Relationship patterns in alexithymia: a study using the core conflictual relationship theme method.

Abstract

BACKGROUND: Alexithymia is a disturbance in regulating affective states. Clinical observations suggest that alexithymic patients relate to others in a specific way. This paper explores whether specific relationship or transference patterns are typical of alexithymia. SAMPLING AND METHODS: Relationship patterns were assessed by means of the Core Conflictual Relationship Theme method, standard categories version. This method examines transference patterns and was applied to clinical interview data collected from a sample (n = 31) of mental health outpatients. Alexithymia was assessed by means of a score on the 20-item Toronto Alexithymia Scale corrected for the degree of depression (measured by the Beck Depression Inventory-II). Data were analysed by means of the leaps and bounds regression algorithm for selecting optimal subsets of indicators and by bootstrapping to determine 95% confidence intervals. RESULTS: First, we observed that alexithymia can be meaningfully explained by typical wishes, typical subjective perceptions of how others respond and one's own typical responses to others. This result indicates that the more marked a patient's alexithymic traits are, the more probable it is that specific transference themes come to the fore. Second, a set of three core indicators of trait alexithymia was mapped: little concern about being good to others, a strong perception of others as cooperative, and weak levels of reacting to others and to conflict by means of somatic symptoms. CONCLUSION: Alexithymia is related to a double interpersonal indifference: not much is expected from others, nor is there a personal urge to fulfill the expectations of others. Moreover, in alexithymia somatic symptoms proved to be non-reactive to interpersonal situations. Implications for diagnosis and treatment are highlighted. Limitations of our study are that alexithymia was only assessed with a self-report measure and that conclusions are based only upon data from a heterogeneous mental health sample.