Diagnosis Of Mental Health Conditions Research Articles

Mortality and suicidality in veterans health administration patients with newly-identified early episode psychosis

Within the Veterans Affairs (VA), management of self-harm is a major clinical priority. However, there is limited information on risks for self-harm among VA patients with emerging psychotic disorders relative to VA patients with other emerging mental health conditions. Using information from fiscal years 2010 through 2018, a national cohort of VA patients 30 or younger was classified based on mental health diagnoses into three groups: 1) early episode psychosis (EEP), 2) non-early episode psychosis mental health (non-EEP MH), or 3) no mental health (no MH). Analyses focused on cohort members' risk for all-cause mortality, suicide mortality, and non-fatal suicide attempts (NFSA) during the year following initial diagnosis of mental health conditions (or first year of VA care, for the no MH group). In unadjusted analyses, the EEP group had elevated rates of all-cause mortality, suicide mortality, and NFSA relative to the non-EEP MH and no MH groups and the non-EEP MH had elevated rates of all-cause mortality, suicide mortality, and NFSA relative to the no MH group. After adjusting for demographics and care receipt, EEP status was unrelated to all-cause mortality but associated with increased suicide mortality risk and NFSA. Non-EEP MH status was associated with reduced risk of all-cause mortality but increased risk for NFSA. In the year following first diagnosis, VA patients with EEP are at increased risk for suicide mortality and self-harm even after accounting for other risk factors. Clinical services targeting this crucial time can help promote safety for this vulnerable group.

Is ChatGPT ready to change mental healthcare? Challenges and considerations: a reality-check

As mental healthcare is highly stigmatized, digital platforms and services are becoming popular. A wide variety of exciting and futuristic applications of AI platforms are available now. One such application getting tremendous attention from users and researchers alike is Chat Generative Pre-trained Transformer (ChatGPT). ChatGPT is a powerful chatbot launched by open artificial intelligence (Open AI). ChatGPT interacts with clients conversationally, answering follow-up questions, admitting mistakes, challenging incorrect premises, and rejecting inappropriate requests. With its multifarious applications, the ethical and privacy considerations surrounding the use of these technologies in sensitive areas such as mental health should be carefully addressed to ensure user safety and wellbeing. The authors comment on the ethical challenges with ChatGPT in mental healthcare that need attention at various levels, outlining six major concerns viz., (1) accurate identification and diagnosis of mental health conditions; (2) limited understanding and misinterpretation; (3) safety, and privacy of users; (4) bias and equity; (5) lack of monitoring and regulation; and (6) gaps in evidence, and lack of educational and training curricula.

Association of Food Insecurity Status with Resolution of Mental Health Conditions in Children and Adolescents.

Adverse consequences related to unresolved mental health issues underscore the importance of identifying factors that impede resolution of mental health conditions. Although studies have identified food insecurity as a risk factor for the diagnosis of mental health conditions, its impact on unresolved mental health issues is not understood. The objective of this study is to investigate the association of food insecurity status with resolution of depression, anxiety, and behavioral/conduct problems in children and adolescents. Using National Survey of Children's Health 2016 to 2019, logistic regression analyses examined the relationship of food insecurity status with the diagnosis and resolution of depression, anxiety, and behavioral/conduct problems in children (aged 5-11 years) and adolescents (aged 12-17 years). Mild, moderate, and severe food insecurity were significantly associated with higher odds of being diagnosed with depression, anxiety, and behavioral/conduct problems. Severe food insecurity was significantly associated with higher odds of unresolved behavioral/conduct problems in children (adjusted odds ratio [aOR], 10.09; 95% confidence interval [CI], 2.99-34.04), after adjustment for demographic covariates. In adolescents, severe food insecurity was significantly related to greater odds of unresolved depression (aOR, 6.64; 95% CI, 2.13-20.70), anxiety (aOR, 3.27; 95% CI, 1.31-8.14), and behavioral/conduct problems (aOR, 5.57; 95% CI, 2.09-14.85). These associations of severe food insecurity with unresolved mental health conditions were significant even after adjustment for the receipt of mental health care. Mild and moderate food insecurity were not significantly associated with unresolved mental health conditions. The findings suggest that severe food insecurity is associated with increased odds of unresolved mental health conditions in children and adolescents. This study highlights the importance of tailoring interventions to provide appropriate mental health services for children and adolescents from severely food insecure households.

