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Record W2900907339 · doi:10.1111/jpm.12504

The experience of hospital staff in applying the Gentle Persuasive Approaches to dementia care

2018· article· en· W2900907339 on OpenAlexafffundabout
Lillian Hung, Cathy Son, Rebecca Hung

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsTrinity Western UniversityWestern UniversityUniversity of British ColumbiaVancouver Coastal Health Research InstituteSimon Fraser University
FundersCanadian Institutes of Health ResearchVancouver Coastal Health Research Institute
KeywordsDementiaWorkforceNursingPsychologyHealth careWork (physics)Workforce developmentMedicineMedical educationPolitical scienceEngineering

Abstract

fetched live from OpenAlex

WHAT IS KNOWN ON THE SUBJECT?: Although the seminal work of McCormack et al. (International Practice Development Journal, 2015, 5, 1) and Nolan, Davies, Brown, Keady, and Nolan () provides useful conceptual frameworks in person-centred care, research is needed to understand how theoretical concepts can be applied into practice to support dementia care. Also, evidence is needed to demonstrate the impacts of implementing person-centred care and staff experiences. WHAT DOES THIS PAPER ADD TO EXISTING KNOWLEDGE?: This paper adds to the emerging work that is providing a greater understanding of how team education in practice can make a difference in building capacity to improve dementia care. We offer timely evidence and useful insights into how an education programme, Gentle Persuasive Approaches (GPA), was implemented ("what worked" and "how") in a large Canadian hospital to improve knowledge and skills among staff in dementia care. The GPA education helped hospital staff enact person-centred care by cultivating shared values and a learning environment to change attitudes, practices and conditions for continuous practice development. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Mental health nurses in advance practice are well positioned to lead dementia education and advocate for person-centred care in hospitals. Hospital leaders are responsible for providing resources to cultivate a supportive environment for continuous learning to ensure the workforce gains the capacity to meet the changing demands and needs of the ageing population. System support is essential for creating conditions to enable person-centred care. ABSTRACT: Introduction Hospital staff lacks knowledge and skills in dementia care. There is a need to understand how person-centred care theory can be operationalized in staff's practices to improve dementia care. Aims To describe the staff's experiences of learning and applying the Gentle Persuasive Approaches (GPA) to enact person-centred care in a hospital. Methods Mixed methods, including posteducation survey and focus groups, were used. Thematic analysis was conducted to identify themes that describe participants' experiences. Results Three hundred and ten staff and leaders in a hospital participated in the GPA education and completed a posteducation survey (n = 297). After 1 year, two follow-up focus groups were conducted with interdisciplinary staff (n = 24) across medicine and mental health programmes. Our analysis identified three themes to enable person-centred care: (a) changing attitudes, (b) changing practices and (c) changing conditions. Discussion This study contributes to the literature by providing evidence of how an education programme was implemented in a large Canadian hospital to build capacity for dementia care. Joint education for interprofessional staff offers value in enabling person-centred care. Implication Mental health nurses are in position to lead dementia education and advocate for person-centred care in hospitals. Staff need structural support to engage in team learning for practice improvement.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.047
GPT teacher head0.430
Teacher spread0.383 · 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 designQualitative
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

Citations28
Published2018
Admission routes3
Has abstractyes

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