scholarly journals On How Chronic Conditions Affect the Patient-AI Interaction: A Literature Review

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 313
Author(s):  
Mohammed Tahri Sqalli ◽  
Dena Al-Thani
Keyword(s):  
Artificial Intelligence ◽  
Grounded Theory ◽  
Literature Review ◽  
Chronic Diseases ◽  
Chronic Conditions ◽  
Selection Process ◽  
System Development ◽  
Healthcare Providers ◽  
Health Coaching ◽  
Different Types

Background: Across the globe, managing chronic diseases has been recognized as a challenge for patients and healthcare providers. The state of the art in managing chronic conditions requires not only responding to the clinical needs of the patient, but also guaranteeing a comfortable state of wellbeing for them, despite living with the disease. This demands mutual effort between the patient and the physician in constantly collecting data, monitoring, and understanding the disease. The advent of artificial intelligence has made this process easier. However, studies have rarely attempted to analyze how the different artificial intelligence based health coaching systems are used to manage different types of chronic conditions. Objective: Throughout this grounded theory literature review, we aim to provide an overview for the features that characterize artificial intelligence based health coaching systems used by patients with chronic diseases. Methods: During our search and paper selection process process, we use three bibliographic libraries (PubMed, IEEE Xplore, and ACM Digital Library). Using the grounded theory, we extract overarching themes for the artificial intelligence based health coaching systems. These systems are then classified according to their role, platform, type of interaction with the patient, as well as targeted chronic conditions. Of 869 citations retrieved, 31 unique studies are included in this review. Results: The included studies assess 14 different chronic conditions. Common roles for AI-based health coaching systems are: developing adherence, informing, motivating, reminding, preventing, building a care network, and entertaining. Health coaching systems combine the aforementioned roles to cater to the needs of the patients. The combinations of these roles differ between multilateral, unilateral, opposing bilateral, complementing bilateral, one-role-missing, and the blurred role combinations. Conclusion: Clinical solutions and research related to artificial intelligence based health coaching systems are very limited. Clear guidelines to help develop artificial intelligence-based health coaching systems are still blurred. This grounded theory literature review attempted to shed the light on the research and development requirements for an effective health coaching system intended for patients with chronic conditions. Researchers are recommended to use this review to identify the most suitable role combination for an effective health coaching system development.

scholarly journals Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review

10.2196/20701 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e20701 ◽  
Author(s):  
Theresa Schachner ◽  
Roman Keller ◽  
Florian v Wangenheim
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Chronic Diseases ◽  
Language Processing ◽  
Systematic Literature Review ◽  
Chronic Conditions ◽  
Experimental Studies ◽  
Future Research ◽  
Conversational Agents ◽  
Quasi Experimental

Background A rising number of conversational agents or chatbots are equipped with artificial intelligence (AI) architecture. They are increasingly prevalent in health care applications such as those providing education and support to patients with chronic diseases, one of the leading causes of death in the 21st century. AI-based chatbots enable more effective and frequent interactions with such patients. Objective The goal of this systematic literature review is to review the characteristics, health care conditions, and AI architectures of AI-based conversational agents designed specifically for chronic diseases. Methods We conducted a systematic literature review using PubMed MEDLINE, EMBASE, PyscInfo, CINAHL, ACM Digital Library, ScienceDirect, and Web of Science. We applied a predefined search strategy using the terms “conversational agent,” “healthcare,” “artificial intelligence,” and their synonyms. We updated the search results using Google alerts, and screened reference lists for other relevant articles. We included primary research studies that involved the prevention, treatment, or rehabilitation of chronic diseases, involved a conversational agent, and included any kind of AI architecture. Two independent reviewers conducted screening and data extraction, and Cohen kappa was used to measure interrater agreement.A narrative approach was applied for data synthesis. Results The literature search found 2052 articles, out of which 10 papers met the inclusion criteria. The small number of identified studies together with the prevalence of quasi-experimental studies (n=7) and prevailing prototype nature of the chatbots (n=7) revealed the immaturity of the field. The reported chatbots addressed a broad variety of chronic diseases (n=6), showcasing a tendency to develop specialized conversational agents for individual chronic conditions. However, there lacks comparison of these chatbots within and between chronic diseases. In addition, the reported evaluation measures were not standardized, and the addressed health goals showed a large range. Together, these study characteristics complicated comparability and open room for future research. While natural language processing represented the most used AI technique (n=7) and the majority of conversational agents allowed for multimodal interaction (n=6), the identified studies demonstrated broad heterogeneity, lack of depth of reported AI techniques and systems, and inconsistent usage of taxonomy of the underlying AI software, further aggravating comparability and generalizability of study results. Conclusions The literature on AI-based conversational agents for chronic conditions is scarce and mostly consists of quasi-experimental studies with chatbots in prototype stage that use natural language processing and allow for multimodal user interaction. Future research could profit from evidence-based evaluation of the AI-based conversational agents and comparison thereof within and between different chronic health conditions. Besides increased comparability, the quality of chatbots developed for specific chronic conditions and their subsequent impact on the target patients could be enhanced by more structured development and standardized evaluation processes.

