Objective: Traditionally illness perception data have been analysed individually. However, it is more realistic to consider illness perceptions as forming an individual’s schemata of perceptions about an illness. The purpose of this paper was to demonstrate how latent class analysis (LCA) can identify groups of cardiac patients who share similar illness schemata. A secondary aim was to examine the relationships between these schemata and psychosocial outcomes, namely quality of life and depression.
Methods: A total of 154 patients admitted to one of two Melbourne hospitals with acute myocardial infarction, unstable angina or heart failure completed a battery of psychosocial tests within four weeks of their admission. The instruments included the Brief Illness Perceptions Questionnaire (BIPQ), Beck Depression Inventory II (BDI II) and The MacNew Health-related Quality of Life (HRQOL) instrument. BIPQ data were subjected to LCA using Mplus and the resulting groups were compared according to their BDI II and MacNew scores.
Results: LCA identified four groups of patients: ‘Well Involved’ (8%) - healthy illness perceptions, strong control of the illness, low depression and high HRQOL; ‘Well Uninvolved’ (20%) - healthy perceptions, low depression and high HRQOL but low control; ‘Unwell Involved’ (21%) - poor illness perceptions, high personal control, very high depression and low HRQOL; ‘Unwell Uninvolved’ (51%) - poor illness perceptions, poor treatment control, moderate depression and HRQOL.
Conclusions: Identifying illness perception schemata has implications for targeting specific cognitive interventions to reduce depression and improve HRQOL after a cardiac event.