Claudia C Bartz PhD RN

International Society for Telemedicine and eHealth Telenursing Working Group


This paper reviews recent, nurse-led telehealth research with the goal of describing research findings that provide evidence for practice. Methods: Using an iterative search method, of eight electronic databases, 84 nurse-led research papers were separated into intervention research, systematic reviews and meta-analyses, and descriptive research. The main emphasis was on full text analysis of the intervention research. Results: Fifteen intervention research papers reported findings related to cardiovascular disease, diabetes mellitus, older age, young adults, early adolescents, children with special health care needs, people with a stoma, post-partum mothers and nurses. Also reviewed for useable evidence for practice were 10 systematic reviews, two meta-analyses and two papers that described reviews plus meta-analyses. Fifty-five papers with descriptive designs are briefly described. Nurse-led intervention research is increasing knowledge about the use of telehealth technology and applications in care delivery. People with healthcare needs do better with individual attention and increased follow-up. People have a tolerance for technology used with them to advance their quality of life and healing but there is a point at which too much technology is overwhelming. Clinical research is a challenge due to the number of extraneous variables that are difficult to control and that can affect a person’s response to the research intervention. Conclusion: Continuation of nurse-led telehealth intervention research will help to ensure that technology used to support and advance care delivery will be evidence-based.

Keywords: nursing; telehealth; intervention research; evidence-based practice; review

Bartz C. J Int Soc Telemed eHealth 2020;8:e19(1-9)
Copyright:© The Author 2020
Open access, published under Creative Commons Attribution 4.0 BY International Licence


More than 20 million nurses worldwide are involved in health professions and care delivery 24/7.1 Nurses have been involved with telehealth technology and applications for decades; the telephone has always been used by nurses to educate, consult with, and support patients and families. Mobile phones and digital capability have extended the reach and scope of nurses for healthcare delivery. Successful nurses use the technology that most appropriately supports their practice. Nurses’ roles in the development of research-based evidence for practice should not be overlooked. Those nurses who lead randomised controlled trials or other intervention research in the telehealth environment are a small fraction of all nurses worldwide. However, these role models show how nurses can be leaders in advancing evidence-based practice. Nursing, with its ethos of holistic caring, will use research to strengthen its impact on healthcare with a growing body of evidence-based knowledge. This is all to the good for health and well-being of people worldwide.

Since late 2016, a constant search of the English language literature has been underway for telehealth research publications that have a nurse as first author. While nurses may be listed among the author group on some articles, or they may clearly have participated in the research interventions without direct attribution, by using the nurse-as-first-author criterion nurses can be given full credit for leading the research team. Literature searches in 2016, 2017 and early 2018 found nurse-led research publications with predominantly descriptive designs that covered telehealth nursing, clinical practice, education and research.2-4 These demonstrated the depth and breadth of nursing in the telehealth environment. Of 51 papers identified in 2017 plus first quarter 2018, 38 used descriptive designs and 5 described technology (apps) evaluations. Eight papers used quasi-experimental designs, resulting in some evidence for practice.4 The papers represented nurses from 19 countries.

The purpose of this paper is to discuss nurse-led telehealth research from 2018 through first quarter 2019, organising the papers by design: intervention research, systematic reviews and meta-analyses, and descriptive designs. The greatest emphasis will be on intervention research and resulting outcomes that can be used to support evidence-based practice. The goal of this work is to encourage more nurses to do intervention research, thus generating observable and measurable evidence for healthcare delivery.


The design for this paper is a critical analysis of nurse-led intervention research, systematic reviews and meta-analyses, and a brief discussion of the descriptive research papers found during the study period. The literature searches supporting the prior and current work are iterative. A medical librarian regularly and repeatedly reviews dozens of tables of contents of health-related publications and then forwards to this author all telehealth research publications found in the ongoing reviews. This provides a steady flow of multidisciplinary papers involving telehealth, e.g., 357 papers in 2018. We recognise that this contrasts with traditional, one-time searches that use one or several search terms and inclusion criteria with databases such as PubMed, CINAHL, PsychINFO, EMBASE, Global Health, HealthStar, ISI Web of Science and Google. However, established databases are slow to add new journals and, with PubMed, to assign MeSH subject headings to new titles. Also, the headings for different databases may overlap or be different. Further, the terms and keywords used in telehealth articles vary a great deal, e.g., tele-(specialty), eHealth, mHealth, mobile health, digital health, artificial intelligence. And, databases that use automatic term mapping make searches more difficult as the search terms are identified wherever they are in the article, making a more detailed manual search necessary after all.


In all of 2018 through first quarter-2019, 84 nurse-led research papers from 21 countries were identified. (Table 1) Fifteen papers described intervention research, ranging from intervention-control studies to randomised controlled trials. Fourteen papers described systematic reviews and/or meta-analyses and 55 papers used descriptive research designs.

Table 1. Papers by country.
Table 1

Intervention Research

The 15 full-text papers were organised by research target group to lead current and future nurse researchers to their areas of interest. Research participants were as follows: those with cardiovascular disease,5-9  diabetes mellitus,10,11 older age;12,13 those who were young adults,14 early adolescents,15 children with special health care needs,16 people with a stoma,17 post-partum mothers,18 and nursing students.19 Ten studies used power analysis to guide their participant recruitment.5-8,10,13,15-18 Each paper’s aim(s) and findings are briefly summarised. The papers themselves must be consulted for detailed methods, care delivery or replication.

