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1.
Med Arch ; 75(1): 50-55, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-34012200

RESUMO

Background: Consumers' willingness to use health chatbots can eventually determine if the adoption of health chatbots will succeed in delivering healthcare services for combating COVID-19. However, little research to date has empirically explored influential factors of consumer willingness toward using these novel technologies, and the effect of individual differences in predicting this willingness. Objectives: This study aims to explore (a) the influential factors of consumers' willingness to use health chatbots related to COVID-19, (b) the effect of individual differences in predicting willingness, and (c) the likelihood of using health chatbots in the near future as well as the challenges/barriers that could hinder peoples' motivations. Methods: An online survey was conducted which comprised of two sections. Section one measured participants' willingness by evaluating the following six factors: performance efficacy, intrinsic motivation, anthropomorphism, social influence, facilitating conditions, and emotions. Section two included questions on demographics, the likelihood of using health chatbots in the future, and concerns that could impede such motivation. Results: A total of 166 individuals provided complete responses. Although 40% were aware of health chatbots and only 24% had used them before, about 84% wanted to use health chatbots in the future. The strongest predictors of willingness to use health chatbots came from the intrinsic motivation factor whereas the next strongest predictors came from the performance efficacy factor. Nearly 39.5% of participants perceived health chatbots to have human-like features such as consciousness and free will, but no emotions. About 38.4% were uncertain about the ease of using health chatbots. Conclusion: This study contributes toward theoretically understanding factors influencing peoples' willingness to use COVID-19-related health chatbots. The findings also show that the perception of chatbots' benefits outweigh the challenges.


Assuntos
Inteligência Artificial/estatística & dados numéricos , Atitude Frente a Saúde , COVID-19/prevenção & controle , Comportamento do Consumidor/estatística & dados numéricos , Telemedicina/estatística & dados numéricos , Adulto , COVID-19/epidemiologia , Humanos , Masculino , Mídias Sociais , Percepção Social , Inquéritos e Questionários
2.
JMIR Mhealth Uhealth ; 9(3): e24322, 2021 03 02.
Artigo em Inglês | MEDLINE | ID: mdl-33626017

RESUMO

BACKGROUND: Mobile phone apps have been leveraged to combat the spread of COVID-19. However, little is known about these technologies' characteristics, technical features, and various applications in health care when responding to this public health crisis. The lack of understanding has led developers and governments to make poor choices about apps' designs, which resulted in creating less useful apps that are overall less appealing to consumers due to their technical flaws. OBJECTIVE: This review aims to identify, analyze, and categorize health apps related to COVID-19 that are currently available for consumers in app stores; in particular, it focuses on exploring their key technical features and classifying the purposes that these apps were designed to serve. METHODS: A review of health apps was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The Apple Store and Google Play were searched between April 20 and September 11, 2020. An app was included if it was dedicated for this disease and was listed under the health and medical categories in these app stores. The descriptions of these apps were extracted from the apps' web pages and thematically analyzed via open coding to identify both their key technical features and overall purpose. The characteristics of the included apps were summarized and presented with descriptive statistics. RESULTS: Of the 298 health apps that were initially retrieved, 115 met the inclusion criteria. A total of 29 technical features were found in our sample of apps, which were then categorized into five key purposes of apps related to COVID-19. A total of 77 (67%) apps were developed by governments or national authorities and for the purpose of promoting users to track their personal health (9/29, 31%). Other purposes included raising awareness on how to combat COVID-19 (8/29, 27%), managing exposure to COVID-19 (6/29, 20%), monitoring health by health care professionals (5/29, 17%), and conducting research studies (1/29, 3.5%). CONCLUSIONS: This study provides an overview and taxonomy of the health apps currently available in the market to combat COVID-19 based on their differences in basic technical features and purpose. As most of the apps were provided by governments or national authorities, it indicates the essential role these apps have as tools in public health crisis management. By involving most of the population in self-tracking their personal health and providing them with the technology to self-assess, the role of these apps is deemed to be a key driver for a participatory approach to curtail the spread of COVID-19. Further effort is required from researchers to evaluate these apps' effectiveness and from governmental organizations to increase public awareness of these digital solutions.


