Challenges of Creating a Peer Support Online Community for Patients With Diabetes-A Case Study.

This study aims to explore the challenges and strategies in creating online communities for individuals with diabetes, emphasizing their role in fostering connections among individuals facing similar health conditions. Using a single-case approach, we investigated the design process of a diabetes online community using the classic waterfall model. Participants were recruited from a diabetes local association, and usability was assessed using the System Usability Scale and the think-aloud method.

Challenges Implementing Patient and Public Involvement in a Digital Health Agile Project Which Includes Research, Business and Software Development.

Patient and public involvement (PPI) is a practice for involving future users in the design, development, and research of health technologies. There is increasing interest and demand for PPI, but little evidence based methodological support for integrating PPI in agile development processes. Multiple sclerosis (MS) is a chronic condition that severely impacts the lives of patients and requires active patient involvement.

Use of Patient-Generated Health Data From Consumer-Grade Devices by Health Care Professionals in the Clinic: Systematic Review.

Background: Mobile health (mHealth) uses mobile technologies to promote wellness and help disease management. Although mHealth solutions used in the clinical setting have typically been medical-grade devices, passive and active sensing capabilities of consumer-grade devices like smartphones and activity trackers have the potential to bridge information gaps regarding patients' behaviors, environment, lifestyle, and other ubiquitous data. Individuals are increasingly adopting mHealth solutions, which facilitate the collection of patient-generated health data (PGHD).

Impact of Digital Interventions on the Treatment Burden of Patients With Chronic Conditions: Protocol for a Systematic Review.

Background: There is great potential for delivering cost-effective, quality health care for patients with chronic conditions through digital interventions. Managing chronic conditions often includes a substantial workload required for adhering to the treatment regimen and negative consequences on the patient's function and well-being. This treatment burden affects adherence to treatment and disease outcomes.

The Use of Patient-Generated Health Data From Consumer-Grade Mobile Devices in Clinical Workflows: Protocol for a Systematic Review.

Background: With the rapid advancement of mobile technology, the scope of mobile health (mHealth) has expanded to include consumer-grade devices such as smartphones and wearable sensors. These solutions have typically been used for fitness purposes; however, due to their ubiquitous capabilities for data collection, they have the potential to bridge information gaps and supplement data from clinical visits. Patient-generated health data (PGHD) can be derived from mHealth solutions and be used by health care professionals (HCPs) as complementary tools in the care process, yet their integration into clinical workflows presents a myriad of challenges.

Health Care Professionals' Perspectives on the Uses of Patient-Generated Health Data.

Integration of digital self-management solutions into health care processes requires the involvement of health care professionals in the adoption and use of the solutions as part of the care pathway. We conducted 23 interviews with diverse profiles of health care professionals participating in the treatment of chronic patients in three different countries. Our results indicate that health care professionals appeared relatively motivated at the prospect of having access to patient-generated data.

Experiences Using Patient and Public Involvement in Digital Health Research for Multiple Sclerosis.

Patient and public involvement (PPI) is increasingly used for improving quality of the research. There are many barriers in translating PPI into practice, including lacking examples of good practices. Frameworks that have been developed in one setting do not readily transfer to other settings.

A Conceptual Framework to Design Connected Mental Health Solutions in the United Arab Emirates: Questionnaire Study.

Background: Connected mental health (CMH) is a field presenting information and communications technology-based mental care interventions that could help overcome many mental care delivery barriers. Culture and background influence people's attitudes, preferences, and acceptance of such solutions. Therefore, the suitability of CMH solutions to the targeted population is an important factor in their successful adoption.

The effect of Covid-19 in digital media use of Finnish physicians - Four wave longitudinal panel survey.

Background: Covid-19 pandemic has boosted digitalization in healthcare, as mobility restrictions and social distancing rules have made healthcare providers to adopt digital tools to replace or complement face-to-face interactions.

Purpose: We discuss the effects of Covid-19 pandemic on physicians' use of digital media. We examine whether Covid-19 conditions have changed how physicians use internet resources for information search, how they engage in social media, and their attitude towards online events.

Rehabilitation Needs of Head and Neck Cancer Patients and Stakeholders: Case Study.

Background: The incidents of Head and Neck Cancer (HNC) are rising worldwide, suggesting that this type of cancer is becoming more common. The foreseen growth of incidents signifies that future rehabilitation services will have to meet the needs of a wider population.

Objective: The aim of this paper is to explore the needs of patients, caregivers and healthcare professionals during HNC rehabilitation.

Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning.

Background: Advanced sensor, measurement, and analytics technologies are enabling entirely new ways to deliver health care. The increased availability of digital data can be used for data-driven personalization of care. Data-driven personalization can complement expert-driven personalization by providing support for decision making or even by automating some parts of decision making in relation to the care process.

Challenges and opportunities for telehealth in the management of chronic obstructive pulmonary disease: a qualitative case study in Greece.

Background: Telehealth (TH) was introduced as a promising tool to support integrated care for the management of chronic obstructive pulmonary disease (COPD). It aims at improving self-management and providing remote support for continuous disease management. However, it is often not clear how TH-supported services fit into existing pathways for COPD management.

Insurance Customers' Expectations for Sharing Health Data: Qualitative Survey Study.

Background: Insurance organizations are essential stakeholders in health care ecosystems. For addressing future health care needs, insurance companies require access to health data to deliver preventative and proactive digital health services to customers. However, extant research is limited in examining the conditions that incentivize health data sharing.

Developing a Smartphone Application to Support Smoking Behavior Change through Social Comparison.

The growing field of mHealth has often dealt with the modification of harmful behaviors, such as smoking, that are associated with medical conditions. Smoking behavior has been targeted by numerous mHealth smoking cessation interventions with the help of a wide range of behavior change support (BCS) techniques. However, the exploitation of the established BCS technique of social comparison by mHealth research on smoking cessation has been limited.

Connected Health User Willingness to Share Personal Health Data: Questionnaire Study.

Background: Connected health has created opportunities for leveraging health data to deliver preventive and personalized health care services. The increasing number of personal devices and advances in measurement technologies contribute to an exponential growth in digital health data. The practices for sharing data across the health ecosystem are evolving as there are more opportunities for using such data to deliver responsive health services.

The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study.

Background: This study examines the development of the connected health (CH) research landscape with a view to providing an overview of the existing CH research. The research field of CH has experienced rapid growth coinciding with increasing pressure on health care systems to become more proactive and patient centered.

Objective: This study aimed to assess the extent and coverage of the current body of knowledge in CH.

Personal health data: A systematic mapping study.

Background: Personal health data (PHD) research has been intensified over the last years, attracting the attention of scientists from different fields, such as software engineers, computer scientists and medical professionals. The increasing interest of researchers can be attributed to the exponential growth of the available PHD due to the widespread adoption of ubiquitous technology in everyday life, as well as to the potential of the ongoing digital transformation in healthcare. This increasing interest requires that academia has an overview of the published scientific literature to plan future endeavors.

Feasibility of digital footprint data for health analytics and services: an explorative pilot study.

Background: As a result of digitalization, data is available about almost every aspect of our lives. Personal data collected by individuals themselves or stored by organizations interacting with people is known as a digital footprint. The purpose of this study was to identify prerequisites for collecting and using digital data that could be valuable for health data analytics and new health services.

Collecting a citizen's digital footprint for health data mining.

This paper describes a case study for collecting digital footprint data for the purpose of health data mining. The case study involved 20 subjects residing in Finland who were instructed to collect data from registries which they evaluated to be useful for understanding their health or health behaviour, current or past. 11 subjects were active, sending 100 data requests to 49 distinct organizations in total.