Mental Health Diagnoses Research Articles

Does becoming amother make you ill?-Frequency of mental health diagnoses in postpartum mothers compared to childless women based on BARMER billing data

Around 700,000 children are born in Germany every year. Many mothers are under great pressure and strain due to prevailing role models and social expectations. Up to 15% of mothers in Germany are said to be affected by postpartum depression. The available studies, however, are mainly based on surveys, are older and vary widely in their results. This study brings another data source into play and asks how frequently diagnoses of mental illness are found in mothers after childbirth compared to childless women in the billing data of alarge health insurance company. Aretrospective matched cohort study was conducted with health insurance data from 2017-2022, comparing mothers and childless women with the same age and the same medical and socioeconomic characteristics with regard to depression, exhaustion and burnout, and anxiety and stress disorder outcomes. The modelling was carried out using Poisson regression. Mothers were less likely than childless women to receive adiagnosis of amental disorder within five years after childbirth. In the long run, however, the frequency of diagnoses equalised. Becoming amother does not lead to more diagnoses of mental disorders compared to childless women, at least in the first five years after giving birth. However, the interpretation of the data is difficult. Possible influence of external factors on making the diagnosis is not seen in the data, such as the social expectation of a"happy mother" or achange in the utilisation of medical care due to maternity.

Predictors and Outcomes of Mental Health Conditions Among Patients with Colorectal Cancer.

Mental health (MH) conditions are common in patients with colorectal cancer (CRC) due to the unique challenges these patients encounter. The primary aim was to investigate predictors of new onset MH conditions after a diagnosis of CRC and determine the association of new MH conditions on survival. A single institution, retrospective study was conducted. A multivariable Fine-Gray competing risks model was used to describe the primary study outcome of new MH diagnosis in patients at least 18years of age with CRC. Survival was modeled using Cox proportional hazards regression with a time-varying covariate for new MH diagnosis. 456 patients were identified for inclusion, with 16% developing a new MH condition and 29% dying during follow-up. A new MH condition was more likely among non-Hispanic white patients compared to non-Hispanic black and were less likely among those who are male or had a pre-cancer MH condition. The onset of a new MH condition was associated with a threefold decrease in survival. In addition, having a pre-cancer MH condition decreased survival nearly twofold. Our findings emphasize the importance of new-onset MH in patients after CRC diagnosis. Standardized screenings may alleviate some of the MH burden that patients with CRC experience in addition to potentially improving the overall health of patients. MH conditions may impact not only CRC outcomes but may direct future studies analyzing the risks of new onset MH conditions in other types of cancers, further expanding the importance of psychiatric support in patients with cancer.

Evaluation of New Mental Health Diagnoses After Pediatric Traumatic Injuries at a Level 1 Pediatric Trauma Center.

Traumatic injury is associated with significant mental health morbidity. To evaluate the need for implementation of active-post injury mental health screening at a Level 1 Pediatric Trauma center, we aimed to characterize all new mental health diagnoses after injury and evaluated for patient or injury factors that may aid in targeting of future screening. A single-center retrospective analysis of trauma patients aged 6-18years presenting in 2022 was performed. Our primary outcome was a new DSM-5 mental health diagnosis documented after traumatic injury. Patients with and without a new mental health diagnosis were compared by age, sex, race, ethnicity, injury type/mechanism, injury severity score (ISS), intensive care unit (ICU) admission, and length of stay (LOS). 492 patients were included. Their median (IQR) age was 13.5 (10.4, 15.4) years. The median (IQR) follow-up interval was 157 (9, 429) days. There were 24 (4.9%) children with a new mental health diagnosis: 12 (50%) with trauma-related stress disorders, with the remaining having diagnoses such as depressive or anxiety disorders. Patients with a new mental health diagnosis had longer LOS (3.0 [1.8, 7.5] vs 2.0 [1.0, 3.3] days, P = 0.02) and were more likely to have sustained penetrating injury (P = 0.01). There were no differences in demographics, rates of preexisting mental health diagnosis or area deprivation index (P > 0.05). There were fewer new mental health diagnoses in our cohort than expected, likely underestimating the acute need. Comprehensive post-injury screening is imperative to sufficiently identify and intervene upon mental health morbidity after pediatric trauma.

