This study aims to assess the effect of primary health care (PHC) service provision continuity on inpatient admissions for people with chronic diseases in Estonia.

Non-communicable diseases (NCDs) were collectively responsible for more than 7 out of 10 deaths worldwide in 2019. As the burden of NCDs increases, PHC has an increased role of coordinating care management. High-performing PHC can reduce unnecessary hospitalizations. Estonia has a strong PHC system focusing on multidisciplinary care. Yet it has not been evaluated for its effect on hospitalizations. Therefore, it is imperative to evaluate PHC continuity to improve care for NCD patients.

This study used routinely collected electronic medical billing data of the Estonian population aged 15 years or older from 2005 to 2020 identifying patients with seven ambulatory care sensitive chronic (ACSC) conditions. We developed an indicator to describe the continuity of PHC. Charlson Comorbidity Index (CCI) was used to assess the impact of comorbidities and we controlled the patient’s age, gender, county of residency and socio-economic status. We estimated multilevel logistic regression models with family doctor patient list random effects to assess how the odds of hospitalization depend on continuity of care, allowing for confounders.

We identified that 45% of the adult Estonian population had at least one of the target diagnoses. Among the target population, 96% had contact with their PHC providers. We found that there is a non-linear relationship between PHC continuity and patient outcomes. Any contact with PHC provider during the past 5 years decreases odds for hospitalization, but hospitalization risk is higher for people who are elderly and have higher CCI score. We found that after accounting for patient characteristics, differences among patient lists minimally impact outcomes. Further research should explore policies to better support family doctors in reducing hospitalizations for chronic patients.

It is unknown whether there is a general factor that accounts for the propensity for both physical and mental conditions in different age groups and how it is associated with lifestyle and well-being.

We analyzed health conditions data from the Millennium Cohort Study (MCS) (age = 17; N = 19,239), the National Child Development Study (NCDS) (age = 44; N = 9293), and the English Longitudinal Study of Ageing (ELSA) (age ≥ 50; N = 7585). The fit of three Confirmatory Factor models was used to select the optimal solution by Comparative Fit Index, Tucker-Lewis Index, and Root Mean Square Error of Approximation. The relationship among d factor, lifestyles, and well-being was further explored.

Supporting the existence of the d factor, the bi-factor model showed the best model fit in 17-year-olds (MCS:CFI = 0.97, TFI = 0.96, RMSEA = 0.01), 44-year-olds (NCDS:CFI = 0.96, TFI = 0.95, RMSEA = 0.02), and 50+ year-olds (ELSA:CFI = 0.97, TFI = 0.96, RMSEA = 0.02). The d factor scores significantly correlated with lifestyle and well-being, suggesting healthier lifestyles were associated with a reduced likelihood of physical and mental health comorbidities, which in turn improved well-being.

Contrary to the traditional dichotomy between mental and physical conditions, our study showed a general factor underlying the comorbidity across mental and physical diseases, related to lifestyle and well-being. Our results inform the conceptualization of mental and physical illness as well as future research assessing risk and pathways of disease transmission, intervention, and prevention. Our results also provide a strong rationale for a systematic screening for mental disorders in individuals with physical conditions and vice versa, and for integrated services addressing multimorbidity.

Drug and alcohol users have been suggested to face disproportionate exclusion from mental health services, but data on any such exclusion are not readily available. This study examined the clinical records of those excluded from an NHS Talking Therapies service due to drug or alcohol use, focusing on (1) quantitative levels of alcohol consumption, and (2) the rationales documented by clinicians for excluding these individuals. Our results suggest that over half (57%) of those excluded due to alcohol use were consuming below the 15-unit daily threshold recommended for signposting to specialist alcohol assessment. Clinicians cited various rationales for exclusion, including the potential for poor treatment outcomes and health risks associated with concurrent use. Due to being based on a single service, these findings may be limited in their generalisability, but they offer an initial signal that there is potential over-exclusion of some alcohol users from NHS Talking Therapies, and that rationales for exclusion may not consistently align with best practice principles. We discuss implications for NHS Talking Therapies clinicians, and for the development of future clinical guidance.

1. (1) To understand how different levels of drug or alcohol use may affect the outcomes of psychological therapy.

2. (2) To learn why individuals with drug or alcohol use experience exclusion from mental health services.

3. (3) To examine how clinical practice within an NHS Talking Therapies service aligns with best practice principles.

4. (4) To explore skills and clinical principles that can lead to optimal treatment planning for these individuals.

5. (5) To explore how integrated working between NHS Talking Therapies and local drug and alcohol services can enhance service-user experiences.