Assuntos
COVID-19/prevenção & controle , Busca de Comunicante/métodos , Aplicativos Móveis , Pandemias/prevenção & controle , Humanos , SARS-CoV-2 , Autocuidado , Tecnologia
3.
Int J Med Inform ; 146: 104362, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33360116

RESUMO

BACKGROUND: Determining the key sets of competencies necessary for a Health Informatics (HI) professional to practice effectively either solo or as a member of a multidisciplinary team has been challenging for the regulator and registration body responsible for the healthcare workforce in Saudi Arabia, which is the Saudi Commission for Health Specialties (SCFHS). OBJECTIVE: The aim of this study was to develop a HI competency framework to guide SCFHS to introduce a HI certification program that meets local healthcare needs and is aligned with the national digital health transformation strategy. METHODOLOGY: A two-phase mixed methods approach was used in this study. For phase 1, a scoping review was conducted to identify HI competencies that have been published in the relevant literature. Out of a total 116 articles found relevant, 20 were included for further analysis. For phase 2, Saudi HI stakeholders (N = 24) that included HI professionals, administrators, academics, and healthcare professionals were identified and participated in an online survey, and asked to rank the importance of HI competencies distinguished in phase 1. To further validate and contextualize the competency framework, multiple focus groups and expert panel meetings were undertaken with the key stakeholders. RESULTS: For phase 1, about 1315 competencies were initially extracted from the included studies. After iterative reviews and refinements of codes and themes, 6 preliminary domains, 23 sub-domains and 152 competencies were identified. In phase 2, a total of 24 experts participated in the online surveys and ranked 58 out of 152 competencies as 'very important/required', each received 75 % or more of votes. The remaining competencies (N = 94) were included in a list for a further discussion in the focus groups. A Total of fourteen HI experts accepted and joined in the focus groups. The multiphase approach resulted in a competency framework that included 92 competencies, that were grouped into 6 domains and 22 subdomains. The six key domains are: Core Principles; Information and Communication Technology (ICT); Health Sciences; Health Data Analytics; Education and Research; Leadership and Management. CONCLUSION: The study developed the Saudi Health Informatics Competency Framework (SHICF) that is based on an iterative, evidence-based approach, with validation from key stakeholders. Future work should continue the validation, review, and development of the framework with continued collaboration from relevant stakeholders representing both the healthcare and educational communities. We anticipate that this work will be expanded and adopted by relative professional and scientific bodies in the Gulf Cooperation Council (GCC) region.


Assuntos
Informática Médica , Pessoal de Saúde , Humanos , Tecnologia da Informação , Liderança , Arábia Saudita
4.
Acta Inform Med ; 28(3): 218-223, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-33417645

RESUMO

Introduction: Health chatbots are increasingly being utilized in healthcare to combat COVID-19. However, few studies have explored the perception and willingness of end-users toward COVID-19-related chatbots. Furthermore, no studies have been conducted in Saudi Arabia. Aim: This paper explored 166 end-users' perceived utilities of health chatbots in Saudi Arabia, and how their characteristics affect their perceptions. Methods: We conducted a quantitative descriptive study by implementing an online survey. The survey asked 20 questions on participants' demographics and their perception of health chatbots' usefulness. Results: We found that users were more willing to use health chatbots to seek general information about COVID-19 (82.5%) over seeking information regarding COVID-19 medical treatments (72.3%). Furthermore, participants with undergraduate degrees tend to use them to learn how to prevent COVID-19's spread (P = 0.015), to self-track COVID-19 symptoms (P = 0.028), and to seek information about medication (P = 0.035) in comparison to those who had postgraduate degrees. Participants who frequently searched for health information on the internet were more likely to look for nearby medical services using health chatbots (P = 0.023). Lastly, participants who provided any sort of healthcare services information were more likely to self-assess COVID-19 symptoms by using health chatbots (P = 0.036). Conclusion: Participant awareness and use of health chatbots were low; however, most had positive perceptions of these emerging technologies and displayed willingness to use them. Further research is needed to capture the real-world usability of these novel technologies by employing more rigid methodological designs (e.g, field trials).

