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Non-suicidal self-injury (NSSI) and suicidal behavior can be viewed as two dimensions of self-harming behavior which differentiate in intention, frequency and mortality. In this review, we present different theoretical models which explain the link between NSSI and suicidal behavior. Furthermore, we review empirical findings regarding NSSI as a risk factor of suicidal behavior. The review indicates that NSSI is a strong and unique predictor of suicidal behavior and that NSSI is a better predictor of suicidal behavior than suicide ideation. Paradoxically, NSSI also seems to protect against later suicide behavior. Identification of self-injuring people at risk of later suicide may contribute to existing prevention interventions. According to the integrated model by Hamza and colleagues, perceived burdensomeness, thwarted belongingness and acquired capacity to hurt one-self may influence whether NSSI leads to suicide. However, existing studies have reported mixed findings which is why more longitudinal studies of the integrated model are needed

Fra selvskade til selvmord

Non-suicidal self-injury (NSSI) and suicidal behavior can be viewed as two dimensions of self-harming behavior which differentiate in intention, frequency and mortality. In this review, we present different theoretical models which explain the link between NSSI and suicidal behavior. Furthermore, we review empirical findings regarding NSSI as a risk factor of suicidal behavior. The review indicates that NSSI is a strong and unique predictor of suicidal behavior and that NSSI is a better predictor of suicidal behavior than suicide ideation. Paradoxically, NSSI also seems to protect against later suicide behavior. Identification of self-injuring people at risk of later suicide may contribute to existing prevention interventions. According to the integrated model by Hamza and colleagues, perceived burdensomeness, thwarted belongingness and acquired capacity to hurt one-self may influence whether NSSI leads to suicide. However, existing studies have reported mixed findings which is why more longitudinal studies of the integrated model are needed

Investigating centrality in PTSD symptoms across diagnostic systems using network analysis*

Background: The posttraumatic stress disorder (PTSD) diagnosis has been widely debated since it was introduced into the diagnostic nomenclature four decades ago. Recently, the debate has focused on consequences of having two different descriptions of PTSD: 20 symptoms belonging to four symptom clusters in the Diagnostic and Statistical Manual of Mental Disorders 5th edition (DSM-5), and three symptoms clusters in the 11th edition of the International Classification of Diseases (ICD-11) most often operationalized by six symptoms in the International Trauma Questionnaire (ITQ) (2017) and Hansen, Hyland, Armour, Shevlin, & Elklit (). Research has provided support for both models of PTSD, but at the same time indicates differences in estimated prevalence rates of PTSD (Hansen et al., , ). A growing body of research has modelled PTSD both theoretically and statistically as a network of interacting symptoms (Birkeland, Greene, & Spiller, ), yet it remains more unclear how the two diagnostic systems perform regarding which symptoms are more central/interconnected. Objectives and methods: We estimated two 23-item Gaussian Graphical Models to investigate whether ICD-11 or DSM-5 PTSD symptoms are more central in two trauma-exposed samples: a community sample (N = 2,367) and a military veteran sample (N = 657). PTSD DSM-5 was measured with the PTSD checklist-5 (PCL-5) and the PTSD ICD-11 was measure by the ITQ PTSD subscale. Results: Five of the six most central symptoms estimated via the expected influence centrality metric across the two samples were identical and represented symptoms from both diagnostic systems operationalized by the PCL-5 and the ITQ. Conclusions: The results of the present study underline that symptoms from both diagnostic systems hold central positions. The implications of the results are discussed from the perspectives of an indexical (i.e. the diagnostic systems reflect both shared and different aspects of PTSD) and a constitutive view (i.e., the diagnostic systems represent different disorders and the results cannot be reconciled per se) of mental health diagnoses (Kendler, )

Trends in incidence of hospitalization for hypoglycemia and diabetic ketoacidosis in individuals with type 1 or type 2 diabetes with and without severe mental illness, in Denmark from 1996-2020:A nationwide study

OBJECTIVETo examine trends in incidence of acute diabetes complications in individuals with type 1 or type 2 diabetes with and without severe mental illness (SMI) in Denmark by age and calendar year.RESEARCH DESIGN AND METHODSWe conducted a cohort study using nationwide registers from 1996-2020 to identify individuals with diabetes, ascertain SMI status (schizophrenia, bipolar disorder, or major depression) and identify the outcomes, hospitalization for hypoglycemia and diabetic ketoacidosis (DKA). We used Poisson regression to estimate incidence rates (IRs) and incidence rate ratios (IRRs) of recurrent hypoglycemia and DKA events by SMI, age, calendar year, accounting for sex, diabetes duration, education, and country of origin.RESULTSAmongst 433,609 individuals with diabetes, 9% had SMI. Risk of (first and subsequent) hypoglycemia events was higher in individuals with SMI versus without SMI (IRR for first hypoglycemia event: type 1 diabetes: 1.77 [95% CI, 1.56-2.00], type 2 diabetes: 1.64 [95% CI, 1.56-1.74]). Individuals with schizophrenia were particularly at risk of recurrent hypoglycemia events. Risk of first DKA event was higher in individuals with SMI (IRR of first DKA event: type 1 diabetes: 1.78 [95% CI. 1.50-2.11], type 2 diabetes: 1.85 [95% CI. 1.64-2.09]). Except for DKA in the type 2 diabetes group, incidence rate differences between individuals with and without SMI were highest in younger individuals (&lt;50 years) but stable across calendar year. CONCLUSIONSSMI is an important risk factor for acute diabetes complication and effective prevention is needed in this population, especially among the younger population and those with schizophrenia.<br/

