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Depression: HELP
Articles by Robert A. Schoevers
Based on 108 articles published since 2008
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Between 2008 and 2019, R. Schoevers wrote the following 108 articles about Depression.
 
+ Citations + Abstracts
Pages: 1 · 2 · 3 · 4 · 5
1 Review [rTMS for treatment resistant depression - proposal for a treatment protocol]. 2018

van Belkum, S M / de Boer, M K / Taams, G-J / Schutter, D J L G / Aleman, A / Schoevers, R A / Haarman, B C M. · ·Tijdschr Psychiatr · Pubmed #30484569.

ABSTRACT: BACKGROUND: At present, the use of repetitive transcranial magnetic stimulation (rtms) for treatment-resistant depression is sufficiently substantiated to be applied in clinical practice. In the Netherlands, it will be reimbursed when offered in combination with cognitive behavior therapy.
AIM: Proposal for a clinical treatment protocol for rtms in The Netherlands.
METHOD: A study of the literature and a critical appraisal of available international guidelines for rtms.
RESULTS: rtms is a safe treatment for patients suffering from a moderate to severe depressive disorder that is relatively treatment-resistant. The duration of the effect is still unknown. It is advised to stimulate the left dorsolateral prefrontal cortex using an intensity of 120% of the resting motor threshold, with a frequency of 10 Hz and using 3000 pulses per session during a total of 20-30 sessions.
CONCLUSION: The proposed treatment protocol is favored based on the available evidence when rtms is used as a treatment aimed to acutely decrease the severity of depressive symptoms. It is further proposed to systematically collect technical and outcome data on treatment with rtms to further improve treatment with rtms in clinical practice.

2 Review Huntingtin gene repeat size variations affect risk of lifetime depression. 2017

Gardiner, Sarah L / van Belzen, Martine J / Boogaard, Merel W / van Roon-Mom, Willeke M C / Rozing, Maarten P / van Hemert, Albert M / Smit, Johannes H / Beekman, Aartjan T F / van Grootheest, Gerard / Schoevers, Robert A / Oude Voshaar, Richard C / Roos, Raymund A C / Comijs, Hannie C / Penninx, Brenda W J H / van der Mast, Roos C / Aziz, N Ahmad. ·Departments of Neurology, Leiden University Medical Centre, Leiden, The Netherlands. · Departments of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands. · Departments of Clinical Genetics, and Leiden University Medical Centre, Leiden, The Netherlands. · Department of Public Health, Section of Social Medicine, University of Copenhagen, Copenhagen, Denmark. · Departments of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Psychiatry, and EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands. · Department of Psychiatry, University Medical Centre Groningen, Groningen, The Netherlands. · Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium. · Departments of Neurology, Leiden University Medical Centre, Leiden, The Netherlands. N.A.Aziz@lumc.nl. · Department of Neurodegenerative Disease, UCL Huntington's Disease Centre, University College London Institute of Neurology, London, United Kingdom. N.A.Aziz@lumc.nl. ·Transl Psychiatry · Pubmed #29225330.

ABSTRACT: Huntington disease (HD) is a severe neuropsychiatric disorder caused by a cytosine-adenine-guanine (CAG) repeat expansion in the HTT gene. Although HD is frequently complicated by depression, it is still unknown to what extent common HTT CAG repeat size variations in the normal range could affect depression risk in the general population. Using binary logistic regression, we assessed the association between HTT CAG repeat size and depression risk in two well-characterized Dutch cohorts─the Netherlands Study of Depression and Anxiety and the Netherlands Study of Depression in Older Persons─including 2165 depressed and 1058 non-depressed persons. In both cohorts, separately as well as combined, there was a significant non-linear association between the risk of lifetime depression and HTT CAG repeat size in which both relatively short and relatively large alleles were associated with an increased risk of depression (β = -0.292 and β = 0.006 for the linear and the quadratic term, respectively; both P < 0.01 after adjustment for the effects of sex, age, and education level). The odds of lifetime depression were lowest in persons with a HTT CAG repeat size of 21 (odds ratio: 0.71, 95% confidence interval: 0.52 to 0.98) compared to the average odds in the total cohort. In conclusion, lifetime depression risk was higher with both relatively short and relatively large HTT CAG repeat sizes in the normal range. Our study provides important proof-of-principle that repeat polymorphisms can act as hitherto unappreciated but complex genetic modifiers of depression.

3 Review Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder. 2017

Kessler, R C / van Loo, H M / Wardenaar, K J / Bossarte, R M / Brenner, L A / Ebert, D D / de Jonge, P / Nierenberg, A A / Rosellini, A J / Sampson, N A / Schoevers, R A / Wilcox, M A / Zaslavsky, A M. ·Department of Health Care Policy,Harvard Medical School,Boston, MA,USA. · Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE),University of Groningen, University Medical Center Groningen,Groningen,The Netherlands. · Department of Veterans Affairs,Office of Public Health,Washington, DC,USA. · VISN 19 Mental Illness Research Education and Clinical Center,University of Colorado,Anschutz Medical Campus,Anschulz, CO,USA. · Department of Psychiatry and Depression Clinical and Research Program,Harvard Medical School and Massachusetts General Hospital,Boston, MA,USA. · Department of Epidemiology,Janssen Research and Development,Titusville, NJ,USA. ·Epidemiol Psychiatr Sci · Pubmed #26810628.

ABSTRACT: BACKGROUNDS: Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful. METHOD: We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments. RESULTS: Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials. CONCLUSIONS: Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.

4 Review Treatment of depression with low-strength transcranial pulsed electromagnetic fields: A mechanistic point of view. 2016

van Belkum, S M / Bosker, F J / Kortekaas, R / Beersma, D G M / Schoevers, R A. ·University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC 30, P.O. Box 30.001, 9700 RB Groningen, The Netherlands. Electronic address: s.m.van.belkum@umcg.nl. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC 30, P.O. Box 30.001, 9700 RB Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC 30, P.O. Box 30.001, 9700 RB Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Neuroscience, P.O. Box 196, 9700 AD Groningen, The Netherlands. · Department Chronobiology, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC 30, P.O. Box 30.001, 9700 RB Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Research School of Behavioural and Cognitive Neurosciences (BCN), Interdisciplinary Center for Psychopathology and Emotion regulation (ICPE), CC 30, P.O. Box 30.001, 9700 RB Groningen, The Netherlands. ·Prog Neuropsychopharmacol Biol Psychiatry · Pubmed #27449361.

ABSTRACT: BACKGROUND: Mood disorders constitute a high burden for both patients and society. Notwithstanding the large arsenal of available treatment options, a considerable group of patients does not remit on current antidepressant treatment. There is an urgent need to develop alternative treatment strategies. Recently, low-strength transcranial pulsed electromagnetic field (tPEMF) stimulation has been purported as a promising strategy for such treatment-resistant depression (TRD). The mode of action of this new technique is however largely unknown. METHODS: We searched PubMed for literature reports on the effects of tPEMF and for information regarding its working mechanism and biological substrate. RESULTS: Most studies more or less connect with the major hypotheses of depression and concern the effects of tPEMF on brain metabolism, neuronal connectivity, brain plasticity, and the immune system. Relatively few studies paid attention to the possible chronobiologic effects of electromagnetic fields. LIMITATIONS: We reviewed the literature of a new and still developing field. Some of the reports involved translational studies, which inevitably limits the reach of the conclusions. CONCLUSION: Weak magnetic fields influence divergent neurobiological processes. The antidepressant effect of tPEMF may be specifically attributable to its effects on local brain activity and connectivity.

