This study examined the prevalence and correlates of mental disorders among youth in Kumasi, Ghana, through a community-based cross-sectional survey. 672 urban participants aged 6-17 years were surveyed. Mental disorders were screened using Rutter's A2 Scale for Parent Assessment of Child Behaviour, with diagnoses confirmed by the Kiddie-Schedule for Affective Disorders and Schizophrenia. The Double Sampling method was used for weighted prevalence estimates, and correlates analysed using chi-square and logistic regression. Lifetime weighted prevalence of CAMH disorders was 30.4% (95% CI: 26.9-33.9), predominantly anxiety-related disorders, with current weighted prevalence 18.6% (95% CI: 15.7-21.5). Notably, lacking an active reading habit was associated with nearly three times the odds of mental illness. Children in the 3rd and 4th wealth quintiles had significantly higher odds of mental disorder (12- and 9-times increased odds, respectively), as did lack of caregiver homework supervision among children under 11 years. This study provides the first community-based prevalence figures for childhood mental disorders in Ghana, highlighting the link between poverty-related factors and mental health, and suggesting potential policy interventions to inform policy.
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http://dx.doi.org/10.1007/s10578-024-01799-8 | DOI Listing |
Int J Bipolar Disord
December 2024
Department for Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany.
Background: Attention-deficit/hyperactivity disorder (ADHD) is a common neuro-developmental disorder that often persists into adulthood. Moreover, it is frequently accompanied by bipolar disorder (BD) as well as borderline personality disorder (BPD). It is unclear whether these disorders share underlying pathomechanisms, given that all three are characterized by alterations in affective states, either long or short-term.
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December 2024
The Department of Mechanical Engineering and Mechatronics, Ariel University, Ariel, Israel.
Autism spectrum disorder (ASD) involves challenges in communication and social interaction, including challenges in recognizing emotions. Existing technological solutions aim to improve social behaviors in individuals with ASD by providing learning aids. This paper presents a real-time environmental translator designed to enhance social behaviors in individuals with ASD using sensory substitution.
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December 2024
Department of Neurology, Union Hospital of Jilin University, Changchun, 130000, China.
Alzheimer's disease (AD) is a severe neurodegenerative disease, and the most common type of dementia, with symptoms of progressive cognitive dysfunction and behavioral impairment. Studying the pathogenesis of AD and exploring new targets for the prevention and treatment of AD is a very worthwhile challenge. Accumulating evidence has highlighted the effects of fatty acid metabolism on AD.
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December 2024
Department of Pharmacology, University of the Basque Country, UPV/EHU, Sarriena S/N, 48940, Leioa, Bizkaia, Spain.
Cannabis use disorder affects up to 42% of individuals with schizophrenia, correlating with earlier onset, increased positive symptoms, and more frequent hospitalizations. This study employed an untargeted lipidomics approach to identify biomarkers in plasma samples from subjects with schizophrenia, cannabis use disorder, or both (dual diagnosis), aiming to elucidate the metabolic underpinnings of cannabis abuse and schizophrenia development. The use of liquid chromatography-high resolution mass spectrometry enabled the annotation of 119 metabolites, with the highest identification confidence level achieved for 16 compounds.
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December 2024
Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha'il, Ha'il, 81481, Saudi Arabia.
Alzheimer's disease (AD) is a brain disorder that causes memory loss and behavioral and thinking problems. The symptoms of Alzheimer's are similar throughout its development stages, which makes it difficult to diagnose manually. Therefore, artificial intelligence (AI) techniques address the limitations of manual diagnosis.
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