Two-year course of depressive and anxiety disorders: Results from the Netherlands Study of Depression and Anxiety (NESDA)

Penninx, Brenda W. J. H.; Nolen, Willem A.; Lamers, Femke; Zitman, Frans G.; Smit, Johannes H.; Spinhoven, Philip; Cuijpers, Pim; Jong, Peter J. de; Marwijk, Harm van; Meer, Klaas van der; Verhaak, Peter; Laurant, Miranda; Graaf, Ron de; Hoogendijk, Witte J.G.; Wee, Nic van der; Ormel, Johan; Dyck, Richard van; Beekman, Aartjan T.F.

doi:10.1016/j.jad.2011.03.027

Cited by 304 publications

(272 citation statements)

References 39 publications

Supporting

Mentioning

251

Contrasting

Unclassified

Order By: Relevance

“…When these disorders co‐occur, the chronicity and functional impairments rise substantially 16, 17, 18. Yet, even though social dysfunction is among the most pervasive and debilitating symptoms of affective psychopathology and tends to persist long after remission, a thorough examination of social functioning in clinically anxious or depressed patients, as well in those presenting comorbidity and those in remission, is currently lacking 19, 20, 21, 22.…”

Section: Introductionmentioning

confidence: 99%

Social functioning in patients with depressive and anxiety disorders

Saris

Aghajani

Werff

et al. 2017

Acta Psychiatr Scand

149

View full text Add to dashboard Cite

ObjectiveAdaptive social functioning is severely impeded in depressive and anxiety disorders, even after remission. However, a comprehensive overview is still lacking.MethodUsing data from the Netherlands Study of Depression and Anxiety (NESDA), behavioural (network size, social activities, social support) and affective (loneliness, affiliation, perceived social disability) indicators of social functioning were analyzed in patients with anxiety (N = 540), depressive (N = 393), comorbid anxiety and depressive disorders (‘comorbid’, N = 748), remitted participants (N = 621), and healthy control subjects (N = 650).ResultsAnalyses revealed an increasing trend of social dysfunction among patient groups, in patients with comorbid anxiety and depressive disorders, showing the most severe impairments, followed by depressed and anxious patients (P's < 0.001 for all social functioning indicators). Affective indicators showed the largest effect sizes (Cohen's d range from 0.13 to 1.76). We also found impairments in social functioning among remitted patients. Furthermore, perceived social disability among patients was predictive of still having a depressive and/or anxiety diagnosis 2 years later (P < 0.01).ConclusionsBehavioural but especially affective indicators of social functioning are impaired in patients with anxiety or depressive disorders and most in patients with comorbid disorders. After remission of affective psychopathology, residual impairments tend to remain, while social dysfunction in patients seems predictive of future psychopathology.

show abstract

Section: Introductionmentioning

confidence: 99%

Social functioning in patients with depressive and anxiety disorders

Saris

Aghajani

Werff

et al. 2017

Acta Psychiatr Scand

149

View full text Add to dashboard Cite

show abstract

“…NIHR Journals Library www.journalslibrary.nihr.ac.uk As well as chest pain, anxiety comorbid with depression is predictive of a worse depression outcome; 138 our participants reported high anxiety levels and we found some evidence of anxiety as a mediator for depression improvement. In a future trial, more active treatment of anxiety should be tested, particularly when associated with chest pain.…”

Section: An Intervention For Symptomatic Coronary Heart Disease and Dmentioning

confidence: 46%

UPBEAT-UK: a programme of research into the relationship between coronary heart disease and depression in primary care patients

