Read the passage and mark the letter A, B, C or D on your answer sheet to indicate the best answer to each of the following questions from 25 to 34.
[I] The accessibility and scalability of digital platforms can significantly lower barriers to mental health care and make it available to a broader population, according to tech researchers. Swept up by a wave of Generative AI, tech companies have been quick to capitalize. [II] Scores of new apps now offer automated counseling, where people can engage in cognitive behavioral therapy sessions-a psychotherapeutic treatment that is proven to assist users in identifying and changing negative thought patterns-with an AI chatbot. [III] The arrival of AI enables adaptive interventions and allows healthcare providers to continuously monitor patients, anticipate when someone may need support, and deliver treatments to alleviate symptoms. [IV]
It is not merely anecdotal. A systematic review of mental health chatbots found that AI chatbots could dramatically cut down symptoms of depression and distress, at least in the short term. Other studies have successfully detected early signs of major depressive disorder from unguarded facial expressions captured during routine phone unlocks and people's typing patterns. Most recently, researchers devised a way to identify suicidal behavior and thoughts without psychiatric records. Their AI model estimated self-harm likelihood in 92 out of 100 cases based on data from simple questionnaire responses and behavioral signals like ranking a random sequence of pictures. Specialists expect that once the model clears clinical trials, they will use it for support, such as scheduling patients depending on perceived urgency, and eventually roll it out to the public in at-home settings.
However, experts urge caution over treating tech solutions as a panacea since they lack the skill, training, and experience of human therapists. Generative AI can be highly unpredictable, fabricate information, and regurgitate deeply embedded societal biases. When a professional counselor tried a popular mental health chatbot to help explore a personal topic, the bot failed to pick up on the issue's nuances. It suggested he "stick to the facts" while removing the emotional content from his replies, advising him to reframe his negative thoughts as a positive. For human therapists, correcting or erasing emotions is counterproductive. They view their primary role as forming a relationship that can hold difficult emotions, making it easier for clients to explore, integrate, or find meaning in them and ultimately know themselves better.
Most therapists agree AI apps can be an ideal initial step in a person's mental health journey, but serious risks arise when they are treated as the sole solution. The consequences can be dire when vulnerable individuals exclusively depend on an AI chatbot; instances have already occurred where bots dispensed harmful advice or exacerbated psychological distress. Furthermore, algorithmic models trained on unchecked internet data often fail when applied to marginalized demographics. Until tech companies overcome these concerns, AI's best near-term use cases will likely be confined to administrative tasks like insurance and billing, ultimately allowing therapists to spend more genuine time with clients.
It is not merely anecdotal. A systematic review of mental health chatbots found that AI chatbots could dramatically cut down symptoms of depression and distress, at least in the short term. Other studies have successfully detected early signs of major depressive disorder from unguarded facial expressions captured during routine phone unlocks and people's typing patterns. Most recently, researchers devised a way to identify suicidal behavior and thoughts without psychiatric records. Their AI model estimated self-harm likelihood in 92 out of 100 cases based on data from simple questionnaire responses and behavioral signals like ranking a random sequence of pictures. Specialists expect that once the model clears clinical trials, they will use it for support, such as scheduling patients depending on perceived urgency, and eventually roll it out to the public in at-home settings.
However, experts urge caution over treating tech solutions as a panacea since they lack the skill, training, and experience of human therapists. Generative AI can be highly unpredictable, fabricate information, and regurgitate deeply embedded societal biases. When a professional counselor tried a popular mental health chatbot to help explore a personal topic, the bot failed to pick up on the issue's nuances. It suggested he "stick to the facts" while removing the emotional content from his replies, advising him to reframe his negative thoughts as a positive. For human therapists, correcting or erasing emotions is counterproductive. They view their primary role as forming a relationship that can hold difficult emotions, making it easier for clients to explore, integrate, or find meaning in them and ultimately know themselves better.
Most therapists agree AI apps can be an ideal initial step in a person's mental health journey, but serious risks arise when they are treated as the sole solution. The consequences can be dire when vulnerable individuals exclusively depend on an AI chatbot; instances have already occurred where bots dispensed harmful advice or exacerbated psychological distress. Furthermore, algorithmic models trained on unchecked internet data often fail when applied to marginalized demographics. Until tech companies overcome these concerns, AI's best near-term use cases will likely be confined to administrative tasks like insurance and billing, ultimately allowing therapists to spend more genuine time with clients.
Question 26. According to paragraph 2, how did the recent research model successfully estimate the likelihood of self-harm?
Question 26. According to paragraph 2, how did the recent research model successfully estimate the likelihood of self-harm?
Chọn một phương án bên dưới để kiểm tra đáp án ngay:
Đáp án chính thức: D
Hướng dẫn giải chi tiết
Đáp án: D. By analyzing responses to basic questionnaires and tracking behavioral signals.
- Đoạn 2 nêu rõ mô hình ước tính nguy cơ tự hại trong 92/100 trường hợp dựa trên “simple questionnaire responses” và “behavioral signals like ranking a random sequence of pictures”. D khớp trực tiếp.
- A trái với chi tiết “without psychiatric records”; B là một nghiên cứu khác về trầm cảm; C nói dữ liệu chỉ từ thử nghiệm lâm sàng, không đúng.
- Đoạn 2 nêu rõ mô hình ước tính nguy cơ tự hại trong 92/100 trường hợp dựa trên “simple questionnaire responses” và “behavioral signals like ranking a random sequence of pictures”. D khớp trực tiếp.
- A trái với chi tiết “without psychiatric records”; B là một nghiên cứu khác về trầm cảm; C nói dữ liệu chỉ từ thử nghiệm lâm sàng, không đúng.