MétaCan
Menu
Back to cohort
Record W4312408100 · doi:10.2196/40699

The Integration of Live Video Tools to Help Bystanders During an Emergency Call: Protocol for a Mixed Methods Simulation Study

2022· article· en· W4312408100 on OpenAlexvenueno aff
Ophélie Morand, Robert Larribau, Stéphane Safin, Romain Pages, Hortense Soichet, Caroline Rizza

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsDebriefingCardiopulmonary resuscitationFirst responderMedical emergencyBasic life supportProtocol (science)Life supportMedicineProcess (computing)Computer scienceMultimediaMedical educationResuscitationEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Early action by bystanders is particularly important for the survival of individuals in need of emergency care, especially those experiencing a cardiac arrest or an airway obstruction. However, only a few bystanders are willing to perform cardiopulmonary resuscitation. The use of a live video during emergency calls appears to have a positive effect on the number of cardiopulmonary resuscitations performed by bystanders. OBJECTIVE: The objective of this study is to propose and evaluate the relevance of a living lab methodology involving video calls in simulated life-threatening emergency situations. METHODS: The first study aimed at analyzing the process of dealing with out-of-hospital cardiac arrest at a dispatch center and identifying the needs of the dispatchers. The second study is a pretest of a living lab. The third study focuses on a living lab in which 16 situations of cardiac arrest and airway obstruction are simulated. The simulation includes both a live video and transmission of a video demonstration of emergency procedures. The measures focus on 3 areas: the impact of video tools, development of collaboration within the community, and evaluation of the method. RESULTS: The results of the first study show that dispatchers have an interest in visualizing the scene with live video and in broadcasting a live demonstration video when possible. The initial results also show that collaboration within the community is enhanced by the shared simulation and debriefing experiences, clarifying regulation procedures, and improving communication. Finally, an iterative development based on the lessons learned, expectations, and constraints of each previous study promotes the existence of a living lab that aims to determine the place of live video tools in the sequence of care performed by dispatchers. CONCLUSIONS: Living labs offer the opportunity to grasp previously undetected insights and refine the use of the applications while potentially developing a sense of community among the stakeholders. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40699.

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)0.051
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.051
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.048
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0040.003
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0040.003
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0420.008

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 head0.419
GPT teacher head0.585
Teacher spread0.166 · 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 designSimulation or modeling
Domainnot available
GenreProtocol

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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicInnovative Approaches in Technology and Social DevelopmentFrench-language works237,207