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1.
Risk Manag Healthc Policy ; 17: 1339-1348, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38799612

RESUMO

Mental health is an essential component of the health and well-being of a person and community, and it is critical for the individual, society, and socio-economic development of any country. Mental healthcare is currently in the health sector transformation era, with emerging technologies such as artificial intelligence (AI) reshaping the screening, diagnosis, and treatment modalities of psychiatric illnesses. The present narrative review is aimed at discussing the current landscape and the role of AI in mental healthcare, including screening, diagnosis, and treatment. Furthermore, this review attempted to highlight the key challenges, limitations, and prospects of AI in providing mental healthcare based on existing works of literature. The literature search for this narrative review was obtained from PubMed, Saudi Digital Library (SDL), Google Scholar, Web of Science, and IEEE Xplore, and we included only English-language articles published in the last five years. Keywords used in combination with Boolean operators ("AND" and "OR") were the following: "Artificial intelligence", "Machine learning", Deep learning", "Early diagnosis", "Treatment", "interventions", "ethical consideration", and "mental Healthcare". Our literature review revealed that, equipped with predictive analytics capabilities, AI can improve treatment planning by predicting an individual's response to various interventions. Predictive analytics, which uses historical data to formulate preventative interventions, aligns with the move toward individualized and preventive mental healthcare. In the screening and diagnostic domains, a subset of AI, such as machine learning and deep learning, has been proven to analyze various mental health data sets and predict the patterns associated with various mental health problems. However, limited studies have evaluated the collaboration between healthcare professionals and AI in delivering mental healthcare, as these sensitive problems require empathy, human connections, and holistic, personalized, and multidisciplinary approaches. Ethical issues, cybersecurity, a lack of data analytics diversity, cultural sensitivity, and language barriers remain concerns for implementing this futuristic approach in mental healthcare. Considering these sensitive problems require empathy, human connections, and holistic, personalized, and multidisciplinary approaches, it is imperative to explore these aspects. Therefore, future comparative trials with larger sample sizes and data sets are warranted to evaluate different AI models used in mental healthcare across regions to fill the existing knowledge gaps.

2.
Artigo em Inglês | MEDLINE | ID: mdl-38372895

RESUMO

Panic disorder (PD) is a severe anxiety disorder characterized by recurrent and unexpected panic attacks that cause intense distress. Despite the high prevalence of panic disorder and its significant impact on life, limited research has been conducted on its prevalence and their associated factors in Saudi Arabia. This study seeks to contribute to the understanding of PD among adults in Saudi Arabia by examining its prevalence and associated factors, using an online survey method. A validated questionnaire-based cross-sectional study was conducted targeting 1276 Saudi adults. Data were collected electronically via Google Forms from the eligible participants. The questionnaire comprised three sections: sociodemographic information, medical history, and a validated diagnostic tool for PD. The prevalence of PD among Saudi adults was 13.1%. Most individuals with PD experienced their first panic attack before the age of 18. Only 38.3% individuals with PD sought medical attention, and approximately one-third of those who sought help did not receive a diagnosis. Multiple logistic regression analysis revealed that significant risk factors for PD included being female; having chronic health problems, a comorbid psychiatric disorder, a high body mass index; and experiencing suicidal ideation (P < 0.05). The highest risk was associated with chronic diseases (adjusted odds ratio = 3.1, 95% confidence interval: 2.1-4.6). This study demonstrates that PD is a prevalent and debilitating mental health condition among Saudi Arabian adults. Non-mental health physicians should be aware of PD, as many cases remain undiagnosed.

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