scholarly journals Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial (Preprint)

2018 ◽  
Author(s):  
Jan-Niklas Kramer ◽  
Florian Künzler ◽  
Varun Mishra ◽  
Bastien Presset ◽  
David Kotz ◽  
...  
Keyword(s):  
Physical Activity ◽  
Financial Incentive ◽  
Primary Objective ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Insurance Company ◽  
Intervention Period ◽  
Incentive Condition ◽  
Self Monitoring ◽  
Smartphone Sensor

BACKGROUND Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Using machine learning techniques to infer each user’s context from smartphone sensor data is a promising approach to further enhance tailoring. OBJECTIVE The primary objective of this study is to quantify main effects, interactions, and moderators of 3 intervention components of a smartphone-based intervention for physical activity. The secondary objective is the exploration of participants’ states of receptivity, that is, situations in which participants are more likely to react to intervention notifications through collection of smartphone sensor data. METHODS In 2017, we developed the Assistant to Lift your Level of activitY (Ally), a chatbot-based mobile health intervention for increasing physical activity that utilizes incentives, planning, and self-monitoring prompts to help participants meet personalized step goals. We used a microrandomized trial design to meet the study objectives. Insurees of a large Swiss insurance company were invited to use the Ally app over a 12-day baseline and a 6-week intervention period. Upon enrollment, participants were randomly allocated to either a financial incentive, a charity incentive, or a no incentive condition. Over the course of the intervention period, participants were repeatedly randomized on a daily basis to either receive prompts that support self-monitoring or not and on a weekly basis to receive 1 of 2 planning interventions or no planning. Participants completed a Web-based questionnaire at baseline and postintervention follow-up. RESULTS Data collection was completed in January 2018. In total, 274 insurees (mean age 41.73 years; 57.7% [158/274] female) enrolled in the study and installed the Ally app on their smartphones. Main reasons for declining participation were having an incompatible smartphone (37/191, 19.4%) and collection of sensor data (35/191, 18.3%). Step data are available for 227 (82.8%, 227/274) participants, and smartphone sensor data are available for 247 (90.1%, 247/274) participants. CONCLUSIONS This study describes the evidence-based development of a JITAI for increasing physical activity. If components prove to be efficacious, they will be included in a revised version of the app that offers scalable promotion of physical activity at low cost. CLINICALTRIAL ClinicalTrials.gov NCT03384550; https://clinicaltrials.gov/ct2/show/NCT03384550 (Archived by WebCite at http://www.webcitation.org/74IgCiK3d) INTERNATIONAL REGISTERED REPOR DERR1-10.2196/11540

Evaluating the Feasibility, Acceptability, and Effects of Deposit Contracts With and Without Daily Feedback to Promote Physical Activity

2020 ◽  
Vol 17 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Stephanie G. Kerrigan ◽  
Evan M. Forman ◽  
Mitesh Patel ◽  
Dave Williams ◽  
Fengqing Zhang ◽  
...  
Keyword(s):  
Physical Activity ◽  
Financial Incentive ◽  
Presentation Order ◽  
Effect Sizes ◽  
Financial Reward ◽  
Self Monitoring ◽  
Modest Increase ◽  
Incentive Programs ◽  
Deposit Contracts ◽  
Objectively Measured

Background: Despite interest in financial incentive programs, evidence regarding the feasibility, acceptability, and effectiveness of deposit contracts (ie, use of participants’ own money as a financial reward) for increasing physical activity (PA) is limited. Furthermore, evidence regarding the use of feedback within incentive programs is limited. Purpose: To evaluate: (1) the feasibility and acceptability of deposit contracts for increasing objectively measured PA and (2) the effects of deposit contracts with or without ongoing feedback on PA. Methods: Participants (n = 24) were exposed to 3 conditions (1) self-monitoring, (2) incentive, and (3) incentive with feedback in an ABACABAC design, with the order of incentive conditions counterbalanced across participants. Results: Effect sizes suggest that individuals had a modest increase in PA during the incentive conditions compared with self-monitoring. Presentation order moderated results, such that individuals exposed to incentives with feedback first performed more poorly across both incentive conditions. In addition, individuals often cited the deposit contract as a reason for not enrolling, and those who did participate reported inadequate acceptability of the incentives and feedback. Conclusions: Results suggest that while deposit contracts may engender modest increases in PA, this type of incentive may not be feasible or acceptable for promoting PA.

scholarly journals Effects of Intervention Characteristics on Willingness to Initiate a Weight Gain Prevention Program

