Stigma is one of the chief reasons for treatment-avoidant behaviour among people with mental health conditions. Stigmatising attitudes are spread through multiple determinants, including but not limited to: (i) individual beliefs; (ii) interpersonal influences; (iii) local cultural values and (iv) shared culture such as depictions in television shows. Our research indicates that popular television shows are currently understudied vectors for narratives that alternately reify or debunk assumptions and stereotypes about people with mental health conditions. Although such shows are fictional, they influence perception by normalising 'common sense' assumptions over extended periods of time. Consequently, representations of patients, psychiatrists and treatments influence knowledge and understanding of mental health and treatment-seeking behaviour. While storytelling about sickness can inspire possibilities and bestow meaning on traumatic experiences, fictional narratives written without sufficient care can have the inverse effect of curtailing horizons and limiting expectations. Problematic portrayals of patients, mental health professionals and psychological interventions are often reductive and may increase stigma and prevent treatment-seeking behaviour. This article analyses the representation of hypnotherapy and electroconvulsive therapy (ECT) in Singaporean television dramas that attract a wide, mainstream audience. Our diverse team investigated dramas in all four of the official languages of Singapore: English, Mandarin Chinese, Bahasa Melayu and Tamil. We found that depictions of hypnotherapy tend to produce problematic images of mental health professionals as manipulative, able to read minds, engaging in criminal behaviour, lacking in compassion and self-interested. Meanwhile, representations of ECT typically focus on the fear and distress of the patient, and it is primarily depicted as a disciplinary tool rather than a safe and effective medical procedure for patients whose condition is severe and refractory to pharmacotherapy and behavioural interventions. These depictions have the potential to discourage treatment-seeking behaviour-when early intervention has found to be crucial-among vulnerable populations.
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http://dx.doi.org/10.1136/medhum-2023-012854 | DOI Listing |
The current study aims to determine how the interactions between practice (distributed/focused) and mental capacity (high/low) in the cloud-computing environment (CCE) affect the development of reproductive health skills and cognitive absorption. The study employed an experimental design, and it included a categorical variable for mental capacity (low/high) and an independent variable with two types of activities (distributed/focused). The research sample consisted of 240 students from the College of Science and College of Applied Medical Sciences at the University of Hail's.
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November 2024
Department of Toxicology, Drug Industry, Management and Legislation, Faculty of Pharmacy, "Victor Babeş" University of Medicine and Pharmacy, 2nd Eftimie Murgu Sq., 300041 Timişoara, Romania.
The COVID-19 outbreak, caused by the SARS-CoV-2 virus, was linked to significant neurological and psychiatric manifestations. This review examines the physiopathological mechanisms underlying these neuropsychiatric outcomes and discusses current management strategies. Primarily a respiratory disease, COVID-19 frequently leads to neurological issues, including cephalalgia and migraines, loss of sensory perception, cerebrovascular accidents, and neurological impairment such as encephalopathy.
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December 2024
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.
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December 2024
Instituto de Estudios de Género, Universidad Carlos III de Madrid, Calle Madrid, 126, 28903 Getafe, Spain.
Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In this sense, there are applications related to the safety and well-being of people (sexual assaults, gender-based violence, children and elderly abuse, mental health, etc.) that require even more improvements.
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December 2024
Abu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.
Electroencephalography (EEG) has emerged as a pivotal tool in both research and clinical practice due to its non-invasive nature, cost-effectiveness, and ability to provide real-time monitoring of brain activity. Wearable EEG technology opens new avenues for consumer applications, such as mental health monitoring, neurofeedback training, and brain-computer interfaces. However, there is still much to verify and re-examine regarding the functionality of these devices and the quality of the signal they capture, particularly as the field evolves rapidly.
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