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Mood and anxiety disorders are heterogeneous conditions with variable course. Knowledge on latent classes and transitions between these classes over time based on longitudinal disorder status information provides insight into clustering of meaningful groups with different disease prognosis.
Methods
Data of all four waves of the Netherlands Mental Health Survey and Incidence Study-2 were used, a representative population-based study of adults (mean duration between two successive waves = 3 years; N at T0 = 6646; T1 = 5303; T2 = 4618; T3 = 4007; this results in a total number of data points: 20 574). Presence of eight mood and anxiety DSM-IV disorders was assessed with the Composite International Diagnostic Interview. Latent class analysis and latent Markov modelling were used.
Results
The best fitting model identified four classes: a healthy class (prevalence: 94.1%), depressed-worried class (3.6%; moderate-to-high proportions of mood disorders and generalized anxiety disorder (GAD)), fear class (1.8%; moderate-to-high proportions of panic and phobia disorders) and high comorbidity class (0.6%). In longitudinal analyses over a three-year period, the minority of those in the depressed-worried and high comorbidity class persisted in their class over time (36.5% and 38.4%, respectively), whereas the majority in the fear class did (67.3%). Suggestive of recovery is switching to the healthy class, this was 39.7% in the depressed-worried class, 12.5% in the fear class and 7.0% in the high comorbidity class.
Conclusions
People with panic or phobia disorders have a considerably more persistent and chronic disease course than those with depressive disorders including GAD. Consequently, they could especially benefit from longer-term monitoring and disease management.
Psychotic experiences (PEs) frequently occur and are associated with a range of negative health outcomes. Prospective studies on PEs are scarce, and to date no study investigated PE prevalence, incidence, persistence, their risk indicators, and psychiatric comorbidity, in one dataset. Furthermore, most studies are based on self-report, and it is unclear how this compares to clinical interviews.
Methods
Data are used from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), a psychiatric cohort study among a representative sample of adults (baseline characteristics: N = 6646; 49.6% female; 18–64 years). Results are presented for self-reported and clinically validated PEs. Associations are assessed for mental disorders, socio-demographic, vulnerability, physical health, and substance use factors.
Results
Based on self-report, at baseline 16.5% of respondents had at least one PE in their lifetime, of those, 30.1% also reported a PE at 3-year follow-up. 4.8% had a first PE at 3-year follow up. The 3-year prevalence of PE was associated with almost all studied risk indicators. Generally, the strongest associations were found for mental health disorders. Prevalence and incidence rates were two to three times higher in self-report than in clinical interview but results on associated factors were similar.
Conclusions
Validated prevalence and incidence estimates of PE are substantially lower than self-reported figures but results on associated factors were similar. Therefore, future studies on associations of PEs can rely on relatively inexpensive self-reports of PEs. The associations between PE and mental disorders underline the importance of assessment of PE in general practice.
Empirical evidence suggests that people use cannabis to ameliorate anxiety and depressive symptoms, yet cannabis also acutely worsens psychosis and affective symptoms. However, the temporal relationship between cannabis use, anxiety and depressive symptoms and psychotic experiences (PE) in longitudinal studies is unclear. This may be informed by examination of mutually mediating roles of cannabis, anxiety and depressive symptoms in the emergence of PE.
Methods
Data were derived from the second longitudinal Netherlands Mental Health Survey and Incidence Study. Mediation analysis was performed to examine the relationship between cannabis use, anxiety/depressive symptoms and PE, using KHB logit in STATA while adjusting for age, sex and education status.
Results
Cannabis use was found to mediate the relationship between preceding anxiety, depressive symptoms and later PE incidence, but the indirect contribution of cannabis use was small (for anxiety: % of total effect attributable to cannabis use = 1.00%; for depression: % of total effect attributable to cannabis use = 1.4%). Interestingly, anxiety and depressive symptoms were found to mediate the relationship between preceding cannabis use and later PE incidence to a greater degree (% of total effect attributable to anxiety = 17%; % of total effect attributable to depression = 37%).
Conclusion
This first longitudinal cohort study examining the mediational relationship between cannabis use, anxiety/depressive symptoms and PE, shows that there is a bidirectional relationship between cannabis use, anxiety/depressive symptoms and PE. However, the contribution of anxiety/depressive symptoms as a mediator was greater than that of cannabis.
A transdiagnostic and contextual framework of ‘clinical characterization’, combining clinical, psychopathological, sociodemographic, etiological, and other personal contextual data, may add clinical value over and above categorical algorithm-based diagnosis.
Methods
Prediction of need for care and health care outcomes was examined prospectively as a function of the contextual clinical characterization diagnostic framework in a prospective general population cohort (n = 6646 at baseline), interviewed four times between 2007 and 2018 (NEMESIS-2). Measures of need, service use, and use of medication were predicted as a function of any of 13 DSM-IV diagnoses, both separately and in combination with clinical characterization across multiple domains: social circumstances/demographics, symptom dimensions, physical health, clinical/etiological factors, staging, and polygenic risk scores (PRS). Effect sizes were expressed as population attributable fractions.
