بیشتر از کلمات؟ ویژگی های شخصیتی Hypomanic، تصویرسازی بصری و اندیشه کلامی در بزرگسالان جوان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|29630||2015||6 صفحه PDF||سفارش دهید||4715 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Consciousness and Cognition, Volume 21, Issue 3, September 2012, Pages 1375–1381
The use of visual mental imagery has been proposed to be a risk factor for the development of bipolar disorder, due to its potential to amplify affective states. This study examined the relation between visual imagery (both trait usage and intrusive experiences of such imagery), intrusive verbal thought, and hypomania, as assessed by self-report questionnaires, in a sample of young adults (N = 219). Regression analyses found (after controlling for anxiety, depression, and positive and negative affect) that levels of intrusive visual imagery predicted levels of hypomania, but that neither trait use of visual imagery nor intrusive verbal thought did. These results were consistent with the proposal that being a ‘visualiser’, as opposed to a ‘verbaliser’, is a risk factor for bipolar disorder, with the caveat that it is specifically intrusive experiences of imagery, rather than the tendency to utilize imagery per se, that acts as a risk factor.
A fisher of mental contents, casting a net into the stream of consciousness of someone attending to the events of the inner world, as opposed to the encroachments of the external, will likely catch a variety of forms of visual, auditory, verbal and non-verbal experiences. One common form of experience is mental imagery, the experience of “seeing with the mind’s eye” and “hearing with the mind’s ear” which is argued to depend on perceptual information accessed from memory (Kosslyn, Ganis, & Thompson, 2001, p. 635). The “sensory qualities” (Hackmann, 1998, p. 301) of mental imagery are a key property used to differentiate it from a second common type of experience said to be “purely verbal or abstract” (Hackmann, 1998, p. 301), often referred to simply as “verbal thought” (Holmes, Geddes, Colm, & Goodwin, 2008, p. 1251). Whilst in dialogic models of verbal thought the simple dichotomy between mental imagery as a perceptual experience and verbal thought as non-perceptual breaks down, with inner speech being literally shot through with other people’s voices (Fernyhough, 2004; McCarthy-Jones & Fernyhough, 2011), the validity of a distinction between mental imagery and verbal thought is supported by studies showing that intrusive visual images and intrusive verbal thoughts are produced by two separate and distinct memory systems (Hagenaars, Brewin, van Minnen, Holmes, & Hoogduin, 2010). In contemporary studies, the distinction between mental imagery and verbal thought is typically operationalized by comparisons of mental imagery conditions, in which participants are given a series of vignettes and told to imagine each event as if it was happening to themselves, and verbal thought conditions, where participants are told to concentrate on the words and meaning as the vignette description unfolds (e.g., Holmes, Lang, & Shah, 2009). Operationalized in this manner, mental imagery and verbal thought have been found to have different emotional sequelae. This is thought to be due to visual imagery’s greater potential to amplify both mood and anxiety than verbal thought (Holmes & Mathews, 2010). For example, a number of studies have found greater levels of anxiety when an event is visually imagined, compared to when it is thought about verbally, such as when visualizing an image of one’s self collapsing from a heart attack as opposed to verbally thinking about such a situation (Holmes & Mathews, 2005). Similarly, compared to verbal thought about events, creating visual imagery about the same events has been found to lead to greater affective responses. For example, Holmes et al. (2009) found that participants reported greater increases in positive affect when they imagined a series of events with positive emotional outcomes as happening to themselves and described their mental image out loud (mental imagery condition), as compared to when they simply focused on the meaning of each description as they heard it (verbal thought condition). Such findings have lent support to Holmes et al.’s (2008) argument that as emotional processing in the brain is thought to be more responsive to mental imagery than verbal thought, visual imagery susceptibility (in their terminology, the tendency to be a “visualizer” rather than a “verbalizer”) is likely to be a neglected risk factor for a range of psychiatric disorders. Given the amplificatory effect of visual imagery on both affect and anxiety, it is unsurprising that the psychiatric disorder that has been the primary focus of initial visual imagery research has been bipolar disorder (e.g., Holmes et al., 2008). Although research in this area is still in its infancy, greater levels of intrusive visual