Integrating Behavioral Trigger Messages into a mHealth System Design for Chronic Disease Management

Recent changes in health information technology have dramatically altered the face, delivery, and management of healthcare particularly as it relates to mHealth. With increases in smart phone ownership, mHealth potentially has the ability to provide far-reaching transformation of chronic disease management particularly when aligned with behavioral change theories and persuasive technology. MHealth applications have an advantage over computers and various print communications as the consumer can engage with the application at any time and at any location. The Interactive Health Communication Application (IHCA) states that by combining support mechanisms such as behavior change theories into electronic devices as a method to transmit or receive health information can potentially lead to changes in knowledge, motivation and self-efficacy. Adding constructs of the Fogg Behavior Model, Social Cognitive Theory and Persuasive Technology to the IHCA framework can create an engaged persuasive system leading to improvements in self-efficacy, self-management and knowledge. The hypotheses for our study are 1) participants will demonstrate improved scores on self-efficacy, knowledge and self-management following the intervention period, 2) participants will be more engaged in the usage of capABILITY following behavioral triggers, and 3) participants who receive spark triggers involving motivation will engage in the utilization of capABILITY faster than those who receive facilitator triggers. The results of this study provide important findings for 1) mHealth system design utilizing IHCA with new constructs for chronic disease management, 2) design and develop of persuasive spark and facilitator trigger messages, and 3) understanding of user engagement when behavioral (spark and facilitator) trigger messages are utilized. The findings of the study revealed that self-efficacy, self-management, and knowledge did improve post intervention. In addition, the study showed that spark triggers continually cued participants to engage with capABILITY quicker than facilitator triggers

Persuasive Technology: Designing Mobile Health Triggers to Impact Health Behavior

Persuasive technology is an interactive computer technology designed to alter people’s attitudes or behaviors. Behavior change in mHealth solutions is often promoted through the use of specific messages called triggers. Fogg, in his work, identified three types of triggers: sparks, facilitators and signals. Each trigger is believed to have a different intent. Sparks provide motivation, facilitators support achievement of a goal, and signals provide simple reminders. While these triggers are theoretically distinct, specifications of the message development are absent in the literature. Here, we describe the challenges in implementing the different types of triggers into comparable but distinct messages. We describe the iterative development used to operationalize trigger messages into reliably distinct categories

Medical Internet of Things: A Survey of the Current Threat and Vulnerability Landscape

The Internet of things (IoT) is a system that utilizes the Internet to facilitate communication between sensors and devices. Given the ubiquitous nature of IoT devices, it is seemingly inevitable that IoT would be used as a conduit to transform healthcare. One such medical IoT (mIoT) device that is revolutionizing healthcare is the medical implant device. These mIoT implant devices which control insulin pumps, cardioverter defibrillators and bone growth stimulators have redefined the way patient data is accessed, and healthcare is delivered. These implant devices are a double-edged sword. While they allow for the effective and efficient noninvasive treatment of patients, this external communication makes the medical implants vulnerable to cyberattacks synonymous with IoT devices. As a result, privacy and security vulnerabilities have surfaced as pronounced challenges for mIoT devices. This work summarizes and synthesizes the inherent vulnerabilities associated with mIoT devices and the implications regarding patient safety

The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation

Background: Persuasive technology is an umbrella term that encompasses software (eg, mobile apps) or hardware (eg, smartwatches) designed to influence users to perform preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the personalized care that persuasive technology can offer. However, there is no guidance for developing personalized persuasive technologies based on the psychological characteristics of users. Objective: This study examined the role that psychological characteristics play in interpreted mobile health (mHealth) screen perceived persuasiveness. In addition, this study aims to explore how users’ psychological characteristics drive the perceived persuasiveness of digital health technologies in an effort to assist developers and researchers of digital health technologies by creating more engaging solutions. Methods: An experiment was designed to evaluate how psychological characteristics (self-efficacy, health consciousness, health motivation, and the Big Five personality traits) affect the perceived persuasiveness of digital health technologies, using the persuasive system design framework. Participants (n=262) were recruited by Qualtrics International, Inc, using the web-based survey system of the XM Research Service. This experiment involved a survey-based design with a series of 25 mHealth app screens that featured the use of persuasive principles, with a focus on physical activity. Exploratory factor analysis and linear regression were used to evaluate the multifaceted needs of digital health users based on their psychological characteristics. Results: The results imply that an individual user’s psychological characteristics (self-efficacy, health consciousness, health motivation, and extraversion) affect interpreted mHealth screen perceived persuasiveness, and combinations of persuasive principles and psychological characteristics lead to greater perceived persuasiveness. The F test (ie, ANOVA) for model 1 was significant (F9,6540=191.806; PR2 of 0.208, indicating that the demographic variables explained 20.8% of the variance in perceived persuasiveness. Gender was a significant predictor, with women having higher perceived persuasiveness (P=.008) relative to men. Age was a significant predictor of perceived persuasiveness with individuals aged 40 to 59 years (PPF13,6536=341.035; PR2 of 0.403, indicating that the demographic variables self-efficacy, health consciousness, health motivation, and extraversion together explained 40.3% of the variance in perceived persuasiveness. Conclusions: This study evaluates the role that psychological characteristics play in interpreted mHealth screen perceived persuasiveness. Findings indicate that self-efficacy, health consciousness, health motivation, extraversion, gender, age, and education significantly influence the perceived persuasiveness of digital health technologies. Moreover, this study showed that varying combinations of psychological characteristics and demographic variables affected the perceived persuasiveness of the primary persuasive technology category

