Technologies for frailty, comorbidity, and multimorbidity in older adults: a systematic review of research designs.


Journal

BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545

Informations de publication

Date de publication:
11 07 2023
Historique:
received: 07 09 2022
accepted: 09 06 2023
medline: 13 7 2023
pubmed: 12 7 2023
entrez: 11 7 2023
Statut: epublish

Résumé

Frailty, neurodegeneration and geriatric syndromes cause a significant impact at the clinical, social, and economic level, mainly in the context of the aging world. Recently, Information and Communication Technologies (ICTs), virtual reality tools, and machine learning models have been increasingly applied to the care of older patients to improve diagnosis, prognosis, and interventions. However, so far, the methodological limitations of studies in this field have prevented to generalize data to real-word. This review systematically overviews the research designs used by studies applying technologies for the assessment and treatment of aging-related syndromes in older people. Following the PRISMA guidelines, records from PubMed, EMBASE, and Web of Science were systematically screened to select original articles in which interventional or observational designs were used to study technologies' applications in samples of frail, comorbid, or multimorbid patients. Thirty-four articles met the inclusion criteria. Most of the studies used diagnostic accuracy designs to test assessment procedures or retrospective cohort designs to build predictive models. A minority were randomized or non-randomized interventional studies. Quality evaluation revealed a high risk of bias for observational studies, while a low risk of bias for interventional studies. The majority of the reviewed articles use an observational design mainly to study diagnostic procedures and suffer from a high risk of bias. The scarce presence of methodologically robust interventional studies may suggest that the field is in its infancy. Methodological considerations will be presented on how to standardize procedures and research quality in this field.

Sections du résumé

BACKGROUND
Frailty, neurodegeneration and geriatric syndromes cause a significant impact at the clinical, social, and economic level, mainly in the context of the aging world. Recently, Information and Communication Technologies (ICTs), virtual reality tools, and machine learning models have been increasingly applied to the care of older patients to improve diagnosis, prognosis, and interventions. However, so far, the methodological limitations of studies in this field have prevented to generalize data to real-word. This review systematically overviews the research designs used by studies applying technologies for the assessment and treatment of aging-related syndromes in older people.
METHODS
Following the PRISMA guidelines, records from PubMed, EMBASE, and Web of Science were systematically screened to select original articles in which interventional or observational designs were used to study technologies' applications in samples of frail, comorbid, or multimorbid patients.
RESULTS
Thirty-four articles met the inclusion criteria. Most of the studies used diagnostic accuracy designs to test assessment procedures or retrospective cohort designs to build predictive models. A minority were randomized or non-randomized interventional studies. Quality evaluation revealed a high risk of bias for observational studies, while a low risk of bias for interventional studies.
CONCLUSIONS
The majority of the reviewed articles use an observational design mainly to study diagnostic procedures and suffer from a high risk of bias. The scarce presence of methodologically robust interventional studies may suggest that the field is in its infancy. Methodological considerations will be presented on how to standardize procedures and research quality in this field.

Identifiants

pubmed: 37434136
doi: 10.1186/s12874-023-01971-z
pii: 10.1186/s12874-023-01971-z
pmc: PMC10334509
doi:

Types de publication

Systematic Review Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

166

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© 2023. The Author(s).

Références

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Auteurs

Alessia Gallucci (A)

IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy. agallucci@dongnocchi.it.

Pietro D Trimarchi (PD)

IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy.

Cosimo Tuena (C)

Applied Technology for Neuro‑Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy.

Silvia Cavedoni (S)

Applied Technology for Neuro‑Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy.

Elisa Pedroli (E)

Applied Technology for Neuro‑Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Faculty of Psychology, University of eCampus, Novedrate, Italy.

Francesca Romana Greco (FR)

Geriatric Unit, Department of Medical Sciences, IRCCS ''Casa Sollievo della Sofferenza'', San Giovanni Rotondo, Italy.

Antonio Greco (A)

Geriatric Unit, Department of Medical Sciences, IRCCS ''Casa Sollievo della Sofferenza'', San Giovanni Rotondo, Italy.

Carlo Abbate (C)

IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy.

Fabrizia Lattanzio (F)

Scientific Direction, IRCCS INRCA, Ancona, Italy.

Marco Stramba-Badiale (M)

Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, Milan, Italy.

Fabrizio Giunco (F)

IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy.

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