MétaCan
Menu
Back to cohort
Record W2055781386 · doi:10.1016/j.pec.2014.03.005

Mandatory communication training of all employees with patient contact

2014· article· en· W2055781386 on OpenAlexaboutno aff
Jette Ammentorp, Lars Toke Graugaard, Marianne Engelbrecht Lau, Troels Præst Andersen, Karin Waidtløw, Poul‐Erik Kofoed

Bibliographic record

VenuePatient Education and Counseling · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
FundersSygehus Lillebælt
KeywordsTraining (meteorology)MEDLINEPsychologyNursingMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

UNLABELLED: In 2010 a communication program that included mandatory communication skills training for all employees with patient contact was developed and launched at a large regional hospital in Denmark. OBJECTIVE: We describe the communication program, the implementation process, and the initial assessment of the process to date. METHOD: The cornerstone of the program is a communication course based on the Calgary Cambridge Guide and on the experiences of several efficacy and effectiveness studies conducted at the same hospital. The specific elements of the program are described in steps and a preliminary assessment based on feedback from the departments will be presented. RESULTS: The elements of the communication program are as follows: (1) education of trainers; (2) courses for health professionals employed in clinical departments; (3) education of new staff; (4) courses for health professionals in service departments; and (5) maintenance of communication skills. Thus far, 70 of 86 staff have become certified trainers and 17 of 18 departments have been included in the program. CONCLUSION AND PRACTICE IMPLICATIONS: Even though the communication program is resource-intensive and competes with several other development projects in the clinical departments, the experiences of the staff and the managers are positive and the program continues as planned.

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)0.000
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.109
GPT teacher head0.378
Teacher spread0.268 · 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

Citations53
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePatient Education and CounselingSame topicPatient-Provider Communication in HealthcareFrench-language works237,207