Skip to main content

Symptom continuum reported by affective disorder patients through a structure-validated questionnaire



Affective disorders, such as major depressive (MDD), bipolar I (BD I) and II (BD II) disorders, are overlapped at a continuum, but their exact loci are not clear. The self-reports from patients with affective disorders might help to clarify this issue.


We invited 738 healthy volunteers, 207 individuals with BD I, 265 BD II, and 192 MDD to answer a 79 item-MATRIX about on-going affective states.


In study 1, all 1402 participants were divided random-evenly and gender-balanced into two subsamples; one subsample was used for exploratory factor analysis, and another for confirmatory factor analysis. A structure-validated inventory with six domains of Overactivation, Psychomotor Acceleration, Distraction/ Impulsivity, Hopelessness, Retardation, and Suicide Tendency, was developed. In study 2, among the four groups, MDD scored the highest on Retardation, Hopelessness and Suicide Tendency, whereas BD I on Distraction/ Impulsivity and Overactivation.


Our patients confirmed the affective continuum from Suicide Tendency to Overactivation, and described the different loci of MDD, BD I and BD II on this continuum.

Peer Review reports


According to current diagnostic documentation, mood disorders are largely composed of bipolar and related disorders and depressive disorders [1, 2]. Bipolar disorder has two main subtypes, i.e., I (BD I) and II (BD II). These two subtypes are different from major depressive disorder (MDD), but their clinical symptoms are mutually overlapping [3]. Therefore, they are considered to sit separately on a continuum of mood states [4], and are difficult to be separated from each other, especially between BD I and BD II. For instance, BD I is characterized by a high prevalence of reckless behavior, distractibility, psychomotor agitation, irritability and increased self-esteem [5], whereas BD II by more severe and persistent depression [6, 7] as well as more frequent and longer episodes of depression [8, 9]. Some patients, previously diagnosed as having major depressive disorders, might qualify for a bipolar disorder diagnosis [10].

In clinics, bipolar disorder usually starts with depressive episodes rather than mania or hypomania. Considering the fact that consecutive hypomanic episodes tend to be short-lived, less severe, and less socially impaired, they are difficult to differentiate from normal mood changes. Thus, bipolar disorder is often misdiagnosed as MDD [11]. Scholars also have noted that the severity of mania and depression symptoms of BD II differ from that of BD I and MDD [12]. Since hypomania has less prominent and milder symptoms, with little impact on life, work, study and interpersonal communication, it is a difficult condition to diagnose, and is easily overlooked. Indeed, the misdiagnoses can lead to ineffective treatment and increase suicide risks of affective disorder patients [13]. For example, antidepressants have little or no efficacy for depressive episodes associated with bipolar disorder [3], and might lead to phase inversion, rapid cycling state, or mixed seizures, which might worsen the condition of bipolar disorder [14]. In addition, medication or other non-pharmacologic therapies available to treat BD I and BD II are not optimally effective and their effects vary between the subtypes [15, 16].

Although the continuum hypothesis of mood symptoms fits into the clinical diagnoses of affective disorders [17], the accurate loci or segments each disorder occupies, and the mood transition or dynamic changes along of the continuum are still unclear. The accurate clinical diagnosis of an affective disorder requires trained professionals with experience and knowledge, which might be inconsistent across professionals in clinical practices, to some degree that individual description of patients might be neglected. On the other hand, symptoms reported by patients using a structure-validated symptom modeling are limited. Most symptom studies, however, were from the hospital-based medical records and professional physician interviews in clinics [3]. The self-reported questionnaire, which can be easily implemented to large samples, is an effective and straightforward method to assess many diseases and explore constructs that might be difficult to acquire through behavioral or physiological measures. Up to present, there are few studies adopting both exploratory and confirmatory factor analyses to present a structure-validated modeling to assess the symptoms of BD I, BD II and MDD, which covers all mania, hypomania and depression in a single design.