Results
Any prediction of DSM-diagnosis in relation to need and outcome in separate models was entirely reducible to components of contextual clinical characterization in joint models, particularly the component of transdiagnostic symptom dimensions (a simple score of the number of anxiety, depression, mania, and psychosis symptoms) and staging (subthreshold, incidence, persistence), and to a lesser degree clinical factors (early adversity, family history, suicidality, slowness at interview, neuroticism, and extraversion), and sociodemographic factors. Clinical characterization components in combination predicted more than any component in isolation. PRS did not meaningfully contribute to any clinical characterization model.
Conclusion
A transdiagnostic framework of contextual clinical characterization is of more value to patients than a categorical system of algorithmic ordering of psychopathology.
Although attenuated psychotic symptoms in the psychosis clinical high-risk state (CHR-P) almost always occur in the context of a non-psychotic disorder (NPD), NPD is considered an undesired ‘comorbidity’ epiphenomenon rather than an integral part of CHR-P itself. Prospective work, however, indicates that much more of the clinical psychosis incidence is attributable to prior mood and drug use disorders than to psychosis clinical high-risk states per se. In order to examine this conundrum, we analysed to what degree the ‘risk’ in CHR-P is indexed by co-present NPD rather than attenuated psychosis per se.
Methods
We examined the incidence of early psychotic experiences (PE) with and without NPD (mood disorders, anxiety disorders, alcohol/drug use disorders), in a prospective general population cohort (n = 6123 at risk of incident PE at baseline). Four interview waves were conducted between 2007 and 2018 (NEMESIS-2). The incidence of PE, alone (PE-only) or with NPD (PE + NPD) was calculated, as were differential associations with schizophrenia polygenic risk score (PRS-Sz), environmental, demographical, clinical and cognitive factors.
Results
The incidence of PE + NPD (0.37%) was lower than the incidence of PE-only (1.04%), representing around a third of the total yearly incidence of PE. Incident PE + NPD was, in comparison with PE-only, differentially characterised by poor functioning, environmental risks, PRS-Sz, positive family history, prescription of antipsychotic medication and (mental) health service use.
Conclusions
The risk in ‘clinical high risk’ states is mediated not by attenuated psychosis per se but specifically the combination of attenuated psychosis and NPD. CHR-P/APS research should be reconceptualised from a focus on attenuated psychotic symptoms with exclusion of non-psychotic DSM-disorders, as the ‘pure' representation of a supposedly homotypic psychosis risk state, towards a focus on poor-outcome NPDs, characterised by a degree of psychosis admixture, on the pathway to psychotic disorder outcomes.
There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation.
Methods
We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls.
Results
The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465).
Conclusions
The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.
Although hallucinations have been studied in terms of prevalence and its associations with psychopathology and functional impairment, very little is known about sensory modalities other than auditory (i.e. haptic, visual and olfactory), as well the incidence of hallucinations, factors predicting incidence and subsequent course.
Methods
We examined the incidence, course and risk factors of hallucinatory experiences across different modalities in two unique prospective general population cohorts in the same country using similar methodology and with three interview waves, one over the period 1996–1999 (NEMESIS) and one over the period 2007–2015 (NEMESIS-2).
Results
In NEMESIS-2, the yearly incidence of self-reported visual hallucinations was highest (0.33%), followed by haptic hallucinations (0.31%), auditory hallucinations (0.26%) and olfactory hallucinations (0.23%). Rates in NEMESIS-1 were similar (respectively: 0.35%, 0.26%, 0.23%, 0.22%). The incidence of clinician-confirmed hallucinations was approximately 60% of the self-reported rate. The persistence rate of incident hallucinations was around 20–30%, increasing to 40–50% for prevalent hallucinations. Incident hallucinations in one modality were very strongly associated with occurrence in another modality (median OR = 59) and all modalities were strongly associated with delusional ideation (median OR = 21). Modalities were approximately equally strongly associated with the presence of any mental disorder (median OR = 4), functioning, indicators of help-seeking and established environmental risk factors for psychotic disorder.
Conclusions
Hallucinations across different modalities are a clinically relevant feature of non-psychotic disorders and need to be studied in relation to each other and in relation to delusional ideation, as all appear to have a common underlying mechanism.
Contemporary models of psychosis implicate the importance of affective dysregulation and cognitive factors (e.g. biases and schemas) in the development and maintenance of psychotic symptoms, but studies testing proposed mechanisms remain limited. This study, uniquely using a prospective design, investigated whether the jumping to conclusions (JTC) reasoning bias contributes to psychosis progression and persistence.
Methods
Data were derived from the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). The Composite International Diagnostic Interview and an add-on instrument were used to assess affective dysregulation (i.e. depression, anxiety and mania) and psychotic experiences (PEs), respectively. The beads task was used to assess JTC bias. Time series analyses were conducted using data from T1 and T2 (N = 8666), excluding individuals who reported high psychosis levels at T0.
