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Record W4221132449 · doi:10.1136/bmjopen-2021-055990

Technology-based group exercise interventions for people living with dementia or mild cognitive impairment: a scoping review protocol

2022· review· en· W4221132449 on OpenAlexaff
Lillian Hung, Hannah Levine, Paavan Randhawa, Juyoung Park

Bibliographic record

VenueBMJ Open · 2022
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsLangara CollegeVancouver General HospitalUniversity of British Columbia
FundersUniversidad del AtlánticoFlorida Atlantic University
KeywordsMedicineDementiaCognitive impairmentPsychological interventionProtocol (science)GerontologyCognitionPhysical therapyPhysical medicine and rehabilitationAlternative medicinePsychiatryDiseasePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: More than 50 million people worldwide are living with dementia in 2020, and this number is expected to double every 20 years. Physical exercise is a growing field in non-pharmacological interventions for dementia care. Due to public health measures during the COVID-19 pandemic, more people have considered adapting to technology-based exercise via digital devices. This scoping review will explore evidence relating to the use of technology-based group exercise by people with dementia or mild cognitive impairment. METHODS AND ANALYSIS: This review will follow the Joanna Briggs Institute scoping review methodology to review literature published between June and December 2021. This review is designed to identify existing types of technology-based group exercise interventions for people with dementia. The review will provide a synthesis of current evidence on the outcome and impacts of technology-based group exercise. The context of this review will include homes, assisted living facilities and memory care services but exclude hospitals. The review will include a three-step search strategy: (a) identify keywords from MEDLINE and Embase, (b) search using the identified keywords in databases (MEDLINE/PubMed, CINAHL, Web of Science, Embase, Cochrane Library, PsychInfo and Google) and (c) review references from included studies to identify additional studies. Only studies in English will be included. Four researchers will independently assess titles and abstracts and then review the full text of the selected articles, applying the inclusion criteria. The extracted data will be presented in tables and summarised narratively. ETHICS AND DISSEMINATION: Scoping review data will be collected from publicly available articles; research ethics approval is not required. The findings will be disseminated to healthcare practitioners and the public through a peer-reviewed publication and conference presentations.

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)0.068
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.091
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.051
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0140.013
Bibliometrics0.0150.013
Science and technology studies0.0050.005
Scholarly communication0.0080.009
Open science0.0060.007
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0910.019

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 head0.178
GPT teacher head0.523
Teacher spread0.345 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations8
Published2022
Admission routes1
Has abstractyes

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