Adult attachment style. II: Its relationship to psychosocial depressive-vulnerability

Abstract

Background A range of studies show adult attachment style is associated with depressive-vulnerability factors such as low self-esteem, poor support and childhood adversity. However, there is wide inconsistency shown in the type of insecure style most highly associated. Few studies have examined attachment style in relation to clinical depression together with a range of such factors in epidemiological series. The present study uses an interview measure of adult attachment which differentiates type of attachment style and degree of insecurity of attachment, to see: (a) if it adds to other vulnerability in predicting depression and (b) if there is specificity of style to type of vulnerability. Method Two hundred and twenty-two high-risk and 80 comparison women were selected from questionnaire screenings of London GP patient lists and intensively interviewed. The Attachment Style Interview (ASI) differentiated five styles (Enmeshed, Fearful, Angry-dismissive, Withdrawn and Standard) as well as the degree to which attitudes and behaviour within such styles were dysfunctional (‘non-standard’). Attachment style was examined in relation to low self-esteem, support and childhood experience of neglect or abuse, and all of these examined in relation to clinical depression in a 12-month period. Results The presence of any ‘non-standard’ style was significantly related to poor support, low self-esteem and childhood adversity. Some specificity of type of style and type of vulnerability was observed. Logistic regression showed that non-standard Enmeshed, Fearful and Angry-dismissive styles, poor support and childhood neglect/abuse provided the best model for clinical depression. Conclusion Non-standard attachment in the form of markedly Enmeshed, Fearful or Angry-dismissive styles was shown to be associated with other depressive-vulnerability factors involving close relationships, self-esteem and childhood adversity and added to these in modelling depression.