The study by Abbasi et al5 used a non-randomised controlled clinical trial with 111 subjects. Their aim was to compare the effects of the self-management education programme using a multi-method approach or multimedia approach on the quality of life among patients with chronic heart failure. Findings were that the multi-method approach and multi-media approach groups had statistically significantly improved total quality of life (QOL) and knowledge compared with the control group. The multi-method approach was statistically significantly more effective than multimedia in terms of increasing QOL and self-efficacy in the knowledge domain.

Dadosky et al6 used a prospective nonrandomised trial design comparing a historical control group that had received standard care with a prospective intervention group receiving standard care plus tele-management. Their aim was to investigate whether tele-management of heart failure patients throughout the post-acute continuum of care would reduce rehospitalisation rates and improve patient self-care knowledge and satisfaction. Patients who were re-admitted within the tele-management group had significantly higher cardiac ejection fractions and significantly higher Centre for Outcomes Research Evaluation scores predicting rehospitalisation risk compared with the historical group. Clinically significant findings were noted for risk reduction in time to intervention for the tele-management group.

Ghezeljeh et al7 completed a randomised clinical trial with control group among people with hypertension (HTN). The aim was to compare the effects of self-management (SM) education using telephone follow-up and smartphone-based social networking follow-up on SM behaviours among patients with HTN. Six weeks after the intervention, there were statistically significant findings. Participants in the telephone and smartphone social networking follow-up groups had statistically significant differences in SM behaviours compared to the control group and the group without follow-up. The telephone and smartphone social networking groups were not significantly different in the effectiveness of the SM education.

Mols et al8 used a single-centre, prospective, randomised controlled design to assess the 30-day impact of a nurse-led telephone follow-up performed 2 to 5 days after same-day discharge following percutaneous coronary intervention pathways. No differences were found between the groups in terms of adherence to platelet inhibitors or aspirin regimens. The portion of patients readmitted, the self-initiated contacts to general practitioners and the knowledge of how to manage symptoms of angina were all significantly lower in the intervention group when compared to the control group. Carrying out healthy physical activity was significantly higher in the intervention group.

Ni et al9 used an exploratory randomised controlled trial to evaluate the feasibility of using mHealth (WeChat and BB Reminder) as a tool to assist people with coronary heart disease to take their cardio-protective medications. While medication adherence increased at the 30-day follow-up for both groups, the intervention group had a greater increase but these changes were not significant. Changes in blood pressure were not significantly different but heart rate significantly decreased at 30 days in the control group.

Two intervention studies targeted people with diabetes. The study by Kotsani et al10 used a randomised controlled design to evaluate the efficacy of telenursing on the frequency of glucose measurements and the improvement of blood glucose variation in young type 1 diabetic adults (age 18-39). The researchers found a significant improvement in the glucose concentrations in the management group in month 1; the mean morning glucose concentration in month 3 were also significantly lower in the intervention group. In month 2 the difference was not significant. Also, the pre-prandial glucose concentration were significantly lower in the control group than the intervention group in months 1 and 3. The changes in HbA1c were not significant.

Mott et al11 reported a study of adults with type 2 diabetes undergoing a surgical intervention. The aim of the study was to develop, implement and evaluate a nurse-led telehealth preoperative intervention to improve glycaemic control prior to surgery. On the day of surgery, a fasting glucose was drawn; there were no significant differences between the usual care group and the telephone intervention group. An interesting finding was that 4 of the 25 participants in the intervention group decided to postpone their surgery, possibly because the education and knowledge from the phone call made them realise their glycaemic control should be improved before a surgical procedure.

Two intervention studies involving older people were found. Bakas et al12 used a quasi-experimental design to test the feasibility of a new programme, the Telehealth Community Health Assistance Team (T-Chat), a nurse-led intervention delivered through a telepresence robot designed to promote chronic disease self-management and healthy independent living among older adults. The primary outcome of the study was unhealthy days based on 2 items in the post-intervention interview and data collection. Depressive symptoms, other symptoms (e.g., fatigue, pain, stress, sleep), aerobic activity, cognitive ability and quality of life were also measured. Trends in positive directions could be seen in the data. For example, the T-CHAT group, in comparison with the wait list control group showed medium to large improvements in unhealthy days and there was a moderate improvement in depressive symptoms favouring the T-CHAT group.

The aim of the quasi-experimental study by Santana et al13 was to compare the effectiveness of telephone versus conventional follow-up in post-surgical older adult patients. The study hypothesis was that the intervention would improve patients’ autonomy for self-care and surgical recovery. Findings were that the patients in the control group showed significantly increased time for surgical recovery and patients in the intervention group had significantly less impaired mobility, need for assistance for self-care, fatigue and time required for recuperation.

