The salutary effect of window views on greenery for inpatients in hospitals on length of stay and recovery rate has been repeatedly shown, however, not for psychiatric inpatients. The study assessed the association between a window view on green trees or man-made objects and brightness of the room on length of stay in a sample of psychiatric inpatients from one clinic.

Data records of 244 psychiatric inpatients (mean age in years 41.8; SD = 11.8; 59.8% female, length of stay varying between 7 and 100 days) that were admitted between May 2013 and October 2018 with affective disorders were examined. Window view was assessed with images taken from each room and classified into showing man-made objects or green trees. The percentage of green within each image was also calculated as greenness of the view. Brightness was assessed with a luxmeter.

Although no effect was found for the dichotomous measures (man-made objects vs. green trees), a suppression effect emerged for percentage of green and brightness. The results indicate that both greenness of the window view as well as brightness significantly reduce length of stay in psychiatric inpatients with affective disorders.

The suppression effect likely results from the characteristics of the windows; the greenest rooms also being the darkest. Due to the infrastructure of the ward, greenness and brightness came at the expense of each other. The results generally support the importance of a view into greenery and natural sunlight for recovery.

This research evaluates the cost-effectiveness of repetitive transcranial magnetic stimulation (rTMS) as add-on therapy to standard care for adults with schizophrenia from an Australian health system perspective.

A Markov model estimated costs in 2021 Australian dollars and Disability-Adjusted Life-Years (DALYs) averted with rTMS added to standard care compared to standard care alone over 12-months for adults aged 25–65 years with hallucinations in schizophrenia refractory to other therapies. rTMS effect size was sourced from a meta-analysis and converted to a relative risk using the Cochrane conversion method. Probabilistic sensitivity analysis evaluated uncertainty in effect size and disability weights. One-way sensitivity analyses varied rTMS session cost and effectiveness, time horizon and inpatient costs.

The base-case average incremental cost-effectiveness ratio (ICER) was $87,310/DALY averted (95% UI: $10,157–$97,877). Reducing rTMS session cost to $100 lowered the ICER to $9,127/DALY (95% UI: Dominant–$50,699). A 4-year time horizon resulted in rTMS being less costly and more effective (Dominant) than standard care. Decreasing the 3-month probability of relapse with rTMS to 4.6% resulted in a 71% probability of rTMS being cost-effective.

Using a threshold of $50,000/ DALY averted, rTMS as add-on therapy to standard care for the treatment of refractory hallucinations in schizophrenia would not be considered a cost-effective treatment option compared to standard care alone. However, given the refractory nature of this condition and the relatively small size of this population, it may be reasonable for decision-makers to adopt a higher ICER threshold.

To evaluate the efficacy of short-term lurasidone in antipsychotic treatment-naïve (TN) adolescents with schizophrenia versus those treated previously (TP) with antipsychotics.

Patients aged 13–17 with schizophrenia, and a Positive and Negative Symptom Scale (PANSS) score ≥ 70 and < 120, were randomized to 6 weeks of double-blind treatment with lurasidone (40 or 80 mg/day) or placebo. In a post-hoc, pooled-dose analysis, efficacy was evaluated for TN (criteria: never received antipsychotic treatment) versus TP at the time of the study. Treatment response criteria: ≥20% reduction in PANSS total score.

Altogether, 57 TN and 269 TP patients enrolled in the 6-week DB study. Mean endpoint change in PANSS total score was significantly greater for lurasidone versus placebo in both the TN group (−25.0 vs. -14.4; p < 0.02; effect size = 0.75), and in the TP group (−17.3 vs. -10.0; p < 0.001; effect size = 0.45); and responder rates were higher for lurasidone versus placebo in both the TN group 84.6% versus 38.9%; number needed to treat [NNT] = 3 and in the TP group (60% vs. 42%; NNT = 6). Rates of treatment-emergent adverse events, and mean changes in body weight and metabolic parameters were similar for the TN and TP groups.

In a 6-week, placebo-controlled trial, lurasidone demonstrated significant efficacy in adolescents with schizophrenia regardless of previous antipsychotic therapy status; however, the effect size was notably larger in the TN patient group. In both the TN and TP groups, minimal effects were noted on weight, metabolic parameters, or prolactin.

Suicidal ideation (SI) is an important risk factor of death by suicide. Recent data suggest that suicidal depression (i.e., moderate to severe depression with SI) could be a specific depression subtype with worse clinical outcomes than nonsuicidal depression (i.e., without SI).

