Exploring the usability, user experience and usefulness of a supportive website for people with dementia and carers

PURPOSE

This study explores the usability, usefulness and user experience of the Forward with Dementia website for people with dementia and family carers, and identifies strategies to improve web design for this population.

METHODS

The website was iteratively user-tested by 12 participants (five people with dementia, seven carers) using the Zoom platform. Data collection involved observations, semi-structured interviews and questionnaires. Integrative mixed-method data analysis was used, informed by inductive thematic qualitative analysis.

RESULTS

Users of Version 1 of the website experienced web functionality, navigation and legibility issues. Strategies for desirable web design were identified as simplifying functions, streamlining navigation and decluttering page layouts. Implementation of strategies produced improvements in usability, user experience and usefulness in Version 2, with mean System Usability Scale scores improving from 15 to 84, and mean task completion improving from 55% to 89%. The user journey for people with dementia and carers overlapped, but each group had their own unique needs in the context of web design.

CONCLUSIONS

The interplay between a website's content, functionality, navigation and legibility can profoundly influence user perceptions of a website. Dementia-related websites play an important role in informing audiences of management strategies, service availability and planning for the progression of dementia. Findings of this study may assist in guiding future web development targeting this population.

Unlocking the Value: Quantifying the Return on Investment of Hospital Artificial Intelligence

PURPOSE

A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in adopting AI.

METHODS

A calculator was constructed to calculate comparative costs, estimated revenues, and quantify the clinical value of using an AI platform compared with no use of AI in radiology workflows of a US hospital over a 5-year time horizon. Parameters were determined on the basis of expert interviews and a literature review. Scenario and deterministic sensitivity analyses were conducted to evaluate calculator drivers.

RESULTS

In the calculator, the introduction of an AI platform into the hospital radiology workflow resulted in labor time reductions and delivery of an ROI of 451% over a 5-year period. The ROI was increased to 791% when radiologist time savings were considered. Time savings for radiologists included more than 15 8-hour working days of waiting time, 78 days in triage time, 10 days in reading time, and 41 days in reporting time. Using the platform also provided revenue benefits for the hospital in bringing in patients for clinically beneficial follow-up scans, hospitalizations, and treatment procedures. Results were sensitive to the time horizon, health center setting, and number of scans performed. Among those, the most influential outcome was the number of additional necessary treatments performed because of AI identification of patients.

CONCLUSIONS

The authors demonstrate a substantial 5-year ROI of implementing an AI platform in a stroke management-accredited hospital. The ROI calculator may be useful for decision makers evaluating AI-powered radiology platforms.

The impact of non-pharmacological interventions on adherence to medication and persistence in dyslipidaemia and hypertension: a systematic review

INTRODUCTION

Suboptimal medication adherence is common among patients with cardiovascular diseases. We sought evidence on non-pharmacological interventions used to support adherence for patients with hypertension and/or dyslipidemia.

METHODS

We searched MEDLINE, EMBASE, MEDLINE In-Process, ClinicalTrials.gov, EUCTR, and conference proceedings from July 2011 to July 2021 to identify trials evaluating effects of health education, phone reminders, or digital interventions on medication adherence or persistence of adult patients with hypertension and/or dyslipidemia. Risk of bias was assessed using the Cochrane Risk of Bias Assessment Tool v2.

RESULTS

Of 64 studies, 62 used health education approaches (e.g. educational interviews, motivational meetings, advice from physicians, and mobile health content), 16 phone reminders (e.g. text reminders, electronic pill-box linked reminders, bi-directional text messaging), and 10 digital applications as interventions (e.g., various self-management applications). All studies assessed medication adherence; only two persistence. Overall, 30 studies (83%) assessing health education approaches alone and 25 (78%) combined with other strategies, 12 (75%) phone reminders and eight studies (80%) digital applications combined with other strategies reported improved medication adherence. Two studies assessing health education approaches reported improved persistence.

CONCLUSIONS

Our findings indicate non-pharmacological interventions may positively impact adherence. Therefore, 'beyond the pill' approaches could play a role in preventing cardiovascular diseases.