Côté et al14 used an experimental design to evaluate the efficacy of a web-based tailored intervention with the aim of reducing cannabis use among young people (18-24 years) by promoting a more positive intention to abstain. Findings were that a higher proportion of participants in the experimental group reduced their cannabis use compared with the control group. There was also a significant intention in the experimental group to abstain over time and intention increased significantly in the experimental group but stayed stable for the control group.

Parisod et al15 used a single-blinded, 3-armed cluster randomised trial to study tobacco-related health literacy among early adolescents (10-13 years). The study aim was to determine the short-term effectiveness of the tobacco-related mobile health game Fume and a non-gamified website in comparison with a no-intervention control group. No statistical significance was found in anti-smoking self-efficacy between the groups after the intervention nor were there differences in the five other outcome variables: smoking outcome expectations, attitudes towards tobacco use, motives to use tobacco, motivation to decline tobacco in the future, and knowledge about tobacco. However, the health game group visited Fume significantly more frequently than the early adolescents in the website group and Fume raised more interest than the website. The authors noted that self-efficacy scores among the early adolescents were high already at baseline and may have hindered favourable results, statistically.

Hooshmand and Foronda16 used a prospective, quasi-experimental design to examine cost, caring, and family-centred care (FCC) from the family perspective in relationship to paediatric specialty services integrating telemedicine (TM) visits compared to traditional face-to-face visits for children with special care needs (CSHCN) in rural, remote and medically underserved areas. There was no difference between the groups on the perception of the care their CSHCN received or their perception of healthcare providers as caring. Significant differences between groups were found on perception of the system of care as family-centred between the traditional and telemedicine groups, with the TM group having significantly higher scores on all six facets of the FCC measure. Costs were not significantly different between groups except if the CHSCN needed care by specialists who were not in the local clinic; then the costs for the traditional care group were significantly higher.

Wang et al17 used a randomised controlled trial to assess the effectiveness of the follow-up care enhanced with a home care mobile app on the psychosocial adjustment, self-efficacy and stoma-related complications of discharged from hospital patients with stomas. Findings were that both groups had improved psychosocial adjustment over time but the intervention group had significantly greater increase in improvement in psychosocial adjustment at 1, 3, and 6-months over the control group. Similarly, the intervention group had significantly higher stoma self-efficacy than the control group at 1, 3 and 6-months after discharge. The intervention group had a lower incidence rate of stoma complications but the differences were not statistically significant.

Harris-Luna and Badr18 used a pragmatic research design to evaluate the effectiveness of a breastfeeding telephone support intervention delivered by promotoras (lay healthcare workers) to increase exclusive breast feeding (EBF) rates among Hispanic women at 12 weeks after birth. A pragmatic trial was described as taking place in the setting where individuals already receive their usual clinical care with trained research staff responsible for recruitment and data collection to maximise applicability and generalisability. Findings were that at 12 weeks after birth, significantly more women in the intervention group than control group were continuing EBF. Perceived breastfeeding support, lower household income, promotora breastfeeding telephone support and higher self-efficacy scores all significantly predicted breastfeeding at 12 weeks after birth.

Liu et al19 used a retrospective, historical control group design to evaluate the effectiveness of platform-based emergency department (ED) training of nurses compared with the same nurses who received their continuing education programme in conventional classroom settings during the prior year. The number of nurses completing the training significantly increased over the previous year (from 60% to 100%) and the examination scores were also significantly improved in the intervention group.

Systematic Reviews and Meta-analyses

Fourteen reviews (systematic or integrative) and meta-analyses were found in this literature review: 10 systematic/integrative,20-29 two meta-analyses,30,31 and two combined.32,33 Traditional search methods were used with hundreds, if not thousands, of citations first found, with a range of 6631 to 14,292.32 Years covered by the searches ranged from 124 to 28,32 with two papers26,30 noting ‘inception to’ or ‘up to’ (current year) and two papers23,31 not noting the range in years. The papers evaluated by the 14 studies ranged from 5 (of 185)29 to 70 (of 3622).21

Topics addressed in these papers were cardiovascular disease,27,29,32,33 cancer,23,31 chronic disease,21,25 chronic obstructive pulmonary disease,30 teledermoscopy,20 follow-up after discharge,28 nurses,22 apps for quality improvement,24 and physical activity in elders.26

A study by Jin et al32 reported a significant finding, that being telehealth significantly improved cardiovascular risk factors. Rush et al25 reported virtual education delivered to patients with chronic diseases was comparable or more effective than usual care. More commonly, authors noted that the studies showed lack of homogeneity,21,22,31 methodological inconsistencies or limitations,23 variable quality,24,29,33 lack of studies,26 or limited evidence.20,27,28,30

Descriptive Research
Of the 55 descriptive research papers, 28 reported studies of availability, acceptability, perceptions, and attitudes of the study targets (patients, people in various age groups, people with various diseases, caregivers in the home or community, and nurses). This set consisted of 12 papers targeting people with diseases or conditions.34-45 Seven papers looked at nurses or nursing students.46-52 Four papers were about maternal-child issues.53-56  Three papers looked at elders or homecare,57-59 and two papers looked at care in limited resource settings.60,61

The second largest set (11) described studies of apps or mHealth applications used for a particular treatment need. Four papers dealt with cardiovascular issues.62-65 Three papers were in oncology settings.66-68 The last four papers addressed single topics: post-operative monitoring,69 e-outpatient visits,70 parenting,71 and eICU.72

Six studies described development, testing and evaluation of apps for care delivery.73-78 Four studies described the use of modelling or other predictive strategies for assessing risks or outcomes.79-82 Four studies described the use of digital learning, simulation or social media for learning and communication among nurses,83-86 and two papers addressed telehealth policy and standards.87,88


The studies found with this literature review show many areas of interest among telehealth nurses. The topics indicate that nurses want to know more about the who, what, when, why and how of integrating telehealth applications into care delivery and education.

