Tag: schizophrenia

  • Antipsychotic use during pregnancy not linked to childhood neurodevelopmental disorders or learning difficulties

    Antipsychotic use during pregnancy not linked to childhood neurodevelopmental disorders or learning difficulties

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    The use of antipsychotics during pregnancy isn’t linked to childhood neurodevelopmental disorders or learning difficulties, UNSW Sydney-led study shows – giving assurance to those concerned about continuing their medications during pregnancy. 

    Antipsychotics – a branch of medication designed to treat schizophrenia and bipolar disorder – are important tools for mental health care management. They work by blocking the effect of dopamine, which can help reduce psychotic symptoms such as hallucinations or delusions. 

    These versatile medications are also widely used for other mental health conditions and developmental disorders, like anxiety, depression, autism spectrum disorder, and insomnia. 

    But many women and pregnant people using these medications may feel concerned about the potential risks they pose to their unborn baby. 

    A new international study led by UNSW Sydney, published today in eClinicalMedicine, tracked the long-term risk of a child developing neurodevelopmental disorders and learning difficulties after being exposed to antipsychotics in the womb. 

    The findings show there’s little to no increased risk of the exposure leading to intellectual disability, poor academic performance in maths and language, or learning, speech and language disorders. 

    The findings are really reassuring for both women managing these psychiatric conditions during pregnancy and their providers.”


    Dr. Claudia Bruno, pharmacoepidemiologist at UNSW’s School of Population Health and lead author of the study

    “There’s no increased risk when taking the medication during pregnancy, not only for the specific neurodevelopmental disorders that we looked at, but also ADHD and autism as shown in our team’s previous studies.” 

    This research is the most comprehensive study on antipsychotics and neurodevelopmental outcomes to date: it pulls together nationwide data from Denmark, Finland, Iceland, Norway, and Sweden into a large sample size of 213,302 children born to mothers with a diagnosed psychiatric condition, 5.5 per cent (11,626) of which were prenatally exposed to antipsychotics. 

    These five Nordic countries all have similar health and education systems and keep detailed data on birth records, filled prescriptions, and diagnoses from inpatient and outpatient specialist care, as well as antenatal care. The researchers teamed these data with results from the children’s first standardised national school test (similar to Australia’s NAPLAN tests), which happens between the ages of 8-10. 

    “It’s reassuring that everything points to the same ‘no major indication’ of increased risks overall,” says Scientia Associate Professor Helga Zoega, senior author of the study and pharmacoepidemiologist, also based at UNSW’s School of Population Health. 

    “The study builds on our team’s previous work that looked at birth outcomes, including serious congenital malformations, where we’ve seen similar null results. 

    “I think it’s important to get excited about null results because this is essential information for the management of serious mental health conditions in pregnancy. It’s as equally important as finding an increased risk of outcomes.” 

    A gap that big health data is trying to fix 

    While this study is part of a growing body of research about medication safety in pregnancy, there’s still a lot left in this field to discover, says A/Prof. Zoega. 

    “This is a hugely understudied area,” she says. “Unfortunately, we know way too little about medication safety during pregnancy.” 

    One of the reasons so little is known about medicines and pregnancy is that it’s simply not feasible – or in many cases, ethical – to conduct randomised clinical trials on pregnant women. The potential risks of testing or withholding treatment to the unborn child and mother or pregnant person is often too great. 

    That’s where harnessing big data can step in – although the research isn’t as simple as looking at the raw data alone. 

    For example, women treated with antipsychotics during pregnancy were more likely to smoke, have higher BMIs, lower education levels, to be older (35 years or more) and use other medications during pregnancy compared to women who didn’t take antipsychotics during pregnancy – all of which are risk factors that can potentially impact birth outcomes. 

    These circumstances – called ‘confounding factors’ – are accounted for in observational research using careful study design and complex adjusted risk models to make sure the results show the impact of the medication alone. 

