Skip to main content

What influences psychological functioning in patients with mood disorders? The role of clinical, sociodemographic, and temperamental characteristics in a naturalistic study

Abstract

Background

The present study aims to assess clinical and psychological correlates of psychological functioning in patients with mood disorders, in a naturalistic setting. In particular, we aimed to describe which sociodemographic, clinical, and temperamental dispositions are more frequently associated with poor psychological functioning, and to describe the association between cognitive and psychological functioning in euthymic patients with major depression and bipolar disorder.

Methods

Inclusion criteria were as follows: (1) diagnosis of major depression, or bipolar disorder type I or II; (2) age between 18 and 65 years; and (3) being in a stable phase of the disorder. Patients’ psychiatric symptoms, quality of life, affective temperaments, and impulsivity were investigated with validated assessment instruments.

Results

166 patients have been recruited, mainly female (55.4%), whose mean age was 47.1 ± 14.2 years. 42.6% of individuals reported a diagnosis of major depression. According to regression analyses, poor cognitive performance (p < 0.05), reduced perceived quality of life (p < .0001), lifetime suicide attempts (p < 0.01), and increased trait-related impulsivity (p <0 .001) strongly correlated with poor psychological functioning. Moreover, cyclothymic and irritable dispositions were also associated with poor social functioning (p < 0.01), whereas hyperthymic affective disposition was associated to a better psychological performance (p < 0.01).

Conclusions

Our results support the evidence that patients with mood disorders should be assessed for psychological functioning and affective dispositions, to identify patients at higher risk to develop worse long-term outcomes and to develop targeted interventions.

Introduction

Mood disorders (MDs) are among the most frequent psychiatric disorders, with a prevalence of major depressive disorder (MDD) ranging from 13 to 20% in the general population [4, 24] and of bipolar disorder (BD) ranging from 3.1 to 8% [48, 71]. Moreover, mood disorders are associated with a significant personal and social burden, being listed among the top-ten leading causes of disability and of premature death by the World Health Organization [20]. More than half of patients with MDs present high comorbidity rates with other psychiatric and physical disorders, including anxiety, alcohol use disorders, chronic pain, and metabolic and cardiovascular disorders [13, 53, 70]. Both depressive and manic/hypomanic symptoms are associated to functional impairment and reduced quality of life (QoL), with difficulties in many areas [43, 63], including work [21], family, and social functioning [22, 39, 44, 66]. The level of impairment is comparable in individuals with MDD and BD during depressive phases and it is worse than that observed in most chronic physical illnesses [11, 29].

Symptoms have been usually considered the primary target of psychiatric treatments [42, 69]. However, patients’ QoL remains unsatisfactory even after clinical remission [18] in a vast majority of patients, including asymptomatic patients and those with residual or subthreshold symptoms [46].

psychological impairment in patients with MDD and BD has been correlated to a variety of factors, including clinical, sociodemographic, and psychological aspects. In particular, from a clinical viewpoint, psychological functioning is influenced by symptom severity, illness duration, presence of psychotic symptoms during acute phases, use of psychotropic medications [41], and cognitive deficits [57, 58], such as attention, executive functions, learning, and memory [7, 38, 46]. In particular, information processing speed, learning and memory impairments, and executive dysfunctions are compromised in patients with MDD and BD [40, 45, 68].

Sociodemographic characteristics associated with higher levels of functional impairment in patients with MDs include older age, male gender, and belonging to ethnical minorities [3, 5]. The psychological dimensions which could affect psychological functioning of patient s with MDs include coping skills, hopelessness, mental rigidity, and problem-solving strategies [54, 78]. Among psychological domains, only rarely the role of affective temperaments in influencing patients’ psychological functioning has been explored. Temperamental dispositions have been described as stable parts of personality [74], which reflect interpersonal styles, energy level, and sensitivity to stimuli. Affective temperaments, as conceptualized by [2], are the anxious, irritable, cyclothymic, hyperthymic, and depressive one [1]. The only dimension of functioning that has been associated to affective disposition is neurocognitive functioning. Russo et al. [60] reported that the presence of cyclothymic and hyperthymic dispositions is associated to a better cognitive performance, and that depressive and anxious predominant dispositions were associated to poor cognitive skills. Considering the relationship between cognitive and psychological functioning, we can only indirectly assume that some affective dispositions can be associated with a better psychological functioning. However, at the moment, no study has directly explored the association between affective dispositions and psychological functioning of individuals with MDs.

Despite levels of psychological impairment in individuals with MDs varies according to the duration and severity of the illness, deficits in global functioning are not always temporally confined to acute episodes, with persistence of psychological impairment over time [15, 37, 73] Impairment in social functioning may persist for years after the resolution of an affective episode, depending on the thoroughness (i.e., with vs. without residual symptoms) and stability (i.e., persistence over time) of the remission.

