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Record W6891823179 · doi:10.48336/55hy-tc63

Exploring the person-centred care practice patterns of mental health nurses: a concurrent mixed methods study

2024· article· en· W6891823179 on OpenAlexaffabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2024
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMental healthOperationalizationQualitative researchParticipant observationMental health careQualitative propertyHealth careData collection

Abstract

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Aim: To understand the person-centred care practice patterns of mental health nurses in one Atlantic Canadian province. Background: There is emphasis on person-centred care within mental health services, yet, person-centred care is often poorly understood and operationalized by health care professionals. Mental health nurses’ person-centred practices remain unclear, as there is limited research on their practices. Design: The Person-centred Practice Framework (McCormack & McCance, 2016), comprising of 17 constructs spanning three domains essential for implementing person-centred care, was the theoretical framework for this concurrent mixed methods study. The quantitative portion of the study was a descriptive cross-sectional design and both interviews and participant observation comprised the qualitative portion. Interpretive description, a nursing methodology, guided the qualitative components of the study. In the integration phase, the analytic technique of merging established the alignment among complementary data within the three sets of study findings. Methods: Seventy Registered Nurses across one Atlantic Canadian province completed the survey package consisting of: 1) the person-centred practice inventory (Slater et al., 2017), 2) the person-centred climate questionnaire (Edvardsson et al. 2010), and 3) 13 demographic and work-related questions. Interviews occurred with eight individuals who had received recent inpatient mental health care in the province. Thirty-six hours of participant observation were conducted on three adult inpatient mental health units. The Pillar Integration Process, a four-stage procedure designed to integrate qualitative and quantitative data using joint display tables, guided the integration. Results: Three patterns were developed from the integrated data that described how nurses conduct and navigate their practice within the care environment: 1) mental health nurses maintain a separation from patients and often deliver nursing care from a distance, 2) mental health nurses practice in an organizational culture that supports the status quo, which is not person-centred care, and 3) when mental health nurses and individuals co-engage in person-centred moments, the results are inspiring and foster hope. The results of each component of the study are presented throughout the dissertation. Conclusion: Nurses face organizational and personal barriers in their delivery of person-centred care. Although person-centred moments were infrequent, they are valued by those who receive care. Advancing beyond discrete moments of person-centred care requires a sustained commitment from both health care professionals and the organization within which they work. Organizations should evaluate current practices and structures to ensure nurses are optimally positioned to provide person-centred care.

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)0.018
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.390
Teacher spread0.266 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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