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Record W4307348177 · doi:10.1186/s12877-022-03533-2

A family carer decision support intervention for people with advanced dementia residing in a nursing home: a study protocol for an international advance care planning intervention (mySupport study)

2022· article· en· W4307348177 on OpenAlexafffundabout
Andrew Harding, Julie Doherty, Laura Bavelaar, Catherine Walshe, Nancy Preston, Sharon Kaasalainen, Tamara Sussman, Jenny T. van der Steen, Nicola Cornally, Irene Hartigan, Martin Loučka, Karolína Vlčková, Paola Di Giulio, Silvia Gonella, Kevin Brazil, Wilco P. Achterberg, Mandy Visser, Catherine Buckley, Serena FitzGerald, Tony Foley, Siobhán Fox, Alan Connolly, Rónán Ó’Caoimh, Selena O’Connell, Catherine Sweeney, Suzanne Timmons, Christine Brown Wilson, Gillian Carter, Emily Cousins, Kay de Vries, Josie Dixon, Karen Harrison Dening, Catherine Henderson, Adrienne McCann

Bibliographic record

VenueBMC Geriatrics · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMcGill UniversityMcMaster University
FundersZonMwAlzheimer's SocietyCanadian Institutes of Health ResearchEU Joint Programme – Neurodegenerative Disease Research
KeywordsIntervention (counseling)NursingContext (archaeology)MedicineDementiaFamily caregivers

Abstract

fetched live from OpenAlex

BACKGROUND: Where it has been determined that a resident in a nursing home living with dementia loses decisional capacity, nursing home staff must deliver care that is in the person's best interests. Ideally, decisions should be made involving those close to the person, typically a family carer and health and social care providers. The aim of the Family Carer Decisional Support intervention is to inform family carers on end-of-life care options for a person living with advanced dementia and enable them to contribute to advance care planning. This implementation study proposes to; 1) adopt and apply the intervention internationally; and, 2) train nursing home staff to deliver the family carer decision support intervention. METHODS: This study will employ a multiple case study design to allow an understanding of the implementation process and to identify the factors which determine how well the intervention will work as intended. We will enrol nursing homes from each country (Canada n = 2 Republic of Ireland = 2, three regions in the UK n = 2 each, The Netherlands n = 2, Italy n = 2 and the Czech Republic n = 2) to reflect the range of characteristics in each national and local context. The RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework will guide the evaluation of implementation of the training and information resources. Our mixed methods study design has three phases to (1) establish knowledge about the context of implementation, (2) participant baseline information and measures and (3) follow up evaluation. DISCUSSION: The use of a multiple case study design will enable evaluation of the intervention in different national, regional, cultural, clinical, social and organisational contexts, and we anticipate collecting rich and in-depth data. While it is hoped that the intervention resources will impact on policy and practice in the nursing homes that are recruited to the study, the development of implementation guidelines will ensure impact on wider national policy and practice. It is our aim that the resources will be sustainable beyond the duration of the study and this will enable the resources to have a longstanding relevance for future advance care planning practice for staff, family carers and residents with advanced dementia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.060
GPT teacher head0.475
Teacher spread0.415 · 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 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".

Quick stats

Citations18
Published2022
Admission routes3
Has abstractyes

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