This paper is in the following e-collection/theme issue:

Digital Health Reviews (1174) Clinical Communication, Electronic Consultation and Telehealth (542) Digital Health, Telehealth and e-Innovation in Clinical Settings (340) Telehealth and Telemonitoring (1556)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26515, first published .
Community Health Programs Delivered Through Information and Communications Technology in High-Income Countries: Scoping Review

Community Health Programs Delivered Through Information and Communications Technology in High-Income Countries: Scoping Review

Community Health Programs Delivered Through Information and Communications Technology in High-Income Countries: Scoping Review

Authors of this article:

Hannah Beks1 Author Orcid Image ;   Olivia King2 Author Orcid Image ;   Renee Clapham3, 4 Author Orcid Image ;   Laura Alston1, 5, 6 Author Orcid Image ;   Kristen Glenister7, 8 Author Orcid Image ;   Carol McKinstry9 Author Orcid Image ;   Claire Quilliam7 Author Orcid Image ;   Ian Wellwood10 Author Orcid Image ;   Catherine Williams2 Author Orcid Image ;   Anna Wong Shee1, 4 Author Orcid Image
Article Authors Cited by (7) Tweetations (5) Metrics

    Review

    1School of Medicine, Deakin University, Geelong, Australia

    2Barwon Health, Geelong, Australia

    3St Vincents Health Australia, Melbourne, Australia

    4Ballarat Health Services, Ballarat, Australia

    5Colac Area Health, Colac, Australia

    6Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, Australia

    7Department of Rural Health, University of Melbourne, Wangaratta, Australia

    8Department of Rural Health, University of Melbourne, Shepparton, Australia

    9La Trobe Rural Health School, La Trobe University, Bendigo, Australia

    10Faculty of Health Sciences, Australian Catholic University, Ballarat, Australia

    Corresponding Author:

    Hannah Beks, MPH

    School of Medicine

    Deakin University

    1 Gheringhap St

    Geelong, 3220

    Australia

    Phone: 61 355633039

    Email: hannah.beks@deakin.edu.au


    Background: The COVID-19 pandemic has required widespread and rapid adoption of information and communications technology (ICT) platforms by health professionals. Transitioning health programs from face-to-face to remote delivery using ICT platforms has introduced new challenges.

    Objective: The objective of this review is to scope for ICT-delivered health programs implemented within the community health setting in high-income countries and rapidly disseminate findings to health professionals.

    Methods: The Joanna Briggs Institute’s scoping review methodology guided the review of the literature.

    Results: The search retrieved 7110 unique citations. Each title and abstract was screened by at least two reviewers, resulting in 399 citations for full-text review. Of these 399 citations, 72 (18%) were included. An additional 27 citations were identified through reviewing the reference lists of the included studies, resulting in 99 citations. Citations examined 83 ICT-delivered programs from 19 high-income countries. Variations in program design, ICT platforms, research design, and outcomes were evident.

    Conclusions: Included programs and research were heterogeneous, addressing prevalent chronic diseases. Evidence was retrieved for the effectiveness of nurse and allied health ICT-delivered programs. Findings indicated that outcomes for participants receiving ICT-delivered programs, when compared with participants receiving in-person programs, were either equivalent or better. Gaps included a paucity of co-designed programs, qualitative research around group programs, programs for patients and carers, and evaluation of cost-effectiveness. During COVID-19 and beyond, health professionals in the community health setting are encouraged to build on existing knowledge and address evidence gaps by developing and evaluating innovative ICT-delivered programs in collaboration with consumers and carers.

    J Med Internet Res 2022;24(3):e26515

    doi:10.2196/26515

    Keywords

    telemedicine; delivery of health care; pandemics; community health services; information and communications technology; mobile phone 


    Background

    Health professionals, working across community and acute health care settings, have responded rapidly to the COVID-19 pandemic by adopting information and communications technology (ICT) to continue delivering health programs [1-3]. Internationally, there has been an upward surge in the use of ICT to facilitate videoconferencing and telephone consultations to meet physical distancing requirements [4-6]. In Australia, this shift to telehealth in the community health setting required a temporary restructure to government funding models [7]. COVID-19 has been a catalyst for global adoption and focus on the prioritization of ICT in health, particularly in the community health setting (primary care, ambulatory care, home-based care, and outpatient hospital care) where primary and secondary prevention health programs are delivered [3,8-13].

    Digital health, eHealth, and telehealth (including telemedicine) are terms used interchangeably and broadly defined as the use of ICT platforms for the remote delivery of health care to consumers [3,14,15]. Examples include videoconferencing and telephone consultations, web-based platforms, electronic health records, SMS text messaging, and smartphone apps (or mobile health, which can include telemonitoring platforms) [14]. Globally, there is increasing support for the use of ICT platforms to improve the accessibility of health services, particularly for health promotion and disease prevention [14,16]. This is evidenced by a surge in research evaluating the usability and effectiveness of ICT-delivered health [17,18], including programs addressing chronic disease risk factors [19-23], patient education and health literacy [24,25], and chronic disease self-management [18,26-28].

    Barriers to the adoption of ICT platforms by health professionals are well documented and include a lack of ICT familiarity, lack of time to implement ICT programs, design and technical concerns, and attitudes toward ICT [29-32]. There has been little scope to address these barriers during the pandemic, where there has been a greater focus on the use of ICT in COVID-19 surveillance [33-35], and delivery of telehealth consultations [3,36]. To support health professionals in transitioning community health programs to remote delivery using ICT during COVID-19, a collaborative group was established between 4 Australian universities and 2 regional health services in April 2020. A review working group was formed, with the purpose of engaging directly with health professionals to understand knowledge gaps regarding program delivery using ICT. During the consultation phase (May to June 2020), health professionals voiced concerns regarding the transition of community health programs (particularly group programs) to an ICT platform and the potential for reduced program effectiveness. Similar concerns have been shared by other health professionals internationally [37].

    Approaches to undertaking reviews to inform evidence-based decision-making in health care vary [38]. Engaging stakeholders in the review process is suggested to generate more relevant review findings and enable prompt dissemination into practice [39]. An initial search was undertaken of MEDLINE Ovid, Cochrane Database of Systematic Reviews, Joanna Briggs Institute’s (JBI) Evidence Synthesis, and PROSPERO for existing reviews (or proposed reviews) examining ICT-delivered health programs implemented in the community health care setting in high-income countries (HIC). No recent reviews were located that mapped the evidence for community health ICT-delivered programs, justifying the need for a scoping review [40]. The review was limited to HIC because advanced use of ICT platforms is more likely with similarities in resourcing [14]. Capturing a broad range of ICT platforms across various health disciplines and specialties was important for participating health professionals seeking to innovate and engage consumers in programs. Responding to these needs, researchers and health professionals in the review working group collaborated to develop the review question, objectives, and inclusion and exclusion criteria.

    Review Questions and Objectives

    The review question is as follows:

    What is the evidence for the development and implementation of health programs delivered through ICT for consumers in the community health care settings in HIC?

    The specific review objectives include the following:

    1. to scope for evidence examining the development and implementation of ICT-delivered health programs in the community health care setting in HIC,
    2. to scope for consumer co-design processes used to develop health programs,
    3. to examine strategies to facilitate the sharing of consumer lived experience and peer interaction through an ICT platform, and
    4. to scope for any andragogical or pedagogical principles or theories, informing program design.

    Overview

    This scoping review examined the evidence around ICT-delivered health programs implemented in HIC community health care settings. This review used the JBI’s scoping review methodology [41]. Search terms were developed for the population, concept, and context. The review question, objectives, inclusion and exclusion criteria, and search strategies were developed and documented in advance (Section S1 in Multimedia Appendix 1 [41-141]). The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) was adhered to (Table S1 in Multimedia Appendix 1) [42-141].

    Search Strategy

    The JBI 3-step search process was used [142]. A preliminary search was undertaken in Ovid MEDLINE and CINAHL using keywords. A tailored search was then developed for each information source using keywords. For databases, a combination of Boolean operators, truncations, and Medical Subject Headings were used to form search strings (Multimedia Appendix 1). Health librarian assistance was obtained for developing the initial Ovid MEDLINE search strategy and translating searches. Reference lists of included studies were also searched for additional studies.

    The databases searched included Ovid MEDLINE, CINAHL (EBSCOhost), Embase (Elsevier), and Cochrane Database of Systematic Reviews (Table S2 in Multimedia Appendix 1). Multiple platforms were searched for gray literature (Table S3 in Multimedia Appendix 1). Database searches were conducted on June 16, 2020. Gray literature searches were conducted between June 15 and 30, 2020.

    Inclusion Criteria and Exclusion Criteria

    The literature was selected according to the inclusion and exclusion criteria presented in Table 1). Health programs (excluding infectious disease screening, surveillance, antenatal and postnatal, and postoperative rehabilitation programs) delivered by a health professional using an ICT platform to all populations (including carers and family members) in the community health context of HIC, as defined by the Organization for Economic Co-operation and Development (OECD) [142], were included. All types of literature published from January 1, 2010, to June 16, 2020, were included to capture a broad range of ICT platforms and health programs. Only studies published in English were included because of resource constraints.

    Table 1. Inclusion and exclusion criteria.

