scholarly journals Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial (Preprint)

2017 ◽  
Author(s):  
Ahmed Hassoon ◽  
Jennifer Schrack ◽  
Daniel Naiman ◽  
Dina Lansey ◽  
Yasmin Baig ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cancer Survivors ◽  
Text Message ◽  
Intelligent Agent ◽  
Data Driven ◽  
Artificial Intelligence Technology ◽  
Intelligent Technology ◽  
Using Data ◽  
Assist Intervention ◽  
Written Materials

BACKGROUND Physical activity has established health benefits, but motivation and adherence remain challenging. OBJECTIVE We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. METHODS A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). RESULTS The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. DISCUSSION This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. CLINICALTRIAL Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji)

scholarly journals Randomized trial of two artificial intelligence coaching interventions to increase physical activity in cancer survivors

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ahmed Hassoon ◽  
Yasmin Baig ◽  
Daniel Q. Naiman ◽  
David D. Celentano ◽  
Dina Lansey ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cancer Survivors ◽  
Randomized Trial ◽  
Breast Cancer Survivors ◽  
Text Message ◽  
Practical Method ◽  
Voice Technology ◽  
Steps Per Day ◽  
Change In Mean

AbstractPhysical activity (PA) has numerous health benefits. Personalized coaching may increase adherence to PA recommendations, but it is challenging to deliver personalized coaching in a scalable manner. The objective of our study was to determine whether novel artificially intelligent (AI) coaching interventions increase PA among overweight or obese, physically inactive cancer survivors compared to a control arm that receives health information. We conducted a single-center, three-arm randomized trial with equal allocation to (1) voice-assisted AI coaching delivered by smart speaker (MyCoach), (2) autonomous AI coaching delivered by text message (SmartText), and (3) control. Data collection was automated via sensors and voice technology, effectively masking outcome ascertainment. The primary outcome was change in mean steps per day from baseline to the end of follow-up at 4 weeks. Of the 42 randomized participants, 91% were female, and 36% were Black; mean age was 62.1 years, and mean BMI was 32.9 kg/m2. The majority were breast cancer survivors (85.7%). At the end of 4 weeks follow-up, steps increased in the MyCoach arm by an average of 3618.2 steps/day; the net gain in this arm was significantly greater [net difference = 3568.9 steps/day (95% CI: 1483–5655), P value <0.001] compared to control arm, and [net difference = 2160.6 steps/day (95% CI: 11–4310), P value 0.049] compared to SmartText. In conclusion, AI-based voice-assisted coaching shows promise as a practical method of delivering scalable, individualized coaching to increase physical activity in sedentary cancer survivors. Additional research is needed to replicate these findings in a broader population of cancer survivors and to investigate the effects of these interventions in the general population.ClinicalTrials.gov Identifier: NCT03212079, July 11, 2017, https://clinicaltrials.gov/ct2/show/NCT03212079.

scholarly journals Mediating Effects of Frailty Indicators on the Risk of Sepsis After Cancer

2018 ◽  
Vol 35 (7) ◽  
pp. 708-719 ◽  
Author(s):  
Justin Xavier Moore ◽  
Tomi Akinyemiju ◽  
Alfred Bartolucci ◽  
Henry E. Wang ◽  
John Waterbor ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cancer Survivors ◽  
Racial Differences ◽  
Cancer Survivorship ◽  
Cox Regression ◽  
Mediation Effect ◽  
Cancer History ◽  
Mediation Effects ◽  
Increased Risk ◽  
Using Data

Background: Cancer survivors are at increased risk of sepsis, possibly attributed to weakened physiologic conditions. The aims of this study were to examine the mediation effect of indicators of frailty on the association between cancer survivorship and sepsis incidence and whether these differences varied by race. Methods: We performed a prospective analysis using data from the REasons for Geographic and Racial Differences in Stroke cohort from years 2003 to 2012. We categorized frailty as the presence of ≥2 frailty components (weakness, exhaustion, and low physical activity). We categorized participants as “cancer survivors” or “no cancer history” derived from self-reported responses of being diagnosed with any cancer. We examined the mediation effect of frailty on the association between cancer survivorship and sepsis incidence using Cox regression. We repeated analysis stratified by race. Results: Among 28 062 eligible participants, 2773 (9.88%) were cancer survivors and 25 289 (90.03%) were no cancer history participants. Among a total 1315 sepsis cases, cancer survivors were more likely to develop sepsis (12.66% vs 3.81%, P < .01) when compared to participants with no cancer history (hazard ratios: 2.62, 95% confidence interval: 2.31-2.98, P < .01). The mediation effects of frailty on the log-hazard scale were very small: weakness (0.57%), exhaustion (0.31%), low physical activity (0.20%), frailty (0.75%), and total number of frailty indicators (0.69%). Similar results were observed when stratified by race. Conclusion: Cancer survivors had more than a 2-fold increased risk of sepsis, and indicators of frailty contributed to less than 1% of this disparity.

