Participatory design of a digital platform for cardiovascular disease self-management: mutual learning through an iterative development process (Preprint)

BACKGROUND People living with cardiovascular disease (CVD) require flexible self-management support for health behaviour change for CVD secondary prevention. Digital health interventions can assist with these complex self-management activities. Many stakeholder groups can be involved in digital health design, including people living with CVD (users), researchers, healthcare professionals and technology developers. However, decision-making and aligning views can be difficult to negotiate within interdisciplinary teams, so the use of appropriate methodological strategies is vital. OBJECTIVE The aim of this paper was to design and develop Salvio, and to reflect on the methodological considerations that were the driving forces of this participatory design process. METHODS A triangulation of research methods was used for this iterative development process. Participatory design approaches used included guided group discussions, activity-based workshops, and think-aloud tasks. Data collection was supported by self-efficacy theory to encourage user contributions. Over a 12-month period, participants met at various time points to collectively design and develop Salvio. Workshops were 2-3 hours in length and were facilitated in small groups of 4-6 participants per session. All sessions were audio-recorded, central parts of workshop conversations were transcribed, and qualitative content analysis of data was undertaken. RESULTS Users (n=8) worked collaboratively with researchers (n=6) and technology developers (n=7). Findings indicated that it was critical to include an interdisciplinary team with a wide range of expertise, to build a meaningful and flexible digital platform. Effective methodological strategies were essential for genuine participation and continuous conflict resolution. Our research highlighted key elements that added to the success of this co-design process including i) the creation of a collaborative space where all voices were acknowledged and considered and ii) the effective translation of information during decision-making stages. CONCLUSIONS Future research is needed to expand and evaluate participatory design tools and techniques which challenge the power relations between users and other stakeholders. By exploring methods that create space for mutual learning and resolving conflict through systematic decision-making, complex digital platforms for health behaviour change can be successfully developed with diverse groups. It is clear that flexible digital platforms may be valuable to users, but further research will also be required for the successful implementation and knowledge translation of these contemporary developments.

Recognizing and Responding to Elder Mistreatment: Developing and Testing an Online Training for EMS Practitioners

Elder mistreatment is an urgent and under recognized public health concern with devastating consequences for older adults, families, and health systems. Risk for elder mistreatment has increased during the COVID-19 pandemic, further highlighting the urgency to address it. Prehospital emergency medical service (EMS) practitioners have unique opportunities to recognize signs of elder mistreatment but often lack the training and tools required to facilitate consistent identification and intervention. To address this gap, Education Development Center collaborated with a team of expert advisors and EMS practitioners to develop and pilot test Recognizing and Responding to Elder Mistreatment: An Online Training for EMS Practitioners with funding from the RRF Foundation for Aging. This training aims to prepare EMS practitioners to recognize potential mistreatment and report suspected elder mistreatment in line with state laws and their professional code of ethics. In this presentation, we will describe the iterative development process, present results from a pilot test conducted with EMS practitioners in Massachusetts and share strategies and progress for disseminating the training nationally. The pilot study utilized a pre-post design to assess changes in knowledge, attitudes, and practices at baseline, immediately after and two months following participation in the training. Results indicate statistically significant improvements in knowledge related to elder mistreatment identification and response from pre- to post-training and maintenance of these improvements two months later. Participants reported feeling more prepared to address elder mistreatment in their work as EMS practitioners and applying their new knowledge and skills during the two months following the training.

Virtual Testing of Seniors: The Feasibility of Research with Online Neuropsychological Tests (FRONT)

