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TitleNew technologies, new disparities: The intersection of electronic health and digital health literacy.
AuthorsSmith, B; Magnani, JW
JournalInternational journal of cardiology
Publication Date1 Oct 2019
Date Added to PubMed7 Jun 2019
AbstractMobile health, or mHealth, is the implementation of digital health services with mobile and wearable devices, and has ample potential to enhance self-management of chronic conditions, especially cardiovascular risk factors (e.g., blood pressure control and supporting tobacco cessation and physical activity). It remains ambiguous, however, whether such technologies can improve cardiovascular outcomes. More importantly, mHealth carries the additional challenge of digital health literacy, which demands particular skills complementary to general and health literacy. Populations at risk for limited health literacy are similarly vulnerable to having challenges with digital health literacy. We identify such challenges and outline solutions to improve access to digital health services and their use for individuals with limited digital health literacy. We present an 18-point "Digital Universal Precautions" as a mandate for health care organizations committed towards addressing and facilitating eHealth literacy. As health care institutions increasingly advance mHealth through delivery of on-line material and patient portals, they face the challenge of ensuring that digital health services and content are available to all patients.
Linkhttp://doi.org/10.1016/j.ijcard.2019.05.066
TitleThe digital revolution and its impact on mental health care.
AuthorsBucci, S; Schwannauer, M; Berry, N
JournalPsychology and psychotherapy
Publication Date1 Jun 2019
Date Added to PubMed30 Mar 2019
AbstractThe digital revolution is evolving at an unstoppable pace. Alongside the unprecedented explosion of digital technology facilities and systems, mental health care is under greater pressure than ever before. With its emphasis on big data, computing power, mobile technology, and network information, digital technology is set to transform health care delivery. This article reviews the field of digital health technology assessment and intervention primarily in secondary service mental health care, including the barriers and facilitators to adopting and implementing digitally mediated interventions in service delivery. We consider the impact of digitally mediated communication on human interaction and its potential impact on various mental states such as those linked to mood, anxiety but also well-being. These developments point to a need for both theory- and data-driven approaches to digital health care. We argue that, as developments in digital technology are outpacing the evaluation of rigorous digital health interventions, more advanced methodologies are needed to keep up with the pace of digital technology development. The need for co-production of digital tools with and for people with chronic and mental health difficulties, and implications of digital technology for psychotherapy practice, will be central to this development. PRACTITIONER POINTS: Mental health problems are one of the main causes of global and societal burden and are a growing public health. People with mental health problems around the world have limited, if any, chance of accessing psychological help at all. Technological innovations and solutions are being considered in an attempt to address the size and scale of the mental health crisis worldwide. Digital platforms allow people to self-monitor and self-manage in a way that face-to-face/paper-based methods of assessment have up until now not allowed. We provide examples of digital tools that are being developed and used in the secondary setting and identify a number of challenges in the digital health field that require careful consideration.
Linkhttp://doi.org/10.1111/papt.12222
TitleThe Use of Mobile Apps and SMS Messaging as Physical and Mental Health Interventions: Systematic Review.
AuthorsRathbone, AL; Prescott, J
JournalJournal of medical Internet research
Publication Date24 Aug 2017
Date Added to PubMed26 Aug 2017
AbstractThe initial introduction of the World Wide Web in 1990 brought around the biggest change in information acquisition. Due to the abundance of devices and ease of access they subsequently allow, the utility of mobile health (mHealth) has never been more endemic. A substantial amount of interactive and psychoeducational apps are readily available to download concerning a wide range of health issues. mHealth has the potential to reduce waiting times for appointments; eradicate the need to meet in person with a clinician, successively diminishing the workload of mental health professionals; be more cost effective to practices; and encourage self-care tactics. Previous research has given valid evidence with empirical studies proving the effectiveness of physical and mental health interventions using mobile apps. Alongside apps, there is evidence to show that receiving short message service (SMS) messages, which entail psychoeducation, medication reminders, and links to useful informative Web pages can also be advantageous to a patient's mental and physical well-being. Available mHealth apps and SMS services and their ever improving quality necessitates a systematic review in the area in reference to reduction of symptomology, adherence to intervention, and usability. The aim of this review was to study the efficacy, usability, and feasibility of mobile apps and SMS messages as mHealth interventions for self-guided care. A systematic literature search was carried out in JMIR, PubMed, PsychINFO, PsychARTICLES, Google Scholar, MEDLINE, and SAGE. The search spanned from January 2008 to January 2017. The primary outcome measures consisted of weight management, (pregnancy) smoking cessation, medication adherence, depression, anxiety and stress. Where possible, adherence, feasibility, and usability outcomes of the apps or SMS services were evaluated. Between-group and within-group effect sizes (Cohen d) for the mHealth intervention method group were determined. A total of 27 studies, inclusive of 4658 participants were reviewed. The papers included randomized controlled trials (RCTs) (n=19), within-group studies (n=7), and 1 within-group study with qualitative aspect. Studies show improvement in physical health and significant reductions of anxiety, stress, and depression. Within-group and between-group effect sizes ranged from 0.05-3.37 (immediately posttest), 0.05-3.25 (1-month follow-up), 0.08-3.08 (2-month follow-up), 0.00-3.10 (3-month follow-up), and 0.02-0.27 (6-month follow-up). Usability and feasibility of mHealth interventions, where reported, also gave promising, significant results. The review shows the promising and emerging efficacy of using mobile apps and SMS text messaging as mHealth interventions.
