To call or not to call: behavioral determinants influencing the decision of intensivists to consult poison centers for calcium channel blocker poisoning
Bibliographic record
Abstract
Purpose: This study aimed to define the behavioral determinants influencing the decision of intensivists to consult a poison center (PC) when managing patients with calcium channel blocker (CCB) poisoning. Material and methods: Semi-structured interviews were conducted involving a convenience sample of 18 intensivists. Two independent reviewers analyzed the interview responses using the Theoretical Domains Framework. Based on the impact and frequency of the reported behaviors, we selected the most relevant domains likely to influence intensivists’ decision to consult a PC for CCB poisoning. Results: Beliefs influencing physicians positively to consult a PC for CCB poisoning were identified in the following domains: knowledge (e.g., lower level of evidence), social or professional role and identity (e.g., high credibility attributed to the PC), reinforcement (e.g., multiple drug poisoning, infrequent or potentially lethal poisoning, medicolegal considerations), and behavioral regulation (e.g., facilitated access of PC to patient’s hospital chart, direct communication with a toxicologist). Beliefs deterring physicians from consulting a PC for CCB poisoning were identified in the following domains: knowledge (e.g., better awareness of recommendations decreases tendency to call), goals (e.g., priority for patient stabilization), and memory, attention, and decision process (e.g., cognitive overload due to an unstable patient). Conclusion: This qualitative study identified potential behavioral targets that future implementation strategies should address to improve collaboration between PCs and intensivists. In light of our results, the Québec PC now asks clinicians if the poisoned patient is unstable prior to collecting any other information. When necessary, a teleconference with the toxicologist is proposed earlier than before.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".