Currently, research on psychological functioning in patients with MDs is still limited, and few evidence is available on the nature and the extent of psychological impairments in individuals with MDs; differences in methodologies greatly contributed to the heterogeneity of results. Moreover, the clinical characterization of patients with MDs presenting a significant psychological impairment is still missing. One possible major contribution to the paucity of available data is the fact that a clear definition of psychological functioning is lacking with regard to patients with MDs. Currently, several definitions of psychological functioning exist, with their common elements comprising both psychological and social functioning. In this paper we adopted the definition formulated by Xhang et al. (2016) who described psychological functioning as the ability of an individual with MDs to create effective relationships with others and the society in a mutually pleasing manner, and the ability to achieve a healthy life independently.

The aim of the current study is to assess the clinical and psychological correlates of psychological functioning in patients with mood disorders. In particular, we aimed to describe which sociodemographic, clinical, and temperamental dispositions are more frequently associated with poor psychological functioning and to describe the relationship between cognitive and psychological functioning in patient with MDD and BD.

Methods

This study was carried out at the Department of Psychiatry of the University of Campania “Luigi Vanvitelli”. Patients were recruited if they (1) had a diagnosis of MDD or BD type I or II; (2) aged between 18 and 65 years; and (3) were in a stable phase of the disorder. Informed consent was obtained by all study participants. Patients were excluded from this study if they presented comorbid neurological diseases or drug and alcohol dependence. This study was approved by the Local Research Ethic Committee (Number: N001567/28.01.2018).

Procedures

Psychopathological assessments

Sociodemographic and clinical characteristics were recorded thought an ad hoc schedule.

The Hamilton Depression Rating Scale (HAM-D) [23] was adopted to assess severity of depressive symptoms. The HAM-D includes 17 items. Of these, 8 items are scored from 0 (absent) to 4 (severe), while nine are scored from 0 to 2. The total score is performed by the sum of the items’ scores and ranges from 0 to 52 points.

Manic symptoms were assessed with the Young Mania Rating Scale (YMRS) [77]. YMRS includes eleven items, assessing symptoms mood, mobility, sexual desire, sleep, irritability, speech, flight of ideas, grandiosity, aggressive behaviors, appearance, and insight. Seven items are rated on a 5-point Likert scale (from 0 to 4), while four items were rated on a 9-point Likert scale (from 0 to 8).

QoL was assessed thought the Manchester Short Assessment of Quality of Life (MANSA) [56], a 12-item instruments which assess satisfaction across different life domains. Items are assessed on a 7-point Likert scale (1–7).

The brief version of the Munster Temperament Evaluation of the Memphis, Pisa, Paris and San Diego (b-TEMPS-M) was administered to assess affective dispositions. The b-TEMPS-M is a 35-item questionnaire. Each item is scored from 1 to 5 (1 = “not at all”; 2 = “a little”; 3 = “moderately”; 4 = “much”; 5 “very much”) [16]. Five subscales can be calculated, corresponding to the five affective temperaments. Cronbach’s alpha coefficients for subscales were all above 0.8, Kaiser-Meyer-Olkin (KMO) was 0.914.

Trait-related impulsiveness was assessed through The Barratt Impulsiveness Scale (BIS-11) [17]. BIS-11 items are scored on a 4-point Likert scale (1 = rarely, 4 = almost always/always). Higher BIS-11 total scores indicate higher impulsivity traits.

Cognitive functioning was assessed through the brief version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB), which included the Trail Making Test–part A (TMT-A), the Brief Assessment of Cognition in Schizophrenia: Symbol Coding (BACS), and the Category Fluency-Animal Naming [30].

psychological functioning was assessed through the Personal and Social Performance Scale [49] which assesses patients’ functioning across four dimensions (social activities, interpersonal relationships, self-care, aggressive behaviors). Based on ratings on the four dimensions a total score can be attributed to score the overall patient’s functioning, ranging from 0 to 100, with higher scores indicating higher functioning.

Statistical analyses

Sociodemographic and clinical characteristics, and total scores for assessment instruments were assessed through descriptive statistics. Sample was then divided according to the diagnosis (i.e., MDD vs. BD). T-Student test or χ2 was used to test differences among groups. Pearson correlation analyses were adopted in order to assess the association between psychological functioning and continuous clinical variables and total scores. Kendall’s rank analyses were performed to assess correlations between psychological functioning and dichotomous variables. Linear regression analyses were performed, using PSP total score as independent variable. Those variables statistically significant at the univariate analyses were included as covariates. The level of statistical significance was set at p < 0.05.

Results

Sociodemographic and clinical characteristics

A total of 166 patients were included in this study (Table 1). Half of recruited sample (55.4%) was female, with a mean age of 47.1 ± 14.2 years. 57.4% of them reported a diagnosis of bipolar disorder, with a mean duration of illness of 16.2 ± 13.8 years. Psychotic symptoms during affective episodes were reported by 29% of the sample, while 36 patients had at least one suicide attempt lifetime, while 25.6% of the sample reported a seasonal pattern. Patients reported a mean score of 22.4 ± 6.5 for the depressive affective disposition, 18.6 ± 5.2 for the hyperthymic one, 18.9 ± 7.3 for the anxious subscale, 22.8 ± 8.2 for the cyclothymic subscale, and 16.9 ± 7.6 for the irritable one. Mean score at PSP was 70.3 ± 19.1 and 37.5 ± 134 at B-MCCB symbol coding, 19.0 ± 6.8 at B-MCCB animal naming, and 48.3 ± 20.6 at B-MCCB trial making test A.