Among 898 French adult inpatients (67% women, mean age: 41.23 [SD: 14.33]) with unipolar depression, 71.94% had moderate to severe depression (defined using the cut-offs of validated scales: beck depression inventory, clinician-rated 30-item inventory depression symptomatology, and quick inventory of depressive symptomatology) and among them, 63.6% had SI according to the suicidal item (score ≥ 2) of the depression scale they filled in. Clinical features (anxiety, psychological pain, and hopelessness) were assessed at baseline. The occurrence of a suicide attempt (SA) or a suicide event (SE) (i.e., actual, aborted or interrupted SA, or hospitalization for SI) was recorded during the 1-year follow-up. The risk of actual SA and SE was compared between groups with adjusted Cox regression models.

The risk of actual SA and SE during the follow-up was 2- and 1.8-fold higher, respectively, in patients with suicidal depression, independently of potential cofounders such as history of lifetime SA, age, sex, and baseline depression severity.

Suicidal depression is associated with poorer prognosis in terms of actual SA/SE, despite optimal care (i.e., care in a hospital department specialized in the management of suicidal crisis). Specific therapeutic strategies might be needed for these patients.

Cannabis use in university students is associated with academic achievement failure and health issues. The objective of the study was to evaluate the association between attention deficit hyperactivity disorder (ADHD) symptoms and cannabis use after 1 year among students according to previous cannabis use.

Students in France were recruited from February 2013 to July 2020 in the i-Share cohort. 4,270 participants were included (2,135 who never used cannabis at inclusion and 2,135 who did). The Adult ADHD Self-Report Scale (ASRS) was used to assess ADHD symptoms at inclusion. Cannabis use frequency was evaluated 1 year after inclusion. Multinomial regressions were conducted to assess the association between inclusion ADHD symptoms and cannabis use after 1 year.

Increase in ASRS scores was linked with a greater probability to use cannabis after 1 year and to have a higher cannabis use frequency (once a year—once a month adjusted odds ratio [OR]: 1.24 (1.15–1.34), more than once a month adjusted OR: 1.43 (1.27–1.61)). Among participants who never used cannabis at inclusion, this association disappeared (once a year—once a month adjusted OR: 1.15 (0.95–1.39), more than once a month adjusted OR: 1.16 (0.67–2)) but remained in participants who ever used cannabis at inclusion (once a year—once a month adjusted OR: 1.17 (1.06–1.29), more than once a month adjusted OR: 1.35 (1.18–1.55)).

High levels of ADHD symptoms in students could lead to continued cannabis use rather than new initiations.

There is a concern that the COVID-19 pandemic will lead to an increase in suicides. Several reports from the first months of the pandemic showed no increase in suicide rates while studies with longer observation times report contrasting results. In this study, we explore the suicide rates in Norway during the first year of the pandemic for the total population as well as for relevant subgroups such as sex, age, geographical areas, and pandemic phases.

This is a cohort study covering the entire Norwegian population between 2010 and 2020. The main outcome was age-standardized suicide rates (per 100,000 inhabitants) in 2020 according to the Norwegian Cause of Death Registry. This was compared with 95% prediction intervals (95% PI) based on the suicide rates between 2010 and 2019.

In 2020, there were 639 suicides in Norway corresponding to a rate of 12.1 per 100,000 (95% PI 10.2–14.4). There were no significant deviations from the predicted values for suicides in 2020 when analyzing age, sex, pandemic phase, or geographical area separately. We observed a trend toward a lower than predicted suicide rate among females (6.5, 95% PI 6.0–9.2), and during the two COVID-19 outbreak phases in 2020 (2.8, 95% PI 2.3–4.3 and 2.8, 95% CI 2.3–4.3).

There is no indication that the COVID-19 pandemic led to an increase in suicide rates in Norway in 2020.

Within-person growth in life satisfaction (LS) can protect against declines in cognitive functioning, and, conversely, over time. However, most studies have been cross-sectional, thereby precluding causal inferences. Thus, we used bivariate dual latent change score modeling to test within-person change-to-future change relations between LS and cognition.

Community adults completed in-person tests of verbal working memory (WM), processing speed, spatial cognition, and an LS self-report. Five waves of assessment occurred across 23 years.

Reduction in LS predicted future decreases in spatial cognition, processing speed, and verbal WM (|d| = 0.150–0.354). Additionally, depletion in processing speed and verbal WM predicted a future decrease in LS (d = 0.142–0.269). However, change in spatial cognition did not predict change in LS (|d| = 0.085).