Interventions to reduce stress and prevent burnout in healthcare professionals supported by digital applications: a scoping review

Aim

Healthcare professionals are at increased risk of burnout, primarily due to workplace-related stressors. The COVID-19 pandemic has further increased this risk. Different interventions exist with varying degrees of effectiveness; little is reported on the content and implementation of such programs. This review fills this gap, with attention to recent programs using digital components.

Methods

PubMed, Embase, PsycInfo, and Google Scholar were searched between January 24th and 28th, 2022, limited to the last 5 years (≥2017). Articles were included if they (1) focused on stress reduction or burnout prevention for nurses and medical doctors within workplace health promotion for nurses or medical doctors, (2) included a digital program component, (3) were conducted in high-income country contexts, and (4) were clinical studies published in English or German. Data was extracted using a priori designed spreadsheets. A group of at least 2 authors at each stage carried out the screening, selection, and data extraction.

Results

The search strategy identified 153 articles, all except 7 were excluded. Two studies were conducted in the USA, two in Spain, one in the Netherlands, Poland, and Korea each. Four studies used a randomized study design, all but one had a control group. A wide range of outcome measures was used. The types of interventions included an adapted mindfulness-based stress reduction program combined with aspects of behavioral therapies, cognitive behavioral therapy, or acceptance and commitment therapy. The digital components used were apps (4 studies), a digital platform, blended learning, and a web-based intervention (1 study each). Six studies focused on individual interventions, one included organizational interventions.

Conclusion

Despite an acute burnout crisis in the healthcare sector, only seven recent interventions were found that integrated digital components. Several problems emerged during the implementation of the interventions that made it clear that organizational support is urgently needed for successful implementation. Although interventions for stress reduction and burnout prevention should combine individual and organizational measures to be as successful as possible, this was only partially the case in one of the intervention programs. The results of this scoping review can be used to further develop or optimize stress and burnout prevention programs.

Digital applications as a means for promotion of healthy behaviours among Albanian children

Digital applications can be effective tools for strengthening school-based health education programs as they can provide valuable health information to children through interactive videos, quizzes and games. We aimed at assessing the change in the prevalence of healthy behaviours among children exposed to digital applications (intervention) employed for promoting healthy behaviours. We conducted a cross-sectional study before the intervention in March 2022 including a representative sample of 1500 Albanian schoolchildren (≈54% girls) aged 12-15 years. In June 2022, after 4-month exposure to digital applications aimed at promoting healthy behaviours (intervention), we carried out a second cross-sectional study in the same sample of schoolchildren. In both survey rounds, an anonymous and structured self-administered questionnaire inquired children about a range of behavioural practices including nutrition, oral health, physical activity and hygiene practices. After the intervention, overall, there was evidence of a significant increase in the prevalence of all healthy behavioural practices measured: ~9% for breakfast consumption and/or environmental protection, 12% for toothbrushing, 14% for handwashing, 15% for leisure time physical exercise and 24% for adequate fruit and vegetable intake (all p < 0.001). Engagement in healthy behaviours only after the intervention was higher among rural children (from 18% for breakfast consumption to 37% for handwashing and/or adequate fruit and vegetable intake) and especially those pertinent to Roma/Egyptian communities (from 18% for breakfast consumption to 46% for adequate fruit and vegetable intake), except for engagement in safe environmental protection which was more prevalent among urban residents (28% vs. 15% among rural children) and ethnic Albanian children (24% vs. 13% among Roma/Egyptian children). Our findings from Albania indicate that digital applications can be useful for strengthening school-based health promotion programs.

When Is a Change Significant? The Update Problem of Apps in Medical and Behavioral Research

Digital applications (apps) are commonly used across the research ecosystem. While apps are frequently updated in the course of clinical and behavioral research, there is limited guidance as to when an app update should trigger action related to human research participant protections and who should be responsible for monitoring and reviewing these updates. We term this the "update problem" and argue that, while it is the principal investigator's duty to track all relevant updates, the level of involvement and re-review by the institutional review board (IRB) of an approved research protocol should vary depending on whether the update may be classified as minor, not minor, or significant. Minor updates require at most annual notification of the IRB, updates that are not minor require prompt notification of the IRB, and significant updates may require full board re-review or another response. We also suggest how these policies might be implemented.

