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Record W2345977868 · doi:10.2196/rehab.5226

Information and Communication Technologies in the Care of the Elderly: Systematic Review of Applications Aimed at Patients With Dementia and Caregivers

2016· review· en· W2345977868 on OpenAlexvenueno aff
Claudia I. Martínez-Alcalá, Patricia Pliego‐Pastrana, Alejandra Rosales-Lagarde, JS Lopez-Noguerola, Eva María Molina-Trinidad

Bibliographic record

VenueJMIR Rehabilitation and Assistive Technologies · 2016
Typereview
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersUniversidad Autónoma del Estado de HidalgoConsejo Nacional de Ciencia y Tecnología
KeywordsDementiaSystematic reviewGerontologyMedicinePsychologyMEDLINEPolitical scienceDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The interest in applying information and communications technology (ICT) in older adult health care is frequently promoted by the increasing and unsustainable costs of health care services. In turn, the unprecedented growth of the elderly population around the globe has urged institutions, companies, industries, and governments to respond to older adults' medical needs. OBJECTIVE: The aim of this review is to systematically identify the opportunities that ICT offers to health services, specifically for patients with dementia and their families. METHODS: A systematic review of the literature about ICT applications that have been developed to assist patients with Alzheimer's disease (AD) and their primary caregivers was conducted. The bibliographic search included works published between January 2005 and July 2015 in the databases Springer Link, Scopus, and Google Scholar. Of the published papers, 902 were obtained in the initial search, of which 214 were potentially relevant. Included studies fulfilled the following inclusion criteria: (1) studies carried out between the years of 2005 and 2015, (2) studies were published in English or Spanish, (3) studies with titles containing the keywords, (4) studies with abstracts containing information on ICT applications and AD, and (5) studies published in indexed journals, proceedings, and book chapters. RESULTS: A total of 26 studies satisfied the inclusion criteria for the current review. Among them, 16 were aimed at the patient with AD and 10 at the primary caregivers and/or family members. The studies targeted applications that included assistive technology (44%, 7/16), telecare (37%, 6/16), and telemedicine (31%, 5/16). The information systems (56%, 9/16) and Internet (44%, 7/16) were the most commonly used enabling technologies for the studies. Finally, areas of attention more covered by the studies were care (56%, 9/16), treatment (56%, 9/16), and management (50%, 8/16). Furthermore, it was found that 20 studies (77%, 8/26) evaluated their ICT applications through carrying out tests with patients with dementia and caregivers. CONCLUSIONS: The key finding of this systematic review revealed that the use of ICT tools can be strongly recommended to be used as a lifestyle in the elderly in order to improve the quality of life for the elderly and their primary caregivers. Since patients with AD are completely dependent in most activities, it is necessary to give attention to their primary caregivers to avoid stress and depression. In addition, the use of ICT in the daily life of caregivers can help them understand the disease process and manage situations in a way that is beneficial for both parties. It is expected that future developments concerning technological projects can support this group of people.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0100.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.293
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations129
Published2016
Admission routes1
Has abstractyes

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