It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Cognitive deficits may be characteristic for only a subgroup of first-episode psychosis (FEP) and the link with clinical and functional outcomes is less profound than previously thought. This study aimed to identify cognitive subgroups in a large sample of FEP using a clustering approach with healthy controls as a reference group, subsequently linking cognitive subgroups to clinical and functional outcomes.

204 FEP patients were included. Hierarchical cluster analysis was performed using baseline brief assessment of cognition in schizophrenia (BACS). Cognitive subgroups were compared to 40 controls and linked to longitudinal clinical and functional outcomes (PANSS, GAF, self-reported WHODAS 2.0) up to 12-month follow-up.

Three distinct cognitive clusters emerged: relative to controls, we found one cluster with preserved cognition (n = 76), one moderately impaired cluster (n = 74) and one severely impaired cluster (n = 54). Patients with severely impaired cognition had more severe clinical symptoms at baseline, 6- and 12-month follow-up as compared to patients with preserved cognition. General functioning (GAF) in the severely impaired cluster was significantly lower than in those with preserved cognition at baseline and showed trend-level effects at 6- and 12-month follow-up. No significant differences in self-reported functional outcome (WHODAS 2.0) were present.

Current results demonstrate the existence of three distinct cognitive subgroups, corresponding with clinical outcome at baseline, 6- and 12-month follow-up. Importantly, the cognitively preserved subgroup was larger than the severely impaired group. Early identification of discrete cognitive profiles can offer valuable information about the clinical outcome but may not be relevant in predicting self-reported functional outcomes.

The Netherlands Study of Depression and Anxiety (NESDA, www.nesda.nl) is an ongoing study to: 1) describe the long-term course and consequences of depressive and anxiety disorders, and 2) to examine the demographic, psychosocial, somatic, biological and genetic determinants of this course. This presentation describes NESDA's rationale, sampling frame and methods.

The design is an 8-year longitudinal cohort study following 2,850 participants aged 18 through 65 years. The sample consists of 1600 persons with a current (6 month recency) diagnosis of depression or anxiety disorder, 850 persons at risk (because of high symptomatology, family or life-time history), and 400 healthy controls. Recruitment takes place in the community, through 65 general practitioners (using a three-stage screening procedure), and through 17 mental health care institutions in order to include patients reflecting various settings and stages of psychopathology. The 4-hour baseline assessment includes questionnaires, interviews, a medical exam, a computer task and blood (including DNA and RNA) and saliva collections. Follow-up assessments are repeated after 1, 2, 4 and 8 years.

Over 2500 respondents with more than 2100 current diagnoses of depression or anxiety disorders, were recruited in November 2006 (mean age = 41 years, 67% female). Expected end date of recruitment is in February 2007.

NESDA is expected to provide more insight into (predictors of) the course of affective disorders. NESDA is open for collaboration (including data utilization) with other European research groups, which we hope to stimulate by a presentation of its design and methods.

The cause of depression is largely unknown, but several studies point to disturbances of biological rhythmicity. The functioning of the suprachiasmatic nucleus (SCN) is impaired, as evidenced by an increased prevalence of day-night rhythm perturbations, such as sleeping disorders. Moreover, the inhibitory SCN neurons on the hypothalamus-pituitary adrenocortical axis (HPA-axis) have decreased activity and HPA-activity is enhanced, when compared to non-depressed elderly. Using bright light therapy (BLT) the SCN can be stimulated. In addition, the beneficial effects of BLT on seasonal depression are well accepted. BLT is a potentially safe, nonexpensive and well accepted treatment option. But the current literature on BLT for depression is inconclusive.

RCT (ClinicalTrials.gov identifier: NCT00332670) in 89 subjects, of 60 years and older with a diagnosis of major depressive disorder. After inclusion subjects were randomly allocated to the active (BLT) vs. placebo (dim red light) condition. just before the start of light therapy, after completion of three weeks therapy period, and three weeks thereafter several endocrinological, psychophysiological, psychometrically, neuropsychological measures are performed:

Main effect analyses on HADRS-17 scores revealed significant antidepressant effects from BLT. Primary results will be presented.

