Impulsivity, Attachment, and Relational Psychopathology

A dimensional approach to conceptualising and responding to mental illnesses is increasingly encouraged to avoid diagnostic misclassifications of complex co-morbidities. Dimensional approaches aspire to ground diagnostic classifications in the emerging evidence from studies of the brain and neuroscience. Whatever the classification system, common presentations occur in a social nexus leading to relational disruption, and major impacts on family and friends, society, and on personal and social identities and roles.

Impulsivity is a pan-diagnostic symptom that is commonly expressed in bipolar disorder, attention deficit hyperactivity disorder (ADHD), and personality disorders that include difficulties with the regulation of mood, self-harm and suicidal ideation. Anxiety, post-traumatic syndromes, eating disorders, and psychoses can all present with impulsivity. Combinations of these illnesses then lead to marked impulsivity, diagnostic overlap, co-morbidity and more severe impairments.^1–4 For example, Meier's intriguing study (pp. 555–560) discovers that people with a combination of ADHD and anxiety have a substantially greater risk of bipolar disorder when compared with those with no prior ADHD or anxiety. Severe mood disorders raise the likelihood of perinatal episodes of illness for women who are planning a family, whether or not they have had a previous perinatal episode, but a previous perinatal episode signals stronger concerns about recurrence (see di Florio et al., pp. 542–547).

Attachment problems will arise if young people's impulsivity, in early childhood and youth, interfere with the stable and secure relational base with carers. Yet the development of impulsivity within the symptom profile of a range of mental illnesses can also disrupt or re-awaken attachment problems, which can then be re-enacted by health care professionals and care providing institutions. Adshead (pp. 511–513) alludes to the importance of attachment literacy amongst health professionals in order to avoid maladaptive responses to psychopathology, which can otherwise lead to greater isolation, poorer esteem, therapeutic pessimism, and even hostility and ‘malignant alienation’.⁵ More attachment-psychological literacy might encourage a thoughtful and compassionate response to patients that challenge professional expectations of the sick role. This is especially important at a time of limited social support and marked psychosocial adversity for patients owing to pressures on the economy and restrictions on welfare supports and health services.

Making diagnostic decisions with overlapping symptoms and syndromes is a relational and emotional art; can machines replace or even do better than human clinicians? Tiffin et al.'s (pp. 509–510) proposition is that machine learning tools may provide better diagnostic decisions than humans by using data harvested from clinical records and social media. Machine learning could also be applied to improve evidence-based medicine, for example, by re-analysing trial data from a position of equipoise to show which patterns or findings best fit the data, rather than whether a specific favoured hypothesis is negated or supported.

Calafato et al. (pp. 535–541) identify more limitations of diagnoses. People with psychoses have dramatic increases in polygenic risk scores for psychosis. However, the accuracy of predictive diagnostic models is modest when polygenic risk scores are applied to identify schizophrenia and bipolar illnesses.

Distinguishing sub-types of bipolar illness raises further questions about diagnostic precision and the value of categories. White matter tracts from the prefrontal cortex to sub-cortical structures are implicated in people diagnosed as having bipolar 1 but not for people diagnosed as having bipolar 2 disorder or healthy controls; these findings suggest unique pathophysiologies for bipolar 1 and 2, yet the white matter tract integrity does not relate to polygenic risk scores (see Foley et al., pp. 548–554). A systematic review in search of biomarkers for bipolar disorders identifies over 50 relevant studies and 14 potential biomarkers. Disappointingly, none of these differentiated mood phase in bipolar disorder, although some inflammatory markers showed promise (see Rowland et al., pp. 514–525).

People with ADHD struggle with impulsivity and poor attention, and they can have histories of conduct problems early in life.⁶ These symptoms can affect attachment, but attachment problems also predict ADHD symptoms in later childhood.⁷ ADHD is a persistent condition in which impairments are influenced by intelligence in adulthood.⁸ Persistent and late onset ADHD leads to poorer psychological and psychosocial outcomes, including substance misuse (see Agnew-Blais et al., pp. 526–534); furthermore, childhood onset ADHD has adverse consequences for physical health and socio-economic outcomes. Might early attachment patterns impact on the risks of ADHD and related lifestyle and health risk behaviours leading to lower levels of sustained employment, anxiety and disruption in affect regulation, and greater risks of significant physical illnesses? Care providers should embrace a better understanding of attachment and how to contain impulsivity in related complex diagnoses.