Examining Responsiveness to an Incentive-Based Mobile Health App: Longitudinal Observational Study

Unveiling Consumer Preferences and Intentions for Cocreated Features of a Combined Diet and Physical Activity App: Cross-Sectional Study in 4 European Countries

BACKGROUND

Numerous mobile health apps are marketed globally, and these have specific features including physical activity tracking, motivational feedback, and recipe provision. It is important to understand which features individuals prefer and whether these preferences differ between consumer groups.

OBJECTIVE

In this study, we aimed to identify consumers' most preferred features and rewards for a mobile app that targets healthy eating and physical activity and to reduce the number of individual mobile health app features to a smaller number of key categories as perceived by consumers. In addition, we investigated the impact of differences in consumers' BMI and self-efficacy on their intention to use and willingness to pay for such an app. Finally, we identified the characteristics of different target groups of consumers and their responses toward app features via cluster analysis.

METHODS

A total of 212 participants from France, Italy, the United Kingdom, and Germany were recruited via the web to answer questions about app features, motivation, self-efficacy, demographics, and geographic factors. It is important to note that our study included an evenly distributed sample of people in the age range of 23 to 50 years (23-35 and 35-50 years). The app features in question were generated from a 14-day cocreation session by a group of consumers from the United Kingdom and the Republic of Ireland.

RESULTS

"Home work out suggestions," "exercise tips," and "progress charts" were the most preferred app features, whereas "gift vouchers" and "shopping discounts" were the most preferred rewards. "Connections with other communication apps" was the least preferred feature, and "charitable giving" was the least preferred reward. Importantly, consumers' positive attitude toward the "social support and connectedness and mindfulness" app feature predicted willingness to pay for such an app (β=.229; P=.004). Differences in consumers' health status, motivational factors, and basic demographics moderated these results and consumers' intention to use and willingness to pay for such an app. Notably, younger and more motivated consumers with more experience and knowledge about health apps indicated more positive attitudes and intentions to use and willingness to pay for this type of app.

CONCLUSIONS

This study indicated that consumers tend to prefer app features that are activity based and demonstrate progress. It also suggested a potential role for monetary rewards in promoting healthy lifestyle behaviors. Moreover, the results highlighted the role of consumers' health status, motivational factors, and socioeconomic status in predicting their app use. These results provide up-to-date, practical, and pragmatic information for the future design and operation of mobile health apps.

Reduction of Financial Health Incentives and Changes in Physical Activity

Importance

Governments and others continue to use financial incentives to influence citizen health behaviors like physical activity. However, when delivered on a population scale they can be prohibitively costly, suggesting more sustainable models are needed.

Objectives

To evaluate the association of incomplete financial incentive withdrawal ("schedule thinning") with physical activity after more than a year of incentive intervention and to explore whether participant characteristics (eg, app engagement and physical activity) are associated with withdrawal outcomes.

Design, Setting, and Participants

This case-control study with a pre-post quasi-experimental design included users of a government-funded health app focused on financial incentives. Eligible participants were residents in 3 Canadian provinces over 25 weeks in 2018 and 2019. Data were analyzed from July 2021 to December 2022.

Exposure

Due to fiscal constraints, financial incentives for daily physical activity goals were withdrawn in Ontario in December 2018 (case)-representing a 90% reduction in incentive earnings-but not in British Columbia or Newfoundland and Labrador (controls).

Main Outcome and Measures

The primary outcome was objectively assessed weekly mean daily step count. Linear regression models were used to compare pre-post changes in daily step counts between provinces (a difference-in-differences approach). Separate models were developed to examine factors associated with changes in daily step count (eg, app engagement and physical activity). Clinically meaningful initial effect sizes were previously reported (approximately 900 steps/d overall and 1800 steps/d among the physically inactive).

