Abstract
Bipolar disorder is a severe, chronic mental illness with currently limited treatment options, both cognitive behavioural therapy (CBT) and pharmacological treatment have modest effects. According to the literature the CBT for bipolar disorder needs to be updated and improved. The treatment for several other mental disorders CBT has been enhanced by using imagery techniques. Research has demonstrated that people suffering from bipolar disorder are more imagery prone and different mood states are associated with various aspects of imagery. Therefore, it is assumed that imagery interventions can enhance current CBT protocols in bipolar disorder. Before integrating imagery in current treatment protocols for bipolar disorder it is important to further explore how different aspects of imagery (tendency, quality, appraisal) relate to different aspects of the disorder (comorbidity, years since diagnosis, number of episodes and current mood state). The current study will investigate imagery in current mood and comorbidity state by using a cross-sectional design. The aim is to include 100 people with the diagnosis bipolar disorder, currently receiving treatment. Imagery aspects will be measured using a questionnaire that will take approximately 20 minutes to fill out. This data will account for the dependent variables. Whereas medical data relevant for bipolar disorder, such as length of diagnosis and comorbidity, will be retrieved from the electronic patient file and questionnaire which will account for the independent variables. This data will be examined using multiple regression analyses.
Keywords: Bipolar Disorder; Imagery; Quality; Appraisal;
1. Introduction
The DSM-5, developed by the American Psychiatric Association (2014), defines bipolar disorder as episodes of extreme moods such as mania or hypomania and depression. It specifies two main types of bipolar disorders. Bipolar I disorder refers to people experiencing manic episodes, where in the vast majority of patients also depressive or hypomanic episodes occur, this is however not a criteria for diagnosis. Whereas the occurrence of both hypomanic and depressive episodes is required for the diagnosis of bipolar II disorder. A relatively stable mood in bipolar disorder is defined as euthymia or a euthymic mood state (APA, 2014). Furthermore, the full bipolar spectrum also includes; cyclothymic disorder defined as mood states that are not qualified for the diagnosis of (hypo)mania or depression; and bipolar disorder ‘not otherwise specified’ including a wide range of mood dysregulation manifestations (Leahy, 2007). The latter has been excluded in the DSM 5 and replaced by Other Specified Bipolar and Related Disorder and Unspecified Bipolar and Related Disorder (APA, 2014). Bipolar disorder has a lifetime prevalence of 2.4% in the general Dutch population as stated in the Netherlands Mental Health Survey and Incidence Study (NEMESIS) (Regeer et al, 2004). As Leahy (2007) states, it has been widely acknowledged that bipolar disorder is a severe chronic mental illness, difficult to diagnose because of its complex nature and presented symptoms. All the more so, because bipolar patients often lack insight into their mania due to poor recall of their manic episodes. Therefore a thorough hetero-anamnesis is necessary to obtain an accurate history and to make a correct diagnosis (Leahy, 2007). In patients with bipolar disorder the lifetime rates of successfully executed suicide attempts is 60 times higher than for the general public (Baldessarini, Pompili, & Tondo, 2006). Moreover, people suffering from bipolar disorder have high medical comorbidity, such as hypertension, thyroid disease and coronary artery disease, with a percentage of 81 and it seldom present with only one mental health disorder with the most common comorbid problems being anxiety disorder, personality disorder and substance abuse (Fenn et al., 2005; Altindag, Yanik, &. Nebioglu, 2006; McIntyre & Keck, 2006).