Evidence-based knowledge can be drawn from the results of the intervention studies. Patients or people with healthcare needs do better with individual attention and longer than usual follow-up using phones or mHealth applications.7,8,10,13,17,18 However, people may be overwhelmed with too much technology given to them at one time.5 Phone or mHealth follow-up can be a useful adjunct to traditional education for self-management of chronic disease.7 Nurse-learners preferred mixed methods. Self-directed online learning was not seen as sufficient and may not have accurately reflected the learner’s participation.19 On the other hand, a web-based tailored intervention reduced cannabis use among 18 to 24-year-olds and increased their intention to abstain over time.14 And, early adolescents (10-13-year-olds) are willing to participate in education with gaming and digital education applications for tobacco-related health literacy.15 Cost of care is a consideration; parents with local access to specialty care via telehealth for their children perceive their care as better.16

Clinical research, and thus evidence accumulation, is a challenge, given countless extraneous variables that can affect the person’s response to an intervention.6,11,12 Historic data used as a study’s control may lack reliability due to missing or unusable data.6 Adequate sample size and study duration, attentive management of the control group, and minimal study complexity are essential to successful research.11,12 Pre-programming and automating mHealth applications could facilitate scaling up the sample size and study duration.9

What can be learned from the 14 systematic reviews and meta-analyses? The answer, unfortunately, is ‘not much.’ It may be that systematic reviews and meta-analyses would be best used to bring together all that is known about a specialty or setting. This endeavour could include anecdotal reports, editorials, opinion pieces, economic analyses, quality and process improvement reports, education programme descriptions, historical information and research reports. Until research itself becomes more programme-driven with consistent terminology, measurement tools, interventions and reporting templates, large research reviews are not contributing to the evidence base for practice. The World Health Organization is making a commitment to bringing the digital era to healthcare worldwide and looks to structured systems for data collection, aggregation and analysis. Its MAPS toolkit is one example: mHealth assessment and planning for scale.89

Descriptive research findings can establish a basic foundation for programmes of research that can continue toward controlled trials to build knowledge and advance practice. Descriptive studies can also help nurses new to research to learn the process and understand the benefits, barriers and challenges of achieving reliable methods and producing valid results. Most telehealth nursing research involves human beings. Researchers would most likely agree that human subjects’ research is difficult due to concern for ethical treatment of the subjects and also to the countless extraneous variables that can diminish the goodness of research results. That said, it is important, if not imperative, that nurse-led research uses intervention studies that generate reliable and valid evidence for practice.

One limitation of this paper is that only English language papers were reviewed. More nurse-led telehealth research has surely been published in other languages. A second limitation is the way that authors are identified in publications; if only the author’s name or name plus practice environment are listed some nurse-led research may have been missed.

The main recommendation drawn from this work is that telehealth nurse researchers must continue to lead intervention studies with large, randomised controlled designs wherein, insofar as possible, all extraneous variables are controlled. With telehealth technology and applications rapidly transforming from optional nice-to-have technologies and applications to being integrated with the healthcare infrastructure,90 nurses know that evidence-based telehealth applications are essential to the capacity of care delivery and quality of care outcomes for people with health needs, their families and their communities.

Corresponding author:
Claudia C Bartz
14388 Cedar Lane
Suring WI 54174

Conflict of interest. The author declares no conflicts of interest.

Funding. The author declared no financial support with respect to the research, authorship, and/or publication of this article.


