scholarly journals The architecture of co-morbidity networks of physical and mental health conditions in military veterans

2020 ◽  
Vol 476 (2239) ◽  
pp. 20190790
Author(s):  
Aaron F. Alexander-Bloch ◽  
Armin Raznahan ◽  
Russell T. Shinohara ◽  
Samuel R. Mathias ◽  
Harini Bathulapalli ◽  
...  
Keyword(s):  
System Analysis ◽  
Systems Of Care ◽  
Military Veterans ◽  
Psychiatric Morbidity ◽  
Psychological Trauma ◽  
Trauma Network ◽  
Targeted Interventions ◽  
Network Analyses ◽  
Co Morbidity ◽  
Psychiatric Conditions

Co-morbidity between medical and psychiatric conditions is commonly considered between individual pairs of conditions. However, an important alternative is to consider all conditions as part of a co-morbidity network, which encompasses all interactions between patients and a healthcare system. Analysis of co-morbidity networks could detect and quantify general tendencies not observed by smaller-scale studies. Here, we investigate the co-morbidity network derived from longitudinal healthcare records from approximately 1 million United States military veterans, a population disproportionately impacted by psychiatric morbidity and psychological trauma. Network analyses revealed marked and heterogenous patterns of co-morbidity, including a multi-scale community structure composed of groups of commonly co-morbid conditions. Psychiatric conditions including posttraumatic stress disorder were strong predictors of future medical morbidity. Neurological conditions and conditions associated with chronic pain were particularly highly co-morbid with psychiatric conditions. Across conditions, the degree of co-morbidity was positively associated with mortality. Co-morbidity was modified by biological sex and could be used to predict future diagnostic status, with out-of-sample prediction accuracy of 90–92%. Understanding complex patterns of disease co-morbidity has the potential to lead to improved designs of systems of care and the development of targeted interventions that consider the broader context of mental and physical health.

scholarly journals The architecture of co-morbidity networks of physical and mental health conditions in military veterans

2020 ◽  
Author(s):  
Aaron F Alexander-Bloch ◽  
Armin Raznahan ◽  
Russell T Shinohara ◽  
Samuel R Mathias ◽  
Harini Bathulapalli ◽  
...  
Keyword(s):  
System Analysis ◽  
Systems Of Care ◽  
Military Veterans ◽  
Psychiatric Morbidity ◽  
Psychological Trauma ◽  
Trauma Network ◽  
Targeted Interventions ◽  
Network Analyses ◽  
Co Morbidity ◽  
Psychiatric Conditions

AbstractCo-morbidity between medical and psychiatric conditions is commonly considered between individual pairs of conditions. However, an important alternative is to consider all conditions as part of a co-morbidity network, which encompasses all interactions between patients and a healthcare system. Analysis of co-morbidity networks could detect and quantify general tendencies not observed by smaller-scale studies. Here, we investigate the co-morbidity network derived from longitudinal healthcare records from approximately 1-million U.S. military veterans, a population disproportionately impacted by psychiatric morbidity and psychological trauma. Network analyses revealed marked and heterogenous patterns of co-morbidity, including a multi-scale community structure composed of groups of commonly co-morbid conditions. Psychiatric conditions including posttraumatic stress disorder were strong predictors of future medical morbidity. Neurological conditions and conditions associated with chronic pain were particularly highly co-morbid with psychiatric conditions. Across conditions, the degree of co-morbidity was positively associated with mortality. Co-morbidity was modified by biological sex and could be used to predict future diagnostic status, with out-of-sample prediction accuracy of 90-92%. Understanding complex patterns of disease co-morbidity has the potential to lead to improved designs of systems of care and the development of targeted interventions that consider the broader context of mental and physical health.

scholarly journals Diagnostic Agreement between Physicians and a Consultation–Liaison Psychiatry Team at a General Hospital: An Exploratory Study across 20 Years of Referrals