5 Review Oral ketamine for the treatment of pain and treatment-resistant depression†. 2016

Schoevers, Robert A / Chaves, Tharcila V / Balukova, Sonya M / aan het Rot, Marije / Kortekaas, Rudie. ·Robert A. Schoevers, MD PhD, Tharcila V. Chaves, MSc, Sonya M. Balukova, MSc, University of Groningen, University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), Interdisciplinary Center for Psychopathology and Emotion Regulation (ICPE), Groningen; Marije aan het Rot, PhD, Department of Psychology and Research School of Behavioral and Cognitive Neurosciences; Rudie Kortekaas, PhD, Department of Psychiatry, Interdisciplinary Center for Psychopathology and Emotion Regulation, Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands r.a.schoevers@umcg.nl. · Robert A. Schoevers, MD PhD, Tharcila V. Chaves, MSc, Sonya M. Balukova, MSc, University of Groningen, University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), Interdisciplinary Center for Psychopathology and Emotion Regulation (ICPE), Groningen; Marije aan het Rot, PhD, Department of Psychology and Research School of Behavioral and Cognitive Neurosciences; Rudie Kortekaas, PhD, Department of Psychiatry, Interdisciplinary Center for Psychopathology and Emotion Regulation, Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. ·Br J Psychiatry · Pubmed #26834167.

ABSTRACT: BACKGROUND: Recent studies with intravenous (i.v.) application of ketamine show remarkable but short-term success in patients with MDD. Studies in patients with chronic pain have used different ketamine applications for longer time periods. This experience may be relevant for psychiatric indications. AIMS: To review the literature about the dosing regimen, duration, effects and side-effects of oral, intravenous, intranasal and subcutaneous routes of administration of ketamine for treatment-resistant depression and pain. METHOD: Searches in PubMed with the terms 'oral ketamine', 'depression', 'chronic pain', 'neuropathic pain', 'intravenous ketamine', 'intranasal ketamine' and 'subcutaneous ketamine' yielded 88 articles. We reviewed all papers for information about dosing regimen, number of individuals who received ketamine, number of ketamine days per study, results and side-effects, as well as study quality. RESULTS: Overall, the methodological strength of studies investigating the antidepressant effects of ketamine was considered low, regardless of the route of administration. The doses for depression were in the lower range compared with studies that investigated analgesic use. Studies on pain suggested that oral ketamine may be acceptable for treatment-resistant depression in terms of tolerability and side-effects. CONCLUSIONS: Oral ketamine, given for longer time periods in the described doses, appears to be well tolerated, but few studies have systematically examined the longer-term negative consequences. The short- and longer-term depression outcomes as well as side-effects need to be studied with rigorous randomised controlled trials.

6 Review Daily symptom ratings for studying premenstrual dysphoric disorder: A review. 2016

Bosman, Renske C / Jung, Sophie E / Miloserdov, Kristina / Schoevers, Robert A / aan het Rot, Marije. ·Department of Psychology, University of Groningen, The Netherlands. Electronic address: r.bosman@ggzingeest.nl. · Department of Psychology, University of Groningen, The Netherlands. · School of Behavioural and Cognitive Neurosciences, University of Groningen, The Netherlands. · University of Groningen, University Medical Centre Groningen, Department of Psychiatry, Groningen, The Netherlands. · Department of Psychology, University of Groningen, The Netherlands; School of Behavioural and Cognitive Neurosciences, University of Groningen, The Netherlands. ·J Affect Disord · Pubmed #26406968.

ABSTRACT: BACKGROUND: To review how daily symptom ratings have been used in research into premenstrual dysphoric disorder (PMDD), and to discuss opportunities for the future. METHODS: PsycINFO and Medline were systematically searched, resulting in the inclusion of 75 studies in which (1) participants met the diagnostic criteria for late luteal phase dysphoric disorder (LLPDD) or PMDD and (2) diaries were used to study LLPDD/PMDD. RESULTS: To date, diaries have been used to gain insight into the aetiology and phenomenology of PMDD, to examine associated biological factors, and to assess treatment efficacy. We found low consistency among the diaries used, and often only part of the menstrual cycle was analysed instead of the whole menstrual cycle. We also observed that there was substantial variability in diagnostic procedures and criteria. LIMITATIONS: This review excluded diary studies conducted in women with premenstrual syndrome, women seeking help for premenstrual complaints without a clear diagnosis, and women without premenstrual complaints. CONCLUSIONS: Prospective daily ratings of symptoms and related variables provide a valuable and important tool in the study of PMDD. This paper addresses some options for improving the use of diaries and proposes the use of experience sampling and ecological momentary assessment to investigate within-person variability in symptoms in more detail.

7 Review Biomarker approaches in major depressive disorder evaluated in the context of current hypotheses. 2015

Jentsch, Mike C / Van Buel, Erin M / Bosker, Fokko J / Gladkevich, Anatoliy V / Klein, Hans C / Oude Voshaar, Richard C / Ruhé, Eric G / Eisel, Uli L M / Schoevers, Robert A. ·University of Groningen, University Medical Centre of Groningen, University Centre of Psychiatry, Groningen, The Netherlands. ·Biomark Med · Pubmed #25731213.

ABSTRACT: Major depressive disorder is a heterogeneous disorder, mostly diagnosed on the basis of symptomatic criteria alone. It would be of great help when specific biomarkers for various subtypes and symptom clusters of depression become available to assist in diagnosis and subtyping of depression, and to enable monitoring and prognosis of treatment response. However, currently known biomarkers do not reach sufficient sensitivity and specificity, and often the relation to underlying pathophysiology is unclear. In this review, we evaluate various biomarker approaches in terms of scientific merit and clinical applicability. Finally, we discuss how combined biomarker approaches in both preclinical and clinical studies can help to make the connection between the clinical manifestations of depression and the underlying pathophysiology.

8 Review Influence of personality on the outcome of treatment in depression: systematic review and meta-analysis. 2014

Newton-Howes, Giles / Tyrer, Peter / Johnson, Tony / Mulder, Roger / Kool, Simone / Dekker, Jack / Schoevers, Robert. · ·J Pers Disord · Pubmed #24256103.

ABSTRACT: There continues to be debate about the influence of personality disorder on the outcome of depressive disorders and is relative interactions with treatment. To determine whether personality disorder, both generically and in terms of individual clusters, leads to a worse outcome in patients with depressive disorders and whether this is influenced by type of treatment, a systematic electronic search of MEDLINE, CINAHL, and PsycINFO from 1966, 1982, and 1882, respectively, until February 2007 was undertaken. The keyword terms depression, mental illness, and personality disorder were used. All references were reviewed and personal correspondence was undertaken. Only English language papers were considered. Any English language paper studying a depressed adult population was considered for inclusion. Studies needed to clearly define depression and personality disorder using peer-reviewed instruments or International Classification of Disease/Diagnostic Statistical Manual criteria. Outcome assessment at greater than 3 weeks was necessary. Final inclusion papers were agreed on by consensus by at least two reviewers. All data were extracted using predetermined criteria for depression by at least two reviewers in parallel. Disagreement was settled by consensus. Complex data extraction was confirmed within the study group. Data were synthesized using log odds ratios in the Cochrane RevMan 5 program. The finding of comorbid personality disorder and depression was associated with a more than double the odds of a poor outcome for depression compared with those with no personality disorder (OR 2.16, CI 1.83-2.56). This effect was not ameliorated by the treatment modality used for the depressive disorder. This finding led to the conclusion that personality disorder has a negative impact on the outcome of depression. This finding is important in considering prognosis in depressive disorders.

