An adaptive physical activity intervention for overweight adults: a randomized controlled trial

The Impact of Monetary Incentives on Delay Discounting Within a Year-Long Physical Activity Intervention

BACKGROUND

Delay discounting is the depreciation in a reward's perceived value as a function of the time until receipt. Monetary incentive programs that provide rewards contingent on meeting daily physical activity (PA) goals may change participants' delay discounting preferences.

PURPOSE

Determine if monetary incentives provided in close temporal proximity to meeting PA goals changed delay discounting, and if such changes mediated intervention effects.

METHODS

Inactive adults (n = 512) wore accelerometers during a 12-month intervention where they received proximal monetary incentives for meeting daily moderate-to-vigorous PA (MVPA) goals or delayed incentives for study participation. Delay discount rate and average MVPA were assessed at baseline, end of intervention, and a 24-month follow-up. Using structural equation modeling, we tested effects of proximal versus delayed rewards on delay discounting and whether any changes mediated intervention effects on MVPA. PA self-efficacy was also evaluated as a potential mediator, and both self-efficacy and delay discounting were assessed as potential moderators of intervention effects.

RESULTS

Proximal rewards significantly increased participants' delay discounting (β = 0.238, confidence interval [CI]: -0.078, 0.380), indicating greater sensitivity to reinforcement timing. This change did not mediate incentive-associated increases in MVPA at the end of the 12-month intervention (β = -0.016, CI: -0.053, 0.019) or at a 24-month follow-up (β = -0.020, CI: -0.059, 0.018). Moderation effects were not found.

CONCLUSIONS

Incentive-induced increases in delay discounting did not deleteriously impact MVPA. This finding may help assuage concerns about using monetary incentives for PA promotion, but further research regarding the consequences of changes in delay discounting is warranted.

Examining a Remote Group-Based Type 2 Diabetes Self-Management Education Program in the COVID-19 Era Using the ORBIT Model: Small 6-Week Feasibility Study

BACKGROUND

To date, most group-based diabetes self-management education (DSME) programs for type 2 diabetes (T2D) have been delivered in person. The rapid transition to remote care at the outset of the COVID-19 pandemic presented opportunities to test, evaluate, and iterate a new remote DSME program.

OBJECTIVE

We aim to refine the delivery and evaluation of a multicomponent remote DSME program for adults living with T2D by examining several feasibility outcomes.

METHODS

We recruited a convenience sample of patients from a London, Canada, outpatient diabetes clinic (serving high-risk, low-income adults) to participate in a 6-week, single cohort feasibility study from November 2020 to March 2021. This small ORBIT phase 1b feasibility study represents the first in a planned series guided by the ORBIT model for developing behavioral interventions for chronic diseases (phase 1: design; phase 2: preliminary testing; phase 3: efficacy; and phase 4: effectiveness). The feasibility of delivering and evaluating a remote DSME program, including (1) live video education classes, (2) individualized physical activity (PA) prescription and counseling, and (3) intermittently scanned continuous glucose and wearable PA monitoring, was assessed. Feasibility outcomes included recruitment and retention rates, program adherence, and acceptability (ie, technology issues and exit survey feedback). PA was assessed with Fitbit Inspire 2 (Fitbit Inc) and estimated glycated hemoglobin (HbA1c) using the FreeStyle Libre (Abbot). Given the small study sample, group- and individual-level data are reported descriptively.

RESULTS

A total of 10 adults living with T2D were recruited (female 60%; age 49.9, SD 14.3 years; estimated HbA1c 6.2%, SD 0.5%). Recruitment and retention rates were 29% and 80%, respectively. Participants attended 83% (25/30) and 93% (37/40) of education classes and PA counseling phone calls, respectively. There were 3.2 (SD 2.6) technology issues reported per person, most of which were related to study data transfer. Exit survey responses suggest most participants (8/9, 89%) were "satisfied" with the program. Recognizing the small sample size and the fact that no inferential statistics were conducted, the mean (SD) for the weekly daily step count and estimated HbA1c are provided for illustrative purposes. Participants accumulated 7103 (SD 2900) and 7515 (SD 3169) steps per day at baseline and week 6, respectively. The estimated HbA1c was 6.2% (SD 0.5%) and 6.2% (SD 0.6%) at baseline and week 6, respectively.

CONCLUSIONS

This ORBIT phase 1b study served to refine the delivery (eg, automatic study data upload process recommended to reduce participant burden) and evaluation (eg, purposeful sampling of participants with baseline HbA1c >8% recommended to address selection bias) of a remote DSME program. Preliminary proof-of-concept testing (ORBIT phase 2) incorporating some of these learnings is now warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04498819; https://clinicaltrials.gov/study/NCT04498819.

Implementing a Sedentary Behavior Change Smartphone App in Cardiac Rehabilitation: A Qualitative Analysis Guided by the Theoretical Domains Framework and Capability, Opportunity, and Motivation-Behavior Model

BACKGROUND

Smartphone apps used in research offer a variety of capabilities to track and influence behavior; however, they often do not translate well into real-world use. Implementation strategies for using apps to reduce sedentary behavior in cardiac rehabilitation are currently unknown.

OBJECTIVE

The aim of this study was to explore (1) barriers and enablers for use of a behavioral smartphone app (Vire and ToDo-CR program) for reducing sedentary behavior in cardiac rehabilitation participants and (2) implementation strategies for future smartphone apps aimed at reducing sedentary behavior in this population.

METHODS

In-depth semistructured interviews were conducted with cardiac rehabilitation participants in the ToDo-CR randomized controlled trial. Participants had used the Vire app and a wearable activity tracker for 6 months. Interviews were audio recorded and transcribed. The researchers used thematic analysis and deductive mapping of themes to the Theoretical Domains Framework and the Capability, Opportunity, and Motivation-Behavior model. Sociodemographic and clinical variables were recorded.

RESULTS

Fifteen participants aged 59 ± 14 years were interviewed. Most were male, tertiary educated, and employed, and had varying experiences with smartphone apps and wearable activity trackers. Five core themes explaining the user experiences of cardiac rehabilitation participants with the Vire app were identified: (1) being tech savvy can be both an enabler and a barrier, (2) app messaging needs to be clear-set expectations from the beginning, (3) get to know me-personalization is important, (4) curious to know more instant feedback, and (5) first impression is key. The themes and subthemes mapped to 12 of the 14 Theoretical Domains Framework domains. Improving engagement and implementation of future smartphone apps for sedentary behavior may be aided by building psychological capability, physical opportunity, and reflective motivation.

CONCLUSIONS

Shifting to in-the-moment behavioral nudges, setting clear expectations, assisting participants to monitor their sitting time, increasing the frequency of tailoring, and understanding more about the participant as well as their experiences and needs for reducing sedentary behavior in cardiac rehabilitation are important future directions.

Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners

BACKGROUND

Mobile health (mHealth) interventions can deliver personalized behavioral support to users in daily contexts. These interventions have been increasingly adopted to support individuals who require low-cost and low-burden support. Prior research has demonstrated the feasibility and acceptability of an mHealth intervention app (CareQOL) designed for use with informal care partners. To further optimize the intervention delivery, we need to investigate how care partners, many of whom lack the time for self-care, react and act in response to different behavioral messages.

OBJECTIVE

The goal of this study was to understand the factors that impact care partners' decision-making and actions in response to different behavioral messages. Insights from this study will help optimize future tailored and personalized behavioral interventions.

METHODS

We conducted semistructured interviews with participants who had recently completed a 3-month randomized controlled feasibility trial of the CareQOL mHealth intervention app. Of the 36 participants from the treatment group of the randomized controlled trial, 23 (64%) participated in these interviews. To prepare for each interview, the team first selected representative behavioral messages (eg, targeting different health dimensions) and presented them to participants during the interview to probe their influence on participants' thoughts and actions. The time of delivery, self-reported perceptions of the day, and user ratings of a message were presented to the participants during the interviews to assist with recall.

RESULTS

The interview data showed that after receiving a message, participants took various actions in response to different messages. Participants performed suggested behaviors or adjusted them either immediately or in a delayed manner (eg, sometimes up to a month later). We identified 4 factors that shape the variations in user actions in response to different behavioral messages: uncertainties about the workload required to perform suggested behaviors, concerns about one's ability to routinize suggested behaviors, in-the-moment willingness and ability to plan for suggested behaviors, and overall capability to engage with the intervention.

CONCLUSIONS

Our study showed that care partners use mHealth behavioral messages differently regarding the immediacy of actions and the adaptation to suggested behaviors. Multiple factors influence people's perceptions and decisions regarding when and how to take actions. Future systems should consider these factors to tailor behavioral support for individuals and design system features to support the delay or adaptation of the suggested behaviors. The findings also suggest extending the assessment of user adherence by considering the variations in user actions on behavioral support (ie, performing suggested or adjusted behaviors immediately or in a delayed manner).

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/32842.

