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New Orleans is no stranger to trauma. The Crescent City has a vast history of environmental calamities and oppression. Yet, New Orleans is renowned for its "joie de vivre"—or "love of life." Specifically, this community is known for its unique practice of second-line parades. Researchers have noted the healing power of second-line processions, but none have analyzed the practice and psychology of this ritual through a trauma-informed lens. The aim of this conceptual paper is to begin the conversation, rather than deliver hard fast conclusions, on the potential therapeutic function of second-line parades in response to grief. Relevant literature is presented to illustrate second-line parades, trauma theory, and to provide evidence that the therapeutic effects of second-lining may, in part, be explained by trauma theory. This paper concludes with remarks on conceptualizing the second-line funeral as a sophisticated trauma-informed approach to grief and a note for future research. [ABSTRACT FROM AUTHOR]

This article comprehensively reviews motor impairments in children with autism spectrum disorder (ASD) to: (1) determine the prevalence of motor problems in children with ASD; (2) understand the nature of motor difficulties in ASD and whether they are consistent with developmental coordination disorder (DCD); and (3) determine if the term DCD was used as a co-occurring diagnosis in children with ASD after publication of the DSM-5 in 2013. The following databases were systematically searched: MEDLINE, EMBASE, CINAHL, and PsycINFO from 2010 to December 2021. Articles were included if they: (1) were peer-reviewed and published in a scientific journal; (2) included children with ASD who were between 5 and 12 years; (3) used motor or function measures to assess motor abilities in children with ASD. Studies that included children with intellectual disabilities were excluded. Two independent reviewers reviewed titles, abstracts, and full-text articles for inclusion. Twenty-seven studies met the inclusion criteria and were assessed for quality by two independent reviewers using the Appraisal tool for Cross-Sectional Studies. The majority of articles (92.5%) indicated that 50–88% of children with ASD had significant motor impairments on standardized motor assessments and/or functional questionnaires. The nature of motor and function problems in ASD were consistent with DCD; however, only three out of 20 papers (15%) that were published from 2014 described the motor problems as DCD. One study reported that 15.1% of children with ASD with motor impairments had a co-occurring diagnosis of DCD, suggesting that DCD is under-recognized in this clinical population. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to describe and compare the proportion of patients classified as an emergency department (ED) mental health presentation under different definitions, including the Australian Institute of Health and Welfare (AIHW) definition. Methods: This retrospective cohort study enrolled all patients that presented to the EDs of a multi-centre Victorian health service between 1 January 2020 and 30 June 2023. Varying definitions of a mental health presentation were applied to each ED attendance, applying the current AIHW definition (using selected diagnosis codes), broader diagnosis-based coding, the presenting complaint recorded at triage and whether the patient was seen by or referred to the emergency psychiatric service (EPS). The proportion of all ED presentations meeting each definition and any overlap between definitions were calculated. The agreement between each definition and the AIHW definition was evaluated using Kappa's coefficient. Results: There were 813,078 presentations to ED of which 34,248 (4.2%) met the AIHW definition for a mental health presentation. Throughout the study, 45,376 (5.6%) patients were seen and/or referred to EPS, and 36,160 (4.4%) patients were allocated a mental health presenting complaint by triage staff. There was moderate interrater agreement between these definitions, with a kappa statistic (95% confidence interval) between the AIHW definition and a mental health presenting complaint recorded at triage of 0.58 (0.58–0.59) and between the AIHW definition and review by EPS of 0.58 (0.57–0.58). Conclusions: The AIHW definition is a conservative measure of ED mental health presentations and may underestimate emergency psychiatry workload in Australian EDs. What is known about this topic? It is unknown whether the Australian Institute of Health and Welfare (AIHW) definition of an emergency department (ED) mental health presentation definition accurately reflects ED mental health workload. What does this paper add? The AIHW definition appears to underestimate the clinical workload related to ED mental health presentations. There is moderate agreement between the AIHW definition and mental health presentations classified according to complaint recorded at triage, or whether the patient is reviewed by psychiatry services. What are the implications for practitioners? Accurate measurement of emergency psychiatry workload should not rely on the AIHW definition alone. [ABSTRACT FROM AUTHOR]

Identifying major depression in children and adolescents is more challenging than in adults. Questionnaires are often used for screening or guiding clinical assessment. Several instruments of different lengths are used as equivalent measures in diagnostic decisions. In this paper, we explore to what extent 18 commonly used depression scales for children and adolescents explore depression clinical symptoms as established by standard DSM-5 diagnosis criteria. We analyzed scale content adequacy by examining the overlap between scale contents and consensus clinical symptoms, the diagnostic time frame for active symptom assessment, and readability for the target age group. The 18 scales encompassed 52 distinct symptoms. These scales included just 50% of clinical symptoms required for diagnosis. The content overlap was low; on average, 29% of symptoms coincide across scales. Half of the scales did not use the standard period for active symptom appraisal, and some did not include a period for assessment. The reading levels on six scales were inappropriate for the scale's target population age group. The substantial heterogeneity in defining the depressive syndrome, the low overlap among scales, different periods of a positive diagnosis, and mismatch of reading competence for detecting may lead to heterogeneity in clinical diagnoses when using different scales. Improving the content of self-report in terms of homogeneity of diagnostic criteria would lead to better diagnostic decisions and patient management. [ABSTRACT FROM AUTHOR]

The increasing prevalence of mental disorders among youth worldwide is one of society's most pressing issues. The proposed methodology introduces an artificial intelligence-based approach for comprehending and analyzing the prevalence of neurological disorders. This work draws upon the analysis of the Cities Health Initiative dataset. It employs advanced machine learning and deep learning techniques, integrated with data science, statistics, optimization, and mathematical modeling, to correlate various lifestyle and environmental factors with the incidence of these mental disorders. In this work, a variety of machine learning and deep learning models with hyper-parameter tuning are utilized to forecast trends in the occurrence of mental disorders about lifestyle choices such as smoking and alcohol consumption, as well as environmental factors like air and noise pollution. Among these models, the convolutional neural network (CNN) architecture, termed as DNN1 in this paper, accurately predicts mental health occurrences relative to the population mean with a maximum accuracy of 99.79%. Among the machine learning models, the XGBoost technique yields an accuracy of 95.30%, with an area under the ROC curve of 0.9985, indicating robust training. The research also involves extracting feature importance scores for the XGBoost classifier, with Stroop test performance results attaining the highest importance score of 0.135. Attributes related to addiction, namely smoking and alcohol consumption, hold importance scores of 0.0273 and 0.0212, respectively. Statistical tests on the training models reveal that XGBoost performs best on the mean squared error and R-squared tests, achieving scores of 0.013356 and 0.946481, respectively. These statistical evaluations bolster the models' credibility and affirm the best-fit models' accuracy. The proposed research in the domains of mental health, addiction, and pollution stands to aid healthcare professionals in diagnosing and treating neurological disorders in both youth and adults promptly through the use of predictive models. Furthermore, it aims to provide valuable insights for policymakers in formulating new regulations on pollution and addiction. [ABSTRACT FROM AUTHOR]