scholarly journals Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Theresa Schachner ◽  
Roman Keller ◽  
Florian von Wangenheim
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Chronic Diseases ◽  
Language Processing ◽  
Systematic Literature Review ◽  
Chronic Conditions ◽  
Experimental Studies ◽  
Future Research ◽  
Conversational Agents ◽  
Quasi Experimental

BACKGROUND A rising number of conversational agents or chatbots are equipped with artificial intelligence (AI) architecture. They are increasingly prevalent in health care applications such as those providing education and support to patients with chronic diseases, one of the leading causes of death in the 21st century. AI-based chatbots enable more effective and frequent interactions with such patients. OBJECTIVE The goal of this systematic literature review is to review the characteristics, health care conditions, and AI architectures of AI-based conversational agents designed specifically for chronic diseases. METHODS We conducted a systematic literature review using PubMed MEDLINE, EMBASE, PyscInfo, CINAHL, ACM Digital Library, ScienceDirect, and Web of Science. We applied a predefined search strategy using the terms “conversational agent,” “healthcare,” “artificial intelligence,” and their synonyms. We updated the search results using Google alerts, and screened reference lists for other relevant articles. We included primary research studies that involved the prevention, treatment, or rehabilitation of chronic diseases, involved a conversational agent, and included any kind of AI architecture. Two independent reviewers conducted screening and data extraction, and Cohen kappa was used to measure interrater agreement.A narrative approach was applied for data synthesis. RESULTS The literature search found 2052 articles, out of which 10 papers met the inclusion criteria. The small number of identified studies together with the prevalence of quasi-experimental studies (n=7) and prevailing prototype nature of the chatbots (n=7) revealed the immaturity of the field. The reported chatbots addressed a broad variety of chronic diseases (n=6), showcasing a tendency to develop specialized conversational agents for individual chronic conditions. However, there lacks comparison of these chatbots within and between chronic diseases. In addition, the reported evaluation measures were not standardized, and the addressed health goals showed a large range. Together, these study characteristics complicated comparability and open room for future research. While natural language processing represented the most used AI technique (n=7) and the majority of conversational agents allowed for multimodal interaction (n=6), the identified studies demonstrated broad heterogeneity, lack of depth of reported AI techniques and systems, and inconsistent usage of taxonomy of the underlying AI software, further aggravating comparability and generalizability of study results. CONCLUSIONS The literature on AI-based conversational agents for chronic conditions is scarce and mostly consists of quasi-experimental studies with chatbots in prototype stage that use natural language processing and allow for multimodal user interaction. Future research could profit from evidence-based evaluation of the AI-based conversational agents and comparison thereof within and between different chronic health conditions. Besides increased comparability, the quality of chatbots developed for specific chronic conditions and their subsequent impact on the target patients could be enhanced by more structured development and standardized evaluation processes.

scholarly journals A systematic literature review of the assessment of treatment burden experienced by patients and their caregivers

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Orla C. Sheehan ◽  
Bruce Leff ◽  
Christine S. Ritchie ◽  
Sarah K. Garrigues ◽  
Lingsheng Li ◽  
...  
Keyword(s):  
New York ◽  
Literature Review ◽  
Chronic Conditions ◽  
Grey Literature ◽  
Healthcare Providers ◽  
Assessment Method ◽  
Cochrane Library ◽  
York Academy ◽  
Multiple Chronic Conditions ◽  
Treatment Burden

