Skip to main content
The Egyptian Journal of Neurology, Psychiatry and Neurosurgery
Download PDF

Role of DSM5 anxious distress specifier interview in acute manic episode: sociodemographic characteristics, clinical presentation and quality of life

The Egyptian Journal of Neurology, Psychiatry and Neurosurgery volume 59, Article number: 33 (2023) Cite this article

Abstract

Background

DSM 5 anxious distress specifier is one of the newly added specifiers for bipolar and related disorders. It may have impacts on the symptoms severity, insight, impulsivity, and different domains of quality of life of acute manic episodes of bipolar disorders. The current study aimed to study the effects of DSM 5 anxious distress specifier in acute manic episodes and its relation to sociodemographic data, clinical characteristics, and quality of life. 380 patients with the diagnosis of acute manic episode were recruited in the study, sociodemographic data, clinical features, DSM 5 anxious distress specifier interview, attitude and insight of the disorder, impulsivity and different aspects of quality of life were also evaluated in those patients.

Results

The studied patients were divided into 2 subgroups according to the presence of high DSM5 anxious distress specifier interview score. The duration of a manic episode (P < 0.001), the severity of the manic episode (P < 0.001), and the presence of psychotic features (P = 0.002) were more common in the subgroup with high DSM 5 anxious distress. DSM 5 anxious distress specifier was severe (P < 0.001) and more frequent (P < 0.001) in the 1st subgroup than the 2nd one. There was a statistically significant difference regarding the attentional facet of the Barratt impulsiveness scale between the studied groups (P = 0.002). In addition, there was a statistically significant difference regarding the mean score (P < 0.001) and severe impairment (P < 0.001) domains of work and social adjustment scale between the 2 subgroups.

Conclusions

DSM 5 anxious distress specifier interview is a very crucial parameter of evaluation the patients with acute manic episodes which may have implications on the clinical presentations, symptoms severity, impulsivity, and variable aspects of quality of life in those patients. All these implications might change the course, prognosis, and outcomes of an acute manic episode of bipolar disorder.

Background

Bipolar disorder (BD) is one of the devastating psychiatric disorders that have a prevalence of around 0.6% for type I and 0.4% for type II [1]. It is one of the commonest psychiatric disorders causing socio-occupational dysfunctioning all over the world [2]. World Health Organization (WHO) declared bipolar disorders as the sixth leading cause of years lost in young adults [3].

Bipolar disorders are manifested by alteration in mood between mania and hypomania or between depression and mixed episodes [4], depressive symptoms usually present in individuals with BD, the clinical operational criteria is the presence of manic or hypo-manic episodes [5]. During episodes of mania or hypomania, the patient may have elevated mood, including euphoria, grandiosity, psychomotor hyperactivity, increased sexual activity, decreased need for sleep, risk-taking behaviors, irritability, and aggression.

On the contrary depressive episode are manifested by anhedonia, depressed mood, vegetative symptoms, and psychomotor retardation. Mixed episodes characterize by concomitant states of mania and depression [6]. Life expectancy is decreased by 9 years on average in individuals with BD as compared with the general population [7].

Anxiety symptoms and anxiety disorders are commonly found in patients with major depressive disorder (MDD) [8], leading to suicidal ideations and attempts [9], drastic deterioration in functioning [10], impaired quality of life [11], worse prognosis [12], frequent depressive episodes [13], and poor adherence to treatment [14].

In addition, Anxiety disorders (AD) are the most frequent psychiatric disorders and are more frequently found in patients with BD than in the general population [15, 16]. Spoorthy et al. [17] noted that more than half of patients with BD will develop AD during their life and about a third of them are likely to be affected by AD throughout the course [18].

For all the previous rationalizations, the anxious distress (ANXD) specifier has been added in the Diagnostics and Statistical Manual of Mental Disorders-5 (DSM-5) in both sections of depressive and related disorders and bipolar disorders, also psychomotor agitation has been used for the detection of the severity of ANXD. Psychomotor agitation in MDD is related to bipolarity [15] and the ANXD specifier could be a screening tool for psychomotor agitation, which was excluded as a manic/hypomanic symptom from the operational criteria of the mixed features specifier in a major depressive episode (MDE).

DSM-5 illustrated criteria for an anxious distress specifier for major depressive disorder (MDD) and bipolar depression [6]. A measure of the severity of anxiety based on the DSM-5 anxious distress criteria offers several advantages over the Hamilton rating scale of anxiety (HAMA) including simplicity, composed of only 5 items versus the 14 items of the HAMA, so it is easily applied and less time-consuming.