  1. ICN. Geneva: International Council of Nurses, 2019. Available at: accessed 12 May 2019.
  2. Bartz C. Telehealth nursing in care settings and specialties. J Int Soc Telemed eHealth 2017;2:5GKR-e5.
  3. Bartz C. Telehealth nursing research-2017. At 22nd International Conference on Telemedicine and eHealth, 6-8 December 2017, Casablanca Morocco: International Society for Telemedicine and eHealth.
  4. Bartz C. Telehealth nursing research 2017-2018. At 23rd International Conference on Telemedicine and eHealth, 15-16 March 2018, Helsinki Finland: International Society for Telemedicine and eHealth.
  5. Abbasi A, Ghezeljeh TN, Farahani MA, et al. Effects of the self-management education program using the multi-method approach and multimedia on the quality of life of patients with chronic heart failure: a non-randomized controlled clinical trial. Contemp Nurse 2018;54(4-5):409-420. DOI: 10.1080/10376.178.2018.1538705
  6. Dadosky A, Overbeck H, Barbetta L, et al. Tele-management of heart failure patients across the post-acute care continuum. Telemed J E Health 2018;24(5):360-366. DOI:10.1089/tmj.2017.0058
  7. Ghezeljeh TN, Sharifian S, Isfahani MN, et al. Comparing the effects of education using telephone follow-up and smartphone-based social networking follow-up on self-management behaviors among patients with hypertension. Contemp Nurse 2018;54(4-5):362-373. DOI: 10.1080/10376178.2018.1441730
  8. Mols RE, Hald M, Vistisen HS, et al. Nurse-led motivational telephone follow-up after same-day percutaneous coronary intervention reduces readmission and contacts to general practice. J Cardiovasc Nurs 2019;34(3):222-230. DOI:1097/JCN.0000000000000566
  9. Ni Z, Liu C, Wu B, et al. An mHealth intervention to improve medication adherence among patients with coronary heart disease in China: development of an intervention. Int J Nurs Sci 2018;5:322-330. DOI: 10.1016/j.ijnss.2018.09.003
  10. Kotsani K, Antonopoulou V, Kountouri A, et al. The role of telenursing in the management of diabetes type 1: a randomized controlled trial. Int J Nurs Stud 2018;80:29-35. DOI: 10.1016/j.ijnurstu2018.01.003
  11. Mott C, Barker K, Schwertfeger R, et al. Using a nurse-led telehealth intervention to improve fasting glucose levels in patients with uncontrolled type 2 diabetes undergoing a surgical intervention. J Doc Nurs Pract 2018;11(2):126-131. DOI: 10.1891/2380-9418.11.2.126
  12. Bakas T, Sampsel D, Israel J, et al. Using telehealth to optimize healthy independent living for older adults: a feasibility study. Geriatr Nurs 2018,39:566-573. DOI: 10.1016/j.gerinurse.2018.04.002
  13. Santana RF, Pereira SK, do Carmo TG, et al. Effectiveness of a telephone follow-up nursing intervention in postsurgical patients. Int J Nurs Pract 2018;24:e12648. DOI:10.1111/ijn.12648
  14. Côté J, Tessier S, Gagnon H, et al. Efficacy of a web-based tailored intervention to reduce cannabis use among young people attending adult education centers in Quebec. Telemed J E Health 2018;24(11):853-860. DOI:10.1089/tmj.2017.0144
  15. Parisod H, Pakarinen A, Axelin A, et al. Feasibility of mobile health game “Fume” in supporting tobacco-related health literacy among early adolescents: a three-armed cluster randomized design. Int J Med Inform 2018;113:26-37. DOI: 10.1016/j.ijmedinf.2018.02.013
  16. Hooshmand M, Foronda C. Comparison of telemedicine to traditional face-to-face care for children with special needs: a quasi-experimental study. Telemed J E Health 2018;24(6):433-441. DOI:10.1089/tmj.2017.0116
  17. Wang Q-Q, Zhao J, Huo X-R, et al. Effects of a home care mobile app on the outcomes of discharged patients with a stoma: a randomized controlled trial. J Clin Nurs 2018;27:3592-3602. DOI:10.1111/jocn.14515
  18. Harris-Luna ML, Badr LK. Pragmatic trial to evaluate the effect of a promotora telephone intervention on the duration of breast feeding. J Obstet Gynecol Neonatal Nurs 2018;47:738-748. DOI: 10.1016/j.jogn.2018.09.001
  19. Liu X, Cheng J, Huang S. Mobile phone training platform for the nursing staff in the emergency department. Telemed J E Health 2019;25(1):66-70. DOI:10.1089/tmj.2017.0317
  20. Bruce AF, Mallow JA, Theeke LA. The use of teledermoscopy in the accurate identification of cancerous skin lesions in the adult population: a systematic review. J Telemed Telecare 2018;24(2):75-83. DOI:10.1177/1357633X16686770
  21. Donevant SB, Estrada RD, Culley JM, et al. Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature. JAMIA 2018;25(10):1407-1418. DOI: 10.1093/jamia/ocy104
  22. 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;32:24-44. DOI: 10.1111/scs.12445
  23. Liptrott S, Bee P, Lovell K. Acceptability of telephone support as perceived by patients with cancer: a systematic review. Eur J Cancer Care 2018;27:e12643. DOI: 10.1111/ecc.12643
