Evidence map›Paper›PMID 37118785›Full record

ArticleArchives of public health = Archives belges de sante publique2023

Development of a frailty index from the Dutch public health monitor 2016 and investigation of its psychometric properties: a cross-sectional study.

Nanda Kleinenberg-Talsma, Fons van der Lucht, Harriët Jager-Wittenaar, Wim Krijnen, Evelyn Finnema

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In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Observational
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nanda Kleinenberg-TalsmaResearch Group Healthy Ageing, Allied Health Care and Nursing, Hanze University of Applied Sciences, Groningen, The Netherlands. n.kleinenberg@pl.hanze.nl.
Fons van der LuchtResearch Group Healthy Ageing, Allied Health Care and Nursing, Hanze University of Applied Sciences, Groningen, The Netherlands.
Harriët Jager-WittenaarResearch Group Healthy Ageing, Allied Health Care and Nursing, Hanze University of Applied Sciences, Groningen, The Netherlands.
Wim KrijnenResearch Group Healthy Ageing, Allied Health Care and Nursing, Hanze University of Applied Sciences, Groningen, The Netherlands.
Evelyn FinnemaFAITH research, Groningen/Leeuwarden, The Netherlands.

Funding

Nationaal Regieorgaan Praktijkgericht Onderzoek SIA SPR.VG01.001
6 · The paper itself

Abstract

backgroundFrailty 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.

methodsWe 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.

resultsCronbach'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.

conclusionThe 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.

Indexed as

FrailtyHealth monitorsOlder adultsPsychometric analysis

Identifiers

PMID37118785
PMCPMC10142448

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.