To further clarify the specificity of affective dysregulation in BPD, we used a recently
\n proposed model of affective dynamics (the DynAffect model) simultaneously modeling
\n three central subcomponents of affective dysregulation (homebase, variability, and
\n attractor strength). Contrary to our expectations, BPD patients did not consistently
\n show a specific pattern of affective dysregulation compared to other clinical groups
\n (i.e., patients with PTSD, with BN, with PD and with MD). Therefore, our results indicate
\n that affective dysregulation is, apart from very few exceptions, not very specific
\n for BPD, as the clinical groups tended to show similar results. In dataset 1 we found
\n no robust differences (i.e., consistent differences between the groups in both types
\n of multilevel analyses) neither regarding the distress level of the homebases nor
\n the valence dimension of the homebases of the BPD patients and the PTSD and BN patients.
\n Furthermore, we did not find consistent results regarding elevated affective variability
\n nor slower return to baseline in the BPD patients compared to either patient group,
\n i.e., PTSD and BN patients (dataset 1) or PD and MD patients (dataset 2). The only
\n robust exception (i.e., with consistent findings in both types of multilevel models)
\n where patients with BPD showed altered affective dynamics compared to the clinical
\n controls was: the BPD patients had a homebase with significantly higher levels of
\n distress compared to the PD and the MD patients (dataset 2). Thus, the only differences
\n emerged with regard to one of three subcomponents. Furthermore, the results regarding
\n the homebase component were not perfectly consistent, since: (a) differences regarding
\n the distress dimension of the homebase were only found in dataset 2 (i.e., the PD
\n and the MD patients), but not in dataset 1 (i.e., the PTSD and BN patients); and (b)
\n no differences regarding the valence dimension of the homebase emerged. Taken together,
\n our results do not show specificity of affective dysregulation regarding several components
\n of affective dysregulation (i.e., homebase, variability, and attractor strength) for
\n patients with BPD. Instead, our results can be interpreted as further empirical evidence
\n for affective dysregulation manifesting in similar ways in several different disorders
\n that are characterized by affective disturbances.\n <\/p>\n
Of course, BPD is the disorder mainly associated with affective dysregulation and As we can exclude with reasonable certainty that subcomponent analyses reveal specificity On top of that, undifferentiated affect or emotional granularity has been discussed Some limitations of our study should be mentioned. We used electronic diaries to investigate When investigating affective dynamics using e-diaries, it is of primary importance Even though both the assessment method and the sample frequencies are appropriate A further limitation is the rather small sample sizes of the clinical control groups To further clarify the specificity of affective dysregulation in BPD, we used a recently proposed model of affective dynamics (the DynAffect model) simultaneously modeling three central subcomponents of affective dysregulation (homebase, variability, and attractor strength). Contrary to our expectations, BPD patients did not consistently show a specific pattern of affective dysregulation compared to other clinical Read More<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-90882","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/posts\/90882","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/comments?post=90882"}],"version-history":[{"count":0,"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/posts\/90882\/revisions"}],"wp:attachment":[{"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/media?parent=90882"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/categories?post=90882"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/healthmedicinet.com\/i\/wp-json\/wp\/v2\/tags?post=90882"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n there is even a BPD journal with emotion dysregulation it its title. However, there
\n are multiple theoretical conceptualizations which associate a variety of mental disorders
\n with affective dysregulation, i.e., some kind of burdensome affective experience,
\n deficient affect regulation, or dysfunctional affect regulation behavior 23<\/a>]\u201327<\/a>]. This is in line with the idea that affect regulation is an essential component to
\n mental health 9<\/a>], 28<\/a>] and an important risk and maintaining factor in various mental disorders 29<\/a>], and that affect regulation strategies are included as treatment modules across numerous
