Which individual, social, and urban factors in early childhood predict psychopathology in later childhood, adolescence and young adulthood? A systematic review.

Background: A comprehensive picture is lacking of the impact of early childhood (age 0-5) risk factors on the subsequent development of mental health symptoms. Objective: In this systematic review, we investigated which individual, social and urban factors, experienced in early childhood, contribute to the development of later anxiety and depression, behavioural problems, and internalising and externalising symptoms in youth. Methods: Embase, MEDLINE, Scopus, and PsycInfo were searched on the 5th of January 2022. Three additional databases were retrieved from a mega-systematic review source that focused on the identification of both risk and protective indicators for the onset and maintenance of prospective depressive, anxiety and substance use disorders. A total of 46,450 records were identified and screened in ASReview, an AI-aided systematic review tool. We included studies with experimental, quasi-experimental, prospective and longitudinal study designs, while studies that focused on biological and genetical factors, were excluded. Results: Twenty studies were included. The majority of studies explored individual-level risk factors (N = 16). Eleven studies also explored social risk factors and three studied urban risk factors. We found evidence for early predictors relating to later psychopathology measures (i.e., anxiety and depression, behavioural problems, and internalising and externalising symptoms) in childhood, adolescence and early adulthood. These were: parental psychopathology, exposure to parental physical and verbal violence and social and neighbourhood disadvantage. Conclusions: Very young children are exposed to a complex mix of risk factors, which operate at different levels and influence children at different time points. The urban environment appears to have an effect on psychopathology but it is understudied compared to individual-level factors. Moreover, we need more research exploring the interaction between individual, social and urban factors.

Identifying relapse predictors in individual participant data with decision trees.

BACKGROUND: Depression is a highly common and recurrent condition. Predicting who is at most risk of relapse or recurrence can inform clinical practice. Applying machine-learning methods to Individual Participant Data (IPD) can be promising to improve the accuracy of risk predictions. METHODS: Individual data of four Randomized Controlled Trials (RCTs) evaluating antidepressant treatment compared to psychological interventions with tapering ([Formula: see text]) were used to identify predictors of relapse and/or recurrence. Ten baseline predictors were assessed. Decision trees with and without gradient boosting were applied. To study the robustness of decision-tree classifications, we also performed a complementary logistic regression analysis. RESULTS: The combination of age, age of onset of depression, and depression severity significantly enhances the prediction of relapse risk when compared to classifiers solely based on depression severity. The studied decision trees can (i) identify relapse patients at intake with an accuracy, specificity, and sensitivity of about 55% (without gradient boosting) and 58% (with gradient boosting), and (ii) slightly outperform classifiers that are based on logistic regression. CONCLUSIONS: Decision tree classifiers based on multiple-rather than single-risk indicators may be useful for developing treatment stratification strategies. These classification models have the potential to contribute to the development of methods aimed at effectively prioritizing treatment for those individuals who require it the most. Our results also underline the existing gaps in understanding how to accurately predict depressive relapse.

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort.

BACKGROUND: People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare. AIMS: To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk. METHOD: Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological). RESULTS: People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors. CONCLUSIONS: People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

The effects of neighbourhood social cohesion on preventing depression and anxiety among adolescents and young adults: rapid review.

BACKGROUND: Research suggests that increasing neighbourhood social cohesion can prevent mental health problems, including depression and anxiety. However, it is unknown whether this is the case for adolescents and young adults. AIMS: To investigate whether neighbourhood social cohesion can prevent depression and anxiety, and identify interventions that can increase neighbourhood cohesion in young people. METHOD: We conducted a rapid review for an overview of the available literature. PubMed, Campbell Collaboration, KSR Ltd and grey literature databases were searched from inception up to 10 July 2020. When synthesising the results, we applied a hierarchy of evidence, prioritising study designs that allowed for the most ability to infer causality. Risk of bias was assessed with the ROBIS tool and Joanna Briggs Institute risk-of-bias assessment. A narrative review and two workshops with young people were conducted to inform what future interventions may look like. RESULTS: Forty-two peer-reviewed publications, including two systematic reviews, 13 longitudinal studies and 27 cross-sectional studies, were identified. Prospective longitudinal studies found that neighbourhood social cohesion factors (safety, trust, positive social connections, helping others and a lack of crime and violence) were associated with fewer depressive symptoms. Future interventions to increase neighbourhood cohesion should involve creating safe and attractive community centres, accessible and safe outdoor spaces, community activity groups and online communities. CONCLUSIONS: Neighbourhood social cohesion has the potential to protect mental health. The next step is to conduct intervention studies to evaluate the effects on onset prevention. Clinicians should consider the impact cohesion can have on mental health, and signpost to community initiatives.