Zimmerman et al. [19] developed and validated a semi-structured interview to assess the criteria of the DSM-5 anxious distress specifier, the DSM-5 Anxious Distress Interview (DADSI)—in depressed patients. The DSM-5 Anxious Distress Specifier Interview (DADSI) evaluated the five symptoms of the anxious distress specifier.

To our knowledge, there is not enough research studying the DADSI as a semi-structured interview for evaluation of ANXD in bipolar disorders, particularly in an acute manic episode, and the impacts of this newly added ANXD on the clinical characteristics, symptoms rating, and quality of life including social and work domains of those patients.

Aim of the work: the current study aimed to study DADSI as a tool for assessment of ANXD in the acute manic episode of bipolar disorder, to find out the effects ANXD which was evaluated by DADSI on symptoms profile and impulsiveness in those patients, and to illustrate the burden of DADSI on the work and social domains of Quality of Life (QOL) in those patients.

Methods

This is a cross-sectional study with an analytical component 380 patients with acute manic episodes of bipolar disorder were recruited in the current study from June 2020 to March 2022, the studied participants were divided into 2 groups according to the presence or absence of high scores of DADSI regarding the severity and frequency of its items.

The study included patients of both sexes, aged from 18 to 60 years, and diagnosis of a manic episode of bipolar disorders by 2 experts Psychiatrists, while the current study excluded any patient with major depressive disorders, schizophrenia, schizoaffective disorders, and other anxiety disorders, Patients with general medical conditions (renal, cardiac, hepatic, epileptic), Patients under psychotropics, Previous admission in Psychiatric units or Electroconvulsive therapy (ECT).

The study consisted of the sociodemographic data of 380 patients with acute manic episodes of bipolar disorder including age, sex, education, residence smoking, marital status, employment, and socioeconomic status. Diagnosis of acute manic episode according to the operational criteria of DSM 5 by 2 expert Psychiatrists.

The study evaluated the clinical characteristics of the patients including a family history of bipolar disorder, Presence of psychotic features, Presence of precipitating event for 1st episode, Duration of a manic episode.

The DSM-5 Anxious Distress Specifier Interview (DADSI) assesses the 5 symptoms of the anxious distress specifier which is mentioned in DSM 5. The DADSI assess symptom presence and severity for the past week, and they also if the symptom was present for the majority of the manic episode. The severity of the items is rated on Lickert from 0 to 4, with the rating level for each item accompanied by a brief description. The total score on the measure ranges from 0 to 20. The joint-interview inter-rater reliability of the DADSI was rated reliably (mean ICC = 0.93; mean kappa = 0.98). The test–retest reliability of the total scale dimensional score was excellent (ICC = 0.80), and the reliability of anxious distress sub typing was good (kappa = 0.60). The DADSI and HAMA were significantly correlated (r = 0.52, P < 0.001). Both the DADSI and HAMA were more highly correlated with measures of anxiety than with measures of the other symptom domains [19].

Young Mania Rating scale: assess the severity of manic episodes which is an 11-item clinician-applied scale to evaluate the severity of manic symptoms [21]. A score of < 13 is considered normal, a score of 13–19 is considered minimal severity, a score of 20–26 is considered mild, a score of 27–38 is considered moderate and that of > 38 is considered severe. The reliability of the instrument was evaluated by comparing each individual item with the total YMRS score. Correlations ranged from 0.41 (appearance) to 0.85 (language and thought disorder), the joint reliability for total scores was 0.93, and the correlation between raters for individual items ranged from 0.66 (disruptive–aggressive behavior) to 0.95 (sleep). The validity of the YMRS was evaluated by comparing its performance with that of the Petterson Mania Scale, the Beigel’s Mania Rating Scale (BMRS), and a global measure of mania. The correlation was 0.88 between the YMRS and a global mania rating scale, 0.71 between the YMRS and the BMRS, and 0.89 between the YMRS and the Petterson Rating Scale [20].

