The Personalized Advantage Index (PAI) shows promise as a method for identifying the most effective treatment for individual patients. Previous studies have demonstrated its utility in retrospective evaluations across various settings. In this study, we explored the effect of different methodological choices in predictive modelling underlying the PAI.

Our approach involved a two-step procedure. First, we conducted a review of prior studies utilizing the PAI, evaluating each study using the Prediction model study Risk Of Bias Assessment Tool (PROBAST). We specifically assessed whether the studies adhered to two standards of predictive modeling: refraining from using leave-one-out cross-validation (LOO CV) and preventing data leakage. Second, we examined the impact of deviating from these methodological standards in real data. We employed both a traditional approach violating these standards and an advanced approach implementing them in two large-scale datasets, PANIC-net (n = 261) and Protect-AD (n = 614).

The PROBAST-rating revealed a substantial risk of bias across studies, primarily due to inappropriate methodological choices. Most studies did not adhere to the examined prediction modeling standards, employing LOO CV and allowing data leakage. The comparison between the traditional and advanced approach revealed that ignoring these standards could systematically overestimate the utility of the PAI.

Our study cautions that violating standards in predictive modeling may strongly influence the evaluation of the PAI's utility, possibly leading to false positive results. To support an unbiased evaluation, crucial for potential clinical application, we provide a low-bias, openly accessible, and meticulously annotated script implementing the PAI.

Observational studies consistently report associations between tobacco use, cannabis use and mental illness. However, the extent to which this association reflects an increased risk of new-onset mental illness is unclear and may be biased by unmeasured confounding.

A systematic review and meta-analysis (CRD42021243903). Electronic databases were searched until November 2022. Longitudinal studies in general population samples assessing tobacco and/or cannabis use and reporting the association (e.g. risk ratio [RR]) with incident anxiety, mood, or psychotic disorders were included. Estimates were combined using random-effects meta-analyses. Bias was explored using a modified Newcastle–Ottawa Scale, confounder matrix, E-values, and Doi plots.

Seventy-five studies were included. Tobacco use was associated with mood disorders (K = 43; RR: 1.39, 95% confidence interval [CI] 1.30–1.47), but not anxiety disorders (K = 7; RR: 1.21, 95% CI 0.87–1.68) and evidence for psychotic disorders was influenced by treatment of outliers (K = 4, RR: 3.45, 95% CI 2.63–4.53; K = 5, RR: 2.06, 95% CI 0.98–4.29). Cannabis use was associated with psychotic disorders (K = 4; RR: 3.19, 95% CI 2.07–4.90), but not mood (K = 7; RR: 1.31, 95% CI 0.92–1.86) or anxiety disorders (K = 7; RR: 1.10, 95% CI 0.99–1.22). Confounder matrices and E-values suggested potential overestimation of effects. Only 27% of studies were rated as high quality.

Both substances were associated with psychotic disorders and tobacco use was associated with mood disorders. There was no clear evidence of an association between cannabis use and mood or anxiety disorders. Limited high-quality studies underscore the need for future research using robust causal inference approaches (e.g. evidence triangulation).

Inadequate response to first- and second-line pharmacological treatments for psychiatric disorders is commonly observed. Ketamine has demonstrated efficacy in treating adults with treatment-resistant depression (TRD), with additional off-label benefits reported for various psychiatric disorders. Herein, we performed a systematic review and meta-analysis to examine the therapeutic applications of ketamine across multiple mental disorders, excluding mood disorders.

We conducted a multidatabase literature search of randomized controlled trials and open-label trials investigating the therapeutic use of ketamine in treating mental disorders. Studies utilizing the same psychological assessments for a given disorder were pooled using the generic inverse variance method to generate a pooled estimated mean difference.

The search in OVID (MedLine, Embase, AMED, PsychINFO, JBI EBP Database), EBSCO CINAHL Plus, Scopus, and Web of Science yielded 44 studies. Ketamine had a statistically significant effect on PTSD Checklist for DSM-5 (PCL-5) scores (pooled estimate = ‒28.07, 95% CI = [‒40.05, ‒16.11], p < 0.001), Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) scores (pooled estimate = ‒14.07, 95% CI = [‒26.24, ‒1.90], p = 0.023), and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores (pooled estimate = ‒8.08, 95% CI = [‒13.64, ‒2.52], p = 0.004) in individuals with PTSD, treatment-resistant PTSD (TR-PTSD), and obsessive compulsive disorder (OCD), respectively. For alcohol use disorders and at-risk drinking, there was disproportionate reporting of decreased urge to drink, increased rate of abstinence, and longer time to relapse following ketamine treatment.

