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Record W2516157642 · doi:10.1177/1049732316664712

Best Practice in Provider/Parent Interaction

2016· article· en· W2516157642 on OpenAlexafffund
Betty Davies, Rose Steele, Guenther Krueger, Susan Albersheim, Jennifer Baird, Michelle Bifirie, Susan Cadell, Gweneth Hartrick Doane, Deepshikha Garga, Harold Siden, Caron Strahlendorf, Yuan Zhao

Bibliographic record

VenueQualitative Health Research · 2016
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of British ColumbiaUniversity of WaterlooYork UniversityChildren's & Women's Health Centre of British ColumbiaUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsConceptualizationGrounded theoryQualitative researchBest practiceNursingPsychologyHealth professionalsHealth careMedicineMedical educationSociology

Abstract

fetched live from OpenAlex

In this 3-year prospective grounded theory study in three pediatric settings, we aimed to develop a conceptualization of best practice health care providers (BPHCPs) in interaction with parents of children with complex, chronic, life-threatening conditions. Analysis of semistructured interviews with 34 parents and 80 health care professionals (HCPs) and 88 observation periods of HCP/parent interactions indicated that BPHCPs shared a broad worldview; values of equity, family-centered care, and integrity; and a commitment to authentic engagement. BPHCPs engaged in direct care activities, in connecting behaviors, and in exquisitely attuning to particularities of the situation in the moment, resulting in positive outcomes for parents and HCPs. By focusing on what HCPs do well, findings showed that not only is it possible for HCPs to practice in this way, but those who do so are also recognized as being the best at what they do. We provide recommendations for practice and initial and ongoing professional education.

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)0.043
metaresearch head score (Gemma)0.055
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 score0.043
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.055
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0060.013
Scholarly communication0.0080.008
Open science0.0030.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.497
GPT teacher head0.654
Teacher spread0.156 · 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

Citations48
Published2016
Admission routes2
Has abstractyes

Explore more

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