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Record W2122544319 · doi:10.5430/jnep.v2n2p24

Evaluating the utility of the FamCHAT ethnocultural nursing assessment tool at a Canadian tertiary care hospital: A pilot study with recommendations for hospital management

2012· article· en· W2122544319 on OpenAlexafffundvenueabout
Gina Higginbottom

Bibliographic record

VenueJournal of Nursing Education and Practice · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Alberta
FundersFaculty of Nursing, University of AlbertaCanadian Institutes of Health ResearchUniversity of Alberta
KeywordsNursingFocus groupRelocationHealth careDescriptive statisticsQualitative propertyMedicinePsychologyFamily medicineSociology

Abstract

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Objectives: The multicultural nature of Canadian society and the decline in health of immigrants after relocation toCanada prioritizes a commitment to ensure equity in health care access and outcomes. An important feature shaping healthcare access and outcomes is the reception of culturally safe and competent care. Partnering with senior management at atertiary care hospital, this pilot study aimed to investigate whether an identified cultural assessment tool, the FamilyCultural Heritage Assessment Tool (FamCHAT), validated for use in a rural primary care setting, was suitable for use intertiary care. The objectives were to investigate: 1) whether using the FamCHAT enabled the nurses to elicit assessmentinformation from their patients who represent diverse ethnocultural groups, and 2) the nurses’ perspectives on the practicaluse of this form in their clinical practice. Methods: Nurses purposively selected from the Women’s, Surgery and Medicine units were asked to complete theFamCHAT form with all patients admitted during a three-month period in 2009. Focus group interviews were then held tolearn the nurses’ perspectives related to the form’s constructs and its use in their practice. The data from the completedFamCHAT forms were tabulated and analyzed using descriptive statistics to determine the extent of completion andaccuracy, and the sample characteristics. The interview data was analyzed using qualitative analytical software (ATLAS.tiScientific Software Development, GmbH, Germany) and Roper and Shapira’s framework for analysis of ethnographicdata. Results: The nurses filled out forty-four FamCHAT forms with patients having a diverse ethnocultural profile. In manyforms, several questions were either left blank or answered incorrectly with regard to the guidance notes containingcategorical answers for the variables of family size and language. Nine nurses participated in two focus groups (n = 4 andn = 5) and one in an individual interview. Five themes emerged from the qualitative data analysis: feasibility of using theFamCHAT in acute care practice; ethnocultural awareness needs of the participating nurses; perspectives of nurses aboutpatient concerns; potential for enhancement to nursing care assessments; and suggestions for enhancing and facilitating anew tool or approach. Nurses participating in the interviews thought that the constructs within FamCHAT could be useful for enhancing nursing assessments in their practice, but thought the tool was too long, was repetitive to some of theircurrent assessment data, and had questions many patients were uncomfortable answering. One option suggested in bothfocus groups was to embed the most useful constructs into existing assessment frameworks. Some of the variables werethought to be of limited relevancy for some nursing specialties. Conclusions: The findings provided valuable information for the hospital management in their efforts to revise nursingassessment tools. Consideration is being given to integrating some of the constructs into their existing nursing assessment,with recognition that each unit might benefit from different approaches. Other, systematic, approaches to enhancingcultural competency also need to be considered. This study highlights the importance of validating practice tools for use insettings that differ from those used for their original development.

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)0.001
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 score0.266
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.184
GPT teacher head0.528
Teacher spread0.344 · 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

Citations2
Published2012
Admission routes4
Has abstractyes

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