Personalized Treatment and Management of Psychiatric Disorders

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Personalized Therapy and Drug Delivery".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 7943

Special Issue Editors

Department of Psychiatry, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
Interests: psychophysiology; brain stimulation; gene polymorphisms; schizophrenia; affective disorders, anxiety disorders
Department of Psychiatry, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
Interests: psychophysiology; brain stimulation; gene polymorphisms; schizophrenia; affective disorders, anxiety disorders
Department of Radiology, College of Medicine, Institute for Bio-Medical Convergence, Incheon St. Mary’s Hospital, The Catholic University of Korea Director, Seoul 21431, Korea
Interests: nuclear medicine; brain stimulation; transcranial focused ultrasound stimulation; mild cognitive impairment; Alzheimer's disease; depression

Special Issue Information

Dear Colleagues,

Personalized treatment and management of psychiatric disorders, unlike traditional approaches that have been based on a single clinical characteristic, represents a new era of personalized psychiatry tailored to the individual patient’s unique neurobiological, molecular, genetic, epigenetic, neurophysiological, neuroimaging, immunological, oxidative, metabolic, hormonal aspects and clinical characteristics to specify a therapeutic approach to avoid the practice of trial-and-error prescriptions, minimizing adverse effects, maximizing effectiveness, improving clinical outcomes, and reducing the cost of both clinical trials and mental health care in general. It has the potential to transform the psychiatric landscape and revolutionize mental health care. Many breakthroughs in technologies and informatics have been drivers in the advance of this field. Due to limitations in research, this field remains in its early phase. This Special Issue of the Journal of Personalized Medicine aims to embody the current scientific knowledge and the state-of-the-art research findings focusing on, but not limited to, the field of personalized treatment and management of psychiatric disorders. We welcome research papers, clinical trials, and reviews addressing factors that contribute to the scientific advances in this field.

Prof. Dr. Hsin-An Chang
Prof. Dr. Chuan-Chia Chang
Prof. Dr. Yong-An Chung
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • personalized treatment
  • psychiatric disorders
  • personalized medicine
  • stratified medicine
  • mental health

Published Papers (5 papers)