The Role of Artificial Intelligence in Revolutionizing Mental Health Services: A Data-Driven Approach

The potential of artificial intelligence (AI) to transform mental health care through individualized treatment approaches is significant. This research investigates the application of AI and extensive healthcare datasets to improve the precision of mental health diagnoses and treatments. The study employs various machine learning techniques, such as Random Forest, CatBoost, K-Nearest Neighbors, XGBoost, Convolutional Neural Networks, and Long Short-Term Memory networks, to analyze diverse data sources including electronic health records, neuroimaging, genetic information, and demographic data. Following thorough data preprocessing, model training, and evaluation using metrics like accuracy, precision, recall, F1 score, and Cohen's Kappa, the Random Forest algorithm emerges as the top performer with 98.7% accuracy. The research highlights the importance of addressing ethical considerations, such as protecting patient privacy, ensuring data security, and mitigating algorithmic bias when implementing AI in mental health services. The findings indicate that AI-based approaches can markedly improve diagnostic accuracy, provide tailored treatment suggestions, and facilitate early relapse detection, thus promoting proactive mental health management. Key Words: Artificial Intelligence, Mental Health, Data- Driven approach, Personalized Treatment, Machine Learning, Natural Language Processing.

Assessing similarities and differences in thematic content across online mental health communities dedicated to trauma-related mental health conditions.

Large online mental health communities exist for both posttraumatic stress disorder (PTSD) and complex posttraumatic stress disorder (CPTSD) on Reddit. These communities have not been sufficiently understood through prior work. Posts (N = 86,267) from r/ptsd and r/CPTSD subreddits from December 2020 to December 2022 were collected, processed, and assessed. A modified reflexive thematic analysis was used to generate themes and codes from corpus data and Bidirectional Encoder Representation from Transformers topic models. Representative posts (N = 397) were coded. Chi-square analyses were used to compare the frequency of themes and codes across r/ptsd and r/CPTSD. Most sampled posts in r/ptsd and r/CPTSD were focused on posting for oneself. Venting was significantly more common in r/CPTSD (p < .01), whereas seeking advice was more frequent in r/ptsd (p < .01). Traumatic experiences, mental health symptoms, treatment, diagnosis, and relationships were discussed frequently in both communities. Discussions of noninterpersonal trauma, anxiety symptoms, sleep-related symptoms, flashback/reexperiencing symptoms, somatic symptoms, diagnosis, and medication use were significantly more prevalent in r/ptsd compared to r/CPTSD (p < .01). Discussions of depression/mood symptoms, resources/coping tools, and interpersonal conflict were significantly more common in r/CPTSD (p < .01). Findings suggest that trauma-related online mental health communities may allow users to fulfill different objectives (i.e., seeking support, venting, or asking for advice) related to a wide range of discussion themes. Findings may be used to help inform the design and delivery of informal and formal interventions directed at these communities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Access to psychological therapies amongst patients with a mental health diagnosis in primary care: a data linkage study.

Significant numbers of people in England have fallen into a gap between primary care psychological therapies and specialist mental health services. We aim to examine pathways to care by looking at demographic variation in detection and referral to primary and secondary psychological services in south London. Longitudinal descriptive study using a record linkage between a primary care database (Lambeth DataNet) and a secondary care mental health database (CRIS). We extracted data on mental health diagnosis, prescriptions and episodes of care in mental health services for all patients of working age registered from 1 January 2008 to 1 March 2018 (pre-covid era). Of those with a mental disorder detected in primary care (n = 110,419; 26.8%); 33.7% (n = 37,253) received no treatment; 21.3% (n = 23,548) exclusively accessed psychological treatment within NHS Talking Therapies and 7.6% accessed secondary care psychological therapies. People from minoritised groups were more likely to be prescribed psychotropic medication as the only treatment offered compared to the White British group. Men, Black African and Asian groups were less likely to access NHS Talking Therapies. People with a personality disorder diagnosis had the highest prevalence and number of NHS Talking Therapies treatment episodes (48.0%, n = 960), a similar percentage (44.1%, n = 881) received secondary care psychology treatment. Our study highlights marked inequalities in access to psychological therapies for men and people from some minoritised ethnic groups across primary and secondary care and how individuals with personality disorders are offered multiple short-term courses in NHS Talking Therapies even where this is not recommended treatment.

