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 groups
(i.e., patients with PTSD, with BN, with PD and with MD). Therefore, our results indicate
that affective dysregulation is, apart from very few exceptions, not very specific
for BPD, as the clinical groups tended to show similar results. In dataset 1 we found
no robust differences (i.e., consistent differences between the groups in both types
of multilevel analyses) neither regarding the distress level of the homebases nor
the valence dimension of the homebases of the BPD patients and the PTSD and BN patients.
Furthermore, we did not find consistent results regarding elevated affective variability
nor slower return to baseline in the BPD patients compared to either patient group,
i.e., PTSD and BN patients (dataset 1) or PD and MD patients (dataset 2). The only
robust exception (i.e., with consistent findings in both types of multilevel models)
where patients with BPD showed altered affective dynamics compared to the clinical
controls was: the BPD patients had a homebase with significantly higher levels of
distress compared to the PD and the MD patients (dataset 2). Thus, the only differences
emerged with regard to one of three subcomponents. Furthermore, the results regarding
the homebase component were not perfectly consistent, since: (a) differences regarding
the distress dimension of the homebase were only found in dataset 2 (i.e., the PD
and the MD patients), but not in dataset 1 (i.e., the PTSD and BN patients); and (b)
no differences regarding the valence dimension of the homebase emerged. Taken together,
our results do not show specificity of affective dysregulation regarding several components
of affective dysregulation (i.e., homebase, variability, and attractor strength) for
patients with BPD. Instead, our results can be interpreted as further empirical evidence
for affective dysregulation manifesting in similar ways in several different disorders
that are characterized by affective disturbances.
Of course, BPD is the disorder mainly associated with affective dysregulation and
there is even a BPD journal with emotion dysregulation it its title. However, there
are multiple theoretical conceptualizations which associate a variety of mental disorders
with affective dysregulation, i.e., some kind of burdensome affective experience,
deficient affect regulation, or dysfunctional affect regulation behavior 23]–27]. This is in line with the idea that affect regulation is an essential component to
mental health 9], 28] and an important risk and maintaining factor in various mental disorders 29], and that affect regulation strategies are included as treatment modules across numerous
disorders, e.g., eating disorders 30], 31], depressive disorders 32], and PTSD 33]. Taken together, these results might be interpreted as an indication that affective
dysregulation rather constitutes a transdiagnostic feature that emerges in several
mental disorders. Moreover, the differences between the patient groups and the healthy
controls regarding all three subcomponents of affective dysregulation are greatly
consistent, both for distress and valence. In a similar vein, prior studies investigating
the specificity of affective instability for BPD revealed mixed findings regarding
heightened instability in BPD compared to clinical controls. While several diary studies
found heightened affective instability in BPD compared to patients with depressive
disorders 34]–36], no differences were found between BPD patients and patients with PTSD 7], those with BN or with anorexia nervosa 7], 37], patients with premenstrual dysphoric syndrome 34], or other personality disorders 38]. Therefore, global instability indices were not able to clearly differentiate the
clinical groups and thus instability did not show sufficient specificity. Due to the
unexpected nature of these findings analyzing subcomponents of the dynamic processes
in order to delineate existing differences in emotional processes between patients
with BPD and clinical controls has been proposed recently 7], 8]. However, this could not resolve inconsistencies as we have shown in the present
paper. Thus, even though we used state of the art assessment (e-diaries) and analytic
methods (multilevel modeling) as well as two comprehensive datasets (N?=?119 and N?=?142) we did not find clear group differences regarding the subcomponents of affective
dysregulation between BPD patients and patients with PTSD, those with BN, those with
PD and those with MD as clinical control groups.
As we can exclude with reasonable certainty that subcomponent analyses reveal specificity
of affective dysregulation for BPD there are, on a methodological level, two more
main topics that should be considered to differentiate affective processes between
disorders 7], 26]: (a) events and triggers of emotional episodes are rarely assessed, but are very
likely to differ between disorders (a notable exception in BPD is 39]). E.g., tempting food might trigger affective processes in patients with BN, but
not in patients with PTSD, whereas for traumatic memories the opposite pattern might
be expected. Moreover, context plays a central role in emotion regulation 40], 41]. Therefore, contextual factors should be systematically incorporated into the study
of emotion dysregulation in future studies.; (b) the appraisal of affective processes
might be worthy of examination, since affective changes that are accompanied by changes
in self-esteem (a further diagnostic criterion for BPD) might be experienced as more
threatening 7]. Thus, the association between affective instability and self-esteem instability
in patients with BPD might differ (and therefore be specific for BPD) from those with
other psychiatric disorders. This association between affective dysregulation and
self-esteem instability in patients with BPD and those with other psychiatric disorders
should be investigated in future studies.