Process evaluation of Dulce Digital-Me: an adaptive mobile health (mHealth) intervention for underserved Hispanics with diabetes

Type 2 diabetes disproportionately impacts ethnic minorities and individuals from low socioeconomic status. Diabetes self-management education and support has been shown to improve clinical outcomes in these populations, and mobile health (mHealth) interventions can reduce barriers to access. Dulce Digital-Me (DD-Me) was developed to integrate adaptive mHealth technologies to enhance self-management and reduce disparities in the high-risk, underserved Hispanic population. The objective of the present study was to evaluate reach, adoption, and implementation of an mHealth diabetes self-management education and support intervention in this underrepresented population. The present analysis is a multimethod process evaluation using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. The study was effective in reaching a sample that was representative of the intended population; only modest but significant differences were observed in sex and age. The DD-Me health coach (HC) cited several important facilitators of intervention adoption, including outreach frequency and personalization, and the automated HC report. Implementation fidelity was high, with participants receiving >90% of intended interventions. Participants who received DD-Me with support from a HC were most engaged, suggesting utility and acceptability of integrating HCs with mHealth interventions. Perceptions of implementation among study participants were positive and consistent across study arms. This evaluation revealed the target population was successfully reached and engaged in the digital health interventions, which was implemented with high fidelity. Further studies should evaluate the efficacy and maintenance of the study following the RE-AIM model to determine whether this intervention warrants expansion to additional settings and populations.

The moderating impact of neighborhood walkability on mHealth interventions to increase moderate to vigorous physical activity for insufficiently active adults in a randomized trial

BACKGROUND

Ecological models suggest that interventions targeting specific behaviors are most effective when supported by the environment. This study prospectively examined the interactions between neighborhood walkability and an mHealth intervention in a large-scale, adequately powered trial to increase moderate-to-vigorous physical activity (MVPA).

METHODS

Healthy, insufficiently active adults (N = 512) were recruited purposefully from census block groups ranked on walkability (high/low) and socioeconomic status (SES, high/low). Participants were block-randomized in groups of four to WalkIT Arizona, a 12-month, 2 × 2 factorial trial evaluating adaptive versus static goal setting and immediate versus delayed financial reinforcement delivered via text messages. Participants wore ActiGraph GT9X accelerometers daily for one year. After recruitment, a walkability index was calculated uniquely for every participant using a 500-m street network buffer. Generalized linear mixed-effects hurdle models tested for interactions between walkability, intervention components, and phase (baseline vs. intervention) on: (1) likelihood of any (versus no) MVPA and (2) daily MVPA minutes, after adjusting for accelerometer wear time, neighborhood SES, and calendar month. Neighborhood walkability was probed at 5th, 25th, 50th, 75th, and 95th percentiles to explore the full range of effects.

RESULTS

Adaptive goal setting was more effective in increasing the likelihood of any MVPA and daily MVPA minutes, especially in lower walkable neighborhoods, while the magnitude of intervention effect declined as walkability increased. Immediate reinforcement showed a greater increase in any and daily MVPA compared to delayed reinforcement, especially relatively greater in higher walkable neighborhoods.

CONCLUSIONS

Results partially supported the synergy hypotheses between neighborhood walkability and PA interventions and suggest the potential of tailoring interventions to individuals' neighborhood characteristics.

TRIAL REGISTRATION

Preregistered at clinicaltrials.gov (NCT02717663).

Application of machine learning to discover interactions predictive of dietary lapses

The purpose of this study it to build a machine learning model to predict dietary lapses with comparable accuracy, sensitivity, and specificity to previous literature while recovering predictor interactions. The sample for the current study consisted of merged data from two separate studies of individuals with obesity/overweight (total N = 87). Participants completed six ecological momentary assessment surveys per day where they were asked about 16 risk factors of lapse and if they had lapsed from their dietary prescriptions since the previous survey. Alcohol consumption and self-efficacy were the most prevalent in the top 10 stable interactions. Alcohol consumption decreased the protective effect of self-efficacy, motivation, and planning. Higher planning predicted higher risk for lapse only when consuming alcohol. Low motivation, hunger, cravings, and lack of healthy food availability increased the protective effect of self-efficacy. Higher self-efficacy increased risk effect of positive mood and having recently eaten a meal on lapse. For individuals with lower levels of self-efficacy, planning increased the risk of lapse. Alcohol intake and self-efficacy interact with several variables to predict dietary lapses, and these interactions should be targeted in just-in-time adaptive interventions that deliver interventions for lapses.

The development of a family-based wearable intervention using behaviour change and co-design approaches: move and connect

BACKGROUND

Previous research has explored the effectiveness of wearable activity trackers (wearables) for increasing child physical activity (PA) levels, but there have been mixed results. The use of theoretical frameworks and co-design techniques are recognised ways of increasing an intervention's acceptability and effectiveness.

AIMS

This study aims to use co-design workshops and an evidence-based theoretical framework (the Behaviour Change Wheel) to develop a family-based PA intervention using wearables.

METHODS

Three stages of intervention development outlined by the Behaviour Change Wheel were used. Co-design workshops with seven families (11 parents and 12 children) and seven PA experts were conducted where stakeholders discussed how to overcome previously identified barriers to families being active and using wearables. This resulted in the intervention's components being developed, with each component's mechanisms of action (e.g. intervention functions and behaviour change techniques) being retrospectively identified.

RESULTS

The 'Move & Connect' intervention was developed, which targets family PA and wearable use. The intervention takes a flexible approach and includes eight components, including wearable devices (Fitbit Alta HR), support resources, an introductory workshop, collective challenges, goal setting and reviewing, engagement prompts, social support and health-related resources (e.g. educational videos). The intervention incorporates six intervention functions targeting PA and wearable use: education, training, modelling, persuasion, incentivisation and environmental restructuring and 24 behaviour change techniques, including goal setting, social comparison, feedback on behaviour and graded task.

CONCLUSIONS

This is the first known study to use an evidence-based framework and co-design to develop a family-based wearable intervention. The identification of the intervention's mechanisms of action will prove useful when implementing and evaluating the 'Move & Connect' intervention and allow researchers to replicate its components.

Increasing Engagement in the Electronic Framingham Heart Study: Factorial Randomized Controlled Trial

BACKGROUND

Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited.

OBJECTIVE

This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data.

METHODS

We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant's name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary).

RESULTS

Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%; P=.006), but no significant differences were observed for HR data transmission (212/324, 65.4% vs 209/327, 63.9%; P=.69). Personalized notifications were associated with increased BP and HR data transmission versus standard at 6 months (BP: 107/291, 36.8% vs 66/295, 22.4%; difference=14.4%, 95% CI 7.1- 21.7%; P<.001; HR: 186/281, 66.2% vs 158/281, 56.2%; difference=10%, 95% CI 2%-18%; P=.02). For BP and HR primary or secondary outcomes, there was no evidence of differences in data transmission for notifications sent on weekend versus weekday or morning versus evening.

CONCLUSIONS

Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019.

Detailed Versus Simplified Dietary Self-monitoring in a Digital Weight Loss Intervention Among Racial and Ethnic Minority Adults: Fully Remote, Randomized Pilot Study

BACKGROUND

Detailed self-monitoring (or tracking) of dietary intake is a popular and effective weight loss approach that can be delivered via digital tools, although engagement declines over time. Simplifying the experience of self-monitoring diet may counteract this decline in engagement. Testing these strategies among racial and ethnic minority groups is important as these groups are often disproportionately affected by obesity yet underrepresented in behavioral obesity treatment.

OBJECTIVE

In this 2-arm pilot study, we aimed to evaluate the feasibility and acceptability of a digital weight loss intervention with either detailed or simplified dietary self-monitoring.

METHODS

We recruited racial and ethnic minority adults aged ≥21 years with a BMI of 25 kg/m² to 45 kg/m² and living in the United States. The Pacific time zone was selected for a fully remote study. Participants received a 3-month stand-alone digital weight loss intervention and were randomized 1:1 to either the detailed arm that was instructed to self-monitor all foods and drinks consumed each day using the Fitbit mobile app or to the simplified arm that was instructed to self-monitor only red zone foods (foods that are highly caloric and of limited nutritional value) each day via a web-based checklist. All participants were instructed to self-monitor both steps and body weight daily. Each week, participants were emailed behavioral lessons, action plans, and personalized feedback. In total, 12 a priori benchmarks were set to establish feasibility, including outcomes related to reach, retention, and self-monitoring engagement (assessed objectively via digital tools). Acceptability was assessed using a questionnaire. Weight change was assessed using scales shipped to the participants' homes and reported descriptively.

RESULTS

The eligibility screen was completed by 248 individuals, of whom 38 (15.3%) were randomized, 18 to detailed and 20 to simplified. At baseline, participants had a mean age of 47.4 (SD 14.0) years and BMI of 31.2 (SD 4.8) kg/m². More than half (22/38, 58%) were identified as Hispanic of any race. The study retention rate was 92% (35/38) at 3 months. The detailed arm met 9 of 12 feasibility benchmarks, while the simplified arm met all 12. Self-monitoring engagement was moderate to high (self-monitoring diet: median of 49% of days for detailed, 97% for simplified; self-monitoring steps: 99% for detailed, 100% for simplified; self-monitoring weight: 67% for detailed, 80% for simplified). Participants in both arms reported high satisfaction, with 89% indicating that they would recommend the intervention. Weight change was -3.4 (95% CI -4.6 to -2.2) kg for detailed and -3.3 (95% CI -4.4 to -2.2) kg for simplified.