Based on previous studies [17], we hypothesize that mania, hypomania, and depression are continuous spectrum from high to low, independent at the same time, and BD I, BD II, and MDD relatively have specific components. We then developed an item-MATRIX measuring the mood symptoms according to diagnostic criteria [1, 2] and the commonly clinical-used questionnaires for depressive and bipolar-related disorders. The item examples we adopted for mania were similar to “I have much more energy than usual”, “I am much more talkative or speak faster than usual” [18], and “I need much less sleep than usual” [19]; those for hypomania were similar to “I am more self-confident”, “My thoughts jump from topic to topic” [20], “I can be exhausting or irritating for others”, and “I am more easily distracted” [19]; and those for depression were similar to “I feel worthless”, “I am making plans to commit suicide” [21], “I find it difficult to make up my mind”, and “I get tired for no reason” [22]. In order to obtain enough the item response variation, the item-MATRIX was tested in both healthy volunteers and patients with affective disorders. Two purposes of the present study were (1) to obtain a structure-validated emotional-symptom questionnaire from the item-MATRIX (Study 1), and (2) to look for the different loci or segments of emotional symptoms mostly associated with BD I, BD II and MDD through self-reports of patients (Study 2).



We altogether invited 1600 participants, some of whom (mostly the volunteer-controls) were excluded after a semi-structured interview or a clinical assessment (see below). Finally this investigation was carried out on 1402 participants: 738 healthy volunteers, and 207 patients with BD I, 265 BD II and 192 MDD; their demographic and grouping information are given in Table 1. The semi-structured interview was performed with each healthy participant to ensure that they were not suffering from any psychiatric or neurological problems. All patients were diagnosed by an experienced psychiatrist (WW) according to Diagnostic Criteria of American Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) [1], were beyond their first-episode, and were confirmed to have no other psychiatric co-morbid conditions, such as schizophrenia, schizoaffective disorder, substance use disorder, eating disorder, etc. All participants were free from any drug or alcohol abuse for at least 72 h prior to the test. In addition, two coauthors were presenting onsite to aid in the proper filling of the informed consent, demographic information, and MATRIX (see below), and to guarantee corrective feedbacks. Our study design was approved by a local Ethics Committee, and all participants were informed and gave written consents to participate.

Table 1 Demographic and grouping information of healthy volunteers (Controls), patients with bipolar I (BD I), II (BD II) and major depressive (MDD) disorders

For Study 1, 1402 participants were divided into two subsamples (n = 701 each), there was no age (One-way ANOVA, subsample 1: F[3697] = 2.512, p = .06, MSE = 90.87; subsample 2: F[3.697] = 1.046, p = .37, MSE = 32.46) or gender (the Pearson Chi-square test with Yates’ correction, subsample 1: χ2 = 4.03, p = .26; subsample 2: χ2 = 3.43, p = .33) differences among the two subsamples. For Study 2, which were based on the participants of Study 1, there was no significant age (one-way ANOVA, F[3, 1398] = 2.45, p = .06, MSE = 84.81) or gender (the Pearson Chi-square test with Yates’ correction, χ2 = 7.52, p = .06) difference among the four groups either.


All participants were asked to complete the 79 MATRIX items in Chinese in a quiet room. Considering the less compliance of an individual during mania or depression, we asked participants to use simpler answer-styles of the force-choice (0 - no, 1 - yes) for some items or the Likert scale (0 - no, 1 - sometimes, 2 - most of the time) for other items, corresponding to their intensity of the on-going affective state of either depression, hypomania or mania.

Statistical analysis

In Study 1, the answers to the 79 items from the first subsample were submitted to a principal component analysis, using SPSS Version 18.0.0 (SPSS Inc., 2009, Chicago, IL). The factor model fits were evaluated by the confirmatory factor analysis using AMOS version 17.0 (AMOS Development Corp., 2008, Crawfordville, FL) in the second subsample. The criteria for factor loadings and cross-loadings, and for selecting model fit parameters were kept consistent with a previous study [23]. When the optimal model fit was established, the factor structure of the questionnaire was developed. The internal reliability (Coefficient H) of each scale was then calculated. After both exploratory and confirmatory factor analyses, the structure-validated factor structure was formed, and a questionnaire was developed.