Table 1 Sociodemographic and clinical characteristics of the sample

Univariate analyses

Compared to patients with major depression, those suffering from bipolar disorders showed a longer duration of illness (20.7 ± 13.2 vs. 10.9 ± 12.5, p < 0.0001), higher levels of impulsivity (BIS-11 total score 82.9 ± 16.0 vs. 71.6 ± 12.1), lower HAM-D total score (6.3 ± 11.5 vs. 11.3 ± 5.7, p < 0.001), and higher YMRS total score (4.6 ± 8.2 vs. 0.7 ± 1.3). Moreover, they presented more frequently a seasonal pattern (39.8% in patients with bipolar disorder vs. 13.2% in patients with major depression, p < 0.0001), history of suicide attempts (26.9% vs. 13.2%, p < 0.05), and psychotic symptoms during acute phases (43% vs. 3.8%, p < 0.0001). Reduced mean score of anxious affective temperament was reported in patients with bipolar disorders, compared to those with major depression (17.1 ± 6.2 vs. 21.4 ± 7.9, p < 0.0001) (Table 2). No statistical differences were detected between the two diagnostic groups with respect to psychological functioning (Table 2).

Table 2 Sociodemographic and clinical characteristics of the sample, according to diagnosis

Correlation analyses

At correlation analyses (Table 3), factors inversely associated with PSP total score with the strongest level of significance (p < 0.0001) were B-MCCB Trial Making Test A score, BIS-11 total score and all BIS-11 subscales (motor, attentional and non-planning impulsiveness), irritable affective temperament, HAM-D total score, and presence of delusions and/or hallucinations during acute phases. Other factors inversely correlated with PSP total score were cyclothymic affective temperament, suicide attempts (p < 0.001), duration of illness, anxious affective temperament, and YMRS total score (p < 0.05). Factors positively associated with PSP total score were MANSA total score (p < 0.0001), B-MCCB animal naming score (p < 0.001), and presence of hyperthymic temperament (p < 0.01).

Table 3 Correlations analyses

Multivariate analysis

According to the linear regression model (Table 4), the likelihood to have a lower PSP total score was increased by the following: (1) the presence of suicidal attempts lifetime (B = − 1687; p < 0.01); (2) lower B-MCCB, animal naming, score (B = 0.680, p < 0.05), and B-MCCB trial making test A score (B = − 179, p < 0.05); (3) lower BIS-11 total score (B = 0.665, p < 0.001); and (4) presence of cyclothymic (B = − 0.343, p < 0.01) and irritable affective temperaments (B = − 0.819, p < 0.01). Moreover, hyperthymic affective temperament (B = 1.24, p < 0.01) and higher MANSA total score (B = 9.15, p < 0.00001) are associated to higher PSP total score.

Table 4 Multivariable regression models

Discussion

This is one of the few studies extensively assessing clinical and psychological correlates of psychological functioning in a sample of patients with affective disorders. Moreover, the possible relationship among the five affective predominant dispositions and psychological functioning in individuals with MDs has been investigated only rarely. We have recruited only stable patients, considering that most of the available evidence, with some exceptions, has been collected in patients presenting affective symptoms to a various degree of severity. It has to be noted that affective temperaments reporting can be influenced by affective symptoms, especially in patients with BDs, during active phases of the disorder.

With regard to the first research aim (i.e., which clinical features are associated to poor psychological functioning?), we found that a poor cognitive performance, a reduced perceived quality of life, presence of suicide attempts lifetime, and increased trait-related impulsivity were strongly correlated with a poor psychological functioning.

The evidence that neurocognitive impairment limits creativity, work performance, QoL, and self-esteem has been reported mainly in individuals with schizophrenia [19, 50, 51]. However, little is known about possible effects of neurocognitive deficits in individuals with MDs [46, 76]. The few studies carried out in patients with active affective symptoms [21] or with residual affective symptoms [61] reported that the association between cognitive and psychological functioning could be biased by the presence of depressive or manic/hypomanic symptoms. The persistence of this association in patients without active affective symptoms, reported by the present study, is rather new and suggests that these deficits, especially in speed of processing, are an enduring component of the neuropsychopathology of affective disorders, and not merely manifestations of acute illness. As such, they could be present even before the onset of the first episode of illness and could predict the onset of an affective disorders [38].

In our study, patients with a higher perceived QoL showed a higher psychological functioning. This finding is consistent with Baune et al. [6] and with Knight et al. [35], confirming that impairment in QoL has detrimental effects not only on patients perceived outcomes but also on the overall functioning, including work, social, and affective functioning [10] also in euthymic patients. It has been reported that psychological functioning and QoL are deeply interconnected, with quality of life influencing overall functioning and vice versa. In fact, a reduced psychological functioning is associated with poor working skills and productivity [5], reduced social contacts, and increased feelings of loneliness, with a significant impact on individuals’ QoL [27, 36, 37]. Conversely, dissatisfaction in several aspects of life (i.e., work, family, social life) could affect occupational competitiveness and patients’ motivation to be engaged in social and leisure activities and to maintain regular contacts with family members and other relevant others, thus affecting overall psychological functioning [8, 28, 35].