CONCLUSIONS

A digital weight loss intervention that incorporated either detailed or simplified dietary self-monitoring was feasible, with high retention and engagement, and acceptable to racial and ethnic minority adults.

TRIAL REGISTRATION

ASPREDICTED #66674; https://aspredicted.org/ka478.pdf.

Addressing people's current and future states in a reinforcement learning algorithm for persuading to quit smoking and to be physically active

Behavior change applications often assign their users activities such as tracking the number of smoked cigarettes or planning a running route. To help a user complete these activities, an application can persuade them in many ways. For example, it may help the user create a plan or mention the experience of peers. Intuitively, the application should thereby pick the message that is most likely to be motivating. In the simplest case, this could be the message that has been most effective in the past. However, one could consider several other elements in an algorithm to choose a message. Possible elements include the user's current state (e.g., self-efficacy), the user's future state after reading a message, and the user's similarity to the users on which data has been gathered. To test the added value of subsequently incorporating these elements into an algorithm that selects persuasive messages, we conducted an experiment in which more than 500 people in four conditions interacted with a text-based virtual coach. The experiment consisted of five sessions, in each of which participants were suggested a preparatory activity for quitting smoking or increasing physical activity together with a persuasive message. Our findings suggest that adding more elements to the algorithm is effective, especially in later sessions and for people who thought the activities were useful. Moreover, while we found some support for transferring knowledge between the two activity types, there was rather low agreement between the optimal policies computed separately for the two activity types. This suggests limited policy generalizability between activities for quitting smoking and those for increasing physical activity. We see our results as supporting the idea of constructing more complex persuasion algorithms. Our dataset on 2,366 persuasive messages sent to 671 people is published together with this article for researchers to build on our algorithm.

Text messages promoting healthy lifestyle and linked with activity monitors stimulate an immediate increase in physical activity among women after gestational diabetes

AIMS

To evaluate the immediate effect of text messages promoting healthy lifestyle and supporting parenting on physical activity amongst women with recent gestational diabetes (GDM).

METHODS

Analysis of data from a pilot randomised controlled trial of a healthy lifestyle program for women with recent GDM. Intervention subjects received text messages providing motivation, reminders, information and feedback as well as an activity monitor. This sub-study examined step count in the 4 h after receipt of a text message, compared to the same time of day on other days among intervention subjects.

RESULTS

Data from 7326 days where step counts were recorded, from 31 women were analysed. The median steps in the 4 h following a text message was 1237 (IQR 18-2240) and it was 1063 (IQR 0-2038) over the same time period on comparison days where there was no message (p < 0.001). The effect was similar whether the messages pertained to physical activity or not. There was no attenuation of the response over 36-38 weeks.

CONCLUSIONS

Women with recent GDM increase their step count in the hours following positive and supportive text messages. This suggests that text messaging programs can facilitate healthy lifestyle and diabetes prevention in this population.

[A decision framework for an adaptive behavioral intervention for physical activity using hybrid model predictive control: illustration with Just Walk]

Physical inactivity is a major contributor to morbidity and mortality worldwide. Many current physical activity behavioral interventions have shown limited success addressing the problem from a long-term perspective that includes maintenance. This paper proposes the design of a decision algorithm for a mobile and wireless health (mHealth) adaptive intervention that is based on control engineering concepts. The design process relies on a behavioral dynamical model based on Social Cognitive Theory (SCT), with a controller formulation based on hybrid model predictive control (HMPC) being used to implement the decision scheme. The discrete and logical features of HMPC coincide naturally with the categorical nature of the intervention components and the logical decisions that are particular to an intervention for physical activity. The intervention incorporates an online controller reconfiguration mode that applies changes in the penalty weights to accomplish the transition between the behavioral initiation and maintenance training stages. Controller performance is illustrated using an ARX model estimated from system identification data of a representative participant for Just Walk, a physical activity intervention designed on the basis of control systems principles.

Linking Gait Biomechanics and Daily Steps After ACL Reconstruction

PURPOSE

Aberrant biomechanics and altered loading frequency are associated with poor knee joint health in osteoarthritis development. After anterior cruciate ligament reconstruction (ACLR), individuals demonstrate underloading (lesser vertical ground reaction force (vGRF)) with stiffened knee gait biomechanics (lesser knee extension moment (KEM) and knee flexion angle) and take fewer daily steps as early as 6 months after surgery. The purpose of this cross-sectional laboratory study is to compare gait biomechanics throughout stance between individuals 6-12 months after ACLR who take the lowest, moderate, and highest daily steps.

METHODS

Individuals with primary, unilateral history of ACLR between the ages of 16 and 35 yr were included (n = 36, 47% females; age, 21 ± 5 yr; months since ACLR, 8 ± 2). Barefoot gait biomechanics of vGRF (body weight), KEM (body weight × height), and knee flexion angle during stance were collected and time normalized. Average daily steps were collected via a waist-mounted accelerometer in free-living settings over 7 d. Participants were separated into tertiles based on lowest daily steps (3326-6042 daily steps), moderate (6043-8198 daily steps), and highest (8199-12,680 daily steps). Biomechanical outcomes of the ACLR limb during stance were compared between daily step groups using functional waveform gait analyses.

RESULTS

There were no significant differences in sex, body mass index, age, or gait speed between daily step groups. Individuals with the lowest daily steps walk with lesser vGRF and lesser KEM during weight acceptance, and lesser knee flexion angle throughout stance in the ACLR limb compared with individuals with highest and moderate daily steps.

CONCLUSIONS

After ACLR, individuals who take the fewest daily steps also walk with lesser vGRF during weight acceptance and a stiffened knee strategy throughout stance. These results highlight complex interactions between joint loading parameters after ACLR.

Adaptive Goals and Reinforcement Timing to Increase Physical Activity in Adults: A Factorial Randomized Trial

INTRODUCTION

Potent lifestyle interventions to increase moderate-to-vigorous physical activity are urgently needed for population-level chronic disease prevention. This trial tested the independent and joint effects of a mobile health system automating adaptive goal setting and immediate financial reinforcement for increasing daily walking among insufficiently active adults.

STUDY DESIGN

Participants were randomized into a 2 (adaptive versus static goal setting) X 2 (immediate versus delayed financial incentive timing) condition factorial trial to increase walking.

SETTINGS/PARTICIPANTS

Participants (N=512 adults) were recruited between 2016 and 2018 and were 64.5% female, aged 18-60 years, 18.8% Hispanic, 6.1% African American, and 83% White.

INTERVENTION

Principles of reinforcement and behavioral economics directed intervention design.

MAIN OUTCOME MEASURES

Participants wore accelerometers daily (133,876 day-level observations) that remotely measured moderate-to-vigorous physical activity bout minutes of ≥3 minutes/day for 1 year. Primary outcomes were between-condition differences in (1) engaging ≥1 bout of moderate-to-vigorous physical activity on each day and (2) on days with ≥1 bout, daily total moderate-to-vigorous physical activity minutes.

RESULTS

Mixed-effects hurdle models tested treatment group X phase (time) interactions using an intent-to-treat approach in 2021. Engaging in any ambulatory moderate-to-vigorous physical activity was greater for Adaptive than for Static Goal groups (OR=2.34, 95% CI=2.10, 2.60 vs OR=1.66, 95% CI=1.50, 1.84; p<0.001) and for Immediate than for Static Reinforcement groups (OR=2.16 95% CI=1.94, 2.40 vs OR=1.77, 95% CI=1.59, 1.97; p<0.01). The Immediate Reinforcement group increased by 16.54 moderate-to-vigorous physical activity minutes/day, whereas the Delayed Reinforcement group increased by 9.91 minutes/day (p<0.001). The combined Adaptive Goals + Immediate Reinforcement group increased by 16.52 moderate-to-vigorous physical activity minutes/day, significantly more than that of either Delayed Reinforcement group.

CONCLUSIONS

This study offers automated and scalable-behavior change strategies for increasing walking among adults most at-risk for chronic diseases attributed to sedentary lifestyles.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.gov (ClinicalTrials.gov Identifier: NCT02717663).

Dulce Digital-Me: protocol for a randomized controlled trial of an adaptive mHealth intervention for underserved Hispanics with diabetes

BACKGROUND

By 2034, the number of US individuals with diabetes is predicted to increase from 23.7 to 44.1 million, and annual diabetes-related spending is expected to grow from $113 to $336 billion. Up to 55% of US Hispanics born in the year 2000 are expected to develop diabetes during their lifetime. Poor healthcare access and cultural barriers prevent optimal care, adherence, and clinical benefit, placing Hispanics at disproportionate risk for costly diabetes complications. Mobile technology is increasingly prevalent in all populations and can circumvent such barriers. Our group developed Dulce Digital, an educational text messaging program that improved glycemic control relative to usual care. Dulce Digital-Me (DD-Me) has been tailored to a participant's individual needs with a greater focus on health behavior change.