Alcohol use in autism spectrum disorder (ASD) is under-researched. Previous reviews have explored substance use as a whole, but this neglects individual characteristics unique to different substances. Alcohol use in non-clinical samples is associated with diverse responses. To advance practice and policy, an improved understanding of alcohol use among people with ASD is crucial to meet individual needs.

This was a narrative systematic review of the current literature on the association between alcohol use and ASD, focusing on aetiology (biological, psychological, social and environmental risk factors) and implications (consequences and protective factors) of alcohol use in autistic populations who utilise clinical services. We sought to identify priority research questions and offer policy and practice recommendations.

PROSPERO Registration: CRD42023430291. The search was conducted across five databases: CINAHL, EMBASE, MEDLINE, PsychINFO and Global Health. Included studies explored alcohol use and ASD within clinical samples.

A total of 22 studies was included in the final review. The pooled prevalence of alcohol use disorder in ASD was 1.6% and 16.1% in large population registers and clinical settings, respectively. Four components were identified as possible aetiological risk factors: age, co-occurring conditions, gender and genetics. We identified ten implications for co-occurring alcohol use disorder in ASD, summarised as a concept map.

Emerging trends in the literature suggest direction and principles for research and practice. Future studies should use a standardised methodological approach, including psychometrically validated instruments and representative samples, to inform policy and improve the experience for autistic populations with co-occurring alcohol use.

Substance use may be associated with the onset of psychotic symptoms, necessitating treatment for individuals with comorbid mental health and substance use disorders (MHD/SUD). COVID-19 significantly impacted individuals with MHD/SUD, reducing access to appropriate care and treatment. Changes in drug availability and prices during the pandemic may have influenced drug consumption. This study aimed to determine the frequency of substance-induced psychosis (SIP) during COVID-19 among individuals with MHD/SUD and to explore substance fidelity by following patterns of SIP over time.

In this retrospective cohort study, we analyzed data from all individuals with MHD/SUD registered in 2019–2021 in the Norwegian Patient Register. We used graphical approaches, descriptives, and Poisson regression to study occurrence and risk of SIP episodes in the three-year observation period. Sankey diagrams were used to examine trajectories of psychotic episodes induced by various substances.

Despite a decrease in individuals diagnosed with SIP during COVID-19, SIP episodes increased overall. We observed a decline in cannabis-induced psychosis, but a rise in SIP episodes involving amphetamines and multiple substances. Among individuals with recurrent SIP episodes, the psychosis was more often induced by different substances during COVID-19 (2020: RR, 1.50 [95% CI, 1.34–1.67]; 2021: RR, 1.30 [95% CI, 1.16–1.46]) than in 2019.

During COVID-19, fewer individuals were hospitalized with SIP, but those patients experienced more episodes. There were fewer cannabis-induced psychotic episodes, but more SIP hospitalizations caused by central stimulants and more SIP diagnoses caused by different substances, possibly reflecting changes in drug availability and pricing.

Among those with common mental health disorders (e.g. mood, anxiety, and stress disorders), comorbidity of substance and other addictive disorders is prevalent. To simplify the seemingly complex relationships underlying such comorbidity, methods that include multiple measures to distill which specific addictions are uniquely associated with specific mental health disorders rather than due to the co-occurrence of other related addictions or mental health disorders can be used.

In a general population sample of Jewish adults in Israel (N = 4002), network analysis methods were used to create partial correlation networks of continuous measures of problematic substance (non-medical use of alcohol, tobacco, cannabis, and prescription sedatives, stimulants, and opioid painkillers) and behavioral (gambling, electronic gaming, sexual behavior, pornography, internet, social media, and smartphone) addictions and common mental health problems (depression, anxiety, and post-traumatic stress disorder [PTSD]), adjusted for all variables in the model.

Strongest associations were observed within these clusters: (1) PTSD, anxiety, and depression; (2) problematic substance use and gambling; (3) technology-based addictive behaviors; and (4) problematic sexual behavior and pornography. In terms of comorbidity, the strongest unique associations were observed for PTSD and problematic technology-based behaviors (social media, smartphone), and sedatives and stimulants use; depression and problematic technology-based behaviors (gaming, internet) and sedatives and cannabis use; and anxiety and problematic smartphone use.

Network analysis isolated unique relationships underlying the observed comorbidity between common mental health problems and addictions, such as associations between mental health problems and technology-based behaviors, which is informative for more focused interventions.

Hoarding disorder studies are primarily based on persons who seek treatment and demonstrate good insight. The aim of the present study is to evaluate whether there are differences between community and treatment-seeking samples of individuals with hoarding disorder (HD).