Associations between constructs related to social relationships and mental health conditions and symptoms: an umbrella review

BackgroundLoneliness and social isolation are increasingly recognised as prevalent among people with mental health problems, and as potential targets for interventions to improve quality of life and outcomes, as well as for preventive strategies. Understanding the relationship between quality and quantity of social relationships and a range of mental health conditions is a helpful step towards development of such interventions.PurposeOur aim was to give an overview of associations between constructs related to social relationships (including loneliness and social isolation) and diagnosed mental conditions and mental health symptoms, as reported in systematic reviews of observational studies.MethodsFor this umbrella review (systematic review of systematic reviews) we searched five databases (PsycINFO, MEDLINE, EMBASE, CINAHL, Web of Science) and relevant online resources (PROSPERO, Campbell Collaboration, Joanna Briggs Institute Evidence Synthesis Journal). We included systematic reviews of studies of associations between constructs related to social relationships and mental health diagnoses or psychiatric symptom severity, in clinical or general population samples. We also included reviews of general population studies investigating the relationship between loneliness and risk of onset of mental health problems.ResultsWe identified 53 relevant systematic reviews, including them in a narrative synthesis. We found evidence regarding associations between (i) loneliness, social isolation, social support, social network size and composition, and individual-level social capital and (ii) diagnoses of mental health conditions and severity of various mental health symptoms. Depression (including post-natal) and psychosis were most often reported on, with few systematic reviews on eating disorders or post-traumatic stress disorder (PTSD), and only four related to anxiety. Social support was the most commonly included social construct. Our findings were limited by low quality of reviews and their inclusion of mainly cross-sectional evidence.ConclusionGood quality evidence is needed on a wider range of social constructs, on conditions other than depression, and on longitudinal relationships between social constructs and mental health symptoms and conditions.

Exploring the differentiation of behavioural and emotional problems across childhood: A prospective longitudinal cohort study.

An individual's overall burden of behavioural and emotional problems across childhood is associated with increased likelihood of later mental health conditions. However, the relative extent of behavioural versus emotional problems - that is, the extent to which the domains are differentiated from one another - may provide additional information about who is at risk of developing a mental health condition. Here, we seek to validate differentiation as an independent predictor of later mental health conditions, and to explore its aetiology. We analysed data from ~79,000 children in the population-based Norwegian Mother, Father, and Child Cohort Study, and linked health-care registries. In preregistered analyses, we modelled the extent and rate of differentiation of behavioural and emotional problems between ages 1.5-5years, and estimated associations with later symptoms (age 8) and diagnoses (after age 8). We also explored the aetiology of differentiation by estimating associations with early life exposures and, in a subset of 23,945 full siblings, assessing the impact of accounting for unobserved familial confounding. Differentiation of behavioural and emotional problems was associated with later symptoms and diagnoses of mental health conditions, independent of total problems. Maternal at-risk drinking (β=0.04 [0.02, 0.06]) and parental relationship problems (β=0.04 [0.02, 0.05]) were associated with higher behavioural relative to emotional problems at age 5. Maternal prenatal distress (|β|=0.04 [0.03, 0.06]), concurrent distress (|β|=0.04 [0.02, 0.06]) and parental education (|β|=0.05 [0.04, 0.07]) predicted higher emotional relative to behavioural problems at age 5. Estimates for maternal prenatal distress and at-risk drinking were consistent across both unadjusted and adjusted analyses accounting for unobserved familial risk. Differentiation of behavioural and emotional problems in early childhood represents a valid source of inter-individual variability linked to the later emergence of psychopathology and may be relevant for early detection and prevention strategies for mental health.

Screening and Diagnosis of Mental Health Conditions During Pregnancy and Postpartum: ACOG Clinical Practice Guideline No. 4.

