Feasibility and acceptability of measuring prenatal stress in daily life using smartphone-based ecological momentary assessment and wearable physiological monitors.

High levels of stress during pregnancy can have lasting effects on maternal and offspring health, which disproportionately impacts families facing financial strain, systemic racism, and other forms of social oppression. Developing ways to monitor daily life stress during pregnancy is important for reducing stress-related health disparities. We evaluated the feasibility and acceptability of using mobile health (mHealth) technology (i.e., wearable biosensors, smartphone-based ecological momentary assessment) to measure prenatal stress in daily life. Fifty pregnant women (67% receiving public assistance; 70% Black, 6% Multiracial, 24% White) completed 10 days of ambulatory assessment, in which they answered smartphone-based surveys six times a day and wore a chest-band device (movisens EcgMove4) to monitor their heart rate, heart rate variability, and activity level. Feasibility and acceptability were evaluated using behavioral meta-data and participant feedback. Findings supported the feasibility and acceptability of mHealth methods: Participants answered approximately 75% of the surveys per day and wore the device for approximately 10 hours per day. Perceived burden was low. Notably, participants with higher reported stressors and financial strain reported lower burden associated with the protocol than participants with fewer life stressors, highlighting the feasibility of mHealth technology for monitoring prenatal stress among pregnant populations living with higher levels of contextual stressors. Findings support the use of mHealth technology to measure prenatal stress in real-world, daily life settings, which shows promise for informing scalable, technology-assisted interventions that may help to reduce health disparities by enabling more accessible and comprehensive care during pregnancy.

Associations between performance-based and patient-reported physical functioning and real-world mobile sensor metrics in older cancer survivors: A pilot study.

INTRODUCTION: Older cancer survivors are at increased risk for impaired physical functioning, but current assessments of function are difficult to implement in busy oncology clinics. Mobile devices measuring continuous activity and mobility in daily life may be useful for estimating physical functioning. The goal of this pilot study was to examine the associations between consumer wearable device (a wrist-worn activity tracker) and smartphone sensor data and commonly used clinical measures of physical function in cancer survivors aged 65 and older. MATERIALS AND METHODS: Older adults within five years of completing primary treatment for any cancer completed standardized questionnaires and performance-based tests to measure physical functioning. Continuous passive data from smartphones and consumer wearable devices were collected for four weeks and linked to patient-reported and performance-based physical functioning as well as patient-reported falls or near falls at the end of the four-week monitoring period. To examine associations between sensor variables and physical functioning, we conducted bivariate Pearson correlations as well as multivariable linear regression analyses. To examine associations between sensor variables and falls, we conducted exploratory receiver operating characteristic curve and multivariable logistic regression analyses. RESULTS: We enrolled 40 participants (mean age 73 years old, range 65-83; 98% White; 50% female). In bivariate analyses, consumer wearable device features reflecting greater amount and speed and lower fragmentation of walking in daily life were significantly related to better patient-reported function (r= 0.43-0.65) and performance-based physical function (r = 0.56-0.72), while smartphone features reflecting more geographic mobility were related to better performance-based physical function (r = 0.40-0.42) but not patient-reported function. After adjusting for age and comorbidities, only consumer wearable device features remained associated with performance-based physical functioning. In exploratory analyses, peak gait cadence was associated with fall risk even after covariate adjustment. DISCUSSION: This study provides preliminary evidence that real-world data from consumer devices may be useful for estimating functional performance among older cancer survivors and potentially for remotely and longitudinally monitoring functioning in older patients during and after cancer treatment.

Impact of the COVID-19 pandemic on cancer patients in western Pennsylvania: rural-urban disparities.

