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Record W2948689416 · doi:10.1186/s12889-019-7014-8

Win/win partnerships between Geneva health-related institutions and caregivers of people with dementia: a descriptive cross-sectional study

2019· article· en· W2948689416 on OpenAlexaff
Marie-Conception Leocadie, Hélène Lefebvre, Monique Rothan‐Tondeur

Bibliographic record

VenueBMC Public Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsBiostatisticsMedicineCross-sectional studyPublic healthDementiaDescriptive researchEpidemiologyEnvironmental healthFamily medicineGerontologyNursingDisease

Abstract

fetched live from OpenAlex

BACKGROUND: In the context of an ageing population and an increase in the appearance of chronic diseases, the commitment of caregivers makes it possible for people confronted with disease to remain at home. Over time, they need support to overcome their difficulties. They also show a need for recognition for their participation in the economic maintenance of the health system. To promote this support, so-called "win/win" partnerships are envisaged. Research is needed to identify the building blocks of an innovative intervention. METHODS: A cross-sectional descriptive study was carried out with health institutions in the canton of Geneva to identify the proportion of institutions with a positive opinion on partnership with caregivers. It has also identified potential partnerships with caregivers of people facing dementia and possible compensation in exchange for the provision of their skills. Descriptive statistics are presented according to their frequencies and relative percentages (categorical variables), as well as by their mean, standard deviation and median (continuous variables). Logistic regression models were used to assess the factors associated with a favorable opinion towards win/win partnerships. RESULTS: The proportion of executives of health-related institutions with a positive opinion of partnership with caregivers is high: 74.7% (95% CI: 64.8-83.1%). Several types of potential partnerships have been identified between health institutions and caregivers. Areas in which certain activities have been identified as being able to be carried out by caregivers include governance, care, provision of services, accompaniment and support, training and research. Types of compensation for caregivers have also been highlighted. CONCLUSION: This study shows that some areas activities of health facilities in the canton of Geneva could be the subject of win-win partnerships with caregivers of people with dementia. Positive view of health executives on partnership with caregivers is encouraging. In the future, innovative projects can emerge to meet the needs of each party.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.175
GPT teacher head0.417
Teacher spread0.243 · 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 designObservational
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".

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Citations2
Published2019
Admission routes1
Has abstractyes

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