Advancing urban mental health research: from complexity science to actionable targets for intervention.

Urbanisation and common mental disorders (CMDs; ie, depressive, anxiety, and substance use disorders) are increasing worldwide. In this Review, we discuss how urbanicity and risk of CMDs relate to each other and call for a complexity science approach to advance understanding of this interrelationship. We did an ecological analysis using data on urbanicity and CMD burden in 191 countries. We found a positive, non-linear relationship with a higher CMD prevalence in more urbanised countries, particularly for anxiety disorders. We also did a review of meta-analytic studies on the association between urban factors and CMD risk. We identified factors relating to the ambient, physical, and social urban environment and showed differences per diagnosis of CMDs. We argue that factors in the urban environment are likely to operate as a complex system and interact with each other and with individual city inhabitants (including their psychological and neurobiological characteristics) to shape mental health in an urban context. These interactions operate on various timescales and show feedback loop mechanisms, rendering system behaviour characterised by non-linearity that is hard to predict over time. We present a conceptual framework for future urban mental health research that uses a complexity science approach. We conclude by discussing how complexity science methodology (eg, network analyses, system-dynamic modelling, and agent-based modelling) could enable identification of actionable targets for treatment and policy, aimed at decreasing CMD burdens in an urban context.

Promoting and Protecting Mental Health: A Delphi Consensus Study for Actionable Public Mental Health Messages.

PURPOSE: Public health campaigns are still relatively rare in mental health. This paper aims to find consensus on the preventive self-management actions (i.e. "healthy behaviors") for common mental health problems (e.g. depression and anxiety) that should be recommended in mental health campaigns directed at the general public. APPROACH: A 3-round Delphi study. PARTICIPANTS: 23 international experts in mental health and 1447 members of the public, most of whom had lived experience of mental health problems. METHOD: The modified Delphi study combined quantitative and qualitative data collection: 1) online qualitative survey data collection thematically analyzed, 2) recommendations rated for consensus, 3) consensus items rated by public panel on a Likert scale. RESULTS: Expert consensus was reached on 15 behaviors that individuals can engage in to sustain mental health. Eight were rated as appropriate by more than half (50%) of the public panel, including: avoiding illicit drugs (80%, n = 1154), reducing debt (72%, n = 1043), improving sleep (69%, n = 1000), regulating mood (65%, n = 941), having things to look forward to (60%, n = 869). CONCLUSIONS: A series of healthy behaviors for the promotion and protection of mental health received expert and public consensus. To our knowledge, this is the first study to offer a set of actions for public health messaging for the prevention of poor mental health. Future research should focus on evaluating effectiveness of these actions in a universal primary prevention context.

Initial treatment choices to achieve sustained response in major depression: a systematic review and network meta-analysis.