PURPOSE: Disparities in cancer care persist between patients living in rural versus urban areas. The COVID-19 pandemic may have impacted concerns related to care and personal health differently in rural cancer patients. Using survey data collected from cancer patients in western Pennsylvania, we examined pandemic-related distress, concerns related to cancer care, impact on personal health, and the extent to which these differed by urban-rural residence. METHODS: Patients filled out an initial survey in August-December 2020; a second survey was completed in March 2021. The following patient concerns related to the pandemic were evaluated: threat of COVID-19 to their health, pandemic-related distress, perceptions of cancer care, and vaccine hesitancy. Multivariable logistic regression models were used to examine relationships between these outcomes and urban-rural residence as well as patient-related factors, including anxiety symptoms and social support. RESULTS: The study sample included 1,980 patients, 17% resided in rural areas. COVID-19 represented a major or catastrophic threat to personal health for 39.7% of rural and 49.0% of urban patients (p = 0.0017). Patients with high general anxiety were 10-times more likely to experience pandemic-related distress (p < 0.001). In the follow-up survey (n = 983), vaccine hesitancy was twice as prevalent among rural patients compared to urban (p = 0.012). CONCLUSIONS: The extent to which perceptions of the threat of COVD-19 to personal health and vaccine hesitancy exacerbates rural-urban disparities in cancer care and prognosis warrants further study. Cancer patients may be vulnerable to heightened anxiety and distress triggered by the pandemic.

Digital health and telehealth in cancer care: a scoping review of reviews.

The COVID-19 pandemic necessitated remote cancer care delivery via the internet and telephone, rapidly accelerating an already growing care delivery model and associated research. This scoping review of reviews characterised the peer-reviewed literature reviews on digital health and telehealth interventions in cancer published from database inception up to May 1, 2022, from PubMed, Cumulated Index to Nursing and Allied Health Literature, PsycINFO, Cochrane Reviews, and Web of Science. Eligible reviews conducted a systematic literature search. Data were extracted in duplicate via a pre-defined online survey. Following screening, 134 reviews met the eligibility criteria. 77 of those reviews were published since 2020. 128 reviews summarised interventions intended for patients, 18 addressed family caregivers, and five addressed health-care providers. 56 reviews did not target a specific phase of the cancer continuum, whereas 48 reviews tended to address the active treatment phase. 29 reviews included a meta-analysis, with results showing positive effects on quality of life, psychological outcomes, and screening behaviours. 83 reviews did not report intervention implementation outcomes but when reported, 36 reported acceptability, 32 feasibility, and 29 fidelity outcomes. Several notable gaps were identified in these literature reviews on digital health and telehealth in cancer care. No reviews specifically addressed older adults, bereavement, or sustainability of interventions and only two reviews focused on comparing telehealth to in-person interventions. Addressing these gaps with rigorous systematic reviews might help guide continued innovation in remote cancer care, particularly for older adults and bereaved families, and integrate and sustain these interventions within oncology.

Patient and Provider Perspectives on Symptom Monitoring During Outpatient Chemotherapy: Interview Study.

BACKGROUND: Fluctuating symptoms and side effects are common during outpatient cancer treatment, and approaches to monitoring symptoms vary widely across providers, patients, and clinical settings. To design a remote symptom monitoring system that patients and providers find to be useful, it may be helpful to understand current clinical approaches to monitoring and managing chemotherapy-related symptoms among patients and providers and assess how more frequent and systematic assessment and sharing of data could improve patient and provider experiences. OBJECTIVE: The goals of this study were to learn about patient and provider perspectives on monitoring symptoms during chemotherapy, understand barriers and challenges to effective symptom monitoring at one institution, and explore the potential value of remote symptom monitoring between provider visits. METHODS: A total of 15 patients who were currently undergoing or had recently completed chemotherapy and 7 oncology providers participated in semistructured interviews. Interviews were transcribed and coded using an iterative thematic analysis approach. The study was conducted at a National Cancer Institute-Designated Comprehensive Cancer Center. RESULTS: Four main themes were discussed by patients and providers: (1) asynchronous nature of current methods for tracking and managing symptoms, (2) variability in reported symptoms due to patient factors, (3) limitations of existing communication channels, and (4) potential value of real-time remote symptom monitoring during chemotherapy. Current asynchronous methods and existing communication channels resulted in a disconnect between when symptoms are most severe and when conversations about symptoms happen, a situation further complicated by memory impairments during chemotherapy. Patients and providers both highlighted improvements in patient-provider communication as a potential benefit of remote real-time symptom monitoring. Providers also emphasized the value of temporal data regarding when symptoms first emerge and how they progress over time, as well as the potential value of concurrent activity or other data about daily activities and functioning. Patients noted that symptom monitoring could result in better preparation for subsequent treatment cycles. CONCLUSIONS: Both patients and providers highlighted significant challenges of asynchronous, patient-initiated, phone-dependent symptom monitoring and management. Oncology patients and providers reported that more routine remote monitoring of symptoms between visits could improve patient-provider communication, prepare patients for subsequent chemotherapy cycles, and facilitate provider insight and clinical decision-making with regard to symptom management.