9 Review Data-driven subtypes of major depressive disorder: a systematic review. 2012

van Loo, Hanna M / de Jonge, Peter / Romeijn, Jan-Willem / Kessler, Ronald C / Schoevers, Robert A. ·Department of Psychiatry, University Medical Center Groningen, Hanzeplein 1, Groningen, 9713 GZ, The Netherlands. ·BMC Med · Pubmed #23210727.

ABSTRACT: BACKGROUND: According to current classification systems, patients with major depressive disorder (MDD) may have very different combinations of symptoms. This symptomatic diversity hinders the progress of research into the causal mechanisms and treatment allocation. Theoretically founded subtypes of depression such as atypical, psychotic, and melancholic depression have limited clinical applicability. Data-driven analyses of symptom dimensions or subtypes of depression are scarce. In this systematic review, we examine the evidence for the existence of data-driven symptomatic subtypes of depression. METHODS: We undertook a systematic literature search of MEDLINE, PsycINFO and Embase in May 2012. We included studies analyzing the depression criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) of adults with MDD in latent variable analyses. RESULTS: In total, 1176 articles were retrieved, of which 20 satisfied the inclusion criteria. These reports described a total of 34 latent variable analyses: 6 confirmatory factor analyses, 6 exploratory factor analyses, 12 principal component analyses, and 10 latent class analyses. The latent class techniques distinguished 2 to 5 classes, which mainly reflected subgroups with different overall severity: 62 of 71 significant differences on symptom level were congruent with a latent class solution reflecting severity. The latent class techniques did not consistently identify specific symptom clusters. Latent factor techniques mostly found a factor explaining the variance in the symptoms depressed mood and interest loss (11 of 13 analyses), often complemented by psychomotor retardation or fatigue (8 of 11 analyses). However, differences in found factors and classes were substantial. CONCLUSIONS: The studies performed to date do not provide conclusive evidence for the existence of depressive symptom dimensions or symptomatic subtypes. The wide diversity of identified factors and classes might result either from the absence of patterns to be found, or from the theoretical and modeling choices preceding analysis.

10 Review [Staging and profiling of unipolar depression]. 2012

Peeters, F P M L / Ruhé, H G / Beekman, A T F / Spijker, J / Schoevers, R / Zitman, F / Schene, A. · ·Tijdschr Psychiatr · Pubmed #23138623.

ABSTRACT: BACKGROUND: Not only is the heterogeneous concept of depression too comprehensive, it is also insufficiently differentiated. This serves as a barrier to scientific research and obscures the symptoms that should indicate what treatment is required. AIM: To describe an accurate model for staging and profiling depression. METHOD: We placed depressive disorders in the context of the entire course of the disorder and we regarded the course as a continuum of psychopathology. RESULTS: First of all we distinguish five stages: (1) the prodromal phase, (2) the first depressive episode, (3) residual symptoms following an episode, (4) the relapse episode and (5) the chronic and/or treatment-resistant depression. The higher the stage, the greater the need for complex and specialised treatment. As characteristics for profiling we distinguish (a) aetiological and pathophysiological variables and (b) clinical factors. The latter are the ones that mainly influence treatment from stage 2 onwards. CONCLUSION: In our article we give a tentative overview of possible characteristics for profiling. At the moment the clinical factors are the ones used most for assessment. Current research into the value of aetiological characteristics for profiling will increase the applicability of a staging and profiling model.

11 Review Mood disorders in everyday life: a systematic review of experience sampling and ecological momentary assessment studies. 2012

aan het Rot, Marije / Hogenelst, Koen / Schoevers, Robert A. ·Department of Psychology, University of Groningen, Netherlands. m.aan.het.rot@rug.nl ·Clin Psychol Rev · Pubmed #22721999.

ABSTRACT: In the past two decades, the study of mood disorder patients using experience sampling methods (ESM) and ecological momentary assessment (EMA) has yielded important findings. In patients with major depressive disorder (MDD), the dynamics of their everyday mood have been associated with various aspects of their lives. To some degree similar studies have been conducted in patients with bipolar disorder (BD). In this paper we present the results of a systematic review of all ESM/EMA studies in MDD and BD to date. We focus not only on the correlates of patients' everyday mood but also on the impact on treatment, residual symptoms in remitted patients, on findings in pediatric populations, on MDD/BD specificity, and on links with neuroscience. After reviewing these six topics, we highlight the benefits of ESM/EMA for researchers, clinicians, and patients, and offer suggestions for future studies.

12 Review A systematic review of instruments to measure depressive symptoms in patients with schizophrenia. 2012

Lako, Irene M / Bruggeman, R / Knegtering, H / Wiersma, D / Schoevers, R A / Slooff, C J / Taxis, K. ·Rob Giel Research Center (RGOc), Department of Psychiatry (UCP), University Medical Center Groningen (UMCG), University of Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands. i.m.lako@umcg.nl ·J Affect Disord · Pubmed #22099566.

ABSTRACT: BACKGROUND: Depressive symptoms require accurate recognition and monitoring in clinical practice of patients with schizophrenia. Depression instruments developed for use in depressed patients may not discriminate depressive symptoms from negative psychotic symptoms. OBJECTIVE: We reviewed depression instruments on their reliability and validity in patients with schizophrenia. METHODOLOGY: A systematic literature search was carried out in three electronic databases. Psychometric properties were extracted for those instruments of which reliability, divergent, concurrent and predictive validity were reported in one or more publications. RESULTS: Forty-eight publications described the reliability and validity of six depression instruments in patients with schizophrenia. The only self-report was the Beck Depression Inventory (BDI). The Brief Psychiatric Rating Scale-Depression subscale (BPRS-D), Positive and Negative Syndrome Scale-Depression subscale (PANSS-D), Hamilton Rating Scale for Depression (HAMD), Montgomery Asberg Depression Rating Scale (MADRS) and Calgary Depression Scale for Schizophrenia (CDSS) were clinician rated. All instruments were reliable for the measurement of depressive symptoms in patients with schizophrenia. The CDSS most accurately differentiated depressive symptoms from other symptoms of schizophrenia (divergent validity), correlated well with other depression instruments (concurrent validity), and was least likely to miss cases of depression or misdiagnose depression (predictive validity). CONCLUSIONS: We would recommend to use the CDSS for the measurement of depressive symptoms in research and in daily clinical practice of patients with schizophrenia. A valid self-report instrument is to be developed for the use in clinical practice.

13 Review Managing the patient with co-morbid depression and an anxiety disorder. 2008

Schoevers, Robert A / Van, Henricus L / Koppelmans, Vincent / Kool, Simone / Dekker, Jack J. ·JellinekMentrum Mental Health Care Amsterdam, Amsterdam, the NetherlandsDepartment of Psychiatry, Medical Center, VU University, Amsterdam, the Netherlands. robert.schoevers@mentrum.nl ·Drugs · Pubmed #18681487.