Abstract Background Many older adults with multiple chronic conditions, particularly those who are functionally impaired, spend considerable time juggling the competing demands of managing their conditions often assisted by caregivers. We examined methods of assessing the treatment burden experienced by this population as a first step to identifying strategies to reduce it. Methods Systematic searches were performed of the peer-reviewed and grey-literature (PubMed, Cochrane library, CINAHL, EMBASE, Web of Science, SCOPUS, New York Academy of Medicine Grey Literature Review, NLM catalog and ProQuest Digital Theses and Dissertations). After title and abstract screening, both qualitative and quantitative articles describing approaches to assessment of treatment burden were included. Results Forty-five articles from the peer reviewed and three items from the grey literature were identified. Most articles (34/48) discussed treatment burden associated with a specific condition. All but one examined the treatment burden experienced by patients and six addressed the treatment burden experienced by caregivers. Qualitative studies revealed many aspects of treatment burden including the burdens of understanding the condition, juggling, monitoring and adjusting treatments, efforts to engage with others for support as well as financial and time burdens. Many tools to assess treatment burden in different populations were identified through the qualitative data. The most commonly used instrument was the Treatment Burden Questionnaire. Conclusions Many instruments are available to assess treatment burden, but no one standardized assessment method was identified. Few articles examined approaches to measuring the treatment burden experienced by caregivers. As people live longer with more chronic conditions healthcare providers need to identify patients and caregivers burdened by treatment and engage in approaches to ameliorate treatment burden. A standard and validated assessment method to measure treatment burden in the clinical setting would help to enhance the care of people with multiple chronic conditions, allow comparison of different approaches to reducing treatment burden, and foster ongoing evaluation and monitoring of burden across conditions, patient populations, and time.

Morbidity profile of patients seeking Naturopathy and Yoga treatment in South India: A descriptive study

2020 ◽  
Vol 17 (3) ◽  
Author(s):  
Naresh Kumar Panneerselvam ◽  
Dhilip Ravindran ◽  
Arunthathi Kathiresan
Keyword(s):  
Chronic Diseases ◽  
Chronic Conditions ◽  
South India ◽  
Descriptive Study ◽  
Treatment Seeking ◽  
Duration Of Treatment ◽  
Different Types ◽  
Seeking Behavior ◽  
And Gender

AbstractBackgroundYoga and Naturopathy (Y&N) is one of the approved Complementary and Traditional systems of Medicine practiced in India. Unlike other systems, it is a drugless system aimed to optimize and facilitate the inherent ability of the human body to heal itself. There is lack of literature on the type of patients seeking Yoga and Naturopathy treatments in India. This study was designed with an objective to assess the morbidity profile of the in-patients treated in a Naturopathy and Yoga hospital.MethodsDescriptive study design based on clinical case records. Six hundred and four cases treated as in-patients between April 2017 and July 2018 was analyzed.ResultsThe average age of the patients was 47.4 (SD ± 16.1) years, with 56% were females and 44% males. About 50 different types of morbidity ranging from general rejuvenation to chronic diseases had been reported. Highest reported diseases were chronic in nature, with higher reporting for multiple system morbidity, followed by Obesity, Diabetes Mellitus, Hypertension, Arthritis, and Back pain. Variations were observed in the morbidities based on age and gender of the patients. The median duration of treatment was 8 days.ConclusionsPatients seek Yoga & Naturopathy care mainly for chronic conditions, further observations on treatment outcomes, quality of life, and treatment seeking behavior can be explored for the efficacy and feasibility of Yoga & Naturopathy care in managing chronic diseases.

Barriers to, and enablers of, use of information and communication technology (ICT) for supporting the care of chronic diseases of ageing: a systematic scoping review (Preprint)

2020 ◽  
Author(s):  
Sojib Bin Zaman ◽  
Raihan Kabir Khan ◽  
Roger G. Evans ◽  
Amanda G. Thrift ◽  
Ralph Maddison ◽  
...  
Keyword(s):  
Older Adults ◽  
Chronic Diseases ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Scoping Review ◽  
Chronic Conditions ◽  
Healthcare Providers ◽  
Health Technologies ◽  
Positive Effects ◽  
Information And Communication

BACKGROUND Information and communication technology (ICT) offer considerable potential for supporting older adults to manage their health, including chronic health conditions. However, there are mixed opinions about the benefits and effectiveness of using ICT in healthcare for older adults. OBJECTIVE We aimed to (i) map the use of ICT for the management of chronic diseases in older adults, and (ii) identify barriers to, and challenges for, its use among older adults. METHODS A scoping review was conducted using four databases (Ovid Medline, Embase, Scopus, and PsycInfo) to identify eligible articles from January 2000 to July 2020. Publications incorporating the use of ICT (e-health, mHealth, telehealth, decision support systems, remote monitoring, and mobile apps) in people aged >55 years with chronic conditions were included. We conducted a ‘strengths, weaknesses, opportunities, and threats (SWOT)’ framework analysis to explore implied enablers of, and barriers to, using ICT in healthcare. RESULTS Of the 286 articles identified, 23 articles (n=4122 participants) met the inclusion criteria. A range of technologies were reported, including: electronic Health (n=5), mobile Health (n=6), telehealth (n=6); mobile applications (n=2), or mixed ICT platforms (n=4). The range of chronic conditions included congestive heart failure (n=9), diabetes (n=7), chronic respiratory disease (n=6), and mental health (n=5). ICT initiatives were all designed to help people self-manage chronic diseases with minimal support from healthcare providers or clinics. Among all the included studies, ICT demonstrated positive effects. Investigators highlighted operational and implementation challenges for integrating health ICT systems in routine practices. Barriers to using ICT in older adults included knowledge gap, lack of willingness to adopt new skills, and reluctance to use health technologies. ICT implementation-related challenges such as slow internet connectivity and lack of the appropriate reimbursement policy were reported. We also identified a list of enablers for using ICT, which could help design mitigation strategies. CONCLUSIONS ICT has the potential to support the care of chronic diseases among older adults, but its integration with routine healthcare is lacking. There is a need to improve awareness and education about ICT among those who could benefit from such initiatives, including older adults, caregivers, and healthcare providers. For promoting ICT adoption, more sustainable funding is required. We recommend involving clinicians and caregivers at the time of designing ICT initiatives. CLINICALTRIAL Not applicable

