Promoting Health and Well-Being Through Mobile Health Technology (Roadmap 2.0) in Family Caregivers and Patients Undergoing Hematopoietic Stem Cell Transplantation: Protocol for the Development of a Mobile Randomized Controlled Trial

Dyadic and Individual Variation in 24-Hour Heart Rates of Cancer Patients and Their Caregivers

BACKGROUND

Twenty-four-hour heart rate (HR) integrates multiple physiological and psychological systems related to health and well-being, and can be continuously monitored in high temporal resolution over several days with wearable HR monitors. Using HR data from two independent datasets of cancer patients and their caregivers, we aimed to identify dyadic and individual patterns of 24 h HR variation and assess their relationship to demographic, environmental, psychological, and clinical variables of interest.

METHODS

a novel regularized approach to high-dimensional canonical correlation analysis (CCA) was used to identify factors reflecting dyadic and individual variation in the 24 h (circadian) HR trajectories of 430 people in 215 dyads, then regression analysis was used to relate these patterns to explanatory variables.

RESULTS

Four distinct factors of dyadic covariation in circadian HR were found, contributing approximately 7% to overall circadian HR variation. These factors, along with non-dyadic factors reflecting individual variation exhibited diverse and statistically robust patterns of association with explanatory variables of interest.

CONCLUSIONS

Both dyadic and individual anomalies are present in the 24 h HR patterns of cancer patients and their caregivers. These patterns are largely synchronous, and their presence robustly associates with multiple explanatory variables. One notable finding is that higher mood scores in cancer patients correspond to an earlier HR nadir in the morning and higher HR during the afternoon.

The Transplantation Ecosystem: A New Concept to Improve Access and Outcomes for Older Allogeneic Hematopoietic Cell Transplantation Patients

Allogeneic hematopoietic cell transplantation (HCT) is increasingly offered to older adults with hematologic malignancies, even though nonrelapse mortality remains a major concern in older patients owing to more comorbidities and greater frailty compared with their younger counterparts. The importance of patient fitness, a well-matched donor, and disease control to the success of allogeneic HCT have been well documented; however, these factors fail to account for the impact of the complex transplantation ecosystem (TE) that older adult HCT candidates must navigate. We propose a definition of the TE modeled after the social determinants of health. Furthermore, we outline a research agenda aimed at increasing understanding of the roles of individual social determinants of transplantation health in the larger ecosystem and how they may benefit or harm older adult HCT candidates. Herein we define the TE and its individual tenets, the social determinants of transplantation health. We review the available literature while incorporating the expertise of the membership of the American Society for Transplantation and Cellular Therapy (ASTCT) Special Interest Group for Aging. The membership of the ASTCT Special Interest Group for Aging identify knowledge gaps and strategies to address them for each of the described social determinants of transplantation health. The ecosystem is an essential but underappreciated pillar for transplant access and success. We put forth this novel research agenda seeking to gain a better understanding of the complexity of HCT in older adults and develop strategies to improve access to HCT, survival, and quality of life.

Mobile Technology to Monitor and Support Health and Well-Being: Qualitative Study of Perspectives and Design Suggestions From Patients Undergoing Hematopoietic Cell Transplantation

BACKGROUND

In the United States, hematopoietic stem cell transplant (HCT) surpasses 22,000 procedures annually. Due to the demanding and time-intensive process of an HCT, patients and family care partners face unique challenges involving their health and well-being. Positive psychology interventions (PPIs) may offer potential solutions to help boost health and well-being.

OBJECTIVE

This study aimed to explore and understand patients' experiences and perceptions about the use of the Roadmap 2.0 app, specifically its PPI features, during the acute phase of HCT.

METHODS

From an ongoing randomized controlled trial, HCT patients (n=17) were recruited to participate in semistructured qualitative interviews between October 2022 and January 2023 within a large academic medical center in the Midwestern states. Using a qualitative descriptive approach, interviews were conducted in person or via Zoom. The data were analyzed through constant comparative analysis. The Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines were followed.

