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ORIGINAL RESEARCH article

Front. Digit. Health, 06 December 2022
Sec. Health Technology Implementation

A blended e-health intervention for improving functional capacity in elderly patients on haemodialysis: A feasibility study

Updated
  • 1Geriatric Service, Ospedale Regionale di Mendrisio, EOC, Mendrisio, Switzerland
  • 2Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
  • 3Directorate of Research and Education, Physiotherapy Occupational Therapy Research Center, University Hospital Zurich, Zurich, Switzerland
  • 4Department of Physiotherapy and Occupational Therapy, University Hospital Zurich, Zurich Switzerland
  • 5Department of Internal Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
  • 6Division of Nephrology, Ente Ospedaliero Cantonale, Lugano, Switzerland
  • 7Faculty of Biomedical Sciences, Università Della Svizzera Italiana, Lugano, Switzerland
  • 8Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
  • 9OST – Eastern Swiss University of Applied Sciences, Department of Health, St. Gallen, Switzerland

Introduction: Physical exercise showed to be beneficial for frail older adults on haemodialysis (HD). However, there are several obstacles hindering the regular practice of exercise, such as transportation difficulties, lack of time, fatigue and comorbidities. E-health in this regard has many potential advantages and could be useful for motivating HD patients to increase their level of physical activity. The aim of this study was to evaluate the feasibility of a blended e-health intervention for elderly HD patients who individually exercise at home while under remote supervision of a physiotherapist.

Material and methods: Patients over 60 years of age with sufficient cognitive and motoric resources to perform a simple physical test battery and to use a tablet-computer were recruited from four HD outpatient facilities. Following baseline assessment at home, the participants were visited by a physiotherapist (PT). The PT set an individual exercise programme and explained how to use the web-based interface. During the 12 weeks of training, the PTs remotely supervised the patients' progress. At 12 weeks follow-up a second assessment took place.

Results: Twenty-two patients were recruited to participate in the study. Seven patients dropped out of the blended programme and 15 patients concluded the programme. The average training frequency of the 15 participants concluding the study was 1.5 times a week [range 0.2–5.8]. The duration of a training session was between 20 and 40 min. The usability of the system was deemed positive. Regarding the efficacy of the intervention, no significant improvement of any measured parameter was found, and effect sizes were small to medium.

Conclusion: A blended e-health intervention supported by a web-based application for exercising at home under remote supervision of a PT is feasible in a HD population including older patients. However, before planning a randomized controlled trial, strategies to increase the recruitment rate and the adherence to such a blended intervention should be further developed, e.g., to improve the recruitment procedures and lower the expectable drop-out rate. Furthermore, the dosage of the blended programme should be adapted to the patients' physical performance levels in future trials.

The study was registered on the website clinicaltrials.gov with ID NCT04076488.

Introduction

Haemodialysis (HD) is the most frequent renal replacement therapy used in patients with end stage kidney disease (1, 2). HD is a time-consuming medical treatment that requires mostly three sessions weekly for up to four hours in an ambulatory hospital setting or a clinic dialysis facility. Due to the chronic nature of the disease and the older mean age of the affected persons (1, 3, 4), the HD population shows a high prevalence of falls (5, 6) and of frailty (7).

Despite the reported health benefits of physical exercise programmes in HD patients (811), the adherence to such programs is known to be hindered – especially in the more older patients – by a number of barriers such as low energy and fatigue, lack of time, medical problems or transportation difficulties (1216).

Since the number of people on HD is small (about 4,700 in Switzerland (17)), no specific training for physiotherapists is available in Switzerland, and the patient specific expertise in this field is limited to the reference HD centres. Furthermore, to the best of our knowledge, the available guidelines in this field are only taking “adults” into account, and are not always entirely applicable to elderly patients (18). Disease specific exercise guidelines are missing (19).

Access to high quality care is often limited in elderly patients because of travel distance and related travel costs (20) that in Switzerland are not covered by the health insurance. Overcoming these barriers and beginning an exercise training programme is, however, considered the basis for a successful intervention in which currently available evidence-based best practice is applied (10). When patients start participation in an exercise programme, a further challenge is the maintenance of high adherence to the training over longer time periods (21).