5.
Stud Health Technol Inform ; 264: 1101-1105, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31438095

RESUMO

In 2018, the Saudi Commission for Health Specialties (SCFHS) created a national working group composed of key health informatics (HI) professionals, researchers and educators tasked with the development of a draft competency framework for Saudi HI professionals. Over an eight-month period, the research group collected data obtained from literature sources (both academic and grey), international competency standards, participant surveys, focus groups, and expert panel reviews. Through multiple rounds of discussions and graphic visualisation of the information collected using Microsoft PowerPoint and flip charts, the data were summarised and a visual representation of the proposed SHICF was developed. The result of this effort was the development of the first Saudi Health Informatics Competency Framework (SHICF). This paper provides a comparative assessment between the Saudi HI competency framework development and that of other internationally recognised HI competency development frameworks. Challenges related to the development of the SHICF are also discussed.


Assuntos
Informática Médica , Pessoal de Saúde , Humanos , Arábia Saudita , Inquéritos e Questionários
6.
J Med Internet Res ; 19(11): e378, 2017 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-29101092

RESUMO

BACKGROUND: The use of wearable tools for health self-quantification (SQ) introduces new ways of thinking about one's body and about how to achieve desired health outcomes. Measurements from individuals, such as heart rate, respiratory volume, skin temperature, sleep, mood, blood pressure, food consumed, and quality of surrounding air can be acquired, quantified, and aggregated in a holistic way that has never been possible before. However, health SQ still lacks a formal common language or taxonomy for describing these kinds of measurements. Establishing such taxonomy is important because it would enable systematic investigations that are needed to advance in the use of wearable tools in health self-care. For a start, a taxonomy would help to improve the accuracy of database searching when doing systematic reviews and meta-analyses in this field. Overall, more systematic research would contribute to build evidence of sufficient quality to determine whether and how health SQ is a worthwhile health care paradigm. OBJECTIVE: The aim of this study was to investigate a sample of SQ tools and services to build and test a taxonomy of measurements in health SQ, titled: the classification of data and activity in self-quantification systems (CDA-SQS). METHODS: Eight health SQ tools and services were selected to be examined: Zeo Sleep Manager, Fitbit Ultra, Fitlinxx Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, and uBiome. An open coding analytical approach was used to find all the themes related to the research aim. RESULTS: This study distinguished three types of measurements in health SQ: body structures and functions, body actions and activities, and around the body. CONCLUSIONS: The CDA-SQS classification should be applicable to align health SQ measurement data from people with many different health objectives, health states, and health conditions. CDA-SQS is a critical contribution to a much more consistent way of studying health SQ.


Assuntos
Classificação/métodos , Atenção à Saúde/métodos , Humanos , Autocuidado
7.
Methods Inf Med ; 56(1): 46-54, 2017 Jan 09.
Artigo em Inglês | MEDLINE | ID: mdl-27523820

RESUMO

BACKGROUND: Questions like 'How is your health? How are you feeling? How have you been?' now can be answered in a different way due to innovative health self-quantification apps and devices. These apps and devices generate data that enable individuals to be informed and more responsible about their own health. OBJECTIVES: The aim of this paper is to review studies on health SQ, firstly, exploring the concepts that are associated with the users' interaction with and around data for managing health; and secondly, the potential benefits and challenges that are associated with the use of such data to maintain or promote health, as well as their impact on the users' certainty or confidence in taking effective actions upon such data. METHODS: To answer these questions, we conducted a comprehensive literature review to build our study sample. We searched a number of electronic bibliographic databases including Scopus, Web of Science, Medline, and Google Scholar. Thematic analysis was conducted for each study to find all the themes that are related to our research aims. RESULTS: In the reviewed literature, conceptualisation of health SQ is messy and inconsistent. Personal tracking, personal analytics, personal experimentation, and personal health activation are different concepts within the practice of health SQ; thus, a new definition and structure is proposed to set out boundaries between them. Using the data that are generated by SQS for managing health has many advantages but also poses many challenges. CONCLUSIONS: Inconsistency in conceptualisation of health SQ - as well as the challenges that users experience in health self-management - reveal the need for frameworks that can describe the users' health SQ practice in a holistic and consistent manner. Our ongoing work toward developing these frameworks will help researchers in this domain to gain better understanding of this practice, and will enable more systematic investigations which are needed to improve the use of SQS and their data in health self-management.