    “These types of studies are methodologically tricky, and can take a long time to do,” says A/Prof. Zoega. “This study has been in the making for almost 10 years now. 

    “We already know these women are dealing with psychiatric conditions, and by genetic default, their children would be more likely to have psychiatric or neurodevelopmental outcomes. But we’re focused on the risks and benefits of the medication treatment in pregnancy, so we use methods to make the comparison groups as similar as possible.” 

    The researchers also strengthened their findings by slicing up the data to take a closer look at whether individual medications, trimesters of exposure, and siblings carried higher risk levels. 

    While one antipsychotic, chlorpromazine, showed potential increased links to language and speech delays, these findings were based on small sample sizes of 8-15 children, so more research is needed to investigate this potential link. 

    Other than this anomaly, the results supported the finding that there was little to no increased risk of children prenatally exposed to antipsychotics developing neurodevelopmental disorders or learning difficulties. 

    Looking ahead 

    Dr Bruno is currently involved in two related studies on prenatal medication use and pregnancy outcomes. One explores if there is a relationship between the use of antiseizure medications during pregnancy and child school performance, and the other examines whether taking ADHD medication use and discontinuation during pregnancy on child health outcomes. 

    But she sees many avenues for future research to build on this work, including harnessing more Australian big health data. 

    “There’s so much to learn about medication safety in pregnancy,” says Dr Bruno. “These women are typically excluded from clinical trials, so there’s a real lack of data or evidence. 

    “While these results are highly generalisable to women in Australia, we now have real-world linked Australian data that can start contributing to large-scale international studies like this one which we’re very excited for.” 

    A/Prof. Zoega co-leads an international research collaboration called International Pregnancy Drug Safety Study (InPreSS), which investigates the safety of medication in pregnancy. She says there’s plenty to do in this space. 

    “Antipsychotics are only one class of medications, and we already know that up to 80 per cent of women use at least one prescription medicine during pregnancy. Most often, there’s little or no guidance on safety. 

    “There are so many unanswered questions that there’s enough for a lifetime of research.” 

    Source:

    Journal reference:

    Bruno, C., et al. (2024) Antipsychotic use during pregnancy and risk of specific neurodevelopmental disorders and learning difficulties in children: a multinational cohort study. eClinicalMedicine. doi.org/10.1016/j.eclinm.2024.102531.

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  • Non-invasive brain stimulation can change specific brain mechanism linked to human behavior

    Non-invasive brain stimulation can change specific brain mechanism linked to human behavior

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    For the first time, researchers at the University of Minnesota Twin Cities showed that non-invasive brain stimulation can change a specific brain mechanism that is directly related to human behavior. This is a major step forward for discovering new therapies to treat brain disorders such as schizophrenia, depression, Alzheimer’s disease, and Parkinson’s disease.

    The study was recently published in Nature Communications, a peer-reviewed, open access, scientific journal. 

    Researchers used what is called “transcranial alternating current stimulation” to modulate brain activity. This technique is also known as neuromodulation. By applying a small electrical current to the brain, the timing of when brain cells are active is shifted. This modulation of neural timing is related to neuroplasticity, which is a change in the connections between brain cells that is needed for human behavior, learning, and cognition. 

    Previous research showed that brain activity was time-locked to stimulation. What we found in this new study is that this relationship slowly changed and the brain adapted over time as we added in external stimulation. This showed brain activity shifting in a way we didn’t expect.” 


    Alexander Opitz, Associate Professor, Department of Biomedical Engineering, University of Minnesota

    This result is called “neural phase precession.” This is when the brain activity gradually changes over time in relation to a repeating pattern, like an external event or in this case non-invasive stimulation. In this research, all three investigated methods (computational models, humans, and animals) showed that the external stimulation could shift brain activity over time.

    “The timing of this repeating pattern has a direct impact on brain processes, for example, how we navigate space, learn, and remember,” Opitz said.

