Understanding smoking after acute illness: An application of the sentinel event method

The sentinel event theory provides a stepwise approach for building models to understand how negative events can spark health behaviour change. This study tested a preliminary model using the sentinel events method in a sample (N = 300) of smokers who sought care for acute cardiac symptoms. Patients completed measures on: smoking-related causal attribution, perceived severity of the acute illness event, illness-related fear and intentions to quit smoking. Patients were followed up one week after the health event and a seven-day timeline follow back was completed to determine abstinence from tobacco. Structural equation models were performed using average predictor scale scores at baseline, as well as three different time anchors for ratings of illness severity and illness-related fear. Quit intentions, actual illness severity and age were the consistent, positive and independent predictors of seven-day point prevalence abstinence. Additional research on the influences of perceptions and emotional reactions is warranted.