Barratt Impulsiveness Scale (BIS) to assess self-reported impulsivity of both healthy individuals and psychiatric populations. The instrument includes 30 items, scored on a four-point scale: (1) rarely/never, (2) occasionally, (3) often, (4) almost always/always. The three main impulsivity factors are the Attentional domain (poor attention and cognitive instability), Motor domain (motor activity and poor perseverance), and non-planning domain (poor self-control and cognitive complexity). Before adding up your scores in each section, reverse the scores of reverse questions; for example, if your score on a reverse score question was 4, then reverse it to 1. The total score is the sum of all the items [21]. The BIS scores were positively moderately correlated with the short Impulsive behaviour scale UPPS-P-G (r = 0.379, P < 0.001), indicating good convergent validity in the Greek population for both of the scales [22].

Insight and treatment attitude questionnaire (ITAQ) to measure the awareness of having a psychiatric disorder and awareness of indication for management either by hospitalization or medications. It is a validated 11-item semi-structured interview that has a score from 0 (no insight) to 22 (maximum insight). The total score is categorized into three groups: good insight (15–22), fair insight (8–14), and poor insight (0–7). The assessment of patients’ opinions via two different methodologies (totals ITAQ score and open interview) showed a high and significant correlation (r = 0.85, P < 0.001) which supported that ITAQ as a valid measure of insight [23].

Work and social adjustment scale (WSAS) which consisted of 5 questions assessing the work and social domains of QOL, the answer ranged on a Likert scale from 0 = Not at all to 8 = very severely. The maximum score is 40, the lower scores are better. A score of WSAS above 20 is considered a severe impairment of QOL, scores between 10 and 20 are associated with significant functional impairment and below 10 is related to subthreshold impairment, The correlations between the WSAS and both the PHQ-9 (r = 0.58, P < 0.001) and GAD-7 (r = 0.51, P < 0.001) were significant with a large effect which evidenced that WSAS is a valid tool for assessment of functional impairment related to definite disorder [24].

Statistical analysis consisted of data that were fed to the computer and analyzed using IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk (2013, IBM Corp, NY, USA). Qualitative data were described using numbers and percentages. Quantitative data were described using median (minimum and maximum) and mean, and standard deviation for parametric data after testing normality using the Kolmogrov–Smirnov test. The significance of the obtained results was judged at the (0.05) level. Data analysis includes Qualitative data: by Chi-Square test and Monte Carlo test for comparison of 2 or more groups. Quantitative data between groups: includes Parametric tests: by Student t test was used to compare 2 independent groups. Spearman’s correlation: is used to determine the strength and direction of a linear relationship between two non-normally distributed continuous variables and/or ordinal variables. Point–biserial correlation is used to determine the strength of a linear relationship between one continuous variable and one nominal variable with two categories including a dichotomous variable. Binary stepwise logistic regression analysis was used for the prediction of independent variables of a binary outcome. Significant predictors in the Univariate analysis were entered into the regression model using the forward Wald method/Enter. Adjusted odds ratios and their 95% confidence interval were calculated.

Results

Table 1 shows the sociodemographic characteristics of the studied group: the studied group was classified into 2 subgroups according to the presence or absence of a high score of DADSI:

Table 1 Comparison of socio-demographic characteristics between studied groups
Full size table

The 1st subgroup with high DADSI: the number of cases 200 cases including 135 (67.5) males and 65 (32.5) females, the age was 35.74 ± 9.61, regarding the employment status, 109 (54.5) were employed and 91 (45.5) were non-employed. In regard to socioeconomic status; 135 (67.5) with satisfactory income and 65 (32.5) with unsatisfactory income.

The 2nd subgroup without high DADSI: the number of cases was 180 including 118 males (65.6) and 62 females (34.4) with an age was 35.60 ± 9.29, regarding socioeconomic status; 112 (62.2) with satisfactory income and 68 (37.8) with unsatisfactory income. There was a statistically significant difference between the 2 subgroups regarding the educational level and smoking status (P < 0.001).

Figure 1 illustrates anxious distress specifier as measured by DADSI between the 2 groups: in which there was a statistically significant difference between the studied groups regarding the severity of DADSI.

Fig. 1
figure 1

Illustrates the DADSI severity between the 2 groups. DADSI: DSM5 Anxious Distress Specifier Interview

Full size image

Table 2 illustrates the clinical characteristics between study groups in which there was a statistically significant difference between the studied groups regarding the presence of psychotic features (P = 0.002), Duration of a manic episode (P < 0.001) and Young mania rating scale (P < 0.001). At the same time, there was no statistically significant difference between the studied groups regarding the Family history of bipolar disorder (P = 0.627), Presence of precipitating stressor for 1st episode (P = 0.073), and Insight and treatment attitude questionnaire (P = 0.676).

