"How Is My Child's Asthma?" Digital Phenotype and Actionable Insights for Pediatric Asthma

User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review

BACKGROUND

There are numerous mobile health (mHealth) interventions for treatment adherence and self-management; yet, little is known about user engagement or interaction with these technologies.

OBJECTIVE

This systematic review aimed to answer the following questions: (1) How is user engagement defined and measured in studies of mHealth interventions to promote adherence to prescribed medical or health regimens or self-management among people living with a health condition? (2) To what degree are patients engaging with these mHealth interventions? (3) What is the association between user engagement with mHealth interventions and adherence or self-management outcomes? (4) How often is user engagement a research end point?

METHODS

Scientific database (Ovid MEDLINE, Embase, Web of Science, PsycINFO, and CINAHL) search results (2016-2021) were screened for inclusion and exclusion criteria. Data were extracted in a standardized electronic form. No risk-of-bias assessment was conducted because this review aimed to characterize user engagement measurement rather than certainty in primary study results. The results were synthesized descriptively and thematically.

RESULTS

A total of 292 studies were included for data extraction. The median number of participants per study was 77 (IQR 34-164). Most of the mHealth interventions were evaluated in nonrandomized studies (157/292, 53.8%), involved people with diabetes (51/292, 17.5%), targeted medication adherence (98/292, 33.6%), and comprised apps (220/292, 75.3%). The principal findings were as follows: (1) >60 unique terms were used to define user engagement; "use" (102/292, 34.9%) and "engagement" (94/292, 32.2%) were the most common; (2) a total of 11 distinct user engagement measurement approaches were identified; the use of objective user log-in data from an app or web portal (160/292, 54.8%) was the most common; (3) although engagement was inconsistently evaluated, most of the studies (99/195, 50.8%) reported >1 level of engagement due to the use of multiple measurement methods or analyses, decreased engagement across time (76/99, 77%), and results and conclusions suggesting that higher engagement was associated with positive adherence or self-management (60/103, 58.3%); and (4) user engagement was a research end point in only 19.2% (56/292) of the studies.

CONCLUSIONS

The results revealed major limitations in the literature reviewed, including significant variability in how user engagement is defined, a tendency to rely on user log-in data over other measurements, and critical gaps in how user engagement is evaluated (infrequently evaluated over time or in relation to adherence or self-management outcomes and rarely considered a research end point). Recommendations are outlined in response to our findings with the goal of improving research rigor in this area.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022289693; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022289693.

iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control

Purpose

The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention.

Patients and Methods

As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged ≥18 years) with self-reported asthma for a risk-benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25-65 years) tested 13 devices to measure these parameters and assessed their usability attributes.

Results

Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control.

Conclusion

These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.

Smartphone and Wearable Device-Based Digital Phenotyping to Understand Substance use and its Syndemics

Digital phenotyping is a process that allows researchers to leverage smartphone and wearable data to explore how technology use relates to behavioral health outcomes. In this Research Concepts article, we provide background on prior research that has employed digital phenotyping; the fundamentals of how digital phenotyping works, using examples from participant data; the application of digital phenotyping in the context of substance use and its syndemics; and the ethical, legal and social implications of digital phenotyping. We discuss applications for digital phenotyping in medical toxicology, as well as potential uses for digital phenotyping in future research. We also highlight the importance of obtaining ground truth annotation in order to identify and establish digital phenotypes of key behaviors of interest. Finally, there are many potential roles for medical toxicologists to leverage digital phenotyping both in research and in the future as a clinical tool to better understand the contextual features associated with drug poisoning and overdose. This article demonstrates how medical toxicologists and researchers can progress through phases of a research trajectory using digital phenotyping to better understand behavior and its association with smartphone usage.

'It would help people to help me': Acceptability of digital phenotyping among young people with visual impairment and their families

Objectives

To explore the acceptability of an eHealth App for vision-related monitoring and symptom reporting among young people with a visual impairment and their parents.

Methods

Qualitative investigation using virtual semi-structured focus groups (via Zoom software) of seven young participants with a genetic eye disorder including inherited retinal disease and structural eye abnormalities (e.g. microphthalmia), and 7 parents; all recruited from ocular genetic clinics at Moorfields Eye Hospital. Audio transcripts were analysed using thematic analysis.