To review evidence on the current understanding of mental health conditions in pregnancy and postpartum, with a focus on mood and anxiety disorders, and to outline guidelines for screening and diagnosis that are consistent with best available scientific evidence. The conditions or symptoms reviewed include depression, anxiety and anxiety-related disorders, bipolar disorder, suicidality, and postpartum psychosis. For information on psychopharmacologic treatment and management, refer to American College of Obstetricians and Gynecologists (ACOG) Clinical Practice Guideline Number 5, "Treatment and Management of Mental Health Conditions During Pregnancy and Postpartum" (1). Pregnant or postpartum individuals with mental health conditions. Onset of these conditions may have predated the perinatal period or may have occurred for the first time in pregnancy or the first year postpartum or may have been exacerbated in that time. This guideline was developed using an a priori protocol in conjunction with a writing team consisting of one specialist in obstetrics and gynecology and one maternal-fetal medicine subspecialist appointed by the ACOG Committee on Clinical Practice Guidelines-Obstetrics and two external subject matter experts. ACOG medical librarians completed a comprehensive literature search for primary literature within Cochrane Library, Cochrane Collaboration Registry of Controlled Trials, EMBASE, PubMed, and MEDLINE. Studies that moved forward to the full-text screening stage were assessed by two authors from the writing team based on standardized inclusion and exclusion criteria. Included studies underwent quality assessment, and a modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) evidence-to-decision framework was applied to interpret and translate the evidence into recommendation statements. This Clinical Practice Guideline includes recommendations on the screening and diagnosis of perinatal mental health conditions including depression, anxiety, bipolar disorder, acute postpartum psychosis, and the symptom of suicidality. Recommendations are classified by strength and evidence quality. Ungraded Good Practice Points are included to provide guidance when a formal recommendation could not be made because of inadequate or nonexistent evidence.

Treatment and Management of Mental Health Conditions During Pregnancy and Postpartum: ACOG Clinical Practice Guideline No. 5.

To assess the evidence regarding safety and efficacy of psychiatric medications to treat mental health conditions during pregnancy and lactation. The conditions reviewed include depression, anxiety and anxiety-related disorders, bipolar disorder, and acute psychosis. For information on screening and diagnosis, refer to American College of Obstetricians and Gynecologists (ACOG) Clinical Practice Guideline Number 4, "Screening and Diagnosis of Mental Health Conditions During Pregnancy and Postpartum" (1). Pregnant or postpartum individuals with mental health conditions with onset that may have predated the perinatal period or may have occurred for the first time in pregnancy or the first year postpartum or may have been exacerbated in that time. This guideline was developed using an a priori protocol in conjunction with a writing team consisting of one specialist in obstetrics and gynecology and one maternal-fetal medicine subspecialist appointed by the ACOG Committee on Clinical Practice Guidelines-Obstetrics and two external subject matter experts. ACOG medical librarians completed a comprehensive literature search for primary literature within Cochrane Library, Cochrane Collaboration Registry of Controlled Trials, EMBASE, PubMed, and MEDLINE. Studies that moved forward to the full-text screening stage were assessed by two authors from the writing team based on standardized inclusion and exclusion criteria. Included studies underwent quality assessment, and a modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) evidence-to-decision framework was applied to interpret and translate the evidence into recommendation statements. This Clinical Practice Guideline includes recommendations on treatment and management of perinatal mental health conditions including depression, anxiety, bipolar disorders, and acute postpartum psychosis, with a focus on psychopharmacotherapy. Recommendations are classified by strength and evidence quality. Ungraded Good Practice Points are included to provide guidance when a formal recommendation could not be made because of inadequate or nonexistent evidence.

Non-communicable disease burden among inpatients at a rural district hospital in Malawi

BackgroundThe burden of non-communicable diseases (NCDs) is high in Malawi. However, resources and training for NCD care remain scarce, especially in rural hospitals. Current care for NCDs in the developing world focuses on the WHO’s traditional 4 × 4 set. However, we do not know the full burden of NCDs outside of that scope, like neurological disease, psychiatric illness, sickle cell disease, and trauma. The goal of this study was to understand the burden of NCDs among inpatients in a rural district hospital in Malawi. We broadened our definition of NCDs beyond the traditional 4 × 4 set of NCDs, and included neurological disease, psychiatric illness, sickle cell disease, and trauma.MethodsWe conducted a retrospective chart review of all inpatients who were admitted to the Neno District Hospital between January 2017 and October 2018. We broke patients down by age, date of admission, type, and number of NCD diagnoses, and HIV status, and constructed multivariate regression models for length of stay and in-hospital mortality.ResultsOf 2239 total visits, 27.5% were patients with NCDs. Patients with NCDs were older (37.6 vs 19.7 years, p < 0.001) and made up 40.2% of total hospital time. We also found two distinct populations of NCD patients. The first were patients 40 years and older with primary diagnoses of hypertension, heart failure, cancer, and stroke. The second were patients under 40 years old with primary diagnoses of mental health conditions, burns, epilepsy, and asthma. We also found significant trauma burden, accounting for 40% of all NCD visits. In multivariate analysis, carrying a medical NCD diagnosis was associated with longer length of stay (coefficient 5.2, p < 0.001) and a higher risk of in-hospital mortality (OR 1.9, p = 0.03). Burn patients also had significantly longer length of stay (coefficient 11.6, p < 0.001).ConclusionsThere is a significant burden of NCDs in a rural hospital in Malawi, including those outside of the traditional 4 × 4 set. We also found high rates of NCDs in the younger population (under 40 years of age). Hospitals must be equipped with adequate resources and training to meet this burden of disease.