Table 2 Comparison of clinical characteristics between studied groups
Full size table

Figure 2 illustrates the Barratt impulsiveness scale between the 2 groups: in which there was a statistically significant difference regarding the attentional facet of BIS between the 2 subgroups.

Fig. 2
figure 2

Illustrates the Barratt impulsiveness scale between the 2 groups

Full size image

Table 3 illustrates the DSM5 anxious distress specifier interview between studied groups in which there was a statistically significant difference between the studied groups regarding the frequency and severity of items of DADSI (P < 0.001).

Table 3 Comparison of DSM5 anxious distress specifier interview between studied groups
Full size table

Figure 3 illustrates the Work and Social Adjustment Scale among the studied groups: in which there was a statistically significant difference regarding the mean score of WSAS between the studied groups.

Fig. 3
figure 3

Illustrates the work and social adjustment scale among the studied groups

Full size image

Table 4 shows the comparison of the Barratt impulsiveness scale between studied groups in which there was a statistically significant difference between the studied groups regarding the attentional facet of the Barratt impulsiveness scale (P = 0.002), also there was no statistically significant difference between the studied groups regarding the attentional facet of Barratt impulsiveness scale regarding the motor facet (P = 0.855) and planning facet of the scale (P = 0.728).

Table 4 Comparison of Barratt impulsiveness scale between studied groups
Full size table

Table 5 illuminates the comparison of the Work and Social Adjustment Scale among the 2 groups in which there was a statistically significant between the studied groups regarding the mean total score of the Work social adjustment scale (P < 0.001), also in the domains of Significant impairment and Severe, worse impairment and psychopathology (P < 0.001).

Table 5 Illustrates the work and social adjustment scale among the two groups
Full size table

Table 6 shows the Univariate regression analysis for predictors of an acute manic episode of bipolar disorder with DADSI in which the educational level including university (P value = 0.028*), higher education (P value = 0.003*) frequency of DADSI present past week (P value ≤ 0.001*), present majority of days of episodes (P value ≤ 0.001*), 2 and 3 met (P value ≤ 0.001*). Regarding the severity of DADSI in which moderate: (P value = 0.002*), moderately severe (P value ≤ 0.001*), presence of psychotic features (P value = 0.002*), duration of manic episode > 30 days (P value = 0.004*), moderately to severe impairment or worse psychopathology of work and social adjustment scale (P value ≤ 0.001*) and Young mania rating scale in which mild (P value = 0.001*) and moderate domain (P value ≤ 0.001*).

Table 6 Univariate regression analysis for predictors of acute manic episode of bipolar disorder with DADSI
Full size table

Discussion

The current study aimed to investigate the role of a new modality of assessment of anxious distress specifier called DADSI in cases of an acute manic episode in the symptoms profile, severity, relation to impulsiveness, disease insight and attitude, and impacts on social and work domains of the patients’ Quality of Life (QOL). To our knowledge this is one leading study to use DADSI in an acute manic episode and its relation as a tool of evaluation of anxious distress specifier to different variables in those patients, also the studies that examined these variables were scarce.

The score of DADSI as a measurement of anxious distress specifier was high in the lower level of education, in divorced and widowed patients and smokers which is in agreement with previous studies conducted in depressed patients with high anxious distress specifier [8, 25, 26]. On the contrary, other studies found there was no significant difference in sociodemographic characteristics between the patients with and without anxious distress [27].

This study revealed that the psychotic features were more common in the subgroup without a high level of ANXD by the new semi-structured DADSI which was not consistent with the studies [25, 28] in which was noted that patients of Major Depressive Disorder (MDD) with high DADSI have more evident psychotic features and indicated for antipsychotic medications after getting resistance to ordinary antidepressants.

In addition, the current study found that patients of an acute manic episode of bipolar disorder with a high level of ANXD evaluated by the new modality of assessment of DADSI have a longer duration of the manic manifestations than the subgroup with a low level of DADSI, this is in line with studies conducted on MDD patients in which longer duration of depressive episode and longer time for remission [28, 29]. In addition, another study found that patients with MDD after 2 years of adequate antidepressants; 43.2% with a high score of ANXD examined by DADSI failed to get remission in comparison with 21.3% without this specifier [30]. On the other hand, another study concluded that no difference in the duration of depressive episodes and time of remission in patients of MDD with or without anxious distress features [31, 32].