BLT reduces nonseasonal depression in elderly patients. Additional lightning may easily be implemented in the homes of patients to serve as add-on treatment to antidepressants or as a stand-alone treatment in elderly depressed patients. Our data support the role of a dysfunctional biological clock in depressed elderly subjects, such a finding may guide further development of novel chronobiological oriented treatment strategies.

The aim of Routine Outcome Monitoring (ROM) is to improve the quality of clinical treatment. Providing feedback on the outcome of treatment to both clinicians and patients is an integral part of ROM, allowing modifications to treatment. Published studies are inconsistent with respect to patient attitudes towards ROM. Clinicians, however, generally appear to be more negative than enthusiastic. Although Routine Outcome Monitoring is currently implemented throughout the Netherlands, the process is not going as smoothly as first envisaged. Research into patient and clinician attitudes towards ROM can offer a partial explanation of the difficulties involved.

The aim of this study is to gain insight into the attitudes of both patients and clinicians towards ROM and the factors that play a role in the implementation of ROM in a general, non-academic psychiatric outpatient setting.

A study was carried out into the attitudes of both patients and clinicians towards the recently introduced ROM procedure. Specifically designed attitude rating scales were presented to a group of 176 patients and their 69 clinicians in the course of their treatment.

Forty-six percent of the patients consulted and 39% of their clinicians completed an attitude rating scale. Patients were generally positive about the use of ROM during the clinical care process. They found it useful and did not find it stressful. The use of a computer during this process was considered to be a positive facet. Clinicians, on the other hand, had a negative reaction and rejected ROM. In the discussion possible explanations for the cause of these findings are offered.

Feedback is an essential part of Routine Outcome Monitoring. Little is known about the effect of feedback provided to the clinician and patient during treatment. A review of the available literature about feedback given to clinician and patient on treatment outcomes in general psychiatry showed a small, almost negligible effect of the provision of feedback. However, Lambert c.s. found that giving feedback about patient-progress that deviated from the expected outcome in a psychotherapeutic setting was associated with a significant improvement afterwards.

To investigate the effect of feedback on treatment outcomes in a general psychiatric outpatient clinic for mood and anxiety disorders in the Netherlands.

a field study in which more attention was paid to the implementation of feedback than usual. Clinicians were trained in interpreting treatment outcomes and explaining them to their patients. The feedback procedure was then monitored. Three groups of patients were distinguished (1) a group of patients who received obligatory protocolled feedback, (2) a group of patients of whom their clinicians voluntary could view the received feedback and had to fill in GAF and CGI scores concerning te progress of their treatment and (3) a group that received neither feedback nor GAF or CGI scores. All three groups completed relevant outcome measures.

from the 176 patients 26 % received feedback from their clinician. Their progress was measured regularly. Even with extra attention paid to the implementation, it appears that providing feedback to the clinician and patient has little effect on treatment outcomes.

There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders.

Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels.

Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant.

Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation.

Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression.

Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS).

Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15–1.32, R2 = 1.47%).

By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.

Technological progress has enabled researchers to use new unobtrusive measures of relationships between actors in social network analysis. However, research on how these unobtrusive measures of peer connections relate to traditional sociometric nominations in adolescents is scarce. Therefore, the current study compared traditional peer nominated networks with more unobtrusive measures of peer connections: Communication networks that consist of instant messages in an online social platform and proximity networks based on smartphones’ Bluetooth signals that measure peer proximity. The three social network types were compared in their coverage, stability, overlap, and the extent to which the networks exhibit the often observed sex segregation in adolescent social networks.

Two samples were derived from the MyMovez project: a longitudinal sample of 444 adolescents who participated in the first three waves of the first year of the project (Y1; 51% male; Mage = 11.29, SDage = 1.26) and a cross-sectional sample of 774 adolescents that participated in fifth wave in the third year (Y3; 48% male; Mage = 10.76, SDage = 1.23). In the project, all participants received a research smartphone and a wrist-worn accelerometer. On the research smartphone, participants received daily questionnaires such as peer nomination questions (i.e., nominated network). In addition, the smartphone automatically scanned for other smartphones via Bluetooth signal every 15 minutes of the day (i.e., proximity network). In the Y3 sample, the research smartphone also had a social platform in which participants could send messages to each other (i.e., communication network).

