Background: Populations globally are ageing, resulting in higher incidence rates of chronic diseases. Digital health platforms, designed to support those with chronic conditions to self-manage at home, offer a promising solution to help people monitor their conditions and lifestyle, maintain good health, and reduce unscheduled clinical visits. However, despite high prevalence rates of multimorbidity or multiple chronic conditions, most platforms tend to focus on a single disease. A further challenge is that despite the importance of users actively engaging with such systems, little research has explored engagement. Objective: The objectives of this study are to design and develop a digital health platform, ProACT, for facilitating older adults self-managing multimorbidity, with support from their care network, and evaluate end user engagement and experiences with this platform through a 12-month trial. Methods: The ProACT digital health platform is presented in this paper. The platform was evaluated in a year-long proof-of-concept action research trial with 120 older persons with multimorbidity in Ireland and Belgium. Alongside the technology, participants had access to a clinical triage service responding to symptom alerts and a technical helpdesk. Interactions with the platform during the trial were logged to determine engagement. Semistructured interviews were conducted with participants and analyzed using inductive thematic analysis, whereas usability and user burden were examined using validated questionnaires. Results: This paper presents the ProACT platform and its components, along with findings on engagement with the platform and its usability. Of the 120 participants who participated, 24 (20%) withdrew before the end of the study, whereas 3 (2.5%) died. The remaining 93 participants actively used the platform until the end of the trial, on average, taking 2 or 3 health readings daily over the course of the trial in Ireland and Belgium, respectively. The participants reported ProACT to be usable and of low burden. Findings from interviews revealed that participants experienced multiple benefits as a result of using ProACT, including improved self-management, health, and well-being and support from the triage service. For those who withdrew, barriers to engagement were poor health and frustration when technology, in particular sensing devices, did not work as expected. Conclusions: This is the first study to present findings from a longitudinal study of older adults using digital health technology to self-manage multimorbidity. Our findings show that older adults sustained engagement with the technology and found it usable. Potential reasons for these results include a strong focus on user-centered design and engagement throughout the project lifecycle, resulting in a platform that meets user needs, as well as the integration of behavior change techniques and personal analytics into the platform. The provision of triage and technical support services alongside the platform during the trial were also important facilitators of engagement. International Registered Report Identifier (IRRID): RR2-10.2196/22125

Background: Multimorbidity is defined as the presence of two or more chronic diseases and associated comorbidities. There is a need to improve best practices around the provision of well-coordinated, person-centered care for persons with multimorbidities. Present health systems across the European Union (EU) focus on supporting a single-disease framework of care; the primary challenge is to create a patient-centric, integrated care ecosystem to understand and manage multimorbidity. ProACT is a large-scale project funded by the European Commission under the Horizon 2020 programme, that involved the design, development, and evaluation of a digital health platform to improve and advance home-based integrated care, and supported self-management, for older adults (aged ≥65 years) living with multimorbidity. Objective: This paper describes the trial implementation protocol of a proof-of-concept digital health platform (ProACT) in 2 EU member states (Ireland and Belgium) to support older persons with multimorbidities self-managing at home, supported by their care network (CN). Methods: Research was conducted across 2 EU member states, Ireland and Belgium. A 12-month action research trial design, divided into 3 evaluation cycles and lasting 3 months each, with a reflective redesign and development phase of 1 month after cycles 1 and 2 was conducted. Participants were 120 (60/120, 50% in Ireland and 60/120, 50% in Belgium) older persons with multimorbidities diagnosed with two or more of the following chronic conditions: diabetes, chronic obstructive pulmonary disease, chronic heart failure, and cardiovascular diseases. With permission from persons with multimorbidities, members of their CN were invited to participate in the study. Persons with multimorbidities were provided with ProACT technologies (tablet, devices, or sensors) to support them in self-managing their conditions. CN members also received access to an app to remotely support their persons with multimorbidity. Qualitative and quantitative feedback and evaluation data from persons with multimorbidity and CN participants were collected across four time points: baseline (T1), at the end of each 3-month action research cycle (T2 and T3), and in a final posttrial interview (T4). Thematic analysis was used to analyze the qualitative interview data. Quantitative data were analyzed via platform use statistics (to assess engagement) and standardized questionnaires (using descriptive and inferential statistics). This study is approved by the ethics committees of Ireland and Belgium. Results: The trial implementation phase for this 44-month (2016-2019) funded study was April 2018 to June 2019. The trial outcomes are at various stages of publication since 2021. Conclusions: ProACT aims to co-design and develop a digital intervention with persons with multimorbidities and their CN, incorporating clinical guidelines with the state of the art in human-computer interaction, behavioral science, health psychology, and data analytic methods to deliver a digital health platform to advance self-management of multimorbidity at home, as part of a proactive, integrated model of supported person-centered care. International Registered Report Identifier (IRRID): RR1-10.2196/22125

Background: Achieving patient-centred care necessitates supporting individuals to have more involvement in the self-management of their care. Digital health technologies are widely recognised as a solution to empower more effective self-management. However, given the complexity of multiple chronic condition (multimorbidity) management, coupled with changes that occur as part of the normal ageing process, human support alongside digital self-management is often necessary for older people with multimorbidity (PwM) to sustain successful self-management. Methods: The aim of the study was to explore the role played by a clinical, nurse-led telephone triage service in responding to alerts generated by older adults using a digital health platform, ProACT, to self-manage multiple chronic conditions over a period of 1 year. Semi-structured interviews with participants with multimorbidity were carried out across four time points during the trial, while interviews and focus groups were conducted with triage nurses at the end of the trial. Thematic analysis was conducted on the resulting transcripts. Results: Themes found in the data include the work of triage nurses; the benefits of triage support; tensions such as anxiety due to patient monitoring; and the relationship between triage nurses and participants. Discussion: This work contributes to an understanding of how older adults with multimorbidity and triage nurses collaborate in multiple chronic disease self-management. Findings are discussed within the context of Hudon et al.'s patient-centred care framework and indicate that patient-centred care was achieved, with both PwM and triage participants reporting positive experiences, relationships and several benefits of the triage support alongside digital self-management.