Results

Data were coded into six key themes: (1) increased involvement in care, (2) opportunity for less hospital-centric care, (3) better representation of visual impairment in a real-world setting, (4) trust in a reputable service provider, (5) harnessing data for health purposes and (6) intended purpose of the app. Both young people and their families were accepting of an eHealth app and felt they would be empowered by greater involvement in their care plan, if privacy of the data was retained, and information was managed correctly. While parents endorsed the opportunity for mental health tracking, young people were hesitant towards its inclusion.

Conclusion

In summary, there was overall acceptability of an eHealth app among young people with a visual impairment and their parents. These findings will help to maximise the effective integration of digital phenotyping when monitoring and supporting young people experiencing sight loss.

Assessing the technical feasibility of a flexible, integrated Internet-of-things connected for asthma (C4A) system to support self-management: a mixed method study exploring patients and healthcare professionals perspectives

Background

A connected system with smart devices could transform patient care and empower patients control of their asthma.

Objective

To explore how a connected-for-asthma system (C4A) with smart devices from multiple companies (smart-inhaler; smart-watch; smart-peak-flow meter, manual digital thermometer during the Coronavirus disease (COVID)-pandemic) could support asthma self-management.

Methods

In a proof-of-concept mixed-methods study (Winter 2021/2022), we collected data from devices linked via the C4A app enabling patients to self-monitor and share a monitoring summary (in PDF format) with their clinician. Ten patients (range of age/gender, asthma experience, Apple/Android user) via social media, used C4A for a month. We conducted pre/post-interviews with patients, and a single post-interview with an asthma nurse and 3 general practitioners. Thematic analysis, informed by the Unified Theory of Acceptance and Use of Technology was triangulated with descriptive analysis of usage data.

Results

The system was perceived as "easy" to use. During the study, 7517 data points were collected from 10 patients; monitoring reduced over the month. Patients used devices if they trusted their "accuracy," and adopted the system to monitor new medication or assess troublesome symptoms. One patient lost contact (because of COVID), 8 wanted to keep using C4A to manage their asthma, though were selective about the most useful devices. Clinicians wanted the report to provide an asthma score/status and reliever usage.

Conclusion

A connected system could enable flexible digital care by linking data from several devices to support self-management. To promote adoption/adherence, setup has to be simple, and patients need to trust that the devices accurately reflect their condition.

Computational phenotyping of obstructive airway diseases: protocol for a systematic review

BACKGROUND

Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim to perform a systematic review of studies using computational approaches to phenotype obstructive airway diseases in children and adults.

METHODS AND ANALYSIS

We will search PubMed, Embase, Scopus, Web of Science, and Google Scholar for papers published between 2010 and 2020. Conferences proceedings, reference list of included papers, and experts will form additional sources of literature. We will include observational epidemiological studies that used a computational approach to derive phenotypes of chronic airway diseases, whether in a general population or in a clinical setting. Two reviewers will independently screen the retrieved studies for eligibility, extract relevant data, and perform quality appraisal of included studies. A third reviewer will arbitrate any disagreements in these processes. Quality appraisal of the studies will be undertaken using the Effective Public Health Practice Project quality assessment tool. We will use summary tables to describe the included studies. We will narratively synthesize the generated evidence, providing critical assessment of the populations, variables, and computational approaches used in deriving the phenotypes across studies CONCLUSION: As progress continues to be made in the area of computational phenotyping of chronic obstructive airway diseases, this systematic review, the first on this topic, will provide the state of the art on the field and highlight important perspectives for future works.

ETHICS AND DISSEMINATION

No ethical approval is needed for this work is based only on the published literature and does not involve collection of any primary or human data.

REGISTRATION AND REPORTING

SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020164898.

Utility of Fitbit devices among children and adolescents with chronic health conditions: a scoping review

Background

While Fitbit® devices were initially intended for leisurely, consumer use, there has been recent interest among scientific and medical communities in the prospective use of Fitbit devices for clinical and research purposes. Those who have chronic health conditions are often required to spend considerable amounts of money and time undergoing physiological tests and activity monitoring to support, stabilize, and manage their health. This disease burden is only amplified in pediatric populations. Devices that are used to collect these data can be invasive, uncomfortable, and disconcerting. Using the Fitbit tracker to acquire such biometric data could ease this burden. Our scoping review seeks to summarize the research that has been conducted on the utilization of Fitbit devices in studies of children and adolescents with chronic health conditions and the feasibility, accuracy, and potential benefits of doing so.