Extant literature supports the potential use of ketamine for the treatment of PTSD, OCD, and alcohol use disorders with significant improvement of patient symptoms. However, the limited number of randomized controlled trials underscores the need to further investigate the short- and long-term benefits and risks of ketamine for the treatment of psychiatric disorders.

Although there is now substantial evidence on the acute impacts of the COVID-19 pandemic on anxiety disorders, the long-term population impact of the pandemic remains largely unexplored.

To quantify a possible longitudinal population-level impact of the pandemic by projecting the prevalence of anxiety disorders through 2030 among men and women aged up to 95 years in Germany under scenarios with varying impacts of the pandemic on the incidence of anxiety disorders.

We used a three-state illness–death model and data from the Global Burden of Disease Study to model historical trends of the prevalence and incidence of anxiety disorders. The German population projections determined the initial values for projections. The COVID-19 incidence rate data informed an additional incidence model, which was parameterised with a wash-in period, delay, wash-out period, incidence increase level and decay constant.

When no additional increase in the incidence during the pandemic waves during 2020–2022 was assumed, it was estimated that 3.86 million women (9.96%) and 2.13 million men (5.40%) would have anxiety disorders in 2030. When increases in incidence following pandemic waves were assumed, the most extreme scenario projected 5.67 million (14.02%) women and 3.30 million (8.14%) men with the mental disorder in 2030.

Any increased incidence during the pandemic resulted in elevated prevalence over the projection period. Projection of anxiety disorder prevalence based on the illness–death model enables simulations with varying assumptions and provides insight for public health planning. These findings should be refined as trend data accumulate and become available.

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.

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.

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.

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.

Anxiety related school avoidance can affect up to 5% of a country’s students each year. VRET (Virtual Reality Exposure Therapy) is a novel therapy proven to be as effective as conventional approaches for treating many anxiety disorders. The aim of this research is to co-design and evaluate a VRET intervention for students experiencing school related anxiety.

Eighteen adolescents participated in design thinking workshops where they developed a script and storyboard for the VRET. Using an iterative approach, a VRET prototype was developed based on this work. Eighteen teenagers were subsequently recruited to engage with the VRET for one session each and provide feedback on their experience via a structured questionnaire (supervised by a study coordinator) particularly focusing on the ability of the VR experience to reduce school related anxiety.

Exposure therapy needs to produce an anxiety response to be effective. The VRET was effective in producing an anxiety response in 89% of participants. Results demonstrated that 93% of participants found the simulations immersive, 94% found the scenarios believable, and 83% could relate to ‘Dala’, the avatar in the videos. 100% of participants believed that VRET would help with school anxiety.

This proof-of-concept study demonstrates favourable face validity indicating promise for this mode of intervention for delivering targeted support to anxious students. VRET could be used as a scalable, cost effective early intervention to reduce the severity of anxiety associated with school avoidance.

Approximately 15% of pregnant women experience anxiety disorders. Effective treatments exist but their acceptability during pregnancy, particularly exposure therapy, is not known.

To understand patient and therapist experiences of time-intensive and weekly exposure-based therapy for anxiety disorders delivered during pregnancy. Trial registration: ISRCTN81203286.

In-depth interviews were conducted with patients and therapists who had taken part in a feasibility trial of predominantly online time-intensive versus weekly cognitive–behavioural therapy in pregnancy in a primary care setting in the UK. Data were analysed using reflexive thematic analysis.

In total, 45 women participating in the trial and 6 therapists who had delivered the treatments were interviewed. Five themes were developed from the data that showed convergence from therapist and patient perspectives: ‘Acquiring tools to navigate the perinatal period’; ‘Motivated yet constrained by pregnancy’; ‘Having the confidence to face fears and tolerate uncertainty’; ‘Momentum with the need for flexibility’; ‘Being removed from the face-to-face world’.

Exposure therapy is acceptable and helpful in pregnancy and can lead to lasting gains. Exposure is a key element of treatment and needs to be confidently conducted by therapists with perinatal knowledge and expertise. Treatments need to consider the unfolding context of pregnancy. The momentum of intensive therapy can lead to rapid improvements, but is demanding for both patients and therapists, especially fitting round other commitments. Online treatments can work well and are a good fit for perinatal women, but this needs to be balanced with the need for social connection, suggesting a hybrid model is the ideal.