LS and verbal WM and processing speed predicted one another across long durations. Evidence-based therapies can be augmented to target LS and cognition.

There is increasing attention on the association of socioeconomic status and individual behaviors (SES/IB) with mental health. However, the impacts of SES/IB on mental disorders are still unclear. To provide evidence for establishing feasible strategies on disease screening and prevention, we implemented Mendelian randomization (MR) design to appraise causality between SES/IB and mental disorders.

We conducted a two-sample MR study to assess the causal effects of SES and IB (dietary habits, habitual physical activity, smoking behaviors, drinking behaviors, sleeping behaviors, leisure sedentary behaviors, risky behaviors, and reproductive behaviors) on three mental disorders, including bipolar disorder, major depressive disorder and schizophrenia. A series of filtering steps were taken to select eligible genetic instruments robustly associated with each of the traits. Inverse variance weighted was used for primary analysis, with alternative MR methods including MR-Egger, weighted median, and weighted mode estimate. Complementary methods were further used to detect pleiotropic bias.

After Bonferroni correction and rigorous quality control, we identified that SES (educational attainment), smoking behaviors (smoking initiation, number of cigarettes per day), risky behaviors (adventurousness, number of sexual partners, automobile speeding propensity) and reproductive behavior (age at first birth) were causally associated with at least one of the mental disorders.

MR study provides robust evidence that SES/IB play broad impacts on mental disorders.

Metabolic dysregulation is currently considered a major risk factor for hippocampal pathology. The aim of the present study was to characterize the influence of key metabolic drivers on functional connectivity of the hippocampus in healthy adults.

Insulin resistance was directly quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test and fasting levels of insulin, glucose, leptin, and cortisol, and measurements of body mass index and waist circumference were obtained in a sample of healthy cognitively intact adults (n = 104). Resting-state neuroimaging data were also acquired for the quantification of hippocampal functional cohesiveness and integration with the major resting-state networks (RSNs). Data-driven analysis using unsupervised machine learning (k-means clustering) was then employed to identify clusters of individuals based on their metabolic and functional connectivity profiles.

K-means clustering identified two clusters of increasing metabolic deviance evidenced by cluster differences in the plasma levels of leptin (40.36 (29.97) vs. 27.59 (25.58) μg/L) and the degree of insulin resistance (SSPG concentration: 161.63 (65.27) vs. 125.72 (66.81) mg/dL). Individuals in the cluster with higher metabolic deviance showed lower functional cohesiveness within each hippocampus and lower integration of posterior and anterior components of the left and right hippocampus with the major RSNs. The two clusters did not differ in general intellectual ability or episodic memory.

We identified two clusters of individuals differentiated by abnormalities in insulin resistance, leptin levels, and hippocampal connectivity, with one of the clusters showing greater deviance. These findings support the link between metabolic dysregulation and hippocampal function even in nonclinical samples.

Subthreshold hypomania during a major depressive episode challenges the bipolar-unipolar dichotomy. In our study we employed a cross-diagnostic cluster analysis - to identify distinct subgroups within a cohort of depressed patients.

A k-means cluster analysis— based on the domain scores of the Mood Spectrum Self-Report (MOODS-SR) questionnaire—was performed on a data set of 300 adults with either bipolar or unipolar depression. After identifying groups, between-clusters comparisons were conducted on MOODS-SR domains and factors and on a set of sociodemographic, clinical and psychometric variables.

Three clusters were identified: one with intermediate depressive and poor manic symptomatology (Mild), one with severe depressive and poor manic symptomatology (Moderate), and a third one with severe depressive and intermediate manic symptomatology (Mixed). Across the clusters, bipolar patients were significantly less represented in the Mild one, while the DSM-5 “Mixed features” specifier did not differentiate the groups. When compared to the other patients, those of Mixed cluster exhibited a stronger association with most of the illness-severity, quality of life, and outcomes measures considered. After performing pairwise comparisons significant differences between “Mixed” and “Moderate” clusters were restricted to: current and disease-onset age, psychotic ideation, suicidal attempts, hospitalization numbers, impulsivity levels and comorbidity for Cluster B personality disorder.

In the present study, a clustering approach based on a spectrum exploration of mood symptomatology led to the identification of three transdiagnostic groups of patients. Consistent with our hypothesis, the magnitude of subthreshold (hypo)manic symptoms was related to a greater clinical severity, regardless of the main categorical diagnosis.

