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Record W38811618 · doi:10.1038/s41467-024-48962-2

The Culture Change Movement among Nursing Homes: Social Workers/Health Care Professionals Perspective

2014· article· en· W38811618 on OpenAlexfundno aff
Emily Nesbitt

Bibliographic record

VenueNature Communications · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsPerspective (graphical)NursingHealth professionalsCulture changeHealth careSocial workMovement (music)Nursing homesMedicinePsychologySociologyPolitical science

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the experience of social workers and other health care professionals that are working in facilities that are or have implemented the Culture Change Movement (CCM) and to determine its impact on older adults and those working with them. This qualitative research study examines social workers and other health care professionals’ perspectives on the implementation of the CCM in nursing home settings. Six licensed social workers and two registered nurses were interviewed for this study from various surrounding nursing homes that are or have implemented the CCM. A semi-structured interview was conducted with each participate to learn more about the CCM and its effects on the nursing home environment. The interviews were conducted in private spaces to ensure confidentiality for each participant. The interview was recorded, transcribed, read and coded to determine themes throughout the interview. Upon completion of the interview and transcription, a reliability check was completed with another academic colleague. The emerging themes from the interviews were as follows: transitioning from an institutionalized setting to a more home-like environment, giving residents more choices, and positive feedback from residents, families and staff. These findings support the literature. Future research in this area will only continue to provide direction to nursing facilities that are implementing the CCM and will help inform them of the impacts of the CCM.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.010
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.057
GPT teacher head0.476
Teacher spread0.419 · 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
Published2014
Admission routes1
Has abstractyes

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