scholarly journals Use of Wearable Activity Tracker in Patients With Cancer Undergoing Chemotherapy: Toward Evaluating Risk of Unplanned Health Care Encounters

2020 ◽  
pp. 839-853
Author(s):  
Tanachat Nilanon ◽  
Luciano P. Nocera ◽  
Alexander S. Martin ◽  
Anand Kolatkar ◽  
Marcella May ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Care ◽  
Exploratory Analysis ◽  
Activity Tracking ◽  
Patients With Cancer ◽  
Activity Tracker ◽  
Activity Measurements ◽  
Health Care Encounters ◽  
Wearable Activity Tracker ◽  
Tracking Period

PURPOSE Unplanned health care encounters (UHEs) such as emergency room visits can occur commonly during cancer chemotherapy treatments. Patients at an increased risk of UHEs are typically identified by clinicians using performance status (PS) assessments based on a descriptive scale, such as the Eastern Cooperative Oncology Group (ECOG) scale. Such assessments can be bias prone, resulting in PS score disagreements between assessors. We therefore propose to evaluate PS using physical activity measurements (eg, energy expenditure) from wearable activity trackers. Specifically, we examined the feasibility of using a wristband (band) and a smartphone app for PS assessments. METHODS We conducted an observational study on a cohort of patients with solid tumor receiving highly emetogenic chemotherapy. Patients were instructed to wear the band for a 60-day activity-tracking period. During clinic visits, we obtained ECOG scores assessed by physicians, coordinators, and patients themselves. UHEs occurring during the activity-tracking period plus a 90-day follow-up period were later compiled. We defined our primary outcome as the percentage of patients adherent to band-wear ≥ 80% of 10 am to 8 pm for ≥ 80% of the activity-tracking period. In an exploratory analysis, we computed hourly metabolic equivalent of task (MET) and counted 10 am to 8 pm hours with > 1.5 METs as nonsedentary physical activity hours. RESULTS Forty-one patients completed the study (56.1% female; 61.0% age 40-60 years); 68% were adherent to band-wear. ECOG score disagreement between assessors ranged from 35.3% to 50.0%. In our exploratory analysis, lower average METs and nonsedentary hours, but not higher ECOG scores, were associated with higher 150-day UHEs. CONCLUSION The use of a wearable activity tracker is generally feasible in a similar population of patients with cancer. A larger randomized controlled trial should be conducted to confirm the association between lower nonsedentary hours and higher UHEs.

scholarly journals An Activity Tracker–Guided Physical Activity Program for Patients Undergoing Radiotherapy: Protocol for a Prospective Phase III Trial (OnkoFit I and II Trials) (Preprint)

2021 ◽  
Author(s):  
Franziska Hauth ◽  
Barbara Gehler ◽  
Andreas Michael Nieß ◽  
Katharina Fischer ◽  
Andreas Toepell ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Functional Assessment ◽  
Exercise Program ◽  
Daily Step ◽  
Patients With Cancer ◽  
Activity Tracker ◽  
Cancer Related Fatigue ◽  
Daily Step Count

BACKGROUND The positive impact that physical activity has on patients with cancer has been shown in several studies over recent years. However, supervised physical activity programs have several limitations, including costs and availability. Therefore, our study proposes a novel approach for the implementation of a patient-executed, activity tracker–guided exercise program to bridge this gap. OBJECTIVE Our trial aims to investigate the impact that an activity tracker–guided, patient-executed exercise program for patients undergoing radiotherapy has on cancer-related fatigue, health-related quality of life, and preoperative health status. METHODS Patients receiving postoperative radiotherapy for breast cancer (OnkoFit I trial) or neoadjuvant, definitive, or postoperative treatment for other types of solid tumors (OnkoFit II trial) will be randomized (1:1:1) into 3-arm studies. Target accrual is 201 patients in each trial (50 patients per year). After providing informed consent, patients will be randomized into a standard care arm (arm A) or 1 of 2 interventional arms (arms B and C). Patients in arms B and C will wear an activity tracker and record their daily step count in a diary. Patients in arm C will receive personalized weekly targets for their physical activity. No further instructions will be given to patients in arm B. The target daily step goals for patients in arm C will be adjusted weekly and will be increased by 10% of the average daily step count of the past week until they reach a maximum of 6000 steps per day. Patients in arm A will not be provided with an activity tracker. The primary end point of the OnkoFit I trial is cancer-related fatigue at 3 months after the completion of radiotherapy. This will be measured by the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire. For the OnkoFit II trial, the primary end point is the overall quality of life, which will be assessed with the Functional Assessment of Cancer Therapy-General sum score at 6 months after treatment to allow for recovery after possible surgery. In parallel, blood samples from before, during, and after treatment will be collected in order to assess inflammatory markers. RESULTS Recruitment for both trials started on August 1, 2020, and to date, 49 and 12 patients have been included in the OnkoFit I and OnkoFit II trials, respectively. Both trials were approved by the institutional review board prior to their initiation. CONCLUSIONS The OnkoFit trials test an innovative, personalized approach for the implementation of an activity tracker–guided training program for patients with cancer during radiotherapy. The program requires only a limited amount of resources. CLINICALTRIAL ClinicalTrials.gov NCT04506476; https://clinicaltrials.gov/ct2/show/NCT04506476. ClinicalTrials.gov NCT04517019; https://clinicaltrials.gov/ct2/show/NCT04517019. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/28524

