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Record W2899161618 · doi:10.1186/s13690-018-0316-y

Barriers and enablers in the use of respite interventions by caregivers of people with dementia: an integrative review

2018· review· en· W2899161618 on OpenAlexaff
Marie-Conception Leocadie, Marie-Hélène Roy, Monique Rothan‐Tondeur

Bibliographic record

VenueArchives of Public Health · 2018
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsRoyal Society of Canada
Fundersnot available
KeywordsRespite careDementiaPsychological interventionPublic healthNursingHealth informaticsMedicineHealth services researchHealth administrationGerontologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Due to the increase in the number of people with dementia, relatives often provide in-home care. This care constitutes a cornerstone of the healthcare system, and maintaining these caregivers' well-being is therefore of paramount importance. Although respite interventions are generally considered an effective support system, they tend to be underutilized. The aim of this integrative literature review is to highlight the factors that promote and impede the use of respite interventions. METHODS: Searches were conducted on the PubMed and CINAHL databases for studies of respite interventions from 1980 to 2016, and they yielded 51 articles of relevance. RESULTS: Analysis of these articles revealed modifiable and immutable factors that influence the use of respite. The most cited topic categories in the literature were attributes of respite services and workload managed by caregivers, which is characterized by the onset of burden. CONCLUSION: The factors promoting or impeding the use of respite interventions identified by our analysis highlight the need to adapt respite service attributes and use caregivers' skills to foster the partnership between healthcare teams and caregivers and to ensure the accompanying dyad's quality and safety.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.792
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.131
GPT teacher head0.419
Teacher spread0.289 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations53
Published2018
Admission routes1
Has abstractyes

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