    		Inclusion criteriaExclusion criteria
    PopulationHealth programs delivered for infants, children, young people, and adults, including those delivered for consumers, carers, and family or friends of consumersNo exclusions
    ConceptHealth programs (interventions, models of health care, and services, including, but not limited to, health education, self-management, health promotion and rehabilitation for secondary prevention of disease) delivered by health professionals (including psychologists, speech therapists, speech pathologists, occupational therapists, physiotherapists, physical therapists, podiatrists, exercise physiologists, dietitians, social workers, audiologists, nurses, and doctors) addressing health conditions including, but not limited to, chronic disease (eg, cardiovascular disease, respiratory disease, diabetes, renal disease, cancer, and mental illness) or risk factors for developing chronic disease including, but not limited to, obesity, physical inactivity, poor health literacy, and alcohol misuse using information and communications technology (eg, mobile health, eHealth, telehealth, web-based interventions, and digital health)Infectious disease screening and surveillance programs, antenatal and postnatal programs, with the exception of gestational diabetes mellitus and postoperative rehabilitation programs
    ContextHealth programs implemented in the community health context in high-income countries (according to the Organization for Economic Co-operation and Development criteria), including primary care clinics and hospital outpatient clinicsPrograms delivered in low- and middle-income countries

    Study Selection and Data Extraction

    Searches were undertaken with the assistance of librarians skilled in systematic reviews. Citations were imported into Covidence (Veritas Health Innovation) for screening. Titles and abstracts were screened independently by at least two reviewers with conflicts resolved through mediation with an independent reviewer. All authors were involved in either screening, resolving conflicts, or both. Authors only resolved conflicts for citations that they did not screen. Full-text review and data extraction was then undertaken. For articles not meeting the inclusion criteria, reasons were noted (Table S4 in Multimedia Appendix 1). Reference lists of the included citations were screened for additional literature. Data extraction was tabulated (Section S1 in Multimedia Appendix 1), and findings were synthesized using a descriptive approach informed by the review objectives [41]. Consistent with scoping review methods and to enable rapid dissemination of findings, a quality assessment of the studies was not undertaken [143,144].


    Overview

    Of the 399 citations eligible for full-text screening, 72 (18%) met the inclusion criteria. An additional 27 citations were identified from the reference lists of the included citations, resulting in 99 citations examining 83 programs (Figure 1). Reasons for exclusion were provided (Table S4 in Multimedia Appendix 1).

    ‎
    Figure 1. PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) flow diagram. ICT: information and communications technology.
    View this figure

    Heterogeneity of Programs Using ICT Platforms

    The included health programs (n=83) were heterogeneous in design and use of ICT platforms, addressing a variety of chronic diseases (cancer, 3/83, 4%; cardiovascular disease [CVD], 12/83, 14%; diabetes [including gestational diabetes], 30/83, 36%; chronic obstructive pulmonary disease [COPD], 14/83, 17%; other chronic diseases, 11/83, 13%; and chronic pain, 2/83, 2%) and risk factors for developing chronic disease (11/83, 13%; Table S5 in Multimedia Appendix 1). The most frequently used ICT platform for program delivery was the telephone (24/83, 29%) and then internet-based platforms (21/83, 25%), telehealth (telemonitoring; 15/83, 18%), and videoconferencing (11/83, 13%). Some programs used a combination of ICT: telephone and internet-based platforms (1/83, 1%); telephone and mobile apps (2/83, 2%); telemonitoring and an internet-based platform (6/83, 7%); and telehealth (telemonitoring), videoconferencing, and telephone (2/83, 2%). Most programs were delivered by nurses (30/83, 36%) or a multidisciplinary health care team (24/83, 29%), dietitians (8/83, 10%), physiotherapists (7/83, 8%), diabetes educators (4/83, 5%), and psychologists (4/83, 5%). Diverse community health settings were captured where the programs were delivered. Most programs were delivered in outpatient hospital settings (51/83, 61%), followed by home-based settings (12/83, 15%; delivered by other community health organizations that were not primary care practices or hospitals), primary care practices (10/83, 12%), and other community health centers, including multidisciplinary centers (7/83, 8%) and community cancer centers (3/83, 4%).

    The included health programs were from 19 OECD HIC. The United States had the highest number of programs (31/83, 37%), followed by Australia (14/83, 17%), Canada (7/83, 8%), Spain (5/83, 6%), the United Kingdom (5/83, 6%), Denmark (4/83, 5%), Norway (3/83, 4%), Italy (3/83, 4%), the Netherlands (2/83, 2%), Belgium (2/83, 2%), Taiwan (2/83, 2%), Greece (2/83, 2%), France (2/83, 2%), Japan (1/83, 1%), Finland (1/83, 1%), Germany (1/83, 1%), South Korea (1/83, 1%), Singapore (1/83, 1%), and Switzerland (1/83, 1%). A total of 2 programs were implemented in >1 country, accounting for 88 sites of program implementation across all included studies [76,86].

    Program Design: Group Programs, Co-design, and Guiding Theories

    The programs primarily targeted only patients (76/83, 92%). Fewer programs were for patients and carers (7/83, 8%) and included 2 programs for cancer management [43,44], 1 telemonitoring program for CVD [56], 1 rehabilitation program for acquired brain injury [61], 1 pediatric asthma management program [64,65], 1 coping skills training program for COPD [78], and 1 self-management program for psychological distress [133].

    Of the 83 programs, 16 (19%) were either delivered to groups of participants or included a component that involved groups of participants. Of these 16 programs, 5 (31%) targeted diabetes education, self-management, and behavior change coaching [101,102,108,116,125]; 4 (25%) programs were CVD rehabilitation (secondary prevention) or counseling programs [46,47,52,53,55,57]; 4 (25%) addressed risk factors for chronic disease through education and behavior change coaching [131,132,136,141]; 1 (6%) involved group cognitive behavioral therapy (CBT) for participants experiencing insomnia [66]; 1 (6%) involved pharmacist-led group education for hepatitis C [73]; and 1 (6%) involved group education for osteoarthritis [70].

    No studies included strategies to facilitate the sharing of consumer lived experience and peer interaction in group ICT-delivered programs. A qualitative study evaluating 1 group program (CVD rehabilitation program) reported that participants engaged in group sessions but did not provide information regarding participants’ experiences [46]. There was limited information of any co-design processes used with consumers or participants to develop programs. Only 2 studies investigating 2 different programs mentioned collaboration with consumers or community organizations to develop interventions; however, no detail about the collaboration was provided [70,119].

    None of the studies used specific andragogical or pedagogical principles to inform the delivery of ICT programs to adult or child participants. A total of 12 citations referred explicitly to health behavior theories that informed program development or delivery. Constructs of social cognitive theory (SCT) were used to inform a diabetes self-management support program (Health Education Access Through Information Technology and Utilization Program) [123], a diabetes telemedicine program [111], a pedometer-based intervention for the secondary prevention of CVD [50], a telephone-based Living Well with Diabetes program [104], a telephone-based symptom management program for people with lung cancer and their carers [76], and a telephone-based health coaching program for the secondary prevention of CVD [58,59]. Strategies were implemented to optimize program participation and adherence by promoting SCT constructs (eg, self-efficacy). Examples of strategies included supporting participants to engage in goal setting (eg, related to physical activity) [50], encouraging participants to seek support and rewarding achievements [104], and equipping participants with skills (through cognitive restructuring, problem solving, or self-soothing) to enhance self-efficacy [76].

    Other theories included self-determination theory, which informed the development of a telephone-based coaching program targeting physical activity and quality of life for inactive adults through self-management [132]. Using self-determination theory as a conceptual framework, the program integrated motivational interviewing and CBT approaches to coaching [132]. The chronic care model developed by Wagner et al [145] and the transtheoretical model [146] were also used to guide a diabetes self-management education program [119], enabling self-management education and management goals to be provided and set specifically for the stage of change participants were at. The transtheoretical model was also used to inform the content and delivery of pediatric asthma management programs delivered to children and their carers [64,65] and a telehealth diabetes self-management program, along with the health belief model [102].

    Research Evidence: Study Designs, Findings, and Limitations

    Heterogeneity was evident in the research design of included citations (n=99) when evaluating the effectiveness, feasibility, or acceptability of the included programs (n=83; Table S6 in Multimedia Appendix 1). Most studies used a randomized controlled trial (RCT) design (58/99, 59%), followed by a single cohort study design (12/99, 12%), a cohort study with 2 or more groups (7/99, 7%), a qualitative design (5/99, 5%), an economic evaluation of an RCT (4/99, 4%), a mixed methods study design (3/99, 3%), or a survey design (2/99, 2%). The remaining citations used other non-RCTs or experimental study designs (8/99, 8%).

    Primary and secondary outcomes, and approaches to measuring outcomes (eg, use of validated questionnaires or devices) varied between studies and conditions (Table S6 in Multimedia Appendix 1). For RCTs, the reported effect was categorized as positive (ICT intervention was effective or more effective than control), neutral (effects were equivalent to control), or negative (ICT intervention was not effective or less effective than control) where appropriate, to provide an indication of the effectiveness of programs using ICT platforms. Of the 58 studies able to be categorized, 30 (52%) reported positive effects on the primary and secondary outcomes attributed to the ICT intervention, when compared with the control group, whereas 28 (48%) studies reported a neutral effect. No RCTs reported that outcomes were worse in the ICT intervention group than in the control group. Owing to the heterogeneity of primary and secondary outcome measures and program design, the most frequently reported outcome measures for condition groups used in RCTs are reported in Table 2, with the effects categorized. From the studies included in this table, there was consistency in the findings of RCTs of COPD programs reporting on health service use outcome measures. The effect of programs on the rate of hospitalization of the ICT intervention and control groups were found to be neutral. However, for RCTs of programs using clinical, anthropometric, or physical activity outcome measures, there was a mix of positive and neutral effects. The length of the final follow-up periods in RCTs ranged from 6 weeks to 5 years (with a median follow-up period of 12, IQR 6-15 months).

    Table 2. Most frequently reported primary outcome measures in included RCTsa.
    StudyReported effect and results
    Outcome measure: HbA1cb (diabetes programs)

    		Baron et al [94]Neutral: Program did not achieve a clinically significant reduction in HbA1c.

    		Blackberry et al [96]Neutral: At 18-months follow-up, the effect on HbA1c did not differ between the intervention and control (mean difference 0.2, 95%CI −0.2 to 0.2; P=.84).

    		Buysse et al [97]Positive: Both groups received tele-education at different time points (delayed access [control] and immediate access [study group]) and demonstrated an overall significant impact of tele-education on HbA1c reduction (−0.5% control and −0.4% study group, respectively).

    		Carter et al [98]Positive: Patients enrolled in intervention were 4.58 times more likely to achieve an HbA1c target <7%.

    		Charpentier et al [99]Positive: At 6 months, mean HbA1c was lower in the intervention group than in the control group (8.41 vs 9.10, respectively).