2020 ◽  
Vol 34 (8) ◽  
pp. 837-847
Author(s):  
Megan A. McVay ◽  
Marissa L. Donahue ◽  
JeeWon Cheong ◽  
Joseph Bacon ◽  
Michael G. Perri ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Gain ◽  
Financial Incentives ◽  
Program Effectiveness ◽  
Financial Incentive ◽  
Prevention Programs ◽  
Weight Gain Prevention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention

Purpose: To determine characteristics of weight gain prevention programs that facilitate engagement. Design: Randomized factorial experiment (5 × 2). Setting: Recruited nationally online. Participants: Adults aged 18 to 75 with body mass index ≥25 who decline a behavioral weight loss intervention (n = 498). Measures: Participants were randomly presented with one of 10 possible descriptions of hypothetical, free weight gain prevention programs that were all low dose and technology-based but differed in regard to 5 behavior change targets (self-weighing only; diet only; physical activity only; combined diet, physical activity, and self-weighing; or choice between diet, physical activity, and self-weighing targets) crossed with 2 financial incentive conditions (presence or absence of incentives for self-monitoring). Participants reported willingness to join the programs, perceived program effectiveness, and reasons for declining enrollment. Analysis: Logistic regression and linear regression to test effects of program characteristics offered on willingness to initiate programs and programs’ perceived effectiveness, respectively. Content analyses for open-ended text responses. Results: Participants offered the self-weighing-only programs were more willing to initiate than those offered the programs targeting all 3 behaviors combined (50% vs 36%; odds ratio [OR] = 1.79; 95% confidence interval [CI], 1.01-3.13). Participants offered the programs with financial incentives were more willing to initiate (50% vs 33%; OR = 2.08; 95% CI, 1.44-2.99) and anticipated greater intervention effectiveness (β = .34, P = .02) than those offered no financial incentives. Reasons for declining to initiate included specific program features, behavior targets, social aspects, and benefits. Conclusion: Targeting self-weighing and providing financial incentives for self-monitoring may result in greater uptake of weight gain prevention programs. Study Preregistration: https://osf.io/b9zfh , June 19, 2018.

scholarly journals Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial

2020 ◽  
Vol 54 (7) ◽  
pp. 518-528 ◽  
Author(s):  
Jan-Niklas Kramer ◽  
Florian Künzler ◽  
Varun Mishra ◽  
Shawna N Smith ◽  
David Kotz ◽  
...  
Keyword(s):  
Physical Activity ◽  
Action Planning ◽  
Goal Achievement ◽  
Control Group ◽  
Insurance Company ◽  
Daily Step ◽  
Self Monitoring ◽  
Coping Planning ◽  
Cash Incentives ◽  
Study Participants

Abstract Background The Assistant to Lift your Level of activitY (Ally) app is a smartphone application that combines financial incentives with chatbot-guided interventions to encourage users to reach personalized daily step goals. Purpose To evaluate the effects of incentives, weekly planning, and daily self-monitoring prompts that were used as intervention components as part of the Ally app. Methods We conducted an 8 week optimization trial with n = 274 insurees of a health insurance company in Switzerland. At baseline, participants were randomized to different incentive conditions (cash incentives vs. charity incentives vs. no incentives). Over the course of the study, participants were randomized weekly to different planning conditions (action planning vs. coping planning vs. no planning) and daily to receiving or not receiving a self-monitoring prompt. Primary outcome was the achievement of personalized daily step goals. Results Study participants were more active and healthier than the general Swiss population. Daily cash incentives increased step-goal achievement by 8.1%, 95% confidence interval (CI): [2.1, 14.1] and, only in the no-incentive control group, action planning increased step-goal achievement by 5.8%, 95% CI: [1.2, 10.4]. Charity incentives, self-monitoring prompts, and coping planning did not affect physical activity. Engagement with planning interventions and self-monitoring prompts was low and 30% of participants stopped using the app over the course of the study. Conclusions Daily cash incentives increased physical activity in the short term. Planning interventions and self-monitoring prompts require revision before they can be included in future versions of the app. Selection effects and engagement can be important challenges for physical-activity apps. Clinical Trial Information This study was registered on ClinicalTrials.gov, NCT03384550.