Methods

Searches were conducted on PubMed for articles relating pediatric health to Fitbit device usage (using a Boolean search strategy). The eligibility criteria included trials being clinical and/or randomized controlled and articles being in English. Once articles were obtained, they underwent screening and exclusion processes and were charted for their titles, authors, objectives, results, and respective chronic illnesses. In the subsequent full-text review, further charting was conducted, collecting study designs, Fitbit parameters, feasibility, accuracy, and related health and clinical outcomes.

Results

Fitbit trackers were unanimously demonstrated to be feasible devices in this population for physical activity monitoring and were determined to be potentially beneficial in measuring and improving overall wellbeing and physical health in children with chronic illness. Nevertheless, sufficient evidence was not found in support of Fitbit accuracy. Additional biases were identified against the population of children with chronic health conditions that may further enable inaccurate data.

Conclusions

While Fitbit devices may be beneficial for those interested in improving physical health, discretion is advised for those seeking to collect accurate and/or medically necessitated data. Given the existing literature evaluated, medical-grade technologies are preferred in instances of the latter, as Fitbit devices have not been found to provide reliably accurate data.

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

BACKGROUND

This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively.

AIMS

Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology.

RESULTS

Overall, 118 studies were assessed as eligible. Considering the terms employed, "EMA", "ESM", and "DP" were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps' information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales.

CONCLUSIONS

Findings suggest links between a person's digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person's broader contextual and developmental circumstances in relation to their digital data/records.

Development and Feasibility of a Mobile Asthma App for Children and Their Caregivers: Mixed Methods Study

Background

Mobile health apps can support the self-management of pediatric asthma. Previous studies on mobile apps for children aged >7 years with asthma are limited, and most reports on asthma apps do not consider interactions between the children and their caregivers. Therefore, we developed an asthma app for children aged 0-12 years and their caregivers based on the results of our previous study regarding user needs.

Objective

The aim of this study was to evaluate the feasibility of a developed mobile app for children with asthma and their caregivers and to modify and complete the app according to the feasibility results.

Methods

We recruited children diagnosed with persistent asthma by an allergy specialist at 2 children’s hospitals, 1 university hospital, 2 general hospitals, and 1 pediatric clinic. Thereafter, the app usage was assessed, and questionnaires were administered. This study used convergent mixed methods, including providing user feedback about the pediatric asthma app, completing questionnaire surveys regarding preferences, and obtaining quantitative data about app usage. Quantitative data were analyzed based on the ratings provided for the app features used by the participants, and the usage of the app features was analyzed using descriptive statistics. Qualitative data were analyzed via a descriptive qualitative research analysis and were used to identify codes from the content-characteristic words.

Results

In total, 30 pairs of children aged 2-12 years and their caregivers responded to the 3-month survey, and 20 pairs of children aged 4-12 years and their caregivers responded to the 6-month survey. In the 3- and 6-month surveys, “record” was the most commonly used feature by both caregivers and children. The average access logs per month among the 20 pairs ranged from 50 to 79 in the 6-month survey. The number of access logs decreased over time. In the qualitative results, app utilization difficulties were identified for 6 categories: record, preparing, alert settings, change settings, mobile phone owner, and display and motivation. Regarding app feasibility, 60% (12/20) of the caregivers strongly agreed or agreed for all evaluation items, while 63% (7/11) of the children strongly agreed or agreed for 6 items, excluding satisfaction. In the qualitative results, feasibility evaluation of the app was classified into 3 categories: high feasibility of the app, improvement points for the app, and personal factors preventing app utilization. Based on the results of the feasibility analysis, the final version of the app was modified and completed.

Conclusions

The app feasibility among children with asthma and their caregivers was generally good. Children aged 7-12 years used elements such as record, quiz, and manga. This app can support the continuous self-management of pediatric asthma. However, efforts must be taken to maintain and improve the app quality.