imagery have been found in individuals with bipolar disorder compared to non-clinical controls (Tzemou & Birchwood, 2007), patients with bipolar disorder have been found, compared to healthy controls, to have significantly greater general mental imagery usage (Holmes et al., 2011), and hypomanic states in euthymic patients with bipolar disorder have been found to be associated with the experience of intrusive visual images (Gregory, Brewin, Mansell, & Donaldson, 2010). People experiencing hypomania, a termed first used by the German neuropsychiatrist Emanuel E. Mendel in 1881 to describe a state in which the typical features of mania are present but less pronounced (Malhi, Chengappa, Gershon, & Goldberg, 2010), are characterized by optimism, happiness, extraversion, sociability, and increased energy but can also be irritable, impulsive, risk-taking, irresponsible and controlling (Meads & Bentall, 2008). The Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR, APA, 2000) formally defines a hypomanic episode as a distinct period of abnormally and persistently elevated, expansive or irritable mood that lasts at least 4 days. During this time there must be the presence of at least three symptoms which include inflated self-esteem or grandiosity, a decreased need for sleep, pressure of speech, flight of ideas or the subjective experience that thoughts are racing, distractibility, increases in goal-directed activity, and an excessive involvement in pleasurable activities that have a high potential for painful consequences (e.g., engaging in unrestrained buying sprees, sexual indiscretions, or foolish business investments). Going beyond diagnosed hypomanic episodes, hypomania has been found to be a dimensional personality trait and part of normal experience (Meads & Bentall, 2008), but it can also be associated with an increased risk of later developing bipolar disorders (Kwapil et al., 2000). Building on the previous work described above linking visual imagery to hypomania, and establishing hypomania as a personality trait, we were concerned in this study to examine whether sub-clinical hypomanic personality traits, characterized by people who appear to be “in a mild manic state most of the time, are energetic, upbeat, gregarious people who are often able to work long hours with little sleep and who juggle numerous projects and social commitments” (Eckblad & Chapman, 1986, p. 216) were also specifically associated with the experience of intrusive visual imagery. First, we hypothesized that intrusive visual imagery would be more strongly associated with hypomania than would the general trait tendency to utilize visual imagery. This prediction was based on studies of other experiences commonly associated with psychopathology, such as hallucinations, showing that intrusive cognitions are related to such experiences both in psychiatric (Morrison & Baker, 2000) and non-psychiatric populations (Jones & Fernyhough, 2006). Second, following Holmes et al. (2008), we hypothesized a stronger relation of hypomania with intrusive visual imagery, than with intrusive verbal thought. Given that hypomanic personality traits in young adults have been found to correlate with levels of anxiety, depression, positive and negative affect (Lovejoy & Steuerwald, 1992) we assessed these variables to control for their potentially confounding effects.
نتیجه گیری انگلیسی
Descriptive statistics, and internal reliability data for the questionnaire measures employed, are presented in Table 1. All questionnaires employed, including the bespoke intrusive visual imagery and intrusive verbal thought questionnaires, were internally consistent. After 1 month a subset of the original participants (N = 36) agreed to complete the bespoke intrusive visual imagery and intrusive verbal thought questionnaire again. As shown in Table 1, both scales showed satisfactory test–retest reliability. Although in the overall sample there was a correlation between scores on the intrusive visual imagery and intrusive verbal thought questionnaires ( Table 2) a principal components factor analysis of responses to the combined 20 items on these two scales supported the argument that these scale represented two distinct constructs. A scree-plot inspection and parallel analysis using a Monte Carlo analysis with 1000 repetitions both suggested the extraction of two factors, with eigenvalues of 7.66 and 2.95, accounting for 53.06% of the observed variance. After varimax rotation, the 10 items on the intrusive visual imagery questionnaire all loaded (>.4) onto the first factor, with no cross-loading (defined as loading >.4 on more than one factor), and the 10 items on the intrusive verbal thought questionnaire loaded onto the second factor with no cross-loading. Table 1. Descriptive statistics for variables under investigation. Measure Mean (SD, range) Cronbach’s alpha Test–retest correlation Hypomania 7.68 (4.12, 0–20) .68 – Anxiety 8.05 (4.18, 1–20) .83 – Depression 4.60 (3.81, 0–21) .81 – Positive affect 29.52 (6.92, 13–49) .88 – Negative affect 22.70 (6.85, 10–46) .84 – Trait use of visual imagery 39.57 (9.31, 16–59) .83 – Intrusive visual imagery 32.88 (8.17, 10–50) .89 .70 Intrusive verbal thought 32.02 (8.61, 10–50) .90 .73 Table options Table 2. Bivariate correlations between variables under investigation. 