E-health refers to health services delivered through the internet or related technologies (22). A blended e-health intervention (a combination of face-to-face care with online care (23)) may help to overcome some of the barriers to regular physical exercise (24, 25). This approach may optimize the timing, the intensity and the sequencing of interventions, and provides opportunities for individuals to receive specialised care rehabilitation in their own social environments, thus enhancing the availability and capacity of rehabilitation programmes (26). Recently the potential of e-health was used for fall prevention programmes in the elderly, reporting encouraging results (2732). An additional advantage of e-health is the possibility of implementing different persuasive technologies such as personalisation, self-monitoring, tailoring, goal setting, comparison, conditioning through positive reinforcement and remote support in the development of exercise programmes, that can enhance patients' motivation to exercise regularly (23, 3335). When web-based and non-web-based interventions are compared this shows more improvement in the ability of individuals using web-based interventions to achieve the desired specified knowledge and/or behavioural changes (36). A web-based solution allows remote supervision and training programme modification by the treating PT. Combining the web-based intervention with face-to-face sessions has shown to improve adherence in the elderly (37).

E-health is relatively new and is considered a promising method in the treatment of patients with chronic kidney disease that should be further developed (38). The aim of this study is to evaluate the feasibility of an interactive individualized web-based blended e-health exercise programme in elderly HD patients. Furthermore, this study evaluates effects of the blended intervention on health-related parameters and functional capacities as secondary outcome.

Material and methods

Study design and participants

HD patients were enrolled into a quasi-experimental single group repeated measures design study over a period of 12 weeks. CONSORT guidelines for feasibility trials (39, 40) and TIDierR guidelines for intervention studies (41) are followed in this manuscript with checklists available in Supplementary Tables S1 and S2.

This is a single-arm feasibility study in which every patient that met inclusion criteria and accepted to participate in the study was prescribed a training program of 12 weeks duration.

Eligible HD patients were over 60 years old, able to walk 20 meters at a minimum without walking aids, were on a stable medical regime (e.g., no ongoing oncological treatment, no recent surgery and no acute severe disease (e.g., a not healed trauma or fracture, ongoing infections) hindering participation in a regular training programme) and did not perform more than one weekly session of vigorous physical activity (including physiotherapy sessions). The exclusion criteria were contraindications to physical exercise, known or suspected non-compliance (e.g., patients not compliant to other therapies like physiotherapy or medicine intake), drug or alcohol abuse, and cognitive impairment that led to the inability to follow the procedure of the study.

Recruitment

We expected to enrol 3–5 patients per HD centre for a total of 12–20 patients. This is in line with a general rule-of-thumb (42) that sets the minimum of participants needed for feasibility studies at 12 (42, 43).

Initially all HD patients were screened by the medical doctors (MD) responsible for the four public HD facilities of the multicentre Hospital “Ente Ospedaliero Cantonale” of Canton Ticino, Switzerland (with centres located in the cities of Mendrisio, Lugano, Bellinzona and Locarno) during four weeks in September 2019. Patients who met inclusion criteria and gave their oral consent to the MD to participate were then contacted by the main investigator for organising a home visit that included the signing of the informed consent to the study and the baseline assessment in the following months.

Intervention

The intervention was a blended therapy approach that combined face-to-face training sessions performed by a PT with an interactive web-based home exercise programme. For this purpose, the application “Fit” was used (Dividat AG, Schindellegi, Switzerland). The application works interactively, meaning that a treating PT supervises the training progress of a patient on a weekly basis via remote communication. The collected data about the frequency of the training session or regarding a specific exercise also allows determining whether an extra home visit is required to motivate the patient or to modify the training programme.

During the initial face-to-face session, the PT examined the patient, set up an individually tailored physical exercise programme with four to six exercises, and practised these with the patient. Before the patient embarked on the 12-week home programme, he/she received a tablet-computer that included the programmed physical exercises, and instructions on how to use the “Fit” application.

The Fit cloud-based application from Dividat AG is described in detail elsewhere (44).

Due to the fact that guidelines about exercise training in HD patients - while planning for this study - was limited to adults (18), we based the development of the exercises mainly on national and international fall prevention guidelines for elderly (4547). Based on the needs of the patient, an individually tailored set of exercises could be provided. A pool of 34 dynamic, single- and multiple-joint exercises with different difficulty levels was available for training strength, balance, mobility, gait, and coordination. The exercise collection with the description in Italian can be made available by the authors upon reasonable request.