Fourteen people with HD from the community and twenty treatment-seeking people with HD were assessed by a battery of instruments to evaluate HD features and other associated characteristics.

Compared to the treatment-seeking sample, the HD community sample was older, had poorer insight, and had a lower prevalence of comorbid obsessive-compulsive disorder (OCD). There were no differences in gender, education, presence of psychiatric comorbidities, quality of life, and hoarding behavior characteristics between the samples. The final logistic regression model with the Dimensional Obsessive-Compulsive Scale (DOCS) as the single predictor of treatment-seeking status was statistically significant, indicating that it was able to distinguish between the two samples. The model explained between 20.7% and 27.9% of the variance of subjects, and correctly classified 67.6% of cases.

Our results indicate that there appear to be few differences between the treatment-seeking and community samples of individuals with HD. The presence of comorbid OCD in treatment-seeking groups seems to be more frequent than in HD community samples.

Mental disorders and physical-health conditions frequently co-occur, impacting treatment outcomes. While most prior research has focused on single pairs of mental disorders and physical-health conditions, this study explores broader associations between multiple mental disorders and physical-health conditions.

Using the Norwegian primary-care register, this population-based cohort study encompassed all 2 203 553 patients born in Norway from January 1945 through December 1984, who were full-time residents from January 2006 until December 2019 (14 years; 363 million person-months). Associations between seven mental disorders (sleep disturbance, anxiety, depression, acute stress reaction, substance-use disorders, phobia/compulsive disorder, psychosis) and 16 physical-health conditions were examined, diagnosed according to the International Classification of Primary Care.

Of 112 mental-disorder/physical-health condition pairs, 96% of associations yielded positive and significant ORs, averaging 1.41 and ranging from 1.05 (99.99% CI 1.00–1.09) to 2.38 (99.99% CI 2.30–2.46). Across 14 years, every mental disorder was associated with multiple different physical-health conditions. Across 363 million person-months, having any mental disorder was associated with increased subsequent risk of all physical-health conditions (HRs:1.40 [99.99% CI 1.35–1.45] to 2.85 [99.99% CI 2.81–2.89]) and vice versa (HRs:1.56 [99.99% CI 1.54–1.59] to 3.56 [99.99% CI 3.54–3.58]). Associations were observed in both sexes, across age groups, and among patients with and without university education.

The breadth of associations between virtually every mental disorder and physical-health condition among patients treated in primary care underscores a need for integrated mental and physical healthcare policy and practice. This remarkable breadth also calls for research into etiological factors and underlying mechanisms that can explain it.

Forcibly displaced people, such as refugees and asylum-seekers (RAS), are at higher risk of mental disorders, mainly post-traumatic stress disorder (PTSD), depression and anxiety. Little is known about the complex relationships between these mental disorders among culturally and linguistically diverse RAS. To investigate this, the present study applied a novel network analytical approach to examine and compare the central and bridge symptoms within and between PTSD, depression and anxiety among Afghan and Syrian RAS in Türkiye.

A large-scale online survey study with 785 Afghan and 798 Syrian RAS in Türkiye was conducted in 2021. Symptoms of PTSD (the short form of Post-Traumatic Stress Disorders Checklist [PCL-5]), depression and anxiety (Hopkins Symptoms Checklist-25) [HSCL-25]) were measured via self-administrated validated instruments. We conducted network analysis to identify symptoms that are most strongly connected with other symptoms (central symptoms) and those that connect the symptoms of different disorders (bridge symptoms) in R Studio using the qgraph package.

Overall, Afghans and Syrians differed in terms of network structure, but not in network strength. Results showed that feeling blue, feeling restless and spells of terror or panic were the most central symptoms maintaining the overall symptom structure of common mental disorders among Afghan participants. For Syrian participants, worrying too much, feeling blue and feeling tense were identified as the central symptoms. For both samples, anger and irritability and feeling low in energy acted as a bridge connecting the symptoms of PTSD, depression and anxiety.

The current findings provide insights into the interconnectedness within and between the symptoms of common mental disorders and highlight the key symptoms that can be potential targets for psychological interventions for RAS. Addressing these symptoms may aid in tailoring existing evidence-based interventions and enhance their effectiveness. This contributes to reducing the overall mental health burden and improving well-being in this population.

Dextromethorphan/bupropion (DXM/BUP) received Food and Drug Administration (FDA) approval for the treatment of adults with major depressive disorder (MDD) in August 2022. This combination is not known to have abuse liability and is not currently scheduled by the Drug Enforcement Administration (DEA). Notwithstanding, dextromethorphan is a drug of abuse. Herein, we sought to determine whether DXM/BUP has alcohol and/or substance misuse liability.