Major depression is often a relapsing disorder. It is therefore important to start its treatment with therapies that maximize the chance of not only getting the patients well but also keeping them well. We examined the associations between initial treatments and sustained response by conducting a network meta-analysis of randomized controlled trials (RCTs) in which adult patients with major depression were randomized to acute treatment with a psychotherapy (PSY), a protocolized antidepressant pharmacotherapy (PHA), their combination (COM), standard treatment in primary or secondary care (STD), or pill placebo, and were then followed up through a maintenance phase. By design, acute phase treatment could be continued into the maintenance phase, switched to another treatment or followed by discretionary treatment. We included 81 RCTs, with 13,722 participants. Sustained response was defined as responding to the acute treatment and subsequently having no depressive relapse through the maintenance phase (mean duration: 42.2±16.2 weeks, range 24-104 weeks). We extracted the data reported at the time point closest to 12 months. COM resulted in more sustained response than PHA, both when these treatments were continued into the maintenance phase (OR=2.52, 95% CI: 1.66-3.85) and when they were followed by discretionary treatment (OR=1.80, 95% CI: 1.21-2.67). The same applied to COM in comparison with STD (OR=2.90, 95% CI: 1.68-5.01 when COM was continued into the maintenance phase; OR=1.97, 95% CI: 1.51-2.58 when COM was followed by discretionary treatment). PSY also kept the patients well more often than PHA, both when these treatments were continued into the maintenance phase (OR=1.53, 95% CI: 1.00-2.35) and when they were followed by discretionary treatment (OR=1.66, 95% CI: 1.13-2.44). The same applied to PSY compared with STD (OR=1.76, 95% CI: 0.97-3.21 when PSY was continued into the maintenance phase; OR=1.83, 95% CI: 1.20-2.78 when PSY was followed by discretionary treatment). Given the average sustained response rate of 29% on STD, the advantages of PSY or COM over PHA or STD translated into risk differences ranging from 12 to 16 percentage points. We conclude that PSY and COM have more enduring effects than PHA. Clinical guidelines on the initial treatment choice for depression may need to be updated accordingly.

Continuation of Antidepressants vs Sequential Psychological Interventions to Prevent Relapse in Depression: An Individual Participant Data Meta-analysis.

Importance: Depression frequently recurs. To prevent relapse, antidepressant medication is often taken in the long term. Sequentially delivering a psychological intervention while undergoing tapering of antidepressant medication might be an alternative to long-term antidepressant use. However, evidence is lacking on which patients may benefit from tapering antidepressant medication while receiving a psychological intervention and which should continue the antidepressant therapy. A meta-analysis of individual patient data with more power and precision than individual randomized clinical trials or a standard meta-analysis is warranted. Objectives: To compare the associations between use of a psychological intervention during and/or after antidepressant tapering vs antidepressant use alone on the risk of relapse of depression and estimate associations of individual clinical factors with relapse. Data Sources: PubMed, the Cochrane Library, Embase, and PsycInfo were last searched on January 23, 2021. Requests for individual participant data from included randomized clinical trials (RCTs) were sent. Study Selection: Randomized clinical trials that compared use of a psychological intervention while tapering antidepressant medication with antidepressant monotherapy were included. Patients had to be in full or partial remission from depression. Two independent assessors conducted screening and study selection. Data Extraction and Synthesis: Of 15 792 screened studies, 236 full-text articles were retrieved, and 4 RCTs that provided individual participant data were included. Main Outcomes and Measures: Time to relapse and relapse status over 15 months measured via a blinded assessor using a diagnostic clinical interview. Results: Individual data from 714 participants (mean [SD] age, 49.2 [11.5] years; 522 [73.1%] female) from 4 RCTs that compared preventive cognitive therapy or mindfulness-based cognitive therapy during and/or after antidepressant tapering vs antidepressant monotherapy were available. Two-stage random-effects meta-analysis found no significant difference in time to depressive relapse between use of a psychological intervention during tapering of antidepressant medication vs antidepressant therapy alone (hazard ratio [HR], 0.86; 95% CI, 0.60-1.23). Younger age at onset (HR, 0.98; 95% CI, 0.97-0.99), shorter duration of remission (HR, 0.99; 95% CI, 0.98-1.00), and higher levels of residual depressive symptoms at baseline (HR, 1.07; 95% CI, 1.04-1.10) were associated with a higher overall risk of relapse. None of the included moderators were associated with risk of relapse. Conclusions and Relevance: The findings of this individual participant data meta-analysis suggest that regardless of the clinical factors included in these studies, the sequential delivery of a psychological intervention during and/or after tapering may be an effective relapse prevention strategy instead of long-term use of antidepressants. These results could be used to inform shared decision-making in clinical practice.

A systematic review of mental health measurement scales for evaluating the effects of mental health prevention interventions.