    		Davis et al [102]Positive: A significant reduction in HbA1c was found in the intervention group, compared with usual care (9.4 to 8.2 in the intervention group, compared with 8.8 to 8.6 in usual care).

    		Fountoulakis et al [107]Positive: Significant reduction in HbA1c in the intervention group at 3 and 6 months, when compared with that in the control group.

    		Greenwood et al [108]Positive: The intervention group had a statistically significant difference of 0.41 percentage points at 6 months when compared with the control group.

    		Klingeman et al [117]Positive: Average HbA1c reduced by 1.7% in the intervention group, compared with 0.3% in the control group.

    		Sood et al [124]Neutral: No statistically significant differences between the intervention and control groups at 18 months.

    		Varney et al [127]Positive: The intervention group experienced a greater mean change in adjusted HbA1c than the controls between baseline and 12 months; however, this was not sustained.

    		Wakefield et al [129]Neutral: Participants in the intervention group experienced decreased HbA1c during the 6-month intervention period when compared with the control group; however, 6 months after the intervention was withdrawn, the intervention groups were comparable with the control group.

    		Weinstock et al [113]Positive: Intervention was associated with improved HbA1c over 5 years, when compared with control.

    		Wild et al [110]Positive: Clinically and statistically significant improvements were observed in the intervention group at 9 months, when compared with the control group.
    Outcome measure: rate of hospitalization (COPDc programs)

    		Antoniades et al [75]Neutral: No significant difference between the intervention and control groups at 12 months.

    		Blumenthal et al [78]Neutral: No significant difference between the intervention and control groups up to 4.4 years follow-up

    		Fairbrother et al [84]Neutral: No significant difference between the intervention and control groups at 12 months.

    		Pinnock et al [85]Neutral: No significant difference between the intervention and control groups at 12 months.

    		Kessler et al [86]Neutral: No significant difference between the intervention and control groups at 12 months.

    		Tabak et al [89]Neutral: No significant difference between the intervention and control groups at 2 months.
    Outcome measure: PAd or capacity (cardiovascular disease programs)

    		Lear et al [47]Positive: Intervention group participants who received support from a health professional through an internet-based platform had a greater increase in maximal time on the treadmill by 45.7 seconds (95% CI 1.04-90.48) compared with the usual care group over the 16 months (P=.045).

    		Furber et al [50]Positive: After the 6-week intervention, improvements in total PA time, total PA sessions, walking time, and walking sessions were all significantly greater in the intervention group who received telephone support than in the control who received 2 education pamphlets and no support via telephone.

    		Hawkes et al [59]Neutral: No significant difference between the PA of participants in the intervention and control groups at 6 months follow-up.

    		Hwang et al [52,53]Neutral: No difference was found between the PA of participants receiving the telerehabilitation intervention when compared with the control group who received center-based care, and it was less costly than center-based heart failure rehabilitation.

    		Nolan et al [57]Positive: More telehealth participants than control participants reported adherence to exercise and diet after treatment at a 6-month follow-up.
    Outcome measure: weight loss or prevention of weight gained (risk factors for chronic disease programs)

    		Ferrara et al [135]Positive: Compared with those receiving usual care, women in the lifestyle intervention had reduced weekly rate of gestational weight gain (mean 0.26 vs 0.32 kg/week).

    		Padwal et al [138]Neutral: Face to-face or web-based delivery of intensive self-management program was no more effective than the once off provision of educational materials and were more costly.

    		Weinstock et al [141]Positive: Mean percent weight loss at 2-year follow-up was higher for the conference call group than for the individual call group (−5.6% compared with −1.8%).

    aRCT: randomized controlled trial.

    bHbA1c: glycated hemoglobin A1c.

    cCOPD: chronic obstructive pulmonary disease.

    dPA: physical activity.

    Of the 7 studies using qualitative inquiry (including mixed methods studies using qualitative inquiry), 3 (43%) studies examined the attitudes of participants (a videoconferencing education workshop for inflammatory arthritis, a COPD telemonitoring program, and a telemonitoring program for diabetes) [71,88,109], 2 (29%) examined perceptions of a T2DM smartphone app [118,121], 1 (14%) measured the patient experience of being involved in a web-based cardiac rehabilitation program [46], and 1 (14%) examined the perceptions of both patients and health professionals involved with a COPD telemonitoring service [83]. Themes varied but generally related to the accessibility of ICT programs [46] and general participant satisfaction [88]. A study also reported no difference in feedback obtained from participants who attended an in-person program compared with those who attended videoconferencing [71]. Another study reported limitations of using ICT platforms, including frustration with using smartphones [118], whereas other studies reported that technology was acceptable [83,88,109,121].

    Studies providing an economic evaluation of an ICT-delivered program, in conjunction with either an RCT [49,52,54,132] or a case-control study [51], supported the potential for the cost-effectiveness of ICT-delivered programs when compared with in-person programs. When examining telerehabilitation for CVD, Hwang et al [52] found the intervention to be as effective and less costly than center-based rehabilitation. Ho et al [51] reported that a telehealth program for CVD was more cost-effective and more likely to prevent hospitalizations than usual care. However, a telemonitoring program for CVD was reportedly not cost-effective because the intervention had higher costs (including equipment costs) than usual care, and no significant difference was found in quality-adjusted life years [54].

    Research limitations frequently reported included high attrition rates, small sample sizes (or not statistically powered for outcome measures), and limited external validity. The total attrition rates of RCTs ranged from 1% to 63%, with a median attrition rate of 18% (IQR 10%-25%). Difficulty in recruiting participants was also reported by some researchers. An RCT conducted a survey of why participants declined to participate in the trial and found personal reasons and concerns with technology were frequently cited by respondents [54].


    Principal Findings

    This review provides a broad overview of research examining ICT-delivered programs implemented in the community health setting in 19 countries, providing a sample of programs from 24% (19/80) of OECD HIC [144]. The highest proportion of included ICT-delivered programs was implemented in the United States, the country with the highest financial investment in health care (16.9% of gross domestic product in 2018) [147] and a growing investment in digital health [148]. Although this review was limited to programs implemented by OECD HIC, other studies have identified a surge in ICT programs and innovations in low- and middle-income countries [149-151]. Because of the COVID-19 pandemic, it is anticipated that ICT-delivered health programs and innovations will continue to increase as global health care systems are transformed [152].

    Included programs and citations were diverse, addressing a range of chronic diseases and risk factors, using a variety of ICT platforms delivered by different health professionals across different community health settings. Programs mostly targeted highly prevalent chronic diseases and risk factors, such as CVD, COPD, diabetes, and obesity or being overweight [153,154], and were delivered in the outpatient hospital setting. The need to facilitate a greater adoption of ICT in other community health settings (eg, primary care practices) has been identified by other international research and is supported by the review findings [155]. Furthermore, there were few self-management and education programs addressing cancer and mental health conditions, other chronic diseases that pose a significant burden on global populations [153]. During the COVID-19 pandemic, the need for improved accessibility to mental health programs has also been identified [156]. There were also few programs implemented for patients and carers. There is an increasing focus on the importance of carer engagement, particularly for dementia care [157] and mental health [158], and research around the role of ICT programs in supporting carers [159].

    A high proportion of programs were delivered using the telephone, internet, and telemonitoring. With a surge in the use of mobile health technologies through smartphone apps and other innovations (eg, activity monitoring devices), this finding suggests that the telephone remains an important ICT platform for improving patient accessibility to health professionals, particularly for self-management and behavior change coaching. This is evident by the use of telehealth during COVID-19 in countries such as Australia, where telephone consultations have had a higher uptake in primary care settings compared with videoconferencing delivered via web-based platforms [160]. The usefulness of videoconferencing for delivering group education, behavior change coaching, and self-management programs is also indicated by the review findings. Although this review reports little about the acceptability of ICT-delivered group programs and strategies to facilitate peer interaction, other reviews have found that group programs delivered through videoconferencing have been acceptable and feasible to participants [161]. Future research needs to examine how to facilitate group interaction in ICT programs [162].

    Although the included studies had a range of research designs (a finding of another systematic review examining emergent eHealth interventions [163]), the findings from this review supported the effectiveness of nurse-led ICT programs in improving pain associated with cancer [43], improving quality-of-life outcomes and reducing hospital admissions for patients with CVD [56], improving health outcomes for patients with CVD [58,59], and improving quality of life in carers of children with asthma [64,65]. Findings also indicated the effectiveness of ICT-delivered programs by allied health professionals, including a telenutrition program delivered by dietitians [60] and a chronic pain program delivered by physiotherapists [91]. The results from included RCTs comparing participant outcomes of an ICT program to a control group (receiving mostly in-person care) were either equivalent or better for ICT programs. Other reviews examining ICT interventions, such as nurse and allied health, delivered telehealth interventions [164], and electronic CBT [165], also concluded that delivering health interventions through ICT platforms does not lead to poorer health outcomes for patients.

    Substantial gaps in research evidence relating to ICT programs delivered in the community health setting by health professionals were identified. There were few co-designed ICT programs (and no documentation of co-design processes) and no reference to specific pedagogical or andragogical educational principles guiding program delivery—gaps identified by other reviews [166,167]. Engaging stakeholders in program development through co-design processes is thought to create programs that are more useful and acceptable to end users [168]. Some programs were developed or guided by theories; however, further research is required to examine whether using theories (eg, SCT) to develop and guide programs results in better outcomes for participants [169]. Few studies have examined participant acceptability, experience, and perceptions of ICT programs through qualitative inquiry. However, qualitative findings resonate with other reviews that have found that participants are generally satisfied with telehealth [170]. Findings indicate that there is a need for greater consumer engagement in the process of developing ICT programs and evaluating effectiveness [171]. There is also a need for more economic evaluations of ICT programs delivered in the community health setting, which is also lacking in broader health services research [172,173].