ABSTRACT: Depression and anxiety disorders frequently co-occur. This type of co-morbidity is associated with higher severity, suicidality, chronicity and treatment resistance. However, available treatment guidelines mainly focus on treatment for singular disorders. The current paper describes diagnostic and treatment issues relevant for adequately addressing patients with depression and an anxiety disorder, using information from both guidelines and a search of recent literature. Apart from differential diagnosis, the diagnostic evaluation should include a thorough assessment of the symptoms of both disorders, preferably by using a structured clinical interview, and an assessment of depression severity in terms of suicidality, psychotic symptoms and impairment. Treatment should first address the primary disorder in terms of severity and risk. As a rule, severe depression should be treated before the anxiety disorder, using antidepressant medication or combined treatment (plus psychotherapy). In less severe pathology, the primary focus may be determined by examining the temporal pattern and the subjective burden of each disorder as experienced by the patient. Treatment is often sequential. Treatment of the primary disorder may or may not relieve the co-morbid disorder as well. If the primary disorder is an anxiety disorder, co-morbid depression generally implies earlier use of an antidepressant. Co-morbid mild depression may also react favourably to psychotherapeutic treatment of the anxiety disorder. Recent literature on concurrent treatment of both depression and anxiety shows that modern antidepressants such as sertraline, paroxetine, fluoxetine, venlafaxine, nefazodone and bupropion have demonstrated efficacy in relieving both depressive and anxiety symptoms compared with placebo. Head-to-head comparisons, although relatively scarce, tend to show superiority over tricyclic antidepressants. Venlafaxine was found to be more effective than fluoxetine in some studies. However, these results should be interpreted with caution because studies vary considerably in terms of patient selection, assessment of anxiety and primary outcome measures. Only one randomized controlled trial compared atypical antipsychotics with placebo. Psychotherapy was generally shown to have a beneficial effect on the co-morbid conditions, and available evidence appears to favour combined treatment. The results should be interpreted with caution because the number of studies on this issue was relatively small, with considerable clinical and methodological heterogeneity.

14 Review Predicting the outcome of antidepressants and psychotherapy for depression: a qualitative, systematic review. 2008

Van, Henricus L / Schoevers, Robert A / Dekker, Jack. ·Depression Research Group, Mentrum Mental Health Care, Amsterdam, The Netherlands. rien.van@mentrum.nl ·Harv Rev Psychiatry · Pubmed #18661365.

ABSTRACT: As treatment outcome in depression varies widely, it is important to understand better the predictive value of particular patient characteristics. However, qualitative systematic reviews of the association between easily identifiable patient characteristics and outcome for commonly used treatment options have been unavailable. This article provides an overview of the consistency of findings on the association between sociodemographic factors and depression characteristics, on the one hand, and outcomes of pharmacotherapy, cognitive-behavioral therapy, and interpersonal/psychodynamic psychotherapy for major depression, on the other. There were no findings indicating that gender was associated with treatment outcome in the case of tricyclic antidepressants. There are some indications that younger patients respond worse to tricyclics, whereas especially women appeared to have better outcomes with modern antidepressants (selective serotonin/norepinephrine reuptake inhibitors). Marital status may be related to better outcome in the case of antidepressants and cognitive-behavioral therapy. Longer duration of depression was identified as a negative predictor, most consistently in psychotherapy. In none of the treatment modalities was recurrence a negative predictor. The relation between severity of depression and outcome appeared to be complex, precluding any straightforward inferences.

15 Clinical Trial Combined sleep deprivation and light therapy: Clinical treatment outcomes in patients with complex unipolar and bipolar depression. 2019

Sikkens, D / Riemersma-Van der Lek, R F / Meesters, Y / Schoevers, R A / Haarman, B C M. ·University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC44,P.O. Box 30.001, 9700 RB Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC44,P.O. Box 30.001, 9700 RB Groningen, The Netherlands. Electronic address: b.c.m.haarman@rug.nl. ·J Affect Disord · Pubmed #30611915.

ABSTRACT: BACKGROUND: The combination of sleep deprivation and light therapy, called combined chronotherapy, may yield positive short- and long-term results, even in patients with treatment resistant depression (TRD). The implementation of combined chronotherapy in daily clinical practice is rare. This study describes the implementation and the effectiveness in a clinical setting. METHODS: Twenty six depressed patients with unipolar or bipolar depression received combined chronotherapy consisting of three nights of sleep deprivation with alternating recovery nights, light therapy, and continuation of antidepressant medication. Inventory of Depressive Symptoms C (IDS-C) scores were determined before chronotherapy and at week 1, 2, and 4. Paired t-tests were used to compare the IDS-C scores over time. RESULTS: The mean pre-treatment IDS-C score was 39.3 ± 9.6, the mean score in week 2 was 28.4 ± 10.2, and 28.6 ± 14.0 in week 4. A subsample of patients with psychiatric co-morbidities showed a reduction in depression severity from a mean score of 42.9 ± 11.0 to a mean score of 34.9 ± 13.0 after 4 weeks. The overall response rate was 34.6%, the remission rate 19.2%. LIMITATIONS: This open label case series has a relative small sample size and no control group CONCLUSION: In a clinical setting patients with major depressive disorder or bipolar disorder benefited significantly from combined chronotherapy. This chronotherapeutic intervention appears to have a rapid effect that lasts for at least several weeks, even in patients with psychiatric comorbidity or TRD. Indicating that chronotherapy can be a valuable treatment addition for depressed patients.

16 Article Comparative responsiveness of generic versus disorder-specific instruments for depression: An assessment in three longitudinal datasets. 2019

de Beurs, Edwin / Vissers, Ellen / Schoevers, Robert / Carlier, Ingrid V E / van Hemert, Albert M / Meesters, Ybe. ·Faculty of Clinical Psychology, Leiden University, Leiden, The Netherlands. · Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. ·Depress Anxiety · Pubmed #30188602.

ABSTRACT: BACKGROUND: Routine outcome monitoring (ROM) may enhance individual treatment and is also advocated as a means to compare the outcome of different treatment programs or providers. There is debate on the optimal instruments to be used for these separate tasks. METHODS: Three sets with longitudinal data from ROM were analyzed with correlational analysis and repeated measures ANOVAs, allowing for a head-to-head comparison of measures regarding their sensitivity to detect change. The responsiveness of three disorder-specific instruments, the Beck Depression Inventory, the Inventory of Depressive Symptoms, and the Mood and Anxiety Symptoms Questionnaire, was compared to three generic instruments, the Symptom Checklist (SCL-90), the Outcome Questionnaire (OQ-45), and the Brief Symptom Inventory, respectively. RESULTS: In two of the three datasets, disorder-specific measures were more responsive compared to the total score on generic instruments. Subscale scores for depression embedded within generic instruments are second best and almost match disorder-specific scales in responsiveness. No evidence of a desynchronous response on outcome measures was found. LIMITATIONS: The present study compares measures head-to-had, and responsiveness is not assessed against an external criterion, such as clinical recovery. DISCUSSION: Disorder-specific measures yield the most precise assessment for individual treatment and are recommended for clinical use. Generic measures may allow for comparisons across diagnostic groups and their embedded subscales approach the responsiveness of disorder-specific measures.

17 Article Can chronotype function as predictor of a persistent course of depressive and anxiety disorder? 2019

Druiven, S J M / Knapen, S E / Penninx, B W J H / Antypa, N / Schoevers, R A / Riese, H / Meesters, Y. ·University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), Groningen, The Netherlands. Electronic address: sjmdruiven@gmail.com. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), Groningen, The Netherlands. · VU University Medical Center, Department of Psychiatry/EMGO+ Institute, Amsterdam, The Netherlands. · Leiden University, Department of Clinical Psychology, Institute of Psychology, Leiden, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands. ·J Affect Disord · Pubmed #30179789.

