Bachelor’s thesis, 15 ECTS
Bachelor programme in Cognitive Science, 180 ECTS Spring term 2021
Supervisors: Esteban Guerrero Rosero and Loïs Vanhée
INCREASING PHYSICAL ACTIVITY WITH GAMIFICATION: EXPLORING COMPETITIVENESS AS A MODERATOR
FOR LEADERBOARD EFFECTIVENESS
Fanny Danelid, Elin Fältman
1
First, we would like to thank our supervisors Loïs Vanhée and Esteban Guerrero Rosero for all your feedback. A big thank you to Fanny Järold who gave us feedback on the questionnaires. Finally, thank you to all of our participants.
2
Abstract
Gamification is a strategy for changing behavior that can be used for increasing physical activity (PA). In Sweden, 34% of the population are not active enough and since sedentary behavior is associated with many health risks, this needs to be improved. One gamification strategy is leaderboards, but most previous research has not looked at isolated gamification strategies. The behavior change effectiveness of leaderboards could increase by personalizing it based on traits. This study investigated the behavior change effectiveness of leaderboards and how individual differences in competitiveness affects the effectiveness. The following research questions were addressed: How effective are leaderboards for increasing physical activity in adults? Does competitiveness level impact a leaderboard’s effectiveness? This experimental study examined 24 participants who reported their PA during one week and were either in an experimental group that saw a leaderboard, or a control group. Their difference in PA before and during the study was compared. Results show that there was no significant difference between the control and experimental group. However, a within-subject significant difference in PA was found (i.e. a significant increase during the experiment) for the experimental group. Additionally, no correlation was found between change in PA and competitiveness. However, competitiveness correlated with enjoyment of the leaderboard.
Future studies should investigate more gamification strategies individually and in relation to other traits. Our conclusion is that the leaderboard did no harm, we did not observe the effectiveness claimed by other studies, and competitiveness had no impact on the effectiveness.
Keywords: gamification, leaderboard, physical activity, competitiveness, cognitive science
Sammanfattning
Spelifiering är en strategi för att ändra beteenden som kan användas för fysisk aktivitet (FA). I Sverige är 34% av befolkningen inte tillräckligt aktiva, och eftersom stillasittande beteende är associerat med många hälsoproblem behöver detta förbättras. En spelifieringsstategi är topplistor, men tidigare forskning har inte isolerat specifika spelifieringsstrategier.
Effektiviteten av topplistor kan öka genom individuell anpassning baserat på personlighetsdrag. Den här studien undersöker effektiviteten av topplistor och hur individuella skillnader i tävlingsinriktning påverkar effektiviteten. Följande forskningsfrågor undersöktes:
Hur effektiva är topplistor för att öka fysisk aktivitet hos vuxna? Påverkar nivån av tävlingsinriktning en topplistas effektivitet? Denna experimentella studie tittade på 24 deltagare som rapporterade in sin FA under en vecka och antingen var i en experimentgrupp som fick se en topplista eller en kontrollgrupp. Deras förändring i FA före och under studien jämfördes. Resultaten visade ingen signifikant skillnad i FA mellan grupperna. Men deltagarna i experimentgruppen hade en signifikant skillnad i FA (alltså en signifikant ökning under experimentet). Vi fann ingen korrelation mellan förändring i FA och tävlingsinriktning. Men tävlingsinriktning korrelerade med att tycka om att se topplistan. Framtida studier borde undersöka mer spelifieringsstrategier individuellt och i relation till andra personlighetsdrag.
Vår slutsats är att topplistan inte gjorde någon skada, den var inte så effektiv som tidigare studier hävdat, och att tävlingsinriktning inte påverkade effektiviteten.
Nyckelord: spelifiering, topplista, fysisk aktivitet, tävlingsinriktning, kognitionsvetenskap
3 Increasing Physical Activity with Gamification: Competitiveness as a Moderator for
Leaderboard Effectiveness
Gamification, defined as “the use of game design elements in non-game contexts'' (Deterding et al., 2011), can be used as a strategy for influencing behavior change (Johnson et al., 2016). Many different gamification strategies have been proposed, such as rewards, badges, points and leaderboards (Johnson et al., 2016). Leaderboards is one of the most common gamification strategies (Huang et al., 2020; Johnson et al., 2016), and is used in areas such as education and physical activity (PA), e.g. Duolingo and Strava. A leaderboard shows a list of participants ordered based on some variable with the participants with the best score at the top.
Social gamification strategies such as leaderboards help participants feel accomplished and empowered (Orji et al., 2019), and encourage competition (Höllig et al., 2020). Some studies have found positive results when using leaderboards (e.g. Call et al., 2021; Landers et al., 2017;
Ortiz-Rojas et al., 2019), while others have not (e.g. Hanus & Fox, 2015).
Gamification has been used for increasing PA (Johnson et al., 2016). The idea is that gamification would make PA more fun and motivating (Zuckerman & Gal-Oz, 2014). The World Health Organisation (WHO; 2018) recommends at least 150-300 minutes of moderate PA per week. Benefits of more PA include reduced risk of non-communicable diseases (e.g.
cardiovascular diseases, diabetes, cancer), reduced mortality risks, improved mental health, and better sleep (Folkhälsomyndigheten, 2020; WHO, 2020). Furthermore, PA can improve memory and concentration (Folkhälsomyndigheten, 2020). In Sweden, 34% of the population is physically active less than 150 minutes a week (Folkhälsomyndigheten, 2021). This implies a need for effective behavior change strategies to reduce physical inactivity.