Tylee

Barley

Walters

et al. 2016

Programme Grants Appl Res

View full text Add to dashboard Cite

BackgroundDepression is common in patients with coronary heart disease (CHD) but the relationship is uncertain. In the UK, general practitioners (GPs) have been remunerated for finding depression in CHD patients; however, it is unclear how to manage these patients.ObjectivesOur aim was to explore the relationship between CHD and depression in a GP population and to develop nurse-led personalised care (PC) for patients with CHD and depression.DesignThe UPBEAT-UK study consisted of four related studies. A cohort study of patients from CHD registers to explore the relationship between CHD and depression. A metasynthesis of relevant literature and two qualitative studies [patients’ perspectives and GP/practice nurse (PN) views on management of CHD and depression] helped develop an intervention. A pilot randomised controlled trial (RCT) of PC was conducted.SettingThirty-three GP surgeries in south London.ParticipantsAdult patients on GP CHD registers.InterventionsFrom the qualitative studies, we developed nurse-led PC, combining case management and self-management theory. Following biopsychosocial assessment, a PC plan was devised for each patient with chest pain and depressive symptoms. Nurses helped patients address their most important related problems. Use of existing resources was promoted. Nurse time was conserved through telephone follow-up.Main outcome measuresThe main outcome of the pilot study of our newly developed PC for people with depression and CHD was to assess the acceptability and feasibility of the intervention and to decide on the best outcome measures. Depression, measured by the Hospital Anxiety and Depression Scale – depression subscale, and chest pain, measured by the Rose angina questionnaire, were the main outcome measures for the feasibility and cohort studies. Cardiac outcomes in the cohort study included: attendance at rapid access chest pain clinics, stent insertion, bypass graft surgery, myocardial infarction and cardiovascular death. Service use and costs were measured and linked to quality-adjusted life-years (QALYs). Data for the pilot RCT were obtained by research assistants from patient interviews at baseline, 1, 6 and 12 months for the pilot RCT and at baseline and 6-monthly interviews for up to 36 months for the cohort study, using standard questionnaires.ResultsPersonalised care was acceptable to patients and proved feasible. The reporting of chest pain in the intervention group was half that of the control group at 6 months, and this reduction was maintained at 1 year. There was also a small improvement in self-efficacy measures in the intervention group at 12 months. Anxiety was more prevalent than depression in our CHD cohort over the 3 years. Nearly half of the cohort complained of chest pain at outset, with two-thirds of these being suggestive of angina. Baseline exertional chest pain (suggestive of angina), anxiety and depression were independent predictors of adverse cardiac outcome. Psychosocial factors predicted the continued reporting of exertional chest pain across the 3 years of follow-up. Costs were slightly lower for the PC group but QALYs were also lower. Neither difference was statistically significant.ConclusionsChest pain, anxiety, depression and social problems are common in patients on CHD registers in primary care and predict adverse cardiac outcomes. Together they pose a complex management problem for GPs and PNs. Our pilot trial of PC suggests a promising approach for treatment of these patients. Generalisation is limited because of the selection bias in recruitment of the practices and the subsequent participation rate of the CHD register patients, and the fact that the research took place in south London boroughs. Future work should explicitly explore methods for effective implementation of the intervention, including staff training needs and changes to practice.Trial registrationCurrent Controlled Trials ISRCTN21615909.FundingThis project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full inProgramme Grants for Applied Research; Vol. 4, No. 8. See the NIHR Journals Library website for further project information.

show abstract

“…To illustrate the use of the RuleFit algorithm, we apply it to a dataset that was used by Penninx et al (2011) to find predictors of the course of depressive and anxiety disorders. Penninx et al (2011) used logistic regression analysis to find sociodemographic and clinical characteristics that predicted psychiatric status (i.e., presence of a depressive or anxiety disorder) after two years.…”

Section: Illustrationmentioning

confidence: 99%

“…Sample Penninx et al (2011) identified predictors of the course of depressive and anxiety disorders using data from the Netherlands Study of Depression and Anxiety (NESDA; Penninx et al, 2008). This longitudinal study includes 2981 respondents, aged 18 through 65 years.…”

Section: Illustrationmentioning

confidence: 99%

“…In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al (2011). The RuleFit algorithm provided a model consisting of two simple decision rules, requiring evaluation of only two to four cues.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Connecting clinical and actuarial prediction with rule-based methods.

Fokkema¹,

Smits²,

Kelderman³

et al. 2015

Psychological Assessment

View full text Add to dashboard Cite

Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. In this paper, we argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic, as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of two simple decision rules, requiring evaluation of only two to four cues. Predictive accuracy of the two-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the two-rule model required evaluation of only three cues, on average. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods.

show abstract

Two-year course of depressive and anxiety disorders: Results from the Netherlands Study of Depression and Anxiety (NESDA)

Abstract: Their differential course trajectory justifies separate consideration of pure depression, pure anxiety and comorbid anxiety-depression in clinical practice and psychiatric nosology.

Cited by 304 publications

References 39 publications

Social functioning in patients with depressive and anxiety disorders

Social functioning in patients with depressive and anxiety disorders

UPBEAT-UK: a programme of research into the relationship between coronary heart disease and depression in primary care patients

Connecting clinical and actuarial prediction with rule-based methods.

Contact Info

Product

Resources

About