ABSTRACT: BACKGROUND: The role of chronotype, the individual timing of sleep/activity, has been studied in relation to depressive and anxiety disorders. A cross-sectional association between a depressive episode and evening-type has been identified. However, until now the predicting capacity of chronotype concerning persistence of psychiatric disorders remains unclear. Our aim is to examine whether a later chronotype in patients with a depressive and/or anxiety disorder can serve as a predictor of a persistent course. METHODS: A subsample of patients with a depressive and/or anxiety disorder diagnosis and chronotype data of the longitudinal Netherlands Study of Depression and Anxiety (NESDA) was used. Diagnosis of depressive and anxiety disorders (1-month DSM-IV based diagnosis) were determined at baseline (n = 505). From this group persistence was determined at 2-year (FU2) (persistent course: n = 248, non-persistent course: n = 208) and 4-year follow-up (FU4) (persistent course: n = 151, non-persistent course: n = 264). Chronotype was assessed at baseline with the Munich Chronotype Questionnaire. RESULTS: A later chronotype did not predict a persistent course of depressive and/or anxiety disorder at FU2 (OR (95% CI) = 0.99 (0.83-1.19), P = 0.92) or at FU4 (OR (95% CI) = 0.94 (0.77-1.15), P = 0.57). LIMITATIONS: Persistence was defined as having a diagnosis of depressive and/or anxiety disorder at the two-year and four-year follow-up, patients may have remitted and relapsed between assessments. CONCLUSION: Chronotype, measured as actual sleep timing, of patients with a depressive or anxiety disorder did not predict a persistent course which suggests it might be unsuitable as predictive tool in clinical settings.

18 Article Body attitude, body satisfaction and body awareness in a clinical group of depressed patients: An observational study on the associations with depression severity and the influence of treatment. 2019

Scheffers, M / van Duijn, M A J / Beldman, M / Bosscher, R J / van Busschbach, J T / Schoevers, R A. ·School of Human Movement and Education,Windesheim University of Applied Sciences, Campus 2-6, Zwolle, CA 8017, The Netherlands. Electronic address: wj.scheffers@windesheim.nl. · Department of Sociology, University of Groningen, Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, University Center of Psychiatry, The Netherlands. · School of Human Movement and Education,Windesheim University of Applied Sciences, Campus 2-6, Zwolle, CA 8017, The Netherlands. · School of Human Movement and Education,Windesheim University of Applied Sciences, Campus 2-6, Zwolle, CA 8017, The Netherlands; Rob Giel Research center (RGOc), University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Groningen, The Netherlands. · Research School of Behavioural and Cognitive Neurosciences (BCN), Interdisciplinary Center for Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Groningen, The Netherlands. ·J Affect Disord · Pubmed #30170235.

ABSTRACT: BACKGROUND: Apart from changes in mood and cognition, depressive disorders are also characterized by changes in body experience, changes that largely influence daily functioning and aggravate distress. In order to gain more insight into this important issue, three domains of body experience - body attitude, body satisfaction and body awareness - and their associations with symptom severity of depression were studied pre- and post-treatment in a clinical sample of depressed patients in a multidisciplinary setting. METHODS: Body attitude (Dresden Body Image Questionnaire), body satisfaction (Body Cathexis Scale), body awareness (Somatic Awareness Questionnaire) and severity of depressive symptoms (Inventory of Depressive Symptomatology) were measured. Differences between pre-treatment and post-treatment scores were studied with paired t-tests. Associations between body experience and depression were analysed with Pearson correlations and partial correlations. RESULTS: At the start of treatment, patients scored significantly lower than a healthy comparison sample on body attitude and body satisfaction, but not on body awareness. After treatment, depression scores decreased with large effect sizes, scores for body attitude and body satisfaction increased with medium effect sizes and body awareness scores increased slightly. Medium pre-treatment and strong post-treatment associations were found between depression severity and body attitude and between depression severity and body satisfaction. LIMITATIONS: The design does not allow to draw causal conclusions. Because of the multidisciplinary treatment no information is available on the specific contribution of interventions targeting body experience. CONCLUSIONS: The study provides evidence for medium to strong associations in clinically depressed patients between body attitude, body satisfaction and depression.

19 Article Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach. 2018

Dinga, Richard / Marquand, Andre F / Veltman, Dick J / Beekman, Aartjan T F / Schoevers, Robert A / van Hemert, Albert M / Penninx, Brenda W J H / Schmaal, Lianne. ·Department of Psychiatry and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. · Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands. · Department of Neuroimaging, Institute of Psychiatry, King's College London, London, United Kingdom. · University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), University of Groningen, Groningen, The Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Department of Psychiatry and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. lianne.schmaal@unimelb.edu.au. · Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia. lianne.schmaal@unimelb.edu.au. · Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia. lianne.schmaal@unimelb.edu.au. ·Transl Psychiatry · Pubmed #30397196.

ABSTRACT: Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psychological, and biological characteristics for predicting the course of depression and aimed to identify the best set of predictors. Eight hundred four unipolar depressed patients (major depressive disorder or dysthymia) patients were assessed on a set involving 81 demographic, clinical, psychological, and biological measures and were clinically followed-up for 2 years. Subjects were grouped according to (i) the presence of a depression diagnosis at 2-year follow-up (yes n = 397, no n = 407), and (ii) three disease course trajectory groups (rapid remission, n = 356, gradual improvement n = 273, and chronic n = 175) identified by a latent class growth analysis. A penalized logistic regression, followed by tight control over type I error, was used to predict depression course and to evaluate the prognostic value of individual variables. Based on the inventory of depressive symptomatology (IDS), we could predict a rapid remission course of depression with an AUROC of 0.69 and 62% accuracy, and the presence of an MDD diagnosis at follow-up with an AUROC of 0.66 and 66% accuracy. Other clinical, psychological, or biological variables did not significantly improve the prediction. Among the large set of variables considered, only the IDS provided predictive value for course prediction on an individual level, although this analysis represents only one possible methodological approach. However, accuracy of course prediction was moderate at best and further improvement is required for these findings to be clinically useful.

20 Article [Complete recovery from depression is the exception rather than the rule: prognosis of depression beyond diagnostic boundaries]. 2018

Verhoeven, Josine E / Verduijn, Judith / Schoevers, Robert A / van Hemert, Albert M / Beekman, Aartjan T F / Penninx, Brenda W J H. ·VUmc, afd. Psychiatrie/GGZ inGeest, Amsterdam. · Contact: J.E. Verhoeven (j.verhoeven@ggzingeest.nl). · UMCG-Rijksuniversiteit Groningen, afd. Psychiatrie. · LUMC, afd. Psychiatrie, Leiden. ·Ned Tijdschr Geneeskd · Pubmed #30306757.

ABSTRACT: OBJECTIVE: To investigate whether the course of depression changes when (a) follow-up duration is longer and (b) in addition to depression other mood and anxiety disorders are considered as outcome measures. DESIGN: Longitudinal observational cohort study. METHOD: We selected patients from the Netherlands Study of Depression and Anxiety (NESDA) who had active depression at baseline (n=903) and for whom data from the 2, 4 and/or 6 year measurements were available. Using DSM-IV diagnoses and data from the 'Life chart interview', we divided participants in one of the following four course categories: (1) recovered (no diagnosis at 2-year measurement or later), (2) recurring without chronic episodes, (3) recurring with chronic episodes or (4) consistent chronic depression since baseline. We looked at the distribution of patients over the course categories from a short, diagnostically narrow perspective (over 2 years, only looking at depression) to a long, diagnostically broad perspective (over 6 years, looking at depression, dysthymia, hypomania, mania and anxiety). RESULTS: In the short, diagnostically narrow perspective, 58% of participants had recovered and 21% met the criteria for a chronic episode. In the long, diagnostically broad perspective however, only 17% had recovered while 55% had chronic episodes. CONCLUSION: Monitoring patients with depression over a longer period and with broader outcome measures (depression and related psychiatric disorders belonging to the mood disorder spectrum) shows that the course of depression is unfavourable and chronic for the majority. Conceptualising depression as a defined episodic disorder underestimates the severity of the prognosis for many patients and, as a consequence, the type of care indicated.