    Engaging with health professionals to understand knowledge gaps regarding community health ICT program delivery during COVID-19 and codevelopment of the scoping review question, objectives, and inclusion and exclusion criteria are strengths of this review. A summary of review findings was rapidly disseminated to health professionals involved, and findings were discussed during a short webinar. The limitations of the review include only a brief search of international gray literature due to the need to rapidly disseminate findings to health professionals. Undertaking a more thorough search of the international gray literature could have minimized publication bias. There is potential that relevant citations were not included in the review owing to this constraint. Despite this, every effort was made to review the reference lists of included citations for additional studies. Studies published in a language other than English were not captured by this review owing to resource constraints.

    Conclusions

    This review identified heterogeneity in available evidence examining ICT-delivered programs in community health settings in HIC. There is promising evidence for the effectiveness of nurse and allied health delivered ICT programs. From RCTs, outcomes for participants receiving ICT programs, compared with those receiving in-person programs, were either equivalent or better. Gaps identified included a paucity of co-designed programs; qualitative research relating to consumer acceptability, experience, and interactions in group programs; and cost-effectiveness of ICT programs and programs targeting patients and carers. It is expected that because of COVID-19, there will be a surge in the innovation, development, and evaluation of community health programs delivered using ICT platforms, providing an opportunity for health professionals and researchers to build on existing knowledge and address evidence gaps.

    Acknowledgments

    This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

    We acknowledge health professionals who participated in the review working group and other collaborators: Luke Evans, Rachel Jamieson, Jessica McDonald, Sarah McKinnon, Fiona Orton, Michael Pang, Rishni Perera, Helen Ramsay, Annabel Brennan, Jeremy Caunt, Marg Dawson, Jaquie Evans-Barker, Tahlia Farragher, Valetta Fraser, Karen Goodwin, Kendl Gorrie, Sarah Kelley, Georgie Kemp, Rachel Maher, Kylie McKenzie, Ellie Orr, Michele Pearson, Andrea Pinch, Peter Roche, Amy Smith, Michelle Stewart, Acushla Thompson, Sue Titcumb, Angela Tudor, and Renee van der Horst. We also acknowledge Deakin University Librarians Fiona Russell, Chrissy Freestone, and Jill Stephens, whose assistance was invaluable in the development of the database search strategies for this review.

    Conflicts of Interest

    None declared.

    ‎
    Multimedia Appendix 1

    Included studies characteristics, search strategies, protocol, excluded studies, and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

