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Record W3208186086 · doi:10.1186/s41077-021-00191-z

Getting everyone to the table: exploring everyday and everynight work to consider ‘latent social threats’ through interprofessional tabletop simulation

2021· article· en· W3208186086 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Simulation · 2021
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity Health NetworkUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsTable (database)Work (physics)Health services researchSocial workPsychologyComputer scienceSociologyPublic healthMedicineNursingEngineeringPolitical science

Abstract

fetched live from OpenAlex

In this methodological intersection article, we describe how we developed a new variation of the established tabletop simulation modality, inspired by institutional ethnography (IE)-informed principles. We aimed to design and conduct pilot implementations of this innovative tabletop simulation modality, which focused uniquely on everyday and everynight work, along with the factors that govern that work. In so doing, we aimed to develop a modality and preliminary findings that researchers and educators can use to simulate healthcare practices across longer episodes of care (i.e., time scales of hours or an entire day) and to detect the 'latent social threats' that can emerge during interprofessional clinical care.An interprofessional team designed tabletop simulation scenarios of interprofessional challenges during transfers of care on a labour and delivery (L&D) unit. Within each scenario, participants provided real-time explanations for their work and associated drivers, both independently and as a team. Thus, we combined 'think-aloud' and simulation principles to design tabletop simulation scenarios to elicit healthcare professionals' descriptions of how they collaborate in their work on the L&D unit. We completed a total of five tabletop simulations with eight participants (obstetricians, N = 2; midwives, N = 2; nurses, N = 5).The conversations stimulated by the tabletop simulation scenarios and debriefs allowed us to generate a preliminary understanding of the texts that govern and organize clinicians' everyday work processes. We generated data about longitudinal, multi-hour work processes in a condensed timeline, with opportunities to pause and probe, and with reduced focus on individual practitioner's competence.We believe our innovative tabletop simulation approach allowed us to examine clinical work in ways no other simulation permits. Participants described how the scenarios opened a productive dialogue between professional groups and suggested this simulation-based approach might contribute to enhanced interprofessional understanding and cultural change. We suggest that others can adapt our low-resource approach to understand clinicians' everyday work and to map how this work is governed by documents, like policies, with the end goal of facilitating system change and managing latent social threats.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.432
Teacher spread0.322 · 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