Anxiety disorders are the most frequently diagnosed psychiatric conditions in children and adolescents. Cognitive behavioural therapy (CBT) is a well-established and effective treatment for anxiety and related disorders across the lifespan. Expectations of psychotherapy have been demonstrated to affect outcomes, yet there is sparse existing literature on adolescent patient and parent perspectives of CBT prior to engagement with treatment.

This study aimed to qualitatively explore the expectations and perceptions of CBT for anxiety and related disorders among adolescent patients and parents.

Fourteen adolescent patients and 16 parents participated in semi-structured individual interviews or focus groups consisting of 2–3 participants. Interview transcripts were analysed using inductive analysis.

Three themes were identified: worries about CBT, expectations and knowledge of the CBT process, and the role of parents and families. Overall, we found that adolescents and parents had generally positive views of CBT. The outset of CBT saw adolescents and parents express concern about stigma as well as the ambiguity of CBT. Parents continued to express a lack of understanding of what CBT entailed during their child’s treatment course.

These results suggest that both adolescents and parents would benefit from early discussion and reinforcement of expectations for CBT treatment. Further research efforts are warranted and should be directed towards determining appropriate expectations for parental involvement in a child’s CBT course and effective communication of treatment expectations to both adolescents and parents.

1. (1) To describe the role of excessive reassurance seeking in checking behaviour, including its negative personal and interpersonal consequences.

2. (2) To learn that therapists commonly report finding it difficult to manage reassurance seeking.

3. (3) To learn that therapists’ beliefs about excessive reassurance seeking may play a key role in helping us understand how to tackle this complicated behaviour.

4. (4) To consider what therapeutic interventions may be appropriate and helpful for treating excessive reassurance seeking.

Perinatal mental health (PMH) problems are a leading cause of maternal death and increase the risk of poor outcomes for women and their families. It is therefore important to identify the barriers and facilitators to implementing and accessing PMH care.

To develop a conceptual framework of barriers and facilitators to PMH care to inform PMH services.

Relevant literature was systematically identified, categorised and mapped onto the framework. The framework was then validated through evaluating confidence with the evidence base and feedback from stakeholders (women and families, health professionals, commissioners and policy makers).

Barriers and facilitators to PMH care were identified at seven levels: individual (e.g. beliefs about mental illness), health professional (e.g. confidence addressing perinatal mental illness), interpersonal (e.g. relationship between women and health professionals), organisational (e.g. continuity of carer), commissioner (e.g. referral pathways), political (e.g. women's economic status) and societal (e.g. stigma). The MATRIx conceptual frameworks provide pictorial representations of 66 barriers and 39 facilitators to PMH care.

The MATRIx frameworks highlight the complex interplay of individual and system-level factors across different stages of the care pathway that influence women accessing PMH care and effective implementation of PMH services. Recommendations are made for health policy and practice. These include using the conceptual frameworks to inform comprehensive, strategic and evidence-based approaches to PMH care; ensuring care is easy to access and flexible; providing culturally sensitive care; adequate funding of services and quality training for health professionals, with protected time to complete it.

Preventing the occurrence of depression/anxiety and suicide during adolescence can lead to substantive health gains over the course of an individual person’s life. This study set out to identify the expected population-level costs and health impacts of implementing universal and indicated school-based socio-emotional learning (SEL) programs in different country contexts.

A Markov model was developed to examine the effectiveness of delivering universal and indicated school-based SEL programs to prevent the onset of depression/anxiety and suicide deaths among adolescents. Intervention health impacts were measured in healthy life years gained (HLYGs) over a 100-year time horizon. Country-specific intervention costs were calculated and denominated in 2017 international dollars (2017 I$) under a health systems perspective. Cost-effectiveness findings were subsequently expressed in terms of I$ per HLYG. Analyses were conducted on a group of 20 countries from different regions and income levels, with final results aggregated and presented by country income group – that is, low and lower middle income countries (LLMICs) and upper middle and high-income countries (UMHICs). Uncertainty and sensitivity analyses were conducted to test model assumptions.