Regarding the Young mania rating scale, the current study revealed a more severe score in the patients with the acute manic episode with high ANXD score assessed by DADSI than those without, this is in harmony with a study mentioned that patients with MDD with high anxious distress features have higher manic scores on rating scales than those without [27]. In the same vein, some studies suggested a debate that the anxious distress specifier utilized for the detection of anxiety manifestations in bipolar disorders might be a separate entity or within the continuum of bipolarity per-se [18, 33].

The current study found the attentional domain of the Barratt Impulsiveness scale (BIS) is statistically significant between the 2 subgroups (P = 0.002), this is in line with previous studies that concluded attentional and response inhibition domains of impulsivity were more affected by the presence of high anxious distress features in bipolar disorders [34, 35]. Some researchers found that acute mania was associated with impairment of both attentional and motor facets of BIS, while in depression, non-planning impulsivity was much impaired. Therefore, variable domains of impulsivity may be related to different mood states in bipolar disorders [36].

On the contrary, there was a study that noted that there was no significant difference regarding the domains of (BIS) between the bipolar patients and the healthy control group [37].

In addition, the current study found that the mean score of work and social adjustment scale (WSAS) was higher in the subgroup with high ANXD evaluated by DADSI than the subgroup without, also there was a statistically significant difference regarding the severe or worse impairment of WSAS between the studied 2 subgroups, these results are consistent with previous studies noted that patients of bipolar disorders with anxious distress features were more likely to have poor work, social and functional domains of QOL, also they were of the lower level of life and health enjoyment [38, 39]. On the contrary, another study found that QOL was not correlated to the severity of manic manifestations in general [40] but this domain is not well-studied in the presence of anxious distress specifier.

The current study revealed that the following risk factors were predictors of the acute manic episode with the presence of a high score of DADSI as a newly developed semi-structured interview for ANXD: educational level including university, higher education, frequency of DADSI, the severity of DADSI, presence of psychotic features, duration of manic episode > 30 days, moderately to severe impairment or worse psychopathology of work and social adjustment scale, and Young mania rating scale including the mild and moderate domains. All these results are in agreement with the previous studies [41,42,43].

Limitations of the study: this is a cross-sectional study, conducted in a single centre, also the evaluation was during the acute manic episode not in the follow-up period, so the results cannot be generalized, and more studies are needed for consolidations of the results. Also some patients had psychotic symptoms which accompanied by anxiety manifestations.

Strength of the study: this is one of the leading studies worldwide which investigated the role of DADSI as a recent modality of interview for evaluation of ANXD in the acute manic episode of bipolar disorders, also the role of high ANXD in symptoms severity, attitude, and insight of illness. In addition, its high score reflected a high ANXD that has impacts on the domains of QOL of those patients.

Recommendations: the current study recommended more studies on the newly added DADSI as an assessment tool of DSM-5 new specifier ANXD in the context of manic episodes of bipolar disorders in the follow-up periods, medicated patients, and with other psychiatric co-morbidities.

Conclusions

DADSI is one of the newly added semi-structured interviews for evaluation of ANXD in bipolar and related disorders; also high ANXD evaluated by DADSI influenced the clinical characteristics, symptoms severity, insight of the illness, and different domains of QOL in patients of an acute manic episode.

Availability of data and materials

The data sets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AD:

Anxiety disorder

ANXD:

Anxious distress

BD:

Bipolar disorder

BIS:

Barratt impulsiveness scale

DADSI:

The DSM-5 Anxious Distress Specifier Interview

DSM 5:

A diagnostic and statistical manual of mental disorders 5

ECT:

Electroconvulsive therapy

HAMA:

Hamilton rating scale of anxiety

ITAQ:

Insight and treatment attitude questionnaire

MDD:

Major depressive disorder

MDE:

Major depressive episode

QOL:

Quality of life

WHO:

World Health Organization

WSAS:

Work and social adjustment scale

YMRS:

Young mania rating scale

References

  1. Merikangas KR, Jin R, He JP, Kessler RC, Lee S, Sampson NA, et al. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch Gen Psychiatry. 2011;68:241–51.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Glick ID. Undiagnosed bipolar disorder: new syndromes and new treatments. Prim Care Companion J Clin Psychiatry. 2004;6:27–33.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Murray CJL, Lopez AD. Global mortality, disability, and the contribution of risk factors: global burden of disease study. Lancet. 1997;349:1436–42.

