Depression is the most common mental health disorder among the older populations, leading to a higher reduction in quality of life and an increased financial burden on the health care system. One promising non-pharmacological approach for improving mental health in older adults is the use of art-based interventions.

This systematic review and meta-analysis followed PRISMA guidelines. Eligible randomized controlled trials (RCTs) examined any form of art intervention (including music, dance, and visual arts) targeting depression in adults aged > 55 years. Databases searched included PubMed, Scopus, Web of Science, PsycINFO, and the Cochrane Library through July 2025. Two reviewers independently extracted data, assessed risk of bias using the Cochrane RoB 2 tool, and determined study eligibility. Standardized mean differences (SMDs) were calculated using random-effects meta-analysis, followed by subgroup analyses, meta-regression, and publication bias assessment (Egger's test and funnel plot).

Out of the 41 RCTs reviewed, 37 report results from 23 of these studies and were eligible for meta-analysis, including a total of 3791 participants. In the pooled analysis, it was revealed that art-based interventions had a greater impact in lowering levels of depression as compared to their respective controls (SMD =  - 0.93, 95% CI: - 1.19 to - 0.68, p < 0.001) and had a high degree of heterogeneity (I² = 91.7%). Subgroup analyses suggested receptive interventions had a stronger effect (SMD =  - 1.97, 95% CI: - 1.43 to - 2.50, p < 0.001) than active interventions (SMD =  - 0.67, 95% CI: - 0.42 to - 0.91, p < 0.001) and interventions provided in the hospital or care home settings. Also, meta-regressions showed no significant association of effect size with the independent variables of age of subjects, number of sessions, or duration of intervention. Most of the studies had moderate to high risk of bias. Egger's test indicated no significant publication bias (p = 0.133).

Art-based interventions effectively reduce depression in older adults and can serve as valuable complements to mental health strategies for aging populations. However, due to heterogeneous study designs and variable quality, additional high-quality trials are needed to confirm these benefits and optimize intervention delivery.

Fibromyalgia (FM) is a disease primarily associated with chronic widespread pain, but other common symptoms are anxiety and depression. We previously proposed that autoimmunity contributes to FM based on findings of increased immunoglobulin G binding to satellite glial cells (anti-SGC IgG) in FM subjects compared to healthy controls (HC). Emerging research suggests that an altered gut microbiota composition is connected to psychological symptoms in FM. Gut microbiota can produce or alter bile acids (BAs) and short-chain fatty acids (SCFAs), which have important immune and inflammatory functions. Here, we investigate alterations in BA and SCFA concentrations in FM subjects compared to HC and potential associations with FM symptoms and anti-SGC IgG levels. Bile acids and SCFAs were quantified using liquid chromatography coupled with high-resolution mass spectrometry and anti-SGC IgG levels were assessed with immunocytochemistry. The correlations between FM symptoms, anti-SGC IgG levels, and serum concentrations of 24 BAs and 11 SCFAs in 35 FM subjects and 32 matched HC were examined. Fibromyalgia subjects had significantly higher levels of non-conjugated microbially produced (secondary) BAs compared to HC. Additionally, total BA levels were significantly elevated in FM subjects with high, compared to those with low, anti-SGC IgG levels. Concentrations of specific BAs were associated with increased disease severity and poorer mental well-being. These results revealed increased levels of non-conjugated secondary BAs in FM subjects compared to HC. The strong association between BAs, anti-SGC IgG levels, and mental well-being may help elucidate the importance of BAs in the psychological symptoms of FM.

Chronic opioid use suppresses hypothalamic-pituitary signalling, leading to hypogonadism and adrenal insufficiency. Whether these abnormalities persist following long-term opioid cessation remains unclear. In particular, data on the female gonadal axis are limited, while other endocrine outcomes are predominantly reported in male cohorts. This study examined endocrine function in a long-term prospective cohort of people with opioid use disorder, comparing those in sustained remission with those continuing opioid use, exploring associations with opioid exposure, sex and depression.

Prospective cohort study using data from the Australian Treatment Outcome Study 18-20 year follow-up.

Participants underwent a structured interview and fasting endocrine assessment, including gonadal, adrenal, thyroid, and prolactin measurements. Endocrinopathies were defined using prespecified biochemical and clinical criteria. Prevalence was compared between opioid-free and opioid-using participants. Associations with opioid exposure, sex and depression were examined using Firth logistic regression.

Among 123 participants with complete endocrine data, 71 (57.7%) had at least one endocrinopathy. Thirty-five participants (28.4%) were opioid-free. Hypogonadism was markedly less common in opioid-free participants (3.3% vs. 26.7%), and no opioid-free participant had hypocortisolism, compared with 14.8% of those with continuing opioid use. Methadone dose, male sex, and depression were independently associated with hypogonadism. Men prescribed methadone had significantly lower testosterone and luteinising hormone levels. No participant with hypogonadism or hypocortisolism had been previously diagnosed or treated.

Opioid-induced endocrine suppression appears reversible with sustained opioid abstinence. Higher methadone dose, male sex, and depression were associated with hypogonadism. Despite frequent healthcare contact, patients remained undiagnosed, highlighting a gap in clinical awareness of opioid-associated endocrinopathies and the need for routine screening in opioid agonist treatment settings.

To assess the potential of opioid settlement dollars disbursed to state and local governments to replace or supplement federal substance use disorder (SUD) funding.

