scholarly journals Exploring the boundaries and ontology of Psychiatric Disorders (PDs) using the Homeostatic Property Cluster (HPC) model

2021 ◽  
Vol 8 (2) ◽  
pp. 15-31
Author(s):  
Marco Casali
Keyword(s):  
Psychiatric Disorders ◽  
Clinical Psychiatry ◽  
Psychiatric Diagnoses ◽  
General Manner ◽  
Change Of Perspective ◽  
Discrete Methods ◽  
Homeostatic Property Cluster ◽  
Insight Into

In this article we show that, even though the classification and diagnosis of Psychiatric Disorders (PDs) are performed according to essentialist terms, the psychiatric diagnoses currently employed, (i.e., clinical psychiatry) do not actually meet these criteria. Diagnosis is performed operationally. In this paper, we suggest a change of perspective. We reject essentialism relating to PDs and argue for the Homeostatic Property Cluster (HPC) model, which allows a greater insight into the ontology of PDs than the operational perspective. More specifically, we argue that the HPC model allows for a synthesis of continuous and discrete methods of understanding the boundaries between PDs. Finally, we specify in a more general manner, the kind of ontology we deal with when adopting the HPC model, arguing that this model can be viewed as a mirror device, reflecting the ontological features of PDs.

Prevalence of Psychiatric Diagnoses and Psychiatric Consultation Service Utilization on Inpatient Medical Units

2021 ◽  
pp. 107839032110055
Author(s):  
Bianca Reis ◽  
Jenny Hsin-Chun Tsai
Keyword(s):  
Health Care ◽  
Psychiatric Disorders ◽  
Health Care Delivery ◽  
Care Delivery ◽  
Adult Patients ◽  
Psychiatric Diagnoses ◽  
Psychiatric Consultation ◽  
Consultation Service ◽  
Icd 10 ◽  
Delivery Models

OBJECTIVE This practice improvement project sought to determine the prevalence of psychiatric diagnoses among patients admitted to a community hospital’s inpatient medical units and which diagnoses were serviced by the hospital’s psychiatric consultation service. METHOD Electronic medical record data on adult patients of five medical units admitted with a psychiatric condition between October 1, 2019, and December 31, 2019, were used. Psychiatric ICD-10 ( International Classification of Diseases, 10th Revision) codes and diagnosis names extracted were categorized into seven major diagnostic groups. A total of 687 adult patients with 82 psychiatric ICD-10 codes were analyzed using descriptive statistics. RESULTS Substance-related and addictive disorders were the most prevalent psychiatric diagnoses. Ninety-six percent ( n = 658) of patients residing on medical floors with psychiatric disorders were hospitalized for a principal medical problem. Seventy-three cases received psychiatric consultations during their stay. Sixty percent ( n = 44) of those cases had psychiatric disorders from two or more diagnostic categories. CONCLUSIONS Multidisciplinary, team-based health care delivery models that include a psychiatric nurse can provide an effective approach to treat patients in community hospitals with multiple psychiatric and medical comorbidities. Hospitals could take a significant role in providing substance use disorder treatment and equipping medical nurses with training to competently care for patients with psychiatric disorders on medical units. Further research into the prevalence and impact of patients with co-occurring and multiple psychiatric diagnoses in community hospitals is needed to implement effective health care delivery models and provide appropriate treatment options in the community.

Early adulthood psychiatric diagnoses and the subsequent risk of life-time incarceration: a cohort study

2019 ◽  
Vol 50 (11) ◽  
pp. 1906-1913
Author(s):  
Sophie D. Walsh ◽  
Bruce P. Dohrenwend ◽  
Itzhak Levav ◽  
Mark Weiser ◽  
Gilad Gal
Keyword(s):  
Substance Use ◽  
Cohort Study ◽  
Psychiatric Disorders ◽  
Early Adulthood ◽  
Vital Statistics ◽  
Birth Cohort Study ◽  
Psychiatric Diagnoses ◽  
Antisocial Personality ◽  
Cross Sectional ◽  
Psychiatric Interview

AbstractBackgroundThe association between incarceration and psychiatric disorders has been noted. Yet, existing studies are cross-sectional or examine the risk of recidivism, which has limited the predictive validity of psychiatric disorders as a risk factor for incarceration. To overcome this limitation, this study used a prospective cohort to examine whether psychiatric diagnoses in early adulthood predicted incarceration throughout a 30-year follow-up. It tested the association between psychiatric diagnoses with future incarcerations, their number and durations, controlling for education and ethnic status.MethodsThis study merged data from three sources in Israel: a prospective 10-year birth cohort study of young adults aged 25–34, conducted in the 1980s (N = 4914) that included a psychiatric interview; data from the Prison Service, including the cause, number and duration of incarcerations; and from the Vital Statistics Registry on death records.ResultsMultivariate analysis showed that substance-use disorders, antisocial personality and lower levels of education predicted future incarceration, their number and maximum duration. The remainder diagnoses were not significantly associated with future incarceration.ConclusionsResults limited the prediction of future incarcerations to persons diagnosed with substance use and antisocial personality, and do not support an independent predictive association between additional psychiatric diagnoses and future incarceration.