Cisplatin-Induced Ototoxicity: A Concise Review of the Burden, Prevention, and Interception Strategies.

Cisplatin is a bedrock of cancer management and one of the most used chemotherapeutic agents in the treatment of germ cell, lung, bladder, ovarian, and head and neck cancers. Approximately 500,000 patients diagnosed annually with these cancer types in the United States could be candidates for treatment with cisplatin. There is a 5-fold increase in the risk of hearing impairment or ototoxicity with cisplatin, which can manifest as ringing in the ear (tinnitus), high-frequency hearing loss, and at late stages, a decreased ability to hear normal conversation. More than half of adult and pediatric patients with cancer treated with cisplatin developed hearing impairment with major impact on patients' health-related quality of life. A considerable evidence gap persists regarding the burden and effective prevention and interception strategies for cisplatin-induced ototoxicity, especially in adult patients with cancer. We conducted a review of the published literature to provide an update on the status of this important clinical challenge. We also surveyed practicing oncologists within our network of academic and community practices to gain a better understanding of how the published literature compares with real-world practice. Our review of the literature showed a lack of standardized guidelines for monitoring and treatment of cisplatin-induced ototoxicity, especially in the adult cancer patient population. Our survey of practicing oncologists mirrored the findings from the published literature with a heterogeneity of practice, which highlights the need for standardization.

A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Pilot Randomized Controlled Trial.

BACKGROUND: Sedentary behavior (SB) is prevalent after abdominal cancer surgery, and interventions targeting perioperative SB could improve postoperative recovery and outcomes. We conducted a pilot study to evaluate the feasibility and preliminary effects of a real-time mobile intervention that detects and disrupts prolonged SB before and after cancer surgery, relative to a monitoring-only control condition. OBJECTIVE: Our aim was to evaluate the feasibility and preliminary effects of a perioperative SB intervention on objective activity behavior, patient-reported quality of life and symptoms, and 30-day readmissions. METHODS: Patients scheduled for surgery for metastatic gastrointestinal cancer (n=26) were enrolled and randomized to receive either the SB intervention or activity monitoring only. Both groups used a Fitbit smartwatch and companion smartphone app to rate daily symptoms and collect continuous objective activity behavior data starting from at least 10 days before surgery through 30 days post discharge. Participants in the intervention group also received prompts to walk after any SB bout that exceeded a prespecified threshold, with less frequent prompts on days that patients reported more severe symptoms. Participants completed end-of-study ratings of acceptability, and we also examined adherence to assessments and to walking prompts. In addition, we examined effects of the intervention on objective SB and step counts, patient-reported quality of life and depressive and physical symptoms, as well as readmissions. RESULTS: Accrual (74%), retention (88%), and acceptability ratings (mean overall satisfaction 88.5/100, SD 9.1) were relatively high. However, adherence to assessments and engagement with the SB intervention decreased significantly after surgery and did not recover to preoperative levels after postoperative discharge. All participants exhibited significant increases in SB and symptoms and decreases in steps and quality of life after surgery, and participants randomized to the SB intervention unexpectedly had longer maximum SB bouts relative to the control group. No significant benefits of the intervention with regard to activity, quality of life, symptoms, or readmission were observed. CONCLUSIONS: Perioperative patients with metastatic gastrointestinal cancer were interested in a real-time SB intervention and rated the intervention as highly acceptable, but engagement with the intervention and with daily symptom and activity monitoring decreased significantly after surgery. There were no significant effects of the intervention on step counts, patient-reported quality of life or symptoms, and postoperative readmissions, and there was an apparent adverse effect on maximum SB. Results highlight the need for additional work to modify the intervention to make reducing SB and engaging with mobile health technology after abdominal cancer surgery more feasible and beneficial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03211806; https://tinyurl.com/3napwkkt.

Continuous-Time Modeling of the Bidirectional Relationship Between Incidental Affect and Physical Activity.

