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5. A pilot study investigating affective forecasting biases with a novel virtual reality-based paradigm

Author

Loisel-Fleuriot, L. (Louise), Fovet, T. (Thomas), Bugnet, A. (Arnaud), Creupelandt, C. (Coralie), Wathelet, M. (Marielle), Szaffarczyk, S. (Sébastien), Duhem, S. (Stéphane), Vaiva, G. (Guillaume), Horn, M. (Mathilde), D’Hondt, F. (Fabien), Université de Lille, Inserm, CHU Lille, and Lille Neurosciences & Cognition (LilNCog) - U 1172

Abstract

A body of research indicates that people are prone to overestimate the affective impact of future events. Here, we developed a novel experimental paradigm to study these affective forecasting biases under laboratory conditions using subjective (arousal and valence) and autonomic measures (skin conductance responses, SCRs, and heart rate). Thirty participants predicted their emotional responses to 15 unpleasant, 15 neutral, and 15 pleasant scenarios (affective forecasting phase) to which they were then exposed in virtual reality (emotional experience phase). Results showed that participants anticipated more extreme arousal and valence scores than they actually experienced for unpleasant and pleasant scenarios. The emotional experience phase was characterized by classic autonomic patterns, i.e., higher SCRs for emotionally arousing scenarios and greater peak cardiac acceleration for pleasant scenarios. During the affective forecasting phase, we found only a moderate association between arousal scores and SCRs and no valence-dependent modulation of cardiac activity. This paradigm opens up new perspectives for investigating affective forecasting abilities under lab-controlled conditions, notably in psychiatric disorders with anxious anticipations. 13;1

Published
2023

9. Psychiatry in Prisons and Corrections

Author

Fovet, T, Mundt, AP, and Fazel, S

Abstract

Over 11 million people are imprisoned worldwide at any given time. Despite methodological challenges, high levels of psychiatric morbidity in people in prison have been documented in many countries, including low- and middle-income countries. Research has consistently shown high levels of major depression, psychosis, posttraumatic stress disorder, substance use disorders and, to a lesser extent, developmental disorders among individuals in prison. Existing evidence also reported high prevalence rates for the co-occurrence of several mental health and substance use problems. Suicide and self-harm are more common in people in prison than community-based persons of similar age and gender. Women, juveniles, and people in prison aged 55 years and older present with higher rates of many disorders than other persons in prison settings. The prison environment is stressful and people suffering from psychiatric disorders may have difficulties coping with the many stressors of the prison regime (violence, victimization, solitary confinement, etc.). Equivalence of healthcare inside and outside prison, independence from the justice system, respect for confidentiality, and informed consent are core ethical principles of practicing psychiatry in prison settings. Evidence-based best practice should be the goal for the psychiatric treatment (including screening and assessment, medication, and psychotherapy) of incarcerated people. Importantly, the transition from prison to the community is associated with poor outcomes and psychiatry in prison settings is therefore not sufficient without follow-up care after release. Research gaps about the mental health problems of people in prison are outlined.

Published
2023
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20. Prisons confinées : quelles conséquences pour les soins psychiatriques et la santé mentale des personnes détenues en France ?

Author

Fovet, T., primary, Lancelevée, C., additional, Eck, M., additional, Scouflaire, T., additional, Bécache, E., additional, Dandelot, D., additional, Giravalli, P., additional, Guillard, A., additional, Horrach, P., additional, Lacambre, M., additional, Lefebvre, T., additional, Moncany, A.-H., additional, Touitou, D., additional, David, M., additional, and Thomas, P., additional

Published
2020
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26. Facteurs de risque et caractéristiques de la dépression psychotique : résultats d’une étude épidémiologique en population générale française

Author

Benard, V., primary, Pignon, B., additional, Geoffroy, P.A., additional, Benradia, I., additional, Roelandt, J.-L., additional, Rolland, B., additional, Fovet, T., additional, D’Hondt, F., additional, Østergaard, S.D., additional, Thomas, P., additional, Vaiva, G., additional, and Amad, A., additional

Published
2019
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29. EEG neurofeedback research: A fertile ground for psychiatry?