2021 ◽  
Vol 18 (2) ◽  
pp. 749
Author(s):  
Mattia Marchi ◽  
Federica Maria Magarini ◽  
Giorgio Mattei ◽  
Luca Pingani ◽  
Maria Moscara ◽  
...  
Keyword(s):  
General Hospital ◽  
Depressive Disorders ◽  
Psychiatric Morbidity ◽  
Clinical Signs ◽  
Kappa Statistics ◽  
Comorbid Depression ◽  
Liaison Psychiatry ◽  
Consultation Liaison Psychiatry ◽  
Psychiatric Conditions ◽  
Diagnostic Concordance

Consultation–liaison psychiatry (CLP) manages psychiatric care for patients admitted to a general hospital (GH) for somatic reasons. We evaluated patterns in psychiatric morbidity, reasons for referral and diagnostic concordance between referring doctors and CL psychiatrists. Referrals over the course of 20 years (2000–2019) made by the CLP Service at Modena GH (Italy) were retrospectively analyzed. Cohen’s kappa statistics were used to estimate the agreement between the diagnoses made by CL psychiatrist and the diagnoses considered by the referring doctors. The analyses covered 18,888 referrals. The most common referral reason was suspicion of depression (n = 4937; 32.3%), followed by agitation (n = 1534; 10.0%). Psychiatric diagnoses were established for 13,883 (73.8%) referrals. Fair agreement was found for depressive disorders (kappa = 0.281) and for delirium (kappa = 0.342), which increased for anxiety comorbid depression (kappa = 0.305) and hyperkinetic delirium (kappa = 0.504). Moderate agreement was found for alcohol or substance abuse (kappa = 0.574). Referring doctors correctly recognized psychiatric conditions due to their exogenous etiology or clear clinical signs; in addition, the presence of positive symptoms (such as panic or agitation) increased diagnostic concordance. Close daily collaboration between CL psychiatrists and GH doctors lead to improvements in the ability to properly detect comorbid psychiatric conditions.

scholarly journals Mental health and suicidal ideation in US military veterans with histories of COVID-19 infection

2021 ◽  
pp. bmjmilitary-2021-001846
Author(s):  
Peter Na ◽  
J Tsai ◽  
I Harpaz-Rotem ◽  
R Pietrzak
Keyword(s):  
Suicidal Ideation ◽  
Protective Factors ◽  
Community Integration ◽  
Military Veterans ◽  
Risk And Protective Factors ◽  
Stress Disorders ◽  
Us Military ◽  
Increased Risk ◽  
Psychiatric Conditions ◽  
Internalising Disorders

IntroductionThere have been reports of increased prevalence in psychiatric conditions in non-veteran survivors of COVID-19. To date, however, no known study has examined the prevalence, risk and protective factors of psychiatric conditions among US military veterans who survived COVID-19.MethodsData were analysed from the 2019 to 2020 National Health and Resilience in Veterans Study, which surveyed a nationally representative, prospective cohort of 3078 US veterans. Prepandemic and 1-year peripandemic risk and protective factors associated with positive screens for peripandemic internalising (major depressive, generalised anxiety and/or posttraumatic stress disorders) and externalising psychiatric disorders (alcohol and/or drug use disorders) and suicidal ideation were examined using bivariate and multivariate logistic regression analyses.ResultsA total of 233 veterans (8.6%) reported having been infected with COVID-19. Relative to veterans who were not infected, veterans who were infected were more likely to screen positive for internalising disorders (20.5% vs 13.9%, p=0.005), externalising disorders (23.2% vs 14.8%, p=0.001) and current suicidal ideation (12.0% vs 7.6%, p=0.015) at peripandemic. Multivariable analyses revealed that greater prepandemic psychiatric symptom severity and COVID-related stressors were the strongest independent predictors of peripandemic internalising disorders, while prepandemic trauma burden was protective. Prepandemic suicidal ideation, greater loneliness and lower household income were the strongest independent predictors of peripandemic suicidal ideation, whereas prepandemic community integration was protective.ConclusionPsychiatric symptoms and suicidal ideation are prevalent in veterans who have survived COVID-19. Veterans with greater prepandemic psychiatric and substance use problems, COVID-related stressors and fewer psychosocial resources may be at increased risk of these outcomes.