In Study 2, the questionnaire developed in Study 1 were tested in groups of BD I, BD II, MDD and healthy controls on one hand, using two-way ANOVA (i.e., Group (4) × Scale (6)); and also tested in groups of different mood states of mania, hypomania, bipolar depression, major depression and healthy controls on the other hand, using two-way ANOVA (i.e., Group (5) × Scale (6)). The post-hoc analysis by the Least Significant Difference test was employed to evaluate between-group differences and to estimate the effect size (Cohen’s d) for difference. A p value less than .05 was considered to be significant.


Study 1: Factor structure development

The principal component analysis extracted 10 factors with eigenvalues larger than 1.0. The screen plot and parallel analysis results suggested a six-factor solution, and the first six factors accounted for 49.40% of the total variance. Deleting items with loadings lower than .40 or with significant cross-loadings higher than .35 on other non-target factors, we constructed a fit modeling, with 37 items which were distributed in the six factors (for the sake of brevity, loading information of all 79 items is presented as a supplementary material). In addition, the structural equation modeling (Fig. 1) confirmed that the six-factor modeling was a suitable solution (χ2/df = 2.86, the goodness of fit index = .88, the adjusted goodness of fit index = .86, the comparative fit index = .87, the Tucker-Lewis index = .86, the root mean square error of approximation = .052, and the standardized root mean square residual = .064).

Fig. 1
figure 1

Standardized six-factor structure in 701 participants

The first factor with 8 items, e.g., “I am more self-confident”, and “My mood is higher and more optimistic”, reflects high spirits or active thoughts subjectively, thus was named “Psychomotor Acceleration” (internal reliability of .88). The second factor with 6 items, e.g., “I feel sad” and “I find it difficult to make up my mind”, narrates the characteristics of depression, including sorrow, self-accusation, hesitation, etc., “Hopelessness” (internal reliability, .85). The third factor with 5 items, e.g., “I think about committing suicide”, and “I am making plans to commit suicide”, describes the thoughts and behavior of suicide, “Suicide Tendency” (internal reliability, .87). The fourth factor with 6 items, e.g., “I have much more energy than usual” and “I am much more talkative or speak faster than usual”, describes the characteristics of increase of targeted behaviors and speaking, agitated mental activity, and tendency to high-risk activities, “Overactivity” (internal reliability, .81). The fifth factor with 6 items, e.g., “I speak less”, and “The speed at which I do things is lower”, represents lack of motivation for speaking and acting, “Retardation” (internal reliability, .84). The six factor with 7 items, e.g., “I am more easily distracted” and “I take more risks in my daily life”, is a mixture of distraction, anxiety and impulsion descriptions, “Distraction/ Impulsivity” (internal reliability, .74) (Table 2).

Table 2 Factor loadings on the six factors in 701 participants

Study 2: Factor structure application

The mean scores of the six factors were significantly different between four groups of BD I, BD II, MDD and healthy controls (main effect, F[3,1398] = 498.74, p < .001, MSE = 1618.52; scale effect, F[5,1396] = 1026.05, p < .001, MSE = 3329.78; group × scale interaction effect, F[15,1386] = 176.76, p < .001, MSE = 573.63). There were significant between-group differences between the four groups on all factors (Psychomotor Acceleration: F[3,1398] = 150.11, p < .001, MSE = 636.61; Hopelessness: F[3,1398] = 338.86, p < .001, MSE = 1867.08; Suicide Tendency: F[3,1398] = 141.46, p < .001, MSE = 255.36; Overactivity: F[3,1398] = 345.36, p < .001, MSE = 581.15; Retardation: F[3,1398] = 193.39, p < .001, MSE = 670.38; Distraction/ Impulsivity: F[3,1398] = 163.78, p < .001, MSE = 373.41). Post-hoc tests showed that the scale scores of Hopelessness, Suicide Tendency and Retardation were significantly higher in MDD than other groups, followed by BD II; BD I showed highest scores on Overactivation and Distraction/ Impulsivity. Both BD I and BD II presented high scores on Psychomotor Acceleration, while BD II and MDD showed low scores in Overactivation (Table 3).

