Comput Inform Nurs

R01 NR015737/NR/NINR NIH HHS/United StatesU01 PS003715/PS/NCHHSTP CDC HHS/United States2017-05-01T00:00:00Z27153226PMC494452

Design methodologies for M-health innovations: a content analysis

Whilst researchers and professionals recognize that m-health offers great opportunities, most existing work has comprised individual project-based developments in specialised areas. Existing review papers generally utilise medical literature and categories: none investigates m-health from an IS design point of view. Identifying application areas, design issues and IS research techniques will demonstrate models, issues, approaches and gaps to inform future research. A comprehensive analysis of up to date literature from this viewpoint is valuable, both for theoretical progression and for guiding real-world innovative developments. Drawing from key IS and multidisciplinary journals we analyse recent (2010-2016) articles concerning m-health application developments and their associated design or development issues. We identify eight application categories, ten design issues (security, privacy, literacy, accessibility, acceptability, reliability, usability, confidentiality, integrity and knowledge sharing) and the stakeholders and development techniques involved. The analysis suggests m-health is an emerging field to which design science is particularly appropriate

The use of a user-centric smart mobile application prototype for supporting safety and security in a city: a design science method

Cities have always been the drivers of innovation, growth and change. Cities around the world are still rapidly expanding, especially on the African and Asian continents. Cape Town is one of those cities, where urbanisation rates are high, and crime is persisting at alarmingly high levels with crime rates being among the worst in the country and the world. Additionally, the city is home to 7 of 10 worst-performing police services in the country. Combining these factors, there is a need to look at ‘smart' ways of growth which includes facilitating a safe and secure city for citizens. Although Cape Town is pursuing smart initiatives, these have failed to place communities and individuals among the key stakeholders in the smart planning process. This research focuses on further researching smart city initiatives in Cape Town, placing citizens at the centre of the development process. As Cape Town's mobile phone penetration rate is high and access to Internet is rapidly expanding, this research aims to use crowdsourcing techniques for developing a smart mobile application prototype that is focused on enhancing community engagement and facilitating increased perceived feelings of safety and security for citizens. The study uses a Design Science Research method with Cape Town citizens as the main stakeholders, to propose an artifact based on their wishes, needs and current issues faced with regards to safety and security in the city. The proposed artifact focuses on enhancing community engagement, through a chat room and user-logged incident reports, as well as a customised safe route planning functionality where users can send emergency signals to comembers with the use of GPS live location tracking. The research shows participants are willing to adopt the use of the mobile application prototype, given there is substantial community buy-in, and the functionalities in the app are easy to use and quickly accessible. The study further identifies the need for better police follow up and involvement, as the city's police system could benefit from crowd-sourced crime-data in reducing the number of crimes in neighbourhoods to make citizens feel more safe and secure

Towards a mobile application to aid law enforcement in diagnosing and preventing mobile bully-victim behaviour in Eastern Free State High Schools of South Africa

Mobile bully-victim behaviour is one cyber aggression that is escalating worldwide. Bully-victims are people who bully others but are also victimised by peers. The behaviour of bully-victims therefore swings between that of pure bullies and pure victims, making it difficult to identify and prevent. Prevention measures require the involvement of a number of stakeholders, including communities. However, there has been a lack of whole-community participation in the fight against cyberbullying and the roles of stakeholders are often unclear. We expect the law enforcement in particular, the police, to play a key role in curbing all forms of bullying. This is a challenging task in South Africa as these law enforcement agents often lack the skills and appropriate legislation to address particularly cyber-related bullying. Literature shows that law enforcement agents need to advance their technological skills and also be equipped with digital interventions if they are to diagnose and prevent mobile bully-victim behaviour effectively. This is particularly important in South Africa, where the rate of crime remains one of the highest in the world. The aim of this study was to develop a mobile application that can aid law enforcement in diagnosing and preventing mobile bully-victim behaviour in high schools. As part of requirements to the application development, it identified the impediments to the law enforcement effectiveness in combating mobile bully-victim behaviour. Extensive literature review on the factors influencing mobile bullying and mobile bully-victim behaviour was conducted and an integrative framework for understanding this behaviour and its prevention was developed. In so doing, the dominant behavioural theories were consulted, including the social-ecological theory, social learning theory, social information processing theories, and the theory of planned behaviour, as well as the general strain theory, and the role theory. The conceptual framework developed in this study extended and tailored the “Cyberbullying Continuum of Harm”, enabling inclusive and moderated diagnosis of bullying categories and severity assessment. That is, instead of focusing on mobile bully-victims only, bullies, victims, and those uninvolved were also identified. Also the physical moderation of the identification process by the police helped to minimise dishonest reporting. This framework informed the design, development and evaluation of a mobile application for the law enforcement agents. The Design Science Research (DSR) methodology within pragmatic paradigm and literature guided the development of the mobile application named mobile bullyvictims response system (M-BRS) and its evaluation for utility. The M-BRS features included functions to enable anonymous reporting and confidential assessments of mobile bully-victims effects in school classrooms. Findings from this study confirmed the utility of the M-BRS to identify learners' involvement in mobile bully-victims behaviour through peer nomination and self-nomination. This study also showed that use of the M-BRS has enabled empowerment of marginalised learners, and mitigation of learners' fear to report, providing them with control over mobile bully-victim reporting. In addition, learners using the M-BRS were inclined to report perpetrators through a safe (anonymous and confidential) reporting platform. With the M-BRS, it was much easier to identify categories of bullies, i.e. mobile bully-victims, bullies, victims, and uninvolved. The practical contributions of this study were skills enhancements in reducing the mobile bully-victims behaviour. These included improvement of the police's technical skills to safely identify mobile bully-victims and their characterisation as propagators and retaliators that enabled targeted interventions. This was particularly helpful in response to courts' reluctance to prosecute teenagers for cyberbullying and the South African lack of legislation thereon so that the police are enabled to restoratively address this behaviour in schools. Also, the identification information was helpful to strengthen evidence for reported cases, which was remarkable because sometimes perpetrators cannot be found due to their concealed online identities. Furthermore, this study made possible the surveillance of mobile bully-victims through the M-BRS, which provided the police some control to reducing the mobile bully-victim behaviour. This study provided a practical way for implementing targeted prevention and interventions programmes using relevant resources towards a most efficient solution for mobile bully-victims problem. Since there are not many mobile-based interventions for mobile bully-victim behaviour, this study provided a way in which artefacts' development could be informed by theory, as a new, innovative and practical contribution in research. In so doing, this study contributed to technology applications' ability to modify desired behaviour

