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New Advances in the Diagnosis and Treatment of Mental Disorders

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A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 8536

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Special Issue Editor

Dr. Diogo Telles-Correia

E-Mail Website
Guest Editor

Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
Interests: psychopharmacology

Special Issue Information

Dear Colleagues,

Mental disorders, as with medical disorders in general, are situations that cause biological harm (death or risk of death) or psychosocial harm (distress and disability) in those who suffer from them, and which can, through tested methods (biological, psychotherapeutic), be improved or even eliminated.

However, there are some specificities in psychiatry in relation to the rest of medicine. These range from its causality models (how neurobiological components and psychosocial variables contribute and interact), to the ways to diagnose it (psychometric instruments and semiology and laboratory correlates) and to the ways to treat it (psychotherapy, psychopharmacology, etc.).

These issues mean that research methods (epistemology) in psychiatry must differ, in some aspects, from those used for the study of medical diseases in general. They have some specificities. Models imported directly from the rest of medicine cannot be replicated, which is mostly based on methods used in only natural sciences.

In recent times, new approaches and paradigms have emerged in research carried out in this area. This research topic intends to include research articles and reviews that include innovative topics related to the diagnosis and treatment of psychiatric disorders.

Dr. Diogo Telles-Correia
Guest Editor

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. Diagnostics is an international peer-reviewed open access semimonthly 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

mental disorders
diagnosis
treatment
translational psychiatry
psychopharmacology, psychopathology

Published Papers (5 papers)

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Research

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24 pages, 1797 KiB

Open AccessArticle

A Novel Method for Assessing Risk-Adjusted Diagnostic Coding Specificity for Depression Using a U.S. Cohort of over One Million Patients

by Alexandra Glass, Nalander C. Melton, Connor Moore, Keyerra Myrick, Kola Thao, Samiat Mogaji, Anna Howell, Kenneth Patton, John Martin, Michael Korvink and Laura H. Gunn

Diagnostics 2024, 14(4), 426; https://doi.org/10.3390/diagnostics14040426 - 15 Feb 2024

Cited by 1 | Viewed by 652

Abstract

Depression is a prevalent and debilitating mental health condition that poses significant challenges for healthcare providers, researchers, and policymakers. The diagnostic coding specificity of depression is crucial for improving patient care, resource allocation, and health outcomes. We propose a novel approach to assess risk-adjusted coding specificity for individuals diagnosed with depression using a vast cohort of over one million inpatient hospitalizations in the United States. Considering various clinical, demographic, and socioeconomic characteristics, we develop a risk-adjusted model that assesses diagnostic coding specificity. Results demonstrate that risk-adjustment is necessary and useful to explain variability in the coding specificity of principal (AUC = 0.76) and secondary (AUC = 0.69) diagnoses. Our approach combines a multivariate logistic regression at the patient hospitalization level to extract risk-adjusted probabilities of specificity with a Poisson Binomial approach at the facility level. This method can be used to identify healthcare facilities that over- and under-specify diagnostic coding when compared to peer-defined standards of practice. Full article

(This article belongs to the Special Issue New Advances in the Diagnosis and Treatment of Mental Disorders)

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14 pages, 3387 KiB

Open AccessArticle

Investigation of Cognitive Impairment in the Course of Post-COVID Syndrome

by Milena Dimitrova, Yoanna Marinova and Dancho Dilkov

Diagnostics 2023, 13(16), 2703; https://doi.org/10.3390/diagnostics13162703 - 18 Aug 2023

Viewed by 1062

Abstract

(1) Background: The study presents results from an investigation of cognitive impairment in patients hospitalized in the first psychiatric clinic in Bulgaria to treat patients with COVID-19 during the pandemic period between 2020 and 2022. One hundred and twenty patients who had recovered from acute COVID-19 infection (up to 12 weeks ago) and had no previous history of cognitive impairment participated in the study. In 23 of them (19.17%), disturbance of cognitive functioning was observed. (2) Methods: All 23 patients underwent neuropsychological (Luria’s test, Platonov’s Maze test, MMSE, Boston Naming test) and neuroimaging examinations. Only seven of them had evidence of cortical atrophy on CT/MRI images. The most significantly demonstrative image of one of those patients is presented. (3) Results: The neuropsychological testing results of both groups show a certain decrease in fixation and memory retention as well as in the range, concentration, distribution and switching of attention. Deviations from the norm on the MMSE, as well as on the Boston Naming Test, were found in the group of patients with cortical atrophy (mild to moderate aphasia). Neuroprotective agents such as Citicoline, Piracetam and Memantine were prescribed to the patients with evident cortical atrophy. After 3 months, positive results of the neuropsychological examination were reported in both groups. (4) Conclusions: Although there are limited data on the benefit of prescribing pro-cognitive agents in the post-COVID period, our clinical experience suggests that it might be useful in the recovery process from the infection’s consequences on cognition for patients with brain pathology. Full article

(This article belongs to the Special Issue New Advances in the Diagnosis and Treatment of Mental Disorders)

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14 pages, 1092 KiB

Open AccessArticle

Measuring Impairments of Mentalization with the 15-Item Mentalization Questionnaire (MZQ) and Introducing the MZQ-6 Short Scale: Reliability, Validity and Norm Values Based on a Representative Sample of the German Population

by David Riedl, Hanna Kampling, Tobias Nolte, Astrid Lampe, Manfred E. Beutel, Elmar Brähler and Johannes Kruse

Diagnostics 2023, 13(1), 135; https://doi.org/10.3390/diagnostics13010135 - 30 Dec 2022