Table 3 Scale scores (mean ± S.D.) of the six factors in healthy volunteers (controls, n = 738), bipolar I (n = 207), bipolar II (n = 265) and major depressive (n = 192) disorder patients

When different affective states were considered, the mean scores of the six factors were significantly different between groups of mania, hypomania, bipolar depression, MDD and healthy controls (main effect, F[4,1397] = 352.05, p < .001, MSE = 1215.40; scale effect, F[5,1396] = 593.03, p < .001, MSE = 2047.37; group × scale interaction effect, F[20,1381] = 99.67, p < .001, MSE = 344.09). There were significant between-group differences among different groups on all factors (Psychomotor Acceleration: F[4,1397] = 112.53, p < .001, MSE = 477.56; Hopelessness: F[4,1397] = 219.66, p < .001, MSE = 1284.18; Suicide Tendency: F[4,1397] = 99.69, p < .001, MSE = 182.63; Overactivity: F[4,1397] = 95.29, p < .001, MSE = 219.49; Retardation: F[4,1397] = 124.79, p < .001, MSE = 531.88. Distraction/ Impulsivity: F[4,1397] = 107.84, p < .001, MSE = 240.10). Post-hoc tests also showed that patients during mania state scored higher on overactivity, while patients during depression scored higher on Hopelessness and Suicidal Tendency (Table 4).

Table 4 Scale scores (mean ± S.D.) of the six factors in healthy volunteers (controls, n = 738), patients in manic (n = 45), hypomanic (n = 111), bipolar depressive (n = 316), and major depressive (n = 192) states


After both exploratory and confirmatory factor analyses on self-reports, we have developed a fit modeling, with 37 items which were distributed in the six factors (Study 1). These factors were located in a continuum from high to low end of the emotional states: Overactivation, Psychomotor Acceleration, Distraction/ Impulsivity, Hopelessness, Retardation, and Suicide Tendency, which supports our first hypothesis. Keeping up with our second hypothesis, patients with BD I, BD II and MDD described themselves differently when referring to the loci or segments of the continuum they occupied (Study 2, Fig. 2), which were supported by results from different affective states as well.

Fig. 2
figure 2

Locations of affective symptom of major depressive, bipolar I and II disorders along a continuum

The first factor, Psychomotor Acceleration, refers to the increased intensity of emotion which is often used to characterize mania and hypomania, as described in hypomanic state previously [9]. Both BD I and BD II patients exhibited similar emotional symptoms, such as psychomotor agitation and strong self-esteem [9, 24]. The fourth factor, Overactivation, describes manic and hypomanic thoughts and behaviors, as previously described in manic state [25]. BD I, instead of BD II, scored highest among all the four groups, showing that BD I patients have more prominent agitated and excited states [5, 26]. MDD patients, however, scored lowest on both Psychomotor Acceleration and Overactivation [3]. One group of scholars also have suggested that, apart from psychotic symptoms, manic and hypomanic episodes have the same symptom profile and differ only in the degree of severity. Studies have reported that manic episodes exhibit a broader spectrum of symptoms [26]. In addition, many scholars have found a prominent mood characteristic to be “elated mood” in BD II compared to similar rates of “elated mood” and “irritable mood” in BD I [9].

The second factor, Hopelessness, describes the loss of incentives, low self-worth, and sad emotions, in thoughts (cognition), as previously described in depression [27, 28]. In terms of scores of the Hopelessness, MDD, BD II, and BD I had diminished scores, which were significantly different from each other, with MDD the lowest. The results were in accordance with previous results in these patients [29, 30]. The fifth factor, Retardation, refers to slow-down behavior, amotivation, in daily activities, also as previously described in depression [31]. It describes the features of lack of motivation, as previously reported in depressive state [32, 33], found to be prominent in our MDD and BD II. Former studies have declared that BD II patients experienced major depressive episodes more frequently than those with BD I [34]. Sub-syndromal depressive episodes, which do not fully meet the criteria for major depressive episode but may contribute to a decline in occupational and social outcome, have also been reported more in BD II [35,36,37].

