Health care chatbots are becoming paramount tools in medical research and routine clinical care. Chatbots are defined as artificial intelligence systems which interact with users via text or spoken language, mimicking human behavior. Noteworthily, the interest in such automated systems was triggered by the Turin test, in which humans had to decide if they were talking to another human or a machine.
Since the development of the first health-related chatbot, ELIZA, in 1966, health care bots have evolved significantly. Today’s health care chatbots are not limited to constrained user input; they connect the information they receive with the ability to learn from past experiences (Laranjo et al., 2018). Smart conversational agents integrate machine learning, big data analytics, and natural language processing, which gives chatbots a human feel.
From providing medical information to facilitating insurance claims, health care chatbots offer a wide range of health-related services. Supported by the advancements in artificial intelligence and computing methods, health care chatbots facilitate automated processes and real-time communication. They can assist health professionals during medical visits, trigger positive behaviors in patients, and support users in their daily lives. Health care chatbots have the potential to transform digital and connected health practices worldwide, underpinning the phenomenon of digital trust.
Used by clinical neuropsychologists, and cognitive and developmental psychologists, the Corsi task is applicable in investigations of nonverbal short-term memory, gender differences, and developmental changes (Capitani et al. 1991; Isaacs & Vargha-Khadem, 1989; Orsini et al. 1986). It also assesses immediate nonverbal memory deficits (De Renzi et al. 1977; De Renzi & Nichelli, 1975; Morris et al., 1988), and clarifies visuospatial memory theoretical conceptions (Jones et al. 1995).
The Corsi task tests clinical populations that include patients with dementia, mental retardation, learning disability, Korsakoff, and other neurological problems. Unlike the conventional physical Corsi board, eCorsi is easy to install, set up, and use. Regarding reaction and span presentation, it is more accurate in determining the forward and backward spans.
Health care chatbots are complex intelligence systems that integrate artificial intelligence, natural language processes, and machine learning. Input can be oral and written; while the output can be oral, written, and visual. Technologies that support health care chatbots include a wide range of digital tools, such as software applications, web browsers, and SMS (Laranjo et al., 2018).
Note that dialogue initiative is one of the main characterizations of health care chatbots. In a systematic review, Laranjo and colleagues (2018) revealed that three types of dialogue initiatives exist. The system can lead the conversation; the user can initiate the talk; or mix. Note that the research team retrieved 1,513 citations, of which only 17 articles were identified as relevant and were included in the study. Also, chatbots can be task-oriented or purely conversational. Interestingly, task-oriented health care chatbots can initiate a conversation to collect health-related information to perform a given task (e.g., set an appointment).
Nevertheless, one of the main differences in health care chatbots comes down to dialogue management. Laranjo and colleagues (2018) found that finite-state, frame-based and agent-based platforms are the three leading types of dialogue management models. Finite-state models refer to an environment where the user engages in a dialogue consisting of pre-determined steps. In frame-based models, the dialogue is not pre-determined, but the outcome depends on the content of the user’s input. Note that such systems need input to perform a task. To set an example, health care chatbots can ask questions and collect information, which will facilitate their performance. Agent-based models, on the other hand, represent the most complex dialogue management platforms. The agent-based dialogue model is based on advanced communication and reasoning settings, which allows the system to evolve quickly. Interestingly, agent-based methods for dialogue management are trained via real human-computer dialogue and offer advanced speech recognition and task performance, as well as a human feel.
The combination of dialogue management models, initiatives, and architectures makes health care chatbots highly beneficial in medical practice and research. Chatbots can support both patients and clinicians across various settings. Some of the main areas of implication cover mental health, asthma, diabetes, cancer, pain monitoring, hypertension, and speech impairment (Laranjo et al., 2018). Health care chatbots can be employed to:
Health care chatbots can provide valuable medical information: With the increasing complexity of medical procedures and drug development, patients crave transparent information and personalized care. Health-care chatbots can help users obtain the information they need in real-time, 24/7. Chatbots can answer health-related questions and eliminate the need for calling a clinician. This aspect will benefit people with limited access to health care, such as those living in remote locations, patients with disabilities, and young users. Note that one of the major challenges in health care chatbot development comes down to the integration of accurate medical information. Because only validated information can improve patient health outcomes, users, IT specialists, and health professionals must collaborate to optimize chatbot performance.