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Research

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12 pages, 289 KiB  
Article
Examination of the Relationship between Peripheral Inflammation Markers and Impulsivity and Aggression in Schizophrenia Patients Involved and Not Involved in Crime
by Suheda Kaya, Gülay Taşcı, Nülüfer Kılıç, Hüsna Karadayı, Filiz Özsoy and Murad Atmaca
J. Pers. Med. 2023, 13(3), 475; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm13030475 - 06 Mar 2023
Cited by 1 | Viewed by 1257
Abstract
Aim: The aim of this study was to examine the relationship between peripheral inflammatory markers and aggression and impulsivity in schizophrenia patients with and without criminal histories. Materials and Methods: The study was conducted with patients with schizophrenia involved in crimes and hospitalized [...] Read more.
Aim: The aim of this study was to examine the relationship between peripheral inflammatory markers and aggression and impulsivity in schizophrenia patients with and without criminal histories. Materials and Methods: The study was conducted with patients with schizophrenia involved in crimes and hospitalized in the Forensic Psychiatry ward of Elazığ Fethi Sekin City Hospital and patients with schizophrenia not involved in crimes and hospitalized in the psychiatry ward of Elazığ Mental Health and Diseases Hospital. All participants completed the Buss–Waren Aggression Scale (BWAS), the Barratt Impulsiveness Scale-11 (BIS-11), and the Positive and Negative Symptom Scale (PANSS). Before treatment, venous blood samples were taken for laboratory measurements on the first day of hospitalization. Results: All participants were male. The mean age of those involved in a crime was 39 ± 9.7 years, while the mean age of those not involved in a crime was 41.2 ± 10.7 years. The PANSS all subscale and total scores of the patients with schizophrenia who were involved in a crime were significantly higher than the group who were not involved (p values were p < 0.001, p = 0.001, p = 0.043, p = 0.001, respectively). The BWAS—physical aggression (p = 0.007) and total scores of the scale (p = 0.046) and BIS-11—inability to plan (p = 0.002) scores of the group involved in a crime were higher than the group not involved. As for laboratory parameters, MCH, MCHC, PDW, eosinophils, basophils, RDW-CV, and RDW-SD values were significantly higher in those involved in crime, while MPV, creatinine, albumin, and LDH values were lower. CRP and CRP/albumin values were significantly higher, while neutrophil/albumin values were significantly lower in those who committed murder in the first degree than those who committed other crimes. Conclusion: Based on our results, we found that inflammatory agents were significantly increased in forensic schizophrenia patients with high aggression scores. Significant correlations between some inflammatory factors and impulsivity and aggression scores and differences in these factors according to crime types showed that these factors might be related to violence and criminal behavior. There is a need for further large-scale studies on this subject at different stages of the disease. Full article
(This article belongs to the Special Issue Personalized Treatment and Management of Psychiatric Disorders)
14 pages, 13594 KiB  
Article
High-Frequency Transcranial Random Noise Stimulation Modulates Gamma-Band EEG Source-Based Large-Scale Functional Network Connectivity in Patients with Schizophrenia: A Randomized, Double-Blind, Sham-Controlled Clinical Trial
by Ta-Chuan Yeh, Cathy Chia-Yu Huang, Yong-An Chung, Jooyeon Jamie Im, Yen-Yue Lin, Chin-Chao Ma, Nian-Sheng Tzeng and Hsin-An Chang
J. Pers. Med. 2022, 12(10), 1617; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm12101617 - 30 Sep 2022
Cited by 3 | Viewed by 1521
Abstract
Schizophrenia is associated with increased resting-state large-scale functional network connectivity in the gamma frequency. High-frequency transcranial random noise stimulation (hf-tRNS) modulates gamma-band endogenous neural oscillations in healthy individuals through the application of low-amplitude electrical noises. Yet, it is unclear if hf-tRNS can modulate [...] Read more.
Schizophrenia is associated with increased resting-state large-scale functional network connectivity in the gamma frequency. High-frequency transcranial random noise stimulation (hf-tRNS) modulates gamma-band endogenous neural oscillations in healthy individuals through the application of low-amplitude electrical noises. Yet, it is unclear if hf-tRNS can modulate gamma-band functional connectivity in patients with schizophrenia. We performed a randomized, double-blind, sham-controlled clinical trial to contrast hf-tRNS (N = 17) and sham stimulation (N = 18) for treating negative symptoms in 35 schizophrenia patients. Short continuous currents without neuromodulatory effects were applied in the sham group to mimic real-stimulation sensations. We used electroencephalography to investigate if a five-day, twice-daily hf-tRNS protocol modulates gamma-band (33–45 Hz) functional network connectivity in schizophrenia. Exact low resolution electromagnetic tomography (eLORETA) was used to compute intra-cortical activity from regions within the default mode network (DMN) and fronto-parietal network (FPN), and functional connectivity was computed using lagged phase synchronization. We found that hf-tRNS reduced gamma-band within-DMN and within-FPN connectivity at the end of stimulation relative to sham stimulation. A trend was obtained between the change in within-FPN functional connectivity from baseline to the end of stimulation and the improvement of negative symptoms at the one-month follow-up (r = −0.49, p = 0.055). Together, our findings suggest that hf-tRNS has potential as a network-level approach to modulate large-scale functional network connectivity pertaining to negative symptoms of schizophrenia. Full article
(This article belongs to the Special Issue Personalized Treatment and Management of Psychiatric Disorders)
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12 pages, 1557 KiB  
Article
Using Boosted Machine Learning to Predict Suicidal Ideation by Socioeconomic Status among Adolescents
by Hwanjin Park and Kounseok Lee
J. Pers. Med. 2022, 12(9), 1357; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm12091357 - 24 Aug 2022
Viewed by 1156
Abstract
(1) Background: This study aimed to use machine learning techniques to identify risk factors for suicidal ideation among adolescents and understand the association between these risk factors and socioeconomic status (SES); (2) Methods: Data from 54,948 participants were analyzed. Risk factors were identified [...] Read more.
(1) Background: This study aimed to use machine learning techniques to identify risk factors for suicidal ideation among adolescents and understand the association between these risk factors and socioeconomic status (SES); (2) Methods: Data from 54,948 participants were analyzed. Risk factors were identified by dividing groups by suicidal ideation and 3 SES levels. The influence of risk factors was confirmed using the synthetic minority over-sampling technique and XGBoost; (3) Results: Adolescents with suicidal thoughts experienced more sadness, higher stress levels, less happiness, and higher anxiety than those without. In the high SES group, academic achievement was a major risk factor for suicidal ideation; in the low SES group, only emotional factors such as stress and anxiety significantly contributed to suicidal ideation; (4) Conclusions: SES plays an important role in the mental health of adolescents. Improvements in SES in adolescence may resolve their negative emotions and reduce the risk of suicide. Full article
(This article belongs to the Special Issue Personalized Treatment and Management of Psychiatric Disorders)
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13 pages, 844 KiB  
Article
A Network Analysis of Depressive Symptoms in the Elderly with Subjective Memory Complaints
by Sunhae Kim and Kounseok Lee
J. Pers. Med. 2022, 12(5), 821; https://doi.org/10.3390/jpm12050821 - 18 May 2022
Cited by 3 | Viewed by 1789
Abstract
(1) Background: Subjective memory complaints (SMCs) are common among the elderly and are important because they can indicate early cognitive impairment. The factor with the greatest correlation with SMCs is depression. The purpose of this study is to examine depressive symptoms among elderly [...] Read more.
(1) Background: Subjective memory complaints (SMCs) are common among the elderly and are important because they can indicate early cognitive impairment. The factor with the greatest correlation with SMCs is depression. The purpose of this study is to examine depressive symptoms among elderly individuals with SMCs through a network analysis that can analyze disease models between symptoms; (2) Methods: A total of 3489 data collected from elderly individuals in the community were analyzed. The Subjective Memory Complaints Questionnaire and Patient Health Questionnaire-9 were evaluated. For statistical analysis, we investigated the features of the depressive symptoms network, including centrality and clustering; (3) Results: Network analysis of the SMC group showed strong associations in the order of Q1–Q2 (r = 0.499), Q7–Q8 (r = 0.330), and Q1–Q6 (r = 0.239). In terms of centrality index, Q2 was highest in strength and expected influence, followed by Q1 in all of betweenness, strength, and expected influence; (4) Conclusions: The network analysis confirmed that the most important factors in the subjective cognitive decline group were depressed mood and anhedonia, which also had a strong correlation in the network pattern. Full article
(This article belongs to the Special Issue Personalized Treatment and Management of Psychiatric Disorders)
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Review