scholarly journals Risk of miscarriage in women with psychiatric disorders

2021 ◽  
pp. 1-6
Author(s):  
Maria C. Magnus ◽  
Alexandra Havdahl ◽  
Nils-Halvdan Morken ◽  
Knut-Arne Wensaas ◽  
Allen J. Wilcox ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Depressive Disorders ◽  
Somatoform Disorders ◽  
Psychiatric Diagnoses ◽  
Schizophrenia Spectrum Disorders ◽  
Birth Registry ◽  
Increased Risk ◽  
Wide Range

Background Some psychiatric disorders have been associated with increased risk of miscarriage. However, there is a lack of studies considering a broader spectrum of psychiatric disorders to clarify the role of common as opposed to independent mechanisms. Aims To examine the risk of miscarriage among women diagnosed with psychiatric conditions. Method We studied registered pregnancies in Norway between 2010 and 2016 (n = 593 009). The birth registry captures pregnancies ending in gestational week 12 or later, and the patient and general practitioner databases were used to identify miscarriages and induced abortions before 12 gestational weeks. Odds ratios of miscarriage according to 12 psychiatric diagnoses were calculated by logistic regression. Miscarriage risk was increased among women with bipolar disorders (adjusted odds ratio 1.35, 95% CI 1.26–1.44), personality disorders (adjusted odds ratio 1.32, 95% CI 1.12–1.55), attention-deficit hyperactivity disorder (adjusted odds ratio 1.27, 95% CI 1.21–1.33), conduct disorders (1.21, 95% CI 1.01, 1.46), anxiety disorders (adjusted odds ratio 1.25, 95% CI 1.23–1.28), depressive disorders (adjusted odds ratio 1.25, 95% CI 1.23–1.27), somatoform disorders (adjusted odds ratio 1.18, 95% CI 1.07–1.31) and eating disorders (adjusted odds ratio 1.14, 95% CI 1.08–1.22). The miscarriage risk was further increased among women with more than one psychiatric diagnosis. Our findings were robust to adjustment for other psychiatric diagnoses, chronic somatic disorders and substance use disorders. After mutual adjustment for co-occurring psychiatric disorders, we also observed a modest increased risk among women with schizophrenia spectrum disorders (adjusted odds ratio 1.22, 95% CI 1.03–1.44). Conclusions A wide range of psychiatric disorders were associated with increased risk of miscarriage. The heightened risk of miscarriage among women diagnosed with psychiatric disorders highlights the need for awareness and surveillance of this risk group in antenatal care.

Endophenotypes

2018 ◽  
pp. 103-106
Author(s):  
David C. Glahn ◽  
Laura Almasy ◽  
John Blangero
Keyword(s):  
Mental Illness ◽  
Genetic Variation ◽  
Psychiatric Disorders ◽  
Genetic Locus ◽  
Molecular Genetic ◽  
Gene Discovery ◽  
Psychiatric Diagnoses ◽  
Behavioral Syndrome ◽  
Molecular Genetic Variation ◽  
Or Gene

Endophenotypes are traits that, while genetically related to an illness, are not used for diagnoses (e.g., a symptom). It is unlikely that specific genes directly code for any of our current psychiatric diagnoses. Rather, genes influence neurobiological processes that either increase or decrease risk for mental illness. One use of an endophenotype is to help characterize a genetic locus or gene previously identified as conferring risk for a particular illness. In this context, endophenotypes help to bridge the gap between a behavioral syndrome and molecular genetic variation. Alternately, endophenotypes can be used for novel locus or gene discovery, particularly when used in multivariate analyses. In this chapter, we define endophenotypes and describe different ways they have been applied to aid our understanding of the genetic architecture of psychiatric disorders.

scholarly journals HOUT-29. THE INFLUENCE OF PSYCHIATRIC ILLNESS ON OUTCOME AND CANCER CARE RECEIVED IN PATIENTS WITH GLIOMAS

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi118-vi118
Author(s):  
Palak Patel ◽  
Terry Li ◽  
Janice Chou ◽  
Amie Patel ◽  
Sylvia Crispino ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Cancer Care ◽  
Psychiatric Illness ◽  
Adjustment Disorder ◽  
Tumor Diagnosis ◽  
Panic Attacks ◽  
Psychiatric Diagnoses ◽  
Increased Risk ◽  
Psychiatric Conditions

