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Record W4360838341 · doi:10.1080/17483107.2023.2192245

Technologies for monitoring activities of daily living in older adults: a systematic review

2023· review· en· W4360838341 on OpenAlexaff
Natasha Gadey, Patricia Pataunia, Andrew Chan, Adriana Ríos Rincón

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2023
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsGlenrose Rehabilitation HospitalUniversity of Alberta
Fundersnot available
KeywordsActivities of daily livingCINAHLChecklistUsabilityIndependent livingPopulationMedicineSystematic reviewScope (computer science)GerontologyMEDLINEPsychologyComputer sciencePhysical therapyNursing

Abstract

fetched live from OpenAlex

PURPOSE: As the older adult population rise globally, technologies to monitoring activities of daily living (ADL) may have a role in supporting aging in place for older adults. The objective of this systematic literature review was to study the scope, diversity and readiness of technologies developed to monitor ADL in older adults. METHODS: We systematically searched two scientific databases (CINAHL and IEEE), following Preferred Reporting Items for Systematic reviews and Meta Analyses (PRISMA) guidelines. We included studies on technologies used to monitor older adults' ADL in the home but excluded studies focused on communication technologies (phone calls, text messages) or monitoring postures alone. The JBI checklist for case series was used for quality assessment. Extracted details included population characteristics, ADL assessment outcomes, types of monitoring technology, and technology readiness and usability. RESULTS: The search found 147 papers, with 16 papers included in the final analysis. The literature described 48 types of technologies. Of moderate quality studies, five studies used wearables at technology readiness level 4-6 to monitor basic ADL (walking, transfers and walking up stairs) and one used ambient sensors to detect urinary incontinence. CONCLUSIONS: Monitoring technologies remain at development stages. More research is needed to strengthen technologies that monitor activities of daily living.

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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
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 score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.024
GPT teacher head0.350
Teacher spread0.325 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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