Implementation costs ranged from an annual per capita investment of I$0.10 in LLMICs to I$0.16 in UMHICs for the universal SEL program and I$0.06 in LLMICs to I$0.09 in UMHICs for the indicated SEL program. The universal SEL program generated 100 HLYGs per 1 million population compared to 5 for the indicated SEL program in LLMICs. The cost per HLYG was I$958 in LLMICS and I$2,006 in UMHICs for the universal SEL program and I$11,123 in LLMICs and I$18,473 in UMHICs for the indicated SEL program. Cost-effectiveness findings were highly sensitive to variations around input parameter values involving the intervention effect sizes and the disability weight used to estimate HLYGs.

The results of this analysis suggest that universal and indicated SEL programs require a low level of investment (in the range of I$0.05 to I$0.20 per head of population) but that universal SEL programs produce significantly greater health benefits at a population level and therefore better value for money (e.g., less than I$1,000 per HLYG in LLMICs). Despite producing fewer population-level health benefits, the implementation of indicated SEL programs may be justified as a means of reducing population inequalities that affect high-risk populations who would benefit from a more tailored intervention approach.

Collaborative care (CC) and consultation liaison (CL) are two conceptual models aiming to improve mental healthcare in primary care. The effects of these models have not been compared in a Danish setting.

To examine the effects of CC versus CL for persons with anxiety and depression in Danish general practices (trial registration: NCT03113175 and NCT03113201).

Two randomised parallel superiority trials for anxiety disorders and depression were carried out in 2018–2019. In the CC-group, care managers collaborated with general practitioners (GPs) to provide evidence-based treatment according to structured treatment plans. They followed up and provided psychoeducation and/or cognitive–behavioural therapy. The GPs initiated pharmacological treatment if indicated, and a psychiatrist provided supervision. In the CL-group, the intervention consisted of the GP's usual treatment. However, the psychiatrist and care manager could be consulted. Primary outcomes were depression symptoms (Beck Depression Inventory-II, BDI-II) in the depression trial and anxiety symptoms (Beck Anxiety Inventory, BAI) in the anxiety trial at 6-month follow-up.

In total, 302 participants with anxiety disorders and 389 participants with depression were included. A significant difference in BDI-II score was found in the depression trial, with larger symptom reductions in the CC-group (CC: 12.7, 95% CI 11.4–14.0; CL: 17.5, 95% CI 16.2–18.9; Cohen's d = −0.50, P ≤ 0.001). There was a significant difference in BAI in the anxiety trial (CC: 14.9, 95% CI 13.5–16.3; CL: 17.9, 95% CI 16.5–19.3; Cohen's d = −0.34, P ≤ 0.001), with larger symptom reductions in the CC-group.

Collaborative care was an effective model to improve outcomes for persons with depression and anxiety disorders.

Guided self-help (GSH) for anxiety is widely implemented in primary care services because of service efficiency gains, but there is also evidence of poor acceptability, low effectiveness and relapse.

The aim was to compare preferences for, acceptability and efficacy of cognitive–behavioural guided self-help (CBT-GSH) versus cognitive–analytic guided self-help (CAT-GSH).

This was a pragmatic, randomised, patient preference trial (Clinical trials identifier: NCT03730532). The Beck Anxiety Inventory (BAI) was the primary outcome at 8- and 24-week follow-up. Interventions were delivered competently on the telephone via structured workbooks over 6–8 (30–35 min) sessions by trained practitioners.

A total of 271 eligible participants were included, of whom 19 (7%) accepted being randomised and 252 (93%) chose their treatment. In the preference cohort, 181 (72%) chose CAT-GSH and 71 (28%) preferred CBT-GSH. BAI outcomes in the preference and randomised cohorts did not differ at 8 weeks (−0.80, 95% confidence interval (CI) −4.52 to 2.92) or 24 weeks (0.85, 95% CI −2.87 to 4.57). After controlling for allocation method and baseline covariates, there were no differences between CAT-GSH and CBT-GSH at 8 weeks (F(1, 263) = 0.22, P = 0.639) or at 24 weeks (F(1, 263) = 0.22, P = 0.639). Mean BAI change from baseline was a reduction of 9.28 for CAT-GSH and 9.78 for CBT-GSH at 8 weeks and 12.90 for CAT-GSH and 12.43 for CBT-GSH at 24 weeks.

Patients accessing routine primary care talking treatments prefer to choose the intervention they receive. CAT-GSH expands the treatment offer in primary care for patients with anxiety seeking a brief but analytically informed GSH solution.