Author Interviews, Medical Research Journals, Mental Health Research / 24.03.2026
Behind the Paywall: Undisclosed Conflicts of Interest in Leading Psychiatry Journals
[caption id="attachment_72893" align="alignleft" width="200"] Francis J. Gesel[/caption]
MedicalResearch.com Interview with:
Francis J. Gesel
Geisinger Commonwealth School of Medicine
Scranton, Pennsylvania
MedicalResearch.com: What is the background for this study?
Response: Conflicts of interest (COIs) in psychiatric research represent a longstanding ethical challenge, given the close relationship between the pharmaceutical industry and psychiatry. Journals require authors to disclose these relationships, while the U.S. Open Payments database, created under the Sunshine Act, provides a record of payments from manufacturers to physicians. However, whether physician-authors in psychiatry’s most influential journals consistently disclose these relationships had not been systematically assessed. We focused on the American Journal of Psychiatry (AJP) and JAMA Psychiatry (JAMA-PSY), two of the highest-impact journals in the field, to evaluate the prevalence and magnitude of undisclosed financial COIs.
Francis J. Gesel[/caption]
MedicalResearch.com Interview with:
Francis J. Gesel
Geisinger Commonwealth School of Medicine
Scranton, Pennsylvania
MedicalResearch.com: What is the background for this study?
Response: Conflicts of interest (COIs) in psychiatric research represent a longstanding ethical challenge, given the close relationship between the pharmaceutical industry and psychiatry. Journals require authors to disclose these relationships, while the U.S. Open Payments database, created under the Sunshine Act, provides a record of payments from manufacturers to physicians. However, whether physician-authors in psychiatry’s most influential journals consistently disclose these relationships had not been systematically assessed. We focused on the American Journal of Psychiatry (AJP) and JAMA Psychiatry (JAMA-PSY), two of the highest-impact journals in the field, to evaluate the prevalence and magnitude of undisclosed financial COIs.
In recent years, the field of psychiatric care has undergone a revolutionary transformation. This is because of groundbreaking research that has redefined our understanding of mental health and treatment methodologies.
From innovative therapies to advanced diagnostic tools, transformative research has played a pivotal role in reshaping the landscape of psychiatric care.
In this article, we will explore the key contributions that researchers have made in this field. We will also talk about how their work is influencing the way mental health is approached and treated.
Dr. Etkin[/caption]
Amit Etkin, MD, PhD
Department of Psychiatry and Behavioral Sciences
Wu Tsai Neurosciences Institute, Stanford Universitu
Stanford, CA
MedicalResearch.com: What is the mission of Cohen Veterans Bioscience - CVB?
Response: Cohen Veterans Bioscience (CVB) is a non-profit 501(c)(3) research biotech dedicated to fast-tracking the development of diagnostic tests and personalized therapeutics for the millions of Veterans and civilians who suffer the devastating effects of trauma-related and other brain disorders.
MedicalResearch.com: How can patients with PTSD or MDD benefit from this information?
Response: With the discovery of this new brain imaging biomarker, patients who suffer from PTSD or MDD may be guided towards the most effective treatment without waiting months and months to find a treatment that may work for them.
MedicalResearch.com: What is the background for this study?
Response: This study, which was supported with a grant from Cohen Veterans Bioscience, grants from the National Institute of Mental Health (NIMH and other supporters, derives from our work over the past few years which has pointed to the critical importance of understanding how patients with a variety of psychiatric disorders differ biologically. The shortcomings of our current diagnostic system have become very clear over the past 1-2 decades, but the availability of tools for transcending these limitations on the back of objective biological tests has not kept pace with the need for those tools.
In prior work, we have used a variety of methods, including different types of brain imaging, to identify brain signals that underpin key biological differences within and across traditional psychiatric diagnoses. We have also developed specialized AI tools for decoding complex patterns of brain activity in order to understand and quantify biological heterogeneity in individual patients. These developments have then, in turn, converged with the completion of a number of large brain imaging-coupled clinical trials, which have provided a scale of these types of data not previously available in the field.
Dr. Kuan-Pin Su[/caption]
Kuan-Pin Su, MD, PhD
China Medical University
Taichung, Taiwan
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: Delirium, also known as acute confusional state, is a serious disturbance in mental abilities that results in confused thinking and reduced awareness of the environment. Delirium can often be traced to one or more contributing factors, such as a severe or chronic illness, changes in metabolic balance (such as low sodium), medication, infection, surgery, or alcohol or drug intoxication or withdrawal. It’s critically important to identify and treat delirium because some of the contributing factors could be life-threatening. However, there is no sufficient evidence for choice of medication to treat or prevent the symptoms of delirium.
