Sophie I Elliott, Rachel B Katz, Robert B Ostroff, Mina Ansari, Sophie E Holmes, Gerard Sanacora
{"title":"Ketamine Versus Electroconvulsive Therapy for the Treatment of Depression: A Guide for Clinicians.","authors":"Sophie I Elliott, Rachel B Katz, Robert B Ostroff, Mina Ansari, Sophie E Holmes, Gerard Sanacora","doi":"10.1176/appi.focus.20240040","DOIUrl":"https://doi.org/10.1176/appi.focus.20240040","url":null,"abstract":"<p><p>The effective treatment of major depressive disorder remains one of the biggest public health challenges globally. For moderate to severe cases, pharmacotherapy often falls short, leading to treatment-resistant depression. Electroconvulsive therapy (ECT) has generally been considered the gold standard for severe cases of treatment-resistant depression. However, emerging evidence suggests that ketamine may serve as a promising alternative. Two relatively large noninferiority trials and three meta-analyses support the efficacy of both treatments but report contradictory findings regarding superiority. The authors discuss possible reasons underlying these discrepant findings, including variations in patient selection criteria, study outcome measures, treatment delivery, and site experience. Additionally, the authors examine the unique risk and benefit profiles of each treatment, highlighting patient-specific considerations. By evaluating the most recent evidence for the efficacy of ketamine versus ECT alongside key patient-specific factors, the authors aimed to guide clinicians in recommending the optimal treatment choice for each patient.</p>","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"195-205"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Melissa G Guineau, N Ikani, M Rinck, R M Collard, P van Eijndhoven, I Tendolkar, A H Schene, E S Becker, J N Vrijsen
{"title":"Anhedonia as a Transdiagnostic Symptom Across Psychological Disorders: A Network Approach.","authors":"Melissa G Guineau, N Ikani, M Rinck, R M Collard, P van Eijndhoven, I Tendolkar, A H Schene, E S Becker, J N Vrijsen","doi":"10.1176/appi.focus.25023012","DOIUrl":"https://doi.org/10.1176/appi.focus.25023012","url":null,"abstract":"<p><strong>Background: </strong>Anhedonia is apparent in different mental disorders and is suggested to be related to dysfunctions in the reward system and/or affect regulation. It may hence be a common underlying feature associated with symptom severity of mental disorders.</p><p><strong>Methods: </strong>We constructed a cross-sectional graphical Least Absolute Shrinkage and Selection Operator (LASSO) network and a relative importance network to estimate the relationships between anhedonia severity and the severity of symptom clusters of major depressive disorder (MDD), anxiety sensitivity (AS), attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD) in a sample of Dutch adult psychiatric patients (<i>N</i> = 557).</p><p><strong>Results: </strong>Both these networks revealed anhedonia severity and depression symptom severity as central to the network. Results suggest that anhedonia severity may be predictive of the severity of symptom clusters of MDD, AS, ADHD, and ASD. MDD symptom severity may be predictive of AS and ADHD symptom severity.</p><p><strong>Conclusions: </strong>The results suggest that anhedonia may serve as a common underlying transdiagnostic psychopathology feature, predictive of the severity of symptom clusters of depression, AS, ADHD, and ASD. Thus, anhedonia may be associated with the high comorbidity between these symptom clusters and disorders. If our results will be replicated in future studies, it is recommended for clinicians to be more vigilant about screening for anhedonia and/or depression severity in individuals diagnosed with an anxiety disorder, ADHD and/or ASD.Appeared originally in <i>Psychol Med 2023; 53:3908-3919</i>.</p>","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"257-269"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antonio L Teixeira, Allison Gregg, Melanie T Gentry, Swathi Gujral, Ellie Rapp, Lauren Oberlin, Olusola Ajilore, Sara Weisenbach, Regan Patrick
{"title":"Cognitive Deficits in Late-Life Depression: From Symptoms and Assessment to Therapeutics.","authors":"Antonio L Teixeira, Allison Gregg, Melanie T Gentry, Swathi Gujral, Ellie Rapp, Lauren Oberlin, Olusola Ajilore, Sara Weisenbach, Regan Patrick","doi":"10.1176/appi.focus.20240046","DOIUrl":"https://doi.org/10.1176/appi.focus.20240046","url":null,"abstract":"<p><p>Cognitive symptoms and deficits are core features of late-life depression (LLD), with an estimated 20%-50% of affected individuals meeting diagnostic criteria for mild cognitive impairment (MCI). Cognitive deficits, especially executive dysfunction, have consistently been associated with poorer treatment outcomes among people with LLD. Furthermore, distinguishing depression with cognitive complaints or cognitive impairment from the early stages of Alzheimer's disease (AD) can be challenging. Cognitive concerns are often emphasized among those with LLD, although, paradoxically, their description of memory difficulty may include detailed recall of specific memory lapses. Conversely, people with AD often have limited insight into their progressive cognitive decline, minimizing and concealing their cognitive difficulties. Neuropsychological assessment is one of the most useful means of clarifying this differential diagnosis. A subcortical cognitive pattern is commonly observed among people with LLD, including psychomotor slowing, variable attention, and executive dysfunction, which can affect memory encoding and free recall. A broad range of therapeutic approaches have been applied to older adults experiencing LLD along with cognitive symptoms, MCI, or dementia. Most studies focus on treatments to address LLD or MCI, with relatively fewer examining treatments specifically at this intersection. Nonpharmacological strategies, including aerobic exercise, cognitive remediation, and neuromodulation, are highly recommended to improve both depression and cognition. Antidepressants may have benefits for elements of cognition among people with LLD, but they have less evidence for their efficacy for people with cognitive deficits and dementia. This review provides an updated conceptual and practical framework for clinicians evaluating and treating LLD.</p>","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"183-194"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jorge A Sanchez-Ruiz, Jason Straub, Peter P Zandi, Olusola Ajilore, Brandon J Coombes, Stephen M Strakowski, Mark A Frye, Monica J Taylor-Desir
