ارزیابی سیار روانشناختی از اختلال در نظم عاطفی در اختلال شخصیت مرزی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38471||2007||11 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Psychiatry Research, Volume 150, Issue 3, 15 April 2007, Pages 265–275
Abstract Many experts now believe that pervasive problems in affect regulation constitute the central area of dysfunction in borderline personality disorder (BPD). However, data is sparse and inconclusive. We hypothesized that patients with BPD, in contrast to healthy gender and nationality-matched controls, show a higher frequency and intensity of self-reported emotions, altered physiological indices of emotions, more complex emotions and greater problems in identifying specific emotions. We took a 24-hour psychophysiological ambulatory monitoring approach to investigate affect regulation during everyday life in 50 patients with BPD and in 50 healthy controls. To provide a typical and unmanipulated sample, we included only patients who were currently in treatment and did not alter their medication schedule. BPD patients reported more negative emotions, fewer positive emotions, and a greater intensity of negative emotions. A subgroup of non-medicated BPD patients manifested higher values of additional heart rate. Additional heart rate is that part of a heart rate increase that does not directly result from metabolic activity, and is used as an indicator of emotional reactivity. Borderline participants were more likely to report the concurrent presence of more than one emotion, and those patients who just started treatment in particular had greater problems in identifying specific emotions. Our findings during naturalistic ambulatory assessment support emotional dysregulation in BPD as defined by the biosocial theory of [Linehan, M.M., 1993. Cognitive–Behavioral Treatment of Borderline Personality Disorder. The Guildford Press, New York.] and suggest the potential utility for evaluating treatment outcome.
Introduction Borderline personality disorder (BPD) is characterized by severe deficits in interpersonal, cognitive, and emotional functioning (Lieb et al., 2004). Many experts now believe that the pervasive problems in affect regulation (often termed “emotion dysregulation”) represent the central area of dysfunction (Linehan, 1993, Coid, 1993, Corrigan et al., 2000, Skodol et al., 2002 and Sanislow et al., 2002). According to the biosocial theory of Linehan (1993), emotion dysregulation in BPD comprises increased sensitivity to emotional stimuli, unusually strong reactions, the occurrence of complex emotions (more than one emotion simultaneously), and problems in identifying emotions. However, data actually demonstrating emotion dysregulation is sparse and inconclusive. Support for the theory of emotion dysregulation is primarily based on subjective measures of emotion and experimental studies. A few studies that used multiple self-rating (diaries) over time reported a higher level of unpleasant affect in BPD patients, compared to a clinical control group (Stein, 1996) and psychologically healthy controls (Cowdry et al., 1991 and Stiglmayr et al., 2001). Using self-rating questionnaires, Koenigsberg et al. (2002) found however no evidence of elevated affect intensity in BPD patients when compared with other personality-disordered individuals. Experimental studies that applied emotion-inducing techniques also supported greater emotional dysregulation in BPD: Levine et al. (1997) elicited a heightened intensity of negative emotions in BPD patients, and Herpertz et al. (1997) provided evidence of elevated baseline emotional activation among patients with self-injuries, as compared to healthy controls. Studies using psychophysiological indicators of emotion have thus far failed to find a consistent pattern of affective dysregulation in BPD. Herpertz et al. (1999) exposed BPD patients and healthy controls to affect-inducing pictures but did not find any hyperreactivity among patients, either with respect to physiological indicators of emotion (heart rate, electromyogram or skin conductance) or to subjective ratings of emotion. In a similar study using functional MRI, Herpertz and colleagues (2001) found no differences in subjective emotions. However, BPD participants did show elevated blood flow in the amygdala. Likewise, Donegan et al. (2003) revealed greater left amygdala activation to emotional facial expression among patients with BPD, and Ebner-Priemer et al. (2005) revealed significantly higher startle response in BPD; enhanced startle response is caused by increased amygdala activation (e.g. by electrical stimulation), at least in animals (Davis et al., 1999). Unfortunately, neither Donegan et al. (2003) nor Ebner-Priemer et al. (2005) reported subjective emotional ratings. There are a number of possible explanations for these conflicting results. First, BPD patients without medication, who are often recruited for psychophysiological studies, are extremely rare (Zanarini et al., 2004) and