Financial Distress and Psychological Well-Being During the COVID-19 Pandemic

Objective: We examine the impact of financial distress caused by the COVID-19 pandemic on mental health and psychological well-being. Methods: We analyze cross-sectional survey data (n = 2,545) from the Life during Pandemic study in Chile. We estimate linear probability models to analyze the relationship between economic fragility, financial distress, and psychological well-being. Results: Our findings show unemployment and income loss are highly predictive of experiencing a range of financial problems, such as a lack of savings, as well as difficulties paying bills, consumer debt, and mortgage loans. In turn, financial distress leads to a higher prevalence of poor well-being and mental health deterioration, and sleep problems. Conclusion: Expansion of mental health assistance services are needed, as new diagnosis of mental health conditions has increased, but treatment has not, pointing to a barrier in the access to some mental health care services during the pandemic. Policies designed with the objective of improving financial education are necessary to increase precautionary savings and financial resilience, and alleviate the psychological burden of debt in the future.

Mental Health of Older Adults With Intellectual Disability.

Across most age groups, individuals with intellectual disability (ID) have higher rates of mental health conditions than the general population. Approximately one third of older adults with ID living in the community experience the same mental health conditions as older adults in the general population but have unique needs for assessment and treatment. A health equity framework offers an important social perspective in addressing these needs. Timely recognition and diagnosis of mental health conditions in individuals with ID involves collaboration with family and other supports. Among older adults with ID, polypharmacy is strongly associated with mental health conditions. Older adults with ID are more likely to use the emergency department for treatment of their mental health conditions. The majority of mental health providers are not trained in working with patients with ID. Education, policy changes, and research are needed to improve the mental health care of this population. [Journal of Psychosocial Nursing and Mental Health Services, 60(7), 10-14.].

Sistem Pakar Mendeteksi Kondisi Kesehatan Mental Dengan Metode Forward Chaining Berbasis Android

The Expert System here is a system designed or built to imitate an expert using Android that can be installed, this system helps in handling and providing tips and solutions for these mental health conditions. From the research carried out, an Android-based expert system for the diagnosis of mental health conditions using the forward chaining method can provide information about 3 types of mental health, 15 symptom data, 3 different types of mental health, provide information about causes and tips on maintaining health conditions. mental health, to suggestions for final treatment. The results of the test using the Alpha Test on 17 respondents who we directed to install the expert system application first, the respondents consisted of students and the general public obtained the answer "Correct" has a percentage value of 0.51 or like 51%, and testing using Black Box testing that shows the value of the results according to the referral site

MHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis.

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

Artificial intelligence and mental health

How AI can be used to improve diagnosis of mental health conditions.

Dual diagnosis of mental health condition and substance use disorder at delivery and maternal morbidity

Substance use disorders (SUDs) are associated with underlying mental health conditions (MHCs). While both SUDs and MHCs are independently associated with increased risk for adverse maternal outcomes, there is limited national data on risk at the intersection of the two. We evaluated the frequency of SUD and MHC diagnoses during deliveries over time and whether combined diagnoses were associated with risk for severe maternal morbidity (SMM).

Impact of COVID-19 and partial lockdown on access to care, self-management and psychological well-being among people with diabetes: A cross-sectional study.