BACKGROUND: Consistent and appropriate measurement is needed in order to improve understanding and evaluation of preventative interventions. This review aims to identify individual-level measurement tools used to evaluate mental health prevention interventions to inform harmonization of outcome measurement in this area. METHODS: Searches were conducted in PubMed, PsychInfo, CINAHL, Cochrane and OpenGrey for studies published between 2008 and 2018 that aimed to evaluate prevention interventions for common mental health problems in adults and used at least one measurement scale (PROSPERO CRD42018095519). For each study, mental health measurement tools were identified and reviewed for reliability, validity, ease-of-use and cultural sensitivity. RESULTS: A total of 127 studies were identified that used 65 mental health measurement tools. Most were used by a single study (57%, N = 37) and measured depression (N = 20) or overall mental health (N = 18). The most commonly used questionnaire (15%) was the Centre for Epidemiological Studies Depression Scale. A further 125 tools were identified which measured non-mental health-specific outcomes. CONCLUSIONS: There was little agreement in measurement tools used across mental health prevention studies, which may hinder comparison across studies. Future research on measurement properties and acceptability of measurements in applied and scientific settings could be explored. Further work on supporting researchers to decide on appropriate outcome measurement for prevention would be beneficial for the field.

Individual participant data (IPD) meta-analysis of psychological relapse prevention interventions versus control for patients in remission from depression: a protocol.

INTRODUCTION: Psychological interventions and antidepressant medication can be effective interventions to prevent depressive relapse for patients currently in remission of depression. Less is known about overall factors that predict or moderate treatment response for patients receiving a psychological intervention for recurrent depression. This is a protocol for an individual participant data (IPD) meta-analysis which aims to assess predictors and moderators of relapse or recurrence for patients currently in remission from depression. METHODS AND ANALYSIS: Searches of PubMed, PsycINFO, Embase and Cochrane Central Register of Controlled Trials were completed on 13 October 2019. Study extractions and risk of bias assessments have been completed. Study authors will be asked to contribute IPD. Standard aggregate meta-analysis and IPD analysis will be conducted, and the outcomes will be compared with assess whether results differ between studies supplying data and those that did not. IPD files of individual data will be merged and variables homogenised where possible for consistency. IPD will be analysed via Cox regression and one and two-stage analyses will be conducted. ETHICS AND DISSEMINATION: The results will be published in peer review journals and shared in a policy briefing as well as accessible formats and shared with a range of stakeholders. The results will inform patients and clinicians and researchers about our current understanding of more personalised ways to prevent a depressive relapse. No local ethics approval was necessary following consultation with the legal department. Guidance on patient data storage and management will be adhered to. PROSPERO REGISTRATION NUMBER: CRD42019127844.

The Effects of Meditation, Yoga, and Mindfulness on Depression, Anxiety, and Stress in Tertiary Education Students: A Meta-Analysis.

Background: Meditation, yoga, and mindfulness are popular interventions at universities and tertiary education institutes to improve mental health. However, the effects on depression, anxiety, and stress are unclear. This study assessed the effectiveness of meditation, yoga, and mindfulness on symptoms of depression, anxiety, and stress in tertiary education students. Methods: We searched Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, PsycINFO and identified 11,936 articles. After retrieving 181 papers for full-text screening, 24 randomized controlled trials were included in the qualitative analysis. We conducted a random-effects meta-analysis amongst 23 studies with 1,373 participants. Results: At post-test, after exclusion of outliers, effect sizes for depression, g = 0.42 (95% CI: 0.16-0.69), anxiety g = 0.46 (95% CI: 0.34-0.59), stress g = 0.42 (95% CI: 0.27-0.57) were moderate. Heterogeneity was low (I 2 = 6%). When compared to active control, the effect decreased to g = 0.13 (95% CI: -0.18-0.43). No RCT reported on safety, only two studies reported on academic achievement, most studies had a high risk of bias. Conclusions: Most studies were of poor quality and results should be interpreted with caution. Overall moderate effects were found which decreased substantially when interventions were compared to active control. It is unclear whether meditation, yoga or mindfulness affect academic achievement or affect have any negative side effects.

Unleashing talent in mental health sciences: gender equality at the top.

Society is undergoing a shift in gender politics. Science and medicine are part of this conversation, not least as women's representation and pay continue to drop as one progresses through more senior academic and clinical levels. Naming and redressing these inequalities needs to be a priority for us all.Declaration of interestNone.