The role of mental disorders in precision medicine for diabetes: a narrative review

This narrative review aims to examine the value of addressing mental disorders as part of the care of people with type 1 and type 2 diabetes in terms of four components of precision medicine. First, we review the empirical literature on the role of common mental disorders in the development and outcomes of diabetes (precision prevention and prognostics). We then review interventions that can address mental disorders in individuals with diabetes or at risk of diabetes (precision treatment) and highlight recent studies that have used novel methods to individualise interventions, in person and through applications, based on mental disorders. Additionally, we discuss the use of detailed assessment of mental disorders using, for example, mobile health technologies (precision monitoring). Finally, we discuss future directions in research and practice and challenges to addressing mental disorders as a factor in precision medicine for diabetes. This review shows that several mental disorders are associated with a higher risk of type 2 diabetes and its complications, while there is suggestive evidence indicating that treating some mental disorders could contribute to the prevention of diabetes and improve diabetes outcomes. Using technologically enabled solutions to identify mental disorders could help individuals who stand to benefit from particular treatments. However, there are considerable gaps in knowledge and several challenges to be met before we can stratify treatment recommendations based on mental disorders. Overall, this review demonstrates that addressing mental disorders as a facet of precision medicine could have considerable value for routine diabetes care and has the potential to improve diabetes outcomes

Psychiatric disorders as risk factors for type 2 diabetes : An umbrella review of systematic reviews with and without meta-analyses

Having a psychiatric disorder may increase the risk of developing type 2 diabetes[T2D] and this umbrella review aims to determine whether people with a psychiatric disorder have an increased risk of developing T2D and to investigate potential underlying mechanisms. A literature search was performed to identify systematic reviews of longitudinal studies investigating different psychiatric disorders as risk factors for incident T2D in humans (>18 years). A total of 8612 abstracts were identified, 180 full-text articles were read, and 25 systematic reviews were included. Six categories of psychiatric disorders were identified. Except for eating disorders, all psychiatric disorders were associated with increased risk of incident T2D ranging from RR = 1.18 [95% CI 1.12-1.24] to RR = 1.60 [95% CI 1.37-1.88] for depression; from RR = 1.27 [95% CI 1.19-1.35] to OR = 1.50 [95% CI 1.08-2.10] for use of antidepressant medication; from OR = 1.93 [1.37-2.73] to OR = 1.94 [1.34-2.80] for use of antipsychotic medication; from RR = 1.55 [95% CI 1.21-1.99] to RR = 1.74 [95% CI 1.30- 2.34] for insomnia, and finally showed OR = 1.47 [95% CI 1.23-1.75] for anxiety disorders. Plausible underlying mechanisms were discussed, but in most reviews corrections for mechanisms did not explain the association. Notable, only 16% of the systematic reviews had a high methodological quality. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Trait Anger, Hostility, and the Risk of Type 2 Diabetes and Diabetes- Related Complications: A Systematic Review of Longitudinal Studies

BACKGROUND: Research suggests associations between trait anger, hostility, and type 2 diabetes and diabetes-related complications, though evidence from longitudinal studies has not yet been synthesized. OBJECTIVE: The present systematic review examined findings from longitudinal research on trait anger or hostility and the risk of incident type 2 diabetes or diabetes-related complications. The review protocol was pre-registered in PROSPERO (CRD42020216356). METHODS: Electronic databases (MEDLINE, PsychINFO, Web of Science, and CINAHL) were searched for articles and abstracts published up to December 15, 2020. Peer-reviewed longitudinal studies with adult samples, with effect estimates reported for trait anger/hostility and incident diabetes or diabetes-related complications, were included. Title and abstract screening, full-text screening, data extraction, and quality assessment using the Newcastle-Ottawa Scale were conducted by two independent reviewers. A narrative synthesis of the extracted data was conducted according to the Synthesis Without Meta-Analysis guidelines. RESULTS: Five studies (N = 155,146 participants) met the inclusion criteria. While results were mixed, our synthesis suggested an overall positive association between high trait-anger/hostility and an increased risk of incident diabetes. Only one study met the criteria for the diabetes-related complications outcome, which demonstrated a positive association between hostility and incident coronary heart disease but no significant association between hostility and incident stroke. CONCLUSION: Based on the available longitudinal evidence, trait anger and hostility are associated with an increased risk of diabetes. Longitudinal studies are needed to investigate the association between trait-anger or hostility and the risk of diabetes-related complications