The prevalence and co-morbidity of subthreshold psychiatric conditions

2004 ◽  
Vol 34 (4) ◽  
pp. 613-622 ◽  
Author(s):  
PETER M. LEWINSOHN ◽  
STEWART A. SHANKMAN ◽  
JEFFREY M. GAU ◽  
DANIEL N. KLEIN
Keyword(s):  
Clinical Practice ◽  
Adolescent Depression ◽  
Internalizing Disorders ◽  
Externalizing Disorders ◽  
Diagnostic Interview ◽  
Future Research ◽  
Co Morbidity ◽  
Psychiatric Conditions ◽  
Dsm Iv ◽  
Males And Females

Background. In previous studies of subthreshold conditions, co-morbidity has been largely ignored. The purpose was to examine rates of co-morbidity among subthreshold disorders and between subthreshold and full-syndrome disorders for the major non-psychotic classes of disorders from DSM-IV.Method. Participants came from the Oregon Adolescent Depression Project (mean age=16·6 years; females=52·1%). On the basis of a diagnostic interview (K-SADS), participants were assigned to eight subthreshold disorders (MDD, bipolar, eating, anxiety, alcohol use, substance use, conduct, ADHD).Results. Of the 1704 adolescents in the analyses, 52·5% had at least one subthreshood disorder. Of those, 40·0% had also experienced a co-morbid subthreshold condition, and 29·9% of those had a second co-morbid subthreshold condition. Of those with a subthreshold, 36·4% also had a full syndrome. The subthreshold forms of externalizing disorders were co-morbid with each other. As expected, subthreshold anxiety was co-morbid with subthreshold MDD but subthreshold anxiety was also co-morbid with subthreshold alcohol, conduct, and ADHD. The pattern of co-morbidities was nearly identical for males and females.Conclusions. The hypotheses that externalizing disorders would be co-morbid with other externalizing disorders and that internalizing disorders would be co-morbid with other internalizing disorders was partially supported. Co-morbidities between subthreshold disorders and between subthreshold disorders and full syndrome should impact future research and clinical practice. The assessment of subthreshold disorders needs to include the assessment of other subthreshold and full-syndrome conditions.

scholarly journals O4B.2 Patterns and predictors of return to work after major trauma: a prospective, population based registry study

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A34.2-A34
Author(s):  
Alex Collie ◽  
Pamela Simpson ◽  
Peter Cameron ◽  
Shanthi Ameratunga ◽  
Jennie Ponsford ◽  
...  
Keyword(s):  
Return To Work ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Multinomial Logistic Regression ◽  
Traumatic Injury ◽  
Population Based ◽  
Full Time ◽  
Post Injury ◽  
Targeted Interventions ◽  
Co Morbidity

BackgroundEmployment is an important marker of functional recovery from injury. There are few population-based studies of long-term employment outcomes, and limited data on the patterns of return to work post injury.ObjectivesThis study sought to characterise patterns of engagement in work over the four-year period following major traumatic injury, and to identify factors associated with those patterns.MethodWe conducted a population-based, prospective cohort study using the Victorian State Trauma Registry. A total of 1086 working age individuals, in paid employment or full-time education before injury, were followed-up through telephone interview at 6, 12, 24, 36, and 48 months post-injury. Responses to return to work (RTW) questions were used to define four discrete patterns: early and sustained; delayed; failed; no RTW. Predictors of RTW patterns were assessed using multivariate multinomial logistic regression.ResultsSlightly more than half of respondents (51.6%) recorded early sustained RTW. A further 15.5% had delayed and 13.3% failed RTW. One in five (19.7%) did not RTW. Compared with early sustained RTW, predictors of delayed and no RTW included being in a manual occupation and injury in a motor vehicle accident. Older age and receiving compensation predicted both failed and no RTW patterns. Pre-injury disability was an additional predictor of failed RTW. Presence of co-morbidity was an additional predictor of no RTW.ConclusionsA range of personal, occupational, injury, health and compensation system factors influence RTW patterns after serious injury. Early identification of people at risk for delayed, failed or no RTW is needed so that targeted interventions can be delivered.