1 2 3 4 5 6 7 8 Hypomania – .28⁎ .42⁎ .30⁎ .40⁎ .16 .16 .35⁎ Trait use of visual imagery – .43⁎ .17 .26⁎ .14 .10 .14 Intrusive visual imagery – .46⁎ .45⁎ .30⁎ −.04 .36⁎ Intrusive verbal thought – .43⁎ .31⁎ −.10 .45⁎ Anxiety – .52⁎ −.24 .68⁎ Depression – −.59 .46⁎ Positive affect – −.14 Negative affect – ⁎ p < .002. Table options There was no relationship between HPS-20 scores and age, r(218) = −.05, p = .49, nor between HPS-20 and gender, ρ(218) = −.03, p = .63. Bivariate correlations between the variables are presented in Table 2. A Bonferroni correction was employed and significance set at p = .002 (i.e., ∼.05/28). A hierarchical multiple linear regression was conducted with HPS-20 scores as the dependent variable. The assumption of independence of residuals was assured, as the Durbin–Watson value of the model was 2.10. A Kolmogorov–Smirnov test indicated that the standardized residuals did not deviate significantly from normality, D(220) = 0.06, p = .09. Examination of a plot of standardized residuals against standardized predicted values suggested no violation of the assumption of homoscedasticity. Results of this regression are reported in Table 3. Anxiety, depression, positive affect and negative affect were entered in a first step, which was statistically significant, ΔR2 = .24, F(4, 215) = 17.25, p < .001. Trait use of visual imagery, intrusive visual imagery and intrusive verbal thought were entered in a second step. Both this second step, ΔR2 = .06, ΔF(3, 212) = 5.50, p < .001, and the overall model, R2 = .30, F(7, 212) = 12.83, p < .001 were significant. In the overall model, positive affect, intrusive visual imagery, and anxiety were significant predictors of HPS-20 scores. When this regression was repeated with the mean-centred interaction between anxiety and positive affect entered in Step 2, this did not change the pattern of which variables were significant predictors of HPS-20 scores, and this interaction term itself was not a significant predictor, β = −.02, p = .79. Table 3. Multiple linear regression analyses predicting hypomania scores. Variable B SE B β p-Value Step 1 Anxiety 0.31 0.08 0.32 <.001 Depression 0.01 0.09 0.09 .31 Positive affect 0.20 0.05 0.33 <.001 Negative affect 0.08 0.05 0.14 .09 Step 2 Anxiety 0.21 0.08 0.21 .02 Depression 0.08 0.09 0.07 .39 Positive affect 0.17 0.04 0.29 <.001 Negative affect 0.07 0.05 0.11 .18 Trait use of visual imagery 0.03 0.03 0.06 .35 Intrusive visual imagery 0.11 0.04 0.22 .003 Intrusive verbal thought 0.01 0.03 0.02 .73 Table options In order to further probe the relation between hypomania, intrusive visual imagery, and affective states, a further multiple linear regression was performed with intrusive visual imagery as the dependent variable, and hypomania, anxiety, depression and positive and negative affect as independent variables. This model was a significant predictor of intrusive visual imagery scores, R2 = .28, F(5, 214) = 16.27, p < .001, with, as reported in Table 4, only anxiety and hypomania predicting levels of intrusive imagery. Table 4. Multiple linear regression analyses predicting intrusive visual imagery. Variable B SE B β p-Value Anxiety 0.59 0.17 0.30 <.001 Depression 0.08 0.18 0.04 .67 Positive affect 0.03 0.09 0.03 .74 Negative affect 0.07 0.10 0.06 .45 Hypomania 0.52 0.13 0.26 <.001 Table options Another notable finding from our data was that both depression and negative affect correlated positively with levels of intrusive visual imagery and intrusive verbal thought, but neither correlated with levels of trait use of visual imagery (Table 2). The correlation between negative affect and intrusive verbal imagery survived partialling for intrusive visual imagery and anxiety, r(216) = .26, p < .001, but depression did not, r(216) = .12, p = .07. Neither the correlation of negative affect nor depression with intrusive visual imagery survived partialling for anxiety and intrusive verbal imagery, r(216) = .01, p = .88, and r(216) = −.04, p = .56, respectively. When we performed equivalent analyses for anxiety, the relation between anxiety and intrusive visual imagery survived partialling for intrusive verbal thoughts, depression, and negative affect, r(215) = .26, p < .001, but the relation between anxiety and intrusive verbal thought did not survive partialling for intrusive visual thoughts, depression and negative affect, r(215) = .05, p = .45. Overall, this demonstrated a specific relation between anxiety and specifically intrusive visual imagery, and negative affect and specifically intrusive verbal thought.