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Record W2810943627 · doi:10.1177/0008417418777530

What do we know about technologies for dementia-related wandering? A scoping review

2018· review· en· W2810943627 on OpenAlexvenueno aff
Noelannah Neubauer, Nolwenn Lapierre, Adriana Ríos Rincón, Antonio Miguel Cruz, Jacqueline Rousseau, Lili Liu

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2018
Typereview
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaPsychological interventionAssistive technologyPsychologyGrey literatureOccupational therapySystematic reviewMedicineMEDLINENursingPsychiatryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Occupational therapists use technologies to manage wandering-related risks to promote safety and independence among individuals with dementia living in the community. PURPOSE: The purpose of this review was to examine types of technologies used to manage wandering behaviour. METHOD: Using a modification of Arksey and O'Malley's methodology, we systematically searched peer-reviewed and grey literature on technologies used in home or supportive care environments for persons with dementia at risk for wandering. Data from the studies were analyzed descriptively. FINDINGS: The literature described 83 technologies. Nineteen devices were clinically tested. Interventions ranged from alarm products to mobile locator devices. Benefits included reductions in risk and caregiver burden. IMPLICATIONS: Occupational therapy strategies include technologies to enhance function in persons with dementia. Technologies can also reduce risks of wandering and should be affordable. Ethical issues of the use of technology must be addressed. More research is needed to increase levels of evidence.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.407
GPT teacher head0.575
Teacher spread0.168 · 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 designOther design
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

Citations41
Published2018
Admission routes1
Has abstractyes

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