Trial Registration

UMIN Clinical Trials Registry UMIN000039058; https://tinyurl.com/3na9zyf8

Digital phenotyping in young breast cancer patients treated with neoadjuvant chemotherapy (the NeoFit Trial): protocol for a national, multicenter single-arm trial

BACKGROUND

Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC.

METHODS

NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link.

DISCUSSION

In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT05011721 . Registration date: 18/08/2021.

Exposome mapping in chronic respiratory diseases: the added value of digital technology

PURPOSE OF REVIEW

The development and progression of chronic respiratory diseases are impacted by a complex interplay between genetic, microbial, and environmental factors. Here we specifically summarize the effects of environmental exposure on asthma, allergic rhinitis, and chronic rhinosinusitis. We furthermore discuss how digital health technology may aid in the assessment of the environmental exposure of patients and how it may be of added value for them.

RECENT FINDINGS

It is well established that one gets allergic symptoms if sensitized and exposed to the same allergen. Viruses, bacteria, pollutants, irritants, and lifestyle-related factors modify the risk of getting sensitized and develop symptoms or may induce symptoms themselves. Understanding these processes and how the various factors interact with each other and the human body require big data and advanced statistics. Mobile health technology enables integration of multiple sources of data of the patients' exposome and link these to patient outcomes. Such technologies may contribute to the increased understanding of the development of chronic respiratory disease.

SUMMARY

Implementation of digital technologies in clinical practice may in future guide the development of preventive strategies to tackle chronic respiratory diseases and eventually improve outcomes of the patient.

HOPES: An Integrative Digital Phenotyping Platform for Data Collection, Monitoring, and Machine Learning

The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual's health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a comprehensive digital phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for security, privacy, ease of use, and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present, and analyze data. This includes a set of dashboards customized to the needs of research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.

Digital Health Technology in Asthma: A Comprehensive Scoping Review

BACKGROUND

A variety of digital intervention approaches have been investigated for asthma therapy during the past decade, with different levels of interactivity and personalization and a range of impacts on different outcome measurements.

OBJECTIVE

To assess the effectiveness of digital interventions in asthma with regard to acceptability and outcomes and evaluate the potential of digital initiatives for monitoring or treating patients with asthma.

METHODS

We evaluated digital interventions using a scoping review methodology through a literature search and review. Of 871 articles identified, 121 were evaluated to explore intervention characteristics, the perception and acceptability of digital interventions to patients and physicians, and effects on asthma outcomes. Interventions were categorized by their level of interactivity with the patient.

RESULTS

Interventions featuring non-individualized content sent to patients appeared capable of promoting improved adherence to inhaled corticosteroids, but with no identified improvement in asthma burden; and data-gathering interventions appeared to have little effect on adherence or asthma burden. Evidence of improvement in both adherence and patients' impairment due to asthma were seen only with interactive interventions involving two-way responsive patient communication. Digital interventions were generally positively perceived by patients and physicians. Implementation was considered feasible, with certain preferences for design and features important to drive use.

CONCLUSIONS

Digital health interventions show substantial promise for asthma disease monitoring and personalization of treatment. To be successful, future interventions will need to include both inhaler device and software elements, combining accurate measurement of clinical parameters with careful consideration of ease of use, personalization, and patient engagement aspects.

Digital health interventions in children with asthma

Although healthcare providers are actively involved in offering education, information and interventions for asthmatic patients, medication and therapeutic adherence remain low in the paediatric population, with estimates suggesting that adherence rates hover below 50%. A range of available digital health interventions has been explored in paediatric asthma with promising but variable results, limiting their widespread adoption in clinical practice. They include emerging technologies that yield the advantage of tracking asthma symptoms and medications, setting drug reminders, improving inhaler technique and delivering asthma education, such as serious games (video games designed for medical‐ or health‐related purposes), electronic monitoring devices, speech recognition calls, text messaging, mobile apps and interactive websites. Some of the proposed digital interventions have used multiple components, including educational and behavioural strategies and interactions with medical professionals. Overall, the implementation of such interventions may offer the opportunity to improve adherence and asthma control. In a state of emergency as the COVID‐19 pandemic, telemedicine can also play a central role in supporting physicians in managing children with asthma. This review evaluates the published literature examining digital health interventions for paediatric asthma and explores the most relevant issues affecting their implementation in practice and the associated evidence gaps, research limitations and future research perspectives.