scholarly journals Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study

10.2196/18491 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e18491
Author(s):  
Tracy E Crane ◽  
Meghan B Skiba ◽  
Austin Miller ◽  
David O Garcia ◽  
Cynthia A Thomson
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Data Collection ◽  
Cancer Survivors ◽  
Accelerometer Data ◽  
Activity Tracking ◽  
Activity Data ◽  
Convenience Sample ◽  
Time Points ◽  
Activity Measurements

Background The collection of self-reported physical activity using validated questionnaires has known bias and measurement error. Objective Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control. Methods From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns. Results We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (P<.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer. Conclusions The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

A personalised smartphone-delivered just-in-time adaptive intervention (JITABug) to increase physical activity in older adults: A feasibility pilot study (Preprint)

2021 ◽  
Author(s):  
Jacqueline Louise Mair ◽  
Lawrence Hayes ◽  
Amy Campbell ◽  
Duncan Buchan ◽  
Chris Easton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Data Collection ◽  
Real Time ◽  
Behaviour Change ◽  
Time Of Day ◽  
Activity Level ◽  
Just In Time ◽  
Activity Tracker ◽  
Wearable Activity Tracker

BACKGROUND Just-in-time-adaptive-interventions (JITAIs) provide real-time ‘in the moment’ behaviour change support to people when they need it most. JITAIs could be a viable way to provide personalised physical activity support to older adults in the community. However, it is unclear how feasible it is to remotely deliver a physical activity intervention via a smartphone to older adults, or how acceptable older adults would find a JITAI targeting physical activity in everyday life. OBJECTIVE (1) to describe the development of “JITABug”, a personalised smartphone and activity tracker delivered JITAI designed to support older adults to increase or maintain their physical activity level; (2) to explore the acceptability of JITABug in a free-living setting, and (3) to assess the feasibility of conducting an effectiveness trial of the JITABug intervention. METHODS The intervention development process was underpinned by the Behaviour Change Wheel. The intervention consisted of a wearable activity tracker (Fitbit) and a companion smartphone app (JITABug) which delivered goal setting, planning, reminders, and just-in-time adaptive messages to encourage achievement of personalised physical activity goals. Message delivery was tailored based on time of day, real-time physical activity tracker data, and weather conditions. We tested the feasibility of remotely delivering the JITAI with older adults in a 6-week trial using a mixed-methods approach. Data collection involved assessment of physical activity by accelerometery and activity tracker, self-reported mood and mental wellbeing via ecological momentary assessment, and contextual information on physical activity via voice memos. Feasibility and acceptability outcomes included: (1) recruitment capability and adherence to the intervention; (2) intervention delivery ‘in the wild’; (3) appropriateness of data collection methodology; (4) adverse events and; (5) participant satisfaction. RESULTS Of 46 recruited older adults (aged 56-72 years old), 65% completed the intervention. The intervention was successfully delivered as intended; 27 participants completed the intervention independently, 94% of physical activity messages were successfully delivered, and 99% of Fitbit and 100% of weather data calls were successful. Wrist-worn accelerometer data were obtained from 96% at baseline and 96% at follow up. On average, participants recorded 8/16 (50%) voice memos, 3/8 (38%) mood assessments, and 2/4 (50%) wellbeing assessments via the app. Overall acceptability of the intervention was very good (77% satisfaction). Participant feedback suggested that more diverse and tailored physical activity messages, app usage reminders, technical refinements regarding real-time data syncing, and an improved user interface could improve the intervention and make it more appealing. CONCLUSIONS This study suggests that a smartphone delivered JITAI utilizing a wearable activity tracker is an acceptable way to support physical activity in older adults in the community. Overall, the intervention is feasible, however based on user feedback, the JITABug app requires further technical refinements that may enhance usage, engagement, and user satisfaction before moving to effectiveness trials. CLINICALTRIAL Non-Applicable

scholarly journals Quantified Kinematics to Evaluate Patient Chemotherapy Risks in Clinic