BACKGROUND: Previous research suggests that there is a bidirectional relationship between incidental affect (i.e., how people feel in day-to-day life) and physical activity behavior. However, many inconsistencies exist in the body of work due to the lag interval between affect and physical activity measurements. PURPOSE: Using a novel continuous-time analysis paradigm, we examined the temporal specificity underlying the dynamic relationship between positive and negative incidental affective states and moderate-to-vigorous physical activity (MVPA). METHODS: A community sample of adults (n = 126, Mage = 27.71, 51.6% Male) completed a 14-day ambulatory assessment protocol measuring momentary positive and negative incidental affect six times a day while wearing a physical activity monitor (Fitbit). Hierarchical Bayesian continuous-time structural equation modeling was used to elucidate the underlying dynamics of the relationship between incidental affective states and MVPA. RESULTS: Based on the continuous-time cross-effects, positive and negative incidental affect predicted subsequent MVPA. Furthermore, engaging in MVPA predicted subsequent positive and negative incidental affect. Incidental affective states had a greater relative influence on predicting subsequent MVPA compared to the reciprocal relationship. Analysis of the discrete-time coefficients suggests that cross-lagged effects increase as the time interval between measurements increase, peaking at about 8 h between measurement occasions before beginning to dissipate. CONCLUSIONS: The results provide support for a recursive relationship between incidental affective states and MVPA, which is particularly strong at 7-9 hr time intervals. Future research designs should consider these medium-term dynamics, for both theory development and intervention.

Association of robotic approach with patient-reported outcomes after pancreatectomy: a prospective cohort study.

BACKGROUND: Robotic-assisted pancreatectomy continues to proliferate despite limited evidence supporting its benefits from the patient's perspective. We compared patient-reported outcomes (PROs) between patients undergoing robotic and open pancreatectomies. METHODS: PROs, measured with the FACT-Hep, FACT-G, and HCS, were assessed in the immediate postoperative (i.e., preoperative to discharge) and recovery (i.e., discharge to three months postoperative) periods. Linear mixed models estimated the association of operative approach on PROs. Minimally important differences (MIDs) were also considered. RESULTS: Among 139 patients, 105 (75.5%) underwent robotic pancreatectomies. Compared to those who underwent open operations, those who underwent robotic operations experienced worse FACT-Hep scores that were both statistically and clinically significant (mean difference [MD] 8.6 points, 95% CI 1.0-16.3). Declines in FACT-G (MD 4.3, 95% CI -1.0 to 9.6) and HCS (MD 4.3, 95% CI 0.8-7.9) scores appeared to contribute equally in both operative approaches to the decline in total FACT-Hep score. Patients who underwent robotic versus open operations both statistically and clinically significantly improved due to improvements in HCS (MD 6.1, 95% CI 2.3-9.9) but not in FACT-G (MD 1.2, 95% CI - 5.1-7.4). CONCLUSION: The robotic approach to pancreas surgery might offer, from the patient's perspective, greater improvement in symptoms over the open approach by three months postoperatively.

Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices.

Smartphone and wearable devices are widely used in behavioral and clinical research to collect longitudinal data that, along with ground truth data, are used to create models of human behavior. Mobile sensing researchers often program data processing and analysis code from scratch even though many research teams collect data from similar mobile sensors, platforms, and devices. This leads to significant inefficiency in not being able to replicate and build on others' work, inconsistency in quality of code and results, and lack of transparency when code is not shared alongside publications. We provide an overview of Reproducible Analysis Pipeline for Data Streams (RAPIDS), a reproducible pipeline to standardize the preprocessing, feature extraction, analysis, visualization, and reporting of data streams coming from mobile sensors. RAPIDS is formed by a group of R and Python scripts that are executed on top of reproducible virtual environments, orchestrated by a workflow management system, and organized following a consistent file structure for data science projects. We share open source, documented, extensible and tested code to preprocess, extract, and visualize behavioral features from data collected with any Android or iOS smartphone sensing app as well as Fitbit and Empatica wearable devices. RAPIDS allows researchers to process mobile sensor data in a rigorous and reproducible way. This saves time and effort during the data analysis phase of a project and facilitates sharing analysis workflows alongside publications.

Digital Biomarkers of Symptom Burden Self-Reported by Perioperative Patients Undergoing Pancreatic Surgery: Prospective Longitudinal Study.