Author

Batail, J.-M., primary, Bioulac, S., additional, Cabestaing, F., additional, Daudet, C., additional, Drapier, D., additional, Fouillen, M., additional, Fovet, T., additional, Hakoun, A., additional, Jardri, R., additional, Jeunet, C., additional, Lotte, F., additional, Maby, E., additional, Mattout, J., additional, Medani, T., additional, Micoulaud-Franchi, J.-A., additional, Mladenovic, J., additional, Perronet, L., additional, Pillette, L., additional, Ros, T., additional, and Vialatte, F., additional

Published
2019
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34. Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity

Author

de Pierrefeu, A., primary, Löfstedt, T., additional, Laidi, C., additional, Hadj‐Selem, F., additional, Bourgin, J., additional, Hajek, T., additional, Spaniel, F., additional, Kolenic, M., additional, Ciuciu, P., additional, Hamdani, N., additional, Leboyer, M., additional, Fovet, T., additional, Jardri, R., additional, Houenou, J., additional, and Duchesnay, E., additional

Published
2018
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38. Neurofeedback: One of today's techniques in psychiatry?

Author

Arns, M.W., Batail, J.M., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., Fovet, T., Jardri, R., Le-Van-Quyen, M., Lotte, F., Mehler, D.M.A., Micoulaud-Franchi, J.A., Purper-Ouakil, D., Vialatte, F., Arns, M.W., Batail, J.M., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., Fovet, T., Jardri, R., Le-Van-Quyen, M., Lotte, F., Mehler, D.M.A., Micoulaud-Franchi, J.A., Purper-Ouakil, D., and Vialatte, F.

Abstract

Item does not contain fulltext, OBJECTIVES: Neurofeedback is a technique that aims to teach a subject to regulate a brain parameter measured by a technical interface to modulate his/her related brain and cognitive activities. However, the use of neurofeedback as a therapeutic tool for psychiatric disorders remains controversial. The aim of this review is to summarize and to comment the level of evidence of electroencephalogram (EEG) neurofeedback and real-time functional magnetic resonance imaging (fMRI) neurofeedback for therapeutic application in psychiatry. METHOD: Literature on neurofeedback and mental disorders but also on brain computer interfaces (BCI) used in the field of neurocognitive science has been considered by the group of expert of the Neurofeedback evaluation & training (NExT) section of the French Association of biological psychiatry and neuropsychopharmacology (AFPBN). RESULTS: Results show a potential efficacy of EEG-neurofeedback in the treatment of attentional-deficit/hyperactivity disorder (ADHD) in children, even if this is still debated. For other mental disorders, there is too limited research to warrant the use of EEG-neurofeedback in clinical practice. Regarding fMRI neurofeedback, the level of evidence remains too weak, for now, to justify clinical use. The literature review highlights various unclear points, such as indications (psychiatric disorders, pathophysiologic rationale), protocols (brain signals targeted, learning characteristics) and techniques (EEG, fMRI, signal processing). CONCLUSION: The field of neurofeedback involves psychiatrists, neurophysiologists and researchers in the field of brain computer interfaces. Future studies should determine the criteria for optimizing neurofeedback sessions. A better understanding of the learning processes underpinning neurofeedback could be a key element to develop the use of this technique in clinical practice.

Published
2017

41. Neurofeedback: One of today's techniques in psychiatry?

Author

Arns, M., primary, Batail, J.-M., additional, Bioulac, S., additional, Congedo, M., additional, Daudet, C., additional, Drapier, D., additional, Fovet, T., additional, Jardri, R., additional, Le-Van-Quyen, M., additional, Lotte, F., additional, Mehler, D., additional, Micoulaud-Franchi, J.-A., additional, Purper-Ouakil, D., additional, and Vialatte, F., additional

Published
2017
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42. Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.