Development and Usability Evaluation of an mHealth Application for Symptom Self-Management in Underserved Persons Living with HIV

Effective symptom management is essential to decrease symptom severity and improve health-related quality of life for persons living with HIV (PLWH). A mobile health (mHealth) application (app) has the potential to be an effective delivery mode of an existing paper-based symptom management manual with self-management strategies for underserved PLWH. The quality of the mHealth app requires a thorough understanding of the needs of the intended end-users and ensuring the app’s usability. The purpose of this study was to translate paper-based health information into an mHealth app for symptom self-management in underserved PLWH, entitled mVIP (mobile Video Information Provider), and assess its usability. To achieve this goal, usability was evaluated rigorously throughout the development process of mVIP. Based on a stratified view of health information technology (IT) usability evaluation framework, usability evaluation was sequentially conducted with the following three levels: 1) user-task, 2) user-task-system, and 3) user-task-system-environment. At level 1 (user-task), we applied a user-centered design method to guide the information architecture of mVIP. Using a reverse in-person card sorting technique, symptoms and self-management strategies from a paper-based HIV/AIDS symptom management manual were ranked. The rank order of the 13 symptoms and 151 self-management strategies determined the order of appearance to end-users of the mVIP app, with higher-ranked symptoms and strategies appearing first. Based on the findings, we developed a prototype of mVIP as following: 1) once users log in, they are guided by an avatar through a series of 13 symptom questions ascertaining the nature and severity of their symptoms, and 2) the avatar recommends three self-management strategies for each symptom reported. At level 2 (user-task-system), we conducted a usability evaluation of the mVIP prototype in a laboratory setting through end-user usability testing and heuristic evaluation. In end-user usability testing, we used an eye-tracking and retrospective think-aloud method to examine task performance by 20 PLWH. For the heuristic evaluation, five usability experts in informatics assessed the user interface. In the two usability evaluations conducted in a laboratory setting, we found strong user acceptance of the mVIP prototype while identifying a number of usability issues with this prototype. Based on the recommendations from the end-users and heuristic evaluators, we iteratively refined the app’s content, functionality, and interface. We then inserted videos of the finalized symptom self-management strategies into the refined mVIP prototype. At level 3 (user-task-system-environment), the usability of the refined mVIP prototype was evaluated in a real-world setting. Through 10 in-depth interviews and four focus groups conducted at the conclusion of a three-month randomized controlled trial, we explored in-depth understandings of users’ experiences, perceptions, and satisfaction of mVIP use. Findings from the study showed that first, mVIP is useful for HIV-related symptom self-management and has the potential for being used as a communication tool with healthcare providers; and second, mVIP is easy to use to monitor symptom experience over time. At the same time, participants suggested mVIP be more sensitively tailored based on years from initial diagnosis of HIV, an individuals’ age, and conditions. The overall user satisfaction with the mVIP prototype was high, which reflects strong user acceptance of mVIP. Integral to the findings from the three-level usability evaluation, we assessed the quality of the mVIP prototype in use and found the prototype was highly accepted by PLWH with high user satisfaction. This study will add to the body of literature on translation of evidence-based health information into an mHealth app and its usability assessment, which highlights the importance of the use of mobile technology for PLWH, specifically racial and ethnic minorities and those from low-socioeconomic groups who have limited health literacy and low level of education

Ontology-based Semantic Harmonization of HIV-associated Common Data Elements for Integration of Diverse HIV Research Datasets