    The discovery of this new technique shows how the brain adapts to external stimulation. This technique can increase or decrease brain activity, but is most powerful when it targets specific brain functions that affect behaviors. This way, long-term memory as well as learning can be improved. The long-term goal is to use this technique in the treatment of psychiatric and neurological disorders.

    Opitz hopes that this discovery will help bring improved knowledge and technology to clinical applications, which could lead to more personalized therapies for schizophrenia, depression, Alzheimer’s disease, and Parkinson’s disease.

    In addition to Opitz, the research team included co-first authors Miles Wischnewski and Harry Tran. Other team members from the University of Minnesota Biomedical Engineering Department include Zhihe Zhao, Zachary Haigh, Nipun Perera, Ivan Alekseichuk, Sina Shirinpour and Jonna Rotteveel. This study was in collaboration with Dr. Jan Zimmermann, associate professor in the University of Minnesota Medical School.

    This work was supported primarily by the National Institute of Health (NIH) along with the Behavior and Brain Research Foundation and the University of Minnesota’s Minnesota’s Discovery, Research, and InnoVation Economy (MnDRIVE) Initiative. Computational resources were provided by the Minnesota Supercomputing Institute (MSI).

    Source:

    Journal reference:

    Wischnewski, M., et al. (2024). Induced neural phase precession through exogenous electric fields. Nature Communications. doi.org/10.1038/s41467-024-45898-5.

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  • Cardiovascular health variances in women’s lifespan

    Cardiovascular health variances in women’s lifespan

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    Women’s cardiovascular disease risks and outcomes differ throughout the lifespan from those of men, according to a collection of studies devoted to cardiovascular medicine research focused on women of all ages, published today in a special “spotlight” issue of the Journal of the American Heart Association, an open access, peer-reviewed journal of the American Heart Association.

    Cardiovascular disease kills more women than all forms of cancer combined. Among females 20 years and older, nearly 45% are living with some form of cardiovascular disease, and less than 50% of women entering pregnancy in the U.S. have good heart health. In addition, more than half of deaths from high blood pressure are in women. Yet, women make up only 38% of participants in cardiovascular disease clinical trials, according to the American Heart Association.

    The special Go Red for Women issue of the Journal, in recognition of American Heart Month, features studies that reveal insights such as: how diet may affect the high preeclampsia risk in pregnant Hispanic/Latina women; how women were less likely than men to receive bystander CPR and automated external defibrillator (AED) treatment, as well as survive the first 30 days post-hospitalization after out-of-hospital cardiac arrest; and how rehospitalization rates differ in women with heart failure and obstructive sleep apnea. In yet another study featured, researchers report that while the incidence of intracerebral hemorrhage (bleeding within the brain), the second most common stroke type, was lower in women, women were more likely to die one year after a stroke than men.

    Below are highlights of some of the manuscripts in this issue,

    • Prospective Associations of Accelerometer-measured Machine-learned Sedentary Behavior with Mortality among Older Women: The OPACH Study

    Steve Nguyen, Ph.D., et al.; University of California, San Diego, La Jolla, California

    This team studied sedentary behavior patterns in nearly 6,000 older women (average age 79 years) to determine the impact of sitting time on death from cardiovascular disease and all causes. Using a measurement tool powered by machine learning to accurately classify sitting time, researchers found those who sat more than 11.6 total hours a day and had longer bouts of uninterrupted sitting had a 57% higher risk of death from all causes and a 78% increased risk of death from cardiovascular disease. This was compared to women who sat less than 9.3 hours a day. The increased risk of death was consistent regardless of age, body mass index, physical functioning, cardiovascular disease risk factors, physical activity intensity and race/ethnicity. Reducing overall sedentary behavior and uninterrupted sitting time would likely have large public health benefits in an aging society, according to researchers.