METHODS

This is a three-arm, parallel group, randomized trial with equal allocation ratio enrolling Hispanic adults with low income and poorly managed type 2 diabetes (N = 414) from a San Diego County Federally Qualified Health Center. Participants are randomized to receive Dulce Digital, Dulce Digital-Me-Automated, or Dulce Digital-Me-Telephonic. The DD-Me groups include Dulce Digital components plus personalized goal-setting and feedback delivered via algorithm-driven automated text messaging (DD-Me-Automated) or by the care team health coach (DD-Me-Telephonic) over a 12-month follow-up period. The study will examine the comparative effectiveness of the three groups in improving diabetes clinical control [HbA1c, primary outcome; low-density lipoprotein cholesterol (LDL-C), and systolic blood pressure (SBP)] and patient-provider communication and patient adherence (i.e., medication, self-management tasks) over 12 months and will examine cost-effectiveness of the three interventions.

DISCUSSION

Our comparative evaluation of three mHealth approaches will elucidate how technology can be integrated most effectively and efficiently within primary care-based chronic care model approaches to reduce diabetes disparities in Hispanics and will assess two modes of personalized messaging delivery (i.e., automated messaging vs. telephonic by health coach) to inform cost and acceptability.

TRIAL REGISTRATION

NCT03130699-All items from the WHO Trial Registration data set are available in https://clinicaltrials.gov/ct2/show/study/NCT03130699 .

Describing Transitions in Adherence to Physical Activity Self-monitoring and Goal Attainment in an Online Behavioral Weight Loss Program: Secondary Analysis of a Randomized Controlled Trial

Background

Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge, and recommendations may not accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie, minutes of moderate-to-vigorous physical activity [MVPA] and daily steps) and guide future recommendations for improved intervention effectiveness.

Objective

This study examined weekly patterns of adherence to step-based and minute-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention.

Methods

Participants were prescribed weekly PA goals for steps (7000-10,000 steps/day) and minutes of MVPA (50-200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as adherent if they self-monitored their PA and met the program PA goal, suboptimally adherent if they self-monitored but did not meet the program goal, or nonadherent if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression.

Results

Participants (N=212) were predominantly middle-aged females with obesity, and 67 (31.6%) self-identified as a racial/ethnic minority. Initially, 73 (34.4%) participants were categorized as adherent to step-based goals, with 110 [51.9%] suboptimally adherent and 29 [13.7%] nonadherent, and there was a high probability of either remaining suboptimally adherent from week to week or transitioning to a nonadherent status. However, 149 (70.3%) participants started out adherent to minute-based goals (34 [16%] suboptimally adherent and 29 [13.7%] nonadherent), with suboptimally adherent seen as the most variable status. During the graded goal phase, participants were more likely to transition to a less adherent status for minute-based goals (odds ratio [OR] 1.39, 95% CI 1.31-1.48) compared to step-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minute-based goals: OR 1.06, 95% CI 1.05-1.08; step-based goals: OR 1.07, 95% CI 1.05-1.08).

Conclusions

States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial 2 months to bring more people toward adherent behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. Although this study describes the probability of adhering to step- and minute-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions.

Trial Registration

ClinicalTrials.gov NCT02688621; https://clinicaltrials.gov/ct2/show/NCT02688621

Distinguishing early patterns of physical activity goal attainment and weight loss in online behavioral obesity treatment using latent class analysis

Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: "Both PA Goals," "MVPA Goals Only," and "Neither PA Goal." The "Both PA Goals" class had significantly greater 6-month weight loss (estimated mean weight loss [95% CI]: -9.4% [7.4 to 11.5]) compared to the "MVPA Goals Only" (-4.8% [3.4 to 6.1]) and "Neither PA Goal" classes (-2.5% [1.4 to 3.6]). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.

REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial

INTRODUCTION

Achieving optimal diabetes control requires several daily self-management behaviours, especially adherence to medication. Evidence supports the use of text messages to support adherence, but there remains much opportunity to improve their effectiveness. One key limitation is that message content has been generic. By contrast, reinforcement learning is a machine learning method that can be used to identify individuals' patterns of responsiveness by observing their response to cues and then optimising them accordingly. Despite its demonstrated benefits outside of healthcare, its application to tailoring communication for patients has received limited attention. The objective of this trial is to test the impact of a reinforcement learning-based text messaging programme on adherence to medication for patients with type 2 diabetes.

METHODS AND ANALYSIS

In the REinforcement learning to Improve Non-adherence For diabetes treatments by Optimising Response and Customising Engagement (REINFORCE) trial, we are randomising 60 patients with suboptimal diabetes control treated with oral diabetes medications to receive a reinforcement learning intervention or control. Subjects in both arms will receive electronic pill bottles to use, and those in the intervention arm will receive up to daily text messages. The messages will be individually adapted using a reinforcement learning prediction algorithm based on daily adherence measurements from the pill bottles. The trial's primary outcome is average adherence to medication over the 6-month follow-up period. Secondary outcomes include diabetes control, measured by glycated haemoglobin A1c, and self-reported adherence. In sum, the REINFORCE trial will evaluate the effect of personalising the framing of text messages for patients to support medication adherence and provide insight into how this could be adapted at scale to improve other self-management interventions.

ETHICS AND DISSEMINATION

This study was approved by the Mass General Brigham Institutional Review Board (IRB) (USA). Findings will be disseminated through peer-reviewed journals, clinicaltrials.gov reporting and conferences.

TRIAL REGISTRATION NUMBER

Clinicaltrials.gov (NCT04473326).

Effectiveness of a customised mobile phone text messaging intervention supported by data from activity monitors for improving lifestyle factors related to the risk of type 2 diabetes among women after gestational diabetes: protocol for a multicentre randomised controlled trial (SMART MUMS with smart phones 2)

INTRODUCTION

Gestational diabetes (GDM) contributes substantially to the population burden of type 2 diabetes (T2DM), with a high long-term risk of developing T2DM. This study will assess whether a structured lifestyle modification programme for women immediately after a GDM pregnancy, delivered via customised text messages and further individualised using data from activity monitors, improves T2DM risk factors, namely weight, physical activity (PA) and diet.

METHODS AND ANALYSIS

This multicentre randomised controlled trial will recruit 180 women with GDM attending Westmead, Campbelltown or Blacktown hospital services in Western Sydney. They will be randomised (1:1) on delivery to usual care with activity monitor (active control) or usual care plus activity monitor and customised education, motivation and support delivered via text messaging (intervention). The intervention will be customised based on breastfeeding status, and messages including their step count achievements to encourage PA. Messages on PA and healthy eating will encourage good lifestyle habits. The primary outcome of the study is healthy lifestyle composed of weight, dietary and PA outcomes, to be evaluated at 6 months. The secondary objectives include the primary objective components, body mass index, breastfeeding duration and frequency, postnatal depression, utilisation of the activity monitor, adherence to obtaining an oral glucose tolerance test post partum and the incidence of dysglycaemia at 12 months. Relative risks and their 95% CIs will be presented for the primary objective and the appropriate regression analysis, adjusting for the baseline outcome results, will be done for each outcome.

ETHICS AND DISSEMINATION

Ethics approval has been received from the Western Sydney Local Health District Human Research Ethics Committee (2019/ETH13240). All patients will provide written informed consent. Study results will be disseminated via the usual channels including peer-reviewed publications and presentations at national and international conferences.

TRIAL REGISTRATION NUMBER

ACTRN12620000615987; Pre-results.

Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review

BACKGROUND

Traditional psychological theories are inadequate to fully leverage the potential of smartphones and improve the effectiveness of physical activity (PA) and sedentary behavior (SB) change interventions. Future interventions need to consider dynamic models taken from other disciplines, such as engineering (eg, control systems). The extent to which such dynamic models have been incorporated in the development of interventions for PA and SB remains unclear.

OBJECTIVE

This review aims to quantify the number of studies that have used dynamic models to develop smartphone-based interventions to promote PA and reduce SB, describe their features, and evaluate their effectiveness where possible.

METHODS

Databases including PubMed, PsycINFO, IEEE Xplore, Cochrane, and Scopus were searched from inception to May 15, 2019, using terms related to mobile health, dynamic models, SB, and PA. The included studies involved the following: PA or SB interventions involving human adults; either developed or evaluated integrated psychological theory with dynamic theories; used smartphones for the intervention delivery; the interventions were adaptive or just-in-time adaptive; included randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post study designs; and were published from 2000 onward. Outcomes included general characteristics, dynamic models, theory or construct integration, and measured SB and PA behaviors. Data were synthesized narratively. There was limited scope for meta-analysis because of the variability in the study results.

RESULTS

A total of 1087 publications were screened, with 11 publications describing 8 studies included in the review. All studies targeted PA; 4 also included SB. Social cognitive theory was the major psychological theory upon which the studies were based. Behavioral intervention technology, control systems, computational agent model, exploit-explore strategy, behavioral analytic algorithm, and dynamic decision network were the dynamic models used in the included studies. The effectiveness of quasi-experimental studies involved reduced SB (1 study; P=.08), increased light PA (1 study; P=.002), walking steps (2 studies; P=.06 and P<.001), walking time (1 study; P=.02), moderate-to-vigorous PA (2 studies; P=.08 and P=.81), and nonwalking exercise time (1 study; P=.31). RCT studies showed increased walking steps (1 study; P=.003) and walking time (1 study; P=.06). To measure activity, 5 studies used built-in smartphone sensors (ie, accelerometers), 3 of which used the phone's GPS, and 3 studies used wearable activity trackers.