\n disorders, e.g., eating disorders 30<\/a>], 31<\/a>], depressive disorders 32<\/a>], and PTSD 33<\/a>]. Taken together, these results might be interpreted as an indication that affective
\n dysregulation rather constitutes a transdiagnostic feature that emerges in several
\n mental disorders. Moreover, the differences between the patient groups and the healthy
\n controls regarding all three subcomponents of affective dysregulation are greatly
\n consistent, both for distress and valence. In a similar vein, prior studies investigating
\n the specificity of affective instability for BPD revealed mixed findings regarding
\n heightened instability in BPD compared to clinical controls. While several diary studies
\n found heightened affective instability in BPD compared to patients with depressive
\n disorders 34<\/a>]\u201336<\/a>], no differences were found between BPD patients and patients with PTSD 7<\/a>], those with BN or with anorexia nervosa 7<\/a>], 37<\/a>], patients with premenstrual dysphoric syndrome 34<\/a>], or other personality disorders 38<\/a>]. Therefore, global instability indices were not able to clearly differentiate the
\n clinical groups and thus instability did not show sufficient specificity. Due to the
\n unexpected nature of these findings analyzing subcomponents of the dynamic processes
\n in order to delineate existing differences in emotional processes between patients
\n with BPD and clinical controls has been proposed recently 7<\/a>], 8<\/a>]. However, this could not resolve inconsistencies as we have shown in the present
\n paper. Thus, even though we used state of the art assessment (e-diaries) and analytic
\n methods (multilevel modeling) as well as two comprehensive datasets (N?=<\/em>?119 and N?=<\/em>?142) we did not find clear group differences regarding the subcomponents of affective
\n dysregulation between BPD patients and patients with PTSD, those with BN, those with
\n PD and those with MD as clinical control groups.\n <\/p>\n
\n of affective dysregulation for BPD there are, on a methodological level, two more
\n main topics that should be considered to differentiate affective processes between
\n disorders 7<\/a>], 26<\/a>]: (a) events and triggers of emotional episodes are rarely assessed, but are very
\n likely to differ between disorders (a notable exception in BPD is 39<\/a>]). E.g., tempting food might trigger affective processes in patients with BN, but
\n not in patients with PTSD, whereas for traumatic memories the opposite pattern might
\n be expected. Moreover, context plays a central role in emotion regulation 40<\/a>], 41<\/a>]. Therefore, contextual factors should be systematically incorporated into the study
\n of emotion dysregulation in future studies.; (b) the appraisal of affective processes
\n might be worthy of examination, since affective changes that are accompanied by changes
\n in self-esteem (a further diagnostic criterion for BPD) might be experienced as more
\n threatening 7<\/a>]. Thus, the association between affective instability and self-esteem instability
\n in patients with BPD might differ (and therefore be specific for BPD) from those with
\n other psychiatric disorders. This association between affective dysregulation and
\n self-esteem instability in patients with BPD and those with other psychiatric disorders
\n should be investigated in future studies.\n <\/p>\n
\n as being an essential component of the affect regulation process 42<\/a>], 43<\/a>]. However, its potential to show specificity of altered affect in BPD patients seems
\n rather limited, since a recent study showed that the experience of undifferentiated
\n affect probably constitutes a transdiagnostic mechanism and might be likely relevant
\n to a range of disorders 44<\/a>].\n <\/p>\nLimitations and methodological particularities<\/h4>\n
\n affective dysregulation in participants\u2019 everyday lives. This comes along with the
\n disadvantage that the control of confounding variables is limited. Even though laboratory
\n studies offer the possibility of testing hypotheses under the most rigorous control,
\n they nonetheless do so under artificial, laboratory conditions, which may account
\n for differences between the laboratory and real life 45<\/a>]\u201347<\/a>]. Investigating affective dysregulation in everyday life has the crucial advantage
\n that it renders experimental symptom induction unnecessary: it is studied in the context
\n where it naturally occurs, in patients\u2019 everyday life 48<\/a>]. Studies that have examined affective dysregulation in BPD in the laboratory have
\n produced inconsistent findings, which might be explained by the affect induction methods