Moreover, in our sample higher levels of trait-related impulsivity strongly reduced patients’ psychological functioning. This association, which has only rarely been investigated, could be mediated by the fact that high levels of trait-related impulsiveness are associated to a worse long-term outcome and to an increased illness chronicity, leading to a reduced psychological functioning [59]. In fact, in patients with bipolar disorder, trait-related impulsiveness has been associated to an earlier age at onset, increased risk of suicide attempts and higher number of relapses [50, 67], reduced time in euthymic phase [12], more frequent rapid cycling course [14], and substance behaviors [64]. Moreover, impulsivity negatively affect long-term outcome in patients with MDD also, by increasing suicidality [34, 47, 75] substance misuse and mood instability [25, 26]. In particular, impulsivity has been reported to be a predictive factor for future suicidal attempts in patients with mood disorders, [50].

In our study, we reported a significant association among psychological functioning and affective temperaments. In particular, cyclothymic and irritable dispositions were associated to a reduced psychological functioning, whereas a predominant hyperthymic affective disposition with better psychological performances. Affective temperaments have been also associated with different psychopathological dimensions in patients with affective disorders [16, 41]; cyclothymic temperament is usually associated with clinically relevant and persistent mood fluctuations and levels of energy [52], while the irritable disposition is associated with impulsivity and anger. These two affective dispositions are generally associated to a worse outcome, but only rarely their relationship with psychological functioning has been explored. The presence of a hyperthymic predominant disposition usually implies the presence of high energy levels, positive thinking, ambition, confidence, increased social abilities, and increased creativity. Patients with this affective disposition could present, therefore, reduced illness severity and increased coping skills to deal with environmental stressors [31, 55].

Of note, both at correlation analyses and at multivariate analyses, psychiatric diagnoses were not statistically associated with global functioning. This suggests that during euthymic phases of the disorder, global levels of functioning do not significantly differ among patients with MDD and BD. This result further highlight that mood disorders could belong to a broad affective spectrum, in which affective dispositions and psychopathological and psychological domains delineate multiple complex clinical phenotypes. The complex interplay among these factors should guide clinicians toward a better clinical characterization [43, 57, 65]. Moreover, our results suggest that a trans-diagnostic approach to mental disorders should be preferred to a rigid categorical approach [33, 62].

Our study has several limitations. First, patients were recruited only in one site. Moreover, the sample size is relatively small. These two factors limit the generalizability our findings, which should be replicated in larger sample sizes. Moreover, we did not include a control group of patients suffering from mental disorders different form affective ones. Third, the cross-sectional design of the study did not allow us to investigate cause–effect relationships. Another possible limitation of the present study is that affective temperaments were detected with a self-reported questionnaire. However, the TEMPS is the most adopted assessment instruments and objective measures to evaluate affective dispositions are not available. Moreover, in our study several clinical characteristics have been retrospectively assessed (i.e., age at onset, number of previous relapses, presence of psychotic symptoms during affective phases, and so on). However, we tried to reduce this recall bias by using a structured schedule to collect retrospective data and we adopted DSM-5 criteria to define previous affective episodes. Lastly, another possible limitation is the exclusion of patients with comorbid substance abuse, which have reduced the generalizability of our findings. It has been reported that patient with severe mental disorder and comorbid substance use disorders presents more negative outcomes than their counterparts without comorbid disorders and presents more frequently a reduced psychological functioning [9]. However, we intended to recruit a sample with MD and comorbid substance abuse in order to compare impairments in psychological functioning among groups.

Conclusions

Results of our study support the evidence that some psychological and temperamental characteristics are associated with functional impairment in mood disorders. Affective dispositions, quality of life, and trait-related impulsivity should be routinely assessed in ordinary practice, with the aim to identify patients with and increased risk to present psychological impairment and to develop personalized and targeted interventions. These interventions could be developed, also taking advantage from new technologies [72] and social media, which can booster the scalability of such interventions [32].

Availability of data and materials

Data presented in this study are available on request from the corresponding author on a reasonable request.

References

  1. Akiskal HS, Mallya G. Criteria for the “soft” bipolar spectrum: treatment implications. Psychopharmacol Bull. 1987;23:68–73.

    CAS  Google Scholar 

  2. Akiskal HS, Placidi GF, Maremmani I, Signoretta S, Liguori A, Gervasi, et al. TEMPS-I delineating the most discriminant traits of the cyclothymic depressive hyperthymic and irritable temperaments in a nonpatient population. J Affect Disord. 1998. https://doi.org/10.1016/S0165-0327(98)00152-9.

    Article  Google Scholar 

  3. Alegria M, Falgas-Bague I, Fong HF. Engagement of ethnic minorities in mental health care. World Psychiatry. 2020;19:35–6.

