PsyQ Rijnmond

Rotterdam, Netherlands

PsyQ Rijnmond

Rotterdam, Netherlands
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Becking K.,University of Groningen | Spijker A.T.,PsyQ Rijnmond | Hoencamp E.,PsyQ Rijnmond | Hoencamp E.,Leiden University | And 5 more authors.
PLoS ONE | Year: 2015

Introduction: Differentiating bipolar depression (BD) from unipolar depression (UD) is difficult in clinical practice and, consequently, accurate recognition of BD can take as long as nine years. Research has therefore focused on the discriminatory capacities of biomarkers, such as markers of the hypothalamic-pituitary-adrenal (HPA) axis or immunological activity. However, no previous study included assessments of both systems, which is problematic as they may influence each other. Therefore, this study aimed to explore whether cortisol indicators and inflammatory markers were a) independently associated with and/or b) showed effect modification in relation to a lifetime (hypo)manic episode in a large sample of depressed patients. Methods: Data were derived from the Netherlands Study of Depression and Anxiety and comprised 764 patients with a DSM-IV depressive disorder at baseline, of which 124 (16.2%) had a lifetime (hypo)manic episode at the 2-year assessment, or a more recent episode at the 4-year or 6-year assessment. Baseline cortisol awakening response, evening cortisol and diurnal cortisol slope were considered as cortisol indicators, while baseline C-reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor Alpha (TNF-α) were included as inflammatory markers. Results: In depressed men and women, none of the cortisol indicators and inflammatory markers were (independently) associated with a (hypo)manic episode. However, effect modification was found of diurnal cortisol slope and CRP in relation to a (hypo)manic episode. Further analyses showed that depressed men with high levels of diurnal cortisol slope and CRP had an increased odds (OR=10.99, p = .001) of having a (hypo)manic episode. No significant differences were found in women. Conclusion: Our findings suggest that the combination of high diurnal cortisol slope and high CRP may differentiate between UD and BD. This stresses the importance of considering HPA-axis and immunological activity simultaneously, but more research is needed to unravel their interrelatedness. Copyright: © 2015 Becking et al.


Koenders M.A.,PsyQ the Hague | Nolen W.A.,University of Groningen | Giltay E.J.,Leiden University | Hoencamp E.,PsyQ the Hague | Spijker A.T.,PsyQ Rijnmond
Journal of Affective Disorders | Year: 2015

Background The severity of bipolar disorder can be assessed using the daily prospective National Institute of Mental Health's Life Chart Method (LCM-p). Also for scientific research the LCM-p, has been used frequently. However, processing and analyzing the LCM-p for research purposes, are challenging because of the multitude of complex measures that can be derived from the data. In the current paper we review the different LCM-p course variables (mood episodes, average severity, proportion of time ill and mood switches) and their definitions. Strengths and limitations and the impact of the use of different LCM-p course measures and definitions on the research results are described. Method A systematic review of original papers on the LCM was conducted using 9 electronic databases for literature between January 1996 and December 2014. Papers using other prospective charting procedures were not evaluated in the current study. Results The initial literature search led to 1352 papers of which 21 were eventually selected. A relatively wide variety of definitions of LCM-p course variables was used across the studies. Especially for the calculation of number of episodes and mood switch no univocal definition seems to exist. Across studies several different durations and severity criteria are applied to calculate these variables. We describe which variables and definitions are most suitable for detecting specific bipolar disease course characteristics and patterns. Conclusion In the absence of a golden standard for the calculation of LCM-p course variables, researchers should report the exact method they applied to their LCM-p data, and clearly motivate why this is their method of first choice considering their research aim. © 2015 Elsevier B.V. All rights reserved.


PubMed | PsyQ The Hague, University of Groningen, Leiden University and PsyQ Rijnmond
Type: | Journal: Journal of affective disorders | Year: 2015

The severity of bipolar disorder can be assessed using the daily prospective National Institute of Mental Healths Life Chart Method (LCM-p). Also for scientific research the LCM-p, has been used frequently. However, processing and analyzing the LCM-p for research purposes, are challenging because of the multitude of complex measures that can be derived from the data. In the current paper we review the different LCM-p course variables (mood episodes, average severity, proportion of time ill and mood switches) and their definitions. Strengths and limitations and the impact of the use of different LCM-p course measures and definitions on the research results are described.A systematic review of original papers on the LCM was conducted using 9 electronic databases for literature between January 1996 and December 2014. Papers using other prospective charting procedures were not evaluated in the current study.The initial literature search led to 1352 papers of which 21 were eventually selected. A relatively wide variety of definitions of LCM-p course variables was used across the studies. Especially for the calculation of number of episodes and mood switch no univocal definition seems to exist. Across studies several different durations and severity criteria are applied to calculate these variables. We describe which variables and definitions are most suitable for detecting specific bipolar disease course characteristics and patterns.In the absence of a golden standard for the calculation of LCM-p course variables, researchers should report the exact method they applied to their LCM-p data, and clearly motivate why this is their method of first choice considering their research aim.