Deterioration in general population mental health since the start of the COVID-19 pandemic has been reported, but the impact of the pandemic on people with severe mental illness (SMI) has received less attention.

To understand the impact of the early stages of the pandemic on the patients with SMI, in terms of provision of mental health care and patient outcomes.

We examined records of 34,446 patients with SMI in Oxford Health Foundation Trust between March 2016 and July 2020. We used interrupted time-series analysis to estimate the immediate and subsequent changes in weekly rates of the use of community mental health services, hospitalization, and patient outcomes (as measured by Health of the Nation Outcome Scales, or HoNOS, scores) during the weeks of lockdown between March 23, 2020 and July 3, 2020.

Mean total HoNOS scores for all patients deteriorated in the weeks subsequent to lockdown (0.060 per week; 95%CI: 0.033, 0.087). Scores for patients with a history of psychosis deteriorated immediately (0.63; 95% CI: 0.26, 1.0). There was an immediate decrease in weekly referrals to community and outpatient services (−196; 95%CI: −300, −91) and no immediate change in weekly inpatient admissions (−4.2; 95%CI: −9.9, 1.5) or weekly total contacts (−26; 95%CI: −475, 423).

Patients with SMI were negatively impacted during the early stages of the COVID-19 pandemic. Patients with a history of psychosis experienced distinct and immediate impacts. During the same period, referrals to community and outpatient services fell with no consequent impact on inpatient admissions.

Subthreshold/attenuated syndromes are established precursors of full-threshold mood and psychotic disorders. Less is known about the individual symptoms that may precede the development of subthreshold syndromes and associated social/functional outcomes among emerging adults.

We modeled two dynamic Bayesian networks (DBN) to investigate associations among self-rated phenomenology and personal/lifestyle factors (role impairment, low social support, and alcohol and substance use) across the 19Up and 25Up waves of the Brisbane Longitudinal Twin Study. We examined whether symptoms and personal/lifestyle factors at 19Up were associated with (a) themselves or different items at 25Up, and (b) onset of a depression-like, hypo-manic-like, or psychotic-like subthreshold syndrome (STS) at 25Up.

The first DBN identified 11 items that when endorsed at 19Up were more likely to be reendorsed at 25Up (e.g., hypersomnia, impaired concentration, impaired sleep quality) and seven items that when endorsed at 19Up were associated with different items being endorsed at 25Up (e.g., earlier fatigue and later role impairment; earlier anergia and later somatic pain). In the second DBN, no arcs met our a priori threshold for inclusion. In an exploratory model with no threshold, >20 items at 19Up were associated with progression to an STS at 25Up (with lower statistical confidence); the top five arcs were: feeling threatened by others and a later psychotic-like STS; increased activity and a later hypo-manic-like STS; and anergia, impaired sleep quality, and/or hypersomnia and a later depression-like STS.

These probabilistic models identify symptoms and personal/lifestyle factors that might prove useful targets for indicated preventative strategies.

Network analysis has been used to explore the interplay between psychopathology and functioning in psychosis, but no study has used dedicated statistical techniques to focus on the bridge symptoms connecting these domains. The current study aims to estimate the network of depressive, negative, and positive symptoms, general psychopathology, and real-world functioning in people with first-episode schizophrenia or schizophreniform disorder, focusing on bridge nodes.

Baseline data from the OPTiMiSE trial were analyzed. The sample included 446 participants (age 40.0 ± 10.9 years, 70% males). The network was estimated with a Gaussian graphical model, using scores on individual items of the positive and negative syndrome scale (PANSS), the Calgary depression scale for schizophrenia, and the personal and social performance scale. Stability, strength centrality, expected influence (EI), predictability, and bridge centrality statistics were computed. The top 20% scoring nodes on bridge strength were selected as bridge nodes.

Nodes from different rating scales assessing similar psychopathological and functioning constructs tended to cluster together in the estimated network. The most central nodes (EI) were Delusions, Emotional Withdrawal, Depression, and Depressed Mood. Bridge nodes included Depression, Conceptual Disorganization, Active Social Avoidance, Delusions, Stereotyped Thinking, Poor Impulse Control, Guilty Feelings, Unusual Thought Content, and Hostility. Most of the bridge nodes belonged to the general psychopathology subscale of the PANSS. Depression (G6) was the bridge node with the highest value.