Assuntos
Saúde , Autocuidado , Comunicação , Humanos
8.
Methods Inf Med ; 56(1): 40-45, 2017 Jan 09.
Artigo em Inglês | MEDLINE | ID: mdl-27782291

RESUMO

OBJECTIVES: The availability of internet-connected mobile, wearable and ambient consumer technologies, direct-to-consumer e-services and peer-to-peer social media sites far outstrips evidence about the efficiency, effectiveness and efficacy of using them in healthcare applications. The aim of this paper is to describe one approach to build a program of health informatics research, so as to generate rich and robust evidence about health data and information processing in self-quantification and associated healthcare and health outcomes. METHODS: The paper summarises relevant health informatics research approaches in the literature and presents an example of developing a program of research in the Health and Biomedical Informatics Centre (HaBIC) at the University of Melbourne. The paper describes this program in terms of research infrastructure, conceptual models, research design, research reporting and knowledge sharing. RESULTS: The paper identifies key outcomes from integrative and multiple-angle approaches to investigating the management of information and data generated by use of this Centre's collection of wearable, mobiles and other devices in health self-monitoring experiments. These research results offer lessons for consumers, developers, clinical practitioners and biomedical and health informatics researchers. CONCLUSIONS: Health informatics is increasingly called upon to make sense of emerging self-quantification and other digital health phenomena that are well beyond the conventions of healthcare in which the field of informatics originated and consolidated. To make a substantial contribution to optimise the aims, processes and outcomes of health self-quantification needs further work at scale in multi-centre collaborations for this Centre and for health informatics researchers generally.


Assuntos
Atenção à Saúde , Informática Médica , Pesquisa , Humanos
9.
J Med Internet Res ; 18(5): e131, 2016 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-27234343

RESUMO

BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a formal framework for describing the self-quantifiers' activities and their contextual components or constructs to pursue these health related goals. Establishing such framework is important because it is the first step to operationalize health SQ fully. This may in turn help to achieve the aims of health professionals and researchers who seek to make or study changes in the self-quantifiers' health systematically. OBJECTIVE: The aim of this study was to review studies on health SQ in order to answer the following questions: What are the general features of the work and the particular activities that self-quantifiers perform to achieve their health objectives? What constructs of health SQ have been identified in the scientific literature? How have these studies described such constructs? How would it be possible to model these constructs theoretically to characterize the work of health SQ? METHODS: A systematic review of peer-reviewed literature was conducted. A total of 26 empirical studies were included. The content of these studies was thematically analyzed using Activity Theory as an organizing framework. RESULTS: The literature provided varying descriptions of health SQ as data-driven and objective-oriented work mediated by SQ tools. From the literature, we identified two types of SQ work: work on data (ie, data management activities) and work with data (ie, health management activities). Using Activity Theory, these activities could be characterized into 6 constructs: users, tracking tools, health objectives, division of work, community or group setting, and SQ plan and rules. We could not find a reference to any single study that accounted for all these activities and constructs of health SQ activity. CONCLUSIONS: A Health Self-Quantification Activity Framework is presented, which shows SQ tool use in context, in relation to the goals, plans, and competence of the user. This makes it easier to analyze issues affecting SQ activity, and thereby makes it more feasible to address them. This review makes two significant contributions to research in this field: it explores health SQ work and its constructs thoroughly and it adapts Activity Theory to describe health SQ activity systematically.


