A Review of Nutritional Tracking Mobile Applications for Diabetes Patient Use

User-Centered Design of a Diabetes Self-Management Tool for Underserved Populations

BACKGROUND

User-centered design (UCD) or user experience design (UXD) methods have gained recent popularity for the design of mobile health (mHealth) interventions. However, there is a gap in application of these methods for diabetes self-management. This study aims to document the UCD process for a self-management mobile application aimed for patients with diabetes in underserved communities.

METHODS

A UCD mixed-methods approach including interviews with patients and providers, a review of literature, and a technology landscape analysis were used to define the app functional information requirements that informed the user experience/user interface design process. Usability studies with the app designers and developers, intended users, and a focus group of nurse educators and dieticians were used to test and improve the design.

RESULTS

An mHealth app was developed with health-tracking features for stress, blood sugar, food, exercise, medications, weight, and blood pressure. We tackled a range of usability and user experience challenges, which encompassed addressing issues like low health literacy by employing a combination of user interface design principles, intuitive visualizations, customizable icons, seamless database integration, and automated data input features. Special attention was given to the design of educational content accounting for the intended users' cultural background and literacy levels.

CONCLUSIONS

User-centered design approach contributed to a better understanding of the intended users' needs, limitations, mental models, and expectations, facilitating the design of a comprehensive mobile app for patients with diabetes in underserved communities that includes essential features for self-management while providing a strong educational component, addressing an important gap in the literature.

Ethical implications of AI and robotics in healthcare: A review

Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical innovation, promising enhanced diagnostics, streamlined processes, and improved patient care. However, this technological revolution is accompanied by intricate ethical implications that demand meticulous consideration. This article navigates the complex ethical terrain surrounding AI and robotics in healthcare, delving into specific dimensions and providing strategies and best practices for ethical navigation. Privacy and data security are paramount concerns, necessitating robust encryption and anonymization techniques to safeguard patient data. Responsible data handling practices, including decentralized data sharing, are critical to preserve patient privacy. Algorithmic bias poses a significant challenge, demanding diverse datasets and ongoing monitoring to ensure fairness. Transparency and explainability in AI decision-making processes enhance trust and accountability. Clear responsibility frameworks are essential to address the accountability of manufacturers, healthcare institutions, and professionals. Ethical guidelines, regularly updated and accessible to all stakeholders, guide decision-making in this dynamic landscape. Moreover, the societal implications of AI and robotics extend to accessibility, equity, and societal trust. Strategies to bridge the digital divide and ensure equitable access must be prioritized. Global collaboration is pivotal in developing adaptable regulations and addressing legal challenges like liability and intellectual property. Ethics must remain at the forefront in the ever-evolving realm of healthcare technology. By embracing these strategies and best practices, healthcare systems and professionals can harness the potential of AI and robotics, ensuring responsible and ethical integration that benefits patients while upholding the highest ethical standards.

Dominican Adolescents' Preferences for Content, Design, and Functionality of a Mobile Application for Type 1 Diabetes Mellitus Self-management

OBJECTIVE

The purpose of this interdisciplinary study was to determine Dominican adolescents' preferences for the content, functionality (i.e. food's glycemic index list, and amount of insulin based on foods' carbohydrate count), and design of a culturally and linguistically relevant mobile application (app) for type 1 diabetes mellitus (T1DM) self-management. The app would facilitate T1DM self-management education and support by addressing providers' challenges in monitoring patients' disease progression and promoting patient adherence to recommended lifestyle changes. Findings inform an app development process that considers the linguistic and cultural values, norms, and structures of people with T1DM and their providers in the Dominican Republic.

METHODS

Phone interviews were conducted with 23 adolescents (14 to 18 years of age), using a semistructured questionnaire. The research team conducted the data analysis using NVivo through a deductive and inductive approach.

RESULTS

The findings suggest that, regardless of the context, adolescents with T1DM desire similar features and functionalities in a self-management app. Overall, participants preferred an app with a graphic format that has accessible information, a straightforward design, and instructional videos. Participants also desired that an app provide information and reminders about proper eating and insulin administration timing and be a vehicle to access a social network to foster mutual support and encouragement.

CONCLUSIONS

Our study highlights adolescents' perspectives on components for inclusion in an app for T1DM self-management. Participants' recommendations for the app's potential usability, contents, and design features will be used to guide the development of a new app to promote engagement and foster better health outcomes.

