Factors Associated with the Successful Recognition of Abnormal Breathing and Cardiac Arrest by Ambulance Communications Officers: A Qualitative Iterative Survey
Bibliographic record
Abstract
OBJECTIVES: We sought to identify barriers and facilitators to ambulance communications officers' (ACOs') recognition of abnormal breathing and administration of cardiopulmonary resuscitation (CPR) instructions. METHODS: We conducted semistructured qualitative interviews based on the constructs of the Theory of Planned Behavior to elicit salient attitudes, social influences, and behavioral controls potentially influencing ACOs' intent to recognize abnormal breathing as a symptom of cardiac arrest and administer CPR instructions over the phone. We conducted interviews until achieving data saturation. We recorded interviews and transcribed them verbatim. Two independent reviewers performed inductive analyses to identify emerging themes. RESULTS: We interviewed 24 ACOs from four Canadian provinces (67% female, median 9.5 years of experience, 33% with paramedic training). We identified eight behavioral, 14 subjective normative, and 22 control beliefs. Important attitudes were as follows: 1) CPR instructions may help the patient and are likely to be beneficial for the caller; 2) abnormal breathing is an early sign of cardiac arrest; and 3) dispatch-assisted CPR instructions can improve survival. The leading social influence was management/quality assurance staff. Behavioral control was the construct most associated with ACOs' ability to recognize abnormal breathing, including 1) adherence to mandatory scripted protocol, 2) poor caller description of breathing pattern, and 3) ACO training on abnormal breathing. CONCLUSIONS: This qualitative study found that control beliefs are most influential on ACOs' intention to recognize abnormal breathing and provide CPR instructions over the phone. Training and policy changes should target these beliefs to increase the frequency of ACO-administered CPR instructions to callers reporting a patient in cardiac arrest.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".