Results

In total there were 584 760 study participants (mean [SD] age, 34.3 [15.5] years; 220 388 women [63.5%]), including 438 731 from Ontario, 124 101 from British Columbia, and 21 928 from Newfoundland and Labrador. Significant physical activity declines were observed when comparing pre-post changes in Ontario to British Columbia (-198 steps/d; 95% CI, -224 to -172 steps/d) and Newfoundland and Labrador (-274 steps/d; 95% CI, -323 to -225 steps/d). The decrease was most pronounced for highly engaged Ontario users (-328 steps/d; 95% CI, -343 to -313 steps/d). Among physically inactive Ontario users, physical activity did not decline following withdrawal (107 steps/d; 95% CI, 90 to 124 steps/d).

Conclusions and Relevance

In this case-control study of incomplete financial incentive withdrawal, statistically significant daily step count reductions were observed in Ontario; however, these declines were modest and not clinically meaningful. Amidst substantial program savings, the physical activity reductions observed here may be acceptable to decision-makers working within finite budgets.

Engagement With mHealth COVID-19 Digital Biomarker Measurements in a Longitudinal Cohort Study: Mixed Methods Evaluation

BACKGROUND

The COVID-19 pandemic accelerated the interest in implementing mobile health (mHealth) in population-based health studies, but evidence is lacking on engagement and adherence in studies. We conducted a fully remote study for ≥6 months tracking COVID-19 digital biomarkers and symptoms using a smartphone app nested within an existing cohort of adults.

OBJECTIVE

We aimed to investigate participant characteristics associated with initial and sustained engagement in digital biomarker collection from a bespoke smartphone app and if engagement changed over time or because of COVID-19 factors and explore participants' reasons for consenting to the smartphone substudy and experiences related to initial and continued engagement.

METHODS

Participants in the Fenland COVID-19 study were invited to the app substudy from August 2020 to October 2020 until study closure (April 30, 2021). Participants were asked to complete digital biomarker modules (oxygen saturation, body temperature, and resting heart rate [RHR]) and possible COVID-19 symptoms in the app 3 times per week. Participants manually entered the measurements, except RHR that was measured using the smartphone camera. Engagement was categorized by median weekly frequency of completing the 3 digital biomarker modules (categories: 0, 1-2, and ≥3 times per week). Sociodemographic and health characteristics of those who did or did not consent to the substudy and by engagement category were explored. Semistructured interviews were conducted with 35 participants who were purposively sampled by sex, age, educational attainment, and engagement category, and data were analyzed thematically; 63% (22/35) of the participants consented to the app substudy, and 37% (13/35) of the participants did not consent.

RESULTS

A total of 62.61% (2524/4031) of Fenland COVID-19 study participants consented to the app substudy. Of those, 90.21% (2277/2524) completed the app onboarding process. Median time in the app substudy was 34.5 weeks (IQR 34-37) with no change in engagement from 0 to 3 months or 3 to 6 months. Completion rates (≥1 per week) across the study between digital biomarkers were similar (RHR: 56,517/77,664, 72.77%; temperature: 56,742/77,664, 73.06%; oxygen saturation: 57,088/77,664, 73.51%). Older age groups and lower managerial and intermediate occupations were associated with higher engagement, whereas working, being a current smoker, being overweight or obese, and high perceived stress were associated with lower engagement. Continued engagement was facilitated through routine and personal motivation, and poor engagement was caused by user error and app or equipment malfunctions preventing data input. From these results, we developed key recommendations to improve engagement in population-based mHealth studies.

CONCLUSIONS

This mixed methods study demonstrated both high initial and sustained engagement in a large mHealth COVID-19 study over a ≥6-month period. Being nested in a known cohort study enabled the identification of participant characteristics and factors associated with engagement to inform future applications in population-based health research.

Recruitment and retention in mobile application-based intervention studies: a critical synopsis of challenges and opportunities

Use of mobile health applications (mHealth apps) is becoming increasingly popular for the management of chronic illnesses, but mHealth-based intervention studies often have limitations associated with subject recruitment and retention. In this synopsis, we focus on targeted aspects of mHealth-based intervention studies, specifically: (i) subject recruitment, (ii) cohort sizes, and (iii) retention rates. We used the Google Scholar (meta-search) and Galileo search engines to identify sample articles focusing on mHealth apps and interventions published between 2010 and 2020 and selected 21 papers for detailed review. Most studies recruited relatively small cohorts (minimum: 20, maximum: 510). Retention rates had high variance with only five studies managing >80% subject retention throughout the study duration, 10.4% being the lowest. Eighty-five percent of the studies expressed concerns regarding study duration, app usage, and lack of proper implementation. The use of mHealth interventions generally yielded positive outcomes, but most studies discussed facing challenges associated with recruitment and retention. There is a clear need to identify strategies for recruiting larger cohorts and improving retention rates, and ultimately increasing the reliability of mHealth app-based intervention studies. We advise that potential underutilized opportunities lie at the intersection of mHealth and social media to address the limitations identified in the synopsis.