CONCLUSIONS

To our knowledge, this is the first systematic review to report on smartphone-based studies to reduce SB and promote PA with a focus on integrated dynamic models. These findings highlight the scarcity of dynamic model-based smartphone studies to reduce SB or promote PA. The limited number of studies that incorporate these models shows promising findings. Future research is required to assess the effectiveness of dynamic models in promoting PA and reducing SB.

TRIAL REGISTRATION

International Prospective Register of Systematic Reviews (PROSPERO) CRD42020139350; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=139350.

Feasibility of a Wearable-Based Physical Activity Goal-Setting Intervention Among Individuals With Anterior Cruciate Ligament Reconstruction

CONTEXT

Individuals with a history of anterior cruciate ligament reconstruction (ACLR) demonstrate persistent reductions in physical activity (PA) volume that are not being addressed during rehabilitation. Currently, it is challenging for clinicians to prescribe exercise interventions that extend beyond in-person rehabilitative care in a manner that is responsive and acceptable to patients.

OBJECTIVE

To investigate the feasibility of using a novel, technology-driven, personalized goal-setting intervention over a 2-month period among young individuals with a history of primary unilateral ACLR.

DESIGN

Single-blinded feasibility study.

SETTING

University community.

PATIENTS OR OTHER PARTICIPANTS

Ten women and 2 men (age = 22.0 ± 3.0 years, time since surgery = 56.0 ± 36.3 months) with a history of primary unilateral ACLR.

INTERVENTION(S)

All participants completed a 28-day PA observation period immediately followed by a 28-day individualized PA goal-setting intervention period delivered via a commercially available PA monitor.

MAIN OUTCOME MEASURE(S)

Primary feasibility outcomes were days of PA monitor wear compliance and days of goal achievement during the intervention period. Participants also completed the Knee Osteoarthritis Outcome Score (KOOS) at study enrollment and after the intervention period, and the individual change in the KOOS Quality of Life subscale was compared with the minimal detectable change (7.2 points).

RESULTS

Average PA monitor wear compliance was 95.5% ± 7.3% during the observation period and 97.7% ± 2.9% during the intervention period. Median goal achievement was 31.5% ± 6.8% during the intervention period. Five participants demonstrated meaningful improvements in the KOOS Quality of Life subscale during the study period.

CONCLUSIONS

Individualized goal setting via mobile technology appears to be a feasible approach to PA promotion. However, based on the low rate of daily goal attainment during the intervention period, continued refinement of this intervention aproach would be beneficial before broad clinical implementation.

A quality-improvement optimization pilot of BariFit, a mobile health intervention to promote physical activity after bariatric surgery

Bariatric surgery is the most effective treatment for severe obesity (body mass index >40), helping individuals lose, on average, 25%-29% of their body weight over the first year. However, many patients begin to plateau and regain weight within 12-24 months, and 20% of patients begin to regain weight within 6 months postsurgery. As physical activity (PA) is an important predictor of weight loss and maintenance postsurgery, there is a need for scalable, effective lifestyle interventions to help bariatric patients increase PA in order to maximize their weight loss and maintenance. To assess feasibility of using mobile health (mHealth) tools to support PA postsurgery, we conducted a quality-improvement optimization pilot of BariFit, an mHealth intervention that combines commercial devices and custom text messages. Fifty-one bariatric patients enrolled in a 16-week optimization pilot of BariFit. To assess feasibility, pre-post changes in PA were assessed using activPAL. In addition, the pilot randomized, using a 2 × 2 factorial design, two adaptive approaches to daily step goals (variable and 60th percentile goals) and provision of rest days (yes/no), and microrandomized provision of SMS-delivered activity suggestions five times a day for each participant. Adherence to using study equipment was over 95% at 16 weeks. Participants increased PA by 1,866 steps from baseline to end-of-study (p < .007). Participants who received variable step goals averaged 1,141 more steps per day (p = .096) than those who received 60th percentile goals. Activity suggestions had no effect. mHealth interventions are feasible for supporting PA postbariatric surgery.

Systematic review of context-aware digital behavior change interventions to improve health

Health risk behaviors are leading contributors to morbidity, premature mortality associated with chronic diseases, and escalating health costs. However, traditional interventions to change health behaviors often have modest effects, and limited applicability and scale. To better support health improvement goals across the care continuum, new approaches incorporating various smart technologies are being utilized to create more individualized digital behavior change interventions (DBCIs). The purpose of this study is to identify context-aware DBCIs that provide individualized interventions to improve health. A systematic review of published literature (2013-2020) was conducted from multiple databases and manual searches. All included DBCIs were context-aware, automated digital health technologies, whereby user input, activity, or location influenced the intervention. Included studies addressed explicit health behaviors and reported data of behavior change outcomes. Data extracted from studies included study design, type of intervention, including its functions and technologies used, behavior change techniques, and target health behavior and outcomes data. Thirty-three articles were included, comprising mobile health (mHealth) applications, Internet of Things wearables/sensors, and internet-based web applications. The most frequently adopted behavior change techniques were in the groupings of feedback and monitoring, shaping knowledge, associations, and goals and planning. Technologies used to apply these in a context-aware, automated fashion included analytic and artificial intelligence (e.g., machine learning and symbolic reasoning) methods requiring various degrees of access to data. Studies demonstrated improvements in physical activity, dietary behaviors, medication adherence, and sun protection practices. Context-aware DBCIs effectively supported behavior change to improve users' health behaviors.

A Clinician-Controlled Just-in-time Adaptive Intervention System (CBT+) Designed to Promote Acquisition and Utilization of Cognitive Behavioral Therapy Skills in Bulimia Nervosa: Development and Preliminary Evaluation Study

Background

Cognitive behavioral therapy (CBT) for bulimia nervosa (BN) is most effective when patients demonstrate adequate skill utilization (ie, the frequency with which a patient practices or uses therapeutic skills) and skill acquisition (ie, the ability to successfully perform a skill learned in treatment). However, rates of utilization and acquisition of key treatment skills (eg, regular eating, urge management skills, and mood management skills) by the end of the treatment are frequently low; as a result, outcomes from CBT for BN are affected. Just-in-time adaptive interventions (JITAIs) may improve skill acquisition and utilization by delivering real-time interventions during algorithm-identified opportunities for skill practice.

Objective

In this manuscript, we describe a newly developed JITAI system called CBT+ that is designed to facilitate the acquisition and utilization of CBT for BN treatment skills when used as a treatment augmentation. We also present feasibility, acceptability, and preliminary outcomes data from a small proof-of-concept pilot trial (n=5 patients and n=3 clinicians) designed to identify opportunities for iterative development of CBT+ ahead of a larger ongoing randomized controlled trial.

Methods

A total of 5 individuals with BN received 16 sessions of outpatient CBT for BN while using the CBT+ app. Data were collected from patients and clinicians to evaluate the feasibility (eg, app use and user adherence), acceptability (eg, qualitative patient and clinician feedback, including usefulness ratings of CBT+ on a 6-point Likert scale ranging from 1=extremely useless to 6=extremely useful), and preliminary outcomes (eg, improvements in skill utilization and acquisition and BN symptoms) of the CBT+ system.

Results

Patients reported that CBT+ was a relatively low burden (eg, quick and easy-to-use self-monitoring interface), and adherence to in-app self-monitoring was high (mean entries per day 3.13, SD 1.03). JITAIs were perceived as useful by both patients (median rating 5/6) and clinicians (median rating 5/6) for encouraging the use of CBT skills. Large improvements in CBT skills and clinically significant reductions in BN symptoms were observed post treatment. Although preliminary findings indicated that the CBT+ system was acceptable to most patients and clinicians, the overall study dropout was relatively high (ie, 2/5, 40% patients), which could indicate some moderate concerns regarding feasibility.

Conclusions

CBT+, the first-ever JITAI system designed to facilitate the acquisition and utilization of CBT for BN treatment skills when used as a treatment augmentation, was shown to be feasible and acceptable. The results indicate that the CBT+ system should be subjected to more rigorous evaluations with larger samples and should be considered for wider implementation if found effective. Areas for iterative improvement of the CBT+ system ahead of a randomized controlled trial are also discussed.

Agent-Oriented Goal Models in Developing Information Systems Supporting Physical Activity Among Adolescents: Literature Review and Expert Interviews

Background

Information and communication technologies (ICTs) are becoming increasingly popular in supporting the fight against low physical activity (PA) levels among adolescents. However, several ICT solutions lack evidence-based content. Therefore, there is a need to identify important features that have the potential to efficiently and consistently support the PA of adolescents using ICT solutions.

Objective

This study aims to create evidence-based models of requirements for ICT solutions supporting PA by combining scientific evidence from literature and health experts. In addition, we test the suitability of agent-oriented goal models in this type of modeling process.

Methods

A literature search of PubMed, Web of Science, and Scopus databases was conducted to identify evidence-based functional, quality, and emotional goals that have previously been proven to be relevant in supporting PAs among youth using ICT solutions. The identified goals were presented in the form of goal models. These models were used to collaborate with health experts to receive their input on the topic and suggestions for improvement. The initial goal models were improved based on the feedback from the experts.