scholarly journals A Study on Psychiatric Co-morbidity Among the Patients with Migraine

1970 ◽  
Vol 21 (2) ◽  
pp. 108-111
Author(s):  
AA Mamun Hussain ◽  
MA Mohit ◽  
MA Ahad ◽  
MA Alim
Keyword(s):  
Early Recognition ◽  
Psychiatric Morbidity ◽  
Integrated Treatment ◽  
Dysthymic Disorder ◽  
Obsessive Compulsive ◽  
College Hospital ◽  
Cross Sectional ◽  
Medical College ◽  
Co Morbidity ◽  
Headache Clinic

A cross-sectional retrospective study was done in the ‘Headache clinic' of Bangabandhu Sheikh Mujib Medical University (BSMMU) and Dhaka Medical College Hospital (DMCH) comprising a sample of eighty patients with migraine. There were 64(80%), female and 16 male (20%). Among them 19(23.75%) had psychiatric disorder as co-morbidity. In accordance with DSM-IV, the commonest psychiatric illness was major depressive disorder (36.84%). The others were panic disorder (21.05%), obsessive compulsive disorders (15.78%) and dysthymic disorder (15.78%). Considering these findings and observation, it so appears that a substantial psychiatric morbidity is prevalent among the sufferers of migraine and it warrants early recognition and proper assessment with the initiation of an integrated treatment modality. doi: 10.3329/taj.v21i2.3787 TAJ 2008; 21(2): 108-111

Mental health promotion: Guidance and strategies

2012 ◽  
Vol 27 (2) ◽  
pp. 81-86 ◽  
Author(s):  
G. Kalra ◽  
G. Christodoulou ◽  
R. Jenkins ◽  
V. Tsipas ◽  
N. Christodoulou ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Promotion ◽  
Psychiatric Disorders ◽  
Psychiatric Morbidity ◽  
Public Mental Health ◽  
Population Group ◽  
Well Being ◽  
Mental Health Promotion ◽  
Targeted Interventions ◽  
Population Mental Health

AbstractPublic mental health incorporates a number of strategies from mental well-being promotion to primary prevention and other forms of prevention. There is considerable evidence in the literature to suggest that early interventions and public education can work well for reducing psychiatric morbidity and resulting burden of disease. Educational strategies need to focus on individual, societal and environmental aspects. Targeted interventions at individuals will also need to focus on the whole population. A nested approach with the individual at the heart of it surrounded by family surrounded by society at large is the most suitable way to approach this. This Guidance should be read along with the European Psychiatric Association (EPA) Guidance on Prevention. Those at risk of developing psychiatric disorders also require adequate interventions as well as those who may have already developed illness. However, on the model of triage, mental health and well-being promotion need to be prioritized to ensure that, with the limited resources available, these activities do not get forgotten. One possibility is to have separate programmes for addressing concerns of a particular population group, another that is relevant for the broader general population. Mental health promotion as a concept is important and this will allow prevention of some psychiatric disorders and, by improving coping strategies, is likely to reduce the burden and stress induced by mental illness.

scholarly journals Dimensions of Misinformation About the HPV Vaccine on Instagram: Content and Network Analysis of Social Media Characteristics