The results show that nominated networks provided data for the most participants compared to the other two networks, but in these networks, participants had the lowest number of connections with peers. Nominated networks showed to be more stable over time compared to proximity or communication networks. That is, more connections remained the same in nominated networks than in proximity networks over the three waves of Y1. The overlap between the three networks was rather small, indicating that the networks measured different types of connections. Nominated and communication networks were segregated by sex, whereas this was less the case in proximity networks.

The communication and proximity networks seem to be promising unobtrusive measures of peer connections and are less of a burden to the participant compared to a nominated network. However, given the structural differences between the networks and the number of connections per wave, the communication and proximity networks should not be used as direct substitutes for sociometric nominations, and researchers should bear in mind what type of connections they wish to assess.

Studies on neighbourhood characteristics and depression show equivocal results.

This large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression.

Cross-sectional design including data are from eight Dutch cohort studies (n= 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis.

The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01–1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87–0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06–1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02–1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01–1.12), less green space (OR = 0.94, 95% CI 0.88–0.99) and less social safety (OR = 0.92, 95% CI 0.88–0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores.

This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.

None.

Major depressive disorder (MDD), represent a major source of risk for suicidality. However, knowledge about risk factors for future suicide attempts (SAs) within MDD is limited. The present longitudinal study examined a wide range of putative non-clinical risk factors (demographic, social, lifestyle, personality) and clinical risk factors (depressive and suicidal indicators) for future SAs among persons with MDD. Furthermore, we examined the relationship between a number of significant predictors and the incidence of a future SA.

Data are from 1713 persons (18–65 years) with a lifetime MDD at the baseline measurement of the Netherlands Study of Depression and Anxiety who were subsequently followed up 2, 4 and 6 years. SAs were assessed in the face-to-face measurements. Cox proportional hazard regression analyses were used to examine a wide range of possible non-clinical and clinical predictors for subsequent SAs during 6-year follow-up.

Over a period of 6 years, 3.4% of the respondents attempted suicide. Younger age, lower education, unemployment, insomnia, antidepressant use, a previous SA and current suicidal thoughts independently predicted a future SA. The number of significant risk factors (ranging from 0 to 7) linearly predicted the incidence of future SAs: in those with 0 predictors the SA incidence was 0%, which increased to 32% incidence in those with 6+ predictors.

Of the non-clinical factors, particularly socio-economic factors predicted a SA independently. Furthermore, preexisting suicidal ideation and insomnia appear to be important clinical risk factors for subsequent SA that are open to preventative intervention.

Which neighbourhood factors most consistently impact on depression and anxiety remains unclear. This study examines whether objectively obtained socioeconomic, physical and social aspects of the neighbourhood in which persons live are associated with the presence and severity of depressive and anxiety disorders.

Cross-sectional data are from the Netherlands Study of Depression and Anxiety including participants (n = 2980) with and without depressive and anxiety disorders in the past year (based on DSM-based psychiatric interviews). We also determined symptom severity of depression (Inventory of Depression Symptomatology), anxiety (Beck Anxiety Inventory) and fear (Fear Questionnaire). Neighbourhood characteristics comprised socioeconomic factors (socioeconomic status, home value, number of social security beneficiaries and percentage of immigrants), physical factors (air pollution, traffic noise and availability of green space and water) and social factors (social cohesion and safety). Multilevel regression analyses were performed with the municipality as the second level while adjusting for individual sociodemographic variables and household income.

Not urbanization grade, but rather neighbourhood socioecononomic factors (low socioeconomic status, more social security beneficiaries and more immigrants), physical factors (high levels of traffic noise) and social factors (lower social cohesion and less safety) were associated with the presence of depressive and anxiety disorders. Most of these neighbourhood characteristics were also associated with increased depressive and anxiety symptoms severity.

These findings suggest that it is not population density in the neighbourhood, but rather the quality of socioeconomic, physical and social neighbourhood characteristics that is associated with the presence and severity of affective disorders.