2020 ◽  
pp. 583-601
Author(s):  
Zaki Hasnain ◽  
Tanachat Nilanon ◽  
Ming Li ◽  
Aaron Mejia ◽  
Anand Kolatkar ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Care ◽  
Motion Capture ◽  
Performance Status ◽  
Area Under The Curve ◽  
The United States ◽  
Clinic Visit ◽  
Activity Levels ◽  
Health Care Encounters ◽  
The Right

PURPOSE Performance status (PS) is a key factor in oncologic decision making, but conventional scales used to measure PS vary among observers. Consumer-grade biometric sensors have previously been identified as objective alternatives to the assessment of PS. Here, we investigate how one such biometric sensor can be used during a clinic visit to identify patients who are at risk for complications, particularly unexpected hospitalizations that may delay treatment or result in low physical activity. We aim to provide a novel and objective means of predicting tolerability to chemotherapy. METHODS Thirty-eight patients across three centers in the United States who were diagnosed with a solid tumor with plans for treatment with two cycles of highly emetogenic chemotherapy were included in this single-arm, observational prospective study. A noninvasive motion-capture system quantified patient movement from chair to table and during the get-up-and-walk test. Activity levels were recorded using a wearable sensor over a 2-month period. Changes in kinematics from two motion-capture data points pre- and post-treatment were tested for correlation with unexpected hospitalizations and physical activity levels as measured by a wearable activity sensor. RESULTS Among 38 patients (mean age, 48.3 years; 53% female), kinematic features from chair to table were the best predictors for unexpected health care encounters (area under the curve, 0.775 ± 0.029) and physical activity (area under the curve, 0.830 ± 0.080). Chair-to-table acceleration of the nonpivoting knee ( t = 3.39; P = .002) was most correlated with unexpected health care encounters. Get-up-and-walk kinematics were most correlated with physical activity, particularly the right knee acceleration ( t = −2.95; P = .006) and left arm angular velocity ( t = −2.4; P = .025). CONCLUSION Chair-to-table kinematics are good predictors of unexpected hospitalizations, whereas the get-up-and-walk kinematics are good predictors of low physical activity.

scholarly journals An Activity Tracker–Guided Physical Activity Program for Patients Undergoing Radiotherapy: Protocol for a Prospective Phase III Trial (OnkoFit I and II Trials)

10.2196/28524 ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. e28524
Author(s):  
Franziska Hauth ◽  
Barbara Gehler ◽  
Andreas Michael Nieß ◽  
Katharina Fischer ◽  
Andreas Toepell ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Functional Assessment ◽  
Exercise Program ◽  
Daily Step ◽  
Patients With Cancer ◽  
Activity Tracker ◽  
Cancer Related Fatigue ◽  
Daily Step Count

Background The positive impact that physical activity has on patients with cancer has been shown in several studies over recent years. However, supervised physical activity programs have several limitations, including costs and availability. Therefore, our study proposes a novel approach for the implementation of a patient-executed, activity tracker–guided exercise program to bridge this gap. Objective Our trial aims to investigate the impact that an activity tracker–guided, patient-executed exercise program for patients undergoing radiotherapy has on cancer-related fatigue, health-related quality of life, and preoperative health status. Methods Patients receiving postoperative radiotherapy for breast cancer (OnkoFit I trial) or neoadjuvant, definitive, or postoperative treatment for other types of solid tumors (OnkoFit II trial) will be randomized (1:1:1) into 3-arm studies. Target accrual is 201 patients in each trial (50 patients per year). After providing informed consent, patients will be randomized into a standard care arm (arm A) or 1 of 2 interventional arms (arms B and C). Patients in arms B and C will wear an activity tracker and record their daily step count in a diary. Patients in arm C will receive personalized weekly targets for their physical activity. No further instructions will be given to patients in arm B. The target daily step goals for patients in arm C will be adjusted weekly and will be increased by 10% of the average daily step count of the past week until they reach a maximum of 6000 steps per day. Patients in arm A will not be provided with an activity tracker. The primary end point of the OnkoFit I trial is cancer-related fatigue at 3 months after the completion of radiotherapy. This will be measured by the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire. For the OnkoFit II trial, the primary end point is the overall quality of life, which will be assessed with the Functional Assessment of Cancer Therapy-General sum score at 6 months after treatment to allow for recovery after possible surgery. In parallel, blood samples from before, during, and after treatment will be collected in order to assess inflammatory markers. Results Recruitment for both trials started on August 1, 2020, and to date, 49 and 12 patients have been included in the OnkoFit I and OnkoFit II trials, respectively. Both trials were approved by the institutional review board prior to their initiation. Conclusions The OnkoFit trials test an innovative, personalized approach for the implementation of an activity tracker–guided training program for patients with cancer during radiotherapy. The program requires only a limited amount of resources. Trial Registration ClinicalTrials.gov NCT04506476; https://clinicaltrials.gov/ct2/show/NCT04506476. ClinicalTrials.gov NCT04517019; https://clinicaltrials.gov/ct2/show/NCT04517019. International Registered Report Identifier (IRRID) DERR1-10.2196/28524

scholarly journals Using a consumer-based wearable activity tracker for physical activity goal setting and measuring steps in pregnant women with gestational diabetes mellitus: exploring acceptance and validity

