Research Onion for Smart IoT-Enabled Mobile Applications

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Abstract

Determining the appropriate approaches and procedures to gain sufficient results is a vital issue that is faced by the majority of researchers. Each type of research can have several methodologies that can be applied. Yet, one approach might lead to concluding more effective outcomes. Thus, designing the research and applying appropriate methods and techniques are the key aim of this experiment. Combining the research onion framework with an advanced Internet of Things- (IoT-) enabled mobile app solution within the real world is the foundation of this research. The framework has six main layers, starting with philosophy and ending with techniques and procedures. This research begins by providing a brief introduction in regard to the selected framework. Then, it provides a comprehensive explanation regarding each of the framework layers and justifying the chosen element within each layer combining with the advanced IoT-enabled mobile app for this research study. Later, it highlights the challenges that can be faced while using such a framework.

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Verbal reports as data.

K. Ericsson, Herbert Simon (1980)

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Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences

Kevin Anderson, Oksana Burford, Lynne M. Emmerton (2016)

Objective Consumers are living longer, creating more pressure on the health system and increasing their requirement for self-care of chronic conditions. Despite rapidly-increasing numbers of mobile health applications (‘apps’) for consumers’ self-care, there is a paucity of research into consumer engagement with electronic self-monitoring. This paper presents a qualitative exploration of how health consumers use apps for health monitoring, their perceived benefits from use of health apps, and suggestions for improvement of health apps. Materials and Methods ‘Health app’ was defined as any commercially-available health or fitness app with capacity for self-monitoring. English-speaking consumers aged 18 years and older using any health app for self-monitoring were recruited for interview from the metropolitan area of Perth, Australia. The semi-structured interview guide comprised questions based on the Technology Acceptance Model, Health Information Technology Acceptance Model, and the Mobile Application Rating Scale, and is the only study to do so. These models also facilitated deductive thematic analysis of interview transcripts. Implicit and explicit responses not aligned to these models were analyzed inductively. Results Twenty-two consumers (15 female, seven male) participated, 13 of whom were aged 26–35 years. Eighteen participants reported on apps used on iPhones. Apps were used to monitor diabetes, asthma, depression, celiac disease, blood pressure, chronic migraine, pain management, menstrual cycle irregularity, and fitness. Most were used approximately weekly for several minutes per session, and prior to meeting initial milestones, with significantly decreased usage thereafter. Deductive and inductive thematic analysis reduced the data to four dominant themes: engagement in use of the app; technical functionality of the app; ease of use and design features; and management of consumers’ data. Conclusions The semi-structured interviews provided insight into usage, benefits and challenges of health monitoring using apps. Understanding the range of consumer experiences and expectations can inform design of health apps to encourage persistence in self-monitoring.