A minimum training frequency was set to 2 sessions per week and for a duration between 20 and 40 min. The intervention was planned to last 12 weeks. This corresponds to the minimum dose for an efficient exercise programme for fall prevention (48). An adherence of ≥ 75% was deemed acceptable and is reflective of reported adherence in people on HD who trained at home (4952). This 75% threshold is somewhat higher compared to the 67% average adherence value for unsupervised home-based resistance training in older adults (53).

The PTs were trained in using the programme and had 2 years of experience using the system. Furthermore, the PTs were actively working in geriatric rehabilitation. The investigator who performed the baseline and the follow-up assessments was a movement scientist trained in the use of the assessments. This person had more than 10 years of working expertise in movement analysis in the geriatric population.

Outcomes

Primary feasibility outcomes

The following parameters were used to analyse the feasibility of the intervention:

Inclusion rate: the ratio of patients fulfilling the inclusion criteria to all elderly HD patients in the 4 facilities.

Recruitment rate: the ratio of patients registered in an HD centre in September 2019 who accepted to participate to all elderly HD patients who met the inclusion criteria.

Attrition: the ratio of participants who did not terminate the 12-weeks programme to all patients who started the exercise program.

Adherence: the ratio of number of training sessions (registered on the cloud) to the number of possible training sessions (2 times a week for 12 weeks = 24).

Additionally, the reasons for drop-out and for low adherence were recorded.

Acceptance of “Fit” was analysed using an adapted version of the TAM (Technology Acceptance Model) questionnaire which contains 20 statements to be rated on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) (5456), with a high score meaning a positive evaluation of the system. The TAM analyses the perceived ease of use (PEU), the perceived usefulness (PU), the attitude towards using (ATU), and the behavioural intention to use (BIU).

Secondary outcomes

Functional capacity and health related aspects were tested by a “blinded” assessor at baseline and after 12 weeks at the participant's home. HD-associated symptoms (e.g., fatigue, dizziness) are common and about 25% patients recover the next day (57). To avoid these symptoms influencing the outcome of the functional tests we set the assessment session 24 h after a HD session. The test-battery included the 4 m walk test (4mWT) without using a walking aid (58), (which was modified through the elimination of the 1 m acceleration phase because of the difficulty in finding a 6 m corridor at every participant's home), handgrip strength (using a Jamar® hydraulic hand dynamometer from Performance Health International LTD, Sutton-in-Ashfield, UK) (59, 60), the Short Physical Performance Battery (SPPB) (61, 62), the 60 s chair stand (63, 64) and the Timed Get up and Go Test (TUG) (65, 66). The latter test was taken under single-, dual-cognitive- (counting backward from 100 by steps of 3) and dual-motor-task (carrying a cup full of water) (67) conditions. The dual-task cost for the TUG (CT-cost for the cognitive and MT-cost for the motoric-dual-task) was calculated in percentage using the formula:

(100×dualtask_value:singletask_value)100

Physical and mental health status was assessed with the Short Form Health Survey (SF-12) (6871) and autonomy with the de Morton Mobility Index (DEMMI) (72). The assessments of the secondary outcomes are described in detail in Supplementary File S3.

Statistical methods

We described the general characteristics, the functional capacities, the health-related characteristics of the patients, and the five aspects of the TAM questionnaire, using mean and standard deviation and reporting minimum and maximum values.

The primary feasibility outcomes were reported with narrative and descriptive statistics with absolute and relative numbers.

Although this is a feasibility study, we assessed the functional capacities before and after the intervention with the intention to describe the population and provide future researchers with data for comparison. Our goal was not to test efficacy of the intervention but, in line with guidelines for feasibility trials (73, 74), confidence intervals are provided to reflect the uncertainty of the main feasibility outcome. We compared the baseline and follow-up data in those patients who concluded the training programme, using the paired-samples t-test and reported mean difference ± standard error, 95% Confidence Interval, and effect size (calculated with Cohen's d for within-group comparisons, where 0.2 stands for a small effect, 0.5 for a medium effect, and 0.8 for a large effect size) (75). For not normally distributed data (normality tested with the Kolmogorov-Smirnov test), the bootstrapped confidence interval was reported.

