Background and objective
Reducing patient decision delay – the time elapsed between symptom onset and the moment the patient decides to seek medical attention – can help improve acute coronary syndrome survival. Patient decision delay is typically investigated in retrospective studies of acute coronary syndrome survivors that are prone to several biases. To offer an alternative approach, the goal of this research was to investigate anticipated patient decision delay in the general population in response to different symptom clusters.
Methods
We developed scenarios representing four commonly experienced symptom clusters: classic (chest symptoms only), heavy (a large number of very intense symptoms including chest pain), diffuse (mild symptoms including chest pain), and weary (mild symptoms without clear chest involvement). The scenarios were administered in random order in a representative survey of 1002 adults ≥55 years old from the non-institutionalized general population in Spain. We measured help-seeking intentions, anticipated patient decision delay (waiting >30 min to seek help), and symptom attribution.
Results
Patient decision delay was most common in the diffuse scenario (55%), followed by the weary (34%), classic (22%), and heavy (11%) scenarios. Attributing the symptoms to a cardiovascular cause and intentions to call emergency services were least frequent in the weary and diffuse scenarios. Women were less likely to intend to seek help than men in the classic (OR = 0.48, [0.27, 0.85], diffuse (OR = 0.67, [0.48, 0.92]), and weary (OR = 0.66, [0.44, 0.98]) scenarios, despite being more likely to attribute symptoms to cardiovascular causes. Participants with traditional cardiovascular risk factors (e.g., diabetes, hypercholesterolemia, hypertension) reported faster help-seeking, whereas participants with obesity and history of depression were more likely to delay.
Discussion
The diverse manifestations of acute coronary syndrome generate fundamentally different appraisals. Anticipated patient decision delay varies as a function of socio-demographic characteristics and medical history, supporting findings from studies with patients who experienced ACS. Measuring anticipated patient decision delay in the general population can help reveal potential barriers to help-seeking and capture effects of population interventions.