We evaluated spontaneous reports of terms such as “alcohol problem, alcoholism, alcohol abuse, substance dependence, substance use disorder (SUD), substance abuse, drug dependence, drug use disorder and drug abuse” in the FDA Adverse Event Reporting System (FAERS). The FAERS is a spontaneous reporting database of adverse events submitted to the FDA.

We performed a comparative assessment of the alcohol and/or substance misuse liability of DXM/BUP since its market authorization in August 2022, using acetaminophen as the control. Dextromethorphan served as the upper-bound reference point. Our findings showed that, since August 2022, dextromethorphan had a significant reporting odds ratio (ROR) for “drug abuse.” In contrast, DXM/BUP did not have a significant ROR for any of the categories of alcohol and/or substance misuse evaluated. Limitations of our findings derive largely from the limitations of the FAERS and its data capture method.

The absence of alcohol or substance misuse reported to the FAERS with DXM/BUP accords with the lack of evidence of abuse liability prior to FDA approval and its non-scheduling by the DEA.

Medications are commonly used to treat co-occurring psychopathology in persons with borderline personality disorder (BPD)

To systematically review and integrate the evidence of medications for treatment of co-occurring psychopathology in people with BPD, and explore the role of comorbidities.

Building on the current Cochrane review of medications in BPD, an update literature search was done in March 2024. We followed the methods of this Cochrane review, but scrutinised all identified placebo-controlled trials post hoc for reporting of non BPD-specific (‘co-occurring’) psychopathology, and explored treatment effects in subgroups of samples with and without defined co-occurring disorders. GRADE ratings were done to assess the evidence certainty.

Twenty-two trials were available for quantitative analyses. For antipsychotics, we found very-low-certainty evidence (VLCE) of an effect on depressive symptoms (standardised mean difference (SMD) −0.22, P = 0.04), and low-certainty evidence (LCE) of an effect on psychotic–dissociative symptoms (SMD −0.28, P = 0.007). There was evidence of effects of anticonvulsants on depressive (SMD −0.44, P = 0.02; LCE) and anxious symptoms (SMD −1.11, P < 0.00001; VLCE). For antidepressants, no significant findings were observed (VLCE). Exploratory subgroup analyses indicated a greater effect of antipsychotics in samples including participants with co-occurring substance use disorders on psychotic–dissociative symptoms (P = 0.001).

Our findings, based on VLCE and LCE only, do not support the use of pharmacological interventions in people with BPD to target co-occurring psychopathology. Overall, the current evidence does not support differential treatment effects in persons with versus without defined comorbidities. Medications should be used cautiously to target co-occurring psychopathology.

Accumulating evidence suggests that early life trauma (ELT) initiates and perpetuates a cycle of depression, leading to challenges in management and achieving remission. This scoping review aimed to examine the intricate relationship between ELT and difficult-to-treat depression (DTD). An extensive literature search from 1 January 2013 to 21 October 2023 was conducted using the Cochrane Library, PubMed, Scopus, PsycINFO and OpenGrey.

Our review identified scientific literature illustrating the multifaceted link between ELT and DTD, highlighting the dual impact of ELT on therapeutic resistance and clinical complexity.

This complexity hampers management of patients with DTD, who are characterised by limited pharmacological responsiveness and heightened relapse risk. While exploring the ELT–DTD nexus, the review revealed a paucity of literature on the impact of ELT within DTD. Findings underscore the profound link between ELT and DTD, which is essential for comprehensive understanding and effective management. Tailoring treatments to address ELT could enhance therapeutic outcomes for patients with DTD. Future studies should use larger samples and well-defined diagnostic criteria and explore varied therapeutic approaches.

Major depressive disorder (MDD) is a leading cause of disability and premature mortality. This study compared the overall survival (OS) between patients with MDD and non-MDD controls stratified by gender, age, and comorbidities.

This nationwide population-based cohort study utilized longitudinal patient data (01/01/2010 – 12/31/2020) from the Hungarian National Health Insurance Fund database, which contains healthcare service data for the Hungarian population. Patients with MDD were selected and matched 1:1 to those without MDD using exact matching. The rates of conversion from MDD to bipolar disorder (BD) or schizophrenia were also investigated.