    DOCX File , 180 KB
    1. Bielicki JA, Duval X, Gobat N, Goossens H, Koopmans M, Tacconelli E, et al. Monitoring approaches for health-care workers during the COVID-19 pandemic. Lancet Infect Dis 2020;20(10):e261-e267 [FREE Full text] [CrossRef] [Medline]
    2. Kishore S, Hayden M. Community health centers and Covid-19 - time for congress to act. N Engl J Med 2020;383(8):e54. [CrossRef] [Medline]
    3. Fisk M, Livingstone A, Pit SW. Telehealth in the context of COVID-19: changing perspectives in Australia, the United Kingdom, and the United States. J Med Internet Res 2020;22(6):e19264 [FREE Full text] [CrossRef] [Medline]
    4. Webster P. Virtual health care in the era of COVID-19. Lancet 2020;395(10231):1180-1181 [FREE Full text] [CrossRef] [Medline]
    5. Thomas EE, Haydon HM, Mehrotra A, Caffery LJ, Snoswell CL, Banbury A, et al. Building on the momentum: sustaining telehealth beyond COVID-19. J Telemed Telecare (forthcoming) 2020:1357633X20960638. [CrossRef] [Medline]
    6. Koonin LM, Hoots B, Tsang CA, Leroy Z, Farris K, Jolly T, et al. Trends in the use of telehealth during the emergence of the COVID-19 pandemic - United States, January-March 2020. MMWR Morb Mortal Wkly Rep 2020;69(43):1595-1599 [FREE Full text] [CrossRef] [Medline]
    7. COVID-19 temporary MBS telehealth services. Australian Government Department of Health. 2020.   URL: http://www.mbsonline.gov.au/internet/mbsonline/publishing.nsf/Content/Factsheet-TempBB [accessed 2020-11-04]
    8. McMahon M, Nadigel J, Thompson E, Glazier RH. Informing Canada's health system response to COVID-19: priorities for health services and policy research. Healthc Policy 2020;16(1):112-124 [FREE Full text] [CrossRef] [Medline]
    9. Bloem BR, Dorsey ER, Okun MS. The coronavirus disease 2019 crisis as catalyst for telemedicine for chronic neurological disorders. JAMA Neurol 2020;77(8):927-928. [CrossRef] [Medline]
    10. Duckett S. What should primary care look like after the COVID-19 pandemic? Aust J Prim Health 2020;26(3):207-211. [CrossRef] [Medline]
    11. Blandford A, Wesson J, Amalberti R, AlHazme R, Allwihan R. Opportunities and challenges for telehealth within, and beyond, a pandemic. Lancet Glob Health 2020;8(11):e1364-e1365 [FREE Full text] [CrossRef] [Medline]
    12. Schwamm LH, Estrada J, Erskine A, Licurse A. Virtual care: new models of caring for our patients and workforce. Lancet Digit Health 2020;2(6):e282-e285 [FREE Full text] [CrossRef] [Medline]
    13. Smith AC, Thomas E, Snoswell CL, Haydon H, Mehrotra A, Clemensen J, et al. Telehealth for global emergencies: implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare 2020;26(5):309-313 [FREE Full text] [CrossRef] [Medline]
    14. Global diffusion of eHealth: making universal health coverage achievable. World Health Organization. 2016.   URL: https://www.who.int/goe/publications/global_diffusion/en/ [accessed 2020-11-04]
    15. Oh H, Rizo C, Enkin M, Jadad A. What is eHealth (3): a systematic review of published definitions. J Med Internet Res 2005;7(1):e1 [FREE Full text] [CrossRef] [Medline]
    16. Digital health. Seventy-First World Health Assembly. 2018.   URL: https://apps.who.int/gb/ebwha/pdf_files/WHA71/A71_R7-en.pdf?ua=1 [accessed 2020-11-04]
    17. Inal Y, Wake JD, Guribye F, Nordgreen T. Usability evaluations of mobile mental health technologies: systematic review. J Med Internet Res 2020;22(1):e15337 [FREE Full text] [CrossRef] [Medline]
    18. Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic review of reviews. Annu Rev Public Health 2015;36:393-415 [FREE Full text] [CrossRef] [Medline]
    19. Marin TS, Kourbelis C, Foote J, Newman P, Brown A, Daniel M, et al. Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: a systematic review. Eur J Prev Cardiol 2019;26(4):382-397. [CrossRef] [Medline]
    20. Stephens J, Allen J. Mobile phone interventions to increase physical activity and reduce weight: a systematic review. J Cardiovasc Nurs 2013;28(4):320-329 [FREE Full text] [CrossRef] [Medline]
    21. Su JJ, Yu DS, Paguio JT. Effect of eHealth cardiac rehabilitation on health outcomes of coronary heart disease patients: a systematic review and meta-analysis. J Adv Nurs 2020;76(3):754-772. [CrossRef] [Medline]
    22. Ryan K, Dockray S, Linehan C. A systematic review of tailored eHealth interventions for weight loss. Digit Health 2019;5:2055207619826685 [FREE Full text] [CrossRef] [Medline]
    23. Brørs G, Pettersen TR, Hansen TB, Fridlund B, Hølvold LB, Lund H, et al. Modes of e-Health delivery in secondary prevention programmes for patients with coronary artery disease: a systematic review. BMC Health Serv Res 2019;19(1):364 [FREE Full text] [CrossRef] [Medline]
    24. Halldorsdottir H, Thoroddsen A, Ingadottir B. Impact of technology-based patient education on modifiable cardiovascular risk factors of people with coronary heart disease: a systematic review. Patient Educ Couns 2020;103(10):2018-2028. [CrossRef] [Medline]
    25. Jacobs RJ, Lou JQ, Ownby RL, Caballero J. A systematic review of eHealth interventions to improve health literacy. Health Informatics J 2016;22(2):81-98 [FREE Full text] [CrossRef] [Medline]
    26. Choi W, Wang S, Lee Y, Oh H, Zheng Z. A systematic review of mobile health technologies to support self-management of concurrent diabetes and hypertension. J Am Med Inform Assoc 2020;27(6):939-945 [FREE Full text] [CrossRef] [Medline]
    27. Low JK, Manias E. Use of technology-based tools to support adolescents and young adults with chronic disease: systematic review and meta-analysis. JMIR Mhealth Uhealth 2019;7(7):e12042 [FREE Full text] [CrossRef] [Medline]
    28. Lunde P, Nilsson BB, Bergland A, Kværner KJ, Bye A. The effectiveness of smartphone apps for lifestyle improvement in noncommunicable diseases: systematic review and meta-analyses. J Med Internet Res 2018;20(5):e162 [FREE Full text] [CrossRef] [Medline]
    29. Gagnon MP, Desmartis M, Labrecque M, Car J, Pagliari C, Pluye P, et al. Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. J Med Syst 2012;36(1):241-277 [FREE Full text] [CrossRef] [Medline]
    30. Koivunen M, Saranto K. Nursing professionals' experiences of the facilitators and barriers to the use of telehealth applications: a systematic review of qualitative studies. Scand J Caring Sci 2018;32(1):24-44. [CrossRef] [Medline]
    31. Scott Kruse C, Karem P, Shifflett K, Vegi L, Ravi K, Brooks M. Evaluating barriers to adopting telemedicine worldwide: a systematic review. J Telemed Telecare 2018;24(1):4-12 [FREE Full text] [CrossRef] [Medline]
    32. Lin CC, Dievler A, Robbins C, Sripipatana A, Quinn M, Nair S. Telehealth in health centers: key adoption factors, barriers, and opportunities. Health Aff (Millwood) 2018;37(12):1967-1974. [CrossRef] [Medline]
    33. Digital tools for COVID-19 contact tracing. World Health Organisation. 2020.   URL: https://www.who.int/publications/i/item/WHO-2019-nCoV-Contact_Tracing-Tools_Annex-2020.1 [accessed 2020-11-04]
    34. Budd J, Miller BS, Manning EM, Lampos V, Zhuang M, Edelstein M, et al. Digital technologies in the public-health response to COVID-19. Nat Med 2020;26(8):1183-1192. [CrossRef] [Medline]
    35. Whitelaw S, Mamas MA, Topol E, Van Spall HG. Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit Health 2020;2(8):e435-e440 [FREE Full text] [CrossRef] [Medline]
    36. Monaghesh E, Hajizadeh A. The role of telehealth during COVID-19 outbreak: a systematic review based on current evidence. BMC Public Health 2020;20(1):1193 [FREE Full text] [CrossRef] [Medline]
    37. Jiménez-Rodríguez S, Santillán García A, Montoro Robles J, Rodríguez Salvador MD, Muñoz Ronda FJ, Arrogante O. Increase in video consultations during the COVID-19 pandemic: healthcare professionals' perceptions about their implementation and adequate management. Int J Environ Res Public Health 2020;17(14):5112 [FREE Full text] [CrossRef] [Medline]
    38. Polisena J, Garritty C, Kamel C, Stevens A, Abou-Setta AM. Rapid review programs to support health care and policy decision making: a descriptive analysis of processes and methods. Syst Rev 2015;4:26 [FREE Full text] [CrossRef] [Medline]
    39. Feldmann J, Puhan MA, Mütsch M. Characteristics of stakeholder involvement in systematic and rapid reviews: a methodological review in the area of health services research. BMJ Open 2019;9(8):e024587 [FREE Full text] [CrossRef] [Medline]
    40. Peters MD, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth 2020;18(10):2119-2126. [CrossRef] [Medline]
    41. Peters MG, Godfrey C, McInerney P, Munn Z, Tricco AC, Khalil H. Chapter 11: Scoping reviews (2020 version). In: Aromataris E, Munn Z, editors. JBI manual for evidence synthesis. Adelaide, Australia: Joanna Briggs Institute; 2020.
    42. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med 2018;169(7):467-473 [FREE Full text] [CrossRef] [Medline]
    43. Badger TA, Segrin C, Sikorskii A, Pasvogel A, Weihs K, Lopez AM, et al. Randomized controlled trial of supportive care interventions to manage psychological distress and symptoms in Latinas with breast cancer and their informal caregivers. Psychol Health 2020;35(1):87-106. [CrossRef] [Medline]
    44. Mosher CE, Winger JG, Hanna N, Jalal SI, Einhorn LH, Birdas TJ, et al. Randomized pilot trial of a telephone symptom management intervention for symptomatic lung cancer patients and their family caregivers. J Pain Symptom Manage 2016;52(4):469-482 [FREE Full text] [CrossRef] [Medline]
    45. Thomas ML, Elliott JE, Rao SM, Fahey KF, Paul SM, Miaskowski C. A randomized, clinical trial of education or motivational-interviewing-based coaching compared to usual care to improve cancer pain management. Oncol Nurs Forum 2012;39(1):39-49 [FREE Full text] [CrossRef] [Medline]
    46. Banner D, Lear S, Kandola D, Singer J, Horvat D, Bates J, et al. The experiences of patients undertaking a 'virtual' cardiac rehabilitation program. Stud Health Technol Inform 2015;209:9-14. [Medline]
    47. Lear SA, Singer J, Banner-Lukaris D, Horvat D, Park JE, Bates J, et al. Improving access to cardiac rehabilitation using the internet: a randomized trial. Stud Health Technol Inform 2015;209:58-66. [Medline]
    48. Barton AB, Okorodudu DE, Bosworth HB, Crowley MJ. Clinical inertia in a randomized trial of telemedicine-based chronic disease management: lessons learned. Telemed J E Health 2018;24(10):742-748. [CrossRef] [Medline]
    49. Donohue JM, Belnap BH, Men A, He F, Roberts MS, Schulberg HC, et al. Twelve-month cost-effectiveness of telephone-delivered collaborative care for treating depression following CABG surgery: a randomized controlled trial. Gen Hosp Psychiatry 2014;36(5):453-459 [FREE Full text] [CrossRef] [Medline]
    50. Furber S, Butler L, Phongsavan P, Mark A, Bauman A. Randomised controlled trial of a pedometer-based telephone intervention to increase physical activity among cardiac patients not attending cardiac rehabilitation. Patient Educ Couns 2010;80(2):212-218. [CrossRef] [Medline]