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Samantha F. Ehrlich ◽  
Jill M. Maples ◽  
Cristina S. Barroso ◽  
Kathleen C. Brown ◽  
David R. Bassett ◽  
...  
Keyword(s):  
Physical Activity ◽  
Gestational Diabetes ◽  
Goal Setting ◽  
Equivalence Testing ◽  
Structured Interviews ◽  
Self Monitoring ◽  
Activity Tracker ◽  
Wearable Activity Tracker ◽  
Stepping In Place ◽  
Monitoring Devices

Abstract Background Activity monitoring devices may be used to facilitate goal-setting, self-monitoring, and feedback towards a step-based physical activity (PA) goal. This study examined the performance of the wrist-worn Fitbit Charge 3™ (FC3) and sought opinions on walking and stepping-in-place from women with gestational diabetes (GDM). Methods Participants completed six 2-min metronome-assisted over ground bouts that varied by cadence (67, 84, or 100 steps per minute) and mode (walking or stepping-in-place; N = 15), with the sequence randomized. Steps were estimated by FC3 and measured, in duplicate, by direct observation (hand-tally device, criterion). Equivalence testing by the two one-sided tests (TOST) method assessed agreement within ± 15%. Mean absolute percent error (MAPE) of steps were compared to 10%, the accuracy standard of the Consumer Technology Association (CTA)™. A subset (n = 10) completed a timed, 200-m self-paced walk to assess natural walking pace and cadence. All participants completed semi-structured interviews, which were transcribed and analyzed using descriptive and interpretive coding. Results Mean age was 27.0 years (SD 4.2), prepregnancy BMI 29.4 kg/m2 (8.3), and gestational age 32.8 weeks (SD 2.6). The FC3 was equivalent to hand-tally for bouts of metronome-assisted walking and stepping-in-place at 84 and 100 steps per minute (i.e., P < .05), although walking at 100 steps per minute (P = .01) was no longer equivalent upon adjustment for multiple comparisons (i.e., at P < .007). The FC3 was equivalent to hand-tally during the 200-m walk (i.e., P < .001), in which mean pace was 68.2 m per minute (SD 10.7), or 2.5 miles per hour, and mean cadence 108.5 steps per minute (SD 6.5). For walking at 84 and 100 steps per minute, stepping-in-place at 100 steps per minute, and the 200-m walk, MAPE was within 10%, the accuracy standard of the CTA™. Interviews revealed motivation for PA, that stepping-in-place was an acceptable alternative to walking, and competing responsibilities made it difficult to find time for PA. Conclusions The FC3 appears to be a valid step counter during the third trimester, particularly when walking or stepping-in-place at or close to women’s preferred cadence.

scholarly journals Sustaining Physical Activity Following Cardiac Rehabilitation Discharge

2021 ◽  
Author(s):  
Kelly R. Evenson ◽  
Ty A. Ridenour ◽  
Jacqueline Bagwell ◽  
Robert D. Furberg
Keyword(s):  
Physical Activity ◽  
Cardiac Rehabilitation ◽  
Mixed Model ◽  
Final Report ◽  
Activity Tracking ◽  
Intervention Effect ◽  
Activity Tracker ◽  
History Information ◽  
Rigorous Study ◽  
Model Trajectory

Because many patients reduce exercise following outpatient cardiac rehabilitation (CR), we developed an intervention to assist with the transition and evaluated its feasibility and preliminary efficacy using a one-group pretest–posttest design. Five CR patients were enrolled ~1 month prior to CR discharge and provided an activity tracker. Each week during CR they received a summary of their physical activity and steps. Following CR discharge, participants received an individualized report that included their physical activity and step history, information on specific features of the activity tracker, and encouraging messages from former CR patients for each of the next 6 weeks. Mixed model trajectory analyses were used to test the intervention effect separately for active minutes and steps modeling three study phases: pre-intervention (day activity tracking began to CR discharge), intervention (day following CR discharge to day when final report sent), and maintenance (day following the final report to ~1 month later). Activity tracking was successfully deployed and, with weekly reports following CR, may offset the usual decline in physical activity. When weekly reports ceased, a decline in steps/day occurred. A scaled-up intervention with a more rigorous study design with sufficient sample size can evaluate this approach further.

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