The current study provides novel insights for understanding the complex phenotype of psychotic disorders and the mechanisms underlying the development and maintenance of comorbidity and functional impairment after psychosis onset.

Young people can receive mental health care from many sources, from formal and informal sectors. Caregiver characteristics/experiences/beliefs may influence whether young people get help and the type of care or support used by their child. We investigate facilitators/barriers to receiving formal and/or informal care, particularly those related to the caregiver’s profile.

We interviewed 1,400 Brazilian primary caregivers of young people (aged 10–19), participants of a high-risk cohort. Caregivers reported on young people’s formal/informal mental health care utilization, and associated barriers and facilitators to care. Data were also collected on youth mental health and its impact on everyday life; and caregiver characteristics—education, socioeconomics, ethnicity, mental health, and stigma. Logistic regression models were used to examine the relationship between caregiver and young people characteristics with formal/informal care utilization.

Persistence and greater impact of youth mental health conditions were associated with a higher likelihood of care, more clearly for formal care. Caregiver characteristics, however, also played a key role in whether young people received any care: lower parental stigma was associated with greater formal service use, and lower socioeconomic class showed higher odds of informal care (mainly from religious leaders).

This study highlights the key role of the caregivers as gatekeepers to child treatment access, particularly parental stigma influencing whether young people received any mental health care, even in a low resource setting. These results help to map barriers for treatment access and delivery for young people, aiming to improve intervention efforts and mental health support.

The first wave of the COVID-19 pandemic in France was associated with a reduced number of hospitalizations for self-harm, with the exception of older people. The on-going pandemic may have both sustained and delayed effects.

Data were extracted from the French national hospital database (PMSI), a nationwide exhaustive database. The number of self-harm hospitalizations (ICD-10 codes X60–84) between September 1, 2020 and August 31, 2021 (N = 85,679) was compared to 2019 (N = 88,782) using Poisson regression models.

There was a decrease in the total number of self-harm hospitalizations during the studied period versus 2019 (−3.5%; Relative Risk [RR] [95% Confidence Intervals] = 0.97 [0.96–0.97]; p < 0.0001). However, sex and age effects were identified. While adults aged 30–59-years-old showed a decrease (monthly decreases: −12.6 to −15.0%), we found an increase in adolescent girls (+27.7%, RR = 1.28 [1.25–1.31]; p < 0.0001), notably since January 2021. Moreover, the numbers were similar to 2019 in adolescent boys, in youths aged 20–29 years, and in people aged 70 and more. Hospitalizations in intensive care units decreased (−6.7%, RR = 0.93 [0.91–0.96]; p < 0.0001) and deaths at hospital following self-harm remained stable (+0.6%, Hazard Ratio = 0.99 [0.91–1.08], p = 0.79).

During this second stage, the number of self-harm hospitalizations remained at a lower level than in the prepandemic period. However, significant variations over time, age, and sex were observed. Young people (notably adolescent girls) appear to have particularly suffered from the persistence of the pandemic, while older people did not show any decrease since the beginning. Vigilance and continuing prevention are warranted.

Despite well-established guidelines for managing major depressive disorder, its extensive disability burden persists. This Value of Treatment mission from the European Brain Council aimed to elucidate the nature and extent of “gaps” between best-practice and current-practice care, specifically to:

1. 1. Identify current treatment gaps along the care pathway and determine the extent of these gaps in comparison with the stepped-care model and

2. 2. Recommend policies intending to better meet patient needs (i.e., minimize treatment gaps).

After agreement upon a set of relevant treatment gaps, data pertaining to each gap were gathered and synthesized from several sources across six European countries. Subsequently, a modified Delphi approach was undertaken to attain consensus among an expert panel on proposed recommendations for minimizing treatment gaps.

Four recommendations were made to increase the depression diagnosis rate (from ~50% episodes), aiming to both increase the number of patients seeking help, and the likelihood of a practitioner to correctly detect depression. These should reduce time to treatment (from ~1 to ~8 years after illness onset) and increase rates of treatment; nine further recommendations aimed to increase rates of treatment (from ~25 to ~50% of patients currently treated), mainly focused on targeting the best treatment to each patient. To improve follow-up after treatment initiation (from ~30 to ~65% followed up within 3 months), seven recommendations focused on increasing continuity of care. For those not responding, 10 recommendations focused on ensuring access to more specialist care (currently at rates of ~5–25% of patients).