The impact of oral health on depression: A systematic review.

As of 2020, about 21% of adults in the United States have a diagnosable mental health disorder, excluding substance use and developmental disorders. Depression, predicted by the WHO to be the leading cause of disease burden by 2030, is linked to various systemic conditions and has been associated with poor oral health. Both behavioral factors, like poor dental hygiene and irregular visits, and biological mechanisms, such as changes in salivary immunity, contribute to this connection, which impacts overall well-being and quality of life. This systematic review aims include: (1) Does tooth loss affect depression? (2) Does oral pain, such as that experienced during chewing and speaking, impact depression? (3) Does oral functionality, including chewing and speaking, influence depression? (4) Does overall oral health affect depression? We conducted a systematic search of PubMed, EBSCO host, Medline, and Google Scholar databases from January 2000 to June 2024 using relevant keywords. Studies examining the impact of oral health parameters (tooth loss, oral pain, oral functionality, overall oral health) on depression were included. Articles were included if (1) full text manuscripts in English were available, (2) the study described the association of oral health and depression, and (3) the independent value was an oral related factor and the dependent value was depression. The following were excluded from our analysis: (1) any articles where oral factors were not the independent value, (2) systematic reviews, (3) case reports, and (4) duplicate studies among our databases. Thirty-one studies met the inclusion criteria. Tooth loss, oral pain, and impaired oral functionality were consistently associated with increased depressive symptoms across the included studies. Greater tooth loss was linked to higher odds of both onset and progression of depression. Oral pain exacerbated depressive symptoms, while difficulties in chewing or speaking were associated with elevated risks of depression. There is a bidirectional relationship between oral health and depression, highlighting the urgent need for comprehensive public health initiatives. Integrating oral health assessments into routine medical care, and developing targeted interventions are crucial steps to mitigate the impact of poor oral health on mental health outcomes.

Examining the Relationship Between Mental Health Diagnoses and Write-Ups During Incarceration

Examining the Relationship Between Mental Health Diagnoses and Write-Ups During Incarceration

Diagnosis and Treatment of Adults with Attention-Deficit/Hyperactivity Disorder (ADHD)

Attention-deficit/hyperactivity disorder (ADHD) is a mental health diagnosis that affects an individual’s brain development and activity, resulting in inattention and/or hyperactivity-impulsivity that interferes with functioning in many aspects of life. A growing number of adults have a diagnosis of ADHD, with approximately one-third of those being diagnosed in adulthood rather than childhood. Symptoms and treatment of adults with ADHD are different than in the pediatric population. Evidence-based practices on identification, diagnosis, and treatment for adults with ADHD will be explored. Clinicians in primary care must be knowledgeable of treatment for adults with ADHD to meet this growing demand.

Do mindfulness interventions cause harm? Findings from the Learning to Apply Mindfulness to Pain (LAMP) Pragmatic Clinical Trial.

Although mindfulness-based interventions (MBIs) are widely used in clinical and nonclinical settings, there has been little systematic study of their potential risks. To address this gap, we examined differences in psychological and physical worsening among participants in the usual care and intervention conditions of a 3-group, randomized pragmatic trial (Learning to Apply Mindfulness to Pain [LAMP]) that tested the effectiveness of 2 approaches to delivering MBIs to patients with chronic pain. The sample consisted of 374 male and 334 female patients with chronic pain enrolled in the LAMP trial who completed a 10-week follow-up survey, 61% of whom had a mental health diagnosis. Psychological and physical worsening was assessed by a checklist asking whether participants experienced specific symptoms since beginning the study. We used multivariable logistic regression models with imputed data to determine whether predicted probabilities of increased symptoms differed between usual care and the 2 MBIs. Participants in usual care were more likely to report experiencing increased psychological and physical worsening than were those in the MBIs, including an increase in disturbing memories; sadness, anxiousness, and fatigue; isolation and loneliness; and feeling more upset than usual when something reminded them of the past. MBIs do not appear to cause harm, in terms of increased symptoms, for this population of patients with chronic pain and high levels of mental health comorbidities. Preregistration with an analysis plan at www.ClinicalTrials.gov: NCT04526158. Patient enrollment began December 4, 2020.