Factors impacting the use of the NZ COVID Tracer application in New Zealand"

The COVID-19 pandemic has clearly created devastating damage on world economics and public health. This project identifies key concerns of end-users toward the NZ COVID-19 contact tracing app in New Zealand. The key research objective in this study is to understand the usage behaviour towards the mobile application NZ COVID-19 Tracer used for contact tracing purposes. Secondly, the study explores the reasons for using the contact tracing app. Thirdly, it examines the relationship between usage behaviour of the NZ-COVID Tracer app with age, the user's perceived health, attitude towards COVID-19, whether family or friends are infected by COVID-19, trust in maintaining social distancing, trust in data privacy, smartphone usage and the media's role in motivating people to use this app. Consequently, understanding these issues and challenges could help improve the usage of this contact tracing app, which in turn would contribute to better public health outcomes in disease management and containment. Findings of the study reveals that age, smartphone usage behaviour, and trust in privacy data protection from the app provider has a statistically significant relationship on usage behaviour of the NZ COVID Tracer app. Self-perceived health status and attitudes towards the COVID-19 pandemic did not have a significant relationship on NZ COVID Tracer app usage behaviour. While social media, such as Facebook, has been shown to be the most popular source of news for COVID-19 among New Zealanders, it is television that acted as a motivational tool to encourage people to use the contact tracing mobile application and to practice other measures to help protect against the COVID-19 pandemic.

Active Use and Engagement in an mHealth Initiative Among Young Men With Obesity: Mixed Methods Study

Background

The effectiveness of mobile health (mHealth) approaches that employ wearable technology to promote physical activity have been the subject of concern due to the declining active use observed in trial settings.

Objective

To better contextualize active use, this study aimed to identify the barriers and enablers to engagement in a tracker-based mHealth initiative among young men who had recently completed a 19-week residential weight loss program.

Methods

A mixed methods study was conducted among 167 young men who had voluntarily enrolled in the national steps challenge (NSC), an mHealth physical activity promotion initiative, following a residential weight loss intervention. A subsample of 29 enrollees with a body mass index of 29.6 (SD 3.1) participated in semistructured interviews and additional follow-up assessments. Quantitative systems data on daily step count rates were used to describe active use. Qualitative data were coded and analyzed to elicit barriers and enablers to microlevel engagement in relation to the NSC, focusing on tracker and smartphone use. We further elicited barriers and enablers to macrolevel engagement by exploring attitudes and behaviors toward the NSC. Using triangulation, we examined how qualitative engagement in the NSC could account for quantitative findings on active use. Using integration of findings, we discussed how the mHealth intervention might have changed physical activity behavior.

Results

Among the 167 original enrollees, active use declined from 72 (47%) in week 1 to 27 (17%) in week 21. Mean daily step counts peaked in week 1 at 10,576 steps per day and were variable throughout the NSC. Barriers to engagement had occurred in the form of technical issues leading to abandonment, device switching, and offline tracking. Passive attitudes toward step counting and disinterest in the rewards had also prevented deeper engagement. Enablers of engagement included self-monitoring and coaching features, while system targets and the implicit prospect of reward had fostered new physical activity behaviors.

Conclusions

Our study showed that as the NSC is implemented in this population, more emphasis should be placed on technical support and personalized activity targets to promote lasting behavior change.

Understanding the user: Patients’ perception, needs, and concerns of health apps for chronic constipation

Objective

Chronic constipation is a prevalent gastrointestinal disorder that requires long-term management and treatment adherence. With increasing smartphone usage, health app adoption represents an opportunity to incorporate personalized, patient-led care into chronic constipation management. Despite the number of apps available targeting patients with constipation, studies have not yet examined user needs and barriers towards successful app adoption and sustained usage. Accordingly, the current study explored user perception, needs, and concerns of health apps in patients with chronic constipation.