Prediction of Chronic Obstructive Pulmonary Disease Exacerbation Events by Using Patient Self-reported Data in a Digital Health App: Statistical Evaluation and Machine Learning Approach

Background

Self-reporting digital apps provide a way of remotely monitoring and managing patients with chronic conditions in the community. Leveraging the data collected by these apps in prognostic models could provide increased personalization of care and reduce the burden of care for people who live with chronic conditions. This study evaluated the predictive ability of prognostic models for the prediction of acute exacerbation events in people with chronic obstructive pulmonary disease by using data self-reported to a digital health app.

Objective

The aim of this study was to evaluate if data self-reported to a digital health app can be used to predict acute exacerbation events in the near future.

Methods

This is a retrospective study evaluating the use of symptom and chronic obstructive pulmonary disease assessment test data self-reported to a digital health app (myCOPD) in predicting acute exacerbation events. We include data from 2374 patients who made 68,139 self-reports. We evaluated the degree to which the different variables self-reported to the app are predictive of exacerbation events and developed both heuristic and machine learning models to predict whether the patient will report an exacerbation event within 3 days of self-reporting to the app. The model’s predictive ability was evaluated based on self-reports from an independent set of patients.

Results

Users self-reported symptoms, and standard chronic obstructive pulmonary disease assessment tests displayed correlation with future exacerbation events. Both a baseline model (area under the receiver operating characteristic curve [AUROC] 0.655, 95% CI 0.689-0.676) and a machine learning model (AUROC 0.727, 95% CI 0.720-0.735) showed moderate ability in predicting exacerbation events, occurring within 3 days of a given self-report. Although the baseline model obtained a fixed sensitivity and specificity of 0.551 (95% CI 0.508-0.596) and 0.759 (95% CI 0.752-0.767) respectively, the sensitivity and specificity of the machine learning model can be tuned by dichotomizing the continuous predictions it provides with different thresholds.

Conclusions

Data self-reported to health care apps designed to remotely monitor patients with chronic obstructive pulmonary disease can be used to predict acute exacerbation events with moderate performance. This could increase personalization of care by allowing preemptive action to be taken to mitigate the risk of future exacerbation events.

Covidseeker: A Geospatial Temporal Surveillance Tool

Introduction: Geospatial temporal data derived from smartphones traditionally used for purposes of navigation may offer valuable information for public health surveillance and locational hot spotting. Our objective was to develop a web-based application, called Covidseeker, that captures continuous fine-grained geospatial temporal data from smartphones and leverages these data to study transmission patterns of COVID-19. Methods: This report describes the development of Covidseeker and the process by which it utilizes geospatial temporal data from smartphones and processes it into a usable format to study geospatial temporal patterns of COVID-19. We provide an overview of the design process, the principles, the software architecture, and the dashboard of the Covidseeker application and consider key challenges and strategic uses of capturing geospatial temporal data and the potential for future applications in outbreak surveillance. Results: A resource such as Covidseeker can support situational awareness by providing information about the location and timing of transmission of diseases such as COVID-19. Geospatial temporal data housed in smartphones hold tremendous potential to capture more depth about where and when transmission occurs and the patterns of human mobility that lead to increases in risk of COVID-19. Conclusion: An enormous and highly rich source of geospatial temporal information about human mobility can be used to provide highly localized discrete information that is difficult to capture by traditional sources. The architecture of Covidseeker can be applied to help track COVID-19 and should be integrated with traditional disease surveillance practices.