According to Geddes and Miklowitz (2013) current treatment for bipolar disorder has mainly focussed on stabilizing the patient with the aim to bring the mania or depression the patient is experiencing to a balanced and stable mood. When the former is established, maintenance treatment concentrates on relapse prevention, decrease in subthreshold symptoms and improving social and occupational skills. These two phases of treatment for bipolar disorder, acute and maintenance, can be difficult to establish because the pharmaceutical treatment for depression to alleviate low mood can cause mania or hypomania, whereas the treatment for mania to depress euphoric mood may provoke a depressive episode (Geddes & Miklowitz, 2013). Moreover, up to 60% of the bipolar patients show non-compliance to drug management, such as lithium, after an acute depressive or manic episode and 40% to 60% of those who are compliant experience re-occurring episodes in 1 to 2 years (Geddes & Miklowitz, 2013; Micklowitz, 2008). Therefore more adjunctive psychosocial treatments, including cognitive behavioural therapy (CBT), are studied as being beneficial for bipolar disorder and psychosocial treatments parallel to medical management is recommended for best treatment results (Geddes & Miklowitz, 2013; Kupka et al, 2015).
Cognitive behavioural therapy (CBT) is a thoroughly researched treatment that has convincingly been demonstrated to be effective for a wide range of mental disorders (Keijsers, van Minnen, & Hoogduin, 2011). The depressive symptoms in bipolar disorder can be successfully treated similarly to unipolar depression as described by Beck (1976), however, the treatment of manic or hypomanic symptoms as been mainly focussed on preventing impulsive behaviour (Kupka & Knoppert- van der Klein, 2008). Stratford, Cooper, Di Simplicio, Blackwell and Holmes (2015) argue that major clinical trials on the effectiveness of CBT in bipolar disorder continue to be inconclusive. Evidence shows that the existing CBT protocols for relapse prevention offer little to no improvement (Stratford, Cooper, Di Simplicio, Blackwell & Holmes, 2015). Isasi, Echeburua, Liminana and Gonzalez-Pinto (2014) state that CBT is only specifically beneficial in the treatment and prevention of depressive symptoms. Combined pharmaceutical and psychological treatment (psycho-education, anxiety-control treatment etc.) has proved more useful in bipolar disorder than pharmaceutical treatment alone. However, it these psychological interventions should only be applied in depressive state as it might otherwise be ineffective (Isasi, Echeburua, Liminana & Gonzalez-Pinto, 2014). These studies demonstrate that there is no effective treatment for patients suffering from bipolar disorder where both mood states ((hypo)manic and depressive) are tackled. In conclusion, there is an overall consensus that the manual of CBT treatment in bipolar disorder needs to be updated to increase the effectiveness of the therapy (Stratford et al, 2015). The goal of the current study is to explore if imagery interventions can enhance CBT treatment for bipolar disorder and which factors might relate to different aspects of imagery.
Imagery has been introduced as one of the new frontiers of cognitive behavioural therapy (Hackmann, Bennett-Levy & Holmes, 2011). Kosslyn, Ganis and Thompson (2001) argue that, in contrast to perception, mental imagery takes place when perceptual information is obtained from memory which is referred to as ‘seeing with the mind’s eye’ or ‘hearing with the mind’s ear’. Mental imagery can also be generated by altering or combining previously stored perceptual information in novel forms (Kosslyn, Ganis & Thompson, 2001). Even though mental imagery has been widely assumed to have a strong effect on emotion, this has not been confirmed since recently (Holmes & Mathews, 2005). In their research Holmes and Mathews (2005) compared two groups of verbal or visual information on anxiety and established that instructions to visualize (imagine) aversive events prompted greater anxiety in participants than focussing on the verbal meaning of the instructions did. This differential effect of verbal and visual processing on emotion has been explored again in a new study which demonstrated clear evidence that imagery has a significantly stronger impact on emotion than verbal processing (Holmes, Mathews, Mackintosh & Dalgleish, 2008). Moreover, in several mental disorders imagery has been demonstrated to stimulate emotions such as anxiety. Holmes and Mathews (2010) suggested that mental imagery in the form of flashbacks to a traumatic event can provoke powerful emotions as presented in post-traumatic stress disorder (PTSD). However, PTSD one of many mental disorders characterized by intrusive and destressing mental images (or efforts to escape them) (Holmes & Mathews, 2010). People suffering from social phobia reported to experience observer-perspective images where they see themselves in social situations, anxious, with a face as red as a tomato (Hackmann Clark & McManus, 2000; Stopa & Bryant, 2004). Agoraphobic patients describe distressing imagery as seeing themselves standing frozen in an intimidating crowd (Day et al., 2004; Hackmann, Day & Holmes, 2009; Wells & Papageorgiou, 1999). Moreover, in body dysmorphic disorder and some other eating disorders distorted body features are the main theme of intrusive images (Osman, Cooper, Hackmann & Vale, 2004; Hinrichsen, Morrison, Waller & Schmidt, 2007; Mountford & Waller, 2006; Somerville, Cooper & Hackman, 2007). Depression is characterized by intrusive negative imagery associated with autobiographical memories (recollections form one’s own life) and imagery related to grief (Brewin et al., 2009; Moulds, Kandris, Williams & Lang (2008); Patel et al., 2007; Wheatley et al., 2007; Williams & Moulds, 2008; Boelen & Huntjens, 2008). Concluding, imagery can profoundly influence emotional states in various mental disorders and are therefore currently attracting interest as treatment target.