BACKGROUND: Cancer treatments can cause a variety of symptoms that impair quality of life and functioning but are frequently missed by clinicians. Smartphone and wearable sensors may capture behavioral and physiological changes indicative of symptom burden, enabling passive and remote real-time monitoring of fluctuating symptoms. OBJECTIVE: The aim of this study was to examine whether smartphone and Fitbit data could be used to estimate daily symptom burden before and after pancreatic surgery. METHODS: A total of 44 patients scheduled for pancreatic surgery participated in this prospective longitudinal study and provided sufficient sensor and self-reported symptom data for analyses. Participants collected smartphone sensor and Fitbit data and completed daily symptom ratings starting at least two weeks before surgery, throughout their inpatient recovery, and for up to 60 days after postoperative discharge. Day-level behavioral features reflecting mobility and activity patterns, sleep, screen time, heart rate, and communication were extracted from raw smartphone and Fitbit data and used to classify the next day as high or low symptom burden, adjusted for each individual's typical level of reported symptoms. In addition to the overall symptom burden, we examined pain, fatigue, and diarrhea specifically. RESULTS: Models using light gradient boosting machine (LightGBM) were able to correctly predict whether the next day would be a high symptom day with 73.5% accuracy, surpassing baseline models. The most important sensor features for discriminating high symptom days were related to physical activity bouts, sleep, heart rate, and location. LightGBM models predicting next-day diarrhea (79.0% accuracy), fatigue (75.8% accuracy), and pain (79.6% accuracy) performed similarly. CONCLUSIONS: Results suggest that digital biomarkers may be useful in predicting patient-reported symptom burden before and after cancer surgery. Although model performance in this small sample may not be adequate for clinical implementation, findings support the feasibility of collecting mobile sensor data from older patients who are acutely ill as well as the potential clinical value of mobile sensing for passive monitoring of patients with cancer and suggest that data from devices that many patients already own and use may be useful in detecting worsening perioperative symptoms and triggering just-in-time symptom management interventions.

Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders.

The goal of precision medicine (individually tailored treatments) is not being achieved for neurobehavioural conditions such as psychiatric disorders. Traditional randomized clinical trial methods are insufficient for advancing precision medicine because of the dynamic complexity of these conditions. We present a pragmatic solution: the precision clinical trial framework, encompassing methods for individually tailored treatments. This framework includes the following: (1) treatment-targeted enrichment, which involves measuring patients' response after a brief bout of an intervention, and then randomizing patients to a full course of treatment, using the acute response to predict long-term outcomes; (2) adaptive treatments, which involve adjusting treatment parameters during the trial to individually optimize the treatment; and (3) precise measurement, which involves measuring predictor and outcome variables with high accuracy and reliability using techniques such as ecological momentary assessment. This review summarizes precision clinical trials and provides a research agenda, including new biomarkers such as precision neuroimaging, transcranial magnetic stimulation-electroencephalogram digital phenotyping and advances in statistical and machine-learning models. Validation of these approaches - and then widespread incorporation of the precision clinical trial framework - could help achieve the vision of precision medicine for neurobehavioural conditions.

Harnessing consumer smartphone and wearable sensors for clinical cancer research.

As smartphones and consumer wearable devices become more ubiquitous, there is a growing opportunity to capture rich mobile sensor data continuously, passively, and in real-world settings with minimal burden. In the context of cancer, changes in these passively sensed digital biomarkers may reflect meaningful variation in functional status, symptom burden, quality of life, and risk for adverse clinical outcomes. These data could enable real-time remote monitoring of patients between clinical encounters and more proactive, comprehensive, and personalized care. Over the past few years, small studies across a variety of cancer populations support the feasibility and potential clinical value of mobile sensors in oncology. Barriers to implementing mobile sensing in clinical oncology care include the challenges of managing and making sense of continuous sensor data, patient engagement issues, difficulty integrating sensor data into existing electronic health systems and clinical workflows, and ethical and privacy concerns. Multidisciplinary collaboration is needed to develop mobile sensing frameworks that overcome these barriers and that can be implemented at large-scale for remote monitoring of deteriorating health during or after cancer treatment or for promotion and tailoring of lifestyle or symptom management interventions. Leveraging digital technology has the potential to enrich scientific understanding of how cancer and its treatment affect patient lives, to use this understanding to offer more timely and personalized support to patients, and to improve clinical oncology outcomes.

Guidelines for wrist-worn consumer wearable assessment of heart rate in biobehavioral research.