21 Article Self-monitoring and personalized feedback based on the experiencing sampling method as a tool to boost depression treatment: a protocol of a pragmatic randomized controlled trial (ZELF-i). 2018

Bastiaansen, Jojanneke A / Meurs, Maaike / Stelwagen, Renee / Wunderink, Lex / Schoevers, Robert A / Wichers, Marieke / Oldehinkel, Albertine J. ·University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, Groningen, The Netherlands. j.bastiaansen@umcg.nl. · Friesland Mental Health Care Services, Department of Education and Research, Leeuwarden, The Netherlands. j.bastiaansen@umcg.nl. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation, Groningen, The Netherlands. · Friesland Mental Health Care Services, Department of Education and Research, Leeuwarden, The Netherlands. ·BMC Psychiatry · Pubmed #30176845.

ABSTRACT: BACKGROUND: Depression is a leading cause of disability worldwide. To reduce the societal burden and improve quality of life for individual patients, treatments for depression need to be optimized. There is a particular need for person-tailored interventions that reinforce self-management of patients. Systematic self-monitoring and personalized feedback through the Experience Sampling Method (ESM) could provide such a person-tailored, empowering intervention that enhances treatment outcomes. The primary aim of this study is to investigate the efficacy of self-monitoring and personalized feedback as an add-on tool in the treatment of depressive complaints in a natural setting. METHODS: The ZELF-i study is a pragmatic multi-site randomized controlled trial (RCT). We aim to recruit 150 individuals with depressive symptoms aged between 18 and 65 years, who have an intake for outpatient basic or specialized treatment at a mental health care organization in the North of the Netherlands. After the intake, participants will be randomly allocated to one of three study arms: two experimental groups engaging in 28 days of systematic self-monitoring (5 times per day) and receiving weekly personalized feedback on positive affect and activities ("Do"-module) or on negative affect and thinking patterns ("Think"-module), and a control group receiving no additional intervention. Self-report inventories of depressive symptoms, psychosocial functioning and feelings of empowerment will be administered before and after the intervention period, and at follow-up measurements at 1, 2, 3 and 6 months. The patient-experienced utility of the intervention will be investigated by a combination of quantitative and qualitative research methods. DISCUSSION: The present study is the first to examine the effects of add-on self-monitoring and personalized feedback on depressive complaints in clinical practice. It is also the first to evaluate two different ESM modules targeted at both of depression's core symptoms. Lastly, it is the first study that uses a combination of qualitative and quantitative methods to evaluate the patient-experienced utility of ESM with personalized feedback as an intervention for depression. Results of the present study may improve treatment for depression, if the intervention is found to be effective. TRIAL REGISTRATION: Dutch Trial Register, NTR5707 , registered prospectively 1 February 2016.

22 Article N-acetylcysteine as add-on to antidepressant medication in therapy refractory major depressive disorder patients with increased inflammatory activity: study protocol of a double-blind randomized placebo-controlled trial. 2018

Yang, Chenghao / Bosker, Fokko J / Li, Jie / Schoevers, Robert A. ·Tianjin Mental Health Institute, Tianjin Anding Hospital, No.13 Liulin Road, Hexi District, Tianjin, China. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Hanzeplein 1, 9700 RB, Groningen, the Netherlands. · University of Groningen, Research School Behavioural and Cognitive Neurosciences (BCN), Hanzeplein 1, 9700 RB, Groningen, the Netherlands. · Tianjin Mental Health Institute, Tianjin Anding Hospital, No.13 Liulin Road, Hexi District, Tianjin, China. jieli@tjmhc.com. ·BMC Psychiatry · Pubmed #30176835.

ABSTRACT: BACKGROUND: A subgroup of depressed patients with increased inflammatory activity was shown to be more susceptible to develop Treatment Resistant Depression (TRD). Earlier studies with anti-inflammatory drugs have shown benefits in the treatment of major depressive disorder (MDD), but the effects are expected to be higher in patients with increased inflammatory activity. Supplementation of N-acetylcysteine (NAC) to ongoing antidepressant therapy may positively influence outcome of depression treatment in these patients. Therefore, this study aims to investigate the efficacy of NAC supplementation in patients with insufficient response to standard antidepressant treatment, and to explore potential roles of inflammation and oxidative stress involved in the alleged pathophysiological processes of TRD. METHODS/DESIGN: A double-blind randomized placebo-controlled study comparing NAC versus placebo as add-on medication to antidepressant treatment with 12-week treatment and 8-week follow up in patients with TRD and increased inflammatory activity. Apart from clinical efficacy defined as the change in Hamilton Depression Rating Scale (HAMD)-17 score, secondary outcomes include changes in pathophysiological mechanisms related to depression as well as changes in local brain activity (functional Magnetic Resonance Imaging, fMRI) and white matter integrity (Diffusion Tensor Imaging, DTI). Importantly, sole patients with CRP levels with values between 0.85 and 10 mg/L will be included. DISCUSSION: This is the first clinical trial taking both TRD and increased inflammatory activity as inclusion criteria. This study will provide reliable evidence for the efficacy of NAC in patients with TRD displaying increased inflammatory activity. And this study also will help explore further the roles of inflammation and oxidative stress involved in the alleged pathophysiological processes of TRD. TRIAL REGISTRATION: The trial protocol has been registered on "ClinicalTrials.gov"with protocol ID "NAC-2015-TJAH" and ClinicalTrials.gov ID " NCT02972398 ".

23 Article Monitoring of somatic parameters at outpatient departments for mood and anxiety disorders. 2018

Simoons, Mirjam / Mulder, Hans / Doornbos, Bennard / Schoevers, Robert A / van Roon, Eric N / Ruhé, Henricus G. ·Department of Clinical Pharmacy, Wilhelmina Hospital Assen, Assen, The Netherlands. · Department of Psychiatry, Interdisciplinary Centre for Psychopathology and Emotion regulation, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands. · Department of Pharmacotherapy, -Epidemiology & -Economics, Department of Pharmacy, University of Groningen, Groningen, The Netherlands. · Mental Health Services Drenthe, Assen, The Netherlands. · Department of Clinical Pharmacy and Clinical Pharmacology, Medical Centre Leeuwarden, Leeuwarden, The Netherlands. · Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom. ·PLoS One · Pubmed #30130372.

ABSTRACT: INTRODUCTION: Somatic complications account for the majority of the 13-30 years shortened life expectancy in psychiatric patients compared to the general population. The study aim was to assess to which extent patients visiting outpatient departments for mood and anxiety disorders were monitored for relevant somatic comorbidities and (adverse) effects of psychotropic drugs-more specifically a) metabolic parameters, b) lithium safety and c) ECGs-during their treatment. METHODS: We performed a retrospective clinical records review and cross-sectional analysis to assess the extent of somatic monitoring at four outpatient departments for mood and anxiety disorders in The Netherlands. We consecutively recruited adult patients visiting a participating outpatient department between March and November 2014. The primary outcome was percentage of patients without monitoring measurements. Secondary outcomes were number of measurements per parameter per patient per year and time from start of treatment to first measurement. RESULTS: We included 324 outpatients, of whom 60.2% were female. Most patients were treated for depressive disorders (39.8%), anxiety disorders (16.7%) or bipolar or related disorders (11.7%) and 198 patients (61.1%) used at least one psychotropic drug. For 186 patients (57.4%), no monitoring records were recorded (median treatment period 7.3 months, range 0-55.6). The median number of measurements per parameter per year since the start of outpatient treatment for patients with monitoring measurements was 0.31 (range 0.0-12.9). The median time to first monitoring measurement per parameter for patients with monitoring measurements was 3.8 months (range 0.0-50.7). DISCUSSION: Somatic monitoring in outpatients with mood and anxiety disorders is not routine clinical practice. Monitoring practices need to be improved to prevent psychiatric outpatients from undetected somatic complications.