A recent paper, Association of Delirium Response and Safety of Pharmacological Interventions for the Management and Prevention of Delirium A Network Meta-analysis, published in JAMA Psychiatry provides important findings of this missing piece in that important clinical uncertainty. The leading author, Professor Kuan-Pin Su, at the China Medical University in Taichung, Taiwan, concludes the main finding about treatment/prevention of delirium: “In this report, we found that the combination of haloperidol and lorazepam demonstrated the best option for treatment of delirium, while ramelteon for prevention against delirium. 
Dr. Nicole Karcher, PhD
Post-doctoral scholar with the NIMH Training in Clinical Sciences fellowship
Department of Psychiatry
Washington University School of Medicine
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: For over fifteen years, researchers have debated the role that cannabis use plays in the development of both psychotic disorders as well as subthreshold psychotic symptoms, such as psychotic-like experiences (PLEs). There is still a lack of consensus regarding the nature of the association between cannabis use and psychosis risk, with some research finding evidence for genetic overlap, while other research finds evidence for potentially causal pathways.
The current study examined data from twins and siblings from two different samples, the U.S.-based Human Connectome Project and the Australian Twin Registry, with a total of 4,674 participants. Overall, psychotic-like experiences were associated with three separate cannabis use variables [frequent (≥100 times) use, a Cannabis Use Disorder diagnosis, and current cannabis use]. Furthermore, the current research found evidence for both shared genetic and individual-specific contributions to the association between PLEs and these three cannabis use variables. More specifically, while the association between cannabis use and psychotic-like experiences was largely attributable to shared genetic factors, cannabis users were more likely to endorse PLEs in comparison to the relative who used cannabis less. 
![MedicalResearch.com Interview with: Dr. Theodore Satterthwaite MD Assistant professor in the department of Psychiatry, and Cedric Xia, a MD-PhD candidate Perelman School of Medicine at the University of Pennsylvania MedicalResearch.com: What is the background for this study? What are the main findings? Response: Unlike other branches of modern medicine, psychiatry still solely replies on patient reports and physician observations for clinical decision-making. Without biologically-based tests, the diagnostic categories for mental health do not carve nature at its joint. This is evident in the high levels of co-morbidity across disorders and heterogeneity within disorders. Through this research, we studied a large sample of adolescents who completed MRI-based functional imaging, and used recently-developed machine learning techniques to uncover specific abnormalities that are highly predictive of a wide variety of psychiatric symptoms. Essentially, we tried to find brain patterns that were predictive of different types of psychiatric symptoms. We discovered four such brain-guided dimensions of psychopathology: mood, psychosis, fear, and disruptive behavior. While each of these dimensions exhibits a unique pattern of brain connectivity, a common feature of brain anomaly is shared across the dimensions. Notably, in all linked dimensions, the default mode network and fronto-parietal network, two brain regions that usually become increasingly distinct as the brain matures, were abnormally connected. This loss of normal brain network segregation supports the hypothesis that many psychiatric illnesses may be disorders of brain development. MedicalResearch.com: What should readers take away from your report? Response: This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories. By moving away from clinical labels developed decades ago, we can begin to let the biology speak for itself. Our ultimate hope is that understanding the biology of mental illnesses will allow us to develop better treatments for our patients. MedicalResearch.com: What recommendations do you have for future research as a result of this work? Response: This study demonstrates the importance of incorporating vast amounts of biological data to study mental illness across clinical diagnostic boundaries. Moving forward, we hope to integrate genomic data in order to describe pathways from genes to brain to symptoms, which could ultimately be the basis for novel treatments for mental illness. MedicalResearch.com: Is there anything else you would like to add? Response: Future breakthroughs in brain science to understand mental illness requires large amount of data. While the current study takes advantage of one of the largest samples of youth, the size (n=999) remains dwarfed by the complexity of the brain. The neuroscience community is actively working towards collecting higher quality data in even larger samples, so we can validate and build upon the findings. Citation: Cedric Huchuan Xia, Zongming Ma, Rastko Ciric, Shi Gu, Richard F. Betzel, Antonia N. Kaczkurkin, Monica E. Calkins, Philip A. Cook, Angel García de la Garza, Simon N. Vandekar, Zaixu Cui, Tyler M. Moore, David R. Roalf, Kosha Ruparel, Daniel H. Wolf, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, Danielle S. Bassett, Theodore D. Satterthwaite. Linked dimensions of psychopathology and connectivity in functional brain networks. Nature Communications, 2018; 9 (1) DOI: 10.1038/s41467-018-05317-y [wysija_form id="3"] [last-modified] The information on MedicalResearch.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.](https://medicalresearch.com/wp-content/uploads/Cross-clinical-diagnostic-categories.jpg)