    • Sex Differences in the Relationship between Schizophrenia and the Development of Cardiovascular Disease

    Hidehiro Kaneko, M.D., Ph.D., et al.; University of Tokyo, Tokyo, Japan

    Researchers studied cardiovascular disease risk in people with schizophrenia, a serious psychotic disorder and one of the top 15 leading causes of disability worldwide. Schizophrenia results in severe, chronic mental illness characterized by disturbances in perception, thought and behavior. The study found a strong association between schizophrenia and risk of developing cardiovascular disease in adults, but particularly in women. This higher risk in women may be related to hormonal changes during pregnancy and menopause, or reports that women are more sedentary than men. Nevertheless, the findings point to the need for health care professionals to take a thorough and gender-focused approach to cardiovascular disease prevention due to the notable role schizophrenia seems to play in cardiovascular disease. The researchers suggest that it’s crucial to promote physical activity, especially among women with schizophrenia, as inactivity may have increased the risk in female participants in this study. Healthcare providers should routinely screen and treat schizophrenia as part of standard clinical practice, with special attention to women, authors wrote.

    • Maternal Dietary Patterns During Pregnancy Are Linked to Hypertensive Disorders of Pregnancy Among a Predominantly Low-Income US Hispanic/Latina Pregnancy Cohort

    Luis E. Maldonado, Ph.D., M.P.H., et al.; Keck School of Medicine, University of Southern California

    In a study of more than 400 predominantly low-income, pregnant Hispanic/Latina women in Los Angeles, researchers found that a diet characterized by higher intakes of solid fats, refined grains and cheese was strongly associated with greater odds of having had a hypertensive disorder of pregnancy including preeclampsia during pregnancy.

    Other papers in the spotlight issue include:

    • Association of Sex With Cardiovascular Outcomes in Heart Failure Patients With Obstructive or Central Sleep Apnea -; Jian Zhang, M.D., Ph.D., et al.; Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
    • Pregnancy History at 40 Years of Age as a Marker of Cardiovascular Risk -; Liv G. Kvalvik, M.D., Ph.D., et al.; University of Bergen, Bergen, Norway
    • Sex Differences in the Epidemiology of Intracerebral Hemorrhage Over 10 Years in a Population-Based Stroke Registry -; Simona Sacco, M.D., et al.; University of L’Aquila, L’Aquila, Italy
    • Sex Differences in Revascularization, Treatment Goals, and Outcomes of Patients With Chronic Coronary Disease: Insights From the ISCHEMIA Trial -; Harmony R. Reynolds, M.D., FAHA, et al.; NYU Grossman School of Medicine, New York City
    • Sex Differences in Receipt of Bystander CPR Considering Neighborhood Racial and Ethnic Composition -; Audrey L. Blewer, Ph.D., M.P.H., et al.; Duke University, Durham, North Carolina
    • Hypertension in Pregnancy among Immigrant and Swedish Women – A Cohort Study of All Pregnant Women in Sweden -; Axel C. Carlsson, Ph.D., et al.; Karolinska Institutet, Huddinge, Sweden
    • Sex Differences In Out-of-Hospital Cardiac Arrest Survival Trends -; R. L. A. Smits, et al.; Amsterdam University Medical Center, Amsterdam, The Netherlands;
    • Posttraumatic Stress Disorder is Associated With Elevated Risk of Incident Stroke and Transient Ischemic Attack in Women Veterans -; Ramin Ebrahimi, M.D., et al.; University of California, Los Angeles; Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles; and
    • Sex differences in Outcomes of Acute Myocardial Injury After Stroke -; Michela Rosso, M.D., et al.; University of Pennsylvania, Philadelphia.

    Source:

    Journal reference:

    Mujahid, M. S. & Peterson, P. N., (2024) JAHA Go Red for Women Spotlight on Women and Cardiovascular Disease and Stroke. Journal of the American Heart Association. doi.org/10.1161/JAHA.124.035104.