Enhancing Bipolar Disorder Detection using Heterogeneous Ensemble Machine Learning Techniques

This paper introduces a novel Heterogeneous Ensemble Machine Learning (HEML) approach designed to detect bipolar disorder, a significant healthcare challenge that demands precise and prompt diagnosis for effective treatment. The HEML method integrates multiple machines learning models, incorporating various physiological, behavioral, and contextual data from patients. By using a comprehensive feature selection technique, relevant features are extracted from each data source and utilized to train individual classifiers for detecting mental disorders. The classifiers include Adaboost, Decision Tree, K-nearest neighbors, Multilayer Perceptron, Random Forest, Relevance Vector Machine, and XGB, with Logistic Regression serving as the meta-model. This ensemble of classifiers enhances overall performance by capturing a wider range of characteristics related to mental disorders. The research evaluates the HEML method across three bipolar disorder datasets: Dataset1 (a multimodal dataset), Dataset2 (a sensor-based dataset), and Dataset3 (a real-time dataset). The HEML approach surpasses traditional methods, achieving superior accuracy rates of 95.21% with Dataset 1, 99.28% with Dataset 2, and 99% with Dataset 3. It outperforms individual models in detecting bipolar disorder, delivering the best Precision, Recall, F1 score, and Kappa Score. This comparative analysis advances the field of mental health diagnosis by leveraging the strengths of ensemble machine learning to improve accuracy and reliability in detection methods.

Pregnancy care experiences for adults with congenital heart disease in the United States

BackgroundResearch to reduce maternal morbidity due to cardiovascular disease is vitally important in the United States, especially for the growing number of individuals with congenital heart disease (CHD) reaching childbearing age. Understanding patient experiences through patient engagement is critical to designing research that is aligned with the needs of adults with CHD undergoing pregnancy. MethodsThis patient engagement project, grounded in human centered design, focuses on the discovering patient and healthcare provider priorities for reducing maternal morbidity in CHD through patient centered outcomes research (PCOR). In this first stage, a capacity building consortium of over 90 key partners, including patients, advocates, healthcare providers, and researchers, was assembled. Baseline education on patient engagement, PCOR, and survey instrument design was delivered virtually. Two questionnaires were designed to elicit tacit knowledge – one for patients and one for providers – regarding gaps and needs across four key pillars: access to clinical care, patient and provider education, mental health, and research opportunities. The pillars were determined through thematic summaries from consortium discussions. ResultsThe patient questionnaire received 828 responses (age range: 18-60 years) from 48 U.S. states. The provider questionnaire garnered 218 responses from professionals. Several common themes for areas of research were observed across all pillars including improved access to specialized cardio-obstetric care and improved education about the need for specialized care. Healthcare providers cited insufficient care coordination models and resources as a major barrier to providing effective clinical care. Both patients and providers expressed a need for improved access to mental health care. While only 28% of patient respondents who underwent a pregnancy reported a pre-existing mental health diagnosis, nearly 2/3 reported having significant anxiety symptoms related to their pregnancy. Of those with significant symptoms, 44% were unable to access mental health services. Additionally, only 55% of healthcare providers reported referral for assessment and treatment if mental health concerns arose during or after pregnancy. ConclusionThe results provide valuable insights into the unique challenges faced by patients with CHD and their providers during pregnancy. By addressing the identified gaps through PCOR, we can work towards a goal to improve maternal care for women with CHD.

Transitioning to fatherhood: Prospective effects of wellbeing on future depression symptoms.