In this paper, I examine Reinforcement Learning (RL) modelling practice in psychiatry, in the context of alcohol use disorders. I argue that the epistemic roles RL currently plays in the development of psychiatric classification and search for explanations of clinically relevant phenomena are best appreciated in terms of Chang's (2004) account of epistemic iteration, and by distinguishing mechanistic and aetiological modes of computational explanation. [ABSTRACT FROM AUTHOR]

This paper examines whether U.S./Mexico border residence in California is related to the prevalence of DSM-5 alcohol use disorder (AUD) among Whites and Hispanics. Household survey data were obtained from 1,209 adults (59.7% female) 18 to 39 years of age resident in four counties in California: Imperial on the U.S./Mexico border; and Kern, Tulare, and Madera in California's Central Valley. Households were selected using a list assisted sample, with data collected on the phone or online. Results show that AUD rates were not different between border and non-border location and between Whites and Hispanics. AUD was negatively associated with higher income ($20,000 to $60,000: AOR=.38; 95%CI=.17–.86; p<.01—more than $60,000: AOR=.27; 95%CI:.09–.81; p<.01) and poor risk perception (AOR=.86; 95%CI=.78–.94; p<.01). AUD was positively associated with continued volume of drinking (AOR = 1.05; 95%CI = 1.01–1.09; p<.01), drinking in Mexico (AOR = 4.28; 95%CI = 1.61–11.36; p<.01), marijuana use (AOR = 4.11; 95%CI = 1.73–9.77; p<.01), and impulsivity (AOR = 1.55; 95%CI = 1.23–1.94). Efforts to prevent AUD in the population in California, and especially among those who live close to the border with Mexico, should take into consideration factors such as impulsivity, marijuana use, border crossing to drink in Mexico, all of which increased risk of AUD. [ABSTRACT FROM AUTHOR]

Difficulties in recruiting newly bereaved families and following them over time present a major barrier in grief research following the death of a spouse/parent. We established FALCON—the first prospective nationwide cohort of families with children below age 18 years whose parent died in Denmark between April 2019 and July 2021. Data from parents and children were collected within 2 months of death with ongoing follow-up assessments up to 18 months post-death. A total of 992 families were invited. The final cohort consisted of 250 families (250 widowed parents, 134 adolescents, 120 children aged 6–12 years and 63 children aged 0–5 years). In this paper, we describe the rationale for the cohort's creation, the challenges of researching grief in families, the methods used and future plans to utilize this unique family-level dataset. [ABSTRACT FROM AUTHOR]

The use of philosophical phenomenology for conceptual debates in psychiatric nosology and psychopathology is beginning to be recognized. In this paper, we extend this trajectory to include Tourette syndrome (TS), focusing on so-called premonitory urges (PU) preceding Tourettic tics. We clarify some inconsistencies around typology in both phenomenological description and medical classification (i.e. in the Diagnostic and Statistical Manual of Mental Disorders , 5th edition, Text Revision, International Classification of Diseases , 10th edition [World Health Organization, 2004], and the scales that elicit PU). We show how a less typological approach might be usefully deployed in the field, that being the dimensional approach developed by Fernandez (2019a; 2019b). We test both the typological and dimensional approaches in relation to the experience and etiological role of PU in Tourette syndrome. Based on our synthesis of existing studies and new information garnered through phenomenological interviews (using an approach associated with "micro-phenomenology"), we argue that the role of PU in nosology challenges both the current "operational" criteria favored by the Diagnostic and Statistical Manual of Mental Disorders , 5th edition, Text Revision, that are focused on behaviorally observed symptoms, as well as essential and prototypical phenomenological descriptions about a given "type" of experience. [ABSTRACT FROM AUTHOR]

Mental health disorders pose a significant global public health challenge. Social media data provides insights into these conditions. Analysing text can help identify indications of mental health disorders through text-based analysis. However, despite the large number of studies on the analysis of mental health disorders, the predominant algorithm in the existing literature is the Multi-Class Single-Level (MCSL) classification algorithm, which is often used for simple classification tasks involving a limited number of classes. Typically, these classes are binary, representing either an unhealthy or a healthy mental state. This paper uses English text data from Reddit to classify mental health disorders. The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. Two different pre-processing scenarios were proposed to handle unstructured text data, one of the most challenging aspects of classifying text from social media. The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. The proposed pre-processing scenario influences the performance of each classifier and improves classification accuracy. The best accuracy results were obtained for the Robustly Optimised BERT Pre-training Approach (RoBERTa) classifier at level 1 and level 2 classifications, namely 0.98 and 0.85, respectively. Overall, the MCML classification algorithm is proven to be used as a benchmark for early detection of text-based mental health disorders. [ABSTRACT FROM AUTHOR]

Though there is evidence autism identification has been inequitable for populations who are culturally and linguistically minoritized, there is limited research that explains the issue of disproportionality and factors contributing to its occurrence, especially within an educational setting. To explore contributors to racial/ethnic disparities in autism special education eligibility, the current investigation evaluated child and evaluation characteristics as they relate to the absence of autism eligibility. Data were obtained from the Autism and Developmental Disabilities Monitoring (ADDM) Network Study and included children with behavioral characteristics consistent with autism and educational evaluation records. Despite documented characteristics consistent with autism, only 72% of the sample received educational services under autism eligibility. To characterize children without autism eligibility, hierarchical logistic regression was used to evaluate factors documented in evaluation records predicting the absence of autism eligibility. Factors influencing autism eligibility included behavioral characteristics documented, evaluation components completed, intellectual ability, and clinical diagnoses present. There was no unique contribution of race/ethnicity in predicting the absence of autism eligibility when accounting for these previous predictors, but many of these predictors differed by racial/ethnic group. Disproportionality in autism may be the manifestation of inequitable evaluation experiences, including experiencing less comprehensive evaluations, and not receiving an autism specific assessment. Though race/ethnicity did not uniquely contribute to the absence of autism eligibility above and beyond those combined factors, it is important to evaluate and reduce inequities experienced within the autism identification process for populations who are culturally and linguistically minoritized. [ABSTRACT FROM AUTHOR]