RESULTS

The majority of the participants reported Roadmap 2.0 as easy to use and enjoyed the ability to track their health data (eg, steps, mood, sleep; 9/17). Regarding the use of PPIs during the acute phase of treatment, 88% of the participants reported interest in participating in PPIs, specifically the Pleasant Activity Scheduling (11/17) followed by Gratitude Journaling (7/17) activities. Additionally, participants provided recommendations on adapting Roadmap 2.0. The major recommendations were (1) "Working Together: Need for Dyadic Involvement," (2) "Connectivity with Other Patients," and (3) "Gap in Nutritional Support." Participants (10/17) expressed the importance of caregiver involvement in activities beyond treatment-related management for maintaining healthy patient-caregiver dyadic relationships. They also expressed their desire for connectivity with other patients undergoing HCT, primarily for comparing experiences and discussing topics such as symptom management (8/17). Lastly, participants identified a gap in nutritional support during the HCT process and expressed interest in an intervention that could promote healthy eating through education and notification reminders (9/17).

CONCLUSIONS

Participants openly expressed their eagerness to participate in research studies that foster connection and positive relationships with their caregivers as well as with other HCT patients. They emphasized the significance of having access to nutritional support or guidance and highlighted the potential benefits of using mobile technology to enhance these collective efforts.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04094844; https://clinicaltrials.gov/study/NCT04094844.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/19288.

Positive psychology interventions for family caregivers coping with cancer: Who will use them?

Background

Positive psychology-based (PPB) activities have been under-researched in cancer caregiving.

Objective

This study investigated caregiver: (1) attitudes toward using PPB activities while caregiving; and (2) characteristics associated with these attitudes.

Methods

Secondary analyses of a cross-sectional survey were conducted in a national caregiver sample of hematopoietic cell transplant (HCT) patients. Survey items assessed caregivers' likelihood of engaging in six PPB activities. Hierarchical regression was performed and potential predictors of PPB activity use (e.g., technology familiarity, coping style, caregiving duration) were examined.

Results

Most of the N = 948 respondents were White (78.9%), female (65.5%), married (86.7%), employed (78.4%), and college-educated (79.8%). Caregivers favorably disposed to positive activities were younger and female, provided care for 6-12 months and >40 h/week, and used coping styles involving religion and social support.

Conclusions

Our findings provide guidance for development and testing of PPB activities for cancer caregivers.

A pilot intervention of using a mobile health app (ONC Roadmap) to enhance health-related quality of life in family caregivers of pediatric patients with cancer

Background

The Roadmap mobile health (mHealth) app was developed to provide health-related quality of life (HRQOL) support for family caregivers of patients with cancer.

Methods

Eligibility included: family caregivers (age ≥18 years) who self-reported as the primary caregiver of their pediatric patient with cancer; patients (age ≥5 years) who were receiving cancer care at the University of Michigan. Feasibility was calculated as the percentage of caregivers who logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the 120-day study duration. Feasibility and acceptability was also assessed through a Feasibility and Acceptability questionnaire and the Mobile App Rating Scale to specifically assess app-quality. Exploratory analyses were also conducted to assess HRQOL self- or parent proxy assessments and physiological data capture.

Results

Between September 2020-September 2021, 100 participants (or 50 caregiver-patient dyads) consented and enrolled in the ONC Roadmap study for 120-days. Feasibility of the study was met, wherein the majority of caregivers (N=32; 65%) logged into ONC Roadmap and engaged with it at least twice weekly for at least 50% of the study duration (defined a priori in the Protocol). The Feasibility and Acceptability questionnaire responses indicated that the study was feasible and acceptable with the majority (>50%) reporting Agree or Strongly Agree with positive Net Favorability [(Agree + Strongly Agree) - (Disagree + Totally Disagree)] in each of the domains (e.g., Fitbit use, ONC Roadmap use, completing longitudinal assessments, engaging in similar future study, study expectations). Improvements were seen across the majority of the mental HRQOL domains across all groups; even though underpowered, there were significant improvements in caregiver-specific aspects of HRQOL and anxiety and in depression and fatigue for children (ages 8-17 years), and a trend toward improvement in depression for children ages 8-17 years and in fatigue for adult patients.