    Article  Google Scholar 

  4. Alonso J, Lépine JP. ESEMeD/MHEDEA 2000 scientific committee overview of key data from the European study of the epidemiology of mental disorders (ESEMeD). J Clin Psychiatry. 2007;68:3–9.

    Google Scholar 

  5. Ba Z, Chen M, Lai J, Liao Y, Fang H, Lu D, et al. Heterogeneity of psychological functioning in patients with bipolar disorder: associations with sociodemographic, clinical, neurocognitive and biochemical variables. Front Psychiatry. 2022;13: 900757.

    Article  Google Scholar 

  6. Baune BT, Miller R, McAfoose J, Johnson M, Quirk F, Mitchell D. The role of cognitive impairment in general functioning in major depression. Psychiatry Res. 2010;176:183–9.

    Article  Google Scholar 

  7. Bearden CE, Hoffman KM, Cannon TD. The neuropsychology and neuroanatomy of bipolar affective disorder: a critical review. Bipolar Disord. 2001;3:106–50.

    Article  CAS  Google Scholar 

  8. Bonnín CDM, Reinares M, Martínez-Arán A, Jiménez E, Sánchez-Moreno J, Solé B, et al. Improving functioning, quality of life, and well-being in patients with bipolar disorder. Int J Neuropsychopharmacol. 2019;22:467–77.

    Google Scholar 

  9. Carrà G, Scioli R, Monti MC, Marinoni A. Severity profiles of substance-abusing patients in Italian community addiction facilities: influence of psychiatric concurrent disorders. Eur Addict Res. 2006;12:96–101.

    Article  Google Scholar 

  10. Coryell W, Scheftner W, Keller M, Endicott J, Maser J, Klerman GL. The enduring psychological consequences of mania and depression. Am J Psychiatry. 1993;150:720–7.

    Article  CAS  Google Scholar 

  11. Cuijpers P, Quero S, Noma H, Ciharova M, Miguel C, Karyotaki E, et al. Psychotherapies for depression: a network meta-analysis covering efficacy, acceptability and long-term outcomes of all main treatment types. World Psychiatry. 2021;20:283–93.

    Article  Google Scholar 

  12. Dawson EL, Shear PK, Howe SR, Adler CM, DelBello MP, Fleck DE, Strakowski SM. Impulsivity predicts time to reach euthymia in adults with bipolar disorder. Bipolar Disord. 2014;16:846–56.

    Article  Google Scholar 

  13. Duffy A, Horrocks J, Doucette S, Keown-Stoneman C, McCloskey S, Grof P. The developmental trajectory of bipolar disorder. Br J Psychiatry. 2014;204:122–8.

    Article  Google Scholar 

  14. Etain B, Mathieu F, Liquet S, Raust A, Cochet B, Richard JR, et al. Clinical features associated with trait-impulsiveness in euthymic bipolar disorder patients. J Affect Disord. 2013;144:240–7.

    Article  CAS  Google Scholar 

  15. Fava GA, Guidi J. The pursuit of euthymia. World Psychiatry. 2020;19:40–50.

    Article  Google Scholar 

  16. Fico G, Luciano M, Sampogna G, Zinno F, Steardo L Jr, Perugi G, et al. Validation of the brief TEMPS-M temperament questionnaire in a clinical Italian sample of bipolar and cyclothymic patients. J Affect Disord. 2020;260:458–62.

    Article  Google Scholar 

  17. Fossati A, Di Ceglie A, Acquarini E, Barratt ES. Psychometric properties of an Italian version of the Barratt impulsive-ness scale-11 (BIS-11) in nonclinical subjects. J Clin Psychol. 2001;57:815–28.

    Article  CAS  Google Scholar 

  18. Fulford KWM, Handa A. New resources for understanding patients’ values in the context of shared clinical decision-making. World Psychiatry. 2021;20:446–7.

    Article  Google Scholar 

  19. Galderisi S, Rucci P, Mucci A, Rossi A, Rocca P, Bertolino A, et al. The interplay among psychopathology, personal resources, context-related factors and real-life functioning in schizophrenia: stability in relationships after 4 years and differences in network structure between recovered and non-recovered patients. World Psychiatry. 2020;19:81–91.

    Article  Google Scholar 

  20. GBD. Mental disorders collaborators. 2022 global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of disease study 2019. Lancet Psychiatry. 2019;9:137–50.

    Google Scholar 

  21. Godard J, Grondin S, Baruch P, Lafleur MF. psychological and neurocognitive profiles in depressed patients with major depressive disorder and bipolar disorder. Psychiatry Res. 2011;190:244–52.

    Article  Google Scholar 

  22. Gutiérrez-Rojas L, Gurpegui M, Ayuso-Mateos JL, Gutiérrez-Ariza JA, Ruiz-Veguilla M, Jurado D. Quality of life in bipolar disorder patients: a comparison with a general population sample. Bipolar Disord. 2008;10:625–34.

    Article  Google Scholar 

  23. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56–62.

