Sharing physical activity data with friends and peers and participating in team-based physical activity games have been an emerging research theme in HCI and non-HCI literature in the past few years. The following sections review some examples published in the HCI literature that have applied the power of participating in physical activity as a team, social sharing and peer support.
Playfulness and enjoyment are important for the achievement of changes in physical activity levels because they stimulate positive emotional states that help to motivate increased physical activity \cite{Blytheetal04}. Several physical activity games attempt to make use of this effect. In one such game, Fish’n’Steps \cite{Linetal06}, users are presented with a fish avatar whose growth, emotional state and behaviour reflects the participant’s recent physical activity. Moreover, Fish’n’Steps includes behavioural goals in a team-based game, with the team-members being responsible for the health and growth of their fish in a shared fish tank. Consistent with the findings in Blyth et al. \cite{Blytheetal04}, the evaluation of Fish‘n’Steps showed rather than provoking increased physical activity, an unhappy avatar (sad or unhealthy looking fish in this example) could cause users to simply stop using an app. In Neat-O-Game \cite{Fujikietal07}, a wearable accelerometer provides data that is used to control an avatar that represents the player in a virtual race. Multiple players can participate in Neat-O-Game. Winners are declared on a daily basis and players can use activity points that they have gained to receive hints in mental games such as Sudoku that are included in the app. In a different example, rather than trying to motivate individuals to reduce the time spent on sedentary activities, Berkovsky et al. \cite{Berkovskyetal09b} focus on integrating physical activity into the predominantly sedentary activity of computer gaming. Berkovsky et al. \cite{Berkovskyetal09b} integrate a novel game design called “Play, Mate!” into an open source game called Neverball and raise players’ motivation by increasing the difficulty of the game and including elements of physical activity. Berkovsky et al. \cite{Berkovskyetal09b} conducted an experimental evaluation of Neverball involving 180 users aged 9 to 12 unfamiliar with this game. They divided participants into two groups: 90 played the sedentary version of Neverball and 90 played the active version of Neverball. The experiment showed that children performed more physical activity and decreased sedentary playing time when they used the active version of Neverball. Furthermore, children did not report any reduction in their enjoyment of playing.
Social games, which encourage physical activity, are not limited to desktop or fixed platforms. Such games are rapidly growing in the smartphone market. For example, Ahtinen et al. \cite{Ahtinenetal10} designed a team-based mobile wellness app called “Into”, which visualised the number of steps for its users with an analogy of a virtual trip from one place to another. As the team members took steps, the application combined the achievements of each team member and visualised the combined progress as a trip between the departure and destination places. Ahtinen et al. conducted a qualitative pilot study with 37 participants (a total of 12 people in four teams) over a period of one week. The more participants took steps, the quicker the line between the places turned to green (achieved goal). The line between the departure and destination places reflected the true distance between the places in the physical world, and respectively the users needed to take as many steps together as the real distance required. The findings from this study showed that setting departure and destination places and viewing up-to-date progress between them can motivate individuals. However, Ahtinen et al. did not report on the impact of feedback and or goal-settings on physical activity.
There is an abundance of research in HCI literature relating to social sharing as a tactic to increase awareness and to promote physical activity \cite{Andersonetal07,Consolvoetal06,harries2013,ToscosFaber06}. For example, Shakra \cite{Andersonetal07}, Houston \cite{Consolvoetal06}, and Chick-Clique \cite{ToscosFaber06} not only allow individuals to self-monitor and set personal goals but also allow groups of friends to share performance data using mobile platforms. These systems integrate social influence through social facilitation and social support. bActive, a smartphone app \cite{harries2013}, employs a social norms approach, showing people what other people do, in order to influence them. Harries et al. investigated this approach amongst 152 young to early middle-age men through a rigorous and large-scale field trial. Unlike most similar active-lifestyle apps, bActive does not need to be activated prior to participating in physical activity and needs no special additional equipment. As a result, it requires minimal initial commitment from the user. The longitudinal data analysis of 6-week randomised control trial of the bActive shows that the number of steps the 22-40 year-old participants walked was 64% higher, on average, if they used the bActive app.
Foster et al. \cite{Fosteretal10} included the social sharing feature in Step Marton, a Facebook app, to create social and competitive context for daily pedometer readings in order to motivate physical activity at the workplace. They studied two versions of the app (social vs. individual) with 10 nurses (1 male) over a period of 21 days and claimed that the total number of steps taken was significantly higher when participants used the social condition (\(Z= -2.5, N=10, p=0.013\)).
Unlike games such as Fish’n’Steps \cite{Linetal06} where the competition is explicitly introduced, Houston \cite{Consolvoetal06} and Chick-Clique \cite{ToscosFaber06} users do not explicitly compete with one another but can view and comment on the progress of their peers. During a three-week evaluation of Houston with young female friends (N=13) Consolvo et al. claimed that the sharing groups were significantly more likely to meet their goal (\(t=2.60, p < 0.05\)). They also reported that average daily step counts increased from the baseline week to the two weeks for seven participants in social sharing groups with goal sharing: daily averages exhibited increases from between 5% to 61% extra steps (median increase: 30%); the average daily step count increased from 180 to 4,587 steps/day (median: 2,234). Shakra \cite{Andersonetal07} tracks the daily physical activities of people, using an Artificial Neural Network (ANN) to classify different activities throughout the day. In a short-term study (10 days) of the prototype that shared activity information amongst groups of friends and or co-workers (an average of three people in three groups), Anderson et al. reported that awareness encouraged reflection on, and increased motivation for, daily activity. In Chick-Clique \cite{ToscosFaber06} the step counts of teenage girls were recorded by pedometers and automatically transmitted to peers’ and friends’ PDAs for sharing. Some teenagers participated in this study expressed concern with regards to negative effects of competition i.e. excessive physical activity levels damaging their friendship. However, some said that it helped them to become more comfortable about talking about physical activity engagement with their friends.
Although there are many examples in the HCI literature which have included social sharing to promote physical activity behaviour change, the effectiveness of this method is unconvincing. For example, the relatively short but big sample size in the bActive study did not find any evidence to suggest that social norms are an essential component of such an app; instead the study found that the impact of feedback limited to individual performance exhibited no significant difference to that of feedback that also included social data. The relatively short data collection periods and small sample size utilized raise questions about the claims made for Step Marton, Houston and Chick-Clique. Moreover, given the lack of precision both in terms of assessing baseline levels and the limited time period over which Houston study data were collected raises doubts over the efficacy of the conclusions drawn, and the sustainability of the changes observed. As with the Shakra pilot study Anderson et al. only observed some encouragement among ‘buddies’ and, in some cases, strong competition but they did not do and or report any quantitative or qualitative analysis on physical activity measures.