Author

Pierrefeu, A., Löfstedt, T., Laidi, C., Hadj‐Selem, F., Bourgin, J., Hajek, T., Spaniel, F., Kolenic, M., Ciuciu, P., Hamdani, N., Leboyer, M., Fovet, T., Jardri, R., Houenou, J., and Duchesnay, E.

Subjects
SCHIZOPHRENIA, MAGNETIC resonance imaging, PSYCHOSES, MACHINE learning, NEUROANATOMY, NEUROBIOLOGY
Abstract

Objective: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predictive performance of the clinical status in cross‐sectional designs, which has limited biological perspectives. Moreover, most studies depend on relatively small cohorts or single recruiting site. Finally, no study controlled for disease stage or medication's effect. These elements cast doubt on previous findings' reproducibility. Method: We propose a machine learning algorithm that provides an interpretable brain signature. Using large datasets collected from 4 sites (276 schizophrenia patients, 330 controls), we assessed cross‐site prediction reproducibility and associated predictive signature. For the first time, we evaluated the predictive signature regarding medication and illness duration using an independent dataset of first‐episode patients. Results: Machine learning classifiers based on neuroanatomical features yield significant intersite prediction accuracies (72%) together with an excellent predictive signature stability. This signature provides a neural score significantly correlated with symptom severity and the extent of cognitive impairments. Moreover, this signature demonstrates its efficiency on first‐episode psychosis patients (73% accuracy). Conclusion: These results highlight the existence of a common neuroanatomical signature for schizophrenia, shared by a majority of patients even from an early stage of the disorder. [ABSTRACT FROM AUTHOR]

Published
2018
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50. Risk factors of suicide in prisons: a comprehensive retrospective cohort study in France, 2017-2020.

Author

Vanhaesebrouck A, Fovet T, Melchior M, and Lefevre T

Subjects
Humans, France epidemiology, Male, Risk Factors, Female, Adult, Retrospective Studies, Middle Aged, Young Adult, Violence statistics & numerical data, Suicide statistics & numerical data, Suicide trends, Prisons statistics & numerical data, Prisoners statistics & numerical data, Prisoners psychology
Abstract

Purpose: Suicide is a leading cause of death in prison and the suicide rates are several times higher in the prison population than in the general population in most countries. Of the studies that have investigated risk factors for suicide in prison, few have controlled for possible confounding factors. The aim of this study is to identify risk factors of suicide among people in French prisons, over a four-year period., Methods: All incarcerations that occurred in France during 2017-2020 were eligible. Sociodemographic, criminal and prison characteristics were collected for each incarceration from data of the National Prison Service. Survival univariate and multivariate analyses were performed with a Cox regression model., Results: 358,522 incarcerations were included, of which 449 ended in suicide during the follow-up. The median length of prison stay was 5.1 months. The median age at prison entry was 30 years and 95.8% of incarcerations involved men. The overall suicide rate was 173 [157-189] per 100,000 person-years. Factors associated with suicide in the multivariate model (p < 0.05) were the early stage of incarceration and in particular the first week (HR = 7.6 [5.4-10.8]), violent offences and in particular homicide (HR = 3.0 [2.1-4.2]), French (HR = 1.7 [1.2-2.4]) and other European nationalities (HR = 2.1 [1.4-3.3]), age above 40 (HR = 2.0 [1.5-2.6]), pre-trial incarceration (HR = 1.8 [1.4-2.3]), being separated (HR = 1.6 [1.1-2.3] and having a high school diploma (HR = 1.4 [1.0-1.8])., Conclusions: Factors associated with suicide in prison are complex and involve individuals' criminal history as well as conditions of incarceration. These characteristics may be relevant to focus suicide prevention efforts., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Published
2024
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