Developing and evaluating ASTHMAXcel adventures: A novel gamified mobile application for pediatric patients with asthma

BACKGROUND

The ASTHMAXcel mobile application has been linked to favorable outcomes among adult patients with asthma.

OBJECTIVE

To assess the impact of ASTHMAXcel Adventures, a gamified, guideline-based, pediatric version on asthma control, knowledge, health care utilization, and patient satisfaction.

METHODS

Pediatric patients with asthma received the ASTHMAXcel Adventures mobile intervention on-site only at baseline (visit 1), 4 months (visit 2), and 6 months (visit 3). The asthma control test, asthma illness representation scale-self-administered, pediatric asthma impact survey, and Client Satisfaction Questionnaire-8 were used to assess asthma control, knowledge, and patient satisfaction. Patients reported the number of asthma-related emergency department (ED) visits, hospitalizations, and oral prednisone use.

RESULTS

A total of 39 patients completed the study. The proportion of controlled asthma increased from visit 1 to visits 2 and 3 (30.8% vs 53.9%, P = .04; 30.8% vs 59.0%, P = .02), and largely seen in boys. The mean asthma illness representation scale-self-administered scores increased from baseline pre- to postintervention, with sustained improvements at visits 2 and 3 (3.55 vs 3.76, P < .001; 3.55 vs 3.80, P = .001; 3.55 vs 3.99, P < .001). The pediatric asthma impact survey scores improved from baseline to visits 2 and 3 (43.33 vs 34.08, P < .001; 43.33 vs 31.74, P < .001). ED visits and prednisone use significantly decreased from baseline to visits 2 and 3 (ED: 0.46 vs 0.13, P = .03; 0.46 vs 0.02, P = .02; prednisone use, 0.49 vs 0.13, P = .02; 0.49 vs 0.03, P = .003. Satisfaction was high with mean client satisfaction questionnaire score of approximately 30 (out of 32) at all visits.

CONCLUSION

ASTHMAXcel Adventures improved asthma control, knowledge, and quality of life, and reduced ED visits and prednisone use with high satisfaction scores.

Transforming Health Care through Digital Revolutions

The Internet, which has spanned several networks in a broad range of domains, is having a significant impact on every aspect of our lives. The next generation of networks will utilize a wide variety of resources with significant sensing capabilities. Such networks will extend beyond physically linked computers to include multimodal-information from biological, cognitive, semantic, and social networks. This paradigm shift will involve symbiotic networks of smart medical devices, and smart phones or mobile personal computing and communication devices. These devices—and the network—will be constantly sensing, monitoring, and interpreting the environment; this is sometimes referred to as the Internet of Things (IoT). We are also witnessing considerable interest in the “Omics” paradigm, which can be viewed as the study of a domain in a massive scale, at different levels of abstraction, in an integrative manner. The IoT revolution, combined with the Omics revolution (genomics and socio-omics or social networks) and artificial intelligence resurgence, will have significant implications for the way health care is delivered in the United States. After discussing a vision for health care in the future, we introduce the P9 health care concept, followed by a discussion of a framework for smart health care. Then, we present a case study and research directions, followed by examples of ongoing work at the National Institute of Standards and Technology (NIST).

Beneficial Features of a mHealth Asthma App for Children and Caregivers: Qualitative Study

Background

mHealth and uHealth apps are available for children with asthma and their caregivers. However, previous studies on mHealth apps for children older than 7 years old with asthma are limited, and most studies on asthma apps do not consider interactions involving communication between children and caregivers. Therefore, a prototype mHealth child asthma app was developed for children and their caregivers, with features of tailored feedback messages in continuing self-management and interactions between children and caregivers.

Objective

The aim of this study was to identify the beneficial features of a prototype mHealth app developed for children with asthma and their caregivers.

Methods

Children diagnosed with persistent asthma by allergy specialists at the National Center for Child Health and Development were recruited. The features of a prototype mHealth app for children with asthma and their caregivers were investigated using semistructured interviews after they tried the app. Data were analyzed using thematic analysis. Content-characteristic words were named and grouped together as categories to explore themes.