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17 pages, 2553 KiB  
Review
Mathematical Model of Interaction of Therapist and Patients with Bipolar Disorder: A Systematic Literature Review
by Indah Nursuprianah, Nursanti Anggriani, Nuning Nuraini and Yudi Rosandi
J. Pers. Med. 2022, 12(9), 1469; https://0-doi-org.brum.beds.ac.uk/10.3390/jpm12091469 - 07 Sep 2022
Viewed by 1636
Abstract
Mood swings in patients with bipolar disorder (BD) are difficult to control and can lead to self-harm and suicide. The interaction between the therapist and BD will determine the success of therapy. The interaction model between the therapist and BD begins by reviewing [...] Read more.
Mood swings in patients with bipolar disorder (BD) are difficult to control and can lead to self-harm and suicide. The interaction between the therapist and BD will determine the success of therapy. The interaction model between the therapist and BD begins by reviewing the models that were previously developed using the Systematic Literature Review and Bibliometric methods. The limit of articles used was sourced from the Science Direct, Google Scholar, and Dimensions databases from 2009 to 2022. The results obtained were 67 articles out of a total of 382 articles, which were then re-selected. The results of the selection of the last articles reviewed were 52 articles. Using VOSviewer version 1.6.16, a visualization of the relationship between the quotes “model”, “therapy”, “emotions”, and “bipolar disorder” can be seen. This study also discusses the types of therapy that can be used by BD, as well as treatment innovations and the mathematical model of the therapy itself. The results of this study are expected to help further researchers to develop an interaction model between therapists and BD to improve the quality of life of BD. Full article
(This article belongs to the Special Issue Personalized Treatment and Management of Psychiatric Disorders)
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