    Article  CAS  PubMed  Google Scholar 

  4. Grande I, Berk M, Birmaher B, Vieta E. Bipolar disorder. Lancet. 2016;387:1561–72.

    Article  PubMed  Google Scholar 

  5. Gonda X, Pompili M, Serafini G, Montebovi F, Campi S, Dome P, et al. Suicidal behavior in bipolar disorder: epidemiology, characteristics, and major risk factors. J Affect Disord. 2012;143:16–26.

    Article  PubMed  Google Scholar 

  6. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5). 5th ed. Washington DC: American Psychiatric Publishing; 2013. p. 168–9.

    Book  Google Scholar 

  7. Crump C, Sundquist K, Winkleby MA, Sundquist J. Comorbidities and mortality in bipolar disorder: a Swedish national cohort study. JAMA Psychiat. 2013;70:931–9.

    Article  Google Scholar 

  8. Kessler RC, Sampson NA, Berglund P, Gruber MJ, Al-Hamzawi A, Andrade L, et al. Anxious and non-anxious major depressive disorder in the World Health Organization world mental health surveys. Epidemiol Psychiatr Sci. 2015;24:210–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Seo HJ, Jung YE, Kim TS, Kim JB, Lee MS, Kim JM, et al. Distinctive clinical characteristics and suicidal tendencies of patients with anxious depression. J Nerv Ment Dis. 2011;199:42–8.

    Article  PubMed  Google Scholar 

  10. Lin CH, Wang FC, Lin SC, Chen CC, Huang CJ. A comparison of inpatients with anxious depression to those with nonanxious depression. Psychiatry Res. 2014;220:855–60.

    Article  PubMed  Google Scholar 

  11. Rhebergen D, Batelaan NM, de Graaf R, Nolen WA, Spijker J, Beekman AT, et al. The 7-year course of depression and anxiety in the general population. Acta Psychiatr Scand. 2011;123:297–306.

    Article  CAS  PubMed  Google Scholar 

  12. Fichter MM, Quadflieg N, Fischer UC, Kohlboeck G. Twenty-five year course and outcome in anxiety and depression in the Upper Bavarian longitudinal community study. Acta Psychiatr Scand. 2010;122:75–85.

    Article  CAS  PubMed  Google Scholar 

  13. Howland RH, Rush AJ, Wisniewski SR, Trivedi MH, Warden D, Fava M, et al. Concurrent anxiety and substance use disorders among outpatients with major depression: clinical features and effect on treatment outcome. Drug Alcohol Depend. 2009;99:248–60.

    Article  PubMed  Google Scholar 

  14. Papakostas GI, Larsen K. Testing anxious depression as a predictor and moderator of symptom improvement in major depressive disorder during treatment with escitalopram. Eur Arch Psychiatry Clin Neurosci. 2010;261:147–56.

    Article  PubMed  Google Scholar 

  15. Iwanami T, Maeshima H, Baba H, Satomura E, Namekawa Y, Shimano T, et al. Psychomotor agitation in major depressive disorder is a predictive factor of mood-switching. J Affect Disord. 2015;170:185–9.

    Article  PubMed  Google Scholar 

  16. Krishnan KR. Psychiatric and medical comorbidities of bipolar disorder. Psychosom Med. 2005;67:1–8.

    Article  PubMed  Google Scholar 

  17. Merikangas KR, Akiskal HS, Angst J, Greenberg PE, Hirschfeld RM, Petukhova M, et al. Lifetime and 12-month prevalence of bipolar spectrum disorder in the national comorbidity survey replication. Arch Gen Psychiatry. 2007;64:543–52.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Spoorthy MS, Chakrabarti S, Grover S. Comorbidity of bipolar and anxiety disorders: an overview of trends in research. World J Psychiatry. 2019;9:7–29.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Zimmerman M, Clark H, McGonigal P, Harris L, Holst CG, Martin J. Reliability and validity of the DSM-5 anxious distress specifier interview. Compr Psychiatry. 2017;76:11–7.

    Article  PubMed  Google Scholar 

  20. Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: reliability, validity, and sensitivity. Br J Psychiatry. 1978;133:429–35.

    Article  CAS  PubMed  Google Scholar 

  21. Patton JH, Stanford MS, Barratt ES. Factor structure of the Barratt impulsiveness scale. J Clin Psychol. 1995;5:768–74.