The treatment gaps in depression care are substantial and concerning, from the proportion of people not entering care pathways to those stagnating in primary care with impairing and persistent illness. A wide range of recommendations can be made to enhance care throughout the pathway.

The COVID-19 pandemic has drastically impacted many aspects of society and has indirectly produced various psychological consequences. This systematic review aimed to estimate the worldwide prevalence of posttraumatic stress disorder (PTSD) in children due to the COVID-19 pandemic, as well as to identify protective or risk factors contributing to child PTSD.

We conducted a systematic literature search in the PubMed, ProQuest, PsycINFO, Embase, Web of Science, WanFang, CNKI, and VIP databases. We searched for studies published between January 1, 2020 and May 26, 2021, that reported the prevalence of child PTSD due to the COVID-19 pandemic, as well as factors contributing to child PTSD. Eighteen studies were included in our systematic review, of which 10 studies were included in the meta-analysis.

The estimated prevalence of child PTSD after the COVID-19 outbreak was 28.15% (95% CI: 19.46–36.84%, I 2 = 99.7%). In subgroup analyses for specific regions the estimated prevalence of post-pandemic child PTSD was 19.61% (95% CI: 11.23–27.98%) in China, 50.8% (95% CI: 34.12–67.49%) in the USA, and 50.08% in Italy (95% CI: 47.32–52.84%).

Factors contributing to child PTSD were categorized into four aspects: personal factors, family factors, social factors and infectious diseases related factors. Based on this, we presented a new framework summarizing the occurrence and influence of the COVID-19 related child PTSD, which may contribute to a better understanding, prevention and development of interventions for child PTSD in forthcoming pandemics.

Depression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).

The GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.

Two genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10−8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10−8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10−3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10−3, preplication GWAS2 = 8.08 × 10−3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).

Our findings provide novel clues for understanding of the complex genetic architecture of depression.

Individuals with anorexia nervosa (AN) are often thought to show heightened self-control and increased ability to inhibit desires. In addition to inhibitory self-control, antecedent-focused strategies (e.g., cognitive reconstrual—the re-evaluation of tempting situations) might contribute to disorder maintenance and enable disorder-typical, maladaptive behaviors.

Over a period of 14 days, 40 acutely underweight young female patients with anorexia nervosa (AN) and 40 healthy control (HC) participants reported their affect and behavior in self-control situations via ecological momentary assessment during inpatient treatment (AN) and everyday life (HC). Data were analyzed via hierarchical analyses (linear and logistic modeling).

Conflict strength had a significantly lower impact on self-control success in AN compared to HC. While AN and HC did not generally differ in the number or strength of self-control conflicts or in the percentage of self-control success, AN reported self-controlled behavior to be less dependent on conflict strength.

While patients with AN were not generally more successful at self-control, they appeared to resolve self-control conflicts more effectively. These findings suggest that the magnitude of self-control conflicts has comparatively little impact on individuals with AN, possibly due to the use of antecedent-focused strategies. If confirmed, cognitive-behavioral therapy might focus on and help patients to exploit these alternative self-control strategies in the battle against their illness.

Child welfare and juvenile justice placed youths show high levels of psychosocial burden and high rates of mental disorders. It remains unclear how mental disorders develop into adulthood in these populations. The aim was to present the rates of mental disorders in adolescence and adulthood in child welfare and juvenile justice samples and to examine their mental health trajectories from adolescence into adulthood.

Seventy adolescents in shared residential care, placed by child welfare (n = 52, mean age = 15 years) or juvenile justice (n = 18, mean age = 17 years) authorities, were followed up into adulthood (child welfare: mean age = 25 years; juvenile justice: mean age = 27 years). Mental disorders were assessed based on the International Classification of Diseases 10th Revision diagnoses at baseline and at follow-up. Epidemiological information on mental disorders was presented for each group. Bivariate correlations and structural equation modeling for the relationship of mental disorders were performed.

In the total sample, prevalence rates of 73% and 86% for any mental disorder were found in adolescence (child welfare: 70%; juvenile justice: 83%) and adulthood (child welfare: 83%; juvenile justice: 94%) respectively. General psychopathology was found to be stable from adolescence into adulthood in both samples.

Our findings showed high prevalence rates and a high stability of general psychopathology into adulthood among child welfare and juvenile justice adolescents in Swiss residential care. Therefore, continuity of mental health care and well-prepared transitions into adulthood for such individuals is highly warranted.