\n used in these studies 8<\/a>]. A further advantage of e-diary assessments is that retrospective single assessments
\n such as questionnaires or interviews are not suited to investigate dynamic processes,
\n such as affective dysregulation 26<\/a>], 48<\/a>]\u201351<\/a>]. By utilizing e-diary methods one can repeatedly assess the variable of interest
\n in real time and therefore actually track the ebb and flow of affective states.\n <\/p>\n
\n that the sampling rate matches the temporal dynamics of the underlying target process
\n 26<\/a>], 48<\/a>], 52<\/a>]. Both a sampling rate that is too infrequent (which might miss the dynamics of interest)
\n as well as a sampling rate that is too frequent (which might overburden participants
\n without increasing insights since the information is irrelevant) is problematic 53<\/a>]. Even though guidelines regarding the sampling frequency are rare, there is a general
\n consensus that the sampling interval must fit the temporal dynamics of the target
\n processes 52<\/a>], 54<\/a>]. In our two datasets the time-based designs differed. Assessments occurred every
\n 15\u00a0min in datasets 1, and every hour in dataset 2. Since the conclusions were largely
\n similar across both datasets, the assessment methods do not seem to have substantially
\n influenced the results. Moreover, we are confident that both sample designs were appropriate
\n to assess the affective dynamics, since it has been empirically shown that a sampling
\n interval of less than 1\u00a0h captures a specific process, whereas the data yielded by
\n low frequency sampling rates (i.e., 2\u00a0h intervals and longer) cannot be distinguished
\n from random data 52<\/a>].\n <\/p>\n
\n to investigate affective dynamics, the cross-sectional design of study 1 and 2 renders
\n it impossible to evaluate the importance of the affective dysregulation in the long
\n term. We determined the three subcomponents of affective dysregulation only during
\n 24\u00a0h and 48\u00a0h, respectively. Thus, we got only a snapshot of affective dysregulation.
\n This is adequate to analyze group differences regarding affective dysregulation; however,
\n it is inappropriate to investigate potential associations between affective dysregulation
\n and long term variables, such as level of functioning and symptom severity, psychopathology,
\n or treatment outcome. Therefore, longitudinal studies allowing for the investigation
\n of the predictive value of affective dysregulation are clearly needed.\n <\/p>\n
\n in both datasets. Even though both datasets were extensive (N?=<\/em>?119 and N?=<\/em>?142, respectively), this was mainly due to large group sizes of the BPD patients
\n and the healthy controls. With regard to the clinical groups, the group sizes of 28
\n patients with PTSD, 20 patients with BN and 26 PD patients and 25 MD patients are
\n low and larger sample sizes are needed to replicate findings. However, prior studies
\n analyzed group differences based on as small group sizes as 15 patients with BPD and
\n four patients with anorexia nervosa 37<\/a>], or 16 patients with BPD, 10 patients with MD and 15 patients with premenstrual dysphoric
\n syndrome 34<\/a>]. Moreover, the patient groups in both datasets differed in their hospitalization
\n rates. However, no differences in symptom severity between hospitalized and non-hospitalized
\n patients emerged (see Santangelo et al. 7<\/a>] for dataset 1 and Stiglmayr et al. 14<\/a>] for dataset 2). Furthermore, because only female participants were included in both
\n datasets, the generalizability of the findings is constrained and the results may
\n not be valid for male BPD patients. However, the use of a pure female sample also
\n reduced heterogeneity, which may be useful given the literature on sex differences
\n on affect 55<\/a>]. In study 1 and 2 BPD diagnoses were made using different diagnostic instruments,
\n i.e., IPDE 16<\/a>] in study 1 and SCID-II 17<\/a>] in study 2. However, both diagnostic instruments are well-validated with very good
\n psychometric properties and good interrater reliability 16<\/a>], 17<\/a>]. Moreover, the two datasets were analyzed separately and independently, thus, diagnoses
\n and group comparisons are valid within each study. Patients, especially BPD patients,
\n in both datasets were diagnosed with a variety of comorbid disorders. Given the finding
\n that comorbidity might alter affective dysregulation 56<\/a>] no statement can be made on whether our findings are independent of any comorbidity.
\n However, in BPD comorbidity is the rule rather than the exception 57<\/a>] and therefore, only BPD patients with comorbid disorders are seen as representative
\n for the BPD population 58<\/a>].\n <\/p>\n","protected":false},"excerpt":{"rendered":"