    51. Ho YL, Yu JY, Lin YH, Chen YH, Huang CC, Hsu TP, et al. Assessment of the cost-effectiveness and clinical outcomes of a fourth-generation synchronous telehealth program for the management of chronic cardiovascular disease. J Med Internet Res 2014;16(6):e145 [FREE Full text] [CrossRef] [Medline]
    52. Hwang R, Morris NR, Mandrusiak A, Bruning J, Peters R, Korczyk D, et al. Cost-utility analysis of home-based telerehabilitation compared with centre-based rehabilitation in patients with heart failure. Heart Lung Circ 2019;28(12):1795-1803. [CrossRef] [Medline]
    53. Hwang R, Bruning J, Morris NR, Mandrusiak A, Russell T. Home-based telerehabilitation is not inferior to a centre-based program in patients with chronic heart failure: a randomised trial. J Physiother 2017;63(2):101-107 [FREE Full text] [CrossRef] [Medline]
    54. Kidholm K, Rasmussen MK, Andreasen JJ, Hansen J, Nielsen G, Spindler H, et al. Cost-utility analysis of a cardiac telerehabilitation program: the teledialog project. Telemed J E Health 2016;22(7):553-563 [FREE Full text] [CrossRef] [Medline]
    55. Laustsen S, Oestergaard LG, van Tulder M, Hjortdal VE, Petersen AK. Telemonitored exercise-based cardiac rehabilitation improves physical capacity and health-related quality of life. J Telemed Telecare 2020;26(1-2):36-44. [CrossRef] [Medline]
    56. Mizukawa M, Moriyama M, Yamamoto H, Rahman MM, Naka M, Kitagawa T, et al. Nurse-led collaborative management using telemonitoring improves quality of life and prevention of rehospitalization in patients with heart failure. Int Heart J 2019;60(6):1293-1302 [FREE Full text] [CrossRef] [Medline]
    57. Nolan RP, Upshur RE, Lynn H, Crichton T, Rukholm E, Stewart DE, et al. Therapeutic benefit of preventive telehealth counseling in the Community Outreach Heart Health and Risk Reduction Trial. Am J Cardiol 2011;107(5):690-696. [CrossRef] [Medline]
    58. O'Neil A, Hawkes AL, Atherton JJ, Patrao TA, Sanderson K, Wolfe R, et al. Telephone-delivered health coaching improves anxiety outcomes after myocardial infarction: the 'ProActive Heart' trial. Eur J Prev Cardiol 2014;21(1):30-38. [CrossRef] [Medline]
    59. Hawkes AL, Patrao TA, Atherton J, Ware RS, Taylor CB, O'Neil A, et al. Effect of a telephone-delivered coronary heart disease secondary prevention program (proactive heart) on quality of life and health behaviours: primary outcomes of a randomised controlled trial. Int J Behav Med 2013;20(3):413-424. [CrossRef] [Medline]
    60. Ventura Marra M, Lilly CL, Nelson KR, Woofter DR, Malone J. A pilot randomized controlled trial of a telenutrition weight loss intervention in middle-aged and older men with multiple risk factors for cardiovascular disease. Nutrients 2019;11(2):229 [FREE Full text] [CrossRef] [Medline]
    61. Baque E, Barber L, Sakzewski L, Boyd RN. Randomized controlled trial of web-based multimodal therapy for children with acquired brain injury to improve gross motor capacity and performance. Clin Rehabil 2017;31(6):722-732. [CrossRef] [Medline]
    62. Cartwright M, Hirani SP, Rixon L, Beynon M, Doll H, Bower P, Whole Systems Demonstrator Evaluation Team. Effect of telehealth on quality of life and psychological outcomes over 12 months (Whole Systems Demonstrator telehealth questionnaire study): nested study of patient reported outcomes in a pragmatic, cluster randomised controlled trial. BMJ 2013;346:f653 [FREE Full text] [CrossRef] [Medline]
    63. Ellis TD, Cavanaugh JT, DeAngelis T, Hendron K, Thomas CA, Saint-Hilaire M, et al. Comparative effectiveness of mHealth-supported exercise compared with exercise alone for people with Parkinson disease: randomized controlled pilot study. Phys Ther 2019;99(2):203-216. [CrossRef] [Medline]
    64. Garbutt JM, Banister C, Highstein G, Sterkel R, Epstein J, Bruns J, et al. Telephone coaching for parents of children with asthma: impact and lessons learned. Arch Pediatr Adolesc Med 2010;164(7):625-630. [CrossRef] [Medline]
    65. Swerczek LM, Banister C, Bloomberg GR, Bruns JM, Epstein J, Highstein GR, et al. A telephone coaching intervention to improve asthma self-management behaviors. Pediatr Nurs 2013;39(3):125-145. [Medline]
    66. Gehrman P, Shah MT, Miles A, Kuna S, Godleski L. Feasibility of group cognitive-behavioral treatment of insomnia delivered by clinical video telehealth. Telemed J E Health 2016;22(12):1041-1046. [CrossRef] [Medline]
    67. Glaser E, Richard C, Lussier M. The impact of a patient web communication intervention on reaching treatment suggested guidelines for chronic diseases: a randomized controlled trial. Patient Educ Couns 2017;100(11):2062-2070. [CrossRef] [Medline]
    68. Patja K, Absetz P, Auvinen A, Tokola K, Kytö J, Oksman E, et al. Health coaching by telephony to support self-care in chronic diseases: clinical outcomes from The TERVA randomized controlled trial. BMC Health Serv Res 2012;12:147 [FREE Full text] [CrossRef] [Medline]
    69. Paul SS, Gardner T, Hubbard A, Johnson J, Canning CG, Leaver A, et al. Feasibility of the PHYZ X 2U program: a mobile and cloud-based outreach service to improve chronic disease outcomes in underserviced rural communities. Aust J Prim Health 2019;25(6):539-546. [CrossRef] [Medline]
    70. Støme LN, Pripp AH, Kværner JS, Kvaerner KJ. Acceptability, usability and utility of a personalised application in promoting behavioural change in patients with osteoarthritis: a feasibility study in Norway. BMJ Open 2019;9(1):e021608 [FREE Full text] [CrossRef] [Medline]
    71. Warmington K, Flewelling C, Kennedy CA, Shupak R, Papachristos A, Jones C, et al. Telemedicine delivery of patient education in remote Ontario communities: feasibility of an Advanced Clinician Practitioner in Arthritis Care (ACPAC)-led inflammatory arthritis education program. Open Access Rheumatol 2017;9:11-19 [FREE Full text] [CrossRef] [Medline]
    72. Kennedy CA, Warmington K, Flewelling C, Shupak R, Papachristos A, Jones C, et al. A prospective comparison of telemedicine versus in-person delivery of an interprofessional education program for adults with inflammatory arthritis. J Telemed Telecare 2017;23(2):197-206. [CrossRef] [Medline]
    73. You A, Kawamoto J, Smith JP. A pharmacist-managed telemedicine clinic for hepatitis C care: a descriptive analysis. J Telemed Telecare 2014;20(2):99-101. [CrossRef] [Medline]
    74. Alcazar B, de Lucas P, Soriano JB, Fernández-Nistal A, Fuster A, González-Moro JM, et al. The evaluation of a remote support program on quality of life and evolution of disease in COPD patients with frequent exacerbations. BMC Pulm Med 2016;16(1):140 [FREE Full text] [CrossRef] [Medline]
    75. Antoniades NC, Rochford PD, Pretto JJ, Pierce RJ, Gogler J, Steinkrug J, et al. Pilot study of remote telemonitoring in COPD. Telemed J E Health 2012;18(8):634-640. [CrossRef] [Medline]
    76. Barberan-Garcia A, Vogiatzis I, Solberg HS, Vilaró J, Rodríguez DA, Garåsen HM, NEXES Consortium. Effects and barriers to deployment of telehealth wellness programs for chronic patients across 3 European countries. Respir Med 2014;108(4):628-637 [FREE Full text] [CrossRef] [Medline]
    77. Barbita J, Neves-Silva S. Partnering with patients: the Toronto central LHIN telehomecare experience. Healthc Q 2017;20(3):36-40. [Medline]
    78. Blumenthal JA, Emery CF, Smith PJ, Keefe FJ, Welty-Wolf K, Mabe S, et al. The effects of a telehealth coping skills intervention on outcomes in chronic obstructive pulmonary disease: primary results from the INSPIRE-II study. Psychosom Med 2014;76(8):581-592 [FREE Full text] [CrossRef] [Medline]
    79. Broendum E, Ulrik CS, Gregersen T, Hansen EF, Green A, Ringbaek T. Barriers for recruitment of patients with chronic obstructive pulmonary disease to a controlled telemedicine trial. Health Informatics J 2018;24(2):216-224 [FREE Full text] [CrossRef] [Medline]
    80. Ringbæk T, Green A, Laursen LC, Frausing E, Brøndum E, Ulrik CS. Effect of tele health care on exacerbations and hospital admissions in patients with chronic obstructive pulmonary disease: a randomized clinical trial. Int J Chron Obstruct Pulmon Dis 2015;10:1801-1808 [FREE Full text] [CrossRef] [Medline]
    81. Cameron-Tucker HL, Wood-Baker R, Joseph L, Walters JA, Schüz N, Walters EH. A randomized controlled trial of telephone-mentoring with home-based walking preceding rehabilitation in COPD. Int J Chron Obstruct Pulmon Dis 2016;11:1991-2000 [FREE Full text] [CrossRef] [Medline]
    82. Esteban C, Moraza J, Iriberri M, Aguirre U, Goiria B, Quintana JM, et al. Outcomes of a telemonitoring-based program (telEPOC) in frequently hospitalized COPD patients. Int J Chron Obstruct Pulmon Dis 2016;11:2919-2930 [FREE Full text] [CrossRef] [Medline]
    83. Ure J, Pinnock H, Hanley J, Kidd G, McCall Smith E, Tarling A, et al. Piloting tele-monitoring in COPD: a mixed methods exploration of issues in design and implementation. Prim Care Respir J 2012;21(1):57-64 [FREE Full text] [CrossRef] [Medline]
    84. Fairbrother P, Pinnock H, Hanley J, McCloughan L, Sheikh A, Pagliari C, TELESCOT programme team. Continuity, but at what cost? The impact of telemonitoring COPD on continuities of care: a qualitative study. Prim Care Respir J 2012;21(3):322-328 [FREE Full text] [CrossRef] [Medline]
    85. Pinnock H, Hanley J, McCloughan L, Todd A, Krishan A, Lewis S, et al. Effectiveness of telemonitoring integrated into existing clinical services on hospital admission for exacerbation of chronic obstructive pulmonary disease: researcher blind, multicentre, randomised controlled trial. BMJ 2013;347:f6070 [FREE Full text] [CrossRef] [Medline]
    86. Kessler R, Casan-Clara P, Koehler D, Tognella S, Viejo JL, Dal Negro RW, et al. COMET: a multicomponent home-based disease-management programme versus routine care in severe COPD. Eur Respir J 2018;51(1):1701612 [FREE Full text] [CrossRef] [Medline]
    87. Kim J, Kim S, Kim HC, Kim KH, Yang SC, Lee CT, et al. Effects of consumer-centered u-health service for the knowledge, skill, and attitude of the patients with chronic obstructive pulmonary disease. Comput Inform Nurs 2012;30(12):661-671. [CrossRef] [Medline]
    88. Nissen L, Lindhardt T. A qualitative study of COPD-patients' experience of a telemedicine intervention. Int J Med Inform 2017;107:11-17. [CrossRef] [Medline]
    89. Tabak M, Brusse-Keizer M, van der Valk P, Hermens H, Vollenbroek-Hutten M. A telehealth program for self-management of COPD exacerbations and promotion of an active lifestyle: a pilot randomized controlled trial. Int J Chron Obstruct Pulmon Dis 2014;9:935-944 [FREE Full text] [CrossRef] [Medline]
    90. Zanaboni P, Lien LA, Hjalmarsen A, Wootton R. Long-term telerehabilitation of COPD patients in their homes: interim results from a pilot study in Northern Norway. J Telemed Telecare 2013;19(7):425-429. [CrossRef] [Medline]