Exploratory Analysis in Information Systems Area

2020 ◽  
pp. 53-76
Keyword(s):  
Grounded Theory ◽  
Information Systems ◽  
Software Engineering ◽  
Literature Review ◽  
System Development ◽  
High Accuracy ◽  
Research Data ◽  
Exploratory Analysis ◽  
Data Sampling ◽  
Is Research

Providing an overview of grounded theory (GT)'s approaches to information systems (IS) research to IS researchers who are now interested in applying GT is the goal of the chapter. Also, research contributions about the application of GT in IS, qualitative perspectives on IS research, the types of GT approaches used in IS research, and the GT study guidelines in IS are presented in this chapter. Examples of GT in IS research, which provide a description of the methodology and references to more detailed presentations, are also included, especially from the field of software engineering and system development. It should be noted that using the GT methodology is time consuming and requires high accuracy, and it starts with a phenomenon that the researcher finds is not well explained by existing theories. In such research, data sampling should provide a broad, in-depth, and pluralist view of the phenomenon under study, and a literature review on the phenomenon should be provided.

scholarly journals Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review

JAMIA Open ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 459-471
Author(s):  
Avishek Choudhury ◽  
Emily Renjilian ◽  
Onur Asan
Keyword(s):  
Machine Learning ◽  
Health Care ◽  
Literature Review ◽  
Chronic Diseases ◽  
Systematic Literature Review ◽  
Chronic Conditions ◽  
Clinical Care ◽  
Psychological Disorder ◽  
Multiple Chronic Conditions ◽  
Health Care Applications

Abstract Objectives Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients’ (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine learning (ML), in geriatric clinical care for chronic diseases. Materials and Methods We restricted our search to eight databases, namely PubMed, WorldCat, MEDLINE, ProQuest, ScienceDirect, SpringerLink, Wiley, and ERIC, to analyze research articles published in English between January 2010 and June 2019. We focused on studies that used ML algorithms in the care of geriatrics patients with chronic conditions. Results We identified 35 eligible studies and classified in three groups: psychological disorder (n = 22), eye diseases (n = 6), and others (n = 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications. Conclusion More studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.

Isolation and Diagnosis of Fungi from Samples of Spices in the City of Nasiriya

2020 ◽  
pp. 7-9
Keyword(s):  
Chronic Diseases ◽  
Dilution Method ◽  
Local Markets ◽  
White Pepper ◽  
Black And White ◽  
Different Types ◽  
Potential Risks ◽  
The City ◽  
Isolated Species

Examination of (35) samples of spices obtained from local markets for the purposes of isolating and diagnosing fungi growing on them. Anine isolates belonging to 13 different types of fungi were diagnosed by the standard dilution method with three replications, and it has been observed that the most samples from which the fungi were isolated is ginger. It was found that the most isolated species of fungi are Penicillium, Aspergillus, and Rizupes spp. A rare colony of fungi was observed, which indicates contamination of the spices under study with the fungus. The present study aims to identify the potential risks of the presence of fungi in spices and what may result from mycotoxins that may be the cause of many chronic diseases as a result of using these spices in large quantities. The study recommends limiting the use of contaminated spices, especially ginger, in preparing food and its uses, in addition to other types such as cloves, black and white pepper, and other types of spices found in the local markets, especially the expired ones.

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

scholarly journals Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Cultural Heritage ◽  
Conceptual Framework ◽  
Interaction Design ◽  
Participatory Design ◽  
Future Directions ◽  
Heritage Sites ◽  
Review Analysis

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.

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