Conclusions

This study supports that mHealth technology may be a promising platform to provide HRQOL support for caregivers of pediatric patients with cancer. Importantly, the findings suggest that the study protocol was feasible, and participants were favorable to participate in future studies of this intervention alongside routine cancer care delivery.

Enhancing Resilience in Family Caregivers Using an mHealth App

BACKGROUND

We previously developed a mobile health (mHealth) app (Roadmap) to promote the resilience of family caregivers during the acute phases of care in patients undergoing hematopoietic cell transplantation (HCT).

OBJECTIVE

This study explored users' perspectives on the uptake of Roadmap's multicomponent features and the app's utility in promoting resilience.

METHODS

Fifteen participants were randomized to the full version of the app that included resilience-building activities and the other 15 were randomized to the control version that included a limited view of the app (i.e., without any resilience-building activities). They were instructed to use the app for 120 days. Semistructured qualitative interviews were then conducted with users as part of an ongoing, larger Roadmap study (NCT04094844). During the interview, caregiver participants were asked about their overall experiences with the app, frequency of use, features used, facilitators of and barriers to use, and their perspectives on its utility in promoting resilience. Data were professionally transcribed, coded, and categorized through content analysis.

RESULTS

Interviews were conducted with 30 participants, which included 23 females and 7 males. The median age of the population was 58 years (range, 23-82). The four main themes that emerged included app use, ease of use, user experiences, and ability to foster resilience. The subthemes identified related to facilitators (convenience and not harmful), barriers (caregiver burden and being too overwhelmed during the acute phases of HCT care), resilience (optimism/positivity and self-care), and app design improvements (personalization and notifications/reminders).

CONCLUSION

The qualitative evaluation provided insights into which components were utilized and how one, or a combination of the multicomponent features, may be enhancing users' experiences. Lessons learned suggest that the Roadmap app contributed to promoting resilience during the acute phases of HCT care. Nonetheless, features that provided enhanced personalization may further improve longer-term engagement.

Family Caregiving during the COVID-19 Pandemic in Canada: A Mediation Analysis

Family caregiving is a public health issue because of caregivers’ significant contribution to the health and social care systems, as well as the substantial impact that giving and receiving care has on the health and quality of life of care receivers and caregivers. While there have been many studies that associate caregivers’ care work, financial difficulty, navigation, and other caregiving factors with family caregivers’ psychological distress, we were interested not only in the factors related to family caregiver anxiety but also in hypothesizing how those effects occur. In this study, we used Andrew Hayes’ PROCESS moderation analysis to explore the link between caregiver frailty, weekly care hours, and perceptions of financial difficulty, social support, and anxiety. In this analysis, we included 474 caregivers with relatively complete data on all of the variables. In regression analysis after controlling for gender and age, social loneliness (β = 0.245), frailty (β = 0.199), financial difficulty (β = 0.196), care time (β = 0.143), and navigation confidence (β = 0.131) were all significant. We then used PROCESS Model 6 to determine the significance of the direct, indirect, and total effects through the serial mediation model. The model pathway from frailty to care time to financial difficulty to social loneliness to anxiety was significant. The proportions of family caregivers who were moderately frail, anxious, and experiencing social loneliness after eighteen months of the COVID-19 pandemic found in this survey should be of concern to policymakers and healthcare providers.

