Mobile health and behavior tracking (mHBT) among cancer survivors: results from a large and diverse sample

Ubiquitous access to smartphones and widely accessible consumer wearable devices have facilitated adoption of mobile health and behavior tracking (mHBT) in the general population (1). For cancer survivors, mHBT helps them better monitor functional status, symptoms, risk of adverse outcomes, and potentially enhances self-care and improves quality of life. Continuous tracking of biomarkers or health behaviors via mHBT potentially enables real-time monitoring of patients between clinical encounters, extends the coverage and reach of care, thus offers opportunities for more proactive and personalized care. In the past decade, small studies (sample sizes ranged 7 to 70) across a variety of cancer populations have shown the feasibility and potential clinical value of mHBT in oncology (2). Integrating digital data from mHBT with electronic health records (EHRs) or other clinical data requires patients’ willingness to share their data, but literature is scarce on whether cancer survivors are willing to share their data. Thus this study, based on a large survey with a diverse sample of cancer survivors, has two objectives: (I) describe the current mHBT adoption, daily use, and willingness to share data among cancer survivors, and (II) examine the key sociodemographic factors independently associated with these mHBT behaviors.

Data were drawn from the Health Information National Trends Survey (HINTS), a nationally representative survey administered by the National Cancer Institute (NCI) every 2–3 years since 2003 (3). In 2021, NCI oversampled cancer survivors using cancer registries of Surveillance, Epidemiology, and End Results (SEER) from Iowa, New Mexico, and San Francisco Bay Area (4). The new HINTS-SEER included a total of 1,234 cancer survivors and the data were first available in December 2022.

The variable of mHBT was measured by two questions on whether the participant has: (I) used an app on tablet or smartphone to track progress on a health-related goal such as quitting smoking, losing weight, or increasing physical activity, and (II) used an electronic wearable device (e.g., Fitbit, Apple Watch) to monitor or track health or activity. Participants who answered “yes” to either of the two questions were considered mHBT users. These mHBT users were further asked about the frequency of using mobile tools to track or monitor health, and those who did so daily or almost daily were considered daily mHBT users. The mHBT users were also asked if they were willing to share their mHBT data with healthcare providers. Independent variables included in the analysis were key sociodemographic (i.e., age, gender, race, income level, and state of residence), perceived quality of cancer care, and confidence in self-care. Binary and multivariate logistic regressions were used to examine the association between dependent and independent variables. For all analyses, final sample weights and jackknife replicate weights were used to obtain all population-level point estimates, appropriate variance estimates, and P values as suggested by the HINTS-SEER methodology report (4).

Results showed that out of 1,234 cancer survivors, the mean age was 68.8 years, 55% were female, and 8% had difficulty with their current income. Approximately 39.16% (n=475) of participants had adopted mHBT. Table 1 lists the characteristics of participants comparing mHBT users and non-users (binary relationship). Out of 475 mHBT users, 305 answered the question of how often they used it, and 52% (n=160) reported daily use. Out of 475 mHBT users, 307 answered the question of if they were willing to share mHBT data with a healthcare provider, and 86% (n=265) reported they were willing to share. Table 2 shows the independent association between mHBT behaviors with key sociodemographic characteristics; mHBT use was associated with younger age, female gender, college education, and better perceived health, but it was not associated with race, income level, or state of residence after controlling for other covariates. Due to small sample sizes for the two multivariate models on daily use and willingness to share mHBT data, none of the sociodemographic factors showed statistical significance.

The HINTS-SEER data showed relatively high rates of mHBT use (nearly 40%), daily use (52% out of users), and willingness to share data (86% out of users) among cancer survivors; these rates were even higher than the general population. Our analyses also revealed significant disparities in mHBT use among cancer survivors. Younger age, female gender, higher level of education, and better perceived health were associated with mHBT use. Targeted interventions are needed to address the new form of digital divide amid the ubiquitous access to Internet and smartphones to prevent further exacerbation of health disparities (5,6).

The high rates of mHBT use and willingness to share data with healthcare providers suggest substantive opportunities for improved cancer care. Digital data collected from mHBT complement snapshots of health data gathered during clinical visits and can enable symptom management, prevent adverse events or deterioration, support informed-decision making, and facilitate patient-provider communication, leading to better quality of care and better quality of life among cancer survivors (2,7).

The current mHBT use among cancer survivors also suggest potential challenges on policy making, healthcare technology, and clinical practice, for example, HIPAA compliance while integrating patient-generated mHBT data into EHR or other clinical dashboards and sending timely feedback, technical challenges in summarization and visualization of large quantity of mHBT data, and potential biases in interpretation and decision-making given the existing digital health divide. In 2019, Center for Medicare and Medicaid Services (CMS) introduced new CPT codes to allow reimbursement for communication with patients on remote monitoring of physiological data from mHBT (8). NCI is leading Electronic Symptom Management (eSyM), an EHR-integrated PRO-based cancer symptom management program (9). These efforts at the federal level suggest the commitment from policy makers to embrace the opportunities and challenges presented by accelerative technology development.

There are several limitations in this study. First, the cross-sectional design of the HINTS-SEER data prohibits causal interpretation of the data. Second, the measurement of mHBT behaviors was limited to adoption, daily use and willingness to share data, purposes and patterns of use, and health outcomes of the use remain unknown. It is also desirable to have cancer survivor-specific mHBT measures. Third, we examined the association of mHBT behaviors with key sociodemographic factors only, important social determinants of health factors were not included. And fourth, all participants were selected from three cancer registries at New Mexico, Iowa, and San Francisco Bay Area, and might not represent all cancer survivors in the nation.

Despite these limitations, this study represents one of first reports of mHBT behaviors among cancer survivors using a large and diverse sample. Our data highlight significant disparities in mHBT use that require targeted interventions. The high rates of mHBT use and willingness to share data with healthcare providers suggest good opportunities of integrating patient-generated mHBT data with other data collected at clinical encounters for continuous, proactive, and precise oncology care. We also advocate for more research to address potential challenges on ethics, technology development, policy making, and clinical practice brought by growing mHBT among cancer survivors.

Acknowledgments

Funding: None.

Footnote

Peer Review File: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-23-58/prf

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-23-58/coif). The author has no conflicts of interest to declare.

Ethical Statement: The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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