Results

We recruited 27 children with asthma aged 2 to 12 years and 26 their caregivers. Findings on the good aspects of the app for children older than 7 years old and caregivers suggested 4 themes (confirmation of asthma knowledge, child-caregiver interaction, design of the app, and child’s interest), and 6 categories were identified. Findings on the good aspects of app for children 7 to 12 years old and caregivers suggested 5 themes (new knowledge, manga as a Japanese-style comic, child’s interest, trigger of self-management, and design and operability), and 11 categories were identified. Findings on the beneficial features of app suggested 6 themes (asthma knowledge, elements for continuous, universal design, notification, monitoring, and functions), and 12 categories were identified.

Conclusions

Children with asthma and their caregivers perceived that the good aspects of the app were learning asthma knowledge with fun, including manga; interaction between child and caregiver; and easy-to-read design, such as colors. They wanted not only the asthma knowledge but also the universal design and enhanced elements, monitoring, and notification functions of the app.

Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis

Background

Sustained self-monitoring and self-management behaviors are crucial to maintain optimal health for individuals with type 2 diabetes mellitus (T2DM). As smartphones and mobile health (mHealth) devices become widely available, self-monitoring using mHealth devices is an appealing strategy in support of successful self-management of T2DM. However, research indicates that engagement with mHealth devices decreases over time. Thus, it is important to understand engagement trajectories to provide varying levels of support that can improve self-monitoring and self-management behaviors.

Objective

The aims of this study were to develop (1) digital phenotypes of the self-monitoring behaviors of patients with T2DM based on their engagement trajectory of using multiple mHealth devices, and (2) assess the association of individual digital phenotypes of self-monitoring behaviors with baseline demographic and clinical characteristics.

Methods

This longitudinal observational feasibility study included 60 participants with T2DM who were instructed to monitor their weight, blood glucose, and physical activity using a wireless weight scale, phone-tethered glucometer, and accelerometer, respectively, over 6 months. We used latent class growth analysis (LCGA) with multitrajectory modeling to associate the digital phenotypes of participants’ self-monitoring behaviors based on their engagement trajectories with multiple mHealth devices. Associations between individual characteristics and digital phenotypes on participants’ self-monitoring behavior were assessed by analysis of variance or the Chi square test.

Results

The engagement with accelerometers to monitor daily physical activities was consistently high for all participants over time. Three distinct digital phenotypes were identified based on participants’ engagement with the wireless weight scale and glucometer: (1) low and waning engagement group (24/60, 40%), (2) medium engagement group (20/60, 33%), and (3) consistently high engagement group (16/60, 27%). Participants that were younger, female, nonwhite, had a low income, and with a higher baseline hemoglobin A_1c level were more likely to be in the low and waning engagement group.

Conclusions

We demonstrated how to digitally phenotype individuals’ self-monitoring behavior based on their engagement trajectory with multiple mHealth devices. Distinct self-monitoring behavior groups were identified. Individual demographic and clinical characteristics were associated with different self-monitoring behavior groups. Future research should identify methods to provide tailored support for people with T2DM to help them better monitor and manage their condition.

International Registered Report Identifier (IRRID)

RR2-10.2196/13517

Wearable Technology and How This Can Be Implemented into Clinical Practice

PURPOSE OF REVIEW

Our day-to-day life is saturated with health data that was previously out of reach. Over the last decade, new devices and fitness technology companies are attempting to tap into this data, uncovering a treasure trove of useful information that, when applied correctly, has the potential to revolutionize the way we approach healthcare and chronic conditions like asthma, especially in the wake of the COVID-19 pandemic.

RECENT FINDINGS

By harnessing exciting developments in personalization, digitization, wellness, and patient engagement, care providers can improve health outcomes for our patients in a way we have never been able to do in the past. While new technologies to capture individual health metrics are everywhere, how can we use this information to make a real difference in our patients' lives? Navigating the complicated landscape of personal wearable devices, asthma inhaler sensors, and exercise apps can be daunting to even the most tech savvy physician. This manuscript will give you the tools necessary to make lasting changes in your patients' lives by exposing them to a world of usable, affordable, and relatable health technology that resonates with their personal fitness and wellness goals. These tools will be even more important post-COVID-19, as the landscape of clinical outpatient care changes from mainly in-person visits to a greater reliance on telemedicine and remote monitoring.

