None listed
Conditions
Brief summary
Behavioural eHealth and mHealth interventions have been moderately successful in increasing physical activity. Therefore, there is still room for further improvement. Chatbots equipped with natural language processing can effectively interact and engage with users. Chatbots can also help continuously self-monitor physical activity levels using data from wearable body sensors and smartphones. However, there is lack of studies evaluating effectiveness of chatbot interventions on physical activity. The aim of this study was to investigate the feasibility, acceptability and effectiveness of an interactive machine learning based chatbot that uses natural language processing and adaptive goal setting to improve physical activity among inactive adults living in Australia.
Interventions
The intervention used a chatbot deployed via Facebook Messenger to help participants increase their physical activity. A quasi-experimental design was conducted with outcomes evaluated at two time points: baseline and six weeks after participants started to use the chatbot. Participants provided their time preferences (up to 3 times per day) when they received a push message from the chatbot. Participants were encouraged to self-initiate contact with the chatbot as much as they could. Push notif
The intervention used a chatbot deployed via Facebook Messenger to help participants increase their physical activity. A quasi-experimental design was conducted with outcomes evaluated at two time points: baseline and six weeks after participants started to use the chatbot. Participants provided their time preferences (up to 3 times per day) when they received a push message from the chatbot. Participants were encouraged to self-initiate contact with the chatbot as much as they could. Push notifications included different messages updating participants about their physical activity level at the time of delivery and also encouraging them to add physical activity to meet their daily goal. Participants could ask the chatbot about benefits of physical activity and were provided relevant sources of information. Participants used their own phone but were provided the Fitbit Flex 1 to measure their daily step. Adherence was assessed using questionnaires at post-intervention. No educational material was developed for use with the chatbot. However, if participants asked for information about physical activity, the chatbot referred participants to relevant source of information from the internet so that participants could self-educate themselves.
Sponsors
Central Queensland University
Study design
Allocation
Non-randomised trial
Intervention model
Single group
Primary purpose
Treatment
Masking
Open (masking not used)
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
Be inactive (less than 20 minutes/day of moderate to vigorous physical activity), live in Australia, have internet access and a smartphone, be at least 18 years old, motivated to improve physical activity, not already participating in another physical activity program, not already owning and used a physical activity tracking device (e.g., pedometer, Fitbit, Garmin), and able to safely increase their activity levels.
Exclusion criteria
Those with health conditions preventing them from increasing physical activity.
Outcome results
None listed