Missing data, for example due to technical problems or health status of the participants, was not substituted, and no adjustment of mean and standard deviation was carried out. For statistical analysis IBM SPSS Statistics 27 was used.

Results

Recruitment took place in September 2019. The first baseline assessments of the first patients were made on the 17th of October 2019 and the last follow-up visit on the 20th of October 2020.

Patient characteristics are presented in Table 1.

TABLE 1
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Table 1. Baseline demographic, clinical and functional data: mean ± SD [range] characteristics of the participants. Where not specified, all 21 participants are included.

Primary feasibility outcomes

One hundred and ninety-seven (197) HD patients over 60 years of age were screened for participation in the four centres. One hundred and eleven (111) out of the 197 patients did not fulfil inclusion criteria (56%). Out of the 86 remaining potential participants, 22 agreed to participate (26%). The main reason for not participating was lack of motivation (refusal without giving a specific explanation) to participate in an exercise programme (64%). One participant willing to participate passed away before the baseline assessment, and out of the 21 participants starting the exercise program, six dropped out (29%). Three participants abandoned the programme because of motivation loss, one was hospitalised, one was institutionalised in a care home, and one was not able to continue due to lack of time. One participant finished the training programme but died before the follow-up assessment, and another refused the follow-up visit at home due to the COVID-19 pandemic; however, this individual completed the questionnaires by phone. Figure 1 shows the study flow diagram.

FIGURE 1
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Figure 1. Study flow diagram.

The 15 participants who concluded the exercise programme had a mean adherence of 73% (ranging between 10% and 290%), whereas six had an adherence ≥ 75%. The reason for the low adherence were health-related in three cases, in two cases because of difficulties using the tablet, one participant preferred outdoor activities to the tablet solution, one participant changed jobs and had no time for training, one lost the motivation to exercise, and one had to take part in informal care. Furthermore, two patients had to undergo surgery, due to a knee injury and femur fracture (not related to the exercise program). After recovery, both patients continued with the programme with mainly exercises performed in a sitting position. The feasibility parameters are summarized in Table 2.

TABLE 2
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Table 2. Feasibility parameters inclusion- and recruitment rate, attrition and adherence.

Table 3 Summary of the acceptance of the “Fit” system based on the TAM questionnaire scores.

TABLE 3
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Table 3. Acceptance of “Fit” as analysed with the technology acceptance model questionnaire (values represent mean ± SD of the given scores).

Secondary outcomes

For the functional capacity and the health status, there were no significant changes after the 12-week exercise programme. The 4 m walk test, handgrip, and the dual-task cost (both cognitive and motor) showed a small to medium effect size, the other parameters measured had a small effect size. The results are summarized in Table 4. The individual participant results are presented graphically in Supplementary Table S4.

TABLE 4
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Table 4. Pre and post measurements (mean ± SD) and statistics.

Discussion

The main aim of this study was to analyse the feasibility of a blended e-health intervention in elderly HD patients, and to quantify the impact of the 12-week training programme with the individualised web-based exercise programme on the functional capacity and the health status of the participants. After excluding 60% of the HD patients, mostly due to their impaired health status, 26% of the eligible patients accepted to participate in the study. 68% concluded the 12-week exercise programme with an adherence of 73%. Our results are similar to other studies that tested home-based training in HD patients (4952, 79, 80). The application “Fit” was evaluated as useful, motivating and easy to use. No significant changes were found in functional capacity and health related aspects in the group that concluded the study.

Due to the more advanced age of the participants, the chronic nature of end stage renal disease with its specific accompanying symptoms (fatigue, comorbidities), and with the time and energy required for haemodialytic therapy, we were aware that it would be difficult to motivate HD patients to invest time and energy in an exercise programme (1216), notwithstanding the known benefits of exercise for these patients (8, 9).

In order to motivate HD participants to exercise we combined the advantage of a home-based training approach (temporal and spatial independence) with technological motivational aspects (self- and external remote monitoring) under the supervision of specialized physiotherapists that included at least one face-to-face visit (2426).