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  • IU researchers develop a breakthrough new blood test for schizophrenia

    IU researchers develop a breakthrough new blood test for schizophrenia

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    A team of researchers led by Indiana University School of Medicine faculty have developed a breakthrough new blood test for schizophrenia, a psychiatric disorder that includes hallucinations and delusions.

    Schizophrenia and related psychotic disorders affect over 3 million people in the United States. The new test identifies biomarkers in a person’s blood that can objectively measure their current severity and future risk for schizophrenia and match them to treatments that will be most effective for their individual biology.

    “Schizophrenia is hard to diagnose, especially early on, and matching people to the right treatment from the beginning is very important,” said Alexander Niculescu, MD, PhD, Professor of Psychiatry and Medical Neuroscience at the IU School of Medicine, staff psychiatrist and investigator at the Richard L. Roudebush Veterans Administration Medical Center in Indianapolis and senior author on the study. “Psychosis usually manifests in young adulthood -; a prime period of life. Stress and drugs, including marijuana, are precipitating factors on a background of genetic vulnerability. If left unchecked, psychosis leads to accumulating biological damage, social damage and psychological damage.”

    In a study published in the high impact Nature Publishing Group journal Molecular Psychiatry, researchers tested psychiatric patients that they followed for over a decade. They identified biomarkers that were predictive of high hallucinations and high delusions states, as well as future psychiatric hospitalizations related to hallucinations and delusions. They also studied which biomarkers are targets of existing drugs, which enables matching of patients to the right treatments.

    The work builds on previous research over the last two decades by Niculescu and his colleagues on blood biomarkers for other psychiatric disorders (mood disorders, anxiety, post-traumatic stress disorder, suicidality risk, pain and memory disorders).Niculescu said in general, the best biomarkers were more predictive than the standard scales used to evaluate someone with hallucinations or delusions, which means the use of this biomarker test can help reduce subjectivity and uncertainty from psychiatric assessments.

    Fortunately, biologically some of the existing medications work quite well if initiated early in the right patients. Social support is also paramount, and once that and medications are in place, psychological support and therapy can help as well. There is still plenty left to understand and apply about cognition and its abnormalities, but there is reason for optimism in this era of emerging precision psychiatry.”


    Alexander Niculescu, MD, PhD, Professor of Psychiatry and Medical Neuroscience at the IU School of Medicine

    Other study authors include M.D. Hill; Sumanpreet Singh Gill; Helen Le-Niculescu, PhD; O. MacKie; Rowan Bhagar; Kyle Roseberry, MD; Olivia Kay Murray; H.D. Dainton; S. K. Wolf; and Anantha Shekhar, MD, PhD of IU School of Medicine; and Sunil Kurian of the Scripps Research.

    The test is anticipated to be available later this year from the IU spin-out company MindX Sciences. For more information about precision psychiatry and blood testing, visit the MindX Sciences website.

    Source:

    Journal reference:

    Hill, M. D., et al. (2024). Precision medicine for psychotic disorders: objective assessment, risk prediction, and pharmacogenomics. Molecular Psychiatry. doi.org/10.1038/s41380-024-02433-8.

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  • Machine learning tool reads brain scans for early signs of psychosis

    Machine learning tool reads brain scans for early signs of psychosis

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    The onset of psychosis can be predicted before it occurs, using a machine-learning tool which can classify MRI brain scans into those who are healthy and those at risk of a psychotic episode. An international consortium including researchers from the University of Tokyo, used the classifier to compare scans from over 2,000 people from 21 global locations. About half of the participants had been identified as being clinically at high risk of developing psychosis. Using training data, the classifier was 85% accurate at differentiating between people who were not at risk and those who later experienced overt psychotic symptoms. Using new data, it was 73% accurate. This tool could be helpful in future clinical settings, as while most people who experience psychosis make a full recovery, earlier intervention typically leads to better outcomes with less negative impact on people’s lives.