BackgroundThe impact of lockdown measures can be widespread, affecting both clinical and psychosocial aspects of health. This study aims to assess changes in health services access, self‐care, behavioural, and psychological impact of COVID‐19 and partial lockdown amongst diabetes patients in Singapore.MethodsWe conducted a cross‐sectional online survey amongst people with diabetes with the Diabetes Health Profile‐18 (DHP‐18). Hierarchical regression analyses were performed for each DHP‐18 subscale (Psychological Distress, Disinhibited Eating and Barriers to Activity) as dependent variables in separate models.ResultsAmong 301 respondents, 45.2% were women, 67.1% of Chinese ethnicity, 24.2% were aged 40 to 49 years, 68.4% have Type 2 diabetes and 42.2% on oral medications alone. During the pandemic and the lockdown, nearly all respondents were able to receive care safely from the clinics they attend (94%) and obtain their medications and diabetes equipment and supplies (97%) when needed. Respondents reported less frequent engagement in physical activity (38%), checking of blood pressure (29%) and blood glucose (22%). Previous diagnosis of mental health conditions (β = 9.33, P = .043), Type 1 diabetes (β = 12.92, P = .023), number of diabetes‐related comorbidities (β = 3.16, P = .007) and Indian ethnicity (β = 6.65, P = .034) were associated with higher psychological distress. Comorbidities were associated with higher disinhibited eating (β = 2.49, P = .014) while ability to reach their doctor despite not going to the clinic is negatively associated with psychological distress (β = −9.50 P = .002) and barriers to activity (β = −7.53, P = .007).ConclusionHealth services access were minimally affected, but COVID‐19 and lockdown had mixed impacts on self‐care and management behaviours. Greater clinical care and attention should be provided to people with diabetes with multiple comorbidities and previous mental health disorders during the pandemic and lockdown.

Crowdsourced privacy-preserved feature tagging of short home videos for machine learning ASD detection

Standard medical diagnosis of mental health conditions requires licensed experts who are increasingly outnumbered by those at risk, limiting reach. We test the hypothesis that a trustworthy crowd of non-experts can efficiently annotate behavioral features needed for accurate machine learning detection of the common childhood developmental disorder Autism Spectrum Disorder (ASD) for children under 8 years old. We implement a novel process for identifying and certifying a trustworthy distributed workforce for video feature extraction, selecting a workforce of 102 workers from a pool of 1,107. Two previously validated ASD logistic regression classifiers, evaluated against parent-reported diagnoses, were used to assess the accuracy of the trusted crowd’s ratings of unstructured home videos. A representative balanced sample (N = 50 videos) of videos were evaluated with and without face box and pitch shift privacy alterations, with AUROC and AUPRC scores > 0.98. With both privacy-preserving modifications, sensitivity is preserved (96.0%) while maintaining specificity (80.0%) and accuracy (88.0%) at levels comparable to prior classification methods without alterations. We find that machine learning classification from features extracted by a certified nonexpert crowd achieves high performance for ASD detection from natural home videos of the child at risk and maintains high sensitivity when privacy-preserving mechanisms are applied. These results suggest that privacy-safeguarded crowdsourced analysis of short home videos can help enable rapid and mobile machine-learning detection of developmental delays in children.

Mental health of undocumented migrants and migrants undergoing regularization in Switzerland: a cross-sectional study

BackgroundUndocumented migrants live and work in precarious conditions. Few studies have explored the mental health consequences of such environment. The objective of this study is to describe the mental health of migrants at different stages of a regularization program.MethodsThis cross-sectional study included migrants undocumented or in the process of regularization. We screened for symptoms of anxiety, depression and sleep disturbance using validated tools. We created a composite outcome of altered mental health including these components plus self-report of a recent diagnosis of mental health condition by a health professional.ResultsWe enrolled 456 participants of whom 246 (53.9%) were undocumented. They were predominantly women (71.9%) with a median age of 43.3 (interquartile range: 15.5) years, from Latin America (63.6%) or Asia (20.2%) who had lived in Switzerland for 12 (IQR: 7) years. Overall, 57.2% presented symptoms of altered mental health. Prevalence of symptoms of anxiety, depression and sleep disturbance were 36% (95% confidence interval: 31.6–40.6%), 45.4% (95% CI: 40.8–50.1%) and 23% (95% CI: 19.2–27.2), respectively. Younger age (adjusted odd ratio: 0.7; 95% CI: 0.5–0.9 for each additional decade), social isolation (aOR: 2.4; 95% CI: 1.4–4.2), exposure to abuse (aOR: 1.9; 95% CI: 1.1–3.5), financial instability (aOR: 2.2; 95% CI: 1.4–3.7) and multi-morbidity (aOR: 3.2; 95% CI: 1.7–6.5) were associated with increased risk of having altered mental health while being in the early stages of the process of regularization had no effect (aOR: 1.3: 95% CI: 0.8–2.2).ConclusionsThis study highlights the need for multi-pronged social and health interventions addressing the various domains of undocumented migrants living difficulties as complement to legal status regularization policies. Protection against unfair working conditions and abuse, access to adequate housing, promoting social integration and preventive interventions to tackle the early occurrence of chronic diseases may all contribute to reduce the burden of altered mental health in this group. More research is needed to assess the long-term impact of legal status regularization on mental health.

