Mental imagery is an under-explored field in clinical psychology research but presents a topic of potential interest and relevance across many clinical disorders, including social phobia, schizophrenia, depression, and post-traumatic stress disorder. There is currently a lack of a guiding framework from which clinicians may select the domains or associated measures most likely to be of appropriate use in mental imagery research. We adopt an interdisciplinary approach and present a review of studies across experimental psychology and clinical psychology in order to highlight the key domains and measures most likely to be of relevance. This includes a consideration of methods for experimentally assessing the generation, maintenance, inspection and transformation of mental images; as well as subjective measures of characteristics such as image vividness and clarity. We present a guiding framework in which we propose that cognitive, subjective and clinical aspects of imagery should be explored in future research. The guiding framework aims to assist researchers in the selection of measures for assessing those aspects of mental imagery that are of most relevance to clinical psychology. We propose that a greater understanding of the role of mental imagery in clinical disorders will help drive forward advances in both theory and treatment.

Bipolar disorder is a psychiatric condition characterized by episodes of elevated mood interspersed with episodes of depression. While treatment developments and understanding the disruptive nature of this illness have focused on these episodes, it is also evident that some patients may have chronic week-to-week mood instability. This is also a major morbidity. The longitudinal pattern of this mood instability is poorly understood as it has, until recently, been difficult to quantify. We propose that understanding this mood variability is critical for the development of cognitive neuroscience-based treatments. In this study, we develop a time-series approach to capture mood variability in two groups of patients with bipolar disorder who appear on the basis of clinical judgement to show relatively stable or unstable illness courses. Using weekly mood scores based on a self-rated scale (quick inventory of depressive symptomatology—self-rated; QIDS-SR) from 23 patients over a 220-week period, we show that the observed mood variability is nonlinear and that the stable and unstable patient groups are described by different nonlinear time-series processes. We emphasize the necessity in combining both appropriate measures of the underlying deterministic processes (the QIDS-SR score) and noise (uncharacterized temporal variation) in understanding dynamical patterns of mood variability associated with bipolar disorder.

A cognitive model of bipolar disorder suggests that mental imagery acts as an emotional amplifier of mood and may be heightened in bipolar disorder. First, we tested whether patients with bipolar disorder would score higher on mental imagery measures than a matched healthy control group. Second, we examined differences in imagery between patients divided into groups according to their level of mood stability. Mood ratings over approximately 6-months, made using a mobile phone messaging system, were used to divide patients into stable or unstable groups. Clinician decisions of mood stability were corroborated with statistical analysis. Results showed (I) compared to healthy controls, patients with bipolar disorder had significantly higher scores for general mental imagery use, more vivid imagery of future events, higher levels of intrusive prospective imagery, and more extreme imagery-based interpretation bias; (II) compared to patients with stable mood, patients with unstable mood had higher levels of intrusive prospective imagery, and this correlated highly with their current levels of anxiety and depression. The findings were consistent with predictions. Further investigation of imagery in bipolar disorder appears warranted as it may highlight processes that contribute to mood instability with relevance for cognitive behaviour therapy.