  24. Radbron E, Wilson V, McCance T, et al. The use of data collected from mHealth apps to inform evidence-based quality improvement: an integrative review. Worldviews Evid Based Nurs 2019;16(1):70-77. DOI: 10.1111/wvn.12343
  25. Rush KL, Hatt L, Janke R, et al. The efficacy of telehealth delivered educational approaches for patients with chronic diseases: a systematic review. Patient Educ Couns 2018;101:1310-1321. DOI: 10.1016/j.pec.2018.02.006
  26. Song Y, Qu J, Zhang D, et al. Feasibility and effectiveness of mobile phones in physical activity promotion for adults 50 years and older. Top Geriatr Rehabil 2018;34(3):213-222. DOI:10.1097/TGR.0000000000000197
  27. Unal E, Giakoumidakis K, Khan E, et al. Mobile phone text messaging for improving secondary prevention in cardiovascular diseases: a systematic review. Heart Lung 2018;47(4):351-359. DOI: 10.1016/j.hrtlng.2018.05.009
  28. Vergara FH, Sullivan NJ, Sheridan DJ, et al. The best practice for increasing outreach. Prof Case Manag 2018;23(6):307-317. DOI:10.1079/NCM.0000000000000296
  29. Woo K, Dowding D. Factors affecting the acceptance of telehealth services by heart failure patients: an integrative review. Telemed J E Health 2018;24(4):292-300. DOI:10.1089/tmj.2017.0080
  30. Deng N, Gu T, Zhao Q, et al. Effects of telephone support on exercise capacity and quality of life in patients with chronic obstructive pulmonary disease: a meta-analysis. Psychol Health Med 2018;23(8):917-933. DOI: 10.1080/13548506.2018.1425462
  31. Zhang Q, Zhang L, Yin R, et al. Effectiveness of telephone-based interventions on health-related quality of life and prognostic outcomes in breast cancer patients and survivors – a meta-analysis. Eur J Cancer Care 2018;27:e12632. DOI:10.1111/ecc.12632
  32. Jin K, Khonsari S, Gallagher R, et al. Telehealth interventions for the secondary prevention of coronary heart disease: a systematic review and meta-analysis. Eur J Cardiovasc Nurs 2019;18(4):260-271. DOI:10.1177/1474515119826510
  33. Yue M, Yu CH, Li C, et al. The effectiveness of electronic health interventions on blood pressure control, self-care behavioural outcomes and psychosocial well-being in patients with hypertension: a systematic review and meta-analysis. Int J Nurs Stud 2019:92:27-46. DOI:  10.1016/j.ijnurstu.2018.11.007
  34. Cajita MI, Hodgson NA, Lam KW, et al. Facilitators and barriers to adoption in older adults with heart failure. Comput Inform Nurs 2018;36(8):376-382. DOI:10.1097/CIN.0000000000000442
  35. Gusdal AK, Josefsson K, Adolfsson ET, et al. Family health conversations conducted by telephone in heart failure nursing care: a feasibility study. SAGE Open Nurs 2018;4:1-13. DOI:10.1177/2377960818803383
  36. Rush KL, Hatt L, Gorman N, et al. Planning telehealth for older adults with atrial fibrillation in rural communities: understanding stakeholder perspectives. Clinical Nurs Res 2019;28(2):130-149. DOI:10.1177.1054773818758170
  37. Cho H, Porras T, Baik D, et al. Understanding the predisposing, enabling, and reinforcing factors influencing the use of mobile-based HIV management app: a real-world usability evaluation. Int J Med Inform 2018;117:88-95. DOI: 10.1016/j.ijmrdinf.2018.06.007
  38. Correal EN, Leiva OB, Galguera AD, et al. Nurse-led telephone advice line for patients with inflammatory bowel disease. Gastroenterol Nurs 2019;42(2):132-139. DOI:10.1097/SGA.0000000000000372
  39. Mammen JR, Elson MJ, Java JJ. Patient and physician perceptions of virtual visits for Parkinson’s disease: a qualitative study. Telemed J E Health 2018;24(4):255-267. DOI:10.1089/tmj.2017.0119
  40. Baird MB, Whitney L, Caedo CE. Experiences and attitudes among psychiatric mental health advanced practice nurses in the use of telemental health: results of an online survey. J Am Psychiatr Nurses Assoc 2018;24(3):235-240. DOI:10.1177/1078390317717330
  41. Bjorkman A, Salzmann-Erikson M. When all other doors are closed: telenurses’ experiences of encountering care seekers with mental illnesses. Int J Ment Health Nurs 2018;27(5):1392-1400. DOI: 10.1111/inm.12438
  42. Guilkey RE, Draucker CB, Wu J, et al. Acceptability of a telecare intervention for persistent musculoskeletal pain. J Telemed Telecare 2018;24(1):44-50. DOI:10.1177/1357633X16670815
  43. Johnson B, Quinlan MM and Marsh JS. Telenursing and nurse-patient communication within Fertility, Inc. J Holist Nurs 2018;36(1):38-53. DOI: 10.117/0898010116685468
  44. Escobedo-Wu ELG, Deehbar F, Harsh G, et al. Nurse telephonic triage service for after-hour patient calls in neurosurgery. Ann Surg 2018; 267(4):e67-e68. DOI:10.1097/SLA.0000000000002548
  45. González-Martinez E, Piotrowska K, Sterie A-C, et al. Surgery nurses’ telephone communication: a mixed methods study with a special focus on newcomers’ calls. Nurs Open 2018;5:197-209. DOI: 10.1002/nop2.128
