title: Knowledge of symptom clusters among adults at risk for acute myocardial infarction.
abstract: BACKGROUND
  Individuals need to recognize acute myocardial infarction symptoms in order to seek treatment promptly. Previous acute myocardial infarction symptom studies asked subjects to identify single symptoms from a list. However, people think about illnesses or respond to symptoms by considering groups or clusters of symptoms.
  
  
  OBJECTIVE
  To use Q methodology to identify the cluster of symptoms that individuals at high risk for acute myocardial infarction and their significant others believe to be associated with acute myocardial infarction.
  
  
  METHODS
  A Q sort instrument that represented a range of symptoms was developed after analysis of 140 interviews with acute myocardial infarction survivors. Individuals with known coronary artery disease or their significant others (n = 63) sorted the resulting 49 statements describing acute myocardial infarction into "most expected" and "least expected" categories. By-person factor analysis was used.
  
  
  RESULTS
  Four factors were identified that described different presentations of acute myocardial infarction symptoms. Respondents loaded on the following factors: Factor 1 (traditional symptoms), Factor 2 (symptoms possibly related to gastrointestinal disorders), Factor 3 (nonspecific symptoms), and Factor 4 (a variation on traditional symptoms). This four-factor solution accounted for 36% of the total variance.
  
  
  CONCLUSIONS
  The Q methodology showed that people with known coronary artery disease and their significant others had varied expectations of acute myocardial infarction symptoms. New and various strategies need to be developed to help patients accurately identify acute myocardial infarction symptoms.
authors.affiliation: UIC College of Nursing, University of Illinois at Chicago, IL 60612, USA. cryan4@uic.edu
authors.forename: Catherine J
authors.initials: CJ
authors.lastname: Ryan
authors.forename: Julie Johnson
authors.initials: JJ
authors.lastname: Zerwic
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D001294:Attitude to Health; D002637:Chest Pain / Q000209:etiology; D016000:Cluster Analysis; D004417:Dyspnea / Q000209:etiology; D004521:Educational Measurement; D005163:Factor Analysis, Statistical; D005260:Female; D005767:Gastrointestinal Diseases / Q000209:etiology; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008297:Male; D008875:Middle Aged; D015146:Midwestern United States; D017202:Myocardial Ischemia / Q000175:diagnosis* / Q000209:etiology* / Q000503:physiopathology; D020380:Needs Assessment; D015404:Nursing Methodology Research; D011779:Q-Sort; D036301:Qualitative Research; D012307:Risk Factors; D013997:Time Factors