10.2196/21451 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e21451
Author(s):  
Philip M Massey ◽  
Matthew D Kearney ◽  
Michael K Hauer ◽  
Preethi Selvan ◽  
Emmanuel Koku ◽  
...  
Keyword(s):  
Social Media ◽  
Health Beliefs ◽  
Hpv Vaccine ◽  
English Language ◽  
Personal Narrative ◽  
Personal Narratives ◽  
Evidence Base ◽  
Conspiracy Theories ◽  
Targeted Interventions ◽  
Network Analyses

Background The human papillomavirus (HPV) vaccine is a major advancement in cancer prevention and this primary prevention tool has the potential to reduce and eliminate HPV-associated cancers; however, the safety and efficacy of vaccines in general and the HPV vaccine specifically have come under attack, particularly through the spread of misinformation on social media. The popular social media platform Instagram represents a significant source of exposure to health (mis)information; 1 in 3 US adults use Instagram. Objective The objective of this analysis was to characterize pro- and anti-HPV vaccine networks on Instagram, and to describe misinformation within the anti-HPV vaccine network. Methods From April 2018 to December 2018, we collected publicly available English-language Instagram posts containing hashtags #HPV, #HPVVaccine, or #Gardasil using Netlytic software (n=16,607). We randomly selected 10% of the sample and content analyzed relevant posts (n=580) for text, image, and social media features as well as holistic attributes (eg, sentiments, personal stories). Among antivaccine posts, we organized elements of misinformation within four broad dimensions: 1) misinformation theoretical domains, 2) vaccine debate topics, 3) evidence base, and 4) health beliefs. We conducted univariate, bivariate, and network analyses on the subsample of posts to quantify the role and position of individual posts in the network. Results Compared to provaccine posts (324/580, 55.9%), antivaccine posts (256/580, 44.1%) were more likely to originate from individuals (64.1% antivaccine vs 25.0% provaccine; P<.001) and include personal narratives (37.1% vs 25.6%; P=.003). In the antivaccine network, core misinformation characteristics included mentioning #Gardasil, purporting to reveal a lie (ie, concealment), conspiracy theories, unsubstantiated claims, and risk of vaccine injury. Information/resource posts clustered around misinformation domains including falsification, nanopublications, and vaccine-preventable disease, whereas personal narrative posts clustered around different domains of misinformation, including concealment, injury, and conspiracy theories. The most liked post (6634 likes) in our full subsample was a positive personal narrative post, created by a non-health individual; the most liked post (5604 likes) in our antivaccine subsample was an informational post created by a health individual. Conclusions Identifying characteristics of misinformation related to HPV vaccine on social media will inform targeted interventions (eg, network opinion leaders) and help sow corrective information and stories tailored to different falsehoods.

scholarly journals Static Ecological System Analysis

2018 ◽  
Author(s):  
Huseyin Coskun
Keyword(s):  
System Analysis ◽  
Interspecific Interactions ◽  
Ecological Systems ◽  
Mathematical Framework ◽  
The Novel ◽  
Holistic View ◽  
Network Analyses ◽  
Input And Output ◽  
Compartmental Systems

In this article, a new mathematical method for static analysis of compartmental systems is developed in the context of ecology. The method is based on the novel system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. That is, the distribution of environmental inputs and intercompartmental system flows, as well as the organization of the associated storages generated by these flows within the system is determined individually and separately. Moreover, the transient and the static direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted along a given flow path or from one compartment, directly or indirectly, to any other are analytically characterized, systematically classified, and mathematically formulated. A quantitative technique for the categorization of interspecific interactions and the determination of their strength within food webs is also developed based on the diact transactions. The proposed methodology allows for both input- and output-oriented analyses of static ecological networks. The input- and output-oriented analyses are introduced within the proposed mathematical framework and their duality is demonstrated. Major flow- and stock-related concepts and quantities of the current static network analyses are also integrated with the proposed measures and indices within this unifying framework. This comprehensive methodology enables a holistic view and analysis of ecological systems.

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