24 Article Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. 2018

Wray, Naomi R / Ripke, Stephan / Mattheisen, Manuel / Trzaskowski, Maciej / Byrne, Enda M / Abdellaoui, Abdel / Adams, Mark J / Agerbo, Esben / Air, Tracy M / Andlauer, Till M F / Bacanu, Silviu-Alin / Bækvad-Hansen, Marie / Beekman, Aartjan F T / Bigdeli, Tim B / Binder, Elisabeth B / Blackwood, Douglas R H / Bryois, Julien / Buttenschøn, Henriette N / Bybjerg-Grauholm, Jonas / Cai, Na / Castelao, Enrique / Christensen, Jane Hvarregaard / Clarke, Toni-Kim / Coleman, Jonathan I R / Colodro-Conde, Lucía / Couvy-Duchesne, Baptiste / Craddock, Nick / Crawford, Gregory E / Crowley, Cheynna A / Dashti, Hassan S / Davies, Gail / Deary, Ian J / Degenhardt, Franziska / Derks, Eske M / Direk, Nese / Dolan, Conor V / Dunn, Erin C / Eley, Thalia C / Eriksson, Nicholas / Escott-Price, Valentina / Kiadeh, Farnush Hassan Farhadi / Finucane, Hilary K / Forstner, Andreas J / Frank, Josef / Gaspar, Héléna A / Gill, Michael / Giusti-Rodríguez, Paola / Goes, Fernando S / Gordon, Scott D / Grove, Jakob / Hall, Lynsey S / Hannon, Eilis / Hansen, Christine Søholm / Hansen, Thomas F / Herms, Stefan / Hickie, Ian B / Hoffmann, Per / Homuth, Georg / Horn, Carsten / Hottenga, Jouke-Jan / Hougaard, David M / Hu, Ming / Hyde, Craig L / Ising, Marcus / Jansen, Rick / Jin, Fulai / Jorgenson, Eric / Knowles, James A / Kohane, Isaac S / Kraft, Julia / Kretzschmar, Warren W / Krogh, Jesper / Kutalik, Zoltán / Lane, Jacqueline M / Li, Yihan / Li, Yun / Lind, Penelope A / Liu, Xiaoxiao / Lu, Leina / MacIntyre, Donald J / MacKinnon, Dean F / Maier, Robert M / Maier, Wolfgang / Marchini, Jonathan / Mbarek, Hamdi / McGrath, Patrick / McGuffin, Peter / Medland, Sarah E / Mehta, Divya / Middeldorp, Christel M / Mihailov, Evelin / Milaneschi, Yuri / Milani, Lili / Mill, Jonathan / Mondimore, Francis M / Montgomery, Grant W / Mostafavi, Sara / Mullins, Niamh / Nauck, Matthias / Ng, Bernard / Nivard, Michel G / Nyholt, Dale R / O'Reilly, Paul F / Oskarsson, Hogni / Owen, Michael J / Painter, Jodie N / Pedersen, Carsten Bøcker / Pedersen, Marianne Giørtz / Peterson, Roseann E / Pettersson, Erik / Peyrot, Wouter J / Pistis, Giorgio / Posthuma, Danielle / Purcell, Shaun M / Quiroz, Jorge A / Qvist, Per / Rice, John P / Riley, Brien P / Rivera, Margarita / Saeed Mirza, Saira / Saxena, Richa / Schoevers, Robert / Schulte, Eva C / Shen, Ling / Shi, Jianxin / Shyn, Stanley I / Sigurdsson, Engilbert / Sinnamon, Grant B C / Smit, Johannes H / Smith, Daniel J / Stefansson, Hreinn / Steinberg, Stacy / Stockmeier, Craig A / Streit, Fabian / Strohmaier, Jana / Tansey, Katherine E / Teismann, Henning / Teumer, Alexander / Thompson, Wesley / Thomson, Pippa A / Thorgeirsson, Thorgeir E / Tian, Chao / Traylor, Matthew / Treutlein, Jens / Trubetskoy, Vassily / Uitterlinden, André G / Umbricht, Daniel / Van der Auwera, Sandra / van Hemert, Albert M / Viktorin, Alexander / Visscher, Peter M / Wang, Yunpeng / Webb, Bradley T / Weinsheimer, Shantel Marie / Wellmann, Jürgen / Willemsen, Gonneke / Witt, Stephanie H / Wu, Yang / Xi, Hualin S / Yang, Jian / Zhang, Futao / Anonymous9151162 / Anonymous9161162 / Arolt, Volker / Baune, Bernhard T / Berger, Klaus / Boomsma, Dorret I / Cichon, Sven / Dannlowski, Udo / de Geus, E C J / DePaulo, J Raymond / Domenici, Enrico / Domschke, Katharina / Esko, Tõnu / Grabe, Hans J / Hamilton, Steven P / Hayward, Caroline / Heath, Andrew C / Hinds, David A / Kendler, Kenneth S / Kloiber, Stefan / Lewis, Glyn / Li, Qingqin S / Lucae, Susanne / Madden, Pamela F A / Magnusson, Patrik K / Martin, Nicholas G / McIntosh, Andrew M / Metspalu, Andres / Mors, Ole / Mortensen, Preben Bo / Müller-Myhsok, Bertram / Nordentoft, Merete / Nöthen, Markus M / O'Donovan, Michael C / Paciga, Sara A / Pedersen, Nancy L / Penninx, Brenda W J H / Perlis, Roy H / Porteous, David J / Potash, James B / Preisig, Martin / Rietschel, Marcella / Schaefer, Catherine / Schulze, Thomas G / Smoller, Jordan W / Stefansson, Kari / Tiemeier, Henning / Uher, Rudolf / Völzke, Henry / Weissman, Myrna M / Werge, Thomas / Winslow, Ashley R / Lewis, Cathryn M / Levinson, Douglas F / Breen, Gerome / Børglum, Anders D / Sullivan, Patrick F / Anonymous9171162. ·Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia. naomi.wray@uq.edu.au. · Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia. naomi.wray@uq.edu.au. · Medical and Population Genetics, Broad Institute, Cambridge, MA, USA. · Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. · Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany. · Department of Biomedicine, Aarhus University, Aarhus, Denmark. · iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark. · iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. · Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. · Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia. · Department of Biological Psychology and EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Division of Psychiatry, University of Edinburgh, Edinburgh, UK. · Centre for Integrated Register-Based Research, Aarhus University, Aarhus, Denmark. · National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark. · Discipline of Psychiatry, University of Adelaide, Adelaide, South Australia, Australia. · Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany. · Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. · Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. · Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark. · Department of Psychiatry, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands. · Virginia Institute for Psychiatric and Behavior Genetics, Richmond, VA, USA. · Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. · Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark. · Statistical Genomics and Systems Genetics, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. · Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK. · Department of Psychiatry, University Hospital of Lausanne, Prilly, Switzerland. · MRC Social Genetic and Developmental Psychiatry Centre, King's College London, London, UK. · Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia. · Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia. · Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia. · Psychological Medicine, Cardiff University, Cardiff, UK. · Center for Genomic and Computational Biology, Duke University, Durham, NC, USA. · Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC, USA. · Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. · Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. · Institute of Human Genetics, University of Bonn, Bonn, Germany. · Life & Brain Center, Department of Genomics, University of Bonn, Bonn, Germany. · Psychiatry, Dokuz Eylul University School of Medicine, Izmir, Turkey. · Epidemiology, Erasmus MC, Rotterdam, The Netherlands. · Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA. · Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA. · Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA. · Research, 23andMe, Inc., Mountain View, CA, USA. · Neuroscience and Mental Health, Cardiff University, Cardiff, UK. · Bioinformatics, University of British Columbia, Vancouver, British Columbia, Canada. · Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. · Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA. · Department of Psychiatry (UPK), University of Basel, Basel, Switzerland. · Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, Switzerland. · Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. · Department of Psychiatry, Trinity College Dublin, Dublin, Ireland. · Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. · Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA. · Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. · Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. · Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, UK. · University of Exeter Medical School, Exeter, UK. · Danish Headache Centre, Department of Neurology, Rigshospitalet, Glostrup, Denmark. · Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark. · iPSYCH, Lundbeck Foundation Initiative for Psychiatric Research, Copenhagen, Denmark. · Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia. · Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Germany. · Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland. · Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA. · Statistics, Pfizer Global Research and Development, Groton, CT, USA. · Max Planck Institute of Psychiatry, Munich, Germany. · Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA. · Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA. · Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA. · Psychiatry and Behavioral Sciences, University of Southern California, Los Angeles, CA, USA. · Informatics Program, Boston Children's Hospital, Boston, MA, USA. · Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. · Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. · Department of Endocrinology at Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark. · Swiss Institute of Bioinformatics, Lausanne, Switzerland. · Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne, Lausanne, Switzerland. · Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA. · Mental Health, NHS 24, Glasgow, UK. · Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. · Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany. · Statistics, University of Oxford, Oxford, UK. · Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA. · School of Psychology and Counseling, Queensland University of Technology, Brisbane, Queensland, Australia. · Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, South Brisbane, Queensland, Australia. · Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia. · Estonian Genome Center, University of Tartu, Tartu, Estonia. · Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada. · Statistics, University of British Columbia, Vancouver, British Columbia, Canada. · DZHK (German Centre for Cardiovascular Research), partner site Greifswald, University Medicine, University Medicine Greifswald, Greifswald, Germany. · Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. · Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia. · Humus, Reykjavik, Iceland. · MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. · Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. · Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. · Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA. · Solid Biosciences, Boston, MA, USA. · Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA. · Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain. · Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Department of Psychiatry and Psychotherapy, Medical Center of the University of Munich, Campus Innenstadt, Munich, Germany. · Institute of Psychiatric Phenomics and Genomics (IPPG), Medical Center of the University of Munich, Campus Innenstadt, Munich, Germany. · Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. · Behavioral Health Services, Kaiser Permanente Washington, Seattle, WA, USA. · Faculty of Medicine, Department of Psychiatry, University of Iceland, Reykjavik, Iceland. · School of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia. · Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. · deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. · Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA. · College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK. · Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany. · Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. · KG Jebsen Centre for Psychosis Research, Norway Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. · Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA. · Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, UK. · Clinical Neurosciences, University of Cambridge, Cambridge, UK. · Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. · Roche Pharmaceutical Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases Discovery and Translational Medicine Area, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland. · Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. · Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, MA, USA. · Department of Psychiatry, University of Münster, Munster, Germany. · Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany. · Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland. · Amsterdam Public Health Institute, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. · Centre for Integrative Biology, Università degli Studi di Trento, Trento, Italy. · Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany. · Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, USA. · MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK. · Centre for Addiction and Mental Health, Toronto, Ontario, Canada. · Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. · Division of Psychiatry, University College London, London, UK. · Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, USA. · Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. · Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark. · Institute of Translational Medicine, University of Liverpool, Liverpool, UK. · Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark. · Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, CT, USA. · Psychiatry, Harvard Medical School, Boston, MA, USA. · Psychiatry, University of Iowa, Iowa City, IA, USA. · Human Genetics Branch, NIMH Division of Intramural Research Programs, Bethesda, MD, USA. · Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany. · Faculty of Medicine, University of Iceland, Reykjavik, Iceland. · Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, The Netherlands. · Psychiatry, Erasmus MC, Rotterdam, The Netherlands. · Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada. · Division of Epidemiology, New York State Psychiatric Institute, New York, NY, USA. · Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. · Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Cambridge, MA, USA. · Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. · Department of Medical and Molecular Genetics, King's College London, London, UK. · Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. · NIHR BRC for Mental Health, King's College London, London, UK. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. pfsulliv@med.unc.edu. · Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. pfsulliv@med.unc.edu. · Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. pfsulliv@med.unc.edu. ·Nat Genet · Pubmed #29700475.