The initial screening process confirmed the frailty prevalence in the HD population, where out of 197 elderly patients on dialysis, 57 had an unstable health status (29%), and 35 were physically, cognitively, or visually impaired (18%). These patients could probably also benefit from the system, but for this study they were not eligible due to our protocol. This included widely used geriatric assessments that contain many walking tasks and expected the participants to use the system autonomously at home, although our experience suggests that the assistance by a family member or a care giver is in some cases useful.

Another aspect that emerged was the lack of motivation in our patient group. About 50% (41 out of 86) stated unwillingness as the reason for their refusal to participate, and 14% (12 out of 86) considered the intervention to be useless from the outset. In this regard, the role of healthcare staff seems to be fundamental, as a positive attitude of the health care staff towards physical exercise has previously shown to improve the motivation of training in their patients (81, 82). For further studies in this field, instruction of the medical staff may be useful for improving the recruitment rate (15). Only two patients motivated their refusal with an aversion towards technology. This confirms the high acceptance towards the web-based technology reported in a recent survey in Switzerland (83).

The mean adherence of the participants who concluded the 12-week programme was 73%, and is in line with similar studies that had an adherence in home-based trainings programme for HD patients of 53%–78% (4952, 79).

Interestingly, the low adherence was not conditioned by health status alone. In fact, two participants continued to exercise regularly even after knee surgery and a hip fracture. In these cases, the training plan was adapted and sitting exercises substituted for standing exercises.

The functional capacity measured in the participants at baseline, mostly in a sub-normal range, the low physical health score, and the number of adverse events (2 deaths, 1 hospitalisation, 1 institutionalisation and 2 surgeries), confirm the frailty status of the HD population, and should be considered in further studies when estimating the drop-out rate in a similar population. An encouraging finding, however, was that no adverse event was related to the intervention.

The application “Fit” was evaluated very positively and was not an obstacle for participation in the programme. The possible technological issues that we anticipated were reduced to a minimum through providing the patients with a complete solution in which as few steps as possible were needed to set up and initiate the system. They received a tablet with the pre-installed application and a subscriber identity module (SIM card) that ensured the internet connection. In addition, the home visit provided the PT, together with the user, with the opportunity to determine how best to set up the system and where to plug the tablet in. In fact, contrary to the findings of a similar project (84), where the patients received the tablet in the hospital and had to connect the system to their own internet service at home without receiving any assistance, no technical problems were reported in our study. In line with, and as described in other publications (24, 25), the blended approach was by and large appreciated, and the supervision by the PT who contacted the participants by phone once an issue came up was positively interpreted by the trainees as a sign of close involvement.

Despite the very high score in perceived usability of the system and the perceived usefulness, only 40% of our study participants trained regularly (6 out of 15 patients). The low adherence and the adverse events (two patients underwent surgery) may be indicative of the vulnerable patient status which possibly also explains the lack of improvement in functional capacity and health status. However, it should be noted that the focus of this study was on feasibility and not on effectiveness. This is why we integrated a rather generic exercise programme instead of developing a training plan with clear SMART goals (85) targeted to the deficits of this population. Nevertheless, lifestyle changes such as the use of an e-health application may be very challenging for HD patients, and the use of education techniques, goal setting, feedback, monitoring and social support are required to prevent progression of the disease (86). Future studies that use this or similar approaches that target effectiveness should pay careful attention to the design of the training content.

The expected cost for the intervention could be an important barrier especially for people with a low income. Therefore, an analysis of the costs of such an intervention should be a topic for future trials. We estimate the costs for a tablet PC at EUR 100 and the monthly abonnement to the internet being about 10 Euros per month. The first visit of the PTs lasted about two hours whereas the remote supervision took about 15 min per week. With a salary of EUR 35 per hour the cost for the whole intervention (material and salary) we estimated a maximal cost of 350 euro for a 3 month intervention in Switzerland. Without the reimbursement at least of a part of the intervention by an health insurance it is unlikely this system can be successful. However, having said this, from a recent review it can be derived that the costs for a blended physiotherapy approach may also show to be substantially lower compared with traditional care (87).