may represent a healthier subgroup of BPD patients than medicated individuals. The same argument may apply to patients with BPD who are assessed after a long treatment program. Secondly, it is possible that the affect-induction methods used were insufficient to evoke affective dysregulation and that more personally relevant stimuli are preferable. Thirdly, most studies have been performed in a laboratory environment, and it is possible that the somewhat artificial conditions of the laboratory (e.g. insufficient time for adaptation, the psychological consequences of being observed and contrived experimental protocols) influenced the measurement of affective dysregulation. One difficulty encountered in the investigation of physiological indices of emotions in ambulatory studies has been the teasing apart of emotional and physical influences. In order to address this problem, Myrtek (2004) developed an algorithm to partition that part of heart rate (HR) increase that does not directly result from physical or metabolic activity; he has termed this measure “additional heart rate" (aHr). The algorithm is based on two experimental findings: namely, that HR reactivity, elicited by a combination of mental, emotional and physical stressors, closely approximates the additive combination of the HR responses evoked by the individual factors (Myrtek and Spital, 1986 and Roth et al., 1990), and that metabolic demand can be estimated with sensitive motion detectors (Myrtek, 2004). This non-metabolic heart rate increase (aHr) appears to be a valid measure of emotional response and has now been validated in multiple studies including more than 1300 participants. For example, aHr in male students was found to be greater when watching erotic films compared to comedies and this applied not only during rest but also under varied levels of physical exercise, and that these physiological differences corresponded to self-ratings of excitement (Myrtek and Bruegner, 1996). This demonstrates that the algorithm is not only able to detect emotional events under basal conditions but also under conditions of activity. Effects on aHr have also been demonstrated for children watching television at home: both school-age boys (Myrtek et al., 1996b) and preschool boys and girls (Wilhelm et al., 1997) manifested greater aHr during films with action scenes. In the same study, girls showed increased aHr while watching commercials that targeted girls (e.g. Barbie), as compared to gender-neutral commercials (Wilhelm et al., 1997). Additionally, one investigation found that train drivers showed higher aHr during situations associated with heightened risk for accidents (Myrtek et al., 1994). aHr is increased during leisure-time activities compared to periods of monotonous work (Myrtek et al., 1999), and in social interactions as compared to being alone (Myrtek et al., 1995). This is consistent with the use of aHr as an emotional indicator. There are several indications that aHr is primarily under sympathetic control: beta-adrenergic blockade studies of HR (Langer, 1985), evidence that metabolically induced HR responses are mainly vagally mediated (Grossman, 1983, Grossman and Svebak, 1987 and Watkins et al., 1998) and the missing correlation between aHr and heart rate variability (Myrtek et al., 1996a). A large and growing literature has linked indices of reduced baseline vagal activity to disorders with dysregulated affective styles, like depression, anxiety and panic (Beauchaine, 2001) and estimates of high vagal activity to relaxation (Houtveen et al., 2002). In order to address the question of emotional dysregulation in BPD, we employed psychophysiological ambulatory monitoring, which is also called ecological momentary assessment (Stone and Shiffman, 1994), to investigate both self-report measures (frequency and intensity of discrete emotions) and physiological indices of emotions (additional heart rate, spectral analysis indices of cardiac vagal activity) during 24 h of normal daily life. This approach circumvents several methodological limitations. Investigating naturally occurring symptoms in everyday life may render affect-inducing methods unnecessary and eliminates many of the problems associated with laboratory studies. We included patients who were currently in our treatment programs and did not alter their medication schedules; this was in order to provide a typical and experimentally unmanipulated sample of BPD patients in treatment, and therefore increase the generalizability of our findings. According to the biosocial theory (Linehan, 1993), we specifically hypothesized that patients with BPD, in contrast to matched healthy controls, would 1) show a higher frequency and intensity of self-reports of emotion, 2) manifest greater levels of additional heart rate and lower levels of heart rate variability indices of autonomic control, 3) report more complex emotions, and 4) show greater difficulty in identifying discrete emotions during periods of reported emotional arousal.