    Article  CAS  Google Scholar 

  24. Hasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, et al. Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiat. 2018;75:336–46.

    Article  Google Scholar 

  25. Henna E, Hatch JP, Nicoletti M, Swann AC, Zunta-Soares G, Soares JC. Is impulsivity a common trait in bipolar and unipolar disorders? Bipolar Disord. 2013;15:223–7.

    Article  Google Scholar 

  26. Hickman M, Hines LA, Gage SH. Assessing the public health effects of cannabis use: can legalization improve the evidence base? World Psychiatry. 2020;19:197–8.

    Article  Google Scholar 

  27. Holt-Lunstad J. A pandemic of social isolation? World Psychiatry. 2021;20:55–6.

    Article  Google Scholar 

  28. Jiménez-López E, Sánchez-Morla EM, López-Villarreal A, Aparicio AI, Martínez-Vizcaíno V, Vieta E, et al. Neurocognition and functional outcome in patients with psychotic, non-psychotic bipolar I disorder, and schizophrenia a five-year follow-up. Eur Psychiatry. 2019;56:60–8.

    Article  Google Scholar 

  29. Joo J. From depression to disability. Int Psychogeriatr. 2017;29:883.

    Article  Google Scholar 

  30. Kern RS, Nuechterlein KH, Green MF, Baade LE, Fenton WS, Gold JM, et al. The MATRICS consensus cognitive battery, part 2: co-norming and standardization. Am J Psychiatry. 2008;165:214–20.

    Article  Google Scholar 

  31. Kesebir S, Gündoğar D, Küçüksubaşı Y, Tatlıdil YE. The relation between affective temperament and resilience in depression: a controlled study. J Affect Disord. 2013;148:352–6.

    Article  Google Scholar 

  32. Keyes KM, Whitley R, Fink D, Santaella J, Pirkis J. The global impact of celebrity suicides: implications for prevention. World Psychiatry. 2021;20:144–5.

    Article  Google Scholar 

  33. Kim H, Turiano NA, Forbes MK, Kotov R, Krueger RF, Eaton NR. HiTOP utility workgroup internalizing psychopathology and all-cause mortality a comparison of transdiagnostic vs diagnosis based risk prediction. World Psychiatry. 2021;20:276–82.

    Article  Google Scholar 

  34. Klonsky ED, Dixon-Luinenburg T, May AM. The critical distinction between suicidal ideation and suicide attempts. World Psychiatry. 2021;20:439–41.

    Article  Google Scholar 

  35. Knight MJ, Lyrtzis E, Baune BT. The association of cognitive deficits with mental and physical quality of life in major depressive disorder. Compr Psychiatry. 2020;97: 152147.

    Article  Google Scholar 

  36. Léda-Rêgo G, Bezerra-Filho S, Miranda-Scippa Â. Functioning in euthymic patients with bipolar disorder: a systematic review and meta-analysis using the functioning assessment short test. Bipolar Disord. 2020;22:569–81.

    Article  Google Scholar 

  37. Leon AC, Solomon DA, Mueller TI, Endicott J, Posternak M, Judd LL. A brief assessment of psychological functioning of subjects with bipolar I disorder the LIFE-RIFT longitudinal interval follow-up evaluation-range impaired functioning tool. J Nerv Ment Dis. 2000;188:805–12.

    Article  CAS  Google Scholar 

  38. Lima IMM, Peckham AD, Johnson SL. Cognitive deficits in bipolar disorders: Implications for emotion. Clin Psychol Rev. 2018;59:126–36.

    Article  Google Scholar 

  39. Luciano M, Del Vecchio V, Giacco D, De Rosa C, Malangone C, Fiorillo A. A “family affair”? The impact of family psychoeducational interventions on depression. Expert Rev Neurother. 2012;12:83–91.

    Article  Google Scholar 

  40. Luciano M, Di Vincenzo M, Mancuso E, Marafioti N, Di Cerbo A, Giallonardo V, et al. Does the brain matter? cortical alterations in pediatric bipolar disorder: a critical review of structural and functional magnetic resonance studies. Curr Neuropharmacol. 2022. https://doi.org/10.2174/1570159X20666220927114417.

    Article  Google Scholar 

  41. Luciano M, Steardo L Jr, Sampogna G, Caivano V, Ciampi C, Del Vecchio V, et al. Affective temperaments and illness severity in patients with bipolar disorder. Medicina. 2021;57:54.

    Article  Google Scholar 

  42. MacLeod A. Euthymia: why it really does matter. World Psychiatry. 2020;19:1–2.

    Article  Google Scholar 

  43. Maj M, Stein DJ, Parker G, Zimmerman M, Fava GA, De Hert M, et al. The clinical characterization of the adult patient with depression aimed at personalization of management. World Psychiatry. 2020;19:269–93.

    Article  Google Scholar 

  44. Marangell LB, Dennehy EB, Miyahara S, Wisniewski SR, Bauer MS, Rapaport MH, et al. The functional impact of subsyndromal depressive symptoms in bipolar disorder: data from STEP-BD. J Affect Disord. 2009;114:58–67.