The aim of this study was to quantify the multivariate relationships between clinical, cognitive performance, executive functioning, and psychological outcomes in women with fibromyalgia (FMS) using network analyses. Demographic (age, height, weight), clinical (pain history, pain intensity, and related disability), neurocognitive (D2 Attention test, Rey-Osterrieth Complex Figure for visual perception, "Digits D/R/I" tests of the WAIS-IV battery for working memory, the 5-Digit Test for mental inhibition, the Symbol Search for processing speed and the Zoo Test for planning/decision making) and psychological (depressive symptoms, anxiety levels, sleep quality, pain hypervigilance) variables were collected in 129 women with FMS and 111 healthy women. Network analyses were conducted separately for each group to quantify the adjusted correlations between the modeled variables and to assess their centrality indices (i.e., connectivity with other symptoms in the network and their importance in the network). The network identified 74 associations in FMS women and 46 associations in controls with small differences. The strongest correlations in both groups were found between different attention variables: d2_CON with d2_C, d2_O with d_2TR, and d2_CON with d2_TA. The most central variables were d2_TA, d2_C, and d2_CON (highest strength centrality in both groups) and anxiety levels and pain hypervigilance (highest harmonic centrality in FMS women). The strength centrality of the network was stable for women with FMS (CScor0.7: 0.68) but not for healthy women (CScor0.7: 0.28). This study found that attention variables are most relevant within a neurocognitive network and that psychological variables are most important for the treatment of women with FMS. The clinical implications of the current findings, such as the development of treatments targeting these variables, are discussed. [ABSTRACT FROM AUTHOR]

The importance of night sleep for maintaining good physical and cognitive health is well documented as well as its negative changes during aging. Since Mild Cognitive Impairment (MCI) patients bear additional disturbances in their sleep, this study aimed at examining whether there are potential mixed effects of sleep and afternoon time of day (ToD) on the storage, processing, and updating components of working memory (WM) capacity in older adults with MCI. In particular, the study compared patients' performance in the three working memory components, in two-time conditions: "early in the morning and after night sleep", and "in the afternoon and after many hours since night sleep". The Working Memory Capacity & Updating Task from the R4Alz battery was administered twice to 50 older adults diagnosed with MCI. The repeated measures analysis showed statistically significant higher performance in the morning condition for the working memory updating component (p < 0.001). Based on the findings, it seems that the afternoon ToD condition negatively affects tasks with high cognitive demands such as the WM updating task in MCI patients. These findings could determine the optimal timing for cognitive rehabilitation programs for MCI patients and the necessary sleep duration when they are engaged in cognitively demanding daily activities. [ABSTRACT FROM AUTHOR]

Background: Family caregivers of terminally ill and dying people do not only experience varying levels but also different dimensions of caregiver-related strain and burden. The aim of the study was to develop a short multidimensional screening tool for the detection of burden in family caregivers in palliative care. Methods: Family caregivers of cancer patients newly admitted to specialist inpatient palliative care (N = 232) completed questionnaires on psychological burden, quality of life, social support and need fulfillment. A latent class mixture model was used to identify discrete classes of family caregivers related to their multidimensional caregiver burden. Multinomial logistic regression analyses were performed to identify the most predictive items from a set of established questionnaires. Results: Four latent classes of family caregivers were identified: Currently stable caregivers (37%), Caregivers with unmet needs (20%), Psychologically burdened caregivers (30%), and High-risk caregivers (13%). Each of these classes describes a different risk profile of multidimensional family caregiver burden, although family caregivers exhibit high levels of distress across all classes. From a set of 48 items, we identified eight items that predicted the class membership best. These items represent the items of the novel multidimensional screening tool: The 8-item Screening Tool for Family Caregiver Burden in Palliative Care (CAREPAL-8). Except for social support, the items maintained fidelity to the conceptualization of multidimensional caregiver burden used in this study. A preliminary classification system was developed, which has yet to be validated. Conclusions: This study represents the first step in the establishment of a practical, self-administered screening tool that might help healthcare providers to tailor caregiver care according to their burden in daily practice. Brevity of the 8-item tool might facilitate its use in routine clinical care. [ABSTRACT FROM AUTHOR]

In the DSM-5 Alternative Model of Personality Disorders (AMPD), psychopathy is marked by the presence of attention seeking, low anxiousness, and lack of social withdrawal, along with traits from the domains of Antagonism and Disinhibition. The triarchic model of psychopathy (TriPM) posits three biobehaviorally based traits underlying it: disinhibition, meanness, and boldness. The current study directly compared relations for measures of the two models with the broad dimensions of externalizing, internalizing, and positive adjustment. Participants (1,678 adults) were surveyed regarding maladaptive personality traits, clinical symptoms, and positive adjustment features. The TriPM model explained more variance than the AMPD in substance use, positive adjustment, and empathy, whereas the AMPD model explained more variance in internalizing symptoms. In addition, AMPD Antagonism and the Psychopathy Specifier diverged from TriPM Meanness and Boldness in their associations with some specific outcomes. Overall, our study provides evidence for complementarity of the two models in characterizing the multifaceted nature of psychopathy. [ABSTRACT FROM AUTHOR]

Background: Non-suicidal self-injury (NSSI) and Feeding or Eating Disorders (FEDs) often coexist during adolescence with reciprocal influences on their clinical picture. The present study aimed to identify differences and similarities in the clinical presentation of young patients with both conditions compared to those with the two non-comorbid disorders. Methods: We consecutively recruited forty-five female patients aged between 11 and 18 at our third-level hospital and subdivided them into three groups (NSSI: n = 15; FED: n = 15; NSSI + FED: n = 15). Patients underwent a full clinical assessment. Results: Based on our results, the NSSI + FED group was characterized by higher rates of binging/purging behaviors, greater prevalence of Cyclothymic Disorder, and a more severe clinical presentation compared to the non-comorbid groups. Moreover, higher levels of suicidal ideation were found in the NSSI + FED group. Pharmacological treatment patterns also differed, with SSRI being prescribed more frequently to NSSI + FED patients while mood stabilizers were prescribed more frequently to NSSI ones. A Principal Component Analysis identified four main dimensions: "Body Image" impairment was more pronounced in NSSI + FED patients, indicating negative attitudes towards their own body; "Metacognition" deficits were higher in NSSI than FED. Conclusions: The present study underscores distinctive clinical features in patients with comorbid NSSI and FED, emphasizing the urgent need for tailored intervention strategies focusing on specific symptom domains. [ABSTRACT FROM AUTHOR]

