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Record W3159189009 · doi:10.1186/s12911-021-01494-x

Ready for SDM: evaluating a train-the-trainer program to facilitate implementation of SDM training in Norway

2021· article· en· W3159189009 on OpenAlexaff
Simone Kienlin, Marie-Ève Poitras, Dawn Stacey, Kari Nytrøen, Jürgen Kasper

Bibliographic record

VenueBMC Medical Informatics and Decision Making · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsOttawa HospitalUniversity of OttawaUniversité de Sherbrooke
FundersHelse Sør-Øst RHFHelse Nord RHF
KeywordsOperationalizationHealth careTrainerMedical educationCompetence (human resources)CurriculumObservational studyDescriptive statisticsMedicineHealth informaticsNursingPsychologyComputer sciencePublic health

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare providers need training to implement shared decision making (SDM). In Norway, we developed "Ready for SDM", a comprehensive SDM curriculum tailored to various healthcare providers, settings, and competence levels, including a course targeting interprofessional healthcare teams. The overall aim was to evaluate a train-the-trainer (TTT) program for healthcare providers wanting to offer this course within their hospital trust. METHODS: Our observational descriptive design was informed by Kirkpatrick´s Model of Educational Outcomes. The South-Eastern Regional Health Authority invited healthcare providers from all health trusts in its jurisdiction to attend. The TTT consisted of a one-day basic course with lectures on SDM, exercises and group reflections followed by a two-day advanced course including an SDM observer training. Immediately after each of the two courses, reaction and learning (Kirkpatrick levels 1 and 2) were assessed using a self-administered questionnaire. After the advanced course, observer skills were operationalized as accuracy of the participants' assessment of a consultation compared to an expert assessment. Within three months post-training, we measured number of trainings conducted and number of healthcare providers trained (Kirkpatrick level 3) using an online survey. Qualitative and quantitative descriptive analysis were performed. RESULTS: Twenty-one out of 24 (basic) and 19 out of 22 (advanced) healthcare providers in 9 health trusts consented to participate. The basic course was evaluated as highly acceptable, the advanced course as complex and challenging. Participants identified a need for more training in pedagogical skills and support for planning implementation of SDM-training. Participants achieved high knowledge scores and were positive about being an SDM trainer. Observer skills regarding patient involvement in decision-making were excellent (mean of weighted t = .80). After three months, 67% of TTT participants had conducted more than two trainings each and trained a total of 458 healthcare providers. CONCLUSION: Findings suggest that the TTT is a feasible approach for supporting large-scale training in SDM. Our study informed us about how to improve the advanced course. Further research shall investigate the efficacy of the training in the context of a comprehensive multifaceted strategy for implementing SDM in clinical practice. TRIAL REGISTRATION: Retrospectively registered at ISRCTN (99432465) March 25, 2020.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.593
GPT teacher head0.582
Teacher spread0.011 · 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 designOther design
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

Citations44
Published2021
Admission routes1
Has abstractyes

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