Moving Food Assistance into the Digital Age: A Scoping Review

One of the most basic needs globally, food assistance refers to the multitude of programs, both governmental and non-governmental, to improve food access and consumption by food-insecure individuals and families. Despite the importance of digital and mobile Health (mHealth) strategies in food insecurity contexts, little is known about their specific use in food assistance programs. Therefore, the purpose of this study was to address that gap by conducting a scoping review of the literature. Keywords were defined within the concepts of food assistance and digital technology. The search included relevant peer-reviewed and grey literature from 2011 to 2021. Excluded articles related to agriculture and non-digital strategies. PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. The final synthesis included 39 studies of which most (84.6%) were from the last five years and United States-based (93.2%). The top three types of articles or studies included text and opinion, qualitative research, and website, application, or model development (17.9%). The top three types of digital tools were websites (56.4%), smartphone applications (20.5%), and chatbots (5.1%). Nineteen digital features were identified as desirable. Most tools included just one or two features. The most popular feature to include was online shopping (n = 14), followed by inventory management, and client tracking. Digital tools for individual food assistance represent an opportunity for equitable and stable access to programs that can enhance or replace in-person services. While this review identified 39 tools, all are in early development and/or implementation stages. Review findings highlight an overall lack of these tools, an absence of user-centered design in their development, and a critical need for research on their effectiveness globally. Further analysis and testing of current digital tool usage and interventions examining the health and food security impacts of such tools should be explored in future studies, including in the context of pandemics, where digital tools allow for help from a distance.

Digital Strategies to Improve Food Assistance in Disasters: A Scoping Review

OBJECTIVE

Modern digital strategies, including Internet of Things, machine learning, and mobile applications, have revolutionized situational awareness during disaster management. Despite their importance, no review of digital strategies to support emergency food security efforts has been conducted. This scoping review fills that gap.

METHODS

Keywords were defined within the concepts of food assistance, digital technology, and disasters. After the database searches, PRISMA guidelines were followed to perform a partnered, 2-round scoping literature review.

RESULTS

The search identified 3201 articles, and 26 articles met criteria and were included in the analysis. The data types used to describe the tools were text/opinion (42.3%), qualitative (23.1%), system architecture (19.2%), quantitative and qualitative (11.5 %), and quantitative (3.8%). The tools' main functions were Resource Allocation (41.7%), Data Collection and Management (33%), Interagency Communications (15.4 %), Beneficiary Communications (11.5%), and Fundraising (7.7%). The platforms used to achieve these goals were Mobile Application (36%), Internet of Things (20%), Website (20%), and Mobile Survey (8%); 92% covered the disaster response phase.

CONCLUSIONS

Digital tools for planning, situational awareness, client choice, and recovery are needed to support emergency food assistance, but there is a lack of these tools and research on their effectiveness across all disaster phases.

Development of Respercise® a Digital Application for Standardizing Home Exercise in COPD Clinical Trials

Background

Pulmonary rehabilitation (PR) is an important therapy for patients with chronic obstructive pulmonary disease (COPD), yet uptake remains low. Intervention strategies which recapitulate the benefits of PR are, therefore, needed and digital, home-based therapies present opportunity in this space. Digital therapies also potentially offer an opportunity to standardize PR in clinical trials for new COPD therapies.

Aims and Methods

We aimed to create a digital application (app), Respercise^®, consisting of up to 4 strengthening exercises in conjunction with Therbands™ and a daily physical activity program with individualized step goals, and to test its feasibility in a clinical trial. App usability was surveyed qualitatively before development iterations and deployment in a 13-week interventional clinical trial. All participants who completed the study were invited for an exit interview and performed the 5-repetition sit-to-stand test amongst other measures.

Results

Feedback from clinical trial participants was positive; 97% of respondents liked the app. A total of 88% of participants reported that it was easy to fit the exercises into their daily routine, and there was over 90% adherence for entering daily step counts. Notably, on day 90 both females and males using Respercise alone demonstrated a 2.22- and 2.27-seconds improvement in time for 5-repetition sit-to-stand tests respectively, above the 1.7 second threshold that is considered clinically meaningful in COPD.

Conclusions

Respercise can be successfully deployed in clinical trials, offering the opportunity for standardization of exercise in clinical trials and, with further development, could have wider reach as a home-based intervention for individuals with COPD.