Linkhttp://doi.org/10.2196/jmir.7740
TitleMental Health Mobile Apps for Preadolescents and Adolescents: A Systematic Review.
AuthorsGrist, R; Porter, J; Stallard, P
JournalJournal of medical Internet research
Publication Date25 May 2017
Date Added to PubMed27 May 2017
AbstractThere are an increasing number of mobile apps available for adolescents with mental health problems and an increasing interest in assimilating mobile health (mHealth) into mental health services. Despite the growing number of apps available, the evidence base for their efficacy is unclear. This review aimed to systematically appraise the available research evidence on the efficacy and acceptability of mobile apps for mental health in children and adolescents younger than 18 years. The following were systematically searched for relevant publications between January 2008 and July 2016: APA PsychNet, ACM Digital Library, Cochrane Library, Community Care Inform-Children, EMBASE, Google Scholar, PubMed, Scopus, Social Policy and Practice, Web of Science, Journal of Medical Internet Research, Cyberpsychology, Behavior and Social Networking, and OpenGrey. Abstracts were included if they described mental health apps (targeting depression, bipolar disorder, anxiety disorders, self-harm, suicide prevention, conduct disorder, eating disorders and body image issues, schizophrenia, psychosis, and insomnia) for mobile devices and for use by adolescents younger than 18 years. A total of 24 publications met the inclusion criteria. These described 15 apps, two of which were available to download. Two small randomized trials and one case study failed to demonstrate a significant effect of three apps on intended mental health outcomes. Articles that analyzed the content of six apps for children and adolescents that were available to download established that none had undergone any research evaluation. Feasibility outcomes suggest acceptability of apps was good and app usage was moderate. Overall, there is currently insufficient research evidence to support the effectiveness of apps for children, preadolescents, and adolescents with mental health problems. Given the number and pace at which mHealth apps are being released on app stores, methodologically robust research studies evaluating their safety, efficacy, and effectiveness is promptly needed.
Linkhttp://doi.org/10.2196/jmir.7332
TitleWhat is Digital Health? Review of Definitions.
AuthorsFatehi, F; Samadbeik, M; Kazemi, A
JournalStudies in health technology and informatics
Publication Date23 Nov 2020
Date Added to PubMed24 Nov 2020
AbstractDigital technologies are transforming the health sector all over the world, however various aspects of this emerging field of science is yet to be properly understood. Ambiguity in the definition of digital health is a hurdle for research, policy, and practice in this field. With the aim of achieving a consensus in the definition of digital health, we undertook a quantitative analysis and term mapping of the published definitions of digital health. After inspecting 1527 records, we analyzed 95 unique definitions of digital health, from both scholar and general sources. The findings showed that digital health, as has been used in the literature, is more concerned about the provision of healthcare rather than the use of technology. Wellbeing of people, both at population and individual levels, have been more emphasized than the care of patients suffering from diseases. Also, the use of data and information for the care of patients was highlighted. A dominant concept in digital health appeared to be mobile health (mHealth), which is related to other concepts such as telehealth, eHealth, and artificial intelligence in healthcare.
Linkhttp://doi.org/10.3233/SHTI200696
TitleDigital Health Interventions for Cardiac Rehabilitation: Systematic Literature Review.