Background/Objectives: Children with autism spectrum disorder (ASD) and/or attention deficit hyperactivity disorder (ADHD) exhibit more executive function (EF) deficits compared to typically developing (TD) peers. EF deficits are linked to various impairments in daily functioning and increased parental stress. The first aim of the present study is to investigate EFs in children with ASD and ADHD compared to their TD peers. The second aim is to explore profiles of executive functions in children with ASD and ADHD and, finally, to determine the differences of EF profiles in relation to parental stress and children's functional impairments. Methods: The sample comprised 30 TD children, 47 children with ASD, and 34 children with ADHD, aged 8 to 12 years. Parents completed questionnaires of parenting stress, and children's social and daily-life functioning. Parents and teachers reported information about children's EF. Results: The results indicated significantly greater impairment of EFs in the clinical groups compared to the TD group. Moreover, three distinct clusters of functioning were identified based on the severity of reported EF difficulties. The significant findings showed that children with more severe EF profiles were associated with greater daily impairment and higher levels of perceived parental stress. Conclusions: Given the impact of EF deficits on the lives of children with ASD and ADHD and their families, it is crucial that studies like this enhance our understanding and inspire future interventions aimed at improving executive functions in children with ASD and ADHD. Such interventions could help reduce parental stress and improve daily functioning. [ABSTRACT FROM AUTHOR]

Mental disorders are increasingly understood as involving complex alterations of self that emerge from dynamical interactions of constituent elements, including cognitive, bodily, affective, social, narrative, cultural and normative aspects and processes. An account of self that supports this view is the pattern theory of self (PTS). The PTS is a non-reductive account of the self, consistent with both embodied-enactive cognition and phenomenological psychopathology; it foregrounds the multi-dimensionality of subjects, stressing situated embodiment and intersubjective processes in the formation of the self-pattern. Indications in the literature already demonstrate the viability of the PTS for formulating an alternative methodology to better understand the lived experience of those suffering mental disorders and to guide mental health research more generally. This article develops a flexible methodological framework that front-loads the self-pattern into a minimally structured phenomenological interview. We call this framework ‘Examination of Self Patterns’ (ESP). The ESP is unconstrained by internalist or externalist assumptions about mind and is flexibly guided by person-specific interpretations rather than pre-determined diagnostic categories. We suggest this approach is advantageous for tackling the inherent complexity of mental health, the clinical protocols and the requirements of research. [ABSTRACT FROM AUTHOR]

There is a need to investigate the diagnostic utility of autism diagnostic questionnaires in school-age children, who are increasingly being referred for autism assessment. Aside from the standardization sample, little research has been conducted on the Autism Spectrum Rating Scales, particularly regarding teacher reports. This study investigated the criterion validity of the Autism Spectrum Rating Scales-Teacher report for ages 6–18 (ASRS-T6-18) in a well-characterized community sample of 409 children (autism [AUT] n = 122; non-autism [NOT] n = 287; X ¯ age = 9.91) evaluated with the Autism Diagnostic Observation Schedule-2, a well-validated autism diagnostic measure. Significant mean differences with small to moderate effect sizes (d = 0.28–0.56) were observed for all scores except Self-Regulation, Adult interaction, and Attention. Logistic Regression and Receiver Operating Characteristic analyses conducted for the Summary, ASRS, and two Treatment scales (Peer and Social-Emotional Reciprocity) indicated low ORs (< |1.08|) and AUCs in the poor range (<.67). Total and Unusual Behavior emerged as comparatively stronger scales with covariates (age and IQ); other scales were generally similar with/without control variables. Sensitivity and specificity could not be optimized. The suggested 60 t -cutpoint had fair or good sensitivity (76.23–83.61) for all examined scales except Unusual Behavior (68.03). However, specificity was poor (46.93–54.36), with high false positive rates (45.64%–63.07%). In complex community samples, the ASRS-T6-18 behaves more like a screener as opposed to a diagnostic measure. [ABSTRACT FROM AUTHOR]

Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists' expertise and interpretive skills. However, the advent of deep learning methodologies has revolutionized the field, offering more accurate and efficient assessments. Attention-based models have emerged as promising tools, focusing on salient features within complex medical imaging data. However, the precise impact of different attention mechanisms, such as channel-wise, spatial, or combined attention within the Channel-wise Attention Mode (CWAM), for brain tumor classification remains relatively unexplored. This study aims to address this gap by leveraging the power of ResNet101 coupled with CWAM (ResNet101-CWAM) for brain tumor classification. The results show that ResNet101-CWAM surpassed conventional deep learning classification methods like ConvNet, achieving exceptional performance metrics of 99.83% accuracy, 99.21% recall, 99.01% precision, 99.27% F1-score and 99.16% AUC on the same dataset. This enhanced capability holds significant implications for clinical decision-making, as accurate and efficient brain tumor classification is crucial for guiding treatment strategies and improving patient outcomes. Integrating ResNet101-CWAM into existing brain classification software platforms is a crucial step towards enhancing diagnostic accuracy and streamlining clinical workflows for physicians. [ABSTRACT FROM AUTHOR]

The widespread use of novel psychoactive substances (NPSs)—defined as new narcotic or psychotropic agents not classified under the Single Convention on Narcotic Drugs of 1961 or the Convention on Psychotropic Substances of 1971—poses a significant challenge to contemporary mental health paradigms due to their impact on psychiatric disorders. This study revisits and expands upon the theory of mental automatism as proposed by Gaëtan Gatian de Clérambault, aiming to elucidate the psychopathological mechanisms underlying substance-induced psychoses (SIP) and their distinction from non-induced psychoses (schizophrenia and related disorders). Through a phenomenological and clinical investigation, we explore the relevance of mental automatism in the development of toxic psychoses, drawing upon the historical and contemporary literature. This research highlights the psychopathological distinctions between induced and non-induced psychoses and the transition mechanisms from acute to chronic psychosis states. De Clérambault's theory, supplemented by Janet, Jackson, and Bonhoeffer's contributions, provides a foundational framework for understanding the genesis of SIP. Our findings suggest that NPS consumption, particularly among adolescents and psychiatric patients, significantly correlates with increased risks of SIP, marked by a transition to chronicity influenced by biological lesions triggered by substance use. Furthermore, we propose a comprehensive framework for SIP, integrating mental automatism, psychopathological distinctions, and transition mechanisms. This framework aims to refine diagnostic criteria and therapeutic approaches, addressing gaps in clinical practice and research. The study underscores the need for a nuanced understanding of SIP, advocating for a paradigm shift in psychiatric assessment and treatment approaches to better address the complexities of substance-induced mental health disorders. [ABSTRACT FROM AUTHOR]

