Creative adapting in a fluid environment: an explanatory model of paramedic decision making in the pre-hospital setting
Bibliographic record
Abstract
BACKGROUND: Paramedics work in a highly complex and unpredictable environment which is characterized by ongoing decision-making. Decisions made by paramedics in the prehospital setting have implications for patient safety, transport, treatment, and health resource utilization. The objective of this study was; a) to understand how paramedics conduct decision-making in the field, and b) to develop a grounded theory of paramedic decision-making in the prehospital setting. METHOD: This study was conducted using classical grounded theory. Paramedics (n = 13) with five or more years' experience, who worked in a large urban center in Western Canada were interviewed. Field observations were conducted, each lasting 12 h, with five different ambulance crews. The data were analyzed and coded using the constant comparative method. RESULTS: The resultant theory, Creative Adapting in a Fluid Environment, indicates paramedic decision-making is a fluid iterative process. Unpredictable and dynamic features of the prehospital environment require paramedics to use a flexible and creative approach to decision-making. The model consists of the three categories constructing a malleable model, revising the model, and situation-specific action. Two additional components, safety and extrication, are considered at each stage of the call. These two components in conjunction with the three categories influence how decisions are made and enacted. CONCLUSION: Paramedic decision-making is highly contextual and requires accurate interpretation and flexible cognitive constructs that are rapidly adaptable. Evaluation of paramedic decision-making needs to account for the complex and dynamic interaction between the environment, patient characteristics, available resources, and provider experience and knowledge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".