    Anyone might experience a psychotic episode, which commonly involves delusions, hallucinations or disorganized thinking. There is no single cause, but it can be triggered by illness or injury, trauma, drug or alcohol use, medication, or a genetic predisposition. Although it can be scary or unsettling, psychosis is treatable and most people recover. As the most common age for a first episode is during adolescence or early adulthood, when the brain and body are undergoing a lot of change, it can be difficult to identify young people in need of help. 

    At most only 30% of clinical high-risk individuals later have overt psychotic symptoms, while the remaining 70% do not. Therefore, clinicians need help to identify those who will go on to have psychotic symptoms using not only subclinical signs, such as changes in thinking, behavior and emotions, but also some biological markers.”

    Shinsuke Koike, Associate Professor, Graduate School of Arts and Sciences, University of Tokyo

    The consortium of researchers have worked together to create a machine-learning tool which uses brain MRI scans to identify people at risk of psychosis before it starts. Previous studies using brain MRI have suggested that structural differences occur in the brain after the onset of psychosis. However, this is reportedly the first time that differences in the brains of those who are at very high risk but have not yet experienced psychosis have been identified.

    The team from 21 different institutions in 15 different countries gathered a large and diverse group of adolescent and young adult participants. According to Koike, MRI research into psychotic disorders can be challenging because variations in brain development and in MRI machines make it difficult to get very accurate, comparable results. Also, with young people, it can be difficult to differentiate between changes that are taking place because of typical development and those due to mental illness. 

    “Different MRI models have different parameters which also influence the results,” explained Koike. “Just like with cameras, varied instruments and shooting specifications create different images of the same scene, in this case the participant’s brain. However, we were able to correct for these differences and create a classifier which is well tuned to predicting psychosis onset.”

    The participants were divided into three groups of people at clinical high risk: those who later developed psychosis; those who didn’t develop psychosis; and people with uncertain follow-up status (1,165 people in total for all three groups), and a fourth group of healthy controls for comparison (1,029 people). Using the scans, the researchers trained a machine-learning algorithm to identify patterns in the brain anatomy of the participants. From these four groups, the researchers used the algorithm to classify participants into two main groups of interest: healthy controls and those at high risk who later developed overt psychotic symptoms.

    In training, the tool was 85% accurate at classifying the results, while in the final test using new data it was 73% accurate at predicting which participants were at high risk of psychosis onset. Based on the results, the team considers that providing brain MRI scans for people identified as being at clinically high risk may be helpful for predicting future psychosis onset. 

    “We still have to test whether the classifier will work well for new sets of data. Since some of the software we used is best for a fixed data set, we need to build a classifier that can robustly classify MRIs from new sites and machines, a challenge which a national brain science project in Japan, called Brain/MINDS Beyond, is now taking on,” said Koike. “If we can do this successfully, we can create more robust classifiers for new data sets, which can then be applied to real-life and routine clinical settings.”

    Source:

    Journal reference:

    Zhu, Y., et al. (2024). Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk. Molecular Psychiatry. doi.org/10.1038/s41380-024-02426-7.

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  • Pioneering repository aims to raise visibility and awareness about people with mental illnesses

    Pioneering repository aims to raise visibility and awareness about people with mental illnesses

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    Metaphors are not just literary devices for writers to embellish their texts. They are linguistic tools used in everyday life, in most cases with the aim of better understanding and conveying the reality of the world around us. Researchers at the Universitat Oberta de Catalunya (UOC) have developed the first Mental Health Metaphor Dictionary, a pioneering repository that brings together and exemplifies the most important conceptual metaphors used in Spanish by people with serious mental illnesses, mainly schizophrenia, bipolar disorder, depression and obsessive-compulsive disorder. The repository is based on first-person accounts of what it is like to live with a particular mental disorder and can be useful for mental health communicators and professionals, relatives of people diagnosed with one of these illnesses and even for the people with these disorders themselves.