    91. Bennell KL, Nelligan R, Dobson F, Rini C, Keefe F, Kasza J, et al. Effectiveness of an internet-delivered exercise and pain-coping skills training intervention for persons with chronic knee pain: a randomized trial. Ann Intern Med 2017;166(7):453-462. [CrossRef] [Medline]
    92. Williams A, Wiggers J, O'Brien KM, Wolfenden L, Yoong SL, Hodder RK, et al. Effectiveness of a healthy lifestyle intervention for chronic low back pain: a randomised controlled trial. Pain 2018;159(6):1137-1146. [CrossRef] [Medline]
    93. Baron J, Hirani S, Newman S. Challenges in patient recruitment, implementation, and fidelity in a mobile telehealth study. Telemed J E Health 2016;22(5):400-409. [CrossRef] [Medline]
    94. Baron JS, Hirani SP, Newman SP. Investigating the behavioural effects of a mobile-phone based home telehealth intervention in people with insulin-requiring diabetes: results of a randomized controlled trial with patient interviews. J Telemed Telecare 2017;23(5):503-512. [CrossRef] [Medline]
    95. Baron JS, Hirani S, Newman SP. A randomised, controlled trial of the effects of a mobile telehealth intervention on clinical and patient-reported outcomes in people with poorly controlled diabetes. J Telemed Telecare 2017;23(2):207-216. [CrossRef] [Medline]
    96. Blackberry ID, Furler JS, Best JD, Chondros P, Vale M, Walker C, et al. Effectiveness of general practice based, practice nurse led telephone coaching on glycaemic control of type 2 diabetes: the Patient Engagement and Coaching for Health (PEACH) pragmatic cluster randomised controlled trial. BMJ 2013;347:f5272 [FREE Full text] [CrossRef] [Medline]
    97. Buysse H, Coremans P, Pouwer F, Ruige J. Sustainable improvement of HbA1c and satisfaction with diabetes care after adding telemedicine in patients on adaptable insulin regimens: results of the TeleDiabetes randomized controlled trial. Health Informatics J 2020;26(1):628-641 [FREE Full text] [CrossRef] [Medline]
    98. Carter EL, Nunlee-Bland G, Callender C. A patient-centric, provider-assisted diabetes telehealth self-management intervention for urban minorities. Perspect Health Inf Manag 2011;8(Winter):1b [FREE Full text] [Medline]
    99. Charpentier G, Benhamou PY, Dardari D, Clergeot A, Franc S, Schaepelynck-Belicar P, TeleDiab Study Group. The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 Study). Diabetes Care 2011;34(3):533-539 [FREE Full text] [CrossRef] [Medline]
    100. Chiu CJ, Yu YC, Du YF, Yang YC, Chen JY, Wong LP, et al. Comparing a social and communication app, telephone intervention, and usual care for diabetes self-management: 3-arm Quasiexperimental evaluation study. JMIR Mhealth Uhealth 2020;8(6):e14024 [FREE Full text] [CrossRef] [Medline]
    101. Ciemins EL, Coon PJ, Coombs NC, Holloway BL, Mullette EJ, Dudley WN. Intent-to-treat analysis of a simultaneous multisite telehealth diabetes prevention program. BMJ Open Diabetes Res Care 2018;6(1):e000515 [FREE Full text] [CrossRef] [Medline]
    102. Davis RM, Hitch AD, Salaam MM, Herman WH, Zimmer-Galler IE, Mayer-Davis EJ. TeleHealth improves diabetes self-management in an underserved community: diabetes TeleCare. Diabetes Care 2010;33(8):1712-1717 [FREE Full text] [CrossRef] [Medline]
    103. du Pon E, Kleefstra N, Cleveringa F, van Dooren A, Heerdink ER, van Dulmen S. Effects of the proactive interdisciplinary self-management (PRISMA) program on online care platform usage in patients with type 2 diabetes in primary care: a randomized controlled trial. J Diabetes Res 2020;2020:5013142 [FREE Full text] [CrossRef] [Medline]
    104. Eakin EG, Winkler EA, Dunstan DW, Healy GN, Owen N, Marshall AM, et al. Living well with diabetes: 24-month outcomes from a randomized trial of telephone-delivered weight loss and physical activity intervention to improve glycemic control. Diabetes Care 2014;37(8):2177-2185. [CrossRef] [Medline]
    105. Goode AD, Winkler EA, Reeves MM, Eakin EG. Relationship between intervention dose and outcomes in living well with diabetes--a randomized trial of a telephone-delivered lifestyle-based weight loss intervention. Am J Health Promot 2015;30(2):120-129. [CrossRef] [Medline]
    106. Esmatjes E, Jansà M, Roca D, Pérez-Ferre N, del Valle L, Martínez-Hervás S, Telemed-Diabetes Group. The efficiency of telemedicine to optimize metabolic control in patients with type 1 diabetes mellitus: Telemed study. Diabetes Technol Ther 2014;16(7):435-441. [CrossRef] [Medline]
    107. Fountoulakis S, Papanastasiou L, Gryparis A, Markou A, Piaditis G. Impact and duration effect of telemonitoring on ΗbA1c, BMI and cost in insulin-treated diabetes mellitus patients with inadequate glycemic control: a randomized controlled study. Hormones (Athens) 2015;14(4):632-643 [FREE Full text] [CrossRef] [Medline]
    108. Greenwood DA, Blozis SA, Young HM, Nesbitt TS, Quinn CC. Overcoming clinical inertia: a randomized clinical trial of a telehealth remote monitoring intervention using paired glucose testing in adults with type 2 diabetes. J Med Internet Res 2015;17(7):e178 [FREE Full text] [CrossRef] [Medline]
    109. Hanley J, Fairbrother P, McCloughan L, Pagliari C, Paterson M, Pinnock H, et al. Qualitative study of telemonitoring of blood glucose and blood pressure in type 2 diabetes. BMJ Open 2015;5(12):e008896 [FREE Full text] [CrossRef] [Medline]
    110. Wild SH, Hanley J, Lewis SC, McKnight JA, McCloughan LB, Padfield PL, et al. Supported telemonitoring and glycemic control in people with type 2 diabetes: the telescot diabetes pragmatic multicenter randomized controlled trial. PLoS Med 2016;13(7):e1002098 [FREE Full text] [CrossRef] [Medline]
    111. Trief PM, Izquierdo R, Eimicke JP, Teresi JA, Goland R, Palmas W, et al. Adherence to diabetes self care for White, African-American and Hispanic American telemedicine participants: 5 year results from the IDEATel project. Ethn Health 2013;18(1):83-96. [CrossRef] [Medline]
    112. Izquierdo R, Lagua CT, Meyer S, Ploutz-Snyder RJ, Palmas W, Eimicke JP, et al. Telemedicine intervention effects on waist circumference and body mass index in the IDEATel project. Diabetes Technol Ther 2010;12(3):213-220. [CrossRef] [Medline]
    113. Weinstock RS, Teresi JA, Goland R, Izquierdo R, Palmas W, Eimicke JP, IDEATel Consortium. Glycemic control and health disparities in older ethnically diverse underserved adults with diabetes: five-year results from the Informatics for Diabetes Education and Telemedicine (IDEATel) study. Diabetes Care 2011;34(2):274-279 [FREE Full text] [CrossRef] [Medline]
    114. Weinstock RS, Brooks G, Palmas W, Morin PC, Teresi JA, Eimicke JP, et al. Lessened decline in physical activity and impairment of older adults with diabetes with telemedicine and pedometer use: results from the IDEATel study. Age Ageing 2011;40(1):98-105. [CrossRef] [Medline]
    115. West SP, Lagua C, Trief PM, Izquierdo R, Weinstock RS. Goal setting using telemedicine in rural underserved older adults with diabetes: experiences from the informatics for diabetes education and telemedicine project. Telemed J E Health 2010;16(4):405-416. [CrossRef] [Medline]
    116. Kearns JW, Bowerman D, Kemmis K, Izquierdo RE, Wade M, Weinstock RS. Group diabetes education administered through telemedicine: tools used and lessons learned. Telemed J E Health 2012;18(5):347-353. [CrossRef] [Medline]
    117. Klingeman H, Funnell M, Jhand A, Lathkar-Pradhan S, Hodish I. Type 2 diabetes specialty clinic model for the accountable care organization era. J Diabetes Complications 2017;31(10):1521-1526. [CrossRef] [Medline]
    118. Lyles CR, Harris LT, Le T, Flowers J, Tufano J, Britt D, et al. Qualitative evaluation of a mobile phone and web-based collaborative care intervention for patients with type 2 diabetes. Diabetes Technol Ther 2011;13(5):563-569. [CrossRef] [Medline]
    119. McLendon SF, Wood FG, Stanley N. Enhancing diabetes care through care coordination, telemedicine, and education: evaluation of a rural pilot program. Public Health Nurs 2019;36(3):310-320. [CrossRef] [Medline]
    120. Musacchio N, Lovagnini Scher A, Giancaterini A, Pessina L, Salis G, Schivalocchi F, et al. Impact of a chronic care model based on patient empowerment on the management of type 2 diabetes: effects of the SINERGIA programme. Diabet Med 2011;28(6):724-730. [CrossRef] [Medline]
    121. Pludwinski S, Ahmad F, Wayne N, Ritvo P. Participant experiences in a smartphone-based health coaching intervention for type 2 diabetes: a qualitative inquiry. J Telemed Telecare 2016;22(3):172-178. [CrossRef] [Medline]
    122. Reinhardt JA, van der Ploeg HP, Grzegrzulka R, Timperley JG. lmplementing lifestyle change through phone-based motivational interviewing in rural-based women with previous gestational diabetes mellitus. Health Promot J Austr 2012;23(1):5-9. [CrossRef] [Medline]
    123. Ryan JG, Schwartz R, Jennings T, Fedders M, Vittoria I. Feasibility of an internet-based intervention for improving diabetes outcomes among low-income patients with a high risk for poor diabetes outcomes followed in a community clinic. Diabetes Educ 2013;39(3):365-375. [CrossRef] [Medline]
    124. Sood A, Watts SA, Johnson JK, Hirth S, Aron DC. Telemedicine consultation for patients with diabetes mellitus: a cluster randomised controlled trial. J Telemed Telecare 2018;24(6):385-391. [CrossRef] [Medline]
    125. Vadheim LM, McPherson C, Kassner DR, Vanderwood KK, Hall TO, Butcher MK, et al. Adapted diabetes prevention program lifestyle intervention can be effectively delivered through telehealth. Diabetes Educ 2010;36(4):651-656. [CrossRef] [Medline]
    126. Van Dyck D, De Greef K, Deforche B, Ruige J, Bouckaert J, Tudor-Locke CE, et al. The relationship between changes in steps/day and health outcomes after a pedometer-based physical activity intervention with telephone support in type 2 diabetes patients. Health Educ Res 2013;28(3):539-545. [CrossRef] [Medline]
    127. Varney JE, Weiland TJ, Inder WJ, Jelinek GA. Effect of hospital-based telephone coaching on glycaemic control and adherence to management guidelines in type 2 diabetes, a randomised controlled trial. Intern Med J 2014;44(9):890-897. [CrossRef] [Medline]
    128. Wai Leng C, Jundong J, Li Wei C, Joo Pin F, Kwong Ming F, Chen R. Telehealth for improved glycaemic control in patients with poorly controlled diabetes after acute hospitalization - a preliminary study in Singapore. J Telemed Telecare 2014;20(6):317-323. [CrossRef] [Medline]
    129. Wakefield BJ, Holman JE, Ray A, Scherubel M, Adams MR, Hillis SL, et al. Effectiveness of home telehealth in comorbid diabetes and hypertension: a randomized, controlled trial. Telemed J E Health 2011;17(4):254-261. [CrossRef] [Medline]
    130. Whitehouse CR, Long JA, Maloney LM, Daniels K, Horowitz DA, Bowles KH. Feasibility of diabetes self-management telehealth education for older adults during transitions in care. Res Gerontol Nurs 2020;13(3):138-145 [FREE Full text] [CrossRef] [Medline]