For each state, we calculated the percentage of Substance Use and Mental Health Services Administration (SAMHSA) SUD funding for each state that can be offset by settlement funds.

We estimated annual opioid settlement distributions (2022-2038) from KFF Health News and SAMHSA-funded SUD awards (2024) from SAMHSA's website and the Tracking Accountability in Government Grants System.

Across states, the mean difference between SAMHSA SUD funds and settlement funds was $56.83 (SD: $53.76) per capita, and the mean percentage of SAMHSA SUD funding that could be replaced by settlement funds was 51.16 (SD: 28.46) per capita. Oregon was the only state where settlement disbursements exceeded SAMHSA SUD funding.

Substantial gaps remain between current federal SUD funding and what opioid settlement funds can offset. Our findings underscore that opioid settlement funds are not a viable replacement for federal funding, both because they were never intended to serve this purpose, and because they are insufficient in scale.

Sunlight has profound impacts on physical and mental health, beyond vision, including effects on circadian rhythms, alertness, mood, and sleep. A family history of any mood disorders is strongly associated with psychiatric disorders including bipolar disorder. The purpose of this study was to evaluate the association between a family history of any mood disorder in patients with bipolar I disorder and solar insolation at varied international onset locations.

Data for this analysis were available from 5842 patients with a diagnosis of bipolar I disorder obtained at 83 collection sites in both hemispheres. This included 4752 patients from 71 collection sites in the northern hemisphere and 1090 patients from 12 collection sites in the southern hemisphere. Patient data variables were obtained from records or interviews. Solar insolation data were obtained from The National Aeronautics and Space Administration (NASA) Power database for each onset location, and the ratio of the mean monthly minimum/mean monthly maximum solar insolation was calculated. Typically, the ratio is largest near the equator (little yearly change in solar insolation) and smallest near the poles (large yearly change in solar insolation).

A significant relationship was found between a family history of any mood disorder, the ratio of the mean monthly minimum/mean monthly maximum solar insolation, and gender. The odds of a family history of mood disorder increased as patient location nears the poles and decreased near the equator. Female gender also increased the odds of having a family history of a mood disorder.

This study highlighted the association between family history, solar insolation, and gender in international patients with bipolar I disorder. Given the profound effects of sunlight on human health, the family of patients with bipolar disorder who live in the same location with the same solar insolation, and especially females, may be at increased risk for a mood disorder.

Internalizing disorders are among the most common psychiatric conditions in adolescence, often associated with long-term adverse outcomes. Early identification of at-risk youth is important for effective intervention, though it remains challenging due to the multifactorial nature of risk. Machine learning (ML) offers opportunities to integrate multiple data sources and improve risk prediction for internalizing disorders.

We used data from 13,743 adolescents (mean age 14.45 years; 52.7% female) participating in the Norwegian Mother, Father and Child Cohort Study (MoBa), linked to national health registries. Logistic regression with elastic net regularization was applied to predict the risk of an internalizing disorder (mood, anxiety or stress-related) occurring within one to five years after assessment. Nested models of increasing complexity incorporated sociodemographic, clinical, lifestyle, mental health, psychosocial, and genetic predictors. Model performance was evaluated in a hold-out test set. Simplified models combining three questionnaire scales were also evaluated.

Test-set performance increased with model complexity, reaching area under the receiver operating characteristic curve (AUC) of 0.731 for the full model. Mental health self-reported symptoms and psychosocial predictors contributed most to the discrimination. Simplified models using three questionnaire scales, alongside age and sex, achieved AUCs up to 0.718 and effectively stratified adolescents into high- and low-risk groups (OR80/20 ranged 6.11-9.35).

Multimodal ML models integrating registry information, mental health symptoms, psychosocial factors, and genetic data demonstrated moderate predictive performance. Simplified models with three questionnaire items reached comparable performance, highlighting their potential utility in the early identification of adolescents at elevated internalizing disorder risk.

To compare two ambient AI documentation tools: Dragon Ambient eXperience (DAX) and Abridge in the emergency department (ED), assessing perceived effects on work burden, usability, documentation quality, satisfaction, and overall preference.

We conducted a single-site, prospective crossover study in an ED over six weeks, from April to June 2025. Twenty faculty were enrolled; 18 completed both phases. Participants used both ambient AI scribe tools in alternating 3-week phases. Pre-, tool-specific, and post-surveys captured four domains: burden, usability, quality, and satisfaction. Adoption was the proportion of notes containing any ambient output. Paired Wilcoxon tests and linear mixed-effects models were used to compare tools, adjusting for order and adoption.

DAX was associated with greater reduction in overall work burden compared with Abridge (median 1.5 vs 2; p=0.025). Usability was high and comparable between tools (SUS medians 73.5 vs 73.5, p = 0.94; UMUX-Lite medians 86 vs 82.5, p = 0.079). PDQI-9 scores favored DAX (median 39 vs 36.5; p = 0.011). DAX received higher satisfaction ratings (median likelihood-to-recommend 9 vs 7.5; p=0.015), but adjusted models suggested these differences reflected order effects more than inherent tool differences. Post-pilot preferences showed no overall preference after accounting for order, with first-tool exposure significantly shaping ratings.

In this 6-week crossover study in the ED, both ambient AI scribes were highly usable, and perceived to reduce documentation burden while preserving note quality. Findings support the feasibility and perceived value of ambient AI scribes in the ED and motivate larger, longer-duration, multi-site evaluations with objective outcomes.