    Article  Google Scholar 

  45. Martínez-Arán A, Vieta E, Colom F, Torrent C, Sánchez-Moreno J, Reinares M. Cognitive impairment in euthymic bipolar patients: implications for clinical and functional outcome. Bipolar Disord. 2004;6:224–32.

    Article  Google Scholar 

  46. McClintock SM, Husain MM, Greer TL, Cullum CM. Association between depression severity and neurocognitive function in major depressive disorder: a review and synthesis. Neuropsychology. 2010;24:9–34.

    Article  Google Scholar 

  47. McIntyre RS, Lee Y. Preventing suicide in the context of the COVID-19 pandemic. World Psychiatry. 2020;19:250–1.

    Article  Google Scholar 

  48. Moreno DH, Andrade LH. The lifetime prevalence, health services utilization and risk of suicide of bipolar spectrum subjects, including subthreshold categories in the São Paulo ECA study. J Affect Disord. 2005;87:231–41.

    Article  Google Scholar 

  49. Morosini PL, Magliano L, Brambilla L, Ugolini S, Pioli R. Development, reliability and acceptability of a new version of the DSM-IV social and occupational functioning assessment scale (SOFAS) to assess routine social functioning. Acta Psychiatr Scand. 2000;101:323–9.

    Article  CAS  Google Scholar 

  50. Oquendo MA, Lizardi D, Greenwald S, Weissman MM, Mann JJ. Rates of lifetime suicide attempt and rates of lifetime major depression in different ethnic groups in the United States. Acta Psychiatr Scand. 2004;110:446–51.

    Article  CAS  Google Scholar 

  51. Penninx BWJH. Psychiatric symptoms and cognitive impairment in “Long COVID”: the relevance of immunopsychiatry. World Psychiatry. 2021;20:357–8.

    Article  Google Scholar 

  52. Perugi G, Akiskal HS. The soft bipolar spectrum redefined: focus on the cyclothymic, anxious-sensitive, impulse-dyscontrol, and binge-eating connection in bipolar II and related conditions. Psychiatr Clin North Am. 2002;25:713–37.

    Article  Google Scholar 

  53. Plana-Ripoll O, Musliner KL, Dalsgaard S, Momen NC, Weye N, Christensen MK, et al. Nature and prevalence of combinations of mental disorders and their association with excess mortality in a population-based cohort study. World Psychiatry. 2020;19:339–49.

    Article  Google Scholar 

  54. Pompili M, Innamorati M, Erbuto D, Luciano M, Sampogna G, Abbate-Daga G, et al. High depression symptomatology and mental pain characterize suicidal psychiatric patients. Eur Psychiatry. 2022;65(1): e54. https://doi.org/10.1192/j.eurpsy.2022.2312.

    Article  Google Scholar 

  55. Pompili M, Rihmer Z, Akiskal HS, Innamorati M, Iliceto P, Akiskal KK, et al. Temperament and personality dimensions in suicidal and nonsuicidal psychiatric inpatients. Psychopathology. 2008;41:313–21.

    Article  Google Scholar 

  56. Priebe S, Huxley P, Knight S, Evans S. Application and results of the manchester short assessment of quality of life (MANSA). Int J Soc Psychiatry. 1999;45:7–12.

    Article  CAS  Google Scholar 

  57. Reynolds CF. Optimizing personalized management of depression: the importance of real-world contexts and the need for a new convergence paradigm in mental health. World Psychiatry. 2020;19:266–8.

    Article  Google Scholar 

  58. Roca M, Monzón S, Vives M, López-Navarro E, Garcia-Toro M, Vicens C, et al. Cognitive function after clinical remission in patients with melancholic and non-melancholic depression: a 6 month follow-up study. J Affect Disord. 2015;171:85–92.

    Article  Google Scholar 

  59. Rote WM, Smetana JG. Within-family dyadic patterns of parental monitoring and adolescent information management. Dev Psychol. 2018;54(12):2302–15. https://doi.org/10.1037/dev0000615. (PMID: 30265033).

    Article  Google Scholar 

  60. Russo M, Mahon K, Shanahan M, Ramjas E, Solon C, Braga RJ. Affective temperaments and neurocognitive functioning in bipolar disorder. J Affect Disord. 2014;169:51–6.

    Article  Google Scholar 

  61. Samalin L, Boyer L, Murru A, Pacchiarotti I, Reinares M, Bonnin CM, et al. Residual depressive symptoms, sleep disturbance and perceived cognitive impairment as determinants of functioning in patients with bipolar disorder. J Affect Disord. 2017;210:280–6.

    Article  Google Scholar 

  62. Shah JL, Scott J, McGorry PD, Cross SPM, Keshavan MS, Nelson B, Wood SJ, Marwaha S, Yung AR, Scott EM, Öngür D, Conus P, Henry C, Hickie IB. International working group on transdiagnostic clinical staging in youth mental health transdiagnostic clinical staging in youth mental health: a first international consensus statement. World Psychiatry. 2020;19:233–42.