Abstract BACKGROUND Data related to the prevalence of different psychiatric disorders and their impact on survival and compliance in patients with glioma is scarce and mostly anecdotal. We aimed to study the prevalence of psychiatric disorders in glioma patients and the possible influence on compliance with cancer care and outcome. METHODS We performed a retrospective, observational study and compared compliance with medical care and outcome in patients who had or did not have a psychiatric illness at time of diagnosis. Kaplan-Meier method was used to compare survival between groups. RESULTS We identified 22 subjects (M=13, F=9) with intracranial glioma with psychiatric diagnosis and 22 matched control subjects (M=13, F=9) without psychiatric illness. Psychiatric diagnoses included depression (12%), anxiety disorder (6%), Adjustment disorder & substance use problems (2% each), bipolar disorder (1%) and panic attacks (1%). Psychiatric diagnoses were predating tumor diagnosis in 9/22 (41%) subjects and occurred around tumor diagnosis in 11/22 (50%) patients. The time of diagnosis with psychiatric illness was unknown in 2/22 (9%) of cases. Tumor diagnoses were glioblastoma in 50%, anaplastic astrocytoma in 9%, anaplastic oligodendroglioma in 13%, oligodendroglioma in 4%, and astrocytoma in 9% of cases. MedianOS was not reached for cases with psychiatric illness (not reached due to censoring) but was 4.2 years (95% CI 1.1 – 7.4) in controls (p=0.263). Subjects with psychiatric illness had an increased risk (OR 7.5, 95% CI 0.81 -68.8) of poor compliance with cancer care (medication, clinic and MRI follow-up compliance) compared to controls (p=0.046). CONCLUSION A variety of psychiatric conditions were observed in patients with glioma and presence of psychiatric illness may influence compliance with treatment and follow-up. Studies with larger population and longer follow-up are warranted to clarify true association between psychiatric conditions and compliance and survival.

scholarly journals Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

Metabolites ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 72 ◽  
Author(s):  
Elke Humer ◽  
Thomas Probst ◽  
Christoph Pieh
Keyword(s):  
Animal Models ◽  
Psychiatric Disorders ◽  
Treatment Strategies ◽  
Mood Stabilizers ◽  
Psychiatric Medication ◽  
Mitochondrial Regulation ◽  
Novel Treatment Strategies ◽  
Insight Into ◽  
Test Treatment

Biomarkers are a recent research target within biological factors of psychiatric disorders. There is growing evidence for deriving biomarkers within psychiatric disorders in serum or urine samples in humans, however, few studies have investigated this differentiation in brain or cerebral fluid samples in psychiatric disorders. As brain samples from humans are only available at autopsy, animal models are commonly applied to determine the pathogenesis of psychiatric diseases and to test treatment strategies. The aim of this review is to summarize studies on biomarkers in animal models for psychiatric disorders. For depression, anxiety and addiction disorders studies, biomarkers in animal brains are available. Furthermore, several studies have investigated psychiatric medication, e.g., antipsychotics, antidepressants, or mood stabilizers, in animals. The most notable changes in biomarkers in depressed animal models were related to the glutamate-γ-aminobutyric acid-glutamine-cycle. In anxiety models, alterations in amino acid and energy metabolism (i.e., mitochondrial regulation) were observed. Addicted animals showed several biomarkers according to the induced drugs. In summary, animal models provide some direct insights into the cellular metabolites that are produced during psychiatric processes. In addition, the influence on biomarkers due to short- or long-term medication is a noticeable finding. Further studies should combine representative animal models and human studies on cerebral fluid to improve insight into mental disorders and advance the development of novel treatment strategies.

scholarly journals Using the Strengths and Difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample

2000 ◽  
Vol 177 (6) ◽  
pp. 534-539 ◽  
Author(s):  
Robert Goodman ◽  
Tamsin Ford ◽  
Helen Simmons ◽  
Rebecca Gatward ◽  
Howart Meltzer
Keyword(s):  
Psychiatric Disorders ◽  
Separation Anxiety ◽  
Community Sample ◽  
Strengths And Difficulties Questionnaire ◽  
Psychiatric Diagnoses ◽  
Older Children ◽  
Community Screening ◽  
Child Psychiatric ◽  
Specific Phobias ◽  
Strengths And Difficulties

BackgroundChild psychiatric disorders are common and treatable, but often go undetected and therefore remain untreated.AimsTo assess the Strengths and Difficulties Questionnaire (SDQ) as a potential means for improving the detection of child psychiatric disorders in the community.MethodSDQ predictions and independent psychiatric diagnoses were compared in a community sample of 7984 5- to 15-year-olds from the 1999 British Child Mental Health Survey.ResultsMulti-informant (parents, teachers, older children) SDQs identified individuals with a psychiatric diagnosis with a specificity of 94.6% (95% CI 94.1–95.1%) and a sensitivity of 63.3% (59.7–66.9%). The questionnaires identified over 70% of individuals with conduct, hyperactivity, depressive and some anxiety disorders, but under 50% of individuals with specific phobias, separation anxiety and eating disorders. Sensitivity was substantially poorer with single-informant rather than multi-informant SDQs.ConclusionsCommunity screening programmes based on multi-informant SDQs could potentially increase the detection of child psychiatric disorders, thereby improving access to effective treatments.

Sign in / Sign up

Export Citation Format

Share Document