Medicaid expansion and the mental health of college students.

Reported mental health problems have risen dramatically among US college students over time, as has treatment for these problems. We examine the effect of state-level Medicaid expansion following the 2014 implementation of the Affordable Care Act on the diagnosis of mental health conditions, psychotropic prescription drug use, and the mental health status of a national sample of college students. We find that students from disadvantaged backgrounds are more likely to report being on public insurance after 2014 in expansion states relative to non-expansion states, while more advantaged students do not see this increase. Both diagnosis of common mental health conditions and psychotropic drug use increase following expansion for disadvantaged students relative to advantaged ones, which translates into an elimination of the pre-expansion gap in these outcomes by family background in expansion states. However, in contrast to some recent work on Medicaid expansion and mental health, we do not find that these changes are associated with improvements in self-reported mental health status. We also do not find that Medicaid expansion has affected risky health behaviors or academic outcomes.

Physical multimorbidity, mental health and unplanned admissions from 2008 to 2018 in Abruzzo region

Abstract Background Multimorbidity is defined as the presence of more than one long-term disorder and it is associated with increased use of health services. Socioeconomic deprivation and mental health conditions may lead to undesirable additional unplanned admission to hospital (urgent or emergency admission). This study examines the association among unplanned admission, multimorbidity, mental health and socioeconomic deprivation for both preventable and not preventable hospitalization. Methods We conducted a retrospective analysis of hospital discharge records between 2008 and 2018 in Abruzzo, an Italian region. Multilevel logistic regression models were implemented for both preventable and not preventable unplanned admissions. We set as levels the district of residence and Local Health Authority. As independent variables we used the Italian Deprivation Index of the district of residence to mitigate socioeconomic inequalities, unweighted count of physical health conditions (0, 1, 2, 3, ≥4), the presence of a diagnosis of mental health condition. All the models were also adjusted for age and gender. Results We selected 2,017,720 non preventable admissions, 836,808 (41.45%) of which unplanned, and 152,938 preventable admissions, 107,336 (70.18%) of which unplanned. Both unplanned and potentially unplanned admissions were associated with increasing physical multimorbidity (for ≥4 v. 0 condition, OR 4.85; CI95% 4.26-5.53 for unplanned admission and OR 1.42; CI95% 1.11-1.83 for preventable unplanned admission) and with mental health conditions (OR 1.66; CI95% 1.57-1.75 for unplanned admission and OR 1.18; CI95% 1.00-1.38 for preventable unplanned admission). Conclusions Co-occurrence of physical multimorbidity and mental health condition was associated either with unplanned admission or unplanned preventable admission. Primary care interventions targeting multimorbidity are necessary to reduce the hospital service burden. Key messages Physical multimorbidity substantially affects the use of acute hospital services. Primary care interventions targeting multimorbidity are necessary to reduce the hospital service burden.

Socieconomic status and psychotropic medicine use during pregnancy: a population-based study in British Columbia, Canada.

Women at the lower end of the socioeconomic distribution have higher rates of depression in pregnancy and lower rates of treatment. In this study, we investigate relationships between income and the use of psychotropic mediciness in pregnancy. This retrospective cohort study using population-based administrative datasets included all women who delivered a live infant in the province of British Columbia, Canada (population of 4.6 million), between April 1, 2000, and December 31, 2009. We compared the socioeconomic distribution in use of psychotropic mediciness in pregnancy. We included 305,984 deliveries among 217,721 women. Women at the low end of the income distribution were significantly more likely to have a diagnosis for all mental health conditions, except anxiety, which was more common in women of highest socioeconomic status. The adjusted odds ratios for psychotropic medicine use indicate that women in the lowest income quintile have lower odds of filling a prescription for a psychotropic medicine after controlling for covariates and diagnoses of mental health conditions. However, they were more likely to fill a prescription for an antipsychotic and were more likely to fill psychotropic medicines from three or more different drug categories during pregnancy. Our findings suggest that women of lower socioeconomic status are less likely to fill a prescription for a psychotropic medicine in pregnancy, a finding largely driven by their decreased likelihood of filling an antidepressant. This is despite overall higher rates of mental illness among women of lower socioeconomic status, suggesting a gap in treatment by socioeconomic status.