AuthorsWongvibulsin, S; Habeos, EE; Huynh, PP; Xun, H; Shan, R; Porosnicu Rodriguez, KA; Wang, J; Gandapur, YK; Osuji, N; Shah, LM; Spaulding, EM; Hung, G; Knowles, K; Yang, WE; Marvel, FA; Levin, E; Maron, DJ; Gordon, NF; Martin, SS
JournalJournal of medical Internet research
Publication Date8 Feb 2021
Date Added to PubMed9 Feb 2021
AbstractCardiovascular disease (CVD) is the leading cause of death worldwide. Despite strong evidence supporting the benefits of cardiac rehabilitation (CR), over 80% of eligible patients do not participate in CR. Digital health technologies (ie, the delivery of care using the internet, wearable devices, and mobile apps) have the potential to address the challenges associated with traditional facility-based CR programs, but little is known about the comprehensiveness of these interventions to serve as digital approaches to CR. Overall, there is a lack of a systematic evaluation of the current literature on digital interventions for CR. The objective of this systematic literature review is to provide an in-depth analysis of the potential of digital health technologies to address the challenges associated with traditional CR. Through this review, we aim to summarize the current literature on digital interventions for CR, identify the key components of CR that have been successfully addressed through digital interventions, and describe the gaps in research that need to be addressed for sustainable and scalable digital CR interventions. Our strategy for identifying the primary literature pertaining to CR with digital solutions (defined as technology employed to deliver remote care beyond the use of the telephone) included a consultation with an expert in the field of digital CR and searches of the PubMed (MEDLINE), Embase, CINAHL, and Cochrane databases for original studies published from January 1990 to October 2018. Our search returned 31 eligible studies, of which 22 were randomized controlled trials. The reviewed CR interventions primarily targeted physical activity counseling (31/31, 100%), baseline assessment (30/31, 97%), and exercise training (27/31, 87%). The most commonly used modalities were smartphones or mobile devices (20/31, 65%), web-based portals (18/31, 58%), and email-SMS (11/31, 35%). Approximately one-third of the studies addressed the CR core components of nutrition counseling, psychological management, and weight management. In contrast, less than a third of the studies addressed other CR core components, including the management of lipids, diabetes, smoking cessation, and blood pressure. Digital technologies have the potential to increase access and participation in CR by mitigating the challenges associated with traditional, facility-based CR. However, previously evaluated interventions primarily focused on physical activity counseling and exercise training. Thus, further research is required with more comprehensive CR interventions and long-term follow-up to understand the clinical impact of digital interventions.
Linkhttp://doi.org/10.2196/18773
TitleFactors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review.
AuthorsJakob, R; Harperink, S; Rudolf, AM; Fleisch, E; Haug, S; Mair, JL; Salamanca-Sanabria, A; Kowatsch, T
JournalJournal of medical Internet research
Publication Date25 May 2022
Date Added to PubMed26 May 2022
AbstractMobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions. This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks. A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings. The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%). This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.
Linkhttp://doi.org/10.2196/35371
TitleThe use of e-health and m-health tools in health promotion and primary prevention among older adults: a systematic literature review.
AuthorsKampmeijer, R; Pavlova, M; Tambor, M; Golinowska, S; Groot, W
JournalBMC health services research
Publication Date5 Sep 2016
Date Added to PubMed10 Sep 2016
AbstractThe use of e-health and m-health technologies in health promotion and primary prevention among older people is largely unexplored. This study provides a systematic review of the evidence on the scope of the use of e-health and m-health tools in health promotion and primary prevention among older adults (age 50+). A systematic literature review was conducted in October 2015. The search for relevant publications was done in the search engine PubMed. The key inclusion criteria were: e-health and m-health tools used, participants' age 50+ years, focus on health promotion and primary prevention, published in the past 10 years, in English, and full-paper can be obtained. The text of the publications was analyzed based on two themes: the characteristics of e-health and m-health tools and the determinants of the use of these tools by older adults. The quality of the studies reviewed was also assessed. The initial search resulted in 656 publications. After we applied the inclusion and exclusion criteria, 45 publications were selected for the review. In the publications reviewed, various types of e-health/m-health tools were described, namely apps, websites, devices, video consults and webinars. Most of the publications (60 %) reported studies in the US. In 37 % of the publications, the study population was older adults in general, while the rest of the publications studied a specific group of older adults (e.g. women or those with overweight). The publications indicated various facilitators and barriers. The most commonly mentioned facilitator was the support for the use of the e-health/m-health tools that the older adults received. E-health and m-health tools are used by older adults in diverse health promotion programs, but also outside formal programs to monitor and improve their health. The latter is hardly studied. The successful use of e-health/m-health tools in health promotion programs for older adults greatly depends on the older adults' motivation and support that older adults receive when using e-health and m-health tools.
Linkhttp://doi.org/10.1186/s12913-016-1522-3
TitleMethods of usability testing in the development of eHealth applications: A scoping review.