    Article  Google Scholar 

  22. Tsatali M, Moraitou D, Papantoniou G, Foutsitzi E, Bonti E, Kougioumtzis G, Ntritsos G, Sofologi M, Tsolaki M. Measuring impulsivity in Greek adults: psychometric properties of the Barratt impulsiveness scale (BIS-11) and impulsive behavior scale (short version of UPPS-P). Brain Sci. 2021;11(8):1007.

    Article  PubMed  PubMed Central  Google Scholar 

  23. McEvoy JP, Apperson LJ, Appelbaum PS, Ortlip P, Brecosky J, Hammill K, et al. Insight in schizophrenia its relationship to acute psychopathology. J Nerv Ment Dis. 1989;177(1):43–7.

    Article  CAS  PubMed  Google Scholar 

  24. Mundt JC, Marks IM, Shear MK, Greist JH. The work and social adjustment scale: a simple measure of impairment in functioning. Br J Psychiatry. 2002;180:461–4.

    Article  PubMed  Google Scholar 

  25. Gaspersz R, Lamers F, Kent JM, Beekman AT, Smit JH, van Hemert AM, et al. Longitudinal predictive validity of the DSM-5 anxious distress specifier for clinical outcomes in a large cohort of patients with major depressive disorder. J Clin Psychiatry. 2017;78:207–13.

    Article  PubMed  Google Scholar 

  26. McIntyre RS, Woldeyohannes HO, Soczynska JK, Vinberg M, Cha DS, Lee Y, et al. The prevalence and clinical characteristics associated with diagnostic and statistical manual version-5-defined anxious distress specifier in adults with major depressive disorder: results from the international mood disorders collaborative project. Ther Adv Chronic Dis. 2016;7:153–9.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Tundo A, Musetti L, de Filippis R, Grande CD, Falaschi V, Proietti L, et al. Is there a relationship between depression with anxious distress DSM-5 specifier and bipolarity? A multi-center cohort study on patients with unipolar, bipolar I, and II disorders. J Affect Disord. 2019;245:819–26.

    Article  PubMed  Google Scholar 

  28. Wiethoff K, Bauer M, Baghai TC, Möller HJ, Fisher R, Hollinde D, et al. Prevalence and treatment outcome in anxious versus nonanxious depression: results from the German algorithm project. J Clin Psychiatry. 2010;71:1047–54.

    Article  PubMed  Google Scholar 

  29. Romera I, Pérez V, Ciudad A, Caballero L, Roca M, Polavieja P, et al. Residual symptoms and functioning in depression, does the type of residual symptom matter? A post hoc analysis. BMC Psychiatry. 2013;11:13–51.

    Google Scholar 

  30. Chan RC, Xu T, Huang J, Wang Y, Zhao Q, Shum DH, et al. Extending the utility of the depression anxiety stress scale by examining its psychometric properties in Chinese settings. Psychiatry Res. 2012;200:879–83.

    Article  PubMed  Google Scholar 

  31. Chan HN, Rush AJ, Nierenberg AA, Trivedi M, Wisniewski SR, Balasubramani GK, et al. Correlates and outcomes of depressed out-patients with greater and fewer anxious symptoms: a CO-MED report. Int J Neuropsychopharmacol. 2012;15:1387–99.

    Article  CAS  PubMed  Google Scholar 

  32. Titone MK, Freed RD, O’Garro-Moore JK, Gepty A, Ng TH, Stange JP, et al. The role of lifetime anxiety history in the course of bipolar spectrum disorders. Psychiatry Res. 2018;264:202–9.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Gitlin MJ, Miklowitz DJ. The difficult lives of individuals with bipolar disorder: a review of functional outcomes and their implications for treatment. J Affect Disord. 2017;209:147–54.

    Article  PubMed  Google Scholar 

  34. Çörekçioğlu S, Cesur E, Devrim BÖ. Relationship between impulsivity, comorbid anxiety and neurocognitive functions in bipolar disorder. Int J Psychiatry Clin Pract. 2021;25:62–72.

    Article  PubMed  Google Scholar 

  35. Ramírez-Martín A, Ramos-Martín J, Mayoral-Cleries F, Moreno-Küstner B, Guzman-Parra J. Impulsivity, decision-making and risk-taking behavior in bipolar disorder: a systematic review and meta-analysis. Psychol Med. 2020;50:2141–53.