Becoming a father is a critical period of life transition. Evidence suggests that lifetime history of mental health disorder/s and elevated depressive symptoms prior to conception increase risk for men's postnatal depression. Less is understood about the role of positive mental health, or wellbeing, as a protective factor for future depressive outcomes during the transition to fatherhood. The present study investigated whether men's post-natal depressive outcomes were associated with pre-conception levels of wellbeing and whether wellbeing during the post-natal period predicted depressive outcomes post-infancy. Secondary analysis of data from a national, longitudinal cohort study of men's health, namely, The Ten to Men Study (TTM), was conducted. Participants in the pre-conception sample were n = 350 men for whom data were available at both a pre-conception baseline and post-natal follow-up. The post-natal sample were n = 427 men with post-natal baseline data and post-infancy follow-up. Multivariate negative binomial regressions and logistic regression models were used to determine pre-conception and post-natal predictors of future depressive outcomes. Men's pre-conception depressive symptoms were the best predictor of post-natal depressive symptoms (IRR = 1.089, p < 0.001) and risk of moderate-severe depression (IRR = 1.193, p = 0.005) the latter of which was also predicted by a previous mental health diagnosis (IRR = 3.079, p = 0.029). Similarly, post-natal depressive symptoms were the best predictor of post-infancy depressive symptoms (IRR = 1.089, p < 0.001) and risk of moderate-severe depression (IRR = 1.193, p = 0.005) alongside lifetime prevalence of a mental health disorder (symptoms: IRR = 1.317, p = 0.011; moderate-severe depression: IRR = 2.606, p = 0.023). Preconception levels of wellbeing predicted lower post-natal depressive symptoms (IRR = 0.988, p < 0.001) and reduced risk of moderate-severe depression (IRR = 0.940, p = 0.002) after controlling for baseline symptoms and sociodemographic and behavioural confounds; however, wellbeing during the post-natal period did not predict either depressive outcome post-infancy. Fatherhood-specific risk factors for mental health outcomes (e.g., conception difficulties, maternal postnatal mental health) were not assessed in the present study, and only one aspect of wellbeing was captured. Screening for history of common mental health disorders and current symptoms is recommended to inform preventative approaches to paternal mental health care during early fatherhood. Inclusion of wellbeing in such screening procedures may be beneficial, however, further research is required to elucidate the prospective associations between wellbeing and depressive symptoms during the transition to fatherhood.

Using machine learning to derive neurobiological subtypes of general psychopathology in late childhood.

Traditional mental health diagnoses rely on symptom-based classifications. Yet this approach can oversimplify clinical presentations as diagnoses often do not adequately map onto neurobiological features. Alternatively, our study used structural imaging data and a semisupervised machine learning technique, heterogeneity through discriminative analysis, to identify neurobiological subtypes in 9- to 10-year-olds with high psychopathology endorsements (n = 9,027). Our model revealed two stable neurobiological subtypes (adjusted Rand index = 0.38). Subtype 1 showed smaller structural properties, elevated conduct problems and attention-deficit/hyperactivity disorder symptoms, and impaired cognitive performance compared to Subtype 2 and typically developing youth. Subtype 2 had larger structural properties, cognitive abilities comparable to typically developing youth, and elevated internalizing symptoms relative to Subtype 1 and typically developing youth. These subtypes remained stable in their neurobiological characteristics, cognitive ability, and associated psychopathology traits over time. Taken together, our data-driven approach uncovered evidence of neural heterogeneity as demonstrated by structural patterns that map onto divergent profiles of psychopathology symptoms and cognitive performance in youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Common mental health diagnoses arising from or coinciding with menopausal transition and prescribing of SSRIs/SNRIs medications and other psychotropic medications.

Women with menopausal transition (MT) have an elevated risk of experiencing common mental health diagnoses (CMHD: depression or anxiety). There is no recent data comparing the rate, and treatment, of CMHD between men and women. In this population-based study, incidence rates (IR) per 100 person-years-at-risk (PYAR) for men and women ≥45years registered with an UK primary care practice between 2010 and 2021 were estimated. Incidence rate ratios (IRR) with 95% confidence intervals (CIs) of CMHD were estimated using men as a reference. We measured first prescriptions for psychotropic medications received within 12months after CMHD. For selective serotonin reuptake inhibitors (SSRIs) /selective norepinephrine reuptake inhibitors (SNRIs), we measured the IR of prescribing per 100 PYAR, by 10-year bands. Proportion of SSRIs/SNRIs prescribing was estimated per 100 persons. Rates of anxiety and depressive disorders were 1.68 and 1.69 per 100 PYAR in women aged 45-54years-old compared to 0.91 and 1.20 per 100 PYAR in men, with IRR of 1.84 (95% CI 1.72-1.97) and 1.44 (1.35-1.53) respectively. SSRIs/SNRIs were the most prescribed medication; in 2021, IRs for SSRIs/SNRIs were 13.4 per 100 PYAR in both sexes. In 2021, the proportion of SSRIs/SNRIs prescribing was 50.67 per 100 women and 41.91 per 100 men. MT is assumed based on women's age as menopause onset is rarely recorded in primary care databases. Women ≥45years experienced more CMHD compared to men, especially 45-54years-olds, which coincides with MT. The proportion of SSRIs/SNRIs prescribing was higher in women.