A content and quality analysis of free, popular mHealth apps supporting 'plant-based' diets

There has been an increased emphasis on plant-based foods and diets. Although mobile technology has the potential to be a convenient and innovative tool to help consumers adhere to dietary guidelines, little is known about the content and quality of free, popular mobile health (mHealth) plant-based diet apps. The objective of the study was to assess the content and quality of free, popular mHealth apps supporting plant-based diets for Canadians. Free mHealth apps with high user ratings, a high number of user ratings, available on both Apple App and GooglePlay stores, and primarily marketed to help users follow plant-based diet were included. Using pre-defined search terms, Apple App and GooglePlay App stores were searched on December 22, 2020; the top 100 returns for each search term were screened for eligibility. Included apps were downloaded and assessed for quality by three dietitians/nutrition research assistants using the Mobile App Rating Scale (MARS) and the App Quality Evaluation (AQEL) scale. Of the 998 apps screened, 16 apps (mean user ratings±SEM: 4.6±0.1) met the eligibility criteria, comprising 10 recipe managers and meal planners, 2 food scanners, 2 community builders, 1 restaurant identifier, and 1 sustainability assessor. All included apps targeted the general population and focused on changing behaviors using education (15 apps), skills training (9 apps), and/or goal setting (4 apps). Although MARS (scale: 1-5) revealed overall adequate app quality scores (3.8±0.1), domain-specific assessments revealed high functionality (4.0±0.1) and aesthetic (4.0±0.2), but low credibility scores (2.4±0.1). The AQEL (scale: 0-10) revealed overall low score in support of knowledge acquisition (4.5±0.4) and adequate scores in other nutrition-focused domains (6.1-7.6). Despite a variety of free plant-based apps available with different focuses to help Canadians follow plant-based diets, our findings suggest a need for increased credibility and additional resources to complement the low support of knowledge acquisition among currently available plant-based apps. This research received no specific grant from any funding agency.

Detection of transdermal biomarkers using gradient-based colorimetric array sensor

Accurate assessment of dietary macronutrients intake is critical for the effective management of multiple diseases, such as obesity, diabetes, cardiovascular disease, metabolic disease, and cancer. Conventional self-reporting method is burdensome, inaccurate, and often biased. Though blood analysis and breath analysis can provide evidence-based information, they are either invasive or subject to human errors. Here we reported a wearable transdermal volatile biomarkers detection system based on novel colorimetric sensing technology for dietary macronutrients intake assessment. This technique quantifies the emission rates of transdermal volatile biomarkers via a gradient-based colorimetric array sensor (GCAS). The optical system of the GCAS device tracks the localized color development associated with the chemical reaction between the volatile biomarkers and the porous sensing probes, and determines the biomarkers emission rates through image processing algorithms. The localized chemical reaction and the image-based signal processing also make the GCAS capable for multiplexed detection of multiple analytes simultaneously. The GCAS sensor has been applied for transdermal acetone detection on 5 subjects in a keto diet intervention. The study indicates that the transdermal acetone increases after the subjects consuming keto diets and it decreases to basal level after intaking carb-rich diets. The transdermal acetone response from the GCAS sensor correlates well with breath acetone concentration in the range between 0 and 40 ppm and the correlation factor (R²) is as high as 0.8877. This method provides a noninvasive, low-cost, and wearable tool for assessing dietary macronutrients intake outside of lab or hospital settings. It could be widely applied in disease management, weight control, and nutrition management.

Understanding Patient Needs Regarding Adverse Drug Reaction Reporting Smartphone Applications: A Qualitative Insight from Saudi Arabia

BACKGROUND

A pragmatic shift in the healthcare sector characterized by moving from curative to preventive approaches highlights the role of pharmacovigilance in patient safety. There have been few published studies on patient reporting of adverse drug reactions (ADRs) in Saudi Arabia. This qualitative study aims to explore the community opinions and the need for patient-friendly smartphone applications (SPAs) to enhance their participation in ADR reporting.

METHODS

Purposeful sampling was followed to recruit study participants, a semi-structured interview guide was used to conduct interviews, and the saturation was reached after the 13th interviewer; no new information was obtained after two subsequent interviews. All the interviews were audio-recorded, transcribed verbatim, and analyzed by means of a standard content analysis framework.