Koenders M.A.,PsyQ the Hague | Koenders M.A.,Leiden University | Giltay E.J.,Leiden University | Hoencamp E.,PsyQ the Hague | And 4 more authors.
Comprehensive Psychiatry | Year: 2015

Bipolar disorder (BD) is a chronic illness, and a great need has been expressed to elucidate factors affecting the course of the disease. Social support is one of the psychosocial factors that is assumed to play an important role in the course of BD, but it is largely unknown whether the depressive and/or manic symptoms also affect the patients' support system. Further, the perception of one's social support appears to have stronger effects on disease outcomes than one's enacted or received support, but whether this also applies to BD has not been investigated. The objective of this study is to examine temporal, bidirectional associations between mood states (depression and mania) and both enacted and perceived support in BD patients. The current study was conducted among 173 BD I and II outpatients, with overall light to mild mood symptoms. Severity of mood symptoms and social support (enacted as well as perceived) were assessed every 3 months, for 2 years (1146 data points). Multilevel regression analyses (linear mixed-models) showed that lower perceived support during 3 months was associated with subsequent higher levels of depressive, but not of manic symptoms in the following 3 months. Vice versa, depressive symptoms during 3 months were associated with less perceived support in the following 3 months. Further, manic symptoms during 3 months were associated with less enacted support in the subsequent 3 months. The current study suggests that perceived, but not enacted, support is consistently related to depressive symptoms in a bidirectional way, while mania is specifically associated with a subsequent loss of enacted support. Clinical implications of the current findings are discussed. © 2015 Elsevier Inc.


Koenders M.A.,Leiden University | De Kleijn R.,Leiden University | Giltay E.J.,Leiden University | Elzinga B.M.,Leiden University | And 2 more authors.
PLoS ONE | Year: 2015

Objective The longitudinal mood course is highly variable among patients with bipolar disorder(BD). One of the strongest predictors of the future disease course is the past disease course, implying that the vulnerability for developing a specific pattern of symptoms is rather consistent over time. We therefore investigated whether BD patients with different longitudinal course types have symptom correlation networks with typical characteristics. To this end we used network analysis, a rather novel approach in the field of psychiatry. Method Based on two-year monthly life charts, 125 patients with complete 2 year data were categorized into three groups: i.e., a minimally impaired (n = 47), a predominantly depressed (n = 42) and a cycling course (n = 36). Associations between symptoms were defined as the groupwise Spearman's rank correlation coefficient between each pair of items of the Young Mania Rating Scale (YMRS) and the Quick Inventory of Depressive Symptomatology (QIDS). Weighted symptom networks and centrality measures were compared among the three groups. Results The weighted networks significantly differed among the three groups, with manic and depressed symptoms being most strongly interconnected in the cycling group. The symptoms with top centrality that were most interconnected also differed among the course group; central symptoms in the stable group were elevated mood and increased speech, in the depressed group loss of self-esteem and psychomotor slowness, and in the cycling group concentration loss and suicidality. Conclusion Symptom networks based on the timepoints with most severe symptoms of bipolar patients with different longitudinal course types are significantly different. The clinical interpretation of this finding and its implications are discussed. © 2015 Koenders et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


PubMed | Leiden University and PsyQ Rijnmond
Type: Journal Article | Journal: PloS one | Year: 2015

The longitudinal mood course is highly variable among patients with bipolar disorder(BD). One of the strongest predictors of the future disease course is the past disease course, implying that the vulnerability for developing a specific pattern of symptoms is rather consistent over time. We therefore investigated whether BD patients with different longitudinal course types have symptom correlation networks with typical characteristics. To this end we used network analysis, a rather novel approach in the field of psychiatry.Based on two-year monthly life charts, 125 patients with complete 2 year data were categorized into three groups: i.e., a minimally impaired (n = 47), a predominantly depressed (n = 42) and a cycling course (n = 36). Associations between symptoms were defined as the groupwise Spearmans rank correlation coefficient between each pair of items of the Young Mania Rating Scale (YMRS) and the Quick Inventory of Depressive Symptomatology (QIDS). Weighted symptom networks and centrality measures were compared among the three groups.The weighted networks significantly differed among the three groups, with manic and depressed symptoms being most strongly interconnected in the cycling group. The symptoms with top centrality that were most interconnected also differed among the course group; central symptoms in the stable group were elevated mood and increased speech, in the depressed group loss of self-esteem and psychomotor slowness, and in the cycling group concentration loss and suicidality.Symptom networks based on the timepoints with most severe symptoms of bipolar patients with different longitudinal course types are significantly different. The clinical interpretation of this finding and its implications are discussed.


PubMed | PsyQ Rijnmond
Type: Journal Article | Journal: Social science & medicine (1982) | Year: 2011

Despite growing concerns of over-treatment, the under-diagnosis and undertreatment of major depressive disorders is still prevalent. Causal attributions are thought to be involved in help seeking behavior, time to diagnosis and the chance for successful referral. Yet, little is known about the extent to which these processes are influenced by causal attributions. 120 patients, involved in the nationwide second Dutch National Survey of General Practice (Schellevis, Westert, & Bakker, 2005), with a current DSM-IV diagnosis of depression, severe depression or with a depression lasting over six months, completed a causal attributions inventory. Demographic and clinical data from the survey, and causal attribution scores were used as independent variables in association with getting a diagnosis of depression from the general practitioner, or being in treatment by a mental health care provider for more than 3 sessions. Causal attributions related to intrapsychic fears were significantly associated with getting a diagnosis of depression and successful referral. Causal attributions related to childhood were also positively associated with successful referral. In association models derived from all the demographic and clinical data available in the survey, causal attributions substantially contributed to the explained variance, 55% and 39% respectively. The findings suggest causal attributions have a statistically significant impact on time to diagnosis and the chance of successful referral. Using the Causal Attribution Inventory with high-risk patients in primary care might enhance the chance of detection and successful referral of depressed patients. Schellevis, F. G., Westert, G. P., & De Bakker, D. H. (2005). The actual role of general practice in the dutch health-care system. Results of the second dutch national survey of general practice. Medizinische Klinik (Munich), 100(10), 656-661.

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