Effectiveness and Safety of Using Chatbots to Improve Mental Health: Systematic Review and Meta-Analysis PMC

The bot also provides useful health advice and information about medicines, service providers, and doctors and is compatible with all popular platforms. Buoy Health offers an AI-powered health chatbot that supports self-diagnosis and connects patients to the right treatment endpoints at the right time based on self-reported symptoms. The company said more than 1 million Americans had used this platform to assess symptoms and seek help during the COVID-19 pandemic. Some patients need constant monitoring after treatment, and intelligent bots can be useful here too. Patients or their caregivers can enter information about their daily activities and health status into a database through chatbots, which the respective physicians can view to investigate the condition and take appropriate action.

• In September 2020, the THL released the mobile contact tracing app Koronavilkku,1 which can collaborate with Omaolo by sharing information and informing the app of positive test cases (THL 2020, p. 14).
• The technology helps clinicians categorize patients depending on how severe their conditions are.
• And while these tools’ rise in popularity can be accredited to the very nature of the COVID-19 pandemic, AI’s role in healthcare has been growing steadily on its own for years — and that’s anticipated to continue.

The dominos fall when chatbots push patients from traditional clinical face-to-face practice to more complicated automated systems. Furthermore, there are work-related and ethical standards in different fields, which have been developed through centuries or longer. For example, as Pasquale argued (2020, p. 57), in medical fields, science has made medicine and practices more reliable, and ‘medical boards developed standards to protect patients from quacks and charlatans’. Thus, one should be cautious when providing and marketing applications such as chatbots to patients. The application should be in line with up-to-date medical regulations, ethical codes and research data.

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Artificial intelligence chatbots based on large language models can pass medical exams but their diagnoses are often inaccurate. Yes, you can deliver an omnichannel experience to your patients, deploying to apps, such as Facebook Messenger, Intercom, Slack, SMS with Twilio, WhatsApp, Hubspot, WordPress, and more. Our seamless integrations can route patients to your telephony and interactive voice response (IVR) systems when they need them. New technologies may form new gatekeepers of access to specialty care or entirely usurp human doctors in many patient cases.

Regulatory standards have been developed to accommodate for rapid modifications and ensure the safety and effectiveness of AI technology, including chatbots. With the growing number of AI algorithms approved by the Food and Drug Administration, they opened public consultations for setting performance targets, monitoring performance, and reviewing when performance strays from preset parameters [102]. The American Medical Association has also adopted the Augmented Intelligence in Health Care policy for the appropriate integration of AI into health care by emphasizing the design approach and enhancement of human intelligence [109].

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Another ethical issue that is often noticed is that the use of technology is frequently overlooked, with mechanical issues being pushed to the front over human interactions. The effects that digitalizing healthcare can have on medical practice are especially concerning, especially on clinical decision-making in complex situations that have moral overtones. One stream of healthcare chatbot development focuses on deriving new knowledge from large datasets, such as scans. This is different from the more traditional image of chatbots that interact with people in real-time, using probabilistic scenarios to give recommendations that improve over time. In this review, the most popular databases in health and information technology were used to run the most sensitive search possible.

Pasquale pointed to an Australian study of 82 mobile apps ‘marketed to those suffering from bipolar disorder’, only to find out that ‘the apps were, in general, not in line with practice guidelines or established self-management principles’ (p. 57). The most famous chatbots currently in use are Siri, Alexa, Google Assistant, Cordana and XiaoIce. Two of the most popular chatbots used in health care are the mental health assistant Woebot and Omaolo, which is used in Finland. From the emergence of the first chatbot, ELIZA, developed by Joseph Weizenbaum (1966), chatbots have been trying to ‘mimic human behaviour in a text-based conversation’ (Shum et al. 2018, p. 10; Abd-Alrazaq et al. 2020).

Over the past few years, artificial intelligence (AI) has made significant advancements in the healthcare industry. One of the most prominent AI-powered tools is ChatGPT, a natural language processing model developed by OpenAI. Dr. Rachel Goodman and colleagues at Vanderbilt University investigated chatbox responses in a recent study in Jama. Their study tested ChatGPT-3.5 and the updated GPT-4 using 284 physician-prompted questions to determine accuracy, completeness, and consistency over time. I will analyze their findings and present the pros and cons of incorporating artificial intelligence chatboxes into the healthcare industry.

The follow-up periods were 2 weeks (6/12), 4 weeks (6/12), 6 weeks (1/12), and 12 weeks (1/12). Characteristics of the comparators and measured outcomes in each included study are presented in Multimedia Appendix 6. ChatGPT is capable of generating human-like responses to a wide range of queries, making it an ideal tool for healthcare applications. From personalized treatment plans to remote patient monitoring, ChatGPT is transforming the way healthcare providers deliver care to their patients. Many healthcare chatbots using artificial intelligence already exist in the healthcare industry. These include OneRemission, which helps cancer patients manage symptoms and side effects, and Ada Health, which assesses symptoms and creates personalized health information, among others.

Its algorithm has a function that recognizes spoken words and responds appropriately to them. Sensely processes the data and information when patients report their symptoms, chatbot in healthcare analyzes their condition, and proposes a diagnosis. There are countless cases where a digital personal assistant or chatbot can help doctors, patients, or their families.

Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact. One of the consequences can be the shift from operator to supervisor, that is, expert work becomes more about monitoring and surveillance than before (Zerilli et al. 2019). Thus, instead of only re-organising work, we are talking about systemic change (e.g. Simondon 2017), that is, change that pervades all parts of a system, taking into account the interrelationships and interdependencies among these parts. In these ethical discussions, technology use is frequently ignored, technically automated mechanical functions are prioritised over human initiatives, or tools are treated as neutral partners in facilitating human cognitive efforts.

Integrating a Medical Chatbot App in Ambulatory Care: Pros, Cons, and Use Cases

Physicians worry about how their patients might look up and try cures mentioned on dubious online sites, but with a chatbot, patients have a dependable source to turn to at any time. In the ever-changing world of technology, where innovation knows no limit, only a few things have evoked as much awe as the exponential growth of computing. The highly capable chips and accelerators of today have transformed the entire digital ecosystem, starting with artificial intelligence.

• Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias.
• This means that the systems’ behavior is hard to explain by merely looking inside, and understanding exactly how they are programmed is nearly impossible.
• An AI-driven chatbot can identify use cases by understanding users’ intent from their requests.
• It utilizes techniques like natural language processing and machine learning to tap into their learnings and deliver clear answers to varied questions in a conversational tone.
• Another app is Weight Mentor, which provides self-help motivation for weight loss maintenance and allows for open conversation without being affected by emotions [47].

Apps were also excluded if they were specific to an event (i.e., apps for conferences or marches). Chatbots can extract patient information by asking simple questions such as their name, address, symptoms, current doctor, and insurance details. The chatbots then, through EDI, store this information in the medical facility database to facilitate patient admission, symptom tracking, doctor-patient communication, and medical record keeping.

Engaging in open conversations about health with medical professionals can be challenging for individuals who anticipate encountering stigma or embarrassment upon revealing their symptoms and experiences of health. This predicament can lead to missed opportunities for early treatment, ultimately impacting overall health and well-being. By facilitating preliminary conversations about embarrassing and stigmatized symptoms, medical chatbots can play a pivotal role in influencing whether or not someone seeks medical guidance. This article discusses medical chatbots, underlining their potential to reshape the healthcare landscape. We address prevalent concerns and highlight recent research findings indicating that chatbots may encourage individuals with sensitive health issues to seek help sooner.