![MedicalResearch.com Interview with: Dr. Theodore Satterthwaite MD Assistant professor in the department of Psychiatry, and Cedric Xia, a MD-PhD candidate Perelman School of Medicine at the University of Pennsylvania MedicalResearch.com: What is the background for this study? What are the main findings? Response: Unlike other branches of modern medicine, psychiatry still solely replies on patient reports and physician observations for clinical decision-making. Without biologically-based tests, the diagnostic categories for mental health do not carve nature at its joint. This is evident in the high levels of co-morbidity across disorders and heterogeneity within disorders. Through this research, we studied a large sample of adolescents who completed MRI-based functional imaging, and used recently-developed machine learning techniques to uncover specific abnormalities that are highly predictive of a wide variety of psychiatric symptoms. Essentially, we tried to find brain patterns that were predictive of different types of psychiatric symptoms. We discovered four such brain-guided dimensions of psychopathology: mood, psychosis, fear, and disruptive behavior. While each of these dimensions exhibits a unique pattern of brain connectivity, a common feature of brain anomaly is shared across the dimensions. Notably, in all linked dimensions, the default mode network and fronto-parietal network, two brain regions that usually become increasingly distinct as the brain matures, were abnormally connected. This loss of normal brain network segregation supports the hypothesis that many psychiatric illnesses may be disorders of brain development. MedicalResearch.com: What should readers take away from your report? Response: This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories. By moving away from clinical labels developed decades ago, we can begin to let the biology speak for itself. Our ultimate hope is that understanding the biology of mental illnesses will allow us to develop better treatments for our patients. MedicalResearch.com: What recommendations do you have for future research as a result of this work? Response: This study demonstrates the importance of incorporating vast amounts of biological data to study mental illness across clinical diagnostic boundaries. Moving forward, we hope to integrate genomic data in order to describe pathways from genes to brain to symptoms, which could ultimately be the basis for novel treatments for mental illness. MedicalResearch.com: Is there anything else you would like to add? Response: Future breakthroughs in brain science to understand mental illness requires large amount of data. While the current study takes advantage of one of the largest samples of youth, the size (n=999) remains dwarfed by the complexity of the brain. The neuroscience community is actively working towards collecting higher quality data in even larger samples, so we can validate and build upon the findings. Citation: Cedric Huchuan Xia, Zongming Ma, Rastko Ciric, Shi Gu, Richard F. Betzel, Antonia N. Kaczkurkin, Monica E. Calkins, Philip A. Cook, Angel García de la Garza, Simon N. Vandekar, Zaixu Cui, Tyler M. Moore, David R. Roalf, Kosha Ruparel, Daniel H. Wolf, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, Danielle S. Bassett, Theodore D. Satterthwaite. Linked dimensions of psychopathology and connectivity in functional brain networks. Nature Communications, 2018; 9 (1) DOI: 10.1038/s41467-018-05317-y [wysija_form id="3"] [last-modified] The information on MedicalResearch.com is provided for educational purposes only, and is in no way intended to diagnose, cure, or treat any medical or other condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. In addition to all other limitations and disclaimers in this agreement, service provider and its third party providers disclaim any liability or loss in connection with the content provided on this website.](https://medicalresearch.com/wp-content/uploads/Cross-clinical-diagnostic-categories-200x180.jpg)
![“Man’s best friend helps NC Guardsman with PTSD [Image 1 of 8]” by DVIDSHUB is licensed under CC BY 2.0](https://medicalresearch.com/wp-content/uploads/ptsd.jpg)
Josephine Mollon[/caption]
MedicalResearch.com Interview with:
Josephine Mollon MSc
Department of Psychosis Studies
Institute of Psychiatry, Psychology, and Neuroscience
King’s College London
London, England
Medical Research: What is the background for this study? What are the main findings?
Dr. Mollon: Psychotic symptoms, such as hallucinations and delusions, are core features of psychotic disorders. A significant minority of the general population also reports subclinical psychotic experiences. Evidence suggests that these experiences may lie on a continuum with clinically significant psychotic symptoms. For example, cognitive deficits, which are a hallmark of psychotic disorders, are also seen in people with subclinical psychotic experiences. We used population-based survey data to characterize cognitive functioning in adults with psychotic experiences while adjusting for important sociodemographic characteristics and investigating the effect of age.
The 171 (9.7%) adults with psychotic experiences showed significant memory and verbal deficits, but not IQ or processing speed deficits. Only participants 50 years and older with psychotic experiences showed medium to large impairments in general IQ, verbal knowledge, working memory and memory after adjusting for socioeconomic status, cannabis use, and common mental disorders.