Cited by 4 | Viewed by 2243

Abstract

Deficits in mentalization are indicated by impaired emotional awareness and self-reflectiveness, and are associated with various mental disorders. However, there is a lack of validated research instruments. In this study, the psychometric properties of the Mentalization Questionnaire (MZQ) were evaluated in a representative German population sample with n = 2487 participants. Analyses included evaluation of the MZQs acceptance, reliability, and validity. Factorial validity was established with exploratory (EFA) and confirmatory factor analyses (CFA) after the dataset was randomly split. Dimensionality was evaluated with a bi-factor model. For convergent validity, correlations with the OPD SQS, PHQ-4, and POMS were calculated. While acceptance was good, internal consistencies (ω = 0.65–0.79) and factor structure of the original four subscales were not acceptable (TLI = 0.87, CFI = 0.91, RMSEA = 0.071). EFA indicated a 3-factor solution, which was not confirmed by CFA (TLI = 0.89, CFI = 0.91, RMSEA = 0.073). Correlations between subscales and bi-factor analyses indicated an underlying general factor (TLI = 0.94, CFI = 0.96, RMSEA = 0.053). A shortened 6-item version was comparable to the original scale. Age and sex-specific representative norm-values are presented. The MZQ is a feasible, reliable and valid self-report instrument to measure representations of inner mental states. However, when applied to non-clinical samples, the total score of the MZQ should be used. Full article

(This article belongs to the Special Issue New Advances in the Diagnosis and Treatment of Mental Disorders)

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Other

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14 pages, 2205 KiB

Open AccessSystematic Review

Inter-Rater Reliability between Structured and Non-Structured Interviews Is Fair in Schizophrenia and Bipolar Disorders—A Systematic Review and Meta-Analysis

by Hélio Rocha Neto, Ana Lúcia R. Moreira, Lucas Hosken, Joshua A. Langfus, Maria Tavares Cavalcanti, Eric Arden Youngstrom and Diogo Telles-Correia

Diagnostics 2023, 13(3), 526; https://doi.org/10.3390/diagnostics13030526 - 31 Jan 2023

Cited by 2 | Viewed by 1937

Abstract

We aimed to find agreement between diagnoses obtained through standardized (SDI) and non-standardized diagnostic interviews (NSDI) for schizophrenia and Bipolar Affective Disorder (BD). Methods: A systematic review with meta-analysis was conducted. Publications from 2007 to 2020 comparing SDI and NSDI diagnoses in adults without neurological disorders were screened in MEDLINE, ISI Web of Science, and SCOPUS, following PROSPERO registration CRD42020187157, PRISMA guidelines, and quality assessment using QUADAS–2. Results: From 54231 entries, 22 studies were analyzed, and 13 were included in the final meta-analysis of kappa agreement using a mixed-effects meta-regression model. A mean kappa of 0.41 (Fair agreement, 95% CI: 0.34 to 0.47) but high heterogeneity (Î² = 92%) were calculated. Gender, mean age, NSDI setting (Inpatient vs. Outpatient; University vs. Non-university), and SDI informant (Self vs. Professional) were tested as predictors in meta-regression. Only SDI informant was relevant for the explanatory model, leaving 79% unexplained heterogeneity. Egger’s test did not indicate significant bias, and QUADAS–2 resulted in “average” data quality. Conclusions: Most studies using SDIs do not report the original sample size, only the SDI-diagnosed patients. Kappa comparison resulted in high heterogeneity, which may reflect the influence of non-systematic bias in diagnostic processes. Although results were highly heterogeneous, we measured a fair agreement kappa between SDI and NSDI, implying clinicians might operate in scenarios not equivalent to psychiatry trials, where samples are filtered, and there may be more emphasis on maintaining reliability. The present study received no funding. Full article

(This article belongs to the Special Issue New Advances in the Diagnosis and Treatment of Mental Disorders)

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20 pages, 1375 KiB

Open AccessSystematic Review

Prevalence of Depression and Related Factors among Patients with Chronic Disease during the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

by Rubén A. García-Lara, Nora Suleiman-Martos, María J. Membrive-Jiménez, Victoria García-Morales, Miguel Quesada-Caballero, Isabel M. Guisado-Requena and José L. Gómez-Urquiza

Diagnostics 2022, 12(12), 3094; https://doi.org/10.3390/diagnostics12123094 - 8 Dec 2022

Cited by 7 | Viewed by 1776

Abstract

The management of chronic diseases in the midst of the COVID-19 pandemic is especially challenging, and reducing potential psychological harm is essential. This review aims to determine the prevalence of depression during the COVID-19 pandemic in patients with chronic disease, and to characterize the impacts of related factors. A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The meta-analysis was performed using StatsDirect software. The review identified 33 articles with a total of 50,905 patients with chronic diseases. Four meta-analyses were performed to estimate the prevalence of depression. In diabetic patients, the prevalence ranged from 17% (95% CI = 7–31) (PHQ-9) to 33% (95% CI = 16–51) (PHQ-8); in obese patients, the prevalence was 48% (95% CI = 26–71); and in hypertensive patients, the prevalence was 18% (95% CI = 13–24). The factors significantly associated with depression were female sex, being single, deterioration in the clinical parameters of diabetes, a decrease in self-care behavior, reduced physical activity and sleep time and fear of contagion. The COVID-19 pandemic has significantly increased levels of depression among persons with chronic disease. Pandemics and other emergency events have a major impact on mental health, so early psychological interventions and health management policies are needed to reinforce chronic patients’ physical and mental health. Full article

(This article belongs to the Special Issue New Advances in the Diagnosis and Treatment of Mental Disorders)

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