This study used the National Survey on Drug Use and Health to assess a nationally representative sample (N = 4596) weighted to represent 35.2 million adults with DSM-5 criteria-determined substance use disorders (SUDs). This study explored substance use treatment utilization in 2020, emphasizing populations with high vulnerability (e.g., criminal justice involvement (CJI) through parole or probation, polysubstance use, severe mental illness, and HIV/STI). Substance use treatment was broadly defined (any inpatient, outpatient/doctor's office, self-help/other for alcohol/drugs). Our results indicated that among adults with SUDs in 2020, 7 million (20%) had multiple SUDs, 1.75 million (5%) had CJI, 5.3 million (15%) had a severe mental illness, and 1.8 million (5%) had a diagnosis of HIV/STI in the last year. Only 7% of individuals with SUD sought any substance use treatment in the past year. CJI (aOR: 13.39, 95% CI: [7.82, 22.94]), serious mental illness (aOR: 3.27, 95% CI: [1.93, 5.55]), and having both 2 (aOR: 2.10, 95% CI: [1.29, 3.42]) or 3 or more SUDs (aOR: 3.46, 95% CI: [1.82, 6.58]) were all associated with a greater likelihood of receiving treatment. Marriage (aOR: 0.43, 95% CI: [0.25, 0.74]) and having an income twice the poverty threshold (aOR: 0.53, 95% CI: [0.29, 0.94]) were associated with reduced odds of receiving any substance use treatment. Compared to those 18 to 25, older individuals had increased odds (2-4 times) of receiving treatment. Interventions are crucially needed to increase access to treatment among those with SUDs. [ABSTRACT FROM AUTHOR]

Background: Very few studies have compared different diagnostic approaches to diagnose depression in patients with cancers. Aim: To compare the different diagnostic approaches used for diagnosing depression in patients with cancers. Methodology: This cross-sectional study included 200 patients (diagnosed with cancer at least 3 months prior to recruitment) attending the outpatient services who were assessed on diagnostic and statistical manual, fifth edition (DSM-5) criteria for depression. Additionally, these patients were also assessed using the inclusive, exclusive, and substitutive criteria for depression using a semistructured interview. Patients completed Patient Health Questionnaire-9 (PHQ-9). Results: The mean age of the patients was 50.28 years (S.D. M14.11). Females outnumbered males. The mean age of onset of malignancy was 47 years (S.D 14.03), and the mean time since diagnosis of cancer was 35.45 years (S.D 36.87). The prevalence of depression was the highest (38.5%) when estimated using the PHQ-9 and was the lowest (21.5%) when assessed using exclusive criteria for depression. All approaches had high degree of concordance with the DSM-5 criteria for depression. Conclusion: A significant proportion of patients with cancer suffer from depression, and the prevalence is influenced by the diagnostic method. [ABSTRACT FROM AUTHOR]

This study aims to determine whether it can distinguish odontogenic keratocyst (OKC) and simple bone cyst (SBC) based solely on preoperative panoramic radiographs through a deep learning algorithm. (1) Methods: We conducted a retrospective analysis of patient data from January 2018 to December 2022 at Pusan National University Dental Hospital. This study included 63 cases of OKC confirmed by histological examination after surgical excision and 125 cases of SBC that underwent surgical curettage. All panoramic radiographs were obtained utilizing the Proline XC system (Planmeca Co., Helsinki, Finland), which already had diagnostic data on them. The panoramic images were cut into 299 × 299 cropped sizes and divided into 80% training and 20% validation data sets for 5-fold cross-validation. Inception-ResNet-V2 system was adopted to train for OKC and SBC discrimination. (2) Results: The classification network for diagnostic performance evaluation achieved 0.829 accuracy, 0.800 precision, 0.615 recall, and a 0.695 F1 score. (4) Conclusions: The deep learning algorithm demonstrated notable accuracy in distinguishing OKC from SBC, facilitated by CAM visualization. This progress is expected to become an essential resource for clinicians, improving diagnostic and treatment outcomes. [ABSTRACT FROM AUTHOR]

Contemporary understanding of combat trauma's psychological effects emphasizes the interpersonal ways survivors process their experiences. Yet cases of incongruence between survivors who want to share their traumatic experience and close others who are not ready to take part in this challenging task are common. Hence, many trauma survivors are compelled to cope with the posttraumatic consequences mostly alone. The present study followed the interpretive phenomenological approach to examine the experience of loneliness, as described by 15 male combat veterans dealing with posttraumatic stress. Participants completed semistructured qualitative interviews in which they shared their knowledge regarding postservice distress, loneliness, coping, and growth. Two main themes emerged: "The Loneliness Complex," highlighting this phenomenon's multifaceted, layered, and cyclical nature; and "Emotional Growth after Loneliness," presenting the positive potential of loneliness. These findings emphasize the importance of interpersonal relations in trauma survivors' recovery process. Participants described how experiences with peers can serve as a pivotal point for coping with postservice distress and how internalization of positive interpersonal interactions seems to be a crucial psychological resource for further rehabilitation and growth. Being a multilayered and cyclical condition, loneliness might serve trauma survivors in their search of safety, while also bearing the potential to motivate them to act upon their condition and promote emotional growth. Clinicians should acknowledge the risks trauma survivors take by leaving their lonely yet safe place, as they are encouraged to process their traumatic experiences and share their inner world with others. [ABSTRACT FROM AUTHOR]

Background: Delirium is a serious neuropsychiatric syndrome with adverse outcomes, which is common but often undiagnosed in terminally ill people. The 4 'A's test or 4AT (www.the4AT.com), a brief delirium detection tool, is widely used in general settings, but validation studies in terminally ill people are lacking. Aim: To determine the diagnostic accuracy of the 4AT in detecting delirium in terminally ill people, who are hospice inpatients. Design: A diagnostic test accuracy study in which participants underwent the 4AT and a reference standard based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The reference standard was informed by Delirium Rating Scale Revised-98 and tests assessing arousal and attention. Assessments were conducted in random order by pairs of independent raters, blinded to the results of the other assessment. Setting/participants: Two hospice inpatient units in Scotland, UK. Participants were 148 hospice inpatients aged ⩾18 years. Results: A total of 137 participants completed both assessments. Three participants had an indeterminate reference standard diagnosis and were excluded, yielding a final sample of 134. Mean age was 70.3 (SD = 10.6) years. About 33% (44/134) had reference standard delirium. The 4AT had a sensitivity of 89% (95% CI 79%–98%) and a specificity of 94% (95% CI 90%–99%). The area under the receiver operating characteristic curve was 0.97 (95% CI 0.94–1). Conclusion: The results of this validation study support use of the 4AT as a delirium detection tool in hospice inpatients, and add to the literature evaluating methods of delirium detection in palliative care settings. Trial registry: ISCRTN 97417474. [ABSTRACT FROM AUTHOR]