The third factor, Suicide Tendency, describes the thoughts and plans to commit suicide which has been reported widely in depressive state [38,39,40]. In our Study 2, MDD scored highest on this domain, followed by BD II and BD I. Previous studies have shown that the disability rates of major depressive and bipolar disorder patients ranked first and second, respectively, around the world [41]. The reasons were mostly related to suicide ideation and behavior, which often occurred in severe depression state or mixed states [42], often found in BD II [9, 43, 44]. Our findings on the highest suicide ideation scores in MDD group might be attributed to the fact that, all MDD patients were currently depressed, only 60% BD II and 80% BD I patients, were in depressed phase.

The sixth factor, Distraction/Impulsivity, describes the less-calmed or dysfunctional attention states, as previously documented in affective disorders [30, 45, 46]. For instance, a 2-year follow-up study has shown that attention is one of the cognitive domains that are persistently affected in bipolar disorder patients, and the deficits seem stable and are not worse over time [47]. The inattention symptom was predictive of change in depression severity over the course of treatment and overall treatment outcome as well [48]. On the other hand, depressive disorder [45, 49, 50] and bipolar disorder patients have displayed high levels of impulsivity [51, 52] and aggressiveness [53] no matter during manic episodes, depressive episodes, or remission stages, and the impulsivity level has been lowered in bipolar disorder patients after efficient treatments [54].

However, there were at least three design limitations of our current investigation. Firstly, we excluded items measuring substance-abuse and delusion, which are the two main features of mania, and other disease-controls such as substance misuse disorder or schizophrenia would be useful additions. Secondly, we recorded neither normal nor disordered personality traits in our participants, as they might also be related to emotional states. Thirdly, our design was cross-sectional, which addressed only the concurrent affective states of each participant. A longitudinal design of emotional measurement, especially in BD I and BD II, and from their first episode on, would be more informative to construct a dynamic model of affective disorders, and distinguish state vs. trait features.


Through self-reports, we have demonstrated a structure-validated measure of emotional state, with 6 domains (37 items) in a continuum, from high to low end, namely Overactivation, Psychomotor Acceleration, Distraction/ Impulsivity, Hopelessness, Retardation, and Suicide Tendency. Patients with BD I, BD II and MDD scored differently from each other along the continuum (Fig. 2). Although our study has not provided the pictures of affective-state transition within the affective disorders, it has demonstrated the existence of and relationship between individual affective disorders.

Availability of data and materials

All data generated or analyzed during this study are available from the corresponding author on reasonable request.



Major depressive disorder


Bipolar I disorder


Bipolar II disorder


Diagnostic Criteria of American Diagnostic and Statistical Manual of Mental Disorders


Predictive analytics software statistics


Analysis of moment structures


  1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington: VA American Psychiatric Publishing; 2013.

    Book  Google Scholar 

  2. World Health Organization. International classification of diseases, 11th revision (ICD-11). Geneva: WHO; 2017.

    Google Scholar 

  3. Hirschfeld RM. Differential diagnosis of bipolar disorder and major depressive disorder. J Affect Disord. 2014;169:S12–6.

    Article  PubMed  Google Scholar 

  4. Mitchell PB, Wilhelm K, Parker G, Austin MP, Rutgers P, Malhi GS. The clinical features of bipolar depression: a comparison with matched major depressive disorder patients. J Clin Psychiatry. 2001;62:212–6.

    Article  CAS  PubMed  Google Scholar 

  5. Serretti A, Olgiati P. Profiles of “manic” symptoms in bipolar I, bipolar II and major depressive disorders. J Affect Disord. 2005;84:159–66.

    Article  PubMed  Google Scholar 

  6. Benazzi F. Prevalence and clinical correlates of residual depressive symptoms in bipolar II disorder. Psychother Psychosom. 2001;70:232–8.