نتیجه گیری انگلیسی
. Results 3.1. Subjective emotions The relative frequency of the first reported emotion (overall and for specific emotions) is shown in Fig. 1. BPD patients reported specific negative emotions (anxious, angry, sad, shame, and disgust) significantly more often than the HC group. Probabilities and effect sizes are shown in Table 2. Furthermore BPD individuals also reported significantly fewer positive emotions (happy and interest). Effect sizes for group differences of all specific positive and negative emotions range between medium and large. Frequency and intensity of self-reported emotions for BPD (n=50) and HC (n=50) ... Fig. 1. Frequency and intensity of self-reported emotions for BPD (n = 50) and HC (n = 50) during 24-h ambulatory monitoring. Figure options Table 2. Probabilities and effect sizes of group differences (BPD vs. HC) for frequency and intensity of all specific positive and negative emotions Frequency of first emotion⁎ Intensity of first emotion Frequency of second emotion⁎ Intensity of second emotion P ES (r) t df P ES (d) P ES (r) t df P ES (d) Overall 0.009 0.26 3.30 98 0.001 0.67 < 0.001 0.43 3.49 94 < 0.001 0.71 Happy < 0.001 0.47 0.33 87 0.739 0.07 0.048 0.20 0.90 61 0.369 0.23 Interest < 0.001 0.42 1.61 92 0.110 0.33 0.123 0.15 1.48 74 0.143 0.34 Anxious < 0.001 0.55 4.90 69 < 0.001 1.20 < 0.001 0.48 4.25 66 < 0.001 1.06 Angry < 0.001 0.33 3.02 80 0.003 0.67 < 0.001 0.34 3.25 42 0.002 1.05 Sad < 0.001 0.55 2.91 55 0.005 0.81 < 0.001 0.44 3.56 50 < 0.001 1.04 Shame < 0.001 0.43 2.98 25 0.006 1.44 < 0.001 0.47 7.26 25.3 < 0.001 2.24 Disgust 0.004 0.29 4.24 28.8 < 0.001 1.48 0.002 0.31 2.54 30 0.016 1.24 Non-specific 0.705 0.04 2.29 93 0.024 0.47 No emotion 0.009 0.26 < 0.001 0.43 ⁎ = Wilcoxon-Test; according to Cohen (1988) effect sizes are considered as follows: r = 0.1: small, r = 0.3: medium, r = 0.5: large; d = 0.2: small, d = 0.5: medium, d = 0.8: large. Table options Because teaching patients to identify and name emotions is a major focus in DBT and patients in Germany/US differed in regard of duration of treatment participation (the German group was investigated before start of DBT treatment, whereas the US group was examined during ongoing DBT treatment), we analyzed the non-specific emotion for both countries separately, resulting in significant differences. German BPD participants had significantly more non-specific emotions than the German HC (χ2 = 4.18, df = 1, P = 0.041), whereas American patients reported fewer non-specific emotions than American HC (χ2 = 5.59, df = 1, P = 0.018). The overall intensity of subjective emotions (see Fig. 1) was significantly increased in BPD patients compared to the HC group (see Table 2 for probabilities and effect sizes). Examination of the specific emotions revealed significantly elevated intensities of all negative emotions for BPD participants, with large effect sizes. The intensity of positive emotions, however, was not significantly higher in the BPD group. Complex emotional responses consist of more than one simultaneous emotion. In analyses of these responses, examination of the second reported emotions revealed results similar to those in the analyses of the first reported emotions (probabilities and effect sizes are listed in Table 2). The frequency of complex emotional responses (overall) was significantly higher in the BPD group (see Fig. 1), as was the experience of all negative emotions. There were no group differences in the specific positive emotions reported. Effect sizes for the frequency of negative emotions ranged between medium and large. The intensity of the second specific negative emotion was significantly higher in BPD patients compared to HC, and this applied for all specific negative emotions (see Fig. 1 and Table 2). All effect sizes for the intensity of negative emotions were large. Positive emotions (second emotion) were not significantly increased in the BPD group. Finally, we examined the possible differences between the subjective ratings of emotion of patients with and without medication. The 36 comparisons (single and global frequency and intensity of all primary and secondary emotions) revealed only one significant difference (not adjusted; α < 0.05). This is below the expected probability doing 36 comparisons. Furthermore, there are no overt systematic differences such as heightened intensity or frequency of negative or positive emotions in one of the groups. 3.2. Physiological data Physiological data and statistics are presented in Table 3. As previously mentioned, we did not exclude patients on medication in order to improve generalizability of the findings. Unfortunately, problems are encountered in the psychophysiological assessment of patients on medication, due to known cardiovascular and autonomic effects of several psychotropic medications (Yeragani et al., 2002 and Ikawa et al., 2001). When we compared BPD patients with and without medication, there were significant differences (with large effect sizes) on nearly every physiological parameter: heart rate, additional heart rate, heart rate baseline, and HF-HRV. Table 3. Physiological statistics for BPD with medication, BPD without medication, and HC as well as probabilities and effect sizes for group differences HC BPD non-med BPD med BPD (total) BPS med. vs. BPS non-med HC vs. BPD non-med Mean (S.D.) t df P ES (d) t df P ES (d) Participants (n) 50 10 40 50 Heart rate (24 h) 78.4 (7.4) 76.9 (6.2) 83.6 (10.8) 82.3 (10.3) − 2.59 24.8 0.016 0.76 − 0.60 58 0.551 0.22 Activity (24 h) 17.9 (4.2) 17.3 (3.1) 18.1 (4.4) 18.0 (4.1) − 0.55 48 0.582 0.21 − 0.472 58 0.638 0.16 Additional heart rate (24 h) 1.84 (0.40) 2.21 (0.52) 1.52 (0.54) 1.66(0.60) 3.64 48 < 0.001 1.25 2.61 58 0.011 0.80 Power of HF-HRV (24 h) log(ms2 + 1) 2.91 (0.32) 3.09 (0.27) 2.45 (0.39) 2.58 (0.45) 4.80 48 < 0.001 1.91 1.61 58 0.112 0.61 Heart rate baseline at night 61.4 (6.6) 57.0 (5.5) 66.3 (8.9) 64.4 (9.2) − 3.05 17.5 0.001 1.26 − 1.96 58 0.054 0.72 Power of HF-HRV (night) log(ms2 + 1) 3.17 (0.36) 3.32 (0.26) 2.89 (0.43) 2.98 (0.43) 3.01 48 0.004 1.21 1.21 58 0.23 0.48 HC = healthy controls; BPD non-med. = borderline patients without medication; BPS med. = borderline patients with medication; HF-HRV = high-frequency heart rate variability log(ms2 + 1); according to Cohen (1988) effect sizes (d) are considered as follows: 0.2 = small, 0.5 = medium, 0.8 = large. Table options Comparing only non-medicated BPD participants to the HCs revealed significantly elevated aHr in the (non-medicated) BPD group. Because the comparison of groups with such different sample sizes is statistically problematic, we compared aHr differences between HC (n = 50) and non-medicated BPD patients (n = 10), using a non-parametric test (Wilcoxon rank-sum). Again, there was a significant group difference (P = 0.023). To further validate this, we age-matched a subgroup of HC (n = 10) with the non-medicated BPD patient and found also a significant difference for aHr (t = 2.21, df = 18, P = 0.040). Another critical point is that the differences of aHr may be caused by age differences of the groups (BPD vs. HC). We therefore double checked our findings using age as a covariate, resulting in the same finding, a significant effect for aHr and a non-significant effect for age (aHr: F = 6.47, df = 1, P = 0.014; age: F = 2.58, df = 1, P = 0.114). Non-medicated BPD participants tended also to have heightened vagal activity (HF-HRV 24 h) in comparison to the HC, and reduced concomitant heart rate baseline. Differences were not significant, but both effect sizes were medium to high. Using a non-parametric test (Wilcoxon rank-sum), we compared vagal activity differences between HCs (n = 50) and non-medicated BPD patients (n = 10), and found a nearly significant group difference (P = 0.077). To further validate this, we age-matched a subgroup of HC (n = 10) with the non-medicated BPD patient, but there was no significant difference for HF-HRV (t = 1.25, df = 18, P = 0.229). There was no group difference for the HF-HRV night-baseline (Wilcoxon P = 0.234; age-matched sample t = 1.37, df = 18, P = 0.189).