AuthorsMaramba, I; Chatterjee, A; Newman, C
JournalInternational journal of medical informatics
Publication Date1 Jun 2019
Date Added to PubMed29 Apr 2019
AbstractThe number of eHealth applications has exponentially increased in recent years, with over 325,000 health apps now available on all major app stores. This is in addition to other eHealth applications available on other platforms such as PC software, web sites and even gaming consoles. As with other digital applications, usability is one of the key factors in the successful implementation of eHealth apps. Reviews of the literature on empirical methods of usability testing in eHealth were last published in 2015. In the context of an exponentially increasing rate of App development year on year, an updated review is warranted. To identify, explore, and summarize the current methods used in the usability testing of eHealth applications. A scoping review was conducted on literature available from April 2014 up to October 2017. Four databases were searched. Literature was considered for inclusion if it was (1) focused on an eHealth application (which includes websites, PC software, smartphone and tablet applications), (2) provided information about usability of the application, (3) provided empirical results of the usability testing, (4) a full or short paper (not an abstract) published in English after March 2014. We then extracted data pertaining to the usability evaluation processes described in the selected studies. 133 articles met the inclusion criteria. The methods used for usability testing, in decreasing order of frequency were: questionnaires (n = 105), task completion (n = 57), 'Think-Aloud' (n = 45), interviews (n = 37), heuristic testing (n = 18) and focus groups (n = 13). Majority of the studies used one (n = 45) or two (n = 46) methods of testing. The rest used a combination of three (n = 30) or four (n = 12) methods of testing usability. None of the studies used automated mechanisms to test usability. The System Usability Scale (SUS) was the most frequently used questionnaire (n = 44). The ten most frequent health conditions or diseases where eHealth apps were being evaluated for usability were the following: mental health (n = 12), cancer (n = 10), nutrition (n = 10), child health (n = 9), diabetes (n = 9), telemedicine (n = 8), cardiovascular disease (n = 6), HIV (n = 4), health information systems (n = 4) and smoking (n = 4). Further iterations of the app were reported in a minority of the studies (n = 41). The use of the 'Think-Aloud' (Pearson Chi-squared test: χ2 = 11.15, p < 0.05) and heuristic walkthrough (Pearson Chi-squared test: χ2 = 4.48, p < 0.05) were significantly associated with at least one further iteration of the app being developed. Although there has been an exponential increase in the number of eHealth apps, the number of studies that have been published that report the results of usability testing on these apps has not increased at an equivalent rate. The number of digital health applications that publish their usability evaluation results remains only a small fraction. Questionnaires are the most prevalent method of evaluating usability in eHealth applications, which provide an overall measure of usability but do not pinpoint the problems that need to be addressed. Qualitative methods may be more useful in this regard. The use of multiple evaluation methods has increased. Automated methods such as eye tracking have not gained traction in evaluating health apps. Further research is needed into which methods are best suited for the different types of eHealth applications, according to their target users and the health conditions being addressed.
Linkhttp://doi.org/10.1016/j.ijmedinf.2019.03.018
TitleMobile Phone-Based Telemedicine Practice in Older Chinese Patients with Type 2 Diabetes Mellitus: Randomized Controlled Trial.
AuthorsSun, C; Sun, L; Xi, S; Zhang, H; Wang, H; Feng, Y; Deng, Y; Wang, H; Xiao, X; Wang, G; Gao, Y; Wang, G
JournalJMIR mHealth and uHealth
Publication Date4 Jan 2019
Date Added to PubMed6 Jan 2019
AbstractPrevious studies on telemedicine interventions have shown that older diabetic patients experience difficulty in using computers, which is a barrier to remote communication between medical teams and older diabetic patients. However, older people in China tend to find it easy to use mobile phones and personal messaging apps that have a user-friendly interface. Therefore, we designed a mobile health (mHealth) system for older people with diabetes that is based on mobile phones, has a streamlined operation interface, and incorporates maximum automation. The goal of the research was to investigate the use of mobile phone-based telemedicine apps for management of older Chinese patients with type 2 diabetes mellitus (T2DM). Variables of interest included efficacy and safety. A total of 91 older (aged over 65 years) patients with T2DM who presented to our department were randomly assigned to one of two groups. Patients in the intervention group (n=44) were provided glucometers capable of data transmission and received advice pertaining to medication, diet, and exercise via the mHealth telemedicine system. Patients assigned to the control group (n=47) received routine outpatient care with no additional intervention. Patients in both groups were followed up at regular 3-month intervals. After 3 months, patients in the intervention group showed significant (P<.05) improvement in postprandial plasma glucose level. After 6 months, patients in the intervention group exhibited a decreasing trend in postprandial plasma glucose and glycated hemoglobin levels compared with the baseline and those in the control group (P<.05). Mobile phone-based telemedicine apps help improve glycemic control in older Chinese patients with T2DM. China Clinical Trial Registration Center ChiCTR 1800015214; http://www.chictr.org.cn/showprojen.aspx?proj=25949 (Archived by WebCite at http://www.webcitation.org/73wKj1GMq).
Linkhttp://doi.org/10.2196/10664
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