Smartphone applications for informal caregivers of chronically ill patients: a scoping review

Mobile-health applications can be used to deliver timely and personalized health information to family and friends of chronically ill adults living in the community. This scoping review aims to investigate the nature and extent of native smartphone applications for informal caregivers. Six databases were searched for articles on applications across ten chronic conditions, namely heart disease, stroke, cancer, chronic obstructive respiratory disease, asthma, diabetes, Alzheimer’s disease or other dementia, rheumatoid arthritis, hypertension, and mood or anxiety disorders. In total, 36 articles were included, encompassing 26 applications. Of these, smartphone applications were designed for use only by caregivers (n = 15), with a few applications also intended to be used with patients (n = 5), healthcare providers (n = 4), or all three roles (n = 2). Most applications targeted a single chronic condition (n = 25), with Alzheimer’s and other dementia being the most common (n = 18). Only one application was designed for management of multiple chronic conditions. Long-term evaluation methods are needed to continually assess the impact of applications on a range of process and health outcomes, such as usability, caregiver burden, and quality of life. Additional directions to advance native smartphone applications for caregivers are discussed, including personalization and expansion of eligibility criteria.

Risk Factors for COVID-19 in College Students Identified by Physical, Mental, and Social Health Reported During the Fall 2020 Semester: Observational Study Using the Roadmap App and Fitbit Wearable Sensors

BACKGROUND

The COVID-19 pandemic triggered a seismic shift in education to web-based learning. With nearly 20 million students enrolled in colleges across the United States, the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic.

OBJECTIVE

This study leveraged mobile health (mHealth) technology and sought to (1) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; (2) assess physical activity through consumer-grade wearable sensors (Fitbit); and (3) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine.

METHODS

After completing a baseline assessment (ie, at Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, wear the Fitbit, and complete subsequent assessments at T1, T2, and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using mean (SD) values, while categorical measures were summarized as n (%) values. Formal comparisons were made on the basis of COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time through backward selection until the optimal model was obtained.

RESULTS

During the fall 2020 semester, 1997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index, with moderate and severe levels in 465 (24%) and 970 (49%) students, respectively. Approximately one-third of students reported having a mental health disorder (n=656, 33%). The average daily steps recorded in this student population was approximately 6500 (mean 6474, SD 3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-19 positivity with the use of marijuana and alcohol (P=.02 and P=.046, respectively) and with lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009).

CONCLUSIONS

Mental health problems were common in this student population. Several factors, including substance use, were associated with the risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/29561.

Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study

BACKGROUND

The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student's mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being.

OBJECTIVE

Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19.

METHODS

We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population.

RESULTS

This study enrolled 2,158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing.

CONCLUSIONS

This study examined student health and well-being during the COVID-19 pandemic. It also assessed the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19.

CLINICALTRIAL

ClinicalTrials.gov NCT04766788.

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

BACKGROUND

Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families.

OBJECTIVE

By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19.

METHODS

We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use.

RESULTS

A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing.

CONCLUSIONS

Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/29562.

A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT)

Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These techniques have applications in the field of hematopoietic cell transplantation (HCT), which is a potentially curative therapy for hematological malignancies. Herein, a systematic review of the application of machine learning (ML) techniques in the HCT setting was conducted. We examined the type of data streams included, specific ML techniques used, and type of clinical outcomes measured. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included "hematopoietic cell transplantation (HCT)," "autologous HCT," "allogeneic HCT," "machine learning," and "artificial intelligence." Only full-text studies reported between January 2015 and July 2020 were included. Data were extracted by two authors using predefined data fields. Following PRISMA guidelines, a total of 242 studies were identified, of which 27 studies met the inclusion criteria. These studies were sub-categorized into three broad topics and the type of ML techniques used included ensemble learning (63%), regression (44%), Bayesian learning (30%), and support vector machine (30%). The majority of studies examined models to predict HCT outcomes (e.g., survival, relapse, graft-versus-host disease). Clinical and genetic data were the most commonly used predictors in the modeling process. Overall, this review provided a systematic review of ML techniques applied in the context of HCT. The evidence is not sufficiently robust to determine the optimal ML technique to use in the HCT setting and/or what minimal data variables are required.