Assuntos
Atividades Cotidianas/classificação , Comportamentos Relacionados com a Saúde , Feminino , Humanos , Masculino , Modelos Teóricos
10.
Stud Health Technol Inform ; 216: 333-7, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26262066

RESUMO

Current self-quantification systems (SQS) are limited in their ability to support the acquisition of health-related information essential for individuals to make informed decisions based on their health status. They do not offer services such as data handling and data aggregation in a single place, and using multiple types of tools for this purpose complicates data and health self-management for self-quantifiers. An online survey was used to elicit information from self-quantifiers about the methods they used to undertake key activities related to health self-management. This paper provides empirical evidence about self-quantifiers' time spent using different data collection, data handling, data analysis, and data sharing tools and draws implications for health self-management activities.


Assuntos
Informação de Saúde ao Consumidor/estatística & dados numéricos , Internet/estatística & dados numéricos , Participação do Paciente/estatística & dados numéricos , Autocuidado/estatística & dados numéricos , Software/estatística & dados numéricos , Gerenciamento do Tempo/organização & administração , Internacionalidade , Inquéritos e Questionários , Revisão da Utilização de Recursos de Saúde
11.
Health Inf Sci Syst ; 3(Suppl 1 HISA Big Data in Biomedicine and Healthcare 2013 Con): S1, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26019809

RESUMO

BACKGROUND: Self-quantification is seen as an emerging paradigm for health care self-management. Self-quantification systems (SQS) can be used for tracking, monitoring, and quantifying health aspects including mental, emotional, physical, and social aspects in order to gain self-knowledge. However, there has been a lack of a systematic approach for conceptualising and mapping the essential activities that are undertaken by individuals who are using SQS in order to improve health outcomes. In this paper, we propose a new model of personal health information self-quantification systems (PHI-SQS). PHI-SQS model describes two types of activities that individuals go through during their journey of health self-managed practice, which are 'self-quantification' and 'self-activation'. OBJECTIVES: In this paper, we aimed to examine thoroughly the first type of activity in PHI-SQS which is 'self-quantification'. Our objectives were to review the data management processes currently supported in a representative set of self-quantification tools and ancillary applications, and provide a systematic approach for conceptualising and mapping these processes with the individuals' activities. METHOD: We reviewed and compared eleven self-quantification tools and applications (Zeo Sleep Manager, Fitbit, Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, uBiome, Digifit, BodyTrack, and Wikilife), that collect three key health data types (Environmental exposure, Physiological patterns, Genetic traits). We investigated the interaction taking place at different data flow stages between the individual user and the self-quantification technology used. FINDINGS: We found that these eleven self-quantification tools and applications represent two major tool types (primary and secondary self-quantification systems). In each type, the individuals experience different processes and activities which are substantially influenced by the technologies' data management capabilities. CONCLUSIONS: Self-quantification in personal health maintenance appears promising and exciting. However, more studies are needed to support its use in this field. The proposed model will in the future lead to developing a measure for assessing the effectiveness of interventions to support using SQS for health self-management (e.g., assessing the complexity of self-quantification activities, and activation of the individuals).

12.
Stud Health Technol Inform ; 202: 79-82, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25000020

RESUMO

Self-monitoring experiments are becoming increasingly common as it is the case in other complex environments their interpretation and reproducibility relies heavily in the amount of associated meta-data available. In this work we propose a standardised reporting guideline to annotate these experiments and facilitate their interpretation. The existence of such reporting guideline may lead the development of future standards that would facilitate platform interoperability, data sharing and the improvement in the interpretation of such experiments as well as their reproducibility.


Assuntos
Registros Eletrônicos de Saúde/normas , Monitorização Ambulatorial/normas , Guias de Prática Clínica como Assunto , Projetos de Pesquisa/normas , Autorrelato/normas , Telemedicina/normas , Austrália , Armazenamento e Recuperação da Informação/normas
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