RESULTS

As per the WHO guidelines, eleven participants were aware of the term "ADR". All the participants denied receiving any prior education and attending events about ADRs and were unaware of the Saudi FDA-ADR reporting systems. The use of technologies such as SPAs has been widely accepted with a high level of concern for data confidentiality and privacy.

CONCLUSIONS

These findings point out the need to build patient-oriented educational programs to increase their awareness of ADR reporting and to prioritize the use of artificial intelligence (AI) to be integrated in the Saudi healthcare system to develop future SPAs for improving both patient safety and signal detection of ADRs.

Mobile Apps for the Care Management of Chronic Kidney and End-Stage Renal Diseases: Systematic Search in App Stores and Evaluation

Background

Numerous free and low-cost mobile apps for the care management of kidney disease have become available in recent years. Although these appear to be promising tools, they have not been evaluated comparatively based on standard mobile app metrics, and thus, limited evidence is available regarding their efficacy. This study systematically cataloged and assessed mobile apps designed to assist medication compliance and nutrition tracking that are useful to the chronic kidney disease (CKD) and the end-stage renal disease (ESRD) patients who are on dialysis.

Objective

The objective of this study was to comprehensively evaluate mobile apps used for medication compliance and nutrition tracking for possible use by CKD and ESRD patients.

Methods

A systematic review framework was applied to the search, screening, and assessment of apps identified and downloaded from the iOS and Android app stores. We selected apps using 13 relevant search terms, narrowed down based on a set of inclusion and exclusion criteria, and then used the Mobile App Rating Scale (MARS), a widely adopted app evaluation tool to assess the effectiveness of apps. The internal consistency and interrater reliability were tested using Cronbach alpha and interclass correlation coefficients (ICCs), respectively.

Results

The MARS total score had excellent internal consistency (Cronbach alpha=.90) and a moderate level of interrater reliability (2-way mixed ICC 0.65). Overall, 11 out of the 12 reviewed apps met the minimum acceptable score of 3.0 in MARS rating. The 3 apps with the highest combined scores were My Kidneys, My Health Handbook (MARS=4.68); My Food Coach (MARS=4.48); and National Kidney Foundation Malaysia (MARS=4.20). The study identified 2 general weaknesses in the existing apps: the apps fell short of accommodating advanced interactive features such as providing motivational feedback and promoting family member and caregiver participations in the app utilization.

Conclusions

The MARS rating system performed well in the app evaluation. The 3 highest ranked apps scored consistently high across the 5 dimensions specified in MARS. These apps were developed in collaboration with reputable organizations and field experts, demonstrating the importance of expert guidance in developing medical apps.

Requirements of an Application to Monitor Diet, Physical Activity and Glucose Values in Patients with Type 2 Diabetes: The Diameter

Adherence to a healthy diet and regular physical activity are two important factors in sufficient type 2 diabetes mellitus management. It is recognized that the traditional treatment of outpatients does not meet the requirements for sufficient lifestyle management. It is hypothesised that a personalized diabetes management mHealth application can help. Such an application ideally measures food intake, physical activity, glucose values, and medication use, and then integrates this to provide patients and healthcare professionals insight in these factors, as well as the effect of lifestyle on glucose values in daily life. The lifestyle data can be used to give tailored coaching to improve adherence to lifestyle recommendations and medication use. This study describes the requirements for such an application: the Diameter. An iterative mixed method design approach is used that consists of a cohort study, pilot studies, literature search, and expert meetings. The requirements are defined according to the Function and events, Interactions and usability, Content and structure and Style and aesthetics (FICS) framework. This resulted in 81 requirements for the dietary (n = 37), activity and sedentary (n = 15), glycaemic (n = 12), and general (n = 17) parts. Although many applications are currently available, many of these requirements are not implemented. This stresses the need for the Diameter as a new personalized diabetes application.

Smartphone Apps Meet Evidence-Based Medicine: The Future of Medicine May (Or May Not) Be in Your Smartphone

"The future of medicine is in your smartphone," proclaimed an eminent medical researcher in a 2015 Wall Street Journal essay. In a sense, that future has already arrived, judging from the proliferation of apps and medical devices now connected to smartphones. One 2015 industry study identified more than 165,000 health-related smartphone apps available from the Google Play Store and Apple iTunes. But to what extent does this technology lead to improved patient outcomes? That question is one for evidence-based medicine, to be answered by clinical trials and systematic reviews by medical experts.