Researchers have increasingly begun to use consumer wearables or wrist-worn smartwatches and fitness monitors for measurement of cardiovascular psychophysiological processes related to mental and physical health outcomes. These devices have strong appeal because they allow for continuous, scalable, unobtrusive, and ecologically valid data collection of cardiac activity in "big data" studies. However, replicability and reproducibility may be hampered moving forward due to the lack of standardization of data collection and processing procedures, and inconsistent reporting of technological factors (e.g., device type, firmware versions, and sampling rate), biobehavioral variables (e.g., body mass index, wrist dominance and circumference), and participant demographic characteristics, such as skin tone, that may influence heart rate measurement. These limitations introduce unnecessary noise into measurement, which can cloud interpretation and generalizability of findings. This paper provides a brief overview of research using commercial wearable devices to measure heart rate, reviews literature on device accuracy, and outlines the challenges that non-standardized reporting pose for the field. We also discuss study design, technological, biobehavioral, and demographic factors that can impact the accuracy of the passive sensing of heart rate measurements, and provide guidelines and corresponding checklist handouts for future study data collection and design, data cleaning and processing, analysis, and reporting that may help ameliorate some of these barriers and inconsistencies in the literature.

A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Usability and Feasibility Study.

BACKGROUND: Sedentary behavior (SB) is common after cancer surgery and may negatively affect recovery and quality of life, but postoperative symptoms such as pain can be a significant barrier to patients achieving recommended physical activity levels. We conducted a single-arm pilot trial evaluating the usability and acceptability of a real-time mobile intervention that detects prolonged SB in the perioperative period and delivers prompts to walk that are tailored to daily self-reported symptom burden. OBJECTIVE: The aim of this study is to develop and test a mobile technology-supported intervention to reduce SB before and after cancer surgery, and to evaluate the usability and feasibility of the intervention. METHODS: A total of 15 patients scheduled for abdominal cancer surgery consented to the study, which involved using a Fitbit smartwatch with a companion smartphone app across the perioperative period (from a minimum of 2 weeks before surgery to 30 days postdischarge). Participants received prompts to walk after any SB that exceeded a prespecified threshold, which varied from day to day based on patient-reported symptom severity. Participants also completed weekly semistructured interviews to collect information on usability, acceptability, and experience using the app and smartphone; in addition, smartwatch logs were examined to assess participant study compliance. RESULTS: Of eligible patients approached, 79% (15/19) agreed to participate. Attrition was low (1/15, 7%) and due to poor health and prolonged hospitalization. Participants rated (0-100) the smartphone and smartwatch apps as very easy (mean 92.3 and 93.2, respectively) and pleasant to use (mean 93.0 and 93.2, respectively). Overall satisfaction with the whole system was 89.9, and the mean System Usability Scale score was 83.8 out of 100. Overall compliance with symptom reporting was 51% (469/927 days), decreasing significantly from before surgery (264/364, 73%) to inpatient recovery (32/143, 22%) and postdischarge (173/420, 41%). Overall Fitbit compliance was 70% (653/927 days) but also declined from before surgery (330/364, 91%) to inpatient (51/143, 36%) and postdischarge (272/420, 65%). CONCLUSIONS: Perioperative patients with cancer were willing to use a smartwatch- and smartphone-based real-time intervention to reduce SB, and they rated the apps as very easy and pleasant to use. Compliance with the intervention declined significantly after surgery. The effects of the intervention on postoperative activity patterns, recovery, and quality of life will be evaluated in an ongoing randomized trial.

Fitbit step counts during inpatient recovery from cancer surgery as a predictor of readmission.

Background: Postoperative ambulation is encouraged to promote timely recovery but is rarely monitored objectively or examined as a predictor of clinical outcomes, despite growing availability of wearable devices that allow passive quantification and remote real-time monitoring of the number of steps taken during recovery. Purpose: To determine whether the number of steps taken during inpatient recovery predicts 30- and 60-day readmission risk after metastatic cancer surgery. Methods: Patients diagnosed with metastatic peritoneal cancer and scheduled for surgical resection were enrolled in this observational cohort study at their preoperative clinic visit. Fitbits were placed on patients' wrists upon transfer from the ICU following surgery and worn for the duration of their inpatient stay. Information about hospital readmission was extracted from electronic medical records. Results: Seventy-one patients participated in the study (mean age = 57.14, range = 31-80 years; 42% female; 51% diagnosed with appendiceal cancer). Mean steps per day were calculated for each participant over the entire inpatient recovery period (mean stay = 12.12 days, 4-37 days). Readmission within 30 and 60 days was medically indicated for 34% and 39% of patients, respectively. After statistically adjusting for age, body mass index, comorbidity, and length of postoperative stay, higher mean steps per day predicted lower 30-day and 60-day readmission risk. Conclusions: Higher Fitbit step counts during inpatient recovery predicted lower risk of 30- and 60-day readmission after surgery for metastatic peritoneal cancer. Results suggest that passively monitoring perioperative ambulation may identify patients at risk for readmission and highlight opportunities for behavioral intervention.

Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study.

BACKGROUND: Physical and psychological symptoms are common during chemotherapy in cancer patients, and real-time monitoring of these symptoms can improve patient outcomes. Sensors embedded in mobile phones and wearable activity trackers could be potentially useful in monitoring symptoms passively, with minimal patient burden. OBJECTIVE: The aim of this study was to explore whether passively sensed mobile phone and Fitbit data could be used to estimate daily symptom burden during chemotherapy. METHODS: A total of 14 patients undergoing chemotherapy for gastrointestinal cancer participated in the 4-week study. Participants carried an Android phone and wore a Fitbit device for the duration of the study and also completed daily severity ratings of 12 common symptoms. Symptom severity ratings were summed to create a total symptom burden score for each day, and ratings were centered on individual patient means and categorized into low, average, and high symptom burden days. Day-level features were extracted from raw mobile phone sensor and Fitbit data and included features reflecting mobility and activity, sleep, phone usage (eg, duration of interaction with phone and apps), and communication (eg, number of incoming and outgoing calls and messages). We used a rotation random forests classifier with cross-validation and resampling with replacement to evaluate population and individual model performance and correlation-based feature subset selection to select nonredundant features with the best predictive ability. RESULTS: Across 295 days of data with both symptom and sensor data, a number of mobile phone and Fitbit features were correlated with patient-reported symptom burden scores. We achieved an accuracy of 88.1% for our population model. The subset of features with the best accuracy included sedentary behavior as the most frequent activity, fewer minutes in light physical activity, less variable and average acceleration of the phone, and longer screen-on time and interactions with apps on the phone. Mobile phone features had better predictive ability than Fitbit features. Accuracy of individual models ranged from 78.1% to 100% (mean 88.4%), and subsets of relevant features varied across participants. CONCLUSIONS: Passive sensor data, including mobile phone accelerometer and usage and Fitbit-assessed activity and sleep, were related to daily symptom burden during chemotherapy. These findings highlight opportunities for long-term monitoring of cancer patients during chemotherapy with minimal patient burden as well as real-time adaptive interventions aimed at early management of worsening or severe symptoms.

Psychological Distress, Health Behaviors, and Benefit Finding in Survivors of Multiple Primary Cancers: Results From the 2010 Livestrong Survey.

PURPOSE/OBJECTIVES: To evaluate whether survivorship of multiple primary cancers (MPCs) is associated with psychological distress, positive health behaviors, and benefit finding.
. DESIGN: Secondary analysis of the 2010 Livestrong cross-sectional survey.
. SETTING: Online survey.
. SAMPLE: 238 MPC survivors and 3,295 single cancer survivors.
. METHODS: Chi-square and t tests for group comparisons were used. Multivariate linear regression, adjusted for covariates, was used to determine associations between variables.
. MAIN RESEARCH VARIABLES: MPC versus single cancer; psychological distress, health behavior (healthy lifestyle and positive healthcare utilization), and benefit-finding scores.
. FINDINGS: Survivors of MPCs (compared to single cancer survivors) were significantly older, less likely to have a spouse or partner, further out from original cancer diagnosis, and less likely to be employed full-time, and they differed by cancer diagnoses and survivorship stage. Having MPCs was associated with significantly higher psychological distress and healthcare utilization but not healthy lifestyle or benefit finding.
. CONCLUSIONS: Relative to those with single cancers, MPC survivors are at increased risk for psychological distress and are more likely to receive recommended cancer screenings. Additional research is needed to understand mechanisms surrounding psychological distress in MPC survivors.
. IMPLICATIONS FOR NURSING: Targeted distress screening in MPC survivors may allow for early identification and interventions to ameliorate distress and reduce negative downstream health effects.