The potential of digital phenotyping to advance the contributions of mobile health to self-management science

Digital phenotyping consists of moment-by-moment quantification of behavioral data from individual people, typically collected passively from smartphones and other sensors. Within the evolving context of precision health, digital phenotyping can advance the use of mobile health -based self-management tools and interventions by enabling more accurate prediction for prevention and treatment, facilitating supportive strategies, and informing the development of features to motivate self-management behaviors within real-world conditions. This represents an advancement in self-management science: with digital phenotyping, nurse scientists have opportunities to tailor interventions with increased precision. In this paper, we discuss the emergence of digital phenotyping, the historical background of ecological momentary assessment, and the current state of the science of digital phenotyping, with implications for research design, computational requirements, and ethical considerations in self-management science, as well as limitations.

Determination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study

BACKGROUND

Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients' environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management.

OBJECTIVE

In this study, pediatric patients were continuously monitored using low-cost sensors to collect asthma-relevant information. The objective of this study was to assess whether kHealth kit, which contains low-cost sensors, can identify personalized triggers and provide actionable insights to clinicians for the development of a tailored asthma care plan.

METHODS

The kHealth asthma kit was developed to continuously track the symptoms of asthma in pediatric patients and monitor the patients' environment and adherence to their care plan for either 1 or 3 months. The kit consists of an Android app-based questionnaire to collect information on asthma symptoms and medication intake, Fitbit to track sleep and activity, the Peak Flow meter to monitor lung functions, and Foobot to monitor indoor air quality. The data on the patient's outdoor environment were collected using third-party Web services based on the patient's zip code. To date, 107 patients consented to participate in the study and were recruited from the Dayton Children's Hospital, of which 83 patients completed the study as instructed.

RESULTS

Patient-generated health data from the 83 patients who completed the study were included in the cohort-level analysis. Of the 19% (16/83) of patients deployed in spring, the symptoms of 63% (10/16) and 19% (3/16) of patients suggested pollen and particulate matter (PM2.5), respectively, to be their major asthma triggers. Of the 17% (14/83) of patients deployed in fall, symptoms of 29% (4/17) and 21% (3/17) of patients suggested pollen and PM2.5, respectively, to be their major triggers. Among the 28% (23/83) of patients deployed in winter, PM2.5 was identified as the major trigger for 83% (19/23) of patients. Similar correlations were not observed between asthma symptoms and factors such as ozone level, temperature, and humidity. Furthermore, 1 patient from each season was chosen to explain, in detail, his or her personalized triggers by observing temporal associations between triggers and asthma symptoms gathered using the kHealth asthma kit.

CONCLUSIONS

The continuous monitoring of pediatric asthma patients using the kHealth asthma kit generates insights on the relationship between their asthma symptoms and triggers across different seasons. This can ultimately inform personalized asthma management and intervention plans.

kBot: Knowledge-enabled Personalized Chatbot for Asthma Self-Management

There is a well-recognized need for a shift to proactive asthma care given the impact asthma has on overall healthcare costs. The demand for continuous monitoring of patient's adherence to the medication care plan, assessment of environmental triggers, and management of asthma can be challenging in traditional clinical settings and taxing on clinical professionals. Recent years have seen a robust growth of general purpose conversational systems. However, they lack the capabilities to support applications such an individual's health, which requires the ability to contextualize, learn interactively, and provide the proper hyper-personalization needed to hold meaningful conversations. In this paper, we present kBot, a knowledge-enabled personalized chatbot system designed for health applications and adapted to help pediatric asthmatic patients (age 8 to 15) to better control their asthma. Its core functionalities include continuous monitoring of the patient's medication adherence and tracking of relevant health signals and environment data. kBot takes the form of an Android application with a frontend chat interface capable of conversing in both text and voice, and a backend cloud-based server application that handles data collection, processing, and dialogue management. It achieves contextualization by piecing together domain knowledge from online sources and inputs from our clinical partners. The personalization aspect is derived from patient answering questionnaires and day-to-day conversations. kBOT's preliminary evaluation focused on chatbot quality, technology acceptance, and system usability involved eight asthma clinicians and eight researchers. For both groups, kBot achieved an overall technology acceptance value of greater than 8 on the 11-point Likert scale and a mean System Usability Score (SUS) greater than 80.