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Record W2103917061 · doi:10.14574/ojrnhc.v7i2.134

Fitting a Round Peg into a Square Hole: Exploring Issues, Challenges, and Strategies for Solutions in Rural Home Care Settings

2007· article· en· W2103917061 on OpenAlexaffabout
Beverly Leipert, Marita Kloseck, Carol L. McWilliam, Dorothy Forbes, Anita Kothari, Abe Oudshoorn

Bibliographic record

VenueOnline Journal of Rural Nursing and Health Care · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsWestern University
Fundersnot available
KeywordsMultidisciplinary approachNursingRural areaBest practiceMedicineFocus groupBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

While home care has received much attention lately, little research to date has drawn on the experiences of rural multidisciplinary teams providing in-home care. Home care is typically studied in urban areas, with the tendency to expand urban practices to rural settings, often with problematic results. This paper presents findings regarding unique rural multidisciplinary home care issues, challenges, and strategies for solutions. Five focus group interviews were held with each of three rural multidisciplinary home care provider groups (n=19) in southwest Ontario, Canada. Findings revealed practice issues related to time, distance, communication, recruitment and retention, as well as system issues regarding poor understanding and scheduling of rural practice by administrators and urban employers. Study findings indicate that rural home care requires enhanced understanding and changes to policies and practices to provide efficient and effective care to rural residents. Best practice guidelines for home care in rural areas are urgently needed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.098
GPT teacher head0.439
Teacher spread0.342 · 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.

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

Citations11
Published2007
Admission routes2
Has abstractyes

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