  46. Bautista JR. Filipino nurses’ use of smartphones in clinical settings. Comput Inform Nurs 2019;37(2):80-89. DOI: 10.1097/CIN.0000000000000482
  47. Choi E-J, Kang S-W. The relationship between acceptance intention toward a smartphone health care application and health promoting behaviors among nursing students. Comput Inform Nurs 2018;36(10):494-500. DOI: 10.1097/CIN.0000000000000433
  48. Honey M, Wright J. Nurses developing confidence and competence in telehealth: results of a descriptive qualitative study. Contemp Nurse 2018;54(4-5):472-482. DOI: 10.1080/10376178.2018.1530945
  49. Pucciarelli G, Simeone S, Virgolesi M, et al. Nursing-related smartphone activities in the Italian nursing population – a descriptive study. Comput Inform Nurs 2019;37(1):29-38. DOI: 10.1097/CIN.0000000000000474
  50. Tu M-H, Chang P, Lee Y-L. Avoiding obsolescence in mobile health – experiences in designing a mobile support system for complicated documentation at long-term care facilities. Comput Inform Nurs 2018;36(10):501-506. DOI: 10.1097/CIN.0000000000000460
  51. Van Houwelingen CTM, Ettema RGA, Kort HSM. Hospital nurses’ self-reported confidence in their telehealth competencies. J Contin Educ Nurs 2019;50(1):26-34. DOI: 10.3928/00220124-20190102-07
  52. Whalberg AC, Bjorkman A. Expert in nursing care but sometimes disrespected – telenurses’ reflections on their work environment and nursing care. J Clin Nurs 2018;27(21-22):4203-4211. DOI: 10.1111/jocn.14622
  53. Bailey CM, Newton JM, Hall HG. Telephone triage in midwifery practice: a cross-sectional survey. Int J Nurs Stud 2019;91:110-118. DOI: 10.1016/j.ijnurstu.2018.11.009
  54. Bonnell S, Griggs A, Avila G, et al. Community health workers and use of mHealth: improving identification of pregnancy complications and access to care in the Dominican Republic. Health Promot Pract 2018;19(3):331-340. DOI: 10.1177/1524839917708795
  55. Connor K, Wambach K, Baird MB. Descriptive, qualitative study of women who use mobile health applications to obtain perinatal health information.  J Obstet Gynecol Neonatal Nurs 2018;47:728-737. DOI: 10.1016/j.jogn.2018.04.138
  56. Richardson B, Goldberg L, Aston M et al. eHealth versus equity: using a feminist poststructural framework to explore the influence of perinatal eHealth resources on health equity. J Clin Nurs 2018;27:4224-4233. DOI:10.1111/jocn.14592
  57. Karlsen C, Moe CE, Haraldstad K, et al. Caring by telecare? A hermeneutic study of experiences among older adults and their family caregivers. J Clin Nurs 2019;28(7-8):1300-1313. DOI:10.1111/jocn.14744
  58. Bakas T, Sampsel D, Israel J, et al. Satisfaction and technology evaluation of a telehealth robotic program to optimize healthy independent living for older adults. J Nurs Scholarsh 2018;50(6):666-675. DOI: 10.1111/jnu.12436
  59. Waterworth S, Rahael D, Parsons J, et al. Older people’s experiences of nurse-patient telephone communication in the primary healthcare setting. J Adv Nurs 2018;74(2):373-382. DOI: 10.1111/jan.13449
  60. Garner SL, Sudia T, Rachaprolu S. Smart phone accessibility and mHealth use in a limited resource setting. Int J Nurs Pract 2018;24:e12609. DOI: 10.1111/ijn.12609
  61. Serafica R, Inouye J, Lukkahatai N, et al. The use of mobile health to assist self-management and access to services in a rural community. Comput Inform Nurs 2019;37(2):62-72. DOI:10.1097/CIN.0000000000000494
  62. Lu J-F, Chen C-MHsu , C-Y. Effect of home telehealth care on blood pressure control: a public healthcare centre model. J Telemed Telecare 2019;25(1):35-45. DOI: 10.1177/1357633X17734258
  63. Maciel ALA, Irigoyen MC and Goldmeier S. Diagnostic accuracy of prehospital tele-electrocardiography in acute coronary syndrome. Telemed J E Health 2019;25(3):1999-204. DOI: 10.1089/tmj.2017.0277
  64. Murphy MM. Telehealth alerts and nurse response. Telemed J E Health 2018;24(7):517-526. DOI: 10.1089/tmj.2017.0181
  65. Woo K, Shang J, Dowding DW. Patient factors associated with the initiation of telehealth services among heart failure patients at home. Home Health Care Serv Q 2018;37(4):277-293. DOI: 10.1080/01621424.2018.1523767
  66. Cannon C. Telehealth, mobile applications, and wearable devices are expanding cancer care beyond walls. Semin Oncol Nurs 2018;34(2):118-125. DOI: 10.1016/j.sonen.2018.03.002
  67. Swanson AJ, Castel LD, McKenna PA, et al. Integration of the National Comprehensive Cancer network (NCCN) Distress Screening Tool as a guidepost for telephonic oncology case management. Prof Case Manag 2019;34(3):148-154. DOI: 10.1097/NCM.0000000000000336
  68. Wittenberg E, Ferrell B, Koczywas M, et al. Pilot study of a communication coaching telephone intervention for lung cancer caregivers. Cancer Nurs 2018;41(6):506-512. DOI:10.1097/NCC0000000000000535