{"title":"Symptom Severity and Treatment Needs Among Racial Groups Seeking Treatment at a Mood Outcomes Program.","authors":"Jorge A Sanchez-Ruiz, Jason Straub, Peter P Zandi, Olusola Ajilore, Brandon J Coombes, Stephen M Strakowski, Mark A Frye, Monica J Taylor-Desir","doi":"10.1176/appi.focus.20240051","DOIUrl":"https://doi.org/10.1176/appi.focus.20240051","url":null,"abstract":"<p><p>Mood disorders are highly prevalent. Despite increased rates of treatment provision, treatment gaps are sustained by inadequate targeting of interventions and little emphasis on prevention. Here, the authors present an overview and analysis of the National Network of Depression Centers (NNDC) Mood Outcomes Program, which is both a measurement-based care program, with a standardized set of mood \"vital signs\" assessed as part of routine clinical care, and a learning health system. The authors analyzed all data collected since the program's inception in 2015 to assess whether baseline symptom severity, prior suicidal ideation or attempts, length of care, and longitudinal symptom severity differed across sociodemographic groups. The results show important treatment needs that are not being fulfilled. Most notably, the groups with the greatest symptom severity were not the groups with the most visits. Efforts to address systemic barriers that prevent access to mental health care are required. Given that the NNDC Mood Outcomes Program is integrated with clinical care, academic programs, and research at each site, the authors anticipate that the program is well suited to support efforts to dismantle systemic barriers to care.</p>","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"156-162"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ethical and Legal Aspects of Evaluating and Treating Mood Disorders.","authors":"Jacob M Appel","doi":"10.1176/appi.focus.20240041","DOIUrl":"https://doi.org/10.1176/appi.focus.20240041","url":null,"abstract":"","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"208-211"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995900/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrienne Grzenda, Nina V Kraguljac, William M McDonald, Charles Nemeroff, John Torous, Jonathan E Alpert, Carolyn I Rodriguez, Alik S Widge
{"title":"Evaluating the Machine Learning Literature: A Primer and User's Guide for Psychiatrists.","authors":"Adrienne Grzenda, Nina V Kraguljac, William M McDonald, Charles Nemeroff, John Torous, Jonathan E Alpert, Carolyn I Rodriguez, Alik S Widge","doi":"10.1176/appi.focus.25023011","DOIUrl":"https://doi.org/10.1176/appi.focus.25023011","url":null,"abstract":"","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"270-284"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995911/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144054356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marie E Gaine, Kathleen M Jagodnik, Ritika Baweja, William V Bobo, Erin C McGlade, Sandra J Weiss, Marissa L Beal, Sharon Dekel, Aysegul Ozerdem
{"title":"Targeted Research and Treatment Implications in Women With Depression.","authors":"Marie E Gaine, Kathleen M Jagodnik, Ritika Baweja, William V Bobo, Erin C McGlade, Sandra J Weiss, Marissa L Beal, Sharon Dekel, Aysegul Ozerdem","doi":"10.1176/appi.focus.20240052","DOIUrl":"https://doi.org/10.1176/appi.focus.20240052","url":null,"abstract":"<p><p>Women with a history of traumatic experience, particularly adversity encountered during childhood, have an increased risk of developing depression. The authors review the biological mechanisms associating trauma with depression, including the role of the hypothalamic-pituitary-adrenal axis. Additionally, the psychosocial and cultural considerations associating traumatic experience with depression are discussed, and current gaps in knowledge about biological mechanisms, psychosocial factors, and cultural aspects relating trauma to depression that remain to be addressed are described. Women with a history of trauma are also at increased risk for engaging in suicidal behaviors, including suicidal ideation and attempts. Increased suicidality in women with a history of trauma has been observed in various populations, including among victims of intimate partner violence, female veterans, refugees, and individuals who identify as lesbian, gay, bisexual, transgender, queer or questioning, or other. Although associations between trauma and suicidality have been well documented, limited research has examined the impact of age or reproductive stage, an important area for future research. A wide range of biological, psychosocial, and cultural factors that can increase the risk for suicidality across the lifespan in women are described, and how they may be included when completing clinical assessments for women is highlighted. Machine learning, and its use in risk and outcome prediction of depression in women across reproductive stages toward individualized psychiatric services, is introduced, with future directions reviewed.</p>","PeriodicalId":73036,"journal":{"name":"Focus (American Psychiatric Publishing)","volume":"23 2","pages":"141-155"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11995897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144031875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}