As stated above, it has been argued that imagery can affect emotion in various mental disorders. Therefore, Hackmann, Bennet-Levy and Holmes (2011) suggested that emotion can be changed by manipulating different qualitative aspects of imagery (vividness, perspective, clarity or compellingness) or the more verbal aspects of imagery related such as appraisals (encapsulated beliefs or metacognitions). Literature stresses the importance of appraisals in the preservation of mental health disorders. For example, in people suffering from social phobia appraisals triggered by imagery are believed to be precipitating and perpetuating factors of negative emotion (Wild & Clark, 2011). Appraisals of imagery in both OCD and PTSD can be divided in two features; encapsulated beliefs (for example ‘having this image reflects a truth about me, this means I am a bad person’) and metacognitions (for example ‘having this image means I’m going mad’) (Salkovskis, 2002; Salkovskis, Richards, & Forrester, 1995; Ehlers, Clark, Hackmann, McManus & Fennell, 2005). These two features of appraisals of imagery reflect the meaning given to the content of the image and the process of having the image which is fuelled by prior core self-beliefs. Identifying ‘hot’ and ‘cold’ appraisals within CBT is common. ‘Hot’ appraisals refer to beliefs that are automatically triggered and are accompanied by strong affect most likely to motivate (Hackman et al., 2011). Ehlers and associates (2005) discovered that combining exposure with hot appraisals of imagery using both verbal and imager strategies had a profoundly large treatment effect. Additionally, Arntz, Tiesema and Kindt (2007) found that exposure therapy would greatly improve by adding imagery re-scripting techniques with the aim to alter hot appraisals. These studies both suggest that modification of hot appraisals in form of encapsulated beliefs or metacognitions significantly increases the effect of treatment compared to exposure alone. As adding imagery techniques with the aim to alter aspects of imagery can profoundly increase the effect of treatment as usual, it would be reasonable to assume that imagery prone people would benefit most from treatment incorporating imagery techniques.
Holmes et al. (2011) claim that patients with bipolar disorder appear to be more imagery prone than healthy controls. They found that people suffering from bipolar disorder scored higher on imagery processing, lower on verbal processing and reported higher levels of intrusive imagery of future events compared to the control group (Holmes et al., 2011). Gregory, Brewin, Mansell and Donaldson (2010) demonstrated for the first time that different mood states (i.e. euthymia, depression and hypomania) in bipolar disorder are characterised by various forms of intrusive memories and images, possessing different qualities. Euthymic mood states (relatively stable mood) were defined by intrusive memories of the past, however, less distressing and interfere less in daily life activities than in depressive mood states. Depression was associated with intrusive memories of negative experiences. In contrast, hypomanic mood states were characterized by positive future-oriented events, with similar vividness and intensity to the images in depression. Thus, the mood states differed in past/future-oriented imagery, perceived enjoyableness and interference in daily life activities (Gregory, Brewin, Mansell & Donaldson, 2010). This study aims to further explore this relationship between different mood states and imagery aspects in patients with bipolar disorder.