This study can be seen as one of the first steps in developing an innovative complex intervention. The next steps needed for further development should preferably be guided by key principles of intervention development recommended by the United Kingdom medical research council (MRC) (88). The next phase would involve refining and optimising our earlier version of the blended exercise intervention. For this purpose we expect that a series of iterations should allow us to assess how acceptable, feasible and engaging the intervention is (88).

Limitations

No analysis was carried out on the patients who refused to participate. This could have been helpful for developing further motivational strategies and improving the recruitment rate. “Fit” and the design of the study were explained to the MD who recruited the patients, but no motivational strategies were discussed. This could also have led to an improvement in the recruitment rate.

We planned only one face-to-face visit, but the PT could organise additional visits in case deemed necessary and contact the participants regularly by phone. Whether more face-to-face sessions would increase adherence is controversial. Liu-Ambrose et al. reported a lower adherence with 4 home sessions (89), whereas Kamide et al. reported a higher adherence with only one face-to-face session (90), both in a 6-month home-based training programme with older participants (not on HD).

The low number of participants and the fact that only 6 out of 15 concluders trained regularly (at least 1.5 training sessions per week) could explain the non-significant impact of the intervention on the assessed parameters. However, the focus of our trial during this stage of development was rather on feasibility and not on effectiveness. In this context a further perceived limitation of our study could be the fact that some clinical tests were adapted or were assessed using different approaches. In future trials that focus on effectiveness it is important using tests and test protocols with known psychometric properties in sufficiently large samples.

Conclusion

If further adapted to the older HD population, a home-based exercise programme supported by a tablet and remotely supervised by a health professional may be feasible and beneficial for users who regularly exercise and are willing to be remotely monitored. Strategies to increase the perception of the benefits of physical activity and to improve the adherence to an exercise programme should be developed, including involvement of medical, nursing, and therapeutic staff. Patients could have, prior to engaging in such an unfamiliar remotely supervised blended exercise programme at home, the more complex intervention system presented to them in an HD centre.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

Ethics statement

The studies involving human participants were reviewed and approved by the regional ethics committee “Comitato etico del Canton Ticino” with ID number 2019-01161, CE 3497. The patients/participants provided their written informed consent to participate in this study (91).

Author contribution

DDZ designed the study, collected and analysed the data, and wrote the manuscript. PBP, RHK, PQ and EDB designed the study and contributed to the writing of the manuscript. OG designed the study, recruited the patients, collected data and contributed to the writing of the manuscript. GB, DG and SL recruited the patients and collected data. All authors contributed to the article and approved the submitted version..

Funding

This study was part of a 4-year health promotion project entitled “Interactive cognitive-motor home training through exergames for frail elderly” promoted by “Promozione Salute Svizzera” in collaboration with “Lega Ticinese contro i reumatismi” and Dividat AG. In this regard, Canton Ticino financed the salary of the PT, the development of “Fit”, the tablet-computers and the SIM cards. In agreement with the promoter, we included a subgroup of elderly people undergoing HD in the project. Open access funding was provided by ETH Zurich.

Acknowledgment

The authors wish to thank the PTs Alessandra Guarino and Giorgia Accardi for their professional support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fdgth.2022.1054932/full#supplementary-material.

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Keywords: tablet-computer, exercise, haemodialysis, elderly, e-health, blended intervention, physiotherapy

Citation: Zemp DD, Baschung Pfister P, Knols R, Quadri P, Bianchi G, Giunzioni D, Lavorato S, Giannini O and de Bruin E (2022) A blended e-health intervention for improving functional capacity in elderly patients on haemodialysis: A feasibility study. Front. Digit. Health 4:1054932. doi: 10.3389/fdgth.2022.1054932

Received: 27 September 2022; Accepted: 17 November 2022;
Published: 6 December 2022.

Edited by:

Subhamoy Mandal, Indian Institute of Technology Kharagpur, India

Reviewed by:

Shyam Vasudevarao, Renalyx Health Systems, India Jessica (Jess) Gorzelitz, The University of Iowa, United States

© 2022 Zemp, Baschung Pfister, Knols, Quadri, Bianchi, Giunzioni, Lavorato, Giannini and de Bruin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Eling de Bruin eling.debruin@hest.ethz.ch

Specialty Section: This article was submitted to Health Technology Implementation, a section of the journal Frontiers in Digital Health

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