The goal was to improve the amount of activity undertaken at work. We used pedometers to measure activity. A pedometer will always be a pedometer. It will always be something you wear to record a step count. Adding tonnes of bells and whistles to it will be of little advantage if we don’t know how to use them to motivate behaviour change. Persuasive technology: Behaviour change is a psychological problem. Must be done with knowledge of the psych lit. Behaviour change brought about through how people use the technology – not the technology itself.
Bad thing Conversely, exercise helps Considering so much time is spent at work, it may prove advantageous to build exercise into this time rather than social time. So, rather than encouraging people to go for walks, might be easier to encourage them to take the stairs.
Chan et al ran a study where there were two groups – one which involved health education (control group), and the other personal/team goal setting (intervention group). Analysis of the study‟s activity data revealed that 51% of participants in the intervention group met the US governments recommendations compared to 31% in the control group.
A - participants could see their friends‟ step data as well as their own B - participants could only see their own personal step activity.
So, it seems the social properties were most attended-to.
Motivating Physical Activity at Work using Social Media
Motivating physical activity at work: Using persuasive social media for competitive step counting Derek Foster, Conor Linehan, Shaun Lawson, Gary James Lincoln Social Computing Research Centre
Introduction <ul><li>Sustainability: </li></ul><ul><ul><li>a new device for every identified problem is not a good idea. </li></ul></ul><ul><li>Behaviour change can be brought about through: </li></ul><ul><ul><li>Simple, accessible technology </li></ul></ul><ul><ul><li>Concentration on psychological processes </li></ul></ul><ul><li>Whether online social interaction & competition can improve users activity levels. </li></ul><ul><li>Case Study: Walking at Work </li></ul>
Structure <ul><li>Background – Exercise at work </li></ul><ul><li>Background – Pedometers as health interventions </li></ul><ul><li>Method – Participants & Design </li></ul><ul><li>Method - Materials (i.e. devices, apps) </li></ul><ul><li>Results </li></ul><ul><li>Discussion </li></ul><ul><li>Conclusion </li></ul>
Exercise at work <ul><li>Modern lifestyles are becoming increasingly sedentary - only 11.6% of UK adults are classed as physically active. </li></ul><ul><li>Physical exercise has been shown to improve health conditions such as heart disease and depression. </li></ul><ul><li>Figures suggest that UK workers spend up to 60% of their waking hours at work. </li></ul><ul><li>There is scope to utilise some of this non-social time to encourage more physical activity </li></ul>
Pedometers as health interventions <ul><li>Chan et al. (2004) - 1442 employees over a 12 week period. Pedometers used to measure effects of two intervention types. </li></ul><ul><li>Found that social interactions & competitiveness may have increased participant step count. </li></ul><ul><li>No technology used for feedback - social and competitive feedback presented to participants was indirect, infrequent and over a long period of time….. </li></ul><ul><li>… ..More direct and frequent feedback, could lead to more positive gains in physical activity. </li></ul>
Study <ul><li>So, we used pedometers to record activity of nurses at work over 21 days </li></ul><ul><li>An application, developed using the Facebook API, was used to record step-counts for each day over the course of the study. </li></ul><ul><li>Condition A, socially enabled - could see their friends’ step data as well as their own </li></ul><ul><li>Condition B there were no social features available - only see their own step activity </li></ul><ul><li>Hypothesis - participants would be more active when using the socially enabled condition </li></ul>
Method – Participants <ul><li>Participants: Ten Registered Nurses (Nine females and one male) recruited through personal contact. </li></ul><ul><li>Regular users of Facebook for the past 12 months. </li></ul><ul><li>Were given a pedometer and asked to wear it during working hours. </li></ul><ul><li>Also asked to record step-count after a shift using the facebook app. </li></ul>
Method – Design <ul><li>Independent Variable - interaction mode, either social or non-social. </li></ul><ul><li>Dependent Variable - the number of steps taken by each participant, with a total step count being recorded in each condition for each participant. </li></ul><ul><li>Repeated measures design </li></ul><ul><li>Each participant experienced both conditions, and order effects were controlled for as carefully as possible. </li></ul>
Method - Materials <ul><li>Pedometer - commercial off-the-shelf pedometer – the ‘Silva Ex3 plus’ (£20) </li></ul><ul><li>Small, robust ‘accelerometer’ based pedometer that easily fits in pocket or around neck with strap </li></ul>
Method - Materials <ul><li>Leveraged the Facebook API and external SQL database to implement Stepmatron </li></ul><ul><li>Nurses add Stepmatron to their Facebook profile to access and share their step activity data </li></ul><ul><li>Features include a step input interface, a rankings interface and a comments board </li></ul><ul><li>Stepmatron sends notification updates to users when their friends update their step activity or post comments </li></ul><ul><li>Only technology required is the pedometer and a web browser </li></ul>
Method - Materials Stepmatron user steps input interface Comments board for rankings interface
Results <ul><li>9/10 participants walked more steps in the social condition than in the non-social condition, with mean step ratings of 42004.4 and 38132.1 for social and non-social conditions respectively. </li></ul><ul><li>A Wilcoxon test showed that the total number of steps taken was significantly higher when participants used the social condition (Z= -2.5, N=10, p=0.013). </li></ul>
Results <ul><li>Google Analytics - In the 21 days the experiment was run, there were 1142 pages views, with 224 unique visits to the Step Matron application, equalling 5 page views per visit. The average time spent during each visit was 6 minutes 11 seconds. </li></ul><ul><li>User generated comments indicated participants were engaged in playful disclosure of information on their own activity and reciprocated comments from friends </li></ul>
Results <ul><li>User comments </li></ul><ul><ul><li>Competition : “ ooooh im number 1 so far :-) ” and “ hay, im number one. not bad for a lazy **** hole like me lol ”. </li></ul></ul><ul><ul><li>Motivation : “ we have walked 7 miles between us not bad eh? X ” and “ hahaha well done [name omitted]!! ” </li></ul></ul><ul><ul><li>External motivation : ” was out dancing fri night, can you imagine how many steps that would have been!!! ” with a response showing empathy over the ‘lost’ steps, “ aaahhh shame! Wouldve bin loads x ” </li></ul></ul>
Discussion <ul><li>Participants recorded a significantly higher number of steps in the social condition </li></ul><ul><li>- This suggests that social interaction over an online social network, such as viewing each other’s step counts, comparing own usage to that of peers, and commenting on each other’s progress, can help motivate participants to increase physical activity in the workplace. </li></ul>
Discussion <ul><li>Simple mobile devices can function as successful triggers for positive behaviour change, when delivered as part of a larger programme. </li></ul><ul><li>Participants only had access to a simple digital read-out during working hours. - it is apparent that the competitive activities occasioned by the Facebook application were not only in action while participants used the application. </li></ul>
Discussion <ul><li>Also demonstrates that social network applications can serve as a powerful context that allows participants to understand quantitative behavioural measures as more than mere numbers </li></ul>
Conclusion <ul><li>The current study demonstrates that the carefully considered combination of two simple technological elements, informed by an understanding of successful behaviour modification programmes, can be effective in motivating behaviour change. </li></ul>
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