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Record W2163522071 · doi:10.1177/1074840709339781

Supporting Relationships Between Family and Staff in Continuing Care Settings

2009· article· en· W2163522071 on OpenAlexaffabout
Wendy Austin, Erika Goble, Vicki R. Strang, Agnes Mitchell, Elizabeth Thompson, Linda Balt, Gillian Lemermeyer, Kelly Vass

Bibliographic record

VenueJournal of Family Nursing · 2009
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsAlberta Health ServicesMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsNursingPsychologyContinuing careMedical educationMedicineFamily medicine

Abstract

fetched live from OpenAlex

In this Canadian study, a participatory action research approach was used to examine the relationships between families of residents of traditional continuing care facilities and the health care team. The objectives were to (a) explore the formation and maintenance of family-staff relationships, with attention paid to the relational elements of engagement and mutual respect; (b) explore family and staff perspectives of environmental supports and constraints; and (c) identify practical ways to support and enhance these relationships. Results indicate that the resource-constrained context of continuing care has directly impacted family and staff relationships. The nature of these relationships are discussed using the themes of "Everybody Knows Your Name," "Loss and Laundry," "It's the Little Things That Count," and "The Chasm of Us Versus Them." Families' and staff's ideas of behaviors that support or undermine relationships are identified, as are concrete suggestions for improving family- staff relationships in traditional continuing care settings in Canada.

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)0.009
metaresearch head score (Gemma)0.020
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 score0.325
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.007
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.424
Teacher spread0.325 · 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

Citations42
Published2009
Admission routes2
Has abstractyes

Explore more

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