Background: Exercise-based cardiac rehabilitation (CR) is recommended for coronary heart disease (CHD). However, poor uptake of and poor adherence to CR exercise programs have been reported globally. Delivering CR exercise classes remotely may remove some of the barriers associated with traditional hospital- or center-based CR. Objective: We have developed a bespoke platform, Eastern Corridor Medical Engineering Centre–Cardiac Rehabilitation (ECME-CR), to support remotely delivered CR exercise. This pilot trial sought to test the ECME-CR platform and examine the efficacy and feasibility of a remote CR exercise program compared to a traditional center-based program. Methods: In all, 21 participants with CHD were recruited and assigned to either the intervention or control group. Both groups performed the same 8-week exercise program. Participants in the intervention group took part in web-based exercise classes and used the ECME-CR platform during the intervention period, whereas participants in the control group attended in-person classes. Outcomes were assessed at baseline and following the 8-week intervention period. The primary outcome measure was exercise capacity, assessed using a 6-minute walk test (6MWT). Secondary outcomes included measurement of grip strength, self-reported quality of life, heart rate, blood pressure, and body composition. A series of mixed between-within subjects ANOVA were conducted to examine the mean differences in study outcomes between and within groups. Participant adherence to the exercise program was also analyzed. Results: In all, 8 participants (male: n=5; age: mean 69.7, SD 7.2 years; height: mean 163.9, SD 5.4 cm; weight: mean 81.6, SD 14.1 kg) in the intervention group and 9 participants (male: n=9; age: mean 69.8, SD 8.2 years; height: mean 173.8, SD 5.2 cm; weight: mean 94.4, SD 18.0 kg) in the control group completed the exercise program. Although improvements in 6MWT distance were observed from baseline to follow-up in both the intervention (mean 490.1, SD 80.2 m to mean 504.5, SD 93.7 m) and control (mean 510.2, SD 48.3 m to mean 520.6, SD 49.4 m) group, no significant interaction effect (F1,14=.026; P=.87) nor effect for time (F1,14=2.51; P=.14) were observed. No significant effects emerged for any of the other secondary end points (all P>.0275). Adherence to the exercise program was high in both the intervention (14.25/16, 89.1%) and control (14.33/16, 89.6%) group. No adverse events or safety issues were reported in either group during the study. Conclusions: This pilot trial did not show evidence of significant positive effect for either the remotely delivered or center-based program. The 6MWT may not have been sufficiently sensitive to identify a change in this cohort of participants with stable CHD. This trial does provide evidence that remote CR exercise, supported with digital self-monitoring, is feasible and may be considered for individuals less likely to participate in traditional center-based programs. International Registered Report Identifier (IRRID): RR2-10.2196/31855

Digital technologies hold great potential to improve and advance home based integrated care for older people living with multiple chronic health conditions. In this paper, we present the results of a user requirement study for a planned digital integrated care system, based on the experiences and needs of key stakeholders. We present rich, multi-stakeholder, qualitative data on the perceptions and use of technology among older people with multiple chronic health conditions and their key support actors. We have outlined our future work for the design of the system, which will involve continuous stakeholder engagement through a user-centred co-design method.

Background: Wrist-worn devices that incorporate photoplethysmography (PPG) sensing represent an exciting means of measuring heart rate (HR). A number of studies have evaluated the accuracy of HR measurements produced by these devices in controlled laboratory environments. However, it is also important to establish the accuracy of measurements produced by these devices outside the laboratory, in real-world, consumer use conditions. Objective: This study sought to examine the accuracy of HR measurements produced by the Withings ScanWatch during free-living activities. Methods: A sample of convenience of 7 participants volunteered (3 male and 4 female; mean age 64, SD 10 years; mean height 164, SD 4 cm; mean weight 77, SD 16 kg) to take part in this real-world validation study. Participants were instructed to wear the ScanWatch for a 12-hour period on their nondominant wrist as they went about their day-to-day activities. A Polar H10 heart rate sensor was used as the criterion measure of HR. Participants used a study diary to document activities undertaken during the 12-hour study period. These activities were classified according to the 11 following domains: desk work, eat or drink, exercise, gardening, household activities, self-care, shopping, sitting, sleep, travel, and walking. Validity was assessed using the Bland-Altman analysis, concordance correlation coefficient (CCC), and mean absolute percentage error (MAPE). Results: Across all activity domains, the ScanWatch measured HR with MAPE values <10%, except for the shopping activity domain (MAPE=10.8%). The activity domains that were more sedentary in nature (eg, desk work, eat or drink, and sitting) produced the most accurate HR measurements with a small mean bias and MAPE values <5%. Moderate to strong correlations (CCC=0.526-0.783) were observed between devices for all activity domains, except during the walking activity domain, which demonstrated a weak correlation (CCC=0.164) between devices. Conclusions: The results of this study show that the ScanWatch measures HR with a degree of accuracy that is acceptable for general consumer use; however, it would not be suitable in circumstances where more accurate measurements of HR are required, such as in health care or in clinical trials. Overall, the ScanWatch was less accurate at measuring HR during ambulatory activities (eg, walking, gardening, and household activities) compared to more sedentary activities (eg, desk work, eat or drink, and sitting). Further larger-scale studies examining this device in different populations and during different activities are required.