Can caregivers trust information technology in the care of their patients? A systematic review

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) requires that healthcare providers allow patients to engage in their healthcare by allowing access to their health records. Often patients need informal caregivers including family members or others to help them with their care. This paper explores whether trust is a key factor for informal caregivers’ decision to use health information technologies (HIT) including electronic health records (EHR), patient portals, mobile apps, or other devices to care for their patient. Six reviewers conducted a comprehensive search of four literature databases using terms that pertained to a caregiver and trust to investigate the role trust plays when caregivers use HIT. While trust is a key factor for the use of HIT, it the researchers only identified ten articles that met the research question thresholds. Four main topics of trust surfaced including perceived confidentiality, perceived security, technological malfunction, and trustworthiness of the information. Trust is a critical factor for informal caregivers when using HIT to assist in the care of their patient (child, loved one, parent, or acquaintance). Based on the findings, it is clear that more research on the use of HIT by caregivers is needed

Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records

<p>Abstract</p> <p>Background</p> <p>We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria.</p> <p>Methods</p> <p>We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content.</p> <p>Results</p> <p>All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified.</p> <p>Conclusion</p> <p>If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.</p

The impact of electronic records on patient safety : a qualitative study

BACKGROUND: Our aim was to explore NHS staff perceptions and experiences of the impact on patient safety of introducing a maternity system. METHODS: Qualitative semi-structured interviews were conducted with 19 members of NHS staff who represented a variety of staff groups (doctors, midwives, health care assistants), staff grades (consultant and midwife grades) and wards within a maternity unit. Participants represented a single maternity unit at a NHS teaching hospital in the North of England. Interviews were conducted during the first 12 months of the system being implemented and were analysed thematically. RESULTS: Participants perceived there to be an elevated risk to patient safety during the system's implementation. The perceived risks were attributed to a range of social and technical factors. For example, poor system design and human error which resulted in an increased potential for missing information and inputting error. CONCLUSIONS: The first 12 months of introducing the maternity system was perceived to and in some cases had already caused actual risk to patient safety. Trusts throughout the NHS are facing increasing pressure to become paperless and should be aware of the potential adverse impacts on patient safety that can occur when introducing electronic systems. Given the potential for increased risk identified, recommendations for further research and for NHS trusts introducing electronic systems are proposed

Mapping Proprioception across a 2D Horizontal Workspace

Relatively few studies have been reported that document how proprioception varies across the workspace of the human arm. Here we examined proprioceptive function across a horizontal planar workspace, using a new method that avoids active movement and interactions with other sensory modalities. We systematically mapped both proprioceptive acuity (sensitivity to hand position change) and bias (perceived location of the hand), across a horizontal-plane 2D workspace. Proprioception of both the left and right arms was tested at nine workspace locations and in 2 orthogonal directions (left-right and forwards-backwards). Subjects made repeated judgments about the position of their hand with respect to a remembered proprioceptive reference position, while grasping the handle of a robotic linkage that passively moved their hand to each judgement location. To rule out the possibility that the memory component of the proprioceptive testing procedure may have influenced our results, we repeated the procedure in a second experiment using a persistent visual reference position. Both methods resulted in qualitatively similar findings. Proprioception is not uniform across the workspace. Acuity was greater for limb configurations in which the hand was closer to the body, and was greater in a forward-backward direction than in a left-right direction. A robust difference in proprioceptive bias was observed across both experiments. At all workspace locations, the left hand was perceived to be to the left of its actual position, and the right hand was perceived to be to the right of its actual position. Finally, bias was smaller for hand positions closer to the body. The results of this study provide a systematic map of proprioceptive acuity and bias across the workspace of the limb that may be used to augment computational models of sensory-motor control, and to inform clinical assessment of sensory function in patients with sensory-motor deficits