:sec>