Results

The results indicated that agent-oriented goal modeling is a suitable method for merging information from the literature and experts. One strength of agent-oriented goal models is that they present emotional requirements together with quality and functional requirements. Another strength is the possibility of presenting results from a literature review in a systematic manner and using them thereafter in the communication process with stakeholders. Agent-oriented goal models that were created were easy to understand for health experts without previous experience in requirements engineering, which facilitates and supports collaboration with nontechnical stakeholders.

Conclusions

The proposed agent-oriented goal models effectively merged information from scientific literature and experts in the field and presented early functional, quality, and emotional requirements in a holistic and coherent manner. We believe that the created models have high potential to help requirements engineers and developers to provide more efficient ICT solutions that support PA among adolescents in the future.

A decision-neuroscientific intervention to improve cognitive recovery after stroke

Functional recovery after stroke is dose-dependent on the amount of rehabilitative training. However, rehabilitative training is subject to motivational hurdles. Decision neuroscience formalizes drivers and dampers of behaviour and provides strategies for tipping motivational trade-offs and behaviour change. Here, we used one such strategy, upfront voluntary choice restriction (‘precommitment’), and tested if it can increase the amount of self-directed rehabilitative training in severely impaired stroke patients. In this randomized controlled study, stroke patients with working memory deficits (n = 83) were prescribed daily self-directed gamified cognitive training as an add-on to standard therapy during post-acute inpatient neurorehabilitation. Patients allocated to the precommitment intervention could choose to restrict competing options to self-directed training, specifically the possibility to meet visitors. This upfront choice restriction was opted for by all patients in the intervention group and highly effective. Patients in the precommitment group performed the prescribed self-directed gamified cognitive training twice as often as control group patients who were not offered precommitment [on 50% versus 21% of days, P_corr = 0.004, d = 0.87, 95% confidence interval (CI_95%) = 0.31 to 1.42], and, as a consequence, reached a 3-fold higher total training dose (90.21 versus 33.60 min, P_corr = 0.004, d = 0.83, CI_95% = 0.27 to 1.38). Moreover, add-on self-directed cognitive training was associated with stronger improvements in visuospatial and verbal working memory performance (P_corr = 0.002, d = 0.72 and P_corr = 0.036, d = 0.62). Our neuroscientific decision add-on intervention strongly increased the amount of effective cognitive training performed by severely impaired stroke patients. These results warrant a full clinical trial to link decision-based neuroscientific interventions directly with clinical outcome.

Project Step: A Randomized Controlled Trial Investigating the Effects of Frequent Feedback and Contingent Incentives on Physical Activity

BACKGROUND

Financial incentives and feedback on behavior offer promise for promoting physical activity. However, evidence for the effect of each of these techniques is inadequate. The present study evaluated the effects of daily versus weekly feedback and incentives contingent on reaching a daily walking goal versus noncontingent incentives in a 2 × 2 trial.

METHODS

Participants (N = 57) had a body mass index >25 kg/m2 and were insufficiently active. Participants received a daily walking goal that adapted weekly.

RESULTS

Participants receiving daily feedback increased daily steps (P = .03) more than those receiving weekly feedback. Participants receiving contingent incentives did not significantly increase steps (P = .12) more than those receiving noncontingent incentives. A trend-level effect (P = .09) suggested that there may be an interaction such that the combination of daily feedback and contingent incentives is most effective.

CONCLUSIONS

Results indicate that feedback is an important component of remotely delivered PA interventions and that evaluating each component of low-intensity interventions may help to improve efficacy. Moreover, results indicate that possible synergistic effects of feedback and rewards should be investigated further to help optimize interventions.

Promoting physical activity in young adult cancer survivors using mHealth and adaptive tailored feedback strategies: Design of the Improving Physical Activity after Cancer Treatment (IMPACT) randomized controlled trial

INTRODUCTION

Despite the health benefits of physical activity for cancer survivors, nearly 60% of young adult cancer survivors (YACS) are physically inactive. Few physical activity interventions have been designed specifically for YACS.

PURPOSE

To describe the rationale and design of the IMPACT (IMproving Physical Activity after Cancer Treatment) trial, which tests the efficacy of a theory-based, mobile physical activity intervention for YACS.

METHODS

A total of 280 physically inactive YACS (diagnosed at ages 18-39) will be randomized to a self-help control or intervention condition. All participants will receive an activity tracker and companion mobile app, cellular-enabled scale, individual videochat session, and access to a Facebook group. Intervention participants will also receive a 6-month mobile intervention based on social cognitive theory, which targets improvements in behavioral capability, self-regulation, self-efficacy, and social support, and incorporates self-regulation strategies and behavior change techniques. The program includes: behavioral lessons; adaptive goal-setting in response to individuals' changing activity patterns; tailored feedback based on objective data and self-report measures; tailored text messages; and Facebook prompts encouraging peer support. Assessments occur at baseline, 3, 6, and 12 months. The primary outcome is total physical activity min/week at 6 months (assessed via accelerometry); secondary outcomes include total physical activity at 12 months, sedentary behavior, weight, and psychosocial measures.

CONCLUSIONS

IMPACT uniquely focuses on physical activity in YACS using an automated tailored mHealth program. Study findings could result in a high-reach, physical activity intervention for YACS that has potential to be adopted on a larger scale and reduce cancer-related morbidity. ClinicalTrials.gov Identifier: NCT03569605.

Incorporating walking into cognitive behavioral therapy for chronic pain: safety and effectiveness of a personalized walking intervention

We examined the effectiveness and safety of a walking program offered as part of cognitive behavioral therapy for chronic pain (CBT-CP). Participants were randomized to 10 weeks of CBT-CP, delivered either in person or by interactive voice response. Participants reported pedometer-measured step counts daily throughout treatment and received a weekly goal to increase their steps by 10% over the prior week's average. Walking-related adverse events (AEs) were assessed weekly. Participants (n = 125) were primarily male (72%), and white (80%) with longstanding pain (median: 11 years). There was no significant difference between treatment groups in rate of change in daily steps, but there was a significant increase in steps from baseline to treatment termination in the combined study sample (1648 steps (95% CI 1063-2225)). Participants classified as active doubled. AEs were mostly minor and temporary. Treatment was effective and safe whether the program was delivered in-person or remotely.Trial registration number: clinicaltrials.gov identifier: NCT01025752.

Effects of Goal Type and Reinforcement Type on Self-Reported Domain-Specific Walking Among Inactive Adults: 2×2 Factorial Randomized Controlled Trial

Background

WalkIT Arizona was a 2×2 factorial trial examining the effects of goal type (adaptive versus static) and reinforcement type (immediate versus delayed) to increase moderate to vigorous physical activity (MVPA) among insufficiently active adults. The 12-month intervention combined mobile health (mHealth) technology with behavioral strategies to test scalable population-health approaches to increasing MVPA. Self-reported physical activity provided domain-specific information to help contextualize the intervention effects.

Objective

The aim of this study was to report on the secondary outcomes of self-reported walking for transportation and leisure over the course of the 12-month WalkIT intervention.

Methods

A total of 512 participants aged 19 to 60 years (n=330 [64.5%] women; n=425 [83%] Caucasian/white, n=96 [18.8%] Hispanic/Latinx) were randomized into interventions based on type of goals and reinforcements. The International Physical Activity Questionnaire-long form assessed walking for transportation and leisure at baseline, and at 6 months and 12 months of the intervention. Negative binomial hurdle models were used to examine the effects of goal and reinforcement type on (1) odds of reporting any (versus no) walking/week and (2) total reported minutes of walking/week, adjusted for neighborhood walkability and socioeconomic status. Separate analyses were conducted for transportation and leisure walking, using complete cases and multiple imputation.

Results

All intervention groups reported increased walking at 12 months relative to baseline. Effects of the intervention differed by domain: a significant three-way goal by reinforcement by time interaction was observed for total minutes of leisure walking/week, whereas time was the only significant factor that contributed to transportation walking. A sensitivity analysis indicated minimal differences between complete case analysis and multiple imputation.

Conclusions

This study is the first to report differential effects of adaptive versus static goals for self-reported walking by domain. Results support the premise that individual-level PA interventions are domain- and context-specific and may be helpful in guiding further intervention refinement.

Trial Registration

Preregistered at clinicaltrials.gov: (NCT02717663) https://clinicaltrials.gov/ct2/show/NCT02717663

International Registered Report Identifier (IRRID)

RR2-10.1016/j.cct.2019.05.001

Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol for a pilot randomised trial using wearable technology, goal setting and text message feedback

Background: Physical activity (PA) and exercise are widely documented as key components in the management of cystic fibrosis (CF). In recent years there have been significant improvements in telehealth, in particular; wearable technology,  smartphone use and remote monitoring, all of which may have potential to impact on PA in adults  with CF. The objective of this pilot randomised trial is to explore the effect of wearable technology, which is remotely monitored, combined with personalised text message feedback and goal setting, on PA in adults with CF. Secondary endpoints include lung function, aerobic capacity, quality of life, body composition, wellbeing and sleep. Methods: This is a pilot randomised trial which will be conducted at the University Hospital Limerick, Ireland. Participants will be randomised to the intervention or active comparator after their baseline assessment. The 12-week intervention will consist of wearable technology (Fitbit Charge 2) which is linked to an online monitoring system (Fitabase) that enables the physiotherapist to remotely monitor participant data. The CF physiotherapist will set individualised PA goals with each participant at baseline and will send text message feedback each week. The text messages will be personalised, one-way texts with positive reinforcement on step count attained by the participant. The active comparator group will receive this wearable technology which is also linked to Fitabase; however, no feedback will be provided to participants in this group. Both groups will be re-assessed at 12 weeks. After this point, both groups will continue with the Fitbit alone for a further 12 weeks. Both groups will be re-assessed at 24 weeks. A semi structured interview will assess satisfaction and acceptability of the intervention. Discussion: This is a novel concept which utilises modern technology, remote monitoring and personalised feedback to investigate the effect on PA  in adults with CF.  Trial registration: ClinicalTrials.gov NCT03672058 (14/09/2018).

Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol for a pilot randomised trial using wearable technology

Background: Physical activity (PA) and exercise are widely documented as key components in the management of cystic fibrosis (CF). In recent years there have been significant improvements in telehealth, in particular; wearable technology,  smartphone use and remote monitoring, all of which may have potential to impact on PA in adults  with CF. The objective of this pilot randomised trial is to explore the effect of wearable technology, which is remotely monitored, combined with personalised text message feedback and goal setting, on PA in adults with CF. Secondary endpoints include lung function, aerobic capacity, quality of life, body composition, wellbeing and sleep. Methods: This is a pilot randomised trial which will be conducted at the University Hospital Limerick, Ireland. Participants will be randomised to the intervention or active comparator after their baseline assessment. The 12-week intervention will consist of wearable technology (Fitbit Charge 2) which is linked to an online monitoring system (Fitabase) that enables the physiotherapist to remotely monitor participant data. The CF physiotherapist will set individualised PA goals with each participant at baseline and will send text message feedback each week. The text messages will be personalised, one-way texts with positive reinforcement on step count attained by the participant. The active comparator group will receive this wearable technology which is also linked to Fitabase; however, no feedback will be provided to participants in this group. Both groups will be re-assessed at 12 weeks. After this point, both groups will continue with the Fitbit alone for a further 12 weeks. Both groups will be re-assessed at 24 weeks. A semi structured interview will assess satisfaction and acceptability of the intervention. Discussion: This is a novel concept which utilises modern technology, remote monitoring and personalised feedback to investigate the effect on PA  in adults with CF.  Trial registration: ClinicalTrials.gov NCT03672058 (14/09/2018).

Inducing illusory control ensures persistence when rewards fade and when others outperform us

Persisting even when the rewards of continued effort are fading is essential for achieving long-term goals, skills, and good health, alike. Yet, we often quit when things get hard. Here, we tested whether augmenting the feeling of control through external measures increases persistence under such discouraging circumstances. In two laboratory experiments, we first induced illusory control by manipulating the base-rate of positive outcomes and then tested the effect of this elevation of participants' perceived control upon their persistence under diminishing returns and in a competition against a stronger opponent. Induced illusory control significantly enhanced people's persistence in both of these motivationally challenging situations. Our findings demonstrate that motivation is dependent upon perceived, rather than objective, control, and reveal that this can be leveraged to counteract quitting behavior when things get hard, for instance in rehabilitation, physical activity interventions, or other training settings.

Understanding and effectively addressing disparities in obesity: A systematic review of the psychological determinants of emotional eating behaviours among Black women

Emotional eating may be a particularly important contributor to differences in body weight and weight loss response to behavioural interventions among non-Hispanic Black women. We performed a systematic review on the impact of psychological factors (stress, anxiety, depression, and discrimination) upon emotional eating and weight among non-Hispanic Black women, applying the Preferred Reporting Items for Systematic Reviews and Meta-analysis for relevant studies. The initial search yielded 4593 articles with 15 accepted for review. Based on this review, there is a suggestion that negative emotions, in particular, perceived stress, may be predictive of emotional eating among non-Hispanic Black women. Results from the only two longitudinal studies identified by the review indicate that stress influences emotional eating, and emotional eating predicts weight gain over time. Findings from this review highlight the need for more studies that examine various negative emotions that may lead to emotional eating and weight gain among non-Hispanic Black women. Findings from this review also highlight the need for more rigorous studies to differentiate the effects of emotional eating from that of the physiologic (ie, activation of the hypothalamic-pituitary axis) responses to stress and its impact on high-risk groups.

Creating value with eHealth: identification of the value proposition with key stakeholders for the resilience navigator app

BACKGROUND

For a stress-management app to be persuasive and impactful, designers and developers should obtain a clear perspective of the value proposition according to key stakeholders before development. However, this is often not the case. In order to increase the chance of creating an impact by means of the Resilience Navigator app, this study aims to identify key stakeholders and work with them to gain an in-depth understanding of the value proposition of this stress-management app.

METHODS

The approach used in this study builds on the approaches taken by Van Limburg et al. and Van Woezik et al. An initial list of stakeholders was identified by means of a literature scan. Stakeholders on this initial list took an online survey to identify key stakeholders with a ranking system. Semi-structured interviews were conducted with a subset of key stakeholders to identify the value proposition using the value proposition canvas as a framework for data collection. Finally, the value proposition was validated by key stakeholders during focus groups.

RESULTS

The key stakeholders identified included employees, employers, participation councils within organisations, HR advisors, product owners, company doctors, and business analysts. The interviews produced a list of approximately one hundred values from which fifteen core values were distilled. One example is to take into account time constraints experienced by users during stress periods. In general, the Resilience Navigator app's main goal is to increase awareness of personal stress levels and causes of stress. In addition, the sub-goal is to increase skills for effective stress management. The focus groups validated the idea that the most important values were reflected in the value proposition and had been appropriately translated into design elements, according to key stakeholders.

CONCLUSIONS

A thorough, bottom-up identification and validation of the value proposition for the Resilience Navigator app was obtained, reflecting key stakeholders' varying ideas on this piece of eHealth technology. The results will facilitate the continued development of the Resilience Navigator app from the value specification phase to the design phase. In the design phase, the remaining assumptions regarding the app's value proposition should be tested using rapid prototyping.

Variable Magnitude and Frequency Financial Reinforcement is Effective at Increasing Adults' Free-Living Physical Activity

Financial rewards can increase health behaviors, but little research has quantified the effects of different reinforcement schedules on this process. This analysis compares the average moderate-to-vigorous physical activity (MVPA) associated with six distinct positive reinforcement schedules implemented within a physical activity promotion clinical trial. In this trial, participants (N = 512) wore an accelerometer for 1 year and were prescribed one of two types of MVPA goals: a static 30-min goal or an adaptive goal based on the MVPA produced over the previous 9 days. As participants met goals, they transitioned through a sequence of reinforcement stages, beginning with a continuous-fixed magnitude (CRF-FM), then CRF-variable magnitude (CRF-VM), followed by a series of variable ratio-VM (VR-VM) schedules. The average accumulation of MVPA bouts over the last 24 days of each stage was compared to each other. Average MVPA during stage transitions was also examined. The results indicated that immediate reinforcement resulted in more MVPA relative to a comparison group and that the relative effectiveness of adaptive versus static goals was dependent on the magnitude of daily MVPA goals. Schedule effects were qualitatively different for individuals who frequently met their daily goals (Large Intervention Effect subgroup) versus those who did not (Small Intervention Effect subgroup). For the Large Intervention Effect group, the CRF-VM schedule produced the most MVPA, in particular within the adaptive goal condition, with increases observed immediately upon encountering this schedule. In contrast, the CRF-FM schedule produced small amounts of MVPA. This pattern was reversed for the Small Intervention Effect subgroup, where the most MVPA was associated with the CRF-FM stage. Future interventions should focus on discriminating small versus large intervention effects as quickly as possible so that the optimal reinforcement schedule can be used.

Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions

Mobile health (mHealth) technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social Cognitive Theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the MILES study) and 2) as a means for discerning the range of "ambitious but doable" daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts, and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

Unpacking mHealth interventions: A systematic review of behavior change techniques used in randomized controlled trials assessing mHealth effectiveness

Objective

Mobile health interventions have surged in popularity but their implementation varies widely and evidence of effectiveness is mixed. We sought to advance understanding of the diversity of behavior change techniques in mHealth interventions, especially those that leverage advanced mobile technologies.

Methods

We conducted a systematic review of articles published between 2007 and 2017 in high-impact journals in medicine, medical informatics, and health psychology to identify randomized controlled trials in which the effectiveness of an mobile health intervention was tested. Search terms included a mix of general (e.g. mobile health), hardware (e.g. Android, iPhone), and format (e.g. SMS, application) terms.

Results

In a systematic review of 21 studies, we found the techniques of personalization, feedback and monitoring, and associations were most commonly used in mobile health interventions, but there remains considerable opportunity to leverage more sophisticated aspects of ubiquitous computing. We found that prompts and cues were the most common behavior change techniques used in effective trials, but there was notable overlap in behavior change techniques used in ineffective trials.

Conclusions

Our results identify techniques that are commonly used in mobile health interventions and highlight pathways to advance the science of mobile health.

Effects of Bluetooth-Enabled Desk Ellipticals on Office Work Performance: Rationale, Design, and Protocol for a Randomized Trial With Overweight and Obese Adults

Background

Workplaces that provide opportunities for physical activity without requiring extra time for activity could help counteract the obesity epidemic. Desk ellipticals can contribute to activity-supportive workplace environments; however, the feasibility of engaging employees in pedaling ellipticals during simultaneous office work has not been well evaluated.