    According to Marta Coll-Florit and Salvador Climent Roca, researchers from the Linguistic Applications Interuniversity Research Group (GRIAL) of the Faculty of Arts and Humanities, who coordinated the development and creation of the repository, “this is a tool to raise visibility and awareness in society about the suffering of people with mental illnesses. We believe that this dictionary can help us all to reflect on the way we talk about mental health and to realize the power of our words.”

    Metaphors are not neutral

    The dictionary is one of the results of the MOMENT project, which seeks to identify the metaphors used in the field of mental health and the underlying conceptualizations. The researchers said: “The metaphors we use are not neutral, but have the power to highlight certain aspects of reality while potentially obscuring others. They’re likely to reveal latent ideas that don’t come out explicitly in our discourse, but may be filtered through figurative language. For example, it’s not the same to say ‘you have to fight your illness’ as it is to say ‘you have to live with your illness’: the first metaphor emphasizes the struggle between the person and the disorder, whereas the second emphasizes the person’s acceptance of their situation.”

    One of the project’s main research conclusions is that this type of metaphor can have beneficial or harmful uses in public discourse and in the discourse of those affected and those who interact with them. “Beneficial uses are those that convey empowerment, control or positive emotions; in other cases, they look to present a problem by separating the negative aspects from the situation as a whole,” they explained. Metaphors that serve these purposes are called “empowering metaphors” and are recommended for use “in public discourse and in relationships with people diagnosed with mental disorders”. The researchers added that “their use should be encouraged by the people with these disorders themselves in order to avoid pejorative views of their situation”.

    A window into the feelings of people with mental disorders

    The dictionary is organized both alphabetically and thematically into three broad areas: metaphors of living with a mental disorder, metaphors of communication and social context, and metaphors of medicine and professional practice. All the metaphors are grouped around different key concepts and come with several examples. As the researchers explained, by systematizing and exemplifying the metaphors used by these people, we can gain a deeper insight into what they “really think and experience”. It is also a way for them to feel “more understood and less alone, realizing that their feelings and experiences are shared by more people.”

    The advantages of blogs and social media

    One of the key features of the repository is that all the metaphors are taken from texts posted in Spanish on blogs or on X (formerly Twitter). These communication channels have an important advantage over other written media. “The authors’ words are not filtered by an external interviewer, but come from a genuine and spontaneous willingness to share a lived experience on social media. In addition, individuals can use the relative anonymity of the internet to reveal things they would not, for example, discuss in a face-to-face research setting. For this reason, the range of metaphors found is much wider than in previous similar studies.”

    This approach has been useful in collecting the many metaphors in the repository that criticize the medical profession or highlight the suffering caused by social stigma and discrimination, showing “how patients seek greater empathy and understanding of their suffering from both medical staff and the wider community”. In this regard, the researchers stressed that the dictionary can be valuable in promoting “more respectful discourse” on mental health by public institutions and the press.

    A tool for detecting psychopathology

    Finally, the Mental Health Metaphor Dictionary can be used as a gateway to detecting psychopathology. “Knowing which conceptual metaphors are most commonly used to express mental distress could help families or people close to those affected to identify possible disorders,” the researchers explained. Likewise, although it cannot be used directly as a diagnostic tool, it could be used to “identify which stage of the disorder the patient is in, according to the type of metaphors used, or to analyze whether therapy has been successful”.

    A pioneering initiative

    This collection of metaphors is the first of its kind. While there are a number of domain-independent repositories of conceptual metaphors based on English texts, there are very few domain-specific repositories in other languages. In fact, in a review carried out by the UOC researchers, they found only two repositories focused on specific subject areas: cognition and health. “Although these subject repositories are potentially the most useful for society, they are the rarest,” they concluded.

    Source:

    Journal reference:

    Coll-Florit, M., & Climent, S. (2023). Metaphor repositories: the case of the mental health metaphor dictionary. Digital Scholarship in the Humanities. doi.org/10.1093/llc/fqad058.

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