    131. Ahrendt AD, Kattelmann KK, Rector TS, Maddox DA. The effectiveness of telemedicine for weight management in the MOVE! program. J Rural Health 2014;30(1):113-119. [CrossRef] [Medline]
    132. Barrett S, Begg S, O'Halloran P, Kingsley M. Cost-effectiveness of telephone coaching for physically inactive ambulatory care hospital patients: economic evaluation alongside the Healthy4U randomised controlled trial. BMJ Open 2019;9(12):e032500 [FREE Full text] [CrossRef] [Medline]
    133. Cox CE, Hough CL, Carson SS, White DB, Kahn JM, Olsen MK, et al. Effects of a telephone- and web-based coping skills training program compared with an education program for survivors of critical illness and their family members. A randomized clinical trial. Am J Respir Crit Care Med 2018;197(1):66-78. [CrossRef] [Medline]
    134. Donaldson EL, Fallows S, Morris M. A text message based weight management intervention for overweight adults. J Hum Nutr Diet 2014;27 Suppl 2:90-97. [CrossRef] [Medline]
    135. Ferrara A, Hedderson MM, Brown SD, Ehrlich SF, Tsai A, Feng J, et al. A telehealth lifestyle intervention to reduce excess gestational weight gain in pregnant women with overweight or obesity (GLOW): a randomised, parallel-group, controlled trial. Lancet Diabetes Endocrinol 2020;8(6):490-500. [CrossRef] [Medline]
    136. Haas K, Hayoz S, Maurer-Wiesner S. Effectiveness and feasibility of a remote lifestyle intervention by dietitians for overweight and obese adults: pilot study. JMIR Mhealth Uhealth 2019;7(4):e12289 [FREE Full text] [CrossRef] [Medline]
    137. Han HR, Kim J, Kim KB, Jeong S, Levine D, Li C, et al. Implementation and success of nurse telephone counseling in linguistically isolated Korean American patients with high blood pressure. Patient Educ Couns 2010;80(1):130-134 [FREE Full text] [CrossRef] [Medline]
    138. Padwal RS, Klarenbach S, Sharma AM, Fradette M, Jelinski SE, Edwards A, et al. The evaluating self-management and educational support in severely obese patients awaiting multidisciplinary bariatric care (EVOLUTION) trial: principal results. BMC Med 2017;15(1):46 [FREE Full text] [CrossRef] [Medline]
    139. Rossi MC, Perozzi C, Consorti C, Almonti T, Foglini P, Giostra N, et al. An interactive diary for diet management (DAI): a new telemedicine system able to promote body weight reduction, nutritional education, and consumption of fresh local produce. Diabetes Technol Ther 2010;12(8):641-647. [CrossRef] [Medline]
    140. Schweickert PA, Rutledge CM, Cattell-Gordon DC, Solenski NJ, Jensen ME, Branson S, et al. Telehealth stroke education for rural elderly Virginians. Telemed J E Health 2011;17(10):784-788. [CrossRef] [Medline]
    141. Weinstock RS, Trief PM, Cibula D, Morin PC, Delahanty LM. Weight loss success in metabolic syndrome by telephone interventions: results from the SHINE Study. J Gen Intern Med 2013;28(12):1620-1628 [FREE Full text] [CrossRef] [Medline]
    142. Data for high income, OECD members, upper middle income. The World Bank. 2020.   URL: https://data.worldbank.org/?locations=XD-OE-XT [accessed 2020-10-30]
    143. Aromataris E, Munn Z. JBI systematic reviews. In: Aromataris E, Munn Z, editors. JBI Manual for Evidence systhesis. Adelaide, Australia: Joanna Briggs Institute; 2017.
    144. Munn Z, Peters MD, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 2018;18(1):143 [FREE Full text] [CrossRef] [Medline]
    145. Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A. Improving chronic illness care: translating evidence into action. Health Aff (Millwood) 2001;20(6):64-78. [CrossRef] [Medline]
    146. Prochaska JO, DiClemente CC, Norcross JC. In search of how people change. Applications to addictive behaviors. Am Psychol 1992 Sep;47(9):1102-1114. [CrossRef] [Medline]
    147. Health at a glance 2019: OECD indicators. Organisation for Economic Co-operation and Development. 2019.   URL: http://www.oecd.org/health/health-systems/health-at-a-glance-19991312.htm [accessed 2020-11-04]
    148. Safavi KC, Cohen AB, Ting DY, Chaguturu S, Rowe JS. Health systems as venture capital investors in digital health: 2011-2019. NPJ Digit Med 2020;3:103 [FREE Full text] [CrossRef] [Medline]
    149. Lewis T, Synowiec C, Lagomarsino G, Schweitzer J. E-health in low- and middle-income countries: findings from the Center for Health Market Innovations. Bull World Health Organ 2012;90(5):332-340 [FREE Full text] [CrossRef] [Medline]
    150. Naslund JA, Aschbrenner KA, Araya R, Marsch LA, Unützer J, Patel V, et al. Digital technology for treating and preventing mental disorders in low-income and middle-income countries: a narrative review of the literature. Lancet Psychiatry 2017;4(6):486-500 [FREE Full text] [CrossRef] [Medline]
    151. Sondaal SF, Browne JL, Amoakoh-Coleman M, Borgstein A, Miltenburg AS, Verwijs M, et al. Assessing the effect of mHealth interventions in improving maternal and neonatal care in low- and middle-income countries: a systematic review. PLoS One 2016;11(5):e0154664 [FREE Full text] [CrossRef] [Medline]
    152. Peek N, Sujan M, Scott P. Digital health and care in pandemic times: impact of COVID-19. BMJ Health Care Inform 2020;27(1):e100166 [FREE Full text] [CrossRef] [Medline]
    153. GBD 2017 DiseaseInjury IncidencePrevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392(10159):1789-1858 [FREE Full text] [CrossRef] [Medline]
    154. Blüher M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol 2019;15(5):288-298. [CrossRef] [Medline]
    155. De Rosis S, Seghieri C. Basic ICT adoption and use by general practitioners: an analysis of primary care systems in 31 European countries. BMC Med Inform Decis Mak 2015;15:70 [FREE Full text] [CrossRef] [Medline]
    156. Moreno C, Wykes T, Galderisi S, Nordentoft M, Crossley N, Jones N, et al. How mental health care should change as a consequence of the COVID-19 pandemic. Lancet Psychiatry 2020;7(9):813-824 [FREE Full text] [CrossRef] [Medline]
    157. Dickinson C, Dow J, Gibson G, Hayes L, Robalino S, Robinson L. Psychosocial intervention for carers of people with dementia: what components are most effective and when? A systematic review of systematic reviews. Int Psychogeriatr 2017;29(1):31-43. [CrossRef] [Medline]
    158. Petkari E, Kaselionyte J, Altun S, Giacco D. Involvement of informal carers in discharge planning and transition between hospital and community mental health care: a systematic review. J Psychiatr Ment Health Nurs 2021;28(4):521-530. [CrossRef] [Medline]
    159. Heynsbergh N, Heckel L, Botti M, Livingston PM. Feasibility, useability and acceptability of technology-based interventions for informal cancer carers: a systematic review. BMC Cancer 2018;18(1):244 [FREE Full text] [CrossRef] [Medline]
    160. Snoswell CL, Caffery LJ, Haydon HM, Thomas EE, Smith AC. Telehealth uptake in general practice as a result of the coronavirus (COVID-19) pandemic. Aust Health Rev 2020;44(5):737-740. [CrossRef] [Medline]
    161. Gentry MT, Lapid MI, Clark MM, Rummans TA. Evidence for telehealth group-based treatment: a systematic review. J Telemed Telecare 2019;25(6):327-342. [CrossRef] [Medline]
    162. Hoey LM, Ieropoli SC, White VM, Jefford M. Systematic review of peer-support programs for people with cancer. Patient Educ Couns 2008;70(3):315-337. [CrossRef] [Medline]
    163. Granja C, Janssen W, Johansen MA. Factors determining the success and failure of eHealth interventions: systematic review of the literature. J Med Internet Res 2018;20(5):e10235 [FREE Full text] [CrossRef] [Medline]
    164. Speyer R, Denman D, Wilkes-Gillan S, Chen YW, Bogaardt H, Kim JH, et al. Effects of telehealth by allied health professionals and nurses in rural and remote areas: a systematic review and meta-analysis. J Rehabil Med 2018;50(3):225-235 [FREE Full text] [CrossRef] [Medline]
    165. Luo C, Sanger N, Singhal N, Pattrick K, Shams I, Shahid H, et al. A comparison of electronically-delivered and face to face cognitive behavioural therapies in depressive disorders: a systematic review and meta-analysis. EClinicalMedicine 2020;24:100442 [FREE Full text] [CrossRef] [Medline]
    166. Eyles H, Jull A, Dobson R, Firestone R, Whittaker R, Te Morenga L, et al. Co-design of mHealth delivered interventions: a systematic review to assess key methods and processes. Curr Nutr Rep 2016;5(3):160-167. [CrossRef]
    167. Hews-Girard J, Guelcher C, Meldau J, McDonald E, Newall F. Principles and theory guiding development and delivery of patient education in disorders of thrombosis and hemostasis: reviewing the current literature. Res Pract Thromb Haemost 2017;1(2):162-171 [FREE Full text] [CrossRef] [Medline]
    168. Sanders EB, Stappers PJ. Co-creation and the new landscapes of design. CoDesign 2008;4(1):5-18. [CrossRef]
    169. Tougas ME, Hayden JA, McGrath PJ, Huguet A, Rozario S. A systematic review exploring the social cognitive theory of self-regulation as a framework for chronic health condition interventions. PLoS One 2015;10(8):e0134977 [FREE Full text] [CrossRef] [Medline]
    170. Orlando JF, Beard M, Kumar S. Systematic review of patient and caregivers' satisfaction with telehealth videoconferencing as a mode of service delivery in managing patients' health. PLoS One 2019;14(8):e0221848 [FREE Full text] [CrossRef] [Medline]
    171. Miller CL, Mott K, Cousins M, Miller S, Johnson A, Lawson T, et al. Integrating consumer engagement in health and medical research - an Australian framework. Health Res Policy Syst 2017;15(1):9 [FREE Full text] [CrossRef] [Medline]
    172. Winpenny EM, Miani C, Pitchforth E, King S, Roland M. Improving the effectiveness and efficiency of outpatient services: a scoping review of interventions at the primary-secondary care interface. J Health Serv Res Policy 2017;22(1):53-64 [FREE Full text] [CrossRef] [Medline]
    173. Jessup R, Putrik P, Buchbinder R, Nezon J, Rischin K, Cyril S, et al. Identifying alternative models of healthcare service delivery to inform health system improvement: scoping review of systematic reviews. BMJ Open 2020;10(3):e036112 [FREE Full text] [CrossRef] [Medline]

    ‎
    CBT: cognitive behavioral therapy
    COPD: chronic obstructive pulmonary disease
    CVD: cardiovascular disease
    HIC: high-income countries
    ICT: information and communications technology
    JBI: Joanna Briggs Institute
    OECD: Organization for Economic Co-operation and Development
    PRISMA-ScR: Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews
    RCT: randomized controlled trial
    SCT: social cognitive theory

    Edited by G Eysenbach; submitted 15.12.20; peer-reviewed by E Thomas, W Zhang; comments to author 08.04.21; revised version received 15.04.21; accepted 18.11.21; published 09.03.22

    Copyright

    ©Hannah Beks, Olivia King, Renee Clapham, Laura Alston, Kristen Glenister, Carol McKinstry, Claire Quilliam, Ian Wellwood, Catherine Williams, Anna Wong Shee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.03.2022.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.