    Article  CAS  PubMed  Google Scholar 

  7. Benazzi F, Bipolar II. Disorder: epidemiology, diagnosis and management. CNS Drugs. 2007;21:727–40.

    Article  CAS  PubMed  Google Scholar 

  8. Judd LL, Akiskal HS, Schettler PJ, et al. The comparative clinical phenotype and long term longitudinal episode course of bipolar I and II: a clinical spectrum or distinct disorders? J Affect Disord. 2003;73:19–32.

    Article  PubMed  Google Scholar 

  9. Baek JH, Park DY, Choi J, et al. Differences between bipolar I and bipolar II disorders in clinical features, comorbidity, and family history. J Affect Disord. 2011;131:59–67.

    Article  PubMed  Google Scholar 

  10. Smith DJ, Craddock N. Unipolar and bipolar depression: different or the same? Br J Psychiatry. 2011;199:272–4.

    Article  PubMed  Google Scholar 

  11. Merikangas KR, Jin R, He J, 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 

  12. Ghaemi SN, Ko JY, Goodwin FK. “Cade’s disease” and beyond: misdiagnosis, antidepressant use, and a proposed definition for bipolar spectrum disorder. Can J Psychiatr. 2002;47:125–34.

    Article  Google Scholar 

  13. Dunner DL. Clinical consequences of under-recognized bipolar spectrum disorder. Bipolar Disord. 2003;5:456–63.

    Article  PubMed  Google Scholar 

  14. Tansey KE, Guipponi M, Domenici E, et al. Genetic susceptibility for bipolar disorder and response to antidepressants in major depressive disorder. Am J Med Genet B Neuropsychiatr Genet. 2014;165:77–83.

    Article  Google Scholar 

  15. Medda P, Perugi G, Zanello S, Ciuffa M, Cassano GB. Response to ECT in bipolar I, bipolar II and unipolar depression. J Affect Disord. 2009;118:55–9.

    Article  CAS  PubMed  Google Scholar 

  16. Tondo L, Baldessarini RJ, Vázquez G, Lepri B, Visioli C. Clinical responses to antidepressants among 1036 acutely depressed patients with bipolar or unipolar major affective disorders. Acta Psychiatr Scand. 2013;127:355–64.

    Article  CAS  PubMed  Google Scholar 

  17. Akiskal HS. Dysthymia: clinical and external validity. Acta Psychiatr Scand. 1994;89:19–23.

    Article  Google Scholar 

  18. Hirschfeld RMA, Williams JBW, Spitzer RL, et al. Development and validation of a screening instrument for bipolar spectrum disorder: the mood disorder questionnaire. Am J Psychiatr. 2000;157:1873–5.

    Article  CAS  PubMed  Google Scholar 

  19. 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 

  20. Angst J, Adolfsson R, Benazzi F, et al. The HCL-32: towards a self-assessment tool for hypomanic symptoms in outpatients. J Affect Disord. 2005;88:217–33.

    Article  PubMed  Google Scholar 

  21. Plutchik R, Plutchik R, Van Praag HM, van Praag HM. Interconvertability of five self-report measures of depression. Psychiatry Res. 1987;22:243–56.

    Article  CAS  PubMed  Google Scholar 

  22. Zung WW. A self-rating depression scale. Arch Gen Psychiatry. 1965;12:63–70.

    Article  CAS  PubMed  Google Scholar 

  23. Wang JW, Zhang BR, Shen CC, Zhang JH, Wang W. Headache symptoms from migraine patients with and without aura through structure-validated self-reports. BMC Neurol. 2017;17:193.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Grande I, Berk M, Birmaher B, Vieta E. Bipolar disorder. Lancet. 2015;387:1561–72.

    Article  PubMed  Google Scholar 

  25. Scott J, Murray G, Henry C, et al. Activation in bipolar disorders: a systematic review. JAMA Psychiatry. 2017;74:189–96.