However, the various mood states are only one aspect that characterizes the expression of bipolar disorder. Merikangas et al (2007) state that 90% of bipolar disorder patients have comorbid anxiety disorder in their lifetime including all anxiety diagnoses. This comorbidity rate is considerably higher than the prevalence of anxiety disorder comorbidity in patients with major depressive disorder (50%; Kessler et al., 2003) or non-affective psychosis (63%; Kessler et al., 2005). It is therefore suggested that anxiety might have implications for the comprehension of the etiology and expression of bipolar disorder (Holmes, Geddes, Colom & Goodwin, 2008). Besides comorbidity other aspects of bipolar disorder such as years since diagnosis and number of episodes might be of influence on the expression of bipolar disorder and imagery as well. However, this relationship has never been researched before.
The current study will address the former issues by exploring how different aspects of bipolar disorder such as comorbidity, years since diagnosis, number of manic/depressive episodes and current mood state (depressive/euthymic/(hypo)manic) affect various features of imagery such as 1) use of imagery, 2) quality of imagery and 3) appraisal of imagery. Subsequently, this research aims to add to the current knowledge of imagery in people suffering from bipolar disorder and employment of this knowledge in treatment protocols such as CBT and thereby improving psychosocial treatment for bipolar patients. To research how these aspects of bipolar disorder may affect features of imagery, an estimated number of 100 bipolar patients will be presented with a newly composed survey aimed at measuring the effect of imagery on emotion and behaviour and a survey used to measure the tendency of people to use visual mental imagery in daily life situations. Information regarding the different aspects of bipolar disorder (comorbidity, years since diagnosis, number of episodes and current mood state) will be addressed in the questionnaire or retrieved from patient records. Furthermore, the reliability of the questionnaire will be investigated to expand previous research.
First, it will be hypothesized that having a comorbid disorder, more years since diagnosis, having experienced more depressive or manic episodes relates to more use of spontaneous imagery and higher quality of imagery (vividness, perspective, autobiographical or flash-forward, compellingness) regardless of current mood state (depressive, euthymic, (hypo)manic). Second, current mood state and the former mentioned features of bipolar disorder will be hypothesized to be of influence on appraisal of imagery (encapsulated beliefs and metacognitions), where current depressive or (hypo)manic mood state, having a comorbid disorder, more years since diagnosis and having experienced more depressive or manic episodes relates to more appraisals of imagery opposed to current euthymic mood state.
2. Method
2.1. Participants
As the study is primarily descriptive with many variables no power calculation is possible, however based on previous studies researching the effect of imagery using interviews or experiments around 20 to 100 participants were included. Therefore, the present study aims to include 100 participants with de diagnosis of bipolar disorder. Inclusion criteria for the study are diagnosis of bipolar I or bipolar II disorder, cyclothymic disorder or bipolar disorder not specified. Exclusion criteria are suicidal ideation, current psychosis, current alcohol or drug misuse and failure to complete the research questionnaire. Participants from all ages and gender will be included in the study as well as participants with various educational levels, with the exception of people suffering from mental retardation.
2.2. Research Design
The design of the current study will be quantitative, cross-sectional, descriptive, within-subjects in its nature.
