Annals of Clinical Psychiatry最新文献

Background: The objective of our study was to determine lifetime and current e-cigarette use among adult cigarette smokers with schizophrenia or schizoaffective disorder, and to describe characteristics of these e-cigarette users.

Methods: Adult daily tobacco smokers with schizophrenia who were psychiatrically stable in outpatient treatment (n = 162) were enrolled in a motivational intervention study from 2013 to 2015 and followed for 6 months. Approximately 80% (n = 140) completed a 6-month follow-up, including the Population Assessment of Tobacco and Health survey.

Results: Among the 140 participants, 46% (n = 64) reported ever using e-cigarettes and 15% (n = 21) reported current use. Participants were significantly more likely to report ever-use if they were younger (Chi-square = 11.7, P < .01), lesbian/gay/bisexual (LGB) (Chi-square = 4.8, P = .03), or reported recent drug use (Chi-square = 6.5, P = .01). In a multivariate model, only age remained a significant predictor of ever-use (coefficient: 0.03; P = .02). The most common reasons for using e-cigarettes were "helps people quit cigarettes" and "less harmful to me or to people around me than cigarettes." Current e-cigarette users had significantly lower carbon monoxide levels than past e-cigarettes users (T = 2.08, P = .04).

Conclusions: Almost one-half of smokers with schizophrenia or schizoaffective disorder reported ever using e-cigarettes. Interventions for tobacco use among this demographic should incorporate recognition of e-cigarette use, particularly among younger adults, illicit drug users, and LGB individuals.

Background: We wanted to determine the factors that influence geriatric psychiatric hospitalization length of stay (LOS).

Methods: We conducted a retrospective cohort study of a sample of hospital admission records from 2012 to 2018. The hospital records were the geriatric inpatient records of St. John's Hospital, Springfield, Illinois. The data collection was based on the inclusion criteria as approved by the Southern Illinois University School of Medicine Institutional Review Board. To be eligible, participants had to have at least 1 inpatient hospitalization between 2012 and 2017. For the purposes of this study, psychiatric diagnosis was based on DSM-IV criteria.

Results: The 141 participants' average age was 71.7 years, and approximately 57% were female; average length of stay was 16 days (range: 1 to 116 days). Indications for current admission included depression and suicidal ideation (45%), psychosis (30%), psychosis and agitation (22%), and mania (3%). Results indicate that having a major depressive disorder (MDD) diagnosis (vs bipolar disorder and schizophrenia) was significantly associated with shorter LOS (P < .001). Other significant predictors were psychosis (P = .03), using mood stabilizers (P = .02), using antidepressants (P = .05), and use of ≥2 (vs 1 or 0) psychotropic medications (P = .02).

Conclusions: Geriatric psychiatric hospitalization was longer in patients with psychosis, but shorter for patients with MDD. Patients receiving mood stabilizers, as well as those receiving ≥2 psychotropics, had longer LOS, while those receiving antidepressants had shorter LOS. This highlights the idea that patients with serious mental illnesses may have longer LOS.

Background: Mood disorders are a leading cause of morbidity. Many patients experience treatment-resistant depression (TRD), and suicide rates are rising. Faster-acting and more effective antidepressant medications are needed. Four decades of research has transformed the use of ketamine from an anesthetic to an outpatient treatment for major depressive disorder (MDD). Ketamine is a N-methyl-d-aspartate (NMDA) receptor antagonist and has been shown to rapidly improve mood symptoms and suicidal ideation by targeting the glutamate system directly.

Methods: We used the PubMed database to identify relevant articles published until September 1, 2020. We focused on meta-analyses, randomized controlled trials, and original observational studies. We included relevant studies for depression, MDD, TRD, bipolar disorder, anxiety, posttraumatic stress disorder (PTSD), suicide, ketamine, and esketamine.

Results: Both racemic ketamine and esketamine have been shown to rapidly treat depression and suicidality. There is evidence that ketamine can be helpful for anxiety and PTSD; however, more research is needed. Intranasal esketamine has been FDA approved to treat depression.

Conclusions: This narrative review describes the evolution of ketamine to treat mood disorders and suicidality. We provide the evidence supporting recent developments using esketamine as well as unresolved issues in the field, such as dosing and safety.

Background: Mood disorders often are diagnosed by clinical interview, yet many cases are missed or misdiagnosed. Mood disorders increase the risk of suicide, making it imperative to diagnose and treat these disorders quickly. Artificial intelligence (AI) has been investigated for diagnosing mood disorders, but the merits of the literature have not been evaluated. This systematic review aims to understand and explain AI methods and evaluate their use in augmenting clinical diagnosis of mood disorders as well as identifying individuals at increased suicide risk.

Methods: We conducted a systematic literature review of all studies until August 1, 2020 examining the efficacy of different AI techniques for diagnosing mood disorders and identifying individuals at increased suicide risk because of a mood disorder.

Results: Our literature search generated 13 studies (10 of mood disorders and 3 describing suicide risk) where AI techniques were used. Machine learning and artificial neural networks were most commonly used; both showed merit in helping to diagnose mood disorders and assess suicide risk.

Conclusions: The data shows that AI methods have merit in improving the diagnosis of mood disorders as well as identifying suicide risk. More research is needed for bipolar disorder because only 2 studies explored this condition, and it is often misdiagnosed. Although only a few AI techniques are discussed in detail in this review, there are many more that can be employed, and should be evaluated in future studies.

Background: Anxiety disorders in youth are frequently underdiagnosed and untreated, partly due to a lack of screening in primary care. The Generalized Anxiety Disorder 7-item (GAD-7) scale is a brief self-report measure designed to screen for anxiety in primary care settings. However, little is known about the psychometrics of this scale with adolescents.

Methods: Participants included 579 youth age 11 to 17 years who received screening for depression in a primary care setting through a web-based application, VitalSign⁶, over a 4-year period. Psychometric analyses were completed based on classical test theory (CTT) and item response theory (IRT).

Results: Using CTT and IRT methods, the GAD-7 has a unidimensional structure with good psychometric properties. In addition, the IRT analysis demonstrates that items 1 and 2 are strongly associated with the total score, and thus are good choices as a 2-item screening tool. Convergent validity was demonstrated, with high correlations between the GAD-7 and other measures of anxiety, and discriminant validity was also demonstrated, with low correlations to measures of other psychological states.

Conclusions: This psychometric evaluation of the GAD-7 provides support for the utility of this measure with adolescents. The GAD-2 is a good estimate of GAD-7 total score.