    Article  PubMed  Google Scholar 

  26. Angst J, Meyer TD, Adolfsson R, et al. Hypomania: a transcultural perspective. World Psychiatry. 2010;9:41–9.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Uher R, Payne JL, Pavlova B, Perlis RH. Major depressive disorder in DSM-5: implications for clinical practice and research of changes from DSM-IV. Depress Anxiety. 2014;31:459–71.

    Article  PubMed  Google Scholar 

  28. Joormann J, Stanton CH. Examining emotion regulation in depression: a review and future directions. Behav Res Ther. 2016;86:35–49.

    Article  PubMed  Google Scholar 

  29. Hanson B, Young MA. Why depressive symptoms cause distress: the clients’ perspective. J Clin Psychol. 2012;68:860–74.

    Article  PubMed  Google Scholar 

  30. Dervic K, Garcia-Amador M, Sudol K, et al. Bipolar I and II versus unipolar depression: clinical differences and impulsivity/aggression traits. Eur Psychiatry. 2014;30:106–13.

    Article  PubMed  Google Scholar 

  31. Fried EI, Nesse RM. The impact of individual depressive symptoms on impairment of psychosocial functioning. PLoS One. 2014;9:e90311.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Mauras T, Masson M, Fossati P, Pessiglione M. Incentive sensitivity as a behavioral marker of clinical remission from major depressive episode. J Clin Psychiatry. 2016;77:e697–703.

    Article  PubMed  Google Scholar 

  33. Dickson JM, Johnson S, Huntley CD, Peckham A, Taylor PJ. An integrative study of motivation and goal regulation processes in subclinical anxiety, depression and hypomania. Psychiatry Res. 2017;256:6–12.

    Article  PubMed  Google Scholar 

  34. Mantere O, Suominen K, Valtonen HM, et al. Differences in outcome of DSM-IV bipolar I and II disorders. Bipolar Disord. 2008;10:413–25.

    Article  PubMed  Google Scholar 

  35. Vieta E, De Arce R, Jiménez-Arriero MA, et al. Detection of subclinical depression in bipolar disorder: a cross-sectional, 4-month prospective follow-up study at community mental health services (SIN-DEPRES). J Clin Psychiatry. 2010;71:1465–74.

    Article  PubMed  Google Scholar 

  36. Kim S, Yu BH, Lee DS, Kim J. Ruminative response in clinical patients with major depressive disorder, bipolar disorder, and anxiety disorders. J Affect Disord. 2012;136:e77–81.

    Article  PubMed  Google Scholar 

  37. Tondo L, Vazquez GH, Baldessarini RJ. Depression and mania in bipolar disorder. Curr Neuropharmacol. 2017;2016(15):353–8.

    Article  Google Scholar 

  38. Harwood D, Hawton K, Hope T, Jacoby R. Psychiatric disorder and personality factors associated with suicide in older people: a descriptive and case-control study. Int J Geriatr Psychiatry. 2001;16:155–65.

    Article  CAS  PubMed  Google Scholar 

  39. Mitchell PB, Malhi GS. Bipolar depression: phenomenological overview and clinical characteristics. Bipolar Disord. 2004;6:530–9.

    Article  PubMed  Google Scholar 

  40. Chesney E, Goodwin GM, Fazel S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry. 2014;13:153–60.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Cerimele JM, Chwastiak, Lydia A, Dodson S, Katon WJ. The prevalence of bipolar disorder in general primary care samples: a systematic review. Gen Hosp Psychiatry. 2014;36:19–25.

    Article  PubMed  Google Scholar 

  42. Isometsä E. Suicidal behaviour in mood disorders—who, when, and why? Can J Psychiatr. 2014;59:120–30.

    Article  Google Scholar 

  43. Rihmer Z, Pestality P. Bipolar II disorder and suicidal behavior. Psychiatr Clin N Am. 1999;22:667–73.

    Article  CAS  Google Scholar 

  44. Valtonen H, Suominen K, Mantere O, Leppämäki S, Arvilommi P, Isometsä ET. Suicidal ideation and attempts in bipolar I and II disorders. J Clin Psychiatry. 2005;66:1456–62.