Synergic@Home is a feasibility study evaluating the effects of exercise and cognitive interventions for the prevention of dementia in at-risk individuals over age 60. The COVID-19 pandemic changed the study’s methods, with standardized neuropsychological tests needing to be administered virtually. Experience and research into the viability of neuropsychological assessments administered virtually is limited. After receiving permission to adapt the tests for virtual administration, a neuropsychologist, project managers, and research coordinators developed their approach. A PowerPoint presentation using text and visual stimuli from the tests was developed with on-screen instructions for the raters. An iterative development process involved feedback from the team in order to maximize the fidelity of these methods compared to in-person administration. Mock assessments supervised by a neuropsychologist further refined the methods and confirmed rater adherence to standardized procedures. A secure videoconferencing platform meeting privacy requirements was used. Dual monitors for the raters provided instructions on one monitor while stimuli for the participant was on the second monitor. The participant could only see the stimuli. This method of administering neuropsychological assessment, the Feasibility of Research with Online Neuropsychological Testing (FRONT), is being used to evaluate older adult participants in Synergic@Home. Results from this feasibility study may set the stage for new research methodologies and/or clinical evaluations in the future. This project is funded by the New Brunswick Healthy Seniors Pilot Project and the Canadian Consortium on Neurodegeneration in Aging (with grants from Public Health Agency of Canada and the Canadian Institutes of Health Research, with additional funding partners).

Dynamic Iteration Method: New Approach to Cultural Events Management

This article provides project managers, the cultural events organizers, a new approach to plan preparation and to the monitoring of events realization. The Dynamic Iteration Method introduced in this article is based on the system dynamic modelling and on the principles of project iterative development. The plan model and the reality model are structurally similar; they differ in values of exogenous variables. The new approach enables to easily monitor the real project course in close connection with the plan and to take timely controlling steps. The effects resulting from the manager´s decisionmaking process are compared with the plan in regular iterations. The method thus reminds of a traveller whose route is adjusted by a GPS navigation system.

Machine Learning to Predict Brain Amyloid Pathology in Pre-dementia Alzheimer’s Disease Using QEEG Features and Genetic Algorithm Heuristic

The use of positron emission tomography (PET) as the initial or sole biomarker of β-amyloid (Aβ) brain pathology may inhibit Alzheimer’s disease (AD) drug development and clinical use due to cost, access, and tolerability. We developed a qEEG-ML algorithm to predict Aβ pathology among subjective cognitive decline (SCD) and mild cognitive impairment (MCI) patients, and validated it using Aβ PET. We compared QEEG data between patients with MCI and those with SCD with and without PET-confirmed beta-amyloid plaque. We compared resting-state eyes-closed electroencephalograms (EEG) patterns between the amyloid positive and negative groups using relative power measures from 19 channels (Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2), divided into eight frequency bands, delta (1–4 Hz), theta (4–8 Hz), alpha 1 (8–10 Hz), alpha 2 (10–12 Hz), beta 1 (12–15 Hz), beta 2 (15–20 Hz), beta 3 (20–30 Hz), and gamma (30–45 Hz) calculated by FFT and denoised by iSyncBrain®. The resulting 152 features were analyzed using a genetic algorithm strategy to identify optimal feature combinations and maximize classification accuracy. Guided by gene modeling methods, we treated each channel and frequency band of EEG power as a gene and modeled it with every possible combination within a given dimension. We then collected the models that showed the best performance and identified the genes that appeared most frequently in the superior models. By repeating this process, we converged on a model that approximates the optimum. We found that the average performance increased as this iterative development of the genetic algorithm progressed. We ultimately achieved 85.7% sensitivity, 89.3% specificity, and 88.6% accuracy in SCD amyloid positive/negative classification, and 83.3% sensitivity, 85.7% specificity, and 84.6% accuracy in MCI amyloid positive/negative classification.

A RE-AIM evaluation in early adopters to iteratively improve the online BeUpstanding™ program supporting workers to sit less and move more