Binary Spectrum Feature for Improved Classifier Performance

2020 ◽  
Author(s):  
Nalika Ulapane ◽  
Karthick Thiyagarajan ◽  
sarath kodagoda
Keyword(s):  
Machine Learning ◽  
Classification Performance ◽  
Feature Reduction ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Svm Classifier ◽  
Monitoring Task ◽  
Classifier Performance ◽  
Spectrum Feature

<div>Classification has become a vital task in modern machine learning and Artificial Intelligence applications, including smart sensing. Numerous machine learning techniques are available to perform classification. Similarly, numerous practices, such as feature selection (i.e., selection of a subset of descriptor variables that optimally describe the output), are available to improve classifier performance. In this paper, we consider the case of a given supervised learning classification task that has to be performed making use of continuous-valued features. It is assumed that an optimal subset of features has already been selected. Therefore, no further feature reduction, or feature addition, is to be carried out. Then, we attempt to improve the classification performance by passing the given feature set through a transformation that produces a new feature set which we have named the “Binary Spectrum”. Via a case study example done on some Pulsed Eddy Current sensor data captured from an infrastructure monitoring task, we demonstrate how the classification accuracy of a Support Vector Machine (SVM) classifier increases through the use of this Binary Spectrum feature, indicating the feature transformation’s potential for broader usage.</div><div><br></div>

scholarly journals Ablation Analysis to Select Wearable Sensors for Classifying Standing, Walking, and Running

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 194
Author(s):  
Sarah Gonzalez ◽  
Paul Stegall ◽  
Harvey Edwards ◽  
Leia Stirling ◽  
Ho Chit Siu
Keyword(s):  
Activity Recognition ◽  
Principal Components ◽  
Classification Accuracy ◽  
Wearable Sensors ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Learning Techniques ◽  
Measurement Units ◽  
The Difference

The field of human activity recognition (HAR) often utilizes wearable sensors and machine learning techniques in order to identify the actions of the subject. This paper considers the activity recognition of walking and running while using a support vector machine (SVM) that was trained on principal components derived from wearable sensor data. An ablation analysis is performed in order to select the subset of sensors that yield the highest classification accuracy. The paper also compares principal components across trials to inform the similarity of the trials. Five subjects were instructed to perform standing, walking, running, and sprinting on a self-paced treadmill, and the data were recorded while using surface electromyography sensors (sEMGs), inertial measurement units (IMUs), and force plates. When all of the sensors were included, the SVM had over 90% classification accuracy using only the first three principal components of the data with the classes of stand, walk, and run/sprint (combined run and sprint class). It was found that sensors that were placed only on the lower leg produce higher accuracies than sensors placed on the upper leg. There was a small decrease in accuracy when the force plates are ablated, but the difference may not be operationally relevant. Using only accelerometers without sEMGs was shown to decrease the accuracy of the SVM.

scholarly journals The Acceptability, Feasibility and Effectiveness of Wearable Activity Trackers for Increasing Physical Activity in Children and Adolescents: A Systematic Review

2021 ◽  
Vol 18 (12) ◽  
pp. 6211
Author(s):  
Amy V. Creaser ◽  
Stacy A. Clemes ◽  
Silvia Costa ◽  
Jennifer Hall ◽  
Nicola D. Ridgers ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Children And Adolescents ◽  
Behaviour Change Techniques ◽  
Physically Active ◽  
Self Monitoring ◽  
Start Date ◽  
Activity Trackers ◽  
Wearable Activity Trackers

Wearable activity trackers (wearables) embed numerous behaviour change techniques (BCTs) that have previously been shown to increase adult physical activity (PA). With few children and adolescents achieving PA guidelines, it is crucial to explore ways to increase their PA. This systematic review examined the acceptability, feasibility, and effectiveness of wearables and their potential mechanisms of action for increasing PA in 5 to 19-year-olds. A systematic search of six databases was conducted, including data from the start date of each database to December 2019 (PROSPERO registration: CRD42020164506). Thirty-three studies were included. Most studies (70%) included only adolescents (10 to 19 years). There was some—but largely mixed—evidence that wearables increase steps and moderate-to-vigorous-intensity PA and reduce sedentary behaviour. There were no apparent differences in effectiveness based on the number of BCTs used and between studies using a wearable alone or as part of a multi-component intervention. Qualitative findings suggested wearables increased motivation to be physically active via self-monitoring, goal setting, feedback, and competition. However, children and adolescents reported technical difficulties and a novelty effect when using wearables, which may impact wearables’ long-term use. More rigorous and long-term studies investigating the acceptability, feasibility, and effectiveness of wearables in 5 to 19-year-olds are warranted.

scholarly journals Effects of the Active Kids voucher program on children and adolescents’ physical activity: a natural experiment evaluating a state-wide intervention