2.3. Material
2.3.1. Imagery Questionnaire (DIMS)
A new online imagery survey designed by v.d. Berg, Voncken and Keijsers (in press) aimed at measuring the effect of imagery on emotion and behaviour will be used as primary measure in the current study. It is based on the existing Imagery Interview and assessment of imagery for interventions in clinical practice and consist of five subscales including: 1) quality of the image, 2) appraisals of the image 3) perceived effect on emotion and 4) perceived effect on behaviour. The imagery questionnaire (DIMS) covers all the above mentioned subscales. The quality of imagery subscale contains 14 questions regarding vividness, perspective, clarity, compellingness, reality and if it is based on a memory or if it is a figment of one’s imagination. The appraisal subscale comprises of two subscales including 16 questions regarding encapsulated beliefs and metacognitions. The first explores if the participant thinks that the image shows positive or negative meaning about themselves, others, the word or the future. The second, metacognitions, examines the participants belief that the image predicts positive or negative future events or if perceiving the image would affect their self-worth or actions. Furthermore, if the image evokes emotions such as feeling sad, happy, anxious, angry or ashamed is analysed by the perceived effect on emotion subscale containing 7 questions. Last, the perceived effect on behaviour subscale with 3 questions investigates if the image stimulates planned behaviour or actual behaviour actions. These subscales add up to 42 questions which are scored on a 9-point likert scale ranging from 1 ‘not at all’ to 9 ‘all the time or extremely’ depending on the question. All four newly created subscales exploring quality of imagery, appraisal of imagery, self-perceived effect of imagery on emotion and self-perceived effect on behaviour appear to have reasonable internal consistencies. Moreover, the outcome results show to be consistent over time indicating good test-retest reliability (v.d. Berg, Voncken, & Keijsers, in press).
Research variables per item in the questionnaire:
– Quality of the imagery (vividness, 1st or 3rd person perspective, autobiographical/flash-forward, compellingess): 14 items.
– Appraisals of the imagery (metacognitions, encapsulated beliefs): 16 items.
– Effect on emotion: 7 items.
– Effect on behaviour: 3 items.
2.3.2. Spontaneous Use of Imagery Scale (SUIS)
The Spontaneous Use of Imagery Scale (SUIS) (Reisberg, Pearson and Kosslyn, 2003) is used to measure the tendency of people to use visual mental imagery in daily life situations. The questionnaire consists of 12 items with a 5-point likert scale ranging from 5 indicating ‘always appropriate’, 3 ‘about half of the time’, to 1 indicating ‘never appropriate’, rating the degree to which each item is appropriate for each participant. The items measure self-reported spontaneous use of imagery, including sample items as ‘If I am looking for new furniture in a store, I always visualize what the furniture would look like in particular places in my home’ and ‘When I first hear a friend’s voice, a visual image of him or her almost always springs to mind’ (Reisberg, Pearson & Kosslyn, 2003). Total scores range from 12 to 60 with higher scores indicating a higher tendency of using visual mental imagery in daily life situations (Andrade, May, Deeprose, Baugh, & Ganis, 2014). Nelis, Holmes, Griffith and Raes created a Dutch version of the SUIS and evaluated its psychometric properties where internal consistency and test-retest reliability were thought to be satisfactory. Internal consistency was assessed using Cronbach’s alpha in the three samples and was considered acceptable (Nelis, Holmes, Griffith & Raes, 2014). However, internal consistency calculated for the English version was high with a Cronbach’s alpha of 0,98 (Reisber, Pearson & Kosslyn, 2003).
2.3.3. The Altman Self-Rating Mania Scale (ASRM)
The ASRM (Altman, Hedekker and Peterson, 1997) is a self-report questionnaire based on the five major symptoms of mania as described in the DSM-IV. Participants choose one of the five statements given for one symptom depending on the degree to which the statement accurately describes their behavioural and emotional state over the last week. For example, 0 ‘I do not feel happier or more cheerful than usual’, 2 ‘I often feel happier or more cheerful than usual’ to 4 ‘I feel happier and more cheerful than usual all of the time’. In their study investigating the reliability and validity of the ASRM a score of greater than 5 resulted in 85,5% sensitivity and 87,3% specificity values (Altman, Hedekker, & Peterson, 1997). Therefore, recent evidence shows that a score of less than 4 (cut-off <4) has to be obtained to determine that a patient is in full remission from bipolar disorder (Berk et al, 2008).