Structural and functional MRI (magnetic resonance imaging) based diagnostic classification using machine learning has long held promise, but there are many roadblocks to achieving their potential. While traditional machine learning models suffered from their inability to capture the complex non-linear mapping, deep learning models tend to overfit the model. This is because there is data scarcity and imbalanced classes in neuroimaging; it is expensive to acquire data from human subjects and even more so in clinical populations. Due to their ability to augment data by learning underlying distributions, generative adversarial networks (GAN) provide a potential solution to this problem. Here, we provide a methodological primer on GANs and review the applications of GANs to classification of mental health disorders from neuroimaging data such as functional MRI and showcase the progress made thus far. We also highlight gaps in methodology as well as interpretability that are yet to be addressed. This provides directions about how the field can move forward. We suggest that since there are a range of methodological choices available to users, it is critical for users to interact with method developers so that the latter can tailor their development according to the users' needs. The field can be enriched by such synthesis between method developers and users in neuroimaging. [ABSTRACT FROM AUTHOR]

The existence of a female phenotype profile in autistic spectrum disorder is one of the current hypotheses to explain the diagnostic discrepancy between men and women. In this context, an international literature review was carried out to evidence and describe the characteristics of restricted interests found in girls with autistic spectrum disorder. A documentary search was conducted on PubMed and a systematic literature review was carried out based on the PRISMA methodology. We selected studies with a population of boys and girls diagnosed as autistic according to the DSM-IV or the DSM-5, in which quantitative and descriptive comparisons of restricted interests, according to gender were carried out. Nineteen studies were found to be relevant. Fifteen enabled a refining of the characteristics of restricted interests among females: fewer restricted interests were identified in comparison with boys, and the autistic girls' interests seem to be closer to those of neurotypical girls than to those of autistic boys, which thus led to more complex screening. Age and Intelligence quotient seem to be two factors that trigger variations in restricted interests differently according to gender. Representations among professionals also have an impact on diagnoses among girls. For future research, one of the perspectives could be a comparison between girls with autism and neurotypical girls to limit gender bias. The present results contribute to potentially extending knowledge of a female phenotypical profile in autism and show the need to improve the general population's awareness, to improve health professionals' training and possibly to revise the diagnostic tools. [ABSTRACT FROM AUTHOR]

The conceptualization of personality disorder has been refined through recent nosological advances introduced in the Alternative Model for Personality Disorders (AMPD). These advances locate self and interpersonal (dys)function at the core of personality pathology. Self-report personality assessment instruments have demonstrated promise in the assessment of Criterion A domains. However, research highlighting the utility of performance-based personality assessment instruments has been largely absent in these advances, despite acknowledgment of their potential. We adhered to PRISMA review guidelines to survey and assess the potential relevance and utility of select performance-based personality instruments in assessing Criterion A domains of the AMPD. We conclude that performance-based personality measures are uniquely positioned to assess maladaptive self- and interpersonal functioning and may address some limitations of self-report measures. Toward this end, we propose a working model that provides ranges of test scores that correspond to the 5-point scale of the Criterion A domains of the AMPD. [ABSTRACT FROM AUTHOR]

The current diagnosis of attention deficit hyperactivity disorder (ADHD) is based on history, clinical observation, and behavioral tests. There is a high demand to find biomarkers for the diagnosis of ADHD. The aim of this study is to analyze the serum profiles of several biomarkers, including homocysteine (Hcy), vitamin B12, vitamin D, ferritin, and iron, in a cohort of 133 male subjects (6.5–12.5 years), including 67 individuals with an ADHD diagnosis based on DSM-V criteria and 66 age-matched healthy boys (healthy controls, HC). Assessments for ADHD included the Iowa Conners' Teacher Rating Scale (CPRS) and the ADHDT test, as well as cognitive assessments using the Wechsler Intelligence Scale for Children-Revised (WISC-R) and the TROG-2 language comprehension test. Hcy and iron were quantified using spectrophotometry, while vitamin B12 and total 25-hydroxy vitamin D levels were determined using an electrochemiluminescence immunoassay (ECLIA) and ferritin was measured using a particle-enhanced immunoturbidimetric assay. The results showed significantly increased Hcy levels and decreased vitamin B12 levels in ADHD patients compared to HCs. Multiple logistic regression analysis indicated that Hcy is a potential prognostic indicator for ADHD. These results suggest that elevated homocysteine and decreased vitamin B12 may serve as markers for the diagnosis and prognosis of ADHD. [ABSTRACT FROM AUTHOR]

Two neurodevelopmental conditions, autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), have been associated with executive function (EF) impairments but the specificity of their impairments is still controversial. The present meta-analysis aimed to identify the differences in EF profiles of ASD, ADHD, and ASD+ADHD in relation to a control group of individuals with typical development (TD) and to understand whether the EF performance could change depending upon the type of measure used to assess EF (performance tests vs. questionnaires). Results from 36 eligible studies revealed that ADHD and ASD showed more difficulties than the TD group in tests and, particularly, in questionnaires. No significant differences in the EF profile emerged between ASD and ADHD when assessed through neuropsychological tests (d = 0.02), while significant differences emerged when assessed through questionnaires, with ADHD having higher ratings than ASD (d = −0.34). EF questionnaires and neuropsychological tests may catch two different constructs of EF, with the former being more predictive of everyday life EF impairments. The comparison between the double diagnosis group (ADHD+ASD) and the clinical groups pointed out that the former has a more similar EF profile to the ADHD-alone one and that it shows more difficulties than ASD-alone. [ABSTRACT FROM AUTHOR]

The article examines why psychiatric diagnoses are neither circular nor uniformative nor lacking in explanatory value despite the absence of known pathophysiological processes as part of their diagnostic criteria. Topics include problems and inadequacies in DSM-5 psychiatric diagnostic categories, mistaken beliefs about the nature, scope, and purpose of the diagnostic categories, and diagnoses that embody so little descriptive or causal content as to be trivially nonexplanatory.