On top of that, undifferentiated affect or emotional granularity has been discussed
as being an essential component of the affect regulation process 42], 43]. However, its potential to show specificity of altered affect in BPD patients seems
rather limited, since a recent study showed that the experience of undifferentiated
affect probably constitutes a transdiagnostic mechanism and might be likely relevant
to a range of disorders 44].
Limitations and methodological particularities
Some limitations of our study should be mentioned. We used electronic diaries to investigate
affective dysregulation in participants’ everyday lives. This comes along with the
disadvantage that the control of confounding variables is limited. Even though laboratory
studies offer the possibility of testing hypotheses under the most rigorous control,
they nonetheless do so under artificial, laboratory conditions, which may account
for differences between the laboratory and real life 45]–47]. Investigating affective dysregulation in everyday life has the crucial advantage
that it renders experimental symptom induction unnecessary: it is studied in the context
where it naturally occurs, in patients’ everyday life 48]. Studies that have examined affective dysregulation in BPD in the laboratory have
produced inconsistent findings, which might be explained by the affect induction methods
used in these studies 8]. A further advantage of e-diary assessments is that retrospective single assessments
such as questionnaires or interviews are not suited to investigate dynamic processes,
such as affective dysregulation 26], 48]–51]. By utilizing e-diary methods one can repeatedly assess the variable of interest
in real time and therefore actually track the ebb and flow of affective states.
When investigating affective dynamics using e-diaries, it is of primary importance
that the sampling rate matches the temporal dynamics of the underlying target process
26], 48], 52]. Both a sampling rate that is too infrequent (which might miss the dynamics of interest)
as well as a sampling rate that is too frequent (which might overburden participants
without increasing insights since the information is irrelevant) is problematic 53]. Even though guidelines regarding the sampling frequency are rare, there is a general
consensus that the sampling interval must fit the temporal dynamics of the target
processes 52], 54]. In our two datasets the time-based designs differed. Assessments occurred every
15 min in datasets 1, and every hour in dataset 2. Since the conclusions were largely
similar across both datasets, the assessment methods do not seem to have substantially
influenced the results. Moreover, we are confident that both sample designs were appropriate
to assess the affective dynamics, since it has been empirically shown that a sampling
interval of less than 1 h captures a specific process, whereas the data yielded by
low frequency sampling rates (i.e., 2 h intervals and longer) cannot be distinguished
from random data 52].
Even though both the assessment method and the sample frequencies are appropriate
to investigate affective dynamics, the cross-sectional design of study 1 and 2 renders
it impossible to evaluate the importance of the affective dysregulation in the long
term. We determined the three subcomponents of affective dysregulation only during
24 h and 48 h, respectively. Thus, we got only a snapshot of affective dysregulation.
This is adequate to analyze group differences regarding affective dysregulation; however,
it is inappropriate to investigate potential associations between affective dysregulation
and long term variables, such as level of functioning and symptom severity, psychopathology,
or treatment outcome. Therefore, longitudinal studies allowing for the investigation
of the predictive value of affective dysregulation are clearly needed.
A further limitation is the rather small sample sizes of the clinical control groups
in both datasets. Even though both datasets were extensive (N?=?119 and N?=?142, respectively), this was mainly due to large group sizes of the BPD patients
and the healthy controls. With regard to the clinical groups, the group sizes of 28
patients with PTSD, 20 patients with BN and 26 PD patients and 25 MD patients are
low and larger sample sizes are needed to replicate findings. However, prior studies
analyzed group differences based on as small group sizes as 15 patients with BPD and
four patients with anorexia nervosa 37], or 16 patients with BPD, 10 patients with MD and 15 patients with premenstrual dysphoric
syndrome 34]. Moreover, the patient groups in both datasets differed in their hospitalization
rates. However, no differences in symptom severity between hospitalized and non-hospitalized
patients emerged (see Santangelo et al. 7] for dataset 1 and Stiglmayr et al. 14] for dataset 2). Furthermore, because only female participants were included in both
datasets, the generalizability of the findings is constrained and the results may
not be valid for male BPD patients. However, the use of a pure female sample also
reduced heterogeneity, which may be useful given the literature on sex differences
on affect 55]. In study 1 and 2 BPD diagnoses were made using different diagnostic instruments,
i.e., IPDE 16] in study 1 and SCID-II 17] in study 2. However, both diagnostic instruments are well-validated with very good
psychometric properties and good interrater reliability 16], 17]. Moreover, the two datasets were analyzed separately and independently, thus, diagnoses
and group comparisons are valid within each study. Patients, especially BPD patients,
in both datasets were diagnosed with a variety of comorbid disorders. Given the finding
that comorbidity might alter affective dysregulation 56] no statement can be made on whether our findings are independent of any comorbidity.
However, in BPD comorbidity is the rule rather than the exception 57] and therefore, only BPD patients with comorbid disorders are seen as representative
for the BPD population 58].