    Article  Google Scholar 

  63. Sheehan DV, Nakagome K, Asami Y, Pappadopulos EA, Boucher M. Restoring function in major depressive disorder: a systematic review. J Affect Disord. 2017;215:299–313.

    Article  Google Scholar 

  64. Squeglia LM. Alcohol and the developing adolescent brain. World Psychiatry. 2020;19:393–4.

    Article  Google Scholar 

  65. Stein DJ, Craske MG, Rothbaum BO, Chamberlain SR, Fineberg NA, Choi KW, de Jonge P, Baldwin DS, Maj M. The clinical characterization of the adult patient with an anxiety or related disorder aimed at personalization of management. World Psychiatry. 2021;20:336–56.

    Article  Google Scholar 

  66. Strine TW, Dhingra SS, Okoro CA, Zack MM, Balluz LS, Berry JT, et al. State-based differences in the prevalence and characteristics of untreated persons with serious psychological distress. Int J Public Health. 2009;54:9–15.

    Article  Google Scholar 

  67. Swann AC, Dougherty DM, Pazzaglia PJ, Pham M, Steinberg JL, et al. Increased impulsivity associated with severity of suicide attempt history in patients with bipolar disorder. Am J Psychiatry. 2005;162:1680–7.

    Article  Google Scholar 

  68. Swann AC, Lijffijt M, Lane SD, Steinberg JL, Moeller FG. Severity of bipolar disorder is associated with impairment of response inhibition. J Affect Disord. 2009;116:30–6.

    Article  Google Scholar 

  69. Swift JK, Mullins RH, Penix EA, Roth KL, Trusty WT. The importance of listening to patient preferences when making mental health care decisions. World Psychiatry. 2021;20:316–7.

    Article  Google Scholar 

  70. Taipale H, Tanskanen A, Mehtälä J, Vattulainen P, Correll CU, Tiihonen J. 20-year follow-up study of physical morbidity and mortality in relationship to antipsychotic treatment in a nationwide cohort of 62,250 patients with schizophrenia (FIN20). World Psychiatry. 2020;19:61–8.

    Article  Google Scholar 

  71. Teh WL, Abdin E, Vaingankar J, Shafie S, Yiang Chua B, Sambasivam R, et al. Prevalence and correlates of bipolar spectrum disorders in Singapore: results from the 2016 Singapore mental health study (SMHS 2016). J Affect Disord. 2020;274:339–46.

    Article  Google Scholar 

  72. Torous J, Choudhury T, Barnett I, Keshavan M, Kane J. Smartphone relapse prediction in serious mental illness: a pathway towards personalized preventive care. World Psychiatry. 2020;19:308–9.

    Article  Google Scholar 

  73. Trivedi MH. Treating partial responders to antidepressant treatment. J Clin Psychiatry. 2009;70: e31.

    Article  Google Scholar 

  74. Turek A, Machalska K, Chrobak AA, Siwek M, Dudek D. Impulsiveness and cyclothymic traits of affective tempera-ment as predictors of risky gambling behavior. Psychiatr Pol. 2020;54:537–52.

    Article  Google Scholar 

  75. Wasserman D, Iosue M, Wuestefeld A, Carli V. Adaptation of evidence-based suicide prevention strategies during and after the COVID-19 pandemic. World Psychiatry. 2020;19:294–306.

    Article  Google Scholar 

  76. Wingo AP, Wingo TS, Harvey PD, Baldessarini RJ. Effects of lithium on cognitive performance: a meta-analysis. J Clin Psychiatry. 2009;70:1588–97.

    Article  CAS  Google Scholar 

  77. 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  Google Scholar 

  78. Zimmerman M, McGlinchey JB, Posternak MA, Friedman M, Boerescu D, Attiullah N. Differences between minimally depressed patients who do and do not consider themselves to be in remission. J Clin Psychiatry. 2005;66:1134–8.

    Article  Google Scholar 

Download references

Acknowledgements

None.

Funding

This research received no external funding.

Author information

Authors and Affiliations

Authors

Contributions

ML, AF, and GS contributed to conceptualization; MDV, ML, AF, and GS contributed to methodology; ML, GS, and EM conducted formal analyses; AV, BDR, LL, and ADC performed investigation; ML and GS were involved in data curation; MDV and ML wrote the original draft; GS and AF were involved in writing––review and editing; AF and GS performed supervision. All the authors have read and agreed to the published version of the manuscript. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Matteo Di Vincenzo.

Ethics declarations

Ethics approval and consent to participate

All patients signed an informed consent. This study was carried out in accordance with the latest version of the Declaration of Helsinki and was approved by the Local Research Ethic Committee (Number: N001567/28.01.2018).

Consent for publication

Not applicable.

Competing interests

The authors declare no conflicts of interest.

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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) 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

Di Vincenzo, M., Sampogna, G., Della Rocca, B. et al. What influences psychological functioning in patients with mood disorders? The role of clinical, sociodemographic, and temperamental characteristics in a naturalistic study. Ann Gen Psychiatry 21, 51 (2022). https://doi.org/10.1186/s12991-022-00428-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12991-022-00428-9

Keywords