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Record W3185086149 · doi:10.3390/su13158465

Sustainable Technologies for Older Adults

2021· article· en· W3185086149 on OpenAlexaboutno aff
Jorge Morato, Sonia Sánchez-Cuadrado, Ana Iglesias, Adrián Campillo, Carmen Fernández-Panadero

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersAgencia Estatal de InvestigaciónMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaMinisterio de Ciencia, Innovación y Universidades
KeywordsScopusSustainabilityPopulation ageingGerontologyQuarter (Canadian coin)PopulationHealthy agingInclusion (mineral)PsychologyPolitical scienceSociologyMedicineSocial scienceMEDLINEGeographyEnvironmental health

Abstract

fetched live from OpenAlex

The exponential evolution of technology and the growth of the elderly population are two phenomena that will inevitably interact with increasing frequency in the future. This paper analyses scientific literature as a means of furthering progress in sustainable technology for senior living. We carried out a bibliometric analysis of papers published in this area and compiled by the Web of Science (WOS) and Scopus, examining the main participants and advances in the field from 2000 to the first quarter of 2021. The study describes some interesting research projects addressing three different aspects of older adults’ daily lives—health, daily activities and wellbeing—and policies to promote healthy aging and improve the sustainability of the healthcare system. It also looks at lines of research into transversal characteristics of technology. Our analysis showed that publications mentioning sustainability technologies for older adults have been growing progressively since the 2000s, but that the big increase in the number of research works in this area took place during the period 2016–2021. These more recent works show a tendency to study those factors that improve healthy aging, ensure the social inclusion of the elderly through technology and prolong the time in which they can live independent lives thanks to smart environments. Current research gaps in the literature are also discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.292
Teacher spread0.285 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations37
Published2021
Admission routes1
Has abstractyes

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