Objective

We aim to present the rationale and methods from an ongoing randomized trial with overweight and obese employees that will evaluate (1) the effects of pedaling a compact desk elliptical on work performance and (2) the influence of different incentive types and schedules on desk pedaling quantity.

Methods

Overweight and obese medical center employees are being recruited in dyads for a 2 (gift card type: healthier food vs Amazon) by 3 (gift card schedule: immediate incentive contingent on individual pedaling quantity; immediate incentive partially contingent on dyads’ joint pedaling quantity; and delayed noncontingent pedaling incentive) cluster randomized within-subjects factorial trial. All participants receive a Bluetooth-enabled desk elliptical for 4 weeks and access to a mobile app that provides real-time pedaling feedback. The primary aims are to assess (1) change in employee work performance from pre- to postelliptical installation via employee and supervisor ratings and (2) effects of gift card type and schedule on quantity of objectively measured desk pedaling completed.

Results

Data collection is ongoing. We expect to complete main outcome analyses in 2020.

Conclusions

This trial represents one of the earliest attempts to assess the effects of desk pedaling and pedaling-incentive types in real-world offices. It could help bridge the research-to-practice gap by providing evidence on whether desk pedaling can be sustained without compromising work performance.

International Registered Report Identifier (IRRID)

DERR1-10.2196/16275

Text Message Interventions for Physical Activity: A Systematic Review and Meta-Analysis

CONTEXT

Despite clear health benefits, many individuals fail to achieve the recommended levels of physical activity. Text message interventions to promote physical activity hold promise owing to the ubiquity of cell phones and the low expense of text message delivery.

EVIDENCE ACQUISITION

A systematic review and meta-analysis were performed to examine the impact of text message interventions on physical activity. Searches of PubMed, PsycINFO, Scopus, Cochrane, and ClinicalTrials.gov databases from inception to December 2017 were performed to identify studies investigating one-way text message interventionss to promote physical activity. A subset of RCTs, including an objective (accelerometer-based) physical activity outcome, were included in random-effects meta-analyses in 2018.

EVIDENCE SYNTHESIS

The systematic search revealed 944 articles. Of these, 59 were included in the systematic review (12 1-arm trials and 47 controlled trials; n=8,742; mean age, 42.2 years; 56.2% female). In meta-analyses of 13 studies (n=1,346), text message interventionss led to significantly greater objectively measured postintervention steps/day (Cohen's d=0.38, 95% CI=0.19, 0.58, n=10 studies). Analysis of postintervention moderate-to-vigorous physical activity found a similar but not statistically significant effect (Cohen's d=0.31, 95% CI= -0.01, 0.63, n=5 studies). Interventions with more components, tailored content, and interventions in medical populations led to nonsignificantly larger effect sizes compared with text message interventions without these features.

CONCLUSIONS

Text message interventions lead to higher objectively measured postintervention physical activity compared with control groups. More extensive, well-controlled studies are needed to examine this relationship further and identify characteristics of effective text message interventions.

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

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.

Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support

Background

The just-in-time adaptive intervention (JITAI) is an intervention design aiming to provide the right type/amount of support, at the right time, by adapting to an individual's changing internal and contextual state. The availability of increasingly powerful mobile and sensing technologies underpins the use of JITAIs to support health behavior, as in such a setting an individual's state can change rapidly, unexpectedly, and in his/her natural environment.

Purpose

Despite the increasing use and appeal of JITAIs, a major gap exists between the growing technological capabilities for delivering JITAIs and research on the development and evaluation of these interventions. Many JITAIs have been developed with minimal use of empirical evidence, theory, or accepted treatment guidelines. Here, we take an essential first step towards bridging this gap.

Methods

Building on health behavior theories and the extant literature on JITAIs, we clarify the scientific motivation for JITAIs, define their fundamental components, and highlight design principles related to these components. Examples of JITAIs from various domains of health behavior research are used for illustration.

Conclusions

As we enter a new era of technological capacity for delivering JITAIs, it is critical that researchers develop sophisticated and nuanced health behavior theories capable of guiding the construction of such interventions. Particular attention has to be given to better understanding the implications of providing timely and ecologically sound support for intervention adherence and retention.

Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss

This randomized trial demonstrated qualified support for the ability of a machine learning-powered, smartphone-based just-in-time, adaptive intervention to enhance weight loss over and above a commercial weight loss program.

Applying machine learning to predict future adherence to physical activity programs

BACKGROUND

Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured physical activity data in the Mobile Phone-Based Physical Activity Education program (mPED) trial. To the best of our knowledge, this is the first to apply Machine Learning methods to predict exercise relapse using accelerometer-recorded physical activity data.

METHODS

We use logistic regression and support vector machine methods to design two versions of a Discontinuation Prediction Score (DiPS), which uses objectively measured past data (e.g., steps and goal achievement) to provide a numerical quantity indicating the likelihood of exercise relapse in the upcoming week. The respective prediction accuracy of these two versions of DiPS are compared, and then numerical simulation is performed to explore the potential of using DiPS to selectively allocate financial incentives to participants to encourage them to increase physical activity.

RESULTS

we had access to a physical activity trial data that were continuously collected every 60 sec every day for 9 months in 210 participants. By using the first 15 weeks of data as training and test on weeks 16-30, we show that both versions of DiPS have a test AUC of 0.9 with high sensitivity and specificity in predicting the probability of exercise adherence. Simulation results assuming different intervention regimes suggest the potential benefit of using DiPS as a score to allocate resources in physical activity intervention programs in reducing costs over other allocation schemes.

CONCLUSIONS

DiPS is capable of making accurate and robust predictions for future weeks. The most predictive features are steps and physical activity intensity. Furthermore, the use of DiPS scores can be a promising approach to determine when or if to provide just-in-time messages and step goal adjustments to improve compliance. Further studies on the use of DiPS in the design of physical activity promotion programs are warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01280812 Registered on January 21, 2011.

A loyalty scheme to encourage physical activity in office workers: a cluster RCT

Background

Increasing physical activity in the workplace can provide physical and mental health benefits for employees and economic benefits for the employer through reduced absenteeism and increased productivity. However, there is limited evidence on effective behaviour change interventions in workplace settings that led to maintained physical activity. This study aimed to address this gap and contribute to the evidence base for effective and cost-effective workplace interventions.

Objectives

To determine the effectiveness and cost-effectiveness of the Physical Activity Loyalty scheme, a multicomponent intervention based on concepts similar to those that underpin a high-street loyalty card, which was aimed at encouraging habitual physical activity behaviour and maintaining increases in mean number of steps per day.

Design

A cluster randomised controlled trial with an embedded economic evaluation, behavioural economic experiments, mediation analyses and process evaluation.

Setting

Office-based employees from public sector organisations in Belfast and Lisburn city centres in Northern Ireland.

Participants

A total of 853 participants [mean age 43.6 years (standard deviation 9.6 years); 71% of participants were female] were randomly allocated by cluster to either the intervention group or the (waiting list) control group.

Intervention

The 6-month intervention consisted of financial incentives (retail vouchers), feedback and other evidence-based behaviour change techniques. Sensors situated in the vicinity of the workplaces allowed participants to monitor their accumulated minutes of physical activity.

Main outcome measures

The primary outcome was mean number of steps per day recorded using a sealed pedometer (Yamax Digiwalker CW-701; Yamax, Tasley, UK) worn on the waist for 7 consecutive days and at 6 and 12 months post intervention. Secondary outcomes included health, mental well-being, quality of life, work absenteeism and presenteeism, and the use of health-care resources.

Results

The mean number of steps per day were significantly lower for the intervention group than the control group [6990 mean number of steps per day (standard deviation 3078) vs. 7576 mean number of steps per day (standard deviation 3345), respectively], with an adjusted mean difference of –336 steps (95% confidence interval –612 to –60 steps; p = 0.02) at 6 months post baseline, but not significantly lower at 12 months post baseline. There was a small but significant enhancement of mental well-being in the intervention group (difference between groups for the Warwick–Edinburgh Mental Wellbeing Scale of 1.34 points, 95% confidence interval 0.48 to 2.20 points), but not for the other secondary outcomes. An economic evaluation suggested that, overall, the scheme was not cost-effective compared with no intervention. The intervention was £25.85 (95% confidence interval –£29.89 to £81.60) more costly per participant than no intervention and had no effect on quality-adjusted life-years (incremental quality-adjusted life-years –0.0000891, 95% confidence interval –0.008 to 0.008).

Limitations

Significant restructuring of participating organisations during the study resulted in lower than anticipated recruitment and retention rates. Technical issues affected intervention fidelity.

Conclusions

Overall, assignment to the intervention group resulted in a small but significant decline in the mean pedometer-measured steps per day at 6 months relative to baseline, compared with the waiting list control group. The Physical Activity Loyalty scheme was deemed not to be cost-effective compared with no intervention, primarily because no additional quality-adjusted life-years were gained through the intervention. Research to better understand the mechanisms of physical activity behaviour change maintenance will help the design of future interventions.

Trial registration

Current Controlled Trials ISRCTN17975376.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 7, No. 15. See the NIHR Journals Library website for further project information.