Methods

Fifteen participants with chronic constipation (age range = 28–79 years, 10 females) in Singapore completed a 60 min semi-structured qualitative interview exploring participant's experiences with and attitudes towards chronic constipation and health apps. Participants also completed two questionnaires regarding their constipation symptoms and general technology usage. Interviews were audio-recorded, transcribed verbatim, and coded using NVivo.

Results

Four themes and 10 sub-themes were identified using inductive thematic analysis. Themes and sub-themes cover importance of patient identity, disease-based expectations of health apps, barriers towards adoption and sustained usage of health apps, necessary conditions when adopting health apps (including perception of supportive benefits, clear understanding of app intention, personalized technology, and trusted sources), and push factor expectations which includes creative engagement and incentivization embedded within the app.

Conclusion

The findings captured barriers and key elements necessary for successful health app adoption and continued usage by patients with chronic constipation. Identified elements that matter to patients can provide app developers with user-focused insights and recommendations to develop effective health apps that sustain user engagement.

Engagement in Digital Mental Health Interventions: Can Monetary Incentives Help?

Digital mental health interventions (DMHI) are scalable and cost-effective strategies for increasing access to mental health care; however, dropout rates associated with digital interventions are high, particularly for open-access digital interventions. While some studies have focused on predictors of dropout from digital mental health programs, few studies have focused on engagement features that might improve engagement. In this perspective article, we discuss whether monetary incentives (MI) are one avenue to increasing user engagement in DMHI. We begin by reviewing the literature on the effects of MI for behavior change in health domains (e.g., dietary behaviors, substance use, and medication adherence). Then, drawing on a pilot study we conducted to test the effects of different levels of MI on usage and improvement in subjective well-being among users of a DMHI (Happify), we discuss the potential applications of MI for DMHI, the potential drawbacks of financial incentives in this context, and open questions for future research.

Is it worth it? Cost-effectiveness analysis of a commercial physical activity app

BACKGROUND

Government interest in investing in commercial physical activity apps has increased with little evidence of their cost-effectiveness. This is the first study to our knowledge to examine the cost-effectiveness of a commercial physical activity app (Carrot Rewards) despite there being over 100,000 in the major app stores.

METHODS

A cost-effectiveness analysis was performed to calculate the incremental cost-effectiveness ratio (ICER) of the app compared to a no-intervention reference scenario using a five-year time horizon. Primary data was collected between 2016 and 2017. Data synthesis, model creation, and statistical analyses were conducted between 2019 and 2020. An age-, sex-, and geography-dependent Markov model was developed assuming a public healthcare payer perspective. A closed cohort (n = 38,452) representing the population reached by Carrot Rewards in two Canadian provinces (British Columbia, Newfoundland & Labrador) at the time of a 12-month prospective study was used. Costs and effects were both discounted at 1.5% and expressed in 2015 Canadian dollars. Subgroup analyses were conducted to compare ICERs between provinces, sexes, age groups, and engagement levels.

RESULTS

Carrot Rewards had an ICER of $11,113 CAD per quality adjusted life year (QALY), well below a $50,000 CAD per QALY willingness-to-pay (WTP) threshold. Subgroup analyses revealed that the app had lower ICERs for British Columbians, females, highly engaged users, and adults aged 35-64 yrs., and was dominant for older adults (65 + yrs). Deterministic sensitivity analyses revealed that the ICER was most influenced by the relative risk of diabetes. Probabilistic sensitivity analyses revealed varying parameter estimates predominantly resulted in ICERs below the WTP threshold.

CONCLUSIONS

The Carrot Rewards app was cost-effective, and dominant for older adults. These results provide, for the first time, rigorous health economic evidence for a commercial physical activity app as part of public health programming.

Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

Background

Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements.

Methods

A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week).

Results

The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; η_p² = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R² = 0.699) with each new STC corresponding to approximately 200 more steps per day.

Conclusion

Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01043-1.