2.3.4. The Patient Health Questionnaire (PHQ-9)
Kroenke, Spitzer and Williams (2001) examined the validity of the brief self-report measure of depression severity (PHQ-9). The questionnaire is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders and the 9 items are based on the criteria for depressive disorders as stated in the DSM-IV (APA, 2000). Every item is scored on a 4-point likert scale, representing the last two weeks, where 0 indicates ‘not at all’, 1 ‘several days’, 2 ‘more than half the days’ and 3 ‘nearly every day’. Severity is measured by the total score ranging from 0 to 27. Scores of less than 5, 5-9, 10-14, 15-19 and 20 or more on the PHQ-9 indicate the absence of depression, mild, moderate, moderately severe, and severe depression. Major depression can be diagnosed if 5 or more of the 9 symptoms have been present ‘more than half the days’ (score of 2) over the last two weeks including depressed mood or anhedonia. Their research concluded that the PHQ-9 is a reliable instrument for measuring severity of depression and its presence (Kroenke, Spitzer, & Williams, 2001).
2.4. Procedure
The aim of the study is to include 100 participants with the diagnosis of bipolar disorder. Every patient attending the outpatient clinic of Altrecht Bipolair and GGzE Centrum Bipolaire Stoornissen will be approached by their lead clinician and researcher of the department (dr. Regeer of Altrecht Bipolair or dr. Rops of GGzE Centrum Bipolaire Stoornissen). The patients will receive an information leaflet (see appendix I) explaining the purpose of the study, the advantages and disadvantages for the participant and procedure regarding the online imagery survey. Patients who consider taking part in the study are invited to email drs. Karin van den Berg. Subsequently, they will receive an email containing a link to the online questionnaire, however, before continuing with the questionnaire they will be asked questions regarding informed consent (see appendix II). Alternatively, patients considering participating which have been handed the information letter and informed consent can submit the consent form to their lead clinician at their following appointment, after which they will be send the link to the online questionnaire via email.
Patient diagnosis, years since receiving diagnosis, current medication, comorbid disorders, age, gender, number of depressive episodes, number of manic episodes (if applicable) and amount of hospitalizations due to their disorder will be retrieved from patient records. The head clinician of patients indicating to participate will retrieve this information by filling out a small questionnaire or the information will be retrieved by a research assistant.
2.5. Data Analysis Plan
As the primary analysis the three hypotheses will be researched by a multiple regression analysis. With independent variables being comorbidity, years since diagnosis, number of manic/depressive episodes and current mood state and current mood state. The dependent variable differs per multiple regression analysis being use of spontaneous imagery, quality of imagery and appraisal of imagery. Since the independent variables comorbidity and current mood state are categorical variables dummy variables will be made before conducting the multiple regression analysis to correct for categorical factors. Multiple regression analysis has several assumption that should be considered before conducting the analysis: 1. The dependent variable is measured on a continuous scale; 2. Two or more independent variables either continuous or categorical; 3. Independence of observations which will be researched using the Durbin-Watson test; 4. Linear relationship between the dependent variable and each independent variable plus the independent variables collectively which will be explored using scatterplots; 5. Homoscedasticity which will be evaluated using the Breusch-Pagan test; 6. Multicollinearity which occurs when two or more independent variables highly correlate with each other which will be researched using the variance inflation factor (VIF); 7. No significant outliers which will be explored using a scatterplot and 8. Normal distribution which will be assessed using the Shapiro-Wilk test (Multiple Regression Analysis using SPSS Statistics, n.d.). When the assumptions for the multiple regression analyses are not met the non-parametric Spearman correlation can be used for the analyses of the hypotheses. As a secondary analysis the reliability of the various questionnaires will be assessed using the Cronbach’s Alpha reliability analysis.
2.6. Ethical Consideration (Human Participants Protections)
Ethical approval for this study has been obtained from the Ethical Committee Catharina Hospital Eindhoven (Medical Research Ethics Committees United) as the committee declared this study not bound by WMO. Moreover, the Ethical Review Committee Psychology and Neuroscience (ERCPN) Maastricht University has approved the start of this external study. Participants are informed of the risks by participating in this study in the information leaflet and they are urged to read this information before consenting to participate. The information gathered during this study is bound by the Wet Bescherming Persoonsgegevens (Wbp) and the study insures that all personal and medical information is anonymized (Gebruik van medische gegevens, n.d.).