ABSTRACT: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

25 Article Effects of a lifestyle intervention on psychosocial well-being of severe mentally ill residential patients: ELIPS, a cluster randomized controlled pragmatic trial. 2018

Stiekema, Annemarie P M / Looijmans, Anne / van der Meer, Lisette / Bruggeman, Richard / Schoevers, Robert A / Corpeleijn, Eva / Jörg, Frederike. ·Department of Rehabilitation, Lentis Psychiatric Institute, Zuidlaren, The Netherlands; School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, Maastricht, The Netherlands. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Rob Giel Research Center, Groningen, The Netherlands. Electronic address: A.Looijmans@umcg.nl. · Department of Rehabilitation, Lentis Psychiatric Institute, Zuidlaren, The Netherlands; University of Groningen, University Medical Center Groningen, Rob Giel Research Center, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Neuroscience, Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Rob Giel Research Center, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Groningen, The Netherlands. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · University of Groningen, University Medical Center Groningen, Rob Giel Research Center, Groningen, The Netherlands; Research Department, Friesland Mental Health Services, Leeuwarden, The Netherlands. ·Schizophr Res · Pubmed #29503230.

ABSTRACT: Large studies investigating the psychosocial effects of lifestyle interventions in patients with a severe mental illness (SMI) are scarce, especially in residential patients. This large, randomized controlled, multicentre pragmatic trial assessed the psychosocial effects of a combined diet-and-exercise lifestyle intervention targeting the obesogenic environment of SMI residential patients. Twenty-nine sheltered and clinical care teams were randomized into intervention (n=15) or control (n=14) arm. Team tailored diet-and-exercise lifestyle plans were set up to change the obesogenic environment into a healthier setting, and team members were trained in supporting patients to make healthier choices. The control group received care-as-usual. The Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), Health of the Nation Outcome Scales (HoNOS) and the Manchester Short Assessment of Quality of Life (MANSA) were assessed at baseline and after three and twelve months. Data were available for 384 intervention and 386 control patients (48.6±12.5years old, 62.7% males, 73.7% psychotic disorder). Linear mixed model analysis showed no psychosocial improvements in the intervention group compared to care-as-usual; the intervention group showed a slightly reduced quality of life (overall) and a small increase in depressive symptoms (clinical care facilities) and psychotic symptoms (sheltered facilities). This may be due to difficulties with implementation, the intervention not being specifically designed for improvements in mental well-being, or the small change approach, which may take longer to reach an effect. Further research might elucidate what type of lifestyle intervention under what circumstances positively affects psychosocial outcomes in this population.

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