    Article  PubMed  Google Scholar 

  36. Okasha TA, El Sheikh MM, El Missiry AA, El Missiry MA, El Serafi D, El Kholy S, et al. Cognitive functions in euthymic Egyptian patients with bipolar disorder: are they different from healthy controls? J Affect Disord. 2014;166:14–21.

    Article  PubMed  Google Scholar 

  37. Wessa M, Kollmann B, Linke J, Schönfelder S, Kanske P. Increased impulsivity as a vulnerability marker for bipolar disorder: evidence from self-report and experimental measures in two high-risk populations. J Affect Disord. 2015;178:18–24.

    Article  PubMed  Google Scholar 

  38. Echezarraga A, Las Hayas C, Calvete E, González-Pinto M, Jones S. Resilience process in bipolar disorder from the views of patients and health professionals. Revista Argentina de Clinica Psicológica. 2019;28:794–807.

    Google Scholar 

  39. Maneeton N, Suttajit S, Maneeton B, Likhitsathian S, Eurviyanukul K, Udomratn P, et al. Clinical and socio-demographic correlates of anxious distress in Asian outpatients with major depressive disorder. Nord J Psychiatry. 2017;71:503–8.

    Article  PubMed  Google Scholar 

  40. Gazalle FK, Hallal PC, Andreazza AC, Frey BN, Kauer-Sant’Anna M, Weyne F, et al. Manic symptoms and quality of life in bipolar disorder. Psychiatry Res. 2007;153:33–8.

    Article  PubMed  Google Scholar 

  41. Lex C, Bazner E, Meyer TD. Does stress play a significant role in bipolar disorder? A meta-analysis. J Affect Disord. 2017;208:298–308.

    Article  PubMed  Google Scholar 

  42. Koenders MA, Giltay EJ, Spijker AT, Hoencamp E, Spinhoven P, Elzinga BM. Stressful life events in bipolar I and II disorder: cause or consequence of mood symptoms? J Affect Disord. 2014;161:55–64.

    Article  CAS  PubMed  Google Scholar 

  43. Faedda GL, Serra G, Marangoni C, Salvatore P, Sani G, Vázquez GH, et al. Clinical risk factors for bipolar disorders: a systematic review of prospective studies. J Affect Disord. 2014;168:314–21.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

None.

Author information

Authors and Affiliations

  1. Department of Psychiatry, Faculty of Medicine, Mansoura University, Mansoura, 35516, Egypt

    Samir El Sayed, Hassan Sonbol & Ibrahem ElKalla

  2. Department of Psychiatry, Mansoura Students’ Hospital, Mansoura University, Mansoura, Egypt

    Sarah Gomaa

  3. Hayat National Hospital, Riyadh, Kingdom of Saudi Arabia

    Alaa Al Hazmi

  4. Department of Psychiatry, Hayat National Hospital, Riyadh, Kingdom of Saudi Arabia

    Samir El Sayed

  5. Department of Psychiatry, Eradaa Mental Complex, Riyadh, Kingdom of Saudi Arabia

    Sarah Gomaa

Authors
  1. Samir El Sayed
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sarah Gomaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alaa Al Hazmi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hassan Sonbol
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ibrahem ElKalla
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SES: conceptualization, interview the patients, evaluation, conceptualization, prepare the manuscript, also he is the corresponding author. SG: share in writing the manuscript, revise the manuscript, conceptualization, AAH: share in interviewing the patients. HS: conceptualization, share in the writing the manuscript. IE: revise the manuscript, data analysis. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Samir El Sayed.

Ethics declarations

Ethics approval and consent to participate

Ethical approval from local ethical committee of Hayat National Hospital, Riyadh, KSA was obtained before conducting the study (IRB, HNH: R.20.07.354). All the steps of the study were in agreement with Declaration of Helsinki and its later amendments (2013). Informed consent obtained from all participants after explanation of the aim of the study. Participants were confirmed about the confidentiality of the information gathered and that they have the right to withdraw or refuse at any time without giving reasons.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

El Sayed, S., Gomaa, S., Al Hazmi, A. et al. Role of DSM5 anxious distress specifier interview in acute manic episode: sociodemographic characteristics, clinical presentation and quality of life. Egypt J Neurol Psychiatry Neurosurg 59, 33 (2023). https://doi.org/10.1186/s41983-023-00634-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s41983-023-00634-6

Keywords