A conjoint analysis to consumer choice in Brazil: Defining device attributes for recognizing customized foods characteristics

the availability of information about food products may be an essential factor in the consumer's value perception in their purchasing decision. As the food product becomes personalized, the customization of this information becomes complex due to the possible combinations of product components. The use of smart technology in devices is one way to provide customers with customized food information. In the following research five attributes were identified in the composition of these devices: (A) portability; (B) precision; (C) diet customization; (D) food quality analysis; and (E) price. This study aims to identify the appropriate combination of possible functionalities or attributes that must be present in a device in order to detect the food composition of customized foods and their relation to market characteristics. One experiment used fractional factorial project to present the attributes in the form of scenarios following the Choice-Based Conjoint Analysis (CBCA) method. The data collection was done using survey methodology, through online questionnaire, with some 303 Brazilian respondents. So, the Logistic Regression was applied to data analysis. The moderating variables-gender, age, gluten restriction, lactose restriction and other restrictions-were also added to verify potential interactions with the primary attributes. From the results obtained, it was possible to observe higher significance for the primary attributes of diet personalization and quality food analyzes function. Our study contributes to the literature by enhancing the understanding about what the attributes should be in a technological device that has the purpose of recognizing food characteristics and is capable of generating information about customized food products. Furthermore, this device can enabler the production of mass customized food with the nutritional labels for each possible combination.

Smartphone apps and the nutrition care process: Current perspectives and future considerations

OBJECTIVE

To provide dietitians with practical guidance on incorporating smartphone applications (apps) in the nutrition care process (NCP) to optimize patient education and counseling.

METHODS

The current evidence-base for mobile health (mHealth) apps was searched using PubMed and Google Scholar. Where and how apps could be implemented by dietitians across the four steps of the NCP is discussed.

RESULTS

With functionality to automatically convert patient dietary records into nutrient components, nutrition assessment can be streamlined using nutrition apps, allowing more time for dietitians to deliver education and nutrition counseling. Dietitians could prescribe apps to provide patients with education on nutrition skills and in counseling for better adherence to behavior change. Improved patient-provider communication is also made possible through the opportunity for real-time monitoring and evaluation of patient progress via apps. A practical framework termed the 'Mobile Nutrition Care Process Grid' provides dietitians with best-practice guidance on how to use apps.

CONCLUSIONS

Including apps into dietetic practice could enhance the efficiency and quality of nutrition care and counseling delivered by dietitians.

PRACTICE IMPLICATIONS

Apps should be considered an adjunct to enable dietetic counseling and care, rather than to replace the expertise, social support and accountability provided by dietitians.

Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications

OBJECTIVE

To assess the accuracy of nutrient intake calculations from leading nutrition tracking applications (apps).

DESIGN

Nutrient intake estimates from thirty 24 h dietary recalls collected using Nutrition Data System for Research (NDSR) were compared with intake calculations from these recalls entered by the researcher into five free nutrition tracking apps. Apps were selected from the Apple App Store based on consumer popularity from the list of free 'Health and Fitness' apps classified as a nutrition tracking apps.

SUBJECTS

Dietary recall data collected from thirty lower-income adults.

RESULTS

Correlations between nutrient intake calculations from NDSR and the nutrition tracking apps ranged from 0·73 to 0·96 for energy and macronutrients. Correlations for the other nutrients examined (Na, total sugars, fibre, cholesterol, saturated fat) ranged from 0·57 to 0·93. For each app, one or more mean nutrient intake calculations were significantly lower than those from NDSR. These differences included total protein (P=0·03), total fat (P=0·005), Na (P=0·02) and cholesterol (P=0·005) for MyFitnessPal; dietary fibre (P=0·04) for Fitbit; total protein (P=0·0004), total fat (P=0·008), Na (P=0·002), sugars (P=0·007), cholesterol (P=0·0006) and saturated fat (P=0·005) for Lose It!; Na (P=0·03) and dietary fibre (P=0·005) for MyPlate; and total fat (P=0·03) for Lifesum.

CONCLUSIONS

Findings suggest that nutrient calculations from leading nutrition tracking apps tend to be lower than those from NDSR, a dietary analysis software developed for research purposes. Further research is needed to evaluate the validity of the apps when foods consumed are entered by consumers.