Text messaging and activity tracker motivation program to increase physical activity in cancer survivors.

2018 ◽  
Vol 36 (7_suppl) ◽  
pp. 92-92
Author(s):  
Bridget F. Koontz ◽  
Erica Levine ◽  
Frances McSherry ◽  
Tykeytra Dale ◽  
Martin Streicher ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cancer Survivors ◽  
Text Messaging ◽  
Text Message ◽  
Application Programming Interface ◽  
Feedback System ◽  
Activity Level ◽  
Step Count ◽  
Activity Tracker ◽  
Application Programming

92 Background: Cancer survivors have high rates of sedentary behavior leading to obesity and cardiovascular disease. Physical activity improves quality of life (QOL) and reduces morbidity and mortality. However, cancer survivors commonly cite motivation as a barrier to increasing physical activity. We hypothesized that a motivational text-messaging feedback system linked to a Fitbit Flex activity tracker would increase the activity level of survivors and those undergoing cancer treatment. Methods: 29 participants were enrolled in an IRB-approved single-institution study. Eligibility allowed any cancer/stage, ≤2 days of exercise per week, life expectancy of 12+ months, and smartphone access. After baseline fitness/QOL testing, participants were provided a Fitbit Flex activity tracker. A text-messaging program automatically uploaded data from the tracker via an application programming interface and provided personalized text message feedback to subject’s smartphone daily for 3 months. Primary endpoint was change in step count from baseline to 3 months, with additional endpoints of change in 6 minute walk/QOL measures at 3 months, and continued exercise/use of tracker at 6 months. Results: To date, 24 have completed the 3 month program. Both academic and community sites participated, including areas with limited internet access. Most participants were female (71%) and white (63%). Eight cancer types and all stages were represented. Three participants withdrew – one because of lost tracker, one cancer death, and one “disappointed” with tracker function. Median daily steps at baseline were 3773 (IQR 2928) and 4365 at 3 months (IQR 4864). 42% had at least a 20% increase in median step count at 3 months. Improvement was noted in 45% of survivors and 38% of active treatment participants. Participants frequently used research nurses for guidance on use of wearable tracker (e.g. syncing, charging, features). Conclusions: Activity tracker with personalized daily feedback via text message successfully motivates cancer patients to increase daily activity. Patients are interested in health technology, but require technical support and coaching to maintain use. Clinical trial information: NCT02627079.

A Nonlinear Data-Driven Model of Glucose Dynamics Accounting for Physical Activity for Type 1 Diabetes: An In Silico Study

2016 ◽  
Author(s):  
Jinyu Xie ◽  
Qian Wang
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Clinical Training ◽  
Time Series Data ◽  
Artificial Pancreas ◽  
Data Driven ◽  
Series Data ◽  
Data Sets ◽  
Using Data

Physical activity is an important physiological information which should be taken into account by artificial pancreas to achieve optimal control of blood glucose in Type 1 Diabetes patients. An accurate glucose dynamic model with physical activity as an additional input is highly desirable for the next generation artificial pancreas. In this paper, we present a nonlinear data-driven model that captures both the insulin-independent and -dependent effect of physical activity, especially the prolonged effect of physical activity on insulin sensitivity that can last 24–48 hours post exercise. The model was identified and validated using data sets generated by a physiological glucose-exercise model under a clinical training protocol. Compared to modeling the effect of physical activity as a linear additive term only in a glucose dynamic equation, the proposed nonlinear model showed significant improvement of prediction accuracy in all three metrics, particularly in large prediction horizons (P < 0.05). Further investigation in time-series data indicates that the improvement mainly resulted from the better prediction of glucose around the first meal time after exercise (6 to 8 hours after the meal was taken).

Physical activity, strength and weight management in breast cancer survivors

2013 ◽  
Author(s):  
Shannon L. Mihalko ◽  
Samantha E. Yocke ◽  
Greg Russell ◽  
Marissa Howard-McNatt ◽  
Edward A. Levine
Keyword(s):  
Breast Cancer ◽  
Physical Activity ◽  
Cancer Survivors ◽  
Weight Management ◽  
Breast Cancer Survivors
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