Overall, 471,773 patients were included in each of the matched MDD and non-MDD groups. Patients with MDD had significantly worse OS than non-MDD controls (hazard ratio [HR] = 1.50; 95% CI: 1.48−1.51; males HR = 1.69, 95% CI: 1.66–1.72; females HR = 1.40, 95% CI: 1.38–1.42). The estimated life expectancy of patients with MDD was 7.8 and 6.0 years less than that of controls aged 20 and 45 years, respectively. Adjusted analyses based on the presence of baseline comorbidities also showed that patients with MDD had worse survival than non-MDD controls (adjusted HR = 1.29, 95% CI: 1.28–1.31). After 11 years of follow-up, the cumulative conversions from MDD to BD and schizophrenia were 6.8 and 3.4%, respectively. Converted patients had significantly worse OS than non-converted patients.

Compared with the non-MDD controls, a higher mortality rate in patients with MDD, especially in those with comorbidities and/or who have converted to BD or schizophrenia, suggests that early detection and personalized treatment of MDD may reduce the mortality in patients diagnosed with MDD.

A nationwide register-based cohort study from Finland including 48 124 incident benzodiazepines and related drug (BZDR) users aged 18–65 years who initiated use in 2006 and were not dispensed BZDRs during 2004–2005. The follow-up was 5 years or until death, whichever occurred first.

To investigate sociodemographic and clinical factors associated with high-dose use of BZDRs (i.e. Z-drugs) among new BZDR users.

The temporal BZDR dose was calculated as a point estimate every 6 months after initiation as defined daily doses (DDDs) per day, based on the PRE2DUP method (an approach based on mathematical modelling of personal drug purchasing behaviours). Sociodemographic and clinical factors associated with dose categories were studied using multinomial logistic regression.

During the 5-year follow-up, very high-dose BZDR use was observed in 7.4% (n = 3557) and medium high-dose use in 25.5% (n = 12 266) of the users (corresponding to ≥30 mg and 10–29 mg in diazepam equivalents, respectively). Very high-dose use was more common among men compared with women (10.9% versus 4.6%). Very high-dose use patterns were especially observed in younger age groups (18- to 25-year-olds). Compared with oxazepam, initiating BZDR use with clonazepam (adjusted odds ratio 3.86, 95% CI 3.24–4.60), diazepam (2.05, 1.78–2.36) or alprazolam (1.76, 1.52–2.03) was associated with increased odds for very high-dose use. Both medium high-dose and very high-dose BZDR use were associated with a lower level of education. In all, 58% of very high-dose use occurred in BZDR users who received their first prescription from general practitioners.

Clinicians should be aware of the dose escalation risk especially when prescribing diazepam, alprazolam or clonazepam for psychiatric indications. If BZDRs are needed, our findings suggest favouring oxazepam.

Obesity-related cardiometabolic comorbidity is common in major depressive disorder (MDD). However, sex differences and MDD recurrence may modify the MDD-obesity-link.

Sex-specific associations of MDD recurrence (single [MDDS] or recurrent episodes [MDDR]) and obesity-related traits were analyzed in 4.100 adults (51.6% women) from a cross-sectional population-based cohort in Germany (SHIP-Trend-0). DSM-IV-based lifetime MDD diagnoses and MDD recurrence status were obtained through diagnostic interviews. Obesity-related outcomes included anthropometrics (weight, body mass index, waist- and hip-circumference, waist-to-hip ratio, waist-to-height ratio), bioelectrical impedance analysis of body fat mass and fat-free mass, and subcutaneous (SAT) and visceral adipose tissue (VAT) from abdominal magnetic resonance imaging. Sex-stratified linear regression models predicting obesity-related traits from MDD recurrence status were adjusted for age, education, and current depressive symptoms.

790 participants (19.3%) fulfilled lifetime MDD criteria (23.8% women vs. 14.5% men, p<0.001). In women, MDDS was inversely associated with anthropometric indicators of general and central obesity, while MDDR was positively associated with all obesity-related traits, except waist-to-hip ratio and fat-free mass. In women, MDDR versus MDDS was associated with higher levels of obesity across all outcomes except fat-free mass. In men, MDD was positively associated with SAT regardless of MDD recurrence. Additionally, lifetime MDD was positively associated with VAT in men. Results remained significant in sensitivity analyses after exclusion of participants with current use of antidepressants.

The MDD-obesity association is modified by MDD recurrence and sex independent of current depressive symptoms. Accounting for sex and MDD recurrence may identify individuals with MDD at increased cardiometabolic risk.

Prominent clinical perspectives posit that the interface of autism and (borderline) personality disorder manifests as either a misdiagnosis of the former as the latter or a comorbidity of both. In this editorial, we integrate these disparate viewpoints by arguing that personality difficulties are inherent to the autistic spectrum.