We posit the hypothesis that False Positive cases (FP) in machine learning classification models of suicidal behavior are at risk of suicidal behavior and should not be seen as sheer classification error. We trained an XGBoost classification model using survey data from 173,663 Norwegian adolescents and compared the classification groups for several suicide-related mental health indicators, such as depression, anxiety, psychological distress, and non-suicidal self-harm. The results showed that as the classification is made at higher risk thresholds - corresponding to higher specificity levels - the severity of anxiety and depression symptoms of the FP and True Positive cases (TP) become significantly more similar. In addition, psychological distress and non-suicidal self-harm were found to be highly prevalent among the FP group, indicating that they are indeed at risk. These findings demonstrate that FP are a relevant risk group for potential suicide prevention programs and should not be dismissed. Although our findings support the hypothesis, we account for limitations that should be examined in future longitudinal studies. Furthermore, we elaborate on the rationale of the hypothesis, potential implications, and its applicability to other mental health outcomes. [ABSTRACT FROM AUTHOR]

Biology education plays a vital role in nurturing the understanding of learners about the intricacy of life. Various efforts have emerged to strengthen learning biological concepts but there were still studies that showed that learners have low mastery in some aspects. To determine how well students understood various biological topics, including human physiology, Concept inventory tests (CIT) were used. The concept inventory test may be able to spot students' misconceptions and ultimately lead to improved comprehension. The crafted CIT developed with the aid of a table of specifications based on Bloom's taxonomy of cognitive domain was assessed according to its validity and reliability. In validation, content validity and item analysis were considered while reliability test was employed through Cronbach's alpha. Distractor analysis was also performed to determine possible source of misconception per item. The CIT was administered to 120 senior high school STEM students (50.8% from the private schools, 37.5% in regular public schools and 11.7% from public schools with special programs in science). The results displayed high content validity with a mean of 4.83 for content validity and an average Aiken's validity coefficient of 0.98. It also highlighted that the test is moderately difficult with the test difficulty of 0.58, as well as, discriminatory with a discriminating level of 0.46. After item classification, 63 items were retained (39 accepted, 24 for revisions) and Chronbach's alpha (a=0.74) indicated good internal consistency. The concept inventory test propounds to be a good classroom test with minor items to be revised. [ABSTRACT FROM AUTHOR]

Compare developmental profiles and core ASD symptom manifestation between male and female toddlers with DSM-5 ASD. Retrospective record review of 500 toddlers (79% male) at time of ASD diagnosis. There were no differences in developmental functioning between males and females. When adjusting for multiple comparisons, sex differences were only noted for sensory seeking behavior occurring at a higher frequency in females. Overall, there were no significant differences in demographic characteristics, developmental functioning, or manifestation of core ASD symptoms between males versus female toddlers at the time of DSM-5 ASD diagnosis. [ABSTRACT FROM AUTHOR]

Background: Mental health service providers are increasingly interested in patient perspectives. We examined rates and predictors of patient-reported satisfaction and perceived helpfulness in a cross-national general population survey of adults with 12-month DSM-IV disorders who saw a provider for help with their mental health. Methods: Data were obtained from epidemiological surveys in the World Mental Health Survey Initiative. Respondents were asked about satisfaction with treatments received from up to 11 different types of providers (very satisfied, satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, very dissatisfied) and helpfulness of the provider (a lot, some, a little, not at all). We modelled predictors of satisfaction and helpfulness using a dataset of patient-provider observations (n = 5,248). Results: Most treatment was provided by general medical providers (37.4%), psychiatrists (18.4%) and psychologists (12.7%). Most patients were satisfied or very satisfied (65.9-87.5%, across provider) and helped a lot or some (64.4-90.3%). Spiritual advisors and healers were most often rated satisfactory and helpful. Social workers in human services settings were rated lowest on both dimensions. Patients also reported comparatively low satisfaction with general medical doctors and psychiatrists/psychologists and found general medical doctors less helpful than other providers. Men and students reported lower levels of satisfaction than women and nonstudents. Respondents with high education reported higher satisfaction and helpfulness than those with lower education. Type of mental disorder was unrelated to satisfaction but in some cases (depression, bipolar spectrum disorder, social phobia) was associated with low perceived helpfulness. Insurance was unrelated to either satisfaction or perceived helpfulness but in some cases was associated with elevated perceived helpfulness for a given level of satisfaction. Conclusions: Satisfaction with and perceived helpfulness of treatment varied as a function of type of provider, service setting, mental status, and socio-demographic variables. Invariably, caution is needed in combining data from multiple countries where there are cultural and service delivery variations. Even so, our findings underscore the utility of patient perspectives in treatment evaluation and may also be relevant in efforts to match patients to treatments. [ABSTRACT FROM AUTHOR]

The intertwined relationship between religion and mental health has been accounted for since the earliest recorded history. This study aimed to explore the relationship between the concept of diseases of the spiritual heart (DOTSH) from the Islamic–Sufi perspective and the medical–psychiatric concept of mental disorder. We examined two essential documents as our primary data sources: (1) Al Ghazali's Ihya Ulumuddin (Revivals of Religion Sciences) Volume III entitled the Quarter of the Destructive and (2) The Diagnostic and Statistical Manual, Fifth Version, Text Revision (DSM-5-TR). We employed a document analysis of the qualitative method by applying six steps of data analysis. We reviewed the English version of Al Ghazali's book to identified DOTSH. In this stage, we found six DOTSH categories which comprised of 40 DOTSH. Then, we searched the correspondence of DOTSH's categories to the DSM-5-TR criteria for mental disorders. We found that all DOTSH categories correspond to DSM-5-TR diagnostics criteria, diagnostic features or diagnostic associated features. We concluded that spiritual heart diseases not only present as symptoms but also can be regarded as mental disorder preconditions that require preventive intervention. [ABSTRACT FROM AUTHOR]

In this rejoinder, I comment on Irmak's 2014 article titled "Schizophrenia or Possession?" published in the Journal of Religion and Health (Irmak, 2014; JORH 53(3):773–777. https://doi.org/10.1007/s10943-012-9673-y). After providing a brief overview of the article and two commentaries on it, I examine the role that demonic possession may or may not play in the development and course of schizophrenia. While keeping an open mind to the possibility of evil influences on the course of illness in those with or without psychosis, I emphasize that schizophrenia is a neurobiological illness that requires compassionate care and expert psychobiological treatment. [ABSTRACT FROM AUTHOR]

