Background: The Carrot Rewards app was developed as part of a public-private partnership to reward Canadians with loyalty points for downloading the app, referring friends, completing educational health quizzes, and health-related behaviors with long-term objectives of increasing health knowledge and encouraging healthy behaviors. During the first 3 months after program rollout in British Columbia, a number of program design elements were adjusted, creating observed differences between groups of users with respect to the potential impact of program features on user engagement levels.
Objective: This study examines the impact of reducing reward size over time and explored the influence of other program features such as quiz timing, health intervention content, and type of reward program on user engagement with a mobile health (mHealth) app.
Methods: Participants in this longitudinal, nonexperimental observational study included British Columbia citizens who downloaded the app between March and July 2016. A regression methodology was used to examine the impact of changes to several program design features on quiz offer acceptance and engagement with this mHealth app.
Results: Our results, based on the longitudinal app use of 54,917 users (mean age 35, SD 13.2 years; 65.03% [35,647/54,917] female), indicated that the key drivers of the likelihood of continued user engagement, in order of greatest to least impact, were (1) type of rewards earned by users (eg, movies [+355%; P<.001], air travel [+210%; P<.001], and grocery [+140%; P<.001] relative to gas), (2) time delay between early offers (-64%; P<.001), (3) the content of the health intervention (eg, healthy eating [-10%; P<.001] vs exercise [+20%, P<.001] relative to health risk assessments), and (4) changes in the number of points offered. Our results demonstrate that reducing the number of points associated with a particular quiz by 10% only led to a 1% decrease in the likelihood of offer response (P<.001) and that each of the other design features had larger impacts on participant retention than did changes in the number of points.
Conclusions: The results of this study demonstrate that this program, built around the principles of behavioral economics in the form of the ongoing awarding of a small number of reward points instantly following the completion of health interventions, was able to drive significantly higher engagement levels than those demonstrated in previous literature exploring the intersection of mHealth apps and financial incentives. Previous studies have demonstrated the presence of incentive matters to user engagement; however, our results indicate that the number of points offered for these reward point-based health interventions is less important than other program design features such as the type of reward points being offered, the timing of intervention and reward offers, and the content of the health interventions in driving continued engagement by users.
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http://dx.doi.org/10.2196/16797 | DOI Listing |
Int J Lang Commun Disord
January 2025
Division of Communication Sciences and Disorders, University of Cape Town, Rondebosch, South Africa.
Background: There is a global need for synthetic speech development in multiple languages and dialects, as many children who cannot communicate using their natural voice struggle to find synthetic voices on high-technology devices that match their age, social and linguistic background.
Aims: To document multiple stakeholders' perspectives surrounding the quality, acceptability and utility of newly created synthetic speech in three under-resourced South African languages, namely South African English, Afrikaans and isiXhosa.
Methods & Procedures: A mixed methods research design was selected.
Sensors (Basel)
January 2025
Department of Instruction and Leadership, Duquesne University, Pittsburgh, PA 15282, USA.
This article examines how sensor technologies (such as environmental sensors, biometric sensors, and IoT devices) intersect with conversational AI models like ChatGPT 4.0. In particular, this article explores how data from different sensors in real time can improve AI models' comprehension of surroundings, user contexts, and physical conditions.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Public Health Sciences, Clemson University, Clemson, SC, USA.
Background: Rich data on diverse patients and their treatments and outcomes within Electronic Health Record (EHR) systems can be used to generate real world evidence. A health recommender system (HRS) framework can be applied to a decision support system application to generate data summaries for similar patients during the clinical encounter to assist physicians and patients in making evidence-based shared treatment decisions.
Objective: A human-centered design (HCD) process was used to develop a HRS for treatment decision support in orthopaedic medicine, the Informatics Consult for Individualized Treatment (I-C-IT).
Eur J Pharmacol
January 2025
Internal Medicine Office, Medical Education Centre, Western General Hospital, Edinburgh EH4 2XU, UK. Electronic address:
The IUPHAR Education Committee's Pharmacology Education Project (PEP; www.pharmacologyeducation.org) provides an open-access, peer-reviewed platform to support pharmacology education globally.
View Article and Find Full Text PDFTraffic Inj Prev
January 2025
National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Centre, Beijing, China.
Objective: Attention forms the foundation for the formation of situation awareness. Low situation awareness can lead to driving performance decline, which can be dangerous in driving. The goal of this study is to investigate how different types of pre-takeover tasks, involving cognitive, visual and physical resources engagement, as well as individual attentional function, affect driver's attention restoration in conditionally automated driving.
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