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bridget C. Foley ◽  
Katherine B. Owen ◽  
Adrian E. Bauman ◽  
William Bellew ◽  
Lindsey J. Reece
Keyword(s):  
Physical Activity ◽  
Children And Adolescents ◽  
Online Survey ◽  
Specific Activity ◽  
Financial Incentive ◽  
Trial Registration ◽  
Physical Activity Participation ◽  
Activity Participation ◽  
Clinical Trial Registry ◽  
Voucher Program

Abstract Background There is an urgent need for scaled-up effective interventions which overcome barriers to health-enhancing physical activity for children and adolescents. In New South Wales (NSW), Australia, the state government implemented a universal voucher program, ‘Active Kids’ to support the cost of structured physical activity registration for school-enrolled children aged 4.5–18 years old. The objective of this study was to understand the effects a financial incentive intervention delivered in a real-world setting has on children and adolescent’s physical activity participation. Method In 2018, all children and adolescents registered for an Active Kids voucher provided sociodemographic characteristics, physical activity and research consent. This prospective cohort study used an online survey with validated items to measure physical activity and other personal and social factors in children and adolescents who used an Active Kids voucher. Generalized linear mixed models were used to examine changes from registration to after voucher use at ≤8 weeks, 9–26 weeks and ≥ 6 months. Results Study participants reported increasing their days achieving physical activity guidelines from 4.0 days per week (95%CI 3.8, 4.2) at registration (n = 37,626 children) to 4.9 days per week (95%CI 4.7, 5.1) after 6 months (n = 14,118 children). Increased physical activity was observed for all sociodemographic population groups. The voucher-specific activity contributed 42.4% (95%CI 39.3, 45.5) to the total time children participated in structured physical activities outside of school. Children and adolescents who increased to, or maintained, high levels of activity were socially supported to be active, had active parent/caregivers, had better concentration and were overall happier than their low-active counterparts. Conclusion The Active Kids program significantly increased children’s physical activity levels and these increases continued over a six-month period. The Active Kids voucher program shows promise as a scaled-up intervention to increase children and adolescents’ physical activity participation. Trial registration Australian New Zealand Clinical Trial Registry ACTRN12618000897268, approved May 29th, 2018 - Retrospectively registered.

scholarly journals Effectiveness of a low-value financial-incentive program for increasing vegetable-rich restaurant meal selection and reducing socioeconomic inequality: a cluster crossover trial

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Wataru Nagatomo ◽  
Junko Saito ◽  
Naoki Kondo
Keyword(s):  
Intervention Program ◽  
Crossover Trial ◽  
Financial Incentive ◽  
Control Period ◽  
Healthy Food ◽  
Intervention Period ◽  
Marginal Value ◽  
Percentage Point Increase ◽  
Point Increase ◽  
Proxy Measure

Abstract Background In light of recent theories in behavioural economics, an intervention program with monetary incentives could be effective for helping patrons order healthy food, even if the incentive is small and less than one’s perceived marginal value. Methods In this single-arm cluster crossover trial at 26 local restaurants, a 1-week campaign offered a 50-yen (approximately 0.5 US dollars) cash-back payment to customers ordering vegetable-rich meals, while no pre-order incentives were offered during the control period. Results In total, 511 respondents out of 7537 customers (6.8%), and 704 respondents out of 7826 customers (9.0%), ordered vegetable-rich meals during the control and intervention periods, respectively. During the intervention period, the covariate-adjusted proportion of vegetable-rich meal orders was 1.50 times higher (95% confidence interval [CI]: 1.29 to 1.75), which increased daily sales by 1.77 times (95% CI: 1.11 to 2.83), even when subtracting the cost of cash-back payments. Respondents who reported spending the least amount of money on eating out (used as a proxy measure for income) were the least likely to order vegetable-rich meals during the control period. However, these individuals increased their proportion of purchasing such meals during the intervention period (a 3.8 percentage point increase (95% CI: 2.82 to 4.76) among those spending the least vs a 2.1 percentage point increase (95% CI: 1.66 to 2.62) among those spending the most; P for interaction = 0.001). Similarly, irregular employees exhibited a larger increase (+ 5.2 percentage points, 95% CI: 4.54 to 5.76) than did regular workers (− 1.4, 95% CI: − 1.66 to − 1.05, P for interaction = 0.001). Conclusions A program with an immediate low-value monetary incentive could be a public health measure for reducing inequalities in making healthy food choices. Trial registration UMIN Clinical Trials Registry, UMIN000022396. Registered 21 May 2016.

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