Results
Although the prospective design resulted in low statistical power, the findings suggest that, compared to those without symptoms, individuals with lifetime affective dysregulation were more likely to progress from low/moderate psychosis levels (state of ‘aberrant salience’, one or two PEs) at T1 to high psychosis levels (‘frank psychosis’, three or more PEs or psychosis-related help-seeking behaviour) at T2 if the JTC bias was present [adj. relative risk ratio (RRR): 3.8, 95% confidence interval (CI) 0.8–18.6, p = 0.101]. Similarly, the JTC bias contributed to the persistence of high psychosis levels (adj. RRR: 12.7, 95% CI 0.7–239.6, p = 0.091).
Conclusions
We found some evidence that the JTC bias may contribute to psychosis progression and persistence in individuals with affective dysregulation. However, well-powered prospective studies are needed to replicate these findings.
Evidence suggests that cannabis use, childhood adversity, and urbanicity, in interaction with proxy measures of genetic risk, may facilitate onset of psychosis in the sense of early affective dysregulation becoming ‘complicated’ by, first, attenuated psychosis and, eventually, full-blown psychotic symptoms.
Methods
Data were derived from three waves of the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). The impact of environmental risk factors (cannabis use, childhood adversity, and urbanicity) was analyzed across severity levels of psychopathology defined by the degree to which affective dysregulation was ‘complicated’ by low-grade psychotic experiences (‘attenuated psychosis’ – moderately severe) and, overt psychotic symptoms leading to help-seeking (‘clinical psychosis’ – most severe). Familial and non-familial strata were defined based on family history of (mostly) affective disorder and used as a proxy for genetic risk in models of family history × environmental risk interaction.
Results
In proxy gene–environment interaction analysis, childhood adversity and cannabis use, and to a lesser extent urbanicity, displayed greater-than-additive risk if there was also evidence of familial affective liability. In addition, the interaction contrast ratio grew progressively greater across severity levels of psychosis admixture (none, attenuated psychosis, clinical psychosis) complicating affective dysregulation.
Conclusion
Known environmental risks interact with familial evidence of affective liability in driving the level of psychosis admixture in states of early affective dysregulation in the general population, constituting an affective pathway to psychosis. There is interest in decomposing family history of affective liability into the environmental and genetic components that underlie the interactions as shown here.
The jumping to conclusions (JTC) reasoning bias and decreased working memory performance (WMP) are associated with psychosis, but associations with affective disturbances (i.e. depression, anxiety, mania) remain inconclusive. Recent findings also suggest a transdiagnostic phenotype of co-occurring affective disturbances and psychotic experiences (PEs). This study investigated whether JTC bias and decreased WMP are associated with co-occurring affective disturbances and PEs.
Methods
Data were derived from the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). Trained interviewers administered the Composite International Diagnostic Interview (CIDI) at three time points in a general population sample (N = 4618). The beads and digit-span task were completed to assess JTC bias and WMP, respectively. CIDI was used to measure affective disturbances and an add-on instrument to measure PEs.
Results
Compared to individuals with neither affective disturbances nor PEs, the JTC bias was more likely to occur in individuals with co-occurring affective disturbances and PEs [moderate psychosis (1–2 PEs): adjusted relative risk ratio (RRR) 1.17, 95% CI 0.98–1.41; and high psychosis (3 or more PEs or psychosis-related help-seeking behaviour): adjusted RRR 1.57, 95% CI 1.19–2.08], but not with affective disturbances and PEs alone, whereas decreased WMP was more likely in all groups. There was some evidence of a dose–response relationship, as JTC bias and decreased WMP were more likely in individuals with affective disturbances as the level of PEs increased or help-seeking behaviour was reported.
Conclusion
The findings suggest that JTC bias and decreased WMP may contribute to a transdiagnostic phenotype of co-occurring affective disturbances and PEs.
Previous studies revealed a relationship between residential green space availability and health, especially mental health. Studies on blue space are scarcer and results less conclusive.
Aims
To investigate the hypotheses that green and blue space availability are negatively associated with anxiety and mood disorders, and positively associated with self-reported mental and general health.
Method
Health data were derived from a nationally representative survey (NEMESIS-2, n=6621), using a diagnostic interview to assess disorders. Green and blue space availability were expressed as percentages of the area within 1 km from one's home.
Results
The hypotheses were confirmed, except for green space and mood disorders. Associations were generally stronger for blue space than for green space, with ORs up to 0.74 for a 10%-point increase.
Conclusions
Despite the different survey design and health measures, the results largely replicate those of previous studies on green space. Blue space availability deserves more systematic attention.
Cannabis use is associated with mental health problems, and young people
in particular are at risk.
Aims
To investigate the association between cannabis use and mental health in
adolescence.
Method
Data from 5551 adolescents aged 12–16 years were drawn from the Dutch
Health Behaviour in School-Aged Children school survey, carried out as
part of the international 2001 World Health Organization project.
Results
After adjusting for confounding factors, cannabis use was linked to
externalising problems (delinquent and aggressive behaviour) but not to
internalising problems (withdrawn behaviour, somatic complaints and
depression). An increasing frequency of use resulted in stronger links.
No significant gender or age by cannabis interaction effects were
found.
Conclusions
In a country with a liberal drug policy like The Netherlands, cannabis
use is associated with aggression and delinquency, just as in other
countries. Cannabis use was not associated with internalising problems.
Alcohol use and regular smoking were strong confounding factors.
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