Analysis of integrated, diverse, Human Immunodeficiency Virus (HIV)-associated datasets can increase knowledge and guide the development of novel and effective interventions for disease prevention and treatment by increasing breadth of variables and statistical power, particularly for sub-group analyses. This topic has been identified as a National Institutes of Health research priority, but few efforts have been made to integrate data across HIV studies. Our aims were to: 1) Characterize the semantic heterogeneity (SH) in the HIV research domain; 2) Identify HIV-associated common data elements (CDEs) in empirically generated and knowledge-based resources; 3) Create a formal representation of HIV-associated CDEs in the form of an HIV-associated Entities in Research Ontology (HERO); 4) Assess the feasibility of using HERO to semantically harmonize HIV research data. Our approach was guided by information/knowledge theory and the DIKW (Data Information Knowledge Wisdom) hierarchical model. Our systematized review of the literature revealed that synergistic use of both ontologies and CDEs included integration, interoperability, data exchange, and data standardization. Moreover, methods and tools included use of experts for CDE identification, the Unified Medical Language System, natural language processing, Extensible Markup Language, Health Level 7, and ontology development tools (e.g., Protégé). Additionally, evaluation methods included expert assessment, quantification of mapping tasks between raters, assessment of interrater reliability, and comparison to established standards. We used these findings to inform our process for achieving the study aims. For Aim 1, we analyzed eight disparate HIV-associated data dictionaries and developed a String Metric-assisted Assessment of Semantic Heterogeneity (SMASH) method, which aided identification of 127 (13%) homogeneous data element (DE) pairs and 1,048 (87%) semantically heterogeneous DE pairs. Most heterogeneous pairs (97%) were semantically-equivalent/syntactically-different, allowing us to determine that SH in the HIV research domain was high. To achieve Aim 2, we used Clinicaltrials.gov, Google Search, and text mining in R to identify HIV-associated CDEs in HIV journal articles, HIV-associated datasets, AIDSinfo HIV/AIDS Glossary, AIDSinfo Drug Database, Logical Observation Identifiers Names and Codes (LOINC), Systematized Nomenclature of Medicine (SNOMED), and RxNORM (understood as prescription normalization). Two HIV experts then manually reviewed DEs from the journal articles and data dictionaries to confirm DE commonality and resolved semantic discrepancies through discussion. Ultimately, we identified 2,179 unique CDEs. Of all CDEs, data-driven approaches identified 2,055 (94%) (999 from the HIV/AIDS Glossary, 398 from the Drug Database, 91 from journal articles, and a total of 567 from LOINC, SNOMED, and RxNorm cumulatively). Expert-based approaches identified 124 (6%) unique CDEs from data dictionaries and confirmed the 91 CDEs from journal articles. In Aim 3, we used the Protégé suite of ontology development tools and the 2,179 CDEs to develop the HERO. We modeled the ontology using the semantic structure of the Medical Entities Dictionary, available hierarchical information from the CDE knowledge resources, and expert knowledge. The ontology fulfilled most relevant criteria from Cimino’s desiderata and OntoClean ontology engineering principles, and it successfully answered eight competency questions. Finally, for Aim 4, we assessed the feasibility of using HERO to semantically harmonize and integrate the data dictionaries from two diverse HIV-associated datasets. Two HIV experts involved in the development of HERO independently assessed each data dictionary. Of the 367 DEs in data dictionary 1 (D1), 181 (49.32%) were identified as CDEs and 186 (50.68%) were not CDEs, and of the 72 DEs in data dictionary 2 (D2), 37 (51.39%) were CDEs and 35 (48.61%) were not CDEs. The HIV experts then traversed HERO’s hierarchy to map CDEs from D1 and D2 to CDEs in HERO. Of the 181 CDEs in D1, 156 (86.19%) were found in HERO, and 25 (13.81%) were not. Similarly, of the 37 CDEs in D2 32 (86.48%) were found in HERO, and 5 (13.51%) were not. Interrater reliability for CDE identification as measured by Cohen’s Kappa was 0.900 for D1 and 0.892 for D2. Cohen’s Kappas for CDEs in D1 and D2 that were also identified in HERO were 0.885 and 0.688, respectively. Subsequently, to demonstrate the integration of the two HIV-associated datasets, a sample of semantically harmonized CDEs in both datasets was categorically selected (e.g. administrative, demographic, and behavioral), and D2 sample size increases were calculated for race (e.g., White, African American/Black, Asian/Pacific Islander, Native American/Indian, and Hispanic/Latino) and for “intravenous drug use” from the integrated datasets. The average increase of D2 CDEs for six selected CDEs was 1,928%. Despite the limitation of HERO developers also serving as evaluators, the contributions of the study to the fields of informatics and HIV research were substantial. Confirmatory contributions include: identification of effective CDE/ontology tools, and use of data-driven and expert-based methods. Novel contributions include: development of SMASH and HERO; and new contributions include documenting that SH is high in HIV-associated datasets, identifying 2,179 HIV-associated CDEs, creating two additional classifications of SH, and showing that using HERO for semantic harmonization of HIV-associated data dictionaries is feasible. Our future work will build upon this research by expanding the numbers and types of datasets, refining our methods and tools, and conducting an external evaluation