Health care chatbots can improve the performance of repetitive tasks in medical research and routine clinical care: Health care chatbots can be used in systematic and repetitive tasks, such as booking appointments, checking insurance information, and providing medical information about drugs and health care specialists. In the field of pharmacology, for instance, chatbots can perform tasks on large databases and deliver information about automatic inventory management. As machines can compute operations fast, health care chatbots can eliminate additional delays and costs in medical research and care. In addition, health care chatbots can provide valuable insights into health care marketing.
Health care chatbots can assist health professionals across a wide range of settings and emergency care: Chatbots can support a wide range of medical services, such as presenting medical information, answering general information, and improving patient-doctor communication. An intelligent solution to a patient’s needs can facilitate routine clinical care and cut waiting times. To set an example, patients can book an appointment at their convenience and obtain information prior to their visit. Also, chatbots can be used for internal record-keeping, so health professionals won’t need to search in a patient record. By having vital patient data available in real-time, 24/7, clinicians can save valuable time and facilitate emergency health care.
Health care chatbots can improve patient outcomes and user experience: Health care chatbots can help patients record symptoms, track drug intake, take note of biometrics, book appointments, and provide companionship to older people. Interestingly, they become virtual companions which assist people in their daily lives. In hospitals, for instance, chatbots can suggest menus for patients with special diets or conditions (e.g., ostomy patients). As a patient’s health condition might be complex, health care chatbots can improve health outcomes in the long term (e.g., chronic therapies). What’s more, bots can help patients navigate through their health records and administrative needs (e.g., insurance claims) to empower their role in today’s medicine.
Health care chatbots can revolutionize digital health: Supported by artificial intelligence and natural language processing technology, chatbots can revolutionize digital health. Bots are able to report adverse effects and organize data gathered from clinical trials. To set an example, health care chatbots can help professionals take note of side effects in breastfeeding mothers and other vulnerable participants. Chatbots can be used to share health-related results across institutions, which can support medical device interoperability. Most of all, health care chatbots can empower patients and increase their participation in digital health.
From recruitment to informed consent practices, health care chatbots can provide digital solutions and a personalized feel all at the same time.
Health care chatbots can improve patient outcomes, especially in the field of mental health. They can provide medical information, trigger positive changes, improve medication adherence, and provide companionship. In a recent study, Fitzpatrick and colleagues found that health care chatbots are feasible, engaging, and effective digital tools to deliver cognitive behavioral therapy (CBT) (Fitzpatrick et al., 2017).
The research team developed an automated conversational agent, Woebot, designed to deliver cognitive behavioral therapy via daily messages and mood tracking. The chatbot was designed to deliver an emphatic response, tailored content, positive reinforcement, set goals, and visuals to facilitate personal reflection. In fact, Woebot integrated vital evidence-based recommendations for app development, such as the use of a cognitive-behavioral therapy framework, engaging interface, and reminders. Fitzpatrick and colleagues recruited 70 students (age 18-28); the subjects were randomized into two groups. The first group was assigned to two weeks of self-help delivered via a text-based conversational agent (n=34); the second group was an information-only control group (n=36). While participants in both groups experienced a significant decrease in anxiety, only the intervention group benefited in terms of a decrease in depression. An intent-to-treat univariate analysis of covariance showed that Woebot could reduce depression symptoms and trigger positive changes in users.
In fact, previous studies also show that humans and non-human systems can establish a therapeutic relationship, a phenomenon known as digital trust. Interestingly, due to the social stigma attached to mental illnesses, patients are more willing to share with a virtual agent instead of a human. Thus, health care chatbots can be highly beneficial across sensitive areas, such as addictions and mental health.
From e-banking to online booking, there’s no doubt chatbots are highly popular across industries and users worldwide. That said, there are several barriers to the successful development of chatbots in health care.
Health care chatbots are one of the most intriguing areas in digital health. Such artificial intelligence systems integrate machine learning, big data analytics, and natural language processing. With an impressive range of capabilities, health care chatbots are able to mimic human behavior, assist health professionals, and support patients in their daily lives. From logging data to boosting people’s well-being, health care chatbots can be applied across various medical settings. Chatbots can also decrease medical costs and improve health outcomes. In fact, data shows that the virtual health care market will generate more than $3.5 billion by 2022. Virtual consultations, mHealth apps, and health care chatbots are becoming leading tools in digital health.
Most of all, health care chatbots have the potential to revolutionize patient-centered care. Such software programs come with engaging reminders and interface, which provides a unique user experience. Health care chatbots can improve patient health outcomes, facilitate the performance of daily tasks, and provide companionship. Chatbots are highly beneficial in the field of mental health, for instance, because they erase the stigma attached to mental illnesses.
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