Prevalent Adverse Childhood Experiences Among Young Adults Returning Home From Jail: The Need for Trauma-Informed Reentry Services.

Prevalence of adverse childhood experiences (ACEs) and the extent to which they relate to health among young adults (ages 18-25) returning home from jail is underexamined. To build on the growing literature examining associations between ACE exposure among young people involved with carceral systems and health, we (1) measured ACE prevalence and (2) explored associations between ACEs and health/well-being indicators among young adults experiencing reentry. Using a telephone survey on reentry experiences, participants completed an ACE screening, single-item responses on health and social indicators, and five-item responses on substance misuse. Fisher's exact tests and t tests compared sociodemographic and health-related factors by the levels of ACEs. Among the 85 participants, 66 (78%) reported four or more ACEs and 48 (56%) reported six or more ACEs, including divorced parents (n = 69, 81%), witnessing violence (n = 63, 74%), and household member incarceration (n = 60, 71%). Higher exposure to ACEs was associated with mental health diagnoses, psychiatric medication prescriptions, psychiatric hospitalizations, drug dependence, binge drinking, and cannabis misuse. High ACE exposure among young adults experiencing reentry portends worse mental health and high rates of substance use. Findings signify an opportunity to apply a trauma-focused developmental framework to support emerging adults during the crucial reentry period.

Sexual Trauma, Polygenic Scores, and Mental Health Diagnoses and Outcomes

Leveraging real-world clinical biobanks to investigate the associations between genetic and environmental risk factors for mental illness may help direct clinical screening efforts and evaluate the portability of polygenic scores across environmental contexts. To examine the associations between sexual trauma, polygenic liability to mental health outcomes, and clinical diagnoses of schizophrenia, bipolar disorder, and major depressive disorder in a clinical biobank setting. This genetic association study was conducted using clinical and genotyping data from 96 002 participants across hospital-linked biobanks located at Vanderbilt University Medical Center (VUMC), Nashville, Tennessee (including 58 262 individuals with high genetic similarity to the 1000 Genomes Project [1KG] Northern European from Utah reference population [1KG-EU-clustered] and 11 047 with high genetic similarity to the 1KG African-ancestry reference population of Yoruba in Ibadan, Nigeria [1KG-YRI-clustered]), and Mass General Brigham (MGB), Boston, Massachusetts (26 693 individuals with high genetic similarity to the combined European-ancestry superpopulation [1KG-EU-clustered]). Clinical data analyzed included diagnostic billing codes and clinical notes spanning from 1976 to 2023. Data analysis was performed from 2022 to 2024. Clinically documented sexual trauma disclosures and polygenic scores for schizophrenia, bipolar disorder, and major depressive disorder. Diagnoses of schizophrenia, bipolar disorder, and major depressive disorder, determined by aggregating related diagnostic billing codes, were the dependent variables in logistic regression models including sexual trauma disclosure status, polygenic scores, and their interactions as the independent variables. Across the VUMC and MGB biobanks, 96 002 individuals were included in analyses (VUMC 1KG-EU-clustered: 33 011 [56.7%] female; median [range] age, 56.8 [10.0 to >89] years; MGB 1KG-EU-clustered: 14 647 [54.9%] female; median [range] age, 58.0 [10.0 to >89] years; VUMC 1KG-YRI-clustered: 6961 [63.0%] female; median [range] age, 44.6 [10.1 to >89] years). Sexual trauma history was associated with all mental health conditions across institutions (ORs ranged from 8.83 [95% CI, 5.50-14.18] for schizophrenia in the VUMC 1KG-YRI-clustered cohort to 17.65 [95% CI, 12.77-24.40] for schizophrenia in the VUMC 1KG-EU-clustered cohort). Sexual trauma history and polygenic scores jointly explained 3.8% to 8.8% of mental health phenotypic variance. Schizophrenia and bipolar disorder polygenic scores had greater associations with mental health outcomes in individuals with no documented disclosures of sexual trauma (schizophrenia interaction: OR, 0.70 [95% CI, 0.56-0.88]; bipolar disorder interaction: OR, 0.83 [95% CI, 0.74-0.94]). Sexual trauma and mental health polygenic scores, while correlated with one another, were independent and joint risk factors for severe mental illness in a large, diverse hospital biobank population. Furthermore, associations of schizophrenia and bipolar disorder polygenic scores with respective diagnoses were greater in those without disclosures, suggesting that genetic predisposition to mental illness as measured by polygenic scores may be less impactful in the presence of this severe environmental risk factor.

Prevalence of central nervous system-active polypharmacy in a cohort of older adults in Argentina.

Central nervous system (CNS)-active polypharmacy is frequent and potentially harmful in older patients. Data on its burden outside the USA and European countries remain limited. To estimate the period prevalence of and factors associated with out-of-hospital CNS-active polypharmacy in older adults. We used data from a cohort of out-patients aged ≥60 years affiliated to the Hospital Italiano de Buenos Aires' health maintenance organisation on 1 January 2021. A CNS-active polypharmacy event was defined as the concurrent exposure to ≥3 CNS-active medications (i.e. antidepressants, anti-epileptics, antipsychotics, benzodiazepines, Z-drugs and opioids) through filled out-of-hospital prescriptions. We calculated the period prevalence of CNS-active polypharmacy for 2021. We identified factors associated with CNS-active polypharmacy using a multivariable logistic regression model to estimate odds ratios and 95% confidence intervals (CI). We included 63 857 patients. Pre-existing mental health diagnoses included anxiety (21%), depressive (14%) and sleep (11%) disorders. CNS-active polypharmacy occurred in 4535 patients, for a period prevalence of 7.1% (95% CI: 6.9-7.3%). The combination of an antidepressant, an antipsychotic and a benzodiazepine accounted for 21% of the CNS-active polypharmacy events. Frontotemporal dementia (odds ratio: 14.67; 95% CI: 4.47-48.20), schizophrenia (odds ratio: 7.93; 95% CI: 4.64-13.56), bipolar disorder (odds ratio: 7.20; 95% CI: 5.45-9.50) and depressive disorder (odds ratio: 3.50; 95% CI: 3.26-3.75) were associated with CNS-active polypharmacy. One in 14 adults aged 60 years and older presented out-of-hospital CNS-active polypharmacy. Future studies should evaluate measures to reduce CNS-active medication use in this population.

Do Children With Accidental Gunshot-related Fractures Experience Greater Risk of Mental Illness and Psychiatric Disorders? A Propensity-matched Study.

Firearm violence is the leading cause of death and is a major source of morbidity for children in the United States. While gunshot wounds (GSWs) are known to cause lasting psychological repercussions beyond physical injury, these effects are not well documented compared with the physical implications. Our study explores the association between accidental gunshot-related fractures in children and subsequent psychiatric outcomes. Relative to non-GSW-related fractures, do children sustaining an accidental GSW-related fracture experience higher risk of mental illness and psychiatric disorders? This study utilized the TriNetX US Collaborative Network as it provides comprehensive inpatient and outpatient data, longitudinal follow-up, and complete medical records across different facilities, closely reflecting real-world patient outcomes in orthopaedic practice. We retrospectively evaluated children diagnosed with an accidental GSW-related fracture and compared mental health diagnoses to children who experienced non-GSW-related fractures. Between January 1, 2003, and March 1, 2023, a total of 5071 children in the United States without preexisting anxiety, mood, psychotic, substance use, or insomnia disorders were reported to have experienced an accidental GSW-related fracture. Among these patients, 55% (2773) had a follow-up period of at least 1 year and met the inclusion criteria for the exposure cohort. In the non-GSW-related fracture cohort, a total of 61% (985,070) of children among 1,613,891 without the preexisting aforementioned conditions had a minimum follow-up period of 1 year and met the inclusion criteria. A total of 2769 children were successfully matched in each cohort using a greedy nearest neighbor propensity score-matching algorithm. Matching was based on age, gender, race, fracture location, and BMI, as these characteristics were identified through a regression analysis as potentially associated with psychiatric outcomes (p < 0.01). The mean ± SD age was 15 ± 4 years, and 16% (451) in the GSW cohort were girls. In the non-GSW cohort 17% (474) were girls. With respect to race and ethnicity, 62% (1709 in the GSW cohort; 1679 in the non-GSW cohort) were Black and 14% (384 in the GSW cohort; 386 in the non-GSW cohort) were Hispanic. Outcomes of interest were recorded for up to 3 years after the index event. The accidental GSW-related fracture cohort experienced a greater hazard of developing anxiety disorders (HR 3.8 [95% confidence interval (CI) 3.2 to 4.6]; p < 0.001), substance use disorders (HR 3.6 [95% CI 3.0 to 4.2]; p < 0.001), mood disorders (HR 2.4 [95% CI 1.9 to 3.1]; p < 0.001), non-mood psychotic disorders (HR 2.4 [95% CI 1.5 to 3.9]; p < 0.001), and insomnia (HR 1.8 [95% CI 1.4 to 2.3]; p < 0.001). Orthopaedic surgeons should implement early psychiatric screenings and integrate mental health support for children with gunshot-related fractures to address elevated risk of anxiety disorders, psychotic disorders, mood disorders, substance abuse, and insomnia. Future studies should focus on identifying effective interventions that mitigate these long-term psychological outcomes, with an emphasis on practical, targeted approaches in clinical care. Level III, prognostic study.

Sexuality and Gender Diversity Among Adolescents in Australia, 2019-2021

Sexuality- and gender-diverse (SGD) young people experience substantial health disparities relative to cisgender heterosexual peers. Little is known about SGD adolescents younger than 15 years. To describe SGD prevalence and associated factors in a population-representative cohort of younger adolescents in Australia. This prospective cohort study was part of the Future Proofing Study, with enrollment of year 8 students at 134 Australian secondary schools from 2019 to 2021 and annual follow-ups for 5 years. Data were analyzed from June 20, 2023, to June 6, 2024. Outcomes of interest were baseline self-reported gender and sexuality identities, individual characteristics, and mental health and disability diagnoses, as well as school characteristics. Among 6388 participants, median (IQR) age was 13.9 (13.6-15.8), with a range of 10.7 to 17.5 years. Most participants attended school in a major city (76.0%), were born in Australia (91.4%), and spoke English at home (93.7%). Approximately half (3122 participants; 48.9% [95% CI, 45.2%-59.0%]) identified as female or girls, and 46.5% (2973 participants; 95% CI, 39.8%-53.4%) identified as male or boys. The overall proportion of transgender identity was 3.3% (95% CI, 2.7%-3.9%), with 23 participants (0.4%) identifying as transgender boys, 10 participants (0.2%) identifying as transgender girls, 117 participants (1.8%) identifying as transgender nonbinary, and 59 participants (0.9%) identifying as another transgender identity. The overall proportion of sexuality diversity was 12.0% (95% CI, 10.4%-13.8%). The proportion of cisgender participants who were sexuality-diverse (13.0% [95% CI, 11.4%-14.8%] of girls and 4.7% [95% CI, 3.7%-5.9%] of boys) was lower than the proportion among gender-diverse participants, which ranged from 30.0% (95% CI, 9.3%-64.1%) of transgender girls to 91.5% (95% CI, 81.3%-96.4%) of those with another diverse gender identity. Gender diversity and sexuality diversity were strongly associated (odds ratio [OR], 66.24; 95% CI, 38.23-114.80), and both were negatively associated with age (gender diversity: OR per 1-year older, 0.61; 95% CI, 0.49-0.76; sexuality diversity: OR per 1-year older, 0.78; 95% CI, 0.65-0.93) and positively with mental health diagnosis (gender diversity: OR, 2.41; 95% CI, 1.79-3.24; sexuality diversity: OR, 2.50; 95% CI, 2.10-2.98), and disability diagnosis (gender diversity: OR, 2.39; 95% CI, 1.68-3.40; sexuality diversity: OR, 1.96; 95% CI, 1.64-2.36). While there were significant associations between individual and school characteristics and responses to gender and sexuality identity items, patterns of association differed, with no consistent association with economic disadvantage. This cohort study of young adolescents found higher rates of SGD than among samples of older adolescents. The significant associations with younger age, poorer mental health, and disability underscored the urgent need for inclusive programs to promote a safe and welcoming environment in schools, health care settings, and communities.