Separating emotions from consequences in muscle disease: comparing beneficial and unhelpful illness schemata to inform intervention development

J Psychosom Res. 2013 Apr;74(4):320-6. doi: 10.1016/j.jpsychores.2012.09.012. Epub 2012 Oct 9.

Abstract

Objective: Muscle diseases are currently untreatable and people with muscle disease experience reduced quality of life (QoL) and low mood. Patient's illness perceptions explain large proportions of the variance in QoL and mood, even after considering the impact of disease severity. Therefore a psychological intervention which helps patients modify their illness perceptions may improve QoL and mood even as the disease progresses. However, it is unknown which profile of illness perceptions (illness schema) an intervention should seek to promote. We aimed to fully describe and compare the illness schemata of clusters associated with better and worse outcomes.

Method: Following a cluster analysis of 217 people with muscle disease, a between-cluster comparison of QoL and mood identified the clusters associated with better and worse outcomes. Functional impairment was compared between-clusters to indicate if this could account for observed differences. Inter-correlations between the illness perceptions held within each cluster were examined across the clusters.

Results: Three stable clusters holding distinct illness schemata emerged. One cluster was characterised by greater functional impairment, worse QoL and mood than the other two clusters. The other two clusters did not differ in functional impairment but differed significantly in QoL and mood. The cluster associated with better outcomes was characterised by realistic views of timeline, greater coherence, reduced emotional representation and identity, and a lack of association between emotional representation and consequences.

Conclusion: Detailed comparison of beneficial and unhelpful illness schemata, taking into account disease-specific concerns, can help inform both the content and composition of an intervention.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Affect
  • Aged
  • Attitude to Health*
  • Cluster Analysis
  • Emotions*
  • Female
  • Humans
  • Illness Behavior*
  • Male
  • Middle Aged
  • Muscular Diseases / psychology*
  • Quality of Life / psychology*
  • Self Concept
  • Severity of Illness Index