    Article  PubMed  Google Scholar 

  45. Strong CM, Nowakowska C, Santosa CM, Wang PW, Kraemer HC, Ketter TA. Temperament–creativity relationships in mood disorder patients, healthy controls and highly creative individuals. J Affect Disord. 2007;100:41–8.

    Article  PubMed  Google Scholar 

  46. Yao J, Xu Y, Qin Y, et al. Relationship between personality disorder functioning styles and the emotional states in bipolar i and II disorders. PLoS One. 2015;10:e0117353.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Mur M, Portella MJ, Martinez-Aran A, Pifarre J, Vieta E. Neuropsychological profile in bipolar disorder: a preliminary study of monotherapy lithium-treated euthymic bipolar patients evaluated at a 2-year interval. Acta Psychiatr Scand. 2008;118:373–81.

    Article  CAS  PubMed  Google Scholar 

  48. Bagby RM, Rector NA, Segal ZV, et al. Rumination and distraction in major depression: assessing response to pharmacological treatment. J Affect Disord. 1999;55:225–9.

    Article  CAS  PubMed  Google Scholar 

  49. Saddichha S, Schuetz C. Impulsivity in remitted depression: a meta-analytical review. Asian J Psychiatr. 2014;9:13–6.

    Article  PubMed  Google Scholar 

  50. Perugi G, Perugi G, Angst J, et al. Mixed features in patients with a major depressive episode: the BRIDGE-II-MIX study. J Clin Psychiatry. 2015;76:e351–8.

    Article  PubMed  Google Scholar 

  51. Peluso MAM, Hatch JP, Glahn DC, et al. Trait impulsivity in patients with mood disorders. J Affect Disord. 2007;100:227–31.

    Article  CAS  PubMed  Google Scholar 

  52. Ekinci O, Albayrak Y, Ekinci AE, Caykoylu A. Relationship of trait impulsivity with clinical presentation in euthymic bipolar disorder patients. Psychiatry Res. 2011;190:259–64.

    Article  PubMed  Google Scholar 

  53. Perroud N, Baud P, Mouthon D, Courtet P, Malafosse A. Impulsivity, aggression and suicidal behavior in unipolar and bipolar disorders. J Affect Disord. 2011;134:112–8.

    Article  PubMed  Google Scholar 

  54. Choi J, Cha B, Jang J, et al. Resilience and impulsivity in euthymic patients with bipolar disorder. J Affect Disord. 2015;170:172–7.

    Article  PubMed  Google Scholar 

Download references


The authors would like to thank all the patients and the healthy volunteers who took part in the sample collection and test.


This study was supported by a Joint Scientific Research Grant between Chinese and Croatian Governments (ID # in Chinese part: 8–27). The funding body played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

Author information

Authors and Affiliations



WW conceived the study, FG, JC, YJ, JW collected the data, FG, JC analyzed the data, FG, JC, NJ, ZK, MS, and WW discussed and interpreted the study results, FG, JC, WW drafted the paper, and FG and JC contributed to the work described in the study. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wei Wang.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Medical Ethics Committee of School of Public Health, Zhejiang University (No. Lunyanpidi ZGL201606–1-3), and written informed consent was obtained for experimentation with the participants.

Consent for publication

Not applicable.

Competing interests

Regarding research work described in the paper, each one of our co-authors, Fanjia Guo, Jingyi Cai, Yanli Jia, Jiawei Wang, Nenad Jakšić, Zsuzsanna Kövi, Marina Šagud, and Wei Wang declares that there is no conflict of interest. Author Wei Wang is currently acting as a Section Editor for BMC Psychiatry.

Additional information

Publisher’s Note

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

Supplementary information

Additional file 1: Table S1.

Factor loadings on the six factors of 79 items.

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 The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, F., Cai, J., Jia, Y. et al. Symptom continuum reported by affective disorder patients through a structure-validated questionnaire. BMC Psychiatry 20, 207 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: