Diagnosis Of Mental Disorders Research Articles

Mental disorder symptoms and diagnoses are differently associated with labour market attachment and registered income until midlife: The Northern Finland Birth Cohort 1966.

Both the symptoms and diagnoses of mental health disorders affect individuals' occupational status and income. However, studies that compare the impact of differences between symptoms and diagnoses on occupational outcomes are lacking. This study aimed to compare labour market attachment and income until midlife between individuals with different histories of mental disorder symptoms and diagnoses. Utilizing the Northern Finland Birth Cohort 1966 with linkages to national registers and self-reported mental disorder symptoms at the age of 31, we compared labour market attachment and income until midlife among individuals with neither mental disorder symptoms nor a diagnosis (reference group), symptomatic undiagnosed mental disorder, asymptomatic diagnosed mental disorder, and with symptomatic diagnosed mental disorder by using cross-tabulations and regression analyses. We stratified our analysis by sex. Compared to the reference group, males but not females with symptomatic undiagnosed mental disorder had an increased risk for poor labour market attachment, with Odds Ratios (95% Confidence intervals) 2.26 [1.41, 3.63] and 0.87 [0.63, 1.19], respectively. The analogous risk was heightened for both males and females with asymptomatic diagnosed mental disorders or symptomatic diagnosed mental disorders. Regarding income, having mental disorder symptoms, a diagnosis, or both was associated with lower earnings irrespective of sex. Mental disorder symptoms and diagnoses are differently associated with labour market attachment and income. Our findings suggest that interventions should be offered not only based on diagnoses but also based on symptoms as they may serve as predictors of future challenges related to work careers.

Perinatal stress and anxiety in Ireland: experiences and support needs.

Perinatal stress and anxiety from conception to two years postpartum have important adverse outcomes for women and infants. This study examined (i) women's perception of sources and experiences of perinatal stress and anxiety, (ii) women's attitudes to and experiences of available supports, and (iii) women's preferences for perinatal stress and anxiety supports in Ireland. An online mixed-methods cross-sectional survey was conducted with 700 women in Ireland. Participants were pregnant women (n = 214) or mothers of children ≤ 2 years old (n = 486). Participants completed closed-ended questionnaires on sociodemographic, birth and child factors, and on stress, anxiety, perceived social support, and resilience. Participants completed open-ended questions about experiences of stress and anxiety and the supports available for stress and anxiety during pregnancy and/or postpartum. Quantitative data were analysed descriptively and using correlations; qualitative data were analysed using thematic analysis. Quantitative data indicated significant relationships between perinatal stress and/or anxiety and women's perceived social support, resilience, having a previous mental health disorder diagnosis (both p < 0.001), and experiencing a high-risk pregnancy or pregnancy complications (p < 0.01). Themes developed in qualitative analyses included: 'perceived responsibilities'; 'self-care'; 'care for maternal health and well-being'; 'social support'; and 'access to support and information'. Women's stress and anxiety are impacted by multiple diverse factors related to the individual, to interpersonal relationships, to perinatal health and mental health outcomes, and to available services and supports. Development of support-based individual-level interventions and increased peer support, coupled with improvements to service provision is needed to provide better perinatal care for women in Ireland.

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.

Psychometric properties of the Maladjustment Inventory in a Spanish clinical and student sample

BackgroundThe various systems of diagnosis and classification of mental disorders underline the need to evaluate the interference caused by the different disorders in a person’s daily life. The Maladjustment Inventory (MI) evaluates the impairment in the individual’s functioning in a brief and self-applied way, through six items. The objective of this research was to explore the psychometric properties of the MI scores through two studies, one with a Spanish clinical sample (Study 1) and another with a Spanish university students’ sample (Study 2).MethodsThe total sample was made up of 928 participants (81.1% women, n = 495 clinical sample). Descriptive analyses, exploration of internal structure and reliability, exploratory and confirmatory factor analyses, relationship with other variables (quality of life, anxiety, depression, neuroticism and extraversion), and percentiles and T-scores were performed.ResultsThe results showed good psychometric properties of the MI, with a good fit model for one factor solution in both samples, Cronbach’s alpha coefficient of 0.84–88, and evidence of validity based on the relationship with other variables.ConclusionThe good psychometric properties of the MI, together with its brevity, make it a recommended instrument for the evaluation of interference in both clinical and research contexts.

Mortality in people with mental disorders in Poland during the COVID-19 pandemic: a nationwide, register-based cohort study.

People with mental disorders in Poland have increased standardized mortality ratios (SMRs). This is the first study to assess all-cause mortality in people with mental disorders in Poland during the COVID-19 pandemic. A nationwide, register-based cohort study utilizing data from the registry of healthcare services (2011-2020) and the all-cause death registry (2021) in Poland was conducted. Individuals who were consulted or hospitalized in public mental healthcare facilities and received at least one diagnosis of mental disorders (ICD-10) from 2011 to 2020 were identified. SMRs were compared between people with a history of mental disorder and the general population. SMRs for the pandemic period were also compared with prepandemic SMRs calculated for 2019.No significant differences in SMRs were observed overall between 2021 and 2019. A minor increase in SMR was observed in 2021 for people treated only in outpatient mental health clinics. In 2021, a significant decrease in SMRs was shown for individuals with diagnoses from groups F10-F19 and F20-F29, and a significant increase in SMRs was observed for those with diagnoses from group F40-F48. SMRs for people with any mental disorder in Poland in 2021 remained at comparable levels to those in 2019.

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.

Affective Computing in Mental Health: The Role of Facial Expression Recognition

Affective computing has emerged as one of the leading interdisciplinary disciplines that utilize technology to detect and interpret human emotions, and so it provides critical information for the mental health monitoring process. The present study addresses the facial expression recognition as an important tool in the diagnosis and treatment of mental health disorders. By discussing the physiological and psychological implications that facial expressions may have, we analyze how FER systems can supplement the traditional approach to mental health evaluation by providing real-time feedback and timely intervention. Improved algorithms for machine learning and computer vision techniques in FER systems enhance the accuracy and efficiency of FER systems, thus increasing their applicability in teletherapy, clinical assessment, and personal well-being applications. This discussion paper shall also touch on the issues and ethical concerns of FER technology, such as privacy and the potential for misinterpretation. Our results indicate that FER can be a meaningful contributor to care for personal mental health by continuous monitoring and understanding of emotional well-being.

Liquid Biopsy-Based Detection and Response Prediction for Depression.

Proactively predicting antidepressant treatment response before medication failures is crucial, as it reduces unsuccessful attempts and facilitates the development of personalized therapeutic strategies, ultimately enhancing treatment efficacy. The current decision-making process, which heavily depends on subjective indicators, underscores the need for an objective, indicator-based approach. This study developed a method for detecting depression and predicting treatment response through deep learning-based spectroscopic analysis of extracellular vesicles (EVs) from plasma. EVs were isolated from the plasma of both nondepressed and depressed groups, followed by Raman signal acquisition, which was used for AI algorithm development. The algorithm successfully distinguished depression patients from healthy individuals and those with panic disorder, achieving an AUC accuracy of 0.95. This demonstrates the model's capability to selectively diagnose depression within a nondepressed group, including those with other mental health disorders. Furthermore, the algorithm identified depression-diagnosed patients likely to respond to antidepressants, classifying responders and nonresponders with an AUC accuracy of 0.91. To establish a diagnostic foundation, the algorithm applied explainable AI (XAI), enabling personalized medicine for companion diagnostics and highlighting its potential for the development of liquid biopsy-based mental disorder diagnosis.

Age-dependent associations with the risk of mental disorders in patients with myocardial infarction: a UK Biobank cohort study

Abstract Background Despite an overall decrease in cardiovascular mortality in recent decades due to effective preventive strategies, a concerning trend is emerging among young adults, with a rising incidence of myocardial infarction (MI) and its poor prognosis. Previous studies report that a significant association between mental disorders and the incidence and prognosis of MI. However, a detailed age-specific information is still lacking. Purpose We aimed to determine whether the risk of developing mental disorders after MI differs based on age and to stratify individuals at a higher risk. Methods From the UK Biobank prospective database (n=502,386), we collected data on patients with a prior MI (n=10,840) and compared them to age- and sex-matched controls (n=54,197) in a 1:5 ratio. Diagnoses of mental disorders were ascertained through linked hospital admission and mortality data, using the appropriate ICD-10-CM codes. Mental disorders were defined by at least two inpatient or outpatient claims within 1 year. The primary outcome was a composite of incident mental disorders, including depression, anxiety, stress-related, and somatoform disorders. Follow-up was done until the first diagnosis of mental disorders or the end of 2022. Results During a median follow-up of 13.7 years (interquartile range 12.8-14.5 years), the incidence rate of the primary outcome was 9.28 vs. 5.37/1,000 person-years among patients with MI and controls, respectively (p&amp;lt;0.001). A prior MI history demonstrated an independent association with the risk of incident mental disorders, yielding an adjusted hazard ratio (aHR) of 1.41 (95% confidence interval [CI], 1.29–1.54; p&amp;lt;0.001) after adjusting for confounders. This was comparable to heavy drinking and family history of depression. Notably, the risk of mental disorders attributed to previous MI was more prominent in younger individuals aged &amp;lt;55 years than their older counterpart (aHR 1.61 vs. 1.33) (p-for-interaction 0.020). Similar results were observed in the analysis of two important components: depression and anxiety disorder. Furthermore, in younger patients with MI (&amp;lt;55 years), mental disorders significantly increased the risk of mortality, while not in older patients. Conclusion MI was associated with a higher risk of incident mental disorders, resulting in poor prognosis, particularly in young individuals. Active surveillance and prevention for incident mental disorders after young MI may be beneficial.Cumulative Incidence of Mental Disorders

Diagnoses of mental health disorders among Norwegian youth and young adults with immigrant parents

Abstract Introduction Adolescence and early adulthood are associated with an increase in mental health problems. Migration is also a risk factor for mental disorders. Yet, there is a notable gap in research concerning the mental well-being of descendants of immigrants. This study investigates the risk of a diagnosis of a mental health disorder among those aged 16-30 years, born in Norway with at least one immigrant parent. Methods Data were sourced from the Medical Birth Registry of Norway, the Norwegian Patient Register, and Statistics Norway. Cox proportional hazard regressions were used to estimate hazard ratios (HR) of being diagnosed with different mental disorders, in total and by parental region of origin, compared to individuals of Norwegian background. Analyses were adjusted for sex, year of birth, and parental education. Results Individuals with two immigrant parents had a lower risk of most mental disorder diagnoses, while those of one immigrant parent had a higher risk. With the exception of schizophrenia, individuals with two immigrant parents had a lower risk of most mental disorder diagnoses compared to those with Norwegian-born parents. The HR for the risk of a diagnosis of anxiety for those with two immigrant parents was: 0.79 [95% CI 0.76 - 0.81], with immigrant mother: 1.07 [95% CI 1.04-1.10], with immigrant father: 1.28 [95% CI 1.24 -1.30]. Similarly, for depression, two immigrant parents: 0.85 [95% CI 0.82-0.88], immigrant mother: 1.13 [95% CI 1.09 - 1.17], immigrant father: 1.31 (95% CI 1.28-1.37). Bipolar disorders, two immigrant parents: 0.67 [95% CI 0.60-0.76], immigrant mother: 1.19 [95% CI 1.07 - 1.31], immigrant father: 1.47 [95% CI 1.35-1.61]. The pattern was relatively consistent across parental regions of origin. Conclusions Those with one immigrant parent are more likely to use specialist mental health services, while those with two immigrant parents are not. These need special attention in adulthood. Key messages • Differences in risk of diagnosis for mental disorders could be due to differences in the utilization of mental health services. • Early prevention of mental health issues seems to be especially important among children and youth raised in families with one immigrant parent.

Sick-leave trajectories among people sickness absent with stress-related diagnoses; cohort studies

Abstract Background Stress-related disorders are common sickness absence (SA) diagnoses in many Western countries. Knowledge of SA and disability pension (DP) patterns among people with such SA is needed. Thus, the aim was to identify future SADP trajectories among people with a new SA spell due to stress-related diagnosis and to examine sociodemographic and health-related factors associated with identified trajectories. Methods Using microdata from nationwide registers, we included all people living in Sweden with a new SA spell &amp;gt;14 days due to stress-related diagnoses (ICD-10 code F43) in 2011 (N = 32,417) or 2018 (N = 65,511), respectively. These two cohorts were followed prospectively for 13 months from the SA spell start, to identify trajectory groups of mean SA/DP days/month using group-based trajectory modeling. We used multinomial logistic regression to explore associations between sociodemographic and health-related predictors and trajectory membership. Results We identified the following SA/DP trajectories in both cohorts: steep drop (30.6% and 35.9% of all included in 2018 and 2011, respectively); fluctuating (8.7%, 11.2%); fast decrease (25.5%, 24.4%); medium decrease (18.1%, 13.1%); slow decrease (10.8%, 7.3%), and constant high (6.2%, 8.0%). Compared to the steep drop trajectory, individuals in the other trajectories were more likely women, older, and had prior SA/DP or secondary outpatient healthcare visits. Starting the SA spell full-time was the strongest predictor for the slow decrease and constant high trajectory, and previous SA or diagnosis of other mental disorders were predictors of the constant fluctuating and constant high trajectory. Conclusions The similarity of the identified trajectories in the two cohorts is a strength. The results reveal the diversity of future SA/DP in this patient group, indicating the importance of identifying patients at risk of long-term SA who might need further interventions early in the process. Key messages • In two population-wide cohorts with a new sickness absence (SA) spell with stress-related diagnoses, six trajectories of SA/disability pension days were identified during the 13-month follow-up. • Most of those in the cohorts had trajectories that ended with no SA/DP after 13 months, while two trajectories, including 15-19% of individuals, showed high or varying SA/DP days during the follow-up.

Courtesy stigma in the families of patients with severe mental disorders: an obstacle to the recovery process?

The general concept of stigma finds wide application in the field of psychiatry by indicating prejudice, stereotypes and discrimination towards patients diagnosed with psychiatric illness. Among the different declinations of this concept, we find courtesy stigma: a form of stigma by association experienced by people in close contact with the stigmatised person.Those who are most likely to experience this type of discrimination are the family members of the psychiatric patient, as they are particularly connected to the person with mental health problems. This experience contributes to increasing levels of expressed emotion (EE), i.e. the index of the emotional climate within the family.This study is based on two samples: a group of users with a diagnosis of severe mental disorder from the Department of Psychiatry of the University of Campania “Luigi Vanvitelli” and another group of family caregivers. This study aimed to: a) assess the impact of courtesy stigma on the levels of recovery and EE perceived by the patient; b) assess the relationship between the latter and the recovery process.To this end, the RAS-DS (Recovery Assessment Scale - Domains and Stages) and LEE (Level of Expressed Emotion Scale) scales were administered to patients, whereas caregivers were administered the CPMI (Stigma scale for Caregivers of People with Mental Illness) scale.Data processing revealed that high levels of courtesy stigma reported by caregivers not only hinder the patients’ recovery process, but also contribute to increasing EE levels according to the patients. Furthermore, as the EE levels perceived by the patients increase, the recovery levels decrease.

Multi-modal EEG NEO-FFI with Trained Attention Layer (MENTAL) for mental disorder prediction.

Early detection and accurate diagnosis of mental disorders is difficult due to the complexity of the diagnostic process, resulting in conditions being left undiagnosed or misdiagnosed. Previous studies have demonstrated that features of Electroencephalogram (EEG) data, such as Power Spectral Density (PSD), are useful biomarkers for indicating the onset of various mental disorders. Existing models using EEG data are typically trained to distinguish between healthy and afflicted individuals, and they are unable to distinguish between individuals with different disorders. We propose MENTAL (Multi-modal EEG NEO-FFI with Trained Attention Layer) to predict an individual's mental state using both EEG and Neo-Five Factor Inventory (NEO-FFI) personality data. We include an attention layer that captures the interactions between personality traits and PSD features, and emphasizes the important PSD features. MENTAL features a Recurrent Neural Network (RNN) to model the temporal nature of EEG data. We train our model with the Two Decades Brainclinics Research Archive for Insights in Neuroscience (TDBRAIN) dataset, which consists of 1274 healthy and psychiatric individuals including over 30 different diagnoses. MENTAL is able to achieve 93.3% accuracy when trained to classify between healthy individuals and those with ADHD. When trained to identify individuals with ADHD from among 33 disorder classes, MENTAL improves accuracy from 70.5 to 81.7%. MENTAL also demonstrates over 20% improvement in predictive accuracy when trained for MDD prediction. For the multi-class classification task of three classes, MENTAL improves accuracy by 4%, and for five classes, by nearly 8%. MENTAL is the first multi-modal model that utilizes both EEG and NEO-FFI data for the task of mental disorder prediction. We are one of the first groups to utilize TDBRAIN for automated disorder classification. MENTAL is accessible and cost-effective, as EEG is more affordable than other neuroimaging methods such as MRI, and the NEO-FFI is a self- reported survey. Our model can lead to acceptance and support for individuals living with mental health challenges and improve quality of life in our society.

Intensive, Real-Time Data Collection of Psychological and Physiological Stress During a 96-Hour Field Training Exercise at a Senior Military College: Feasibility and Acceptability Cohort Study.

Poor physical fitness, stress, and fatigue are factors impacting military readiness, national security, and economic burden for the United States Department of Defense. Improved accuracy of wearable biosensors and remote field biologic sample collection strategies could make critical contributions to understanding how physical readiness and occupational stressors result in on-the-job and environment-related injury, sleep impairments, diagnosis of mental health disorders, and reductions in performance in war-fighters. This study aimed to evaluate the feasibility and acceptability of intensive biomarker and biometric data collection to understand physiological and psychological stress in Army Reserved Officer Training Corps cadets before, during, and after a 96-hour field training exercise (FTX). A prospective pilot study evaluated the feasibility and acceptability of multimodal field data collection using passive drool saliva sampling, sweat sensors, accelerometry, actigraphy, and photoplethysmography. In addition, physical fitness (Army Combat Fitness Test), self-reported injury, and psychological resilience (Brief Resilience Scale) were measured. A total of 22 cadets were included. Two were lost to follow-up due to injury during FTX, for a retention rate of 91%. Assessments of performance and psychological resilience were completed for all remaining participants, resulting in 100% testing adherence. All participants provided saliva samples before the FTX, with 98% adherence at the second time point and 91% at the third. For sweat, data collection was not possible. Average daily wear time for photoplethysmography devices was good to excellent, meeting a 70% threshold with data collected for ≥80% of person-days at all time points. Of the participants who completed the FTX and 12 completed a post-FTX acceptability survey for a response rate of 60%. Overall, participant acceptance was high (≥80%) for all metrics and devices. This study demonstrates that wearable biosensors and remote field biologic sample collection strategies during a military FTX have the potential to be used in higher stakes tactical environments in the future for some, but not all, of the strategies. Overall, real-time biometric and biomarker sampling is feasible and acceptable during field-based training and provides insights and strategies for future interventions on military cadet and active-duty readiness, environmental stress, and recovery.

Long-Term Mental Health Outcomes of Bronchopulmonary Dysplasia in Neonates: An 18-Year National Cohort Study

To evaluate the association between neonatal bronchopulmonary dysplasia and the subsequent development of mental health conditions in children and adolescents. This was a retrospective cohort study, utilizing data from individuals born in South Korea between 2002 and 2005 and followed up until 2021, using the National Health Insurance Database. The cohort included 1,893,314 participants born during that period, with 927 diagnosed with bronchopulmonary dysplasia during the neonatal period (the exposed cohort). They were matched 1:10 with 9,270 unexposed individuals (the unexposed cohort) based on key demographic factors. The median age at the first mental health disorder diagnosis was 9 years (interquartile range, 5-15 years), with 5,698 individuals (55.9%) being male. During an average follow-up of 15.2 years, the incidence rate was 481/10,000 person-years in the exposed and 138/10,000 person-years in the unexposed cohort. By the age of 18 years, the cumulative incidence in the exposed cohort was 54% (95% confidence interval [CI]; 50%-57%), with an adjusted hazard ratio of 3.18 (95% CI; 2.81-3.60) compared with the unexposed cohort, and adjusted hazard ratios for early- and late-onset mental health disorders of 4.48 (95% CI; 3.84-5.22) and 1.89 (95% CI; 1.61-2.22), respectively. Sensitivity analyses confirmed these findings, and a subgroup analysis revealed a higher risk among individuals with bronchopulmonary dysplasia who required prolonged respiratory support or oxygen. Half of children with bronchopulmonary dysplasia in our cohort developed mental health disorders by the age of 18 years, emphasizing the need for interventions and support for such individuals.

Diagnosable mental disorders among American Indians and Alaska Natives in the United States: A scoping review.

Diagnosable mental disorders among American Indians and Alaska Natives in the United States: A scoping review.

The Association Between Mental Health Literacy of Parents and Referral of Children and Adolescents to Mental Health Service Centers

Background: Mental health literacy refers to an individual’s knowledge and beliefs about mental health, which can aid in the detection, management, and prevention of mental illnesses. Prompt diagnosis of mental disorders is crucial for timely intervention and treatment. This study aims to investigate the mental health literacy and help-seeking behaviors of parents with children and adolescents under the age of 18. Methods: In this descriptive-analytical study, a cross-sectional design was utilized, and a surveying method was employed. A total of 134 parents of children and adolescents under 18, who were referred to the mental health service centers at Iran University of Medical Sciences and private psychiatric clinics in 2019 and 2020, participated in the study through convenient sampling. Two psychiatrists evaluated the psychiatric disorders of the children, and the parents completed the General Health Questionnaire-28 (GHQ-28) and the Mental Health Literacy Questionnaire. The collected data were analyzed using SPSS version 24. Results: The results of the one-way analysis of variance indicated that the total score of mental health literacy significantly differed among groups with varying levels of maternal education (p=0.001). Conclusion: This study underscores the impact of maternal education on mental health literacy among parents. Notably, parents with higher levels of education exhibited greater mental health literacy. It is essential to consider these findings in developing targeted interventions to improve mental health literacy among parents from diverse educational backgrounds. Further research should explore effective strategies for increasing awareness and knowledge about mental health in communities with varying levels of education.

Differences in the Rates of Diagnoses of Mental and Behavioral Disorders Due to Psychoactive Substance Use by Sex and Age during Pre-Pandemic and COVID-19 Pandemic Periods in Kazakhstan.

The COVID-19 pandemic had profound impacts worldwide on individuals with mental and behavioral disorders, including disorders due to psychoactive substance use. We investigated how the COVID-19 pandemic affected the trends in these disorders in the Republic of Kazakhstan. We researched and compared ICD-10 data on mental and behavioral disorders due to substance use in Kazakhstan that were diagnosed in 2018-2019 (pre-pandemic) versus 2020-2021 (the pandemic period). The data for the pandemic period were significantly different from those of the pre-pandemic in that (i) 'other stimulant-related disorders (F15)' and 'other psychoactive substance-related disorders (F19)' were increased in the younger age groups, (ii) the risk of 'opioid-related disorders (F11)' was decreased in the 30-year-old group in both males and females, and (iii) the risk of 'alcohol-related disorders (F10)' was increased in the 30-year-old group and decreased in the 20- and 50-year-old groups. In only the males, (iv) the risk of 'other psychoactive substance-related disorders (F19)' was increased in almost all of the age groups, and (v) the risk of 'cannabis-related disorders (F12)' was increased in the ≥50-year-olds. The pre-pandemic and pandemic periods thus involved changes due to COVID-19 in both males and females that were especially notable in males. These results indicate that further measures designed to prevent mental and behavioral disorders due to psychoactive substances are necessary at the primary, secondary, and tertiary levels, and personnel in medicine/nursing, the government, private organizations, and the public need to collaborate to devise such measures.

Supplemental Material for Diagnosable Mental Disorders Among American Indians and Alaska Natives in the United States: A Scoping Review

Supplemental Material for Diagnosable Mental Disorders Among American Indians and Alaska Natives in the United States: A Scoping Review

Maternal mental disorders and neonatal outcomes: Danish population-based cohort study.

Previous studies have indicated associations between maternal mental disorders and adverse birth outcomes; however, these studies mainly focus on certain types of mental disorders, rather than the whole spectrum. We aimed to conduct a broad study examining all maternal mental disorder types and adverse neonatal outcomes which is needed to provide a more complete understanding of the associations. We included 1 132 757 liveborn singletons born between 1997 and 2015 in Denmark. We compared children of mothers with a past (>2 years prior to conception; n = 48 646), recent (2 years prior to conception and during pregnancy; n = 15 899) or persistent (both past and recent; n = 10 905) diagnosis of any mental disorder, with children of mothers with no mental disorder diagnosis before the index delivery (n = 1 057 307). We also considered different types of mental disorders. We calculated odds ratios and 95% CIs of low birthweight, preterm birth, small for gestational age, low Apgar score, Caesarean delivery and neonatal death. Odds ratios for children exposed to past, recent and persistent maternal mental disorders suggested an increased risk for almost all adverse neonatal outcomes. Estimates were highest for children in the 'persistent' group for all outcomes, with the exception of the association between persistent maternal mental disorders and neonatal death (odds ratio 0.96, 0.62-1.48). Our study provides evidence for increased risk of multiple adverse neonatal outcomes among children of mothers with mental disorders, highlighting the need for close monitoring and support for women with mental disorders.