Spinal injuries, including cervical and thoracolumbar fractures, continue to be a major public health concern. Recent advancements in machine learning and deep learning technologies offer exciting prospects for improving both diagnostic and prognostic approaches in spinal injury care. This narrative review systematically explores the practical utility of these computational methods, with a focus on their application in imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI), as well as in structured clinical data. Of the 39 studies included, 34 were focused on diagnostic applications, chiefly using deep learning to carry out tasks like vertebral fracture identification, differentiation between benign and malignant fractures, and AO fracture classification. The remaining five were prognostic, using machine learning to analyze parameters for predicting outcomes such as vertebral collapse and future fracture risk. This review highlights the potential benefit of machine learning and deep learning in spinal injury care, especially their roles in enhancing diagnostic capabilities, detailed fracture characterization, risk assessments, and individualized treatment planning. [ABSTRACT FROM AUTHOR]

Background—There is no validated dementia screening tool for multi-ethnic Asian populations comprising Chinese, Malays, and Indians. This study aimed to establish the psychometric properties of the Community Screening Instrument for Dementia (CSI-D), Chinese Mini Mental State Examination (CMMSE), and Elderly Cognitive Assessment Questionnaire (ECAQ) in multi-ethnic Singapore. Methods—Participants were randomly drawn from a community-based neurological diseases study of older adults conducted in Singapore, with oversampling to allow similar subject numbers from the three major ethnicities: Chinese, Malay, and Indian. The CSI-D, CMMSE, and ECAQ were administered by trained research nurses using a standardised translated questionnaire in a language the participant was most conversant in. Participants were independently diagnosed as a case/non-case of dementia using the DSM-IV. Results—There were 259 participants (85 Chinese, 85 Malays, and 89 Indians, mean age 70.15 years, 65.4% female, 58.8% had no/minimal formal education); 22.8% (n = 59) had dementia. Correlations between the measures were substantial. All the measures had acceptable overall discriminative abilities. Diagnostic accuracies of the instruments did not differ across the ethnic groups. Effects of education were present in the cognitive screening measures. Conclusions—The CSI-D, CMMSE, and ECAQ are valid dementia instruments in this multi-ethnic Asian setting. [ABSTRACT FROM AUTHOR]

Most adolescents and young adults who experience psychological distress do not seek professional help. This study aims to enhance the understanding of sociodemographic, psychological, and clinical characteristics associated with the underuse of health services by adolescents and young adults with mental disorders. Data from a cross-sectional, epidemiological study with a population-based sample (N = 1180 participants, 14–21 years old) were used. Participants completed a fully standardized, computer-assisted diagnostic interview (DIA-X-5/D-CIDI) administered by trained clinical interviewers to assess lifetime mental disorders according to DSM-5 as well as lifetime health service use for mental health problems, and completed self-report questionnaires to assess various psychological variables (e.g., stigma). Predictors of health service use were examined using univariate and multiple logistic regression analyses, data were weighted for age and sex to improve representativeness Of n = 597 participants with any lifetime mental disorder, 32.4% [95% CI 28.4; 36.7] had ever used any health services because of a mental health, psychosomatic, or substance use problem. Even less had received psychotherapeutic or pharmacological treatment (Cognitive Behavioral Therapy: 12.1% [9.5; 15.2]; other psychotherapy: 10.7% [8.4; 13.7]; medication: 5.4% [3.7; 7.8]). High education was associated with less health service use (low/ middle/ other vs. high education: 53.8% vs. 26.9%; OR = 0.26, p <.001). In the multiple regression model, stigma toward mental disorders was the single psychological variable associated with a reduced likelihood of using health services (OR = 0.69 [0.52; 0.90], p <.01). These findings draw attention to the treatment gap for mental disorders during adolescence and highlight related factors to be addressed in public health contexts. [ABSTRACT FROM AUTHOR]

This study aims to identify the sensory characteristics of children with both developmental disabilities such as ASD and ADHD and a history of child maltreatment (DM group), children with developmental disabilities (DD group), and typically developed children (TD group). The sensory characteristics of 24 children were assessed through virtual reality and self-administered questionnaires. The results elucidated that the duration of gazing at the "teacher" (60–75 s) was significantly different with the DM group's gaze being shorter than the DD group's gaze (p = 0.042). The duration of the "others" gaze (45–60 s) was also significantly different with the DM group's gaze being longer than the DD and TD groups' gaze (p = 0.018; p = 0.030). Additionally, the scores for tactile sensitivity, taste/smell sensitivity, under-responsive/seeks sensation, and the total short-term sensory profile were significantly different between the DM-DD and DD-TD groups. The scores of the heart rate perception test and Multidimensional Assessment of Interoceptive Awareness were significantly lower in the DM and DD groups. In conclusion, children who have experienced trauma and developmental disabilities may have different sensory characteristics than children with only developmental disabilities or none, implying the need for further research and tailored care. [ABSTRACT FROM AUTHOR]

Background: Traditional diagnostic methods are limited in accuracy when detecting maxillary sinus fungal balls, leading to a higher risk of misdiagnosis or missed diagnosis. This study focuses on a deep learning-based algorithm for assisting in the localization and diagnosis of maxillary sinus fungal balls, addressing the limitations of conventional diagnostic procedures. Materials and Methods: Axial CT imaging data of maxillary sinus were collected from 107 patients, including 47 cases of maxillary sinus fungal balls, 30 cases of other maxillary sinus lesions and 30 cases of healthy maxillary sinus, based on which, a dataset was constructed and a two-stage assisted diagnosis algorithm consisting of a classification and detection model was established. In the first stage, slices containing maxillary sinus were classified and selected. In the second stage, the selected slices were detected to diagnose and localize the fungal ball lesions in the maxillary sinus. Results: The accuracy of the classification model was 92.71%, the mAP and AP50 of the detection model were 0.73 and 0.76, respectively, and the accuracy of the algorithm for the diagnosis of maxillary sinus fungal balls was 84.4%. Conclusion: It is feasible to develop a two-stage auxiliary diagnosis method for maxillary sinus fungal ball based on deep learning. [ABSTRACT FROM AUTHOR]

Sensory differences are highly prevalent in autistic individuals. However, few studies have compared their presentation between autistic males and autistic females. We used psychophysics to assess and compare tactile perceptual sensitivity between autistic and non-autistic boys and girls aged between 8 and 12 years of age. While there were sex-differences of amplitude discrimination, frequency discrimination and order judgement thresholds, these sex-differences were not autism-specific. Mean RTs and detection thresholds were elevated in autism but were comparable between the sexes. Tactile sensitivity measures that are elevated in autism but are otherwise comparable between autistic males and autistic females suggest the possibility that certain sensory features could be used as sex-indifferent markers of autism. Further investigation with larger and more representative samples should be conducted before any stronger conclusions are made. [ABSTRACT FROM AUTHOR]

Background: Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation. Methods: Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months. Results: 10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation. Conclusion: Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning. [ABSTRACT FROM AUTHOR]