Background The web-based BeUpstanding program supports desk workers to sit less and move more. Successfully translated from a research-delivered intervention, BeUpstanding has gone through iterative development and evaluation phases in preparation for wide-scale implementation. In the third planned “early-adopters” phase (01/09/2017–11/06/2019), the program was made freely-available online. An integrated delivery and evaluation platform was also developed to enable workplace champions to run and evaluate the intervention within their work team independent of researcher support. Using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, this study reports on the extent to which the program and processes were “fit-for-purpose” for a national implementation trial across the indicators of uptake (reach and adoption), implementation and engagement, and effectiveness for behaviour change. Methods Data were collected via the online surveys embedded in the program and through program access analytics. Descriptive data (with linearized variance for the clustered staff-level data) and results from mixed models (repeated data and clustering for pre-post changes) are reported. Results Despite purposeful limited promotion, uptake was good, with 182 Australian users initially registering (208 total) and 135 (from 113 organisations) then completing the sign-up process. Recruitment reached users across Australia and in 16 of 19 Australian industries. Implementation was inconsistent and limited, with signed-up users completing 0 to 14 of the program’s 14 steps and only 7 (5.2%) completing all seven core steps. Many champions (n = 69, 51.1%) had low engagement (1 day toolkit usage) and few (n = 30, 22%) were highly engaged (> 1 day toolkit usage and surveyed staff). Although only 18 users (7 organisations) performed the pre- and post-program staff evaluations (337 and 167 staff, respectively), pre-post changes showed the program effectively reduced workplace sitting by − 9.0% (95% CI -12.0, − 5.9%). Discussion The program had uptake across industries and across Australia, but implementation and engagement varied widely. Few workplaces completed the evaluation components. In those that did, the program was effective for the primary outcome (workplace sitting). Conducting a planned early adopters phase and a comprehensive evaluation according to RE-AIM helped highlight necessary program improvements to make it more suitable for wide-scale implementation and evaluation. Trial registration Australian and New Zealand Clinic Trials Registry ACTRN12617000682347. Date registered: 12/05/2017.

A progressive development of a visual analysis interface of climate-related VGI

This paper describes the progressive development of three approaches of successively increasing analytic functionality for visually exploring and analysing climate-related volunteered geographic information. The information is collected in the CitizenSensing project within which urban citizens voluntarily submit reports of site-specific extreme weather conditions, their impacts, and recommendations for best-practice adaptation measures. The work has pursued an iterative development process where the limitations of one approach have become the trigger for the subsequent ones. The proposed visual exploration approaches are: an initial map application providing a low-level data overview, a visual analysis prototype comprising three visual dashboards for more in-depth exploration, and a final custom-made visual analysis interface, the CitizenSensing Visual Analysis Interface (CS-VAI), which enables the flexible multifaceted exploration of the climate-related geographic information in focus. The approaches developed in this work are assessed with volunteered data collected in two of the CitizenSensing project’s campaigns held in the city of Norrköping, Sweden.

Using an Individual-Centered Approach to Gain Insights From Wearable Data in the Quantified Flu Platform: Netnography Study

Background Wearables have been used widely for monitoring health in general, and recent research results show that they can be used to predict infections based on physiological symptoms. To date, evidence has been generated in large, population-based settings. In contrast, the Quantified Self and Personal Science communities are composed of people who are interested in learning about themselves individually by using their own data, which are often gathered via wearable devices. Objective This study aims to explore how a cocreation process involving a heterogeneous community of personal science practitioners can develop a collective self-tracking system for monitoring symptoms of infection alongside wearable sensor data. Methods We engaged in a cocreation and design process with an existing community of personal science practitioners to jointly develop a working prototype of a web-based tool for symptom tracking. In addition to the iterative creation of the prototype (started on March 16, 2020), we performed a netnographic analysis to investigate the process of how this prototype was created in a decentralized and iterative fashion. Results The Quantified Flu prototype allowed users to perform daily symptom reporting and was capable of presenting symptom reports on a timeline together with resting heart rates, body temperature data, and respiratory rates measured by wearable devices. We observed a high level of engagement; over half of the users (52/92, 56%) who engaged in symptom tracking became regular users and reported over 3 months of data each. Furthermore, our netnographic analysis highlighted how the current Quantified Flu prototype was a result of an iterative and continuous cocreation process in which new prototype releases sparked further discussions of features and vice versa. Conclusions As shown by the high level of user engagement and iterative development process, an open cocreation process can be successfully used to develop a tool that is tailored to individual needs, thereby decreasing dropout rates.