  69. McGillion MH, Duceppe E, Allan K, et al. Postoperative remote automated monitoring: need for and state of the science. Can J Cardiol 2018;34:850-862. DOI: 10.1016/j.cjca.2018.04.021
  70. Penza KS, Murray MA, Pecina JL, et al. Electronic visits for minor acute illnesses: analysis of patient demographics, prescription rates, and follow-up care within an asynchronous text-based online visit. Telemed J E Health 2018;24(3):210-215. DOI: 10.1089/tmj.2017.0091
  71. Walker AJ, Lewis FM, Al-Mulla H, et al. Being fully present – gains patients attribute to a telephone-delivered parenting program for child-rearing mothers with cancer. Cancer Nurs 2018;41(4):E12-E17. DOI: 10.1097/NCC.0000000000000515
  72. Williams L-MS, Nemeth LS, Johnson E, et al. Telemedicine intensive care unit nursing interventions to prevent failure to rescue. Am J Crit Care 2019;28(1):64-75 DOI: 10.4037/ajcc2019577
  73. Foster M. A mobile application for patients with heart failure – theory and evidence-based design and testing. Comput Inform Nurs 2018;36(11):540-549. DOI:10.1097/CIN.0000000000000465
  74. Georgsson M, Staggers N, Årsand E, et al. Employing a user-centered cognitive walkthrough to evaluate a mHealth diabetes self-management application: a case study and beginning method validation. J Biomed Inform 2019;91:103110. DOI: 10.1016/j.jbi.2019.103110
  75. Gustavell T, Langius-Eklöf A, Wengström Y, et al. Development and feasibility of an interactive smartphone app for early assessment and management of symptoms following pancreaticoduodenectomy. Cancer Nurs 2019;42(3):E1-E10. DOI:10.1097/NCC.0000000000000584
  76. Moral-Munoz JA, Esteban-Moreno B, Herrera-Viedma E, et al. Smartphone applications to perform body balance assessment: a standardized review. J Med Syst 2018;42(7):119. DOI: 10.1007/s10916-018-0970-1
  77. Njie-Carr, VPS, Jones-Parker H, Massey C, et al. Leveraging community engagement of develop a mobile health application for older women with HIV infection. J Obstet Gynecol Neonatal Nurs 2018;47(6):833-843. DOI:  10.1016/j.jogn.2018.08.005
  78. Teitelman AM, Kim SK, Waas R, et al. Development of the NowIKnow mobile application to promote completion of HPV vaccine series among young adult women. J Obstet Gynecol Neonatal Nurs 2018;47(6):844-852. DOI: 10.1016/j.jogn.2018.06.001
  79. Baik D, Reading M, Jia H, et al. Measuring health status and symptom burden using a web-based mHealth application in patients with heart failure. Eur J Cardiovasc Nurs 2019;18(4):325-331. DOI: 10.1177/1474515119825704
  80. Bose E, Radhakrishnan K. Using unsupervised machine learning to identify subgroups among home health patients with heart failure using telehealth. Comput Inform Nurs 2018;36(5):242-245. DOI: 10.1097/CIN.0000000000000423
  81. Lee H, Kim J. A structural equation model on Korean adolescents’ excessive use of smartphones. Asian Nurs Res 2018;12(2):91-98. DOI: 10.1016/j.anr.2018.03.002
  82. Murphy MM. Telehealth factors for predicting hospital length of stay. J Gerontol Nurs 2018;44(10):16-20. DOI:10.3928/00989134-20180305-01
  83. Abbass-Dick J, Brolly M, Huizinga J, et al. Designing an eHealth breastfeeding resource with indigenous families using a participatory design. J Transcult Nur 2018;29(5):480-488. DOI: 10.1177/1043659617731818
  84. Ferguson C, Hickman LD, Phillips J, et al. An mHealth intervention to improve nurses’ atrial fibrillation and anticoagulation knowledge and practice: the EVICOAG study. Eur J Cardiovasc Nurs 2019;18(1):7-15. DOI:10.1177/1474515118793051
  85. Kress D, Godack CA, Berwanger TL, et al. The new script of nursing: using social media and advances in communication to create a contemporary image of nursing. Contemp Nurse 2018;54(4-5):388-394. DOI: 10.1080/10376178.2018.1537720
  86. Lister M, Vaughn J, Brennan-Cook, J et al. Telehealth and telenursing using simulation for pre-licensure USA students. Nurse Educ Pract 2018;29:59-63. DOI: 10.1016/j.nepr.2017.10.031
  87. Adams SM, Rice MJ, Jones SL, et al. TeleMental health: standards, reimbursement, and interstate practice. J Am Psychiatri Nurses Assoc 2018;24(4):295-305. DOI: 10.1177/1078390318763963
  88. Park J, Erikson C, Han X, et al. Are state telehealth policies associated with the use of telehealth services among underserved populations? Health Aff 2018;37(12):2060-2068. DOI: 10.1377/hlthaff.2018.05101
  89. Joshi S, Hasvold PE, Wroblewska N. Dear WHO, welcome to the digital era! UN Special 2019;May:28.
  90. Doarn C, Henderson K, Rasmussen P, et al. Best practices: Understanding new and sustainable approaches integrated into health care systems. Telemed J eHealth 2019;25(7):525-532. DOI:10.1089/tmj.2019.29024.rtl

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