Behavior change strategies in PA applications have difficulties with keeping people’s interest and engagement (Baretta et al., 2019). Therefore, a need for personalised gamification has been highlighted in Liu et al.’s (2017) design guidelines for gamification. Zuckerman and Gal-Oz (2014) also identifies the opportunities with personalised gamified applications and proposes competitiveness as a trait to investigate in regard to gamification.
Leaderboards incite competition greatly because they expose users to a comparison between their own and other users’ points (Höllig et al., 2020). Competition is defined as “a desire to win in interpersonal situations” (Helmreich & Spence, 1978, as cited in Harris &
Houston, 2010). Competitiveness can be seen as a trait that varies across time and contexts, where people have more or less desire to compete with others depending on the situation (Elliot et al., 2018). Another view is that personality traits, including competitiveness, generally are stable across situations (Krägeloh et al., 2018), but there might be situations that make even individuals with low trait competitiveness engage in competitions (Harris & Huston, 2010).
From now on, when we talk about competitiveness, we mean it in the sense of a stable trait.
Competitive people are more likely to use and enjoy a competitive gamification strategy, such as leaderboards (Amo et al., 2020; Höllig et al., 2020).
Further research is needed on the impact of individual gamification strategies (Johnson et al., 2016) since most gamification studies investigate applications that use several gamification strategies at the same time (e.g. Kappen et al., 2020; Maher et al., 2015).
Furthermore, few studies have had a control group when investigating gamification strategies (Johnson et al., 2016). A control group is additionally important because merely engaging in self-monitoring and reflection of one’s PA could be enough to promote an increase in PA (Zuckerman & Gal-Oz, 2014). Moreover, Liu et al. (2017) suggest that future studies should investigate how users respond to gamification depending on individual differences in personality traits.
Consequently, in this project we investigated the gamification strategy leaderboards
4 independently and compared it to a control group. Additionally, the project examined the leaderboard’s behavior change effect in relation to the trait competitiveness. This was investigated in a PA context where participants reported their active minutes every day for a week. With PA, the risk of overtraining emerges. However, the WHO (2020) concludes that health benefits from engaging in more PA outweighs potential risks. Seeing as this experiment’s duration was one week and participation was voluntary, the exposure to risks was minor. The project addresses the following two research questions:
● How effective are leaderboards for increasing physical activity in adults?
● Does competitiveness level impact a leaderboard’s effectiveness?
Leaderboards from a Cognitive Science Perspective
Several psychological and cognitive science theories can help explain why gamification, specifically leaderboards, might work. A psychology meta analysis showed that self-monitoring in combination with one or more other self-regulation techniques (e.g.
intention formation, setting goals, and getting feedback on performance) resulted in effective behavior change interventions for increasing PA (Michie et al., 2009). This indicates that a gamification strategy that employs these techniques should be effective.
Leaderboards invoke social comparison by showing an individual’s performance in relation to others (Arigo et al. 2020). Social comparison theory states that comparison is automatic (Klein & Rice, 2019) and can be directed upward, by looking at those who are better than oneself, or downwards, by looking at those who are worse off (Garcia et al., 2013).
According to Garcia et al. (2013), a feeling of competitiveness arises from how much one compares oneself to others. Comparison is decided by factors such as having a personal connection to one’s opponents, the relevance of the subject for oneself, how similar one is to one’s opponents, how close one is to the standard, and how many opponents there are (Garcia et al., 2013). Leaderboards provide its users with various options of comparison, both upwards and downwards. Furthermore, behavior change interventions that use social comparison have been able to increase step counts (Chapman et al., 2016).
Goal setting theory can also explain leaderboards (Landers et al., 2017). Goal setting involves judging one’s achievement based on the difference between one’s performance and the goal. Leaderboards function similarly to goal setting as they present users with various possible goals the user can strive towards (Landers et al., 2017). However, commitment to reach the goal impacts the effectiveness (Landers et al., 2017). Landers et al. (2017) found that leaderboards were as effective as explicitly given difficult or impossible goals if the leaderboard’s top places corresponded to these goals.
Nevertheless, there are concerns that gamification has misunderstood what makes games motivating, and that points and leaderboards might do more harm than good (Ryan &
Deci, 2017). According to Ryan and Deci (2017), gamification often pastes gamified elements on top of a system, resulting in it feeling irrelevant to users. The worry is that gamification will undermine intrinsic motivation, i.e. doing something for the enjoyment of it, and replace it with extrinsic motivation, i.e. doing something for rewards, to avoid punishment, or because of social pressure (Mitchell et al., 2020; Ryan & Deci, 2017). Gamification can have detrimental effects on intrinsic motivation (Hanus & Fox, 2015), but this could simply be a result of poor design and application (Liu et al., 2017; Mitchell et al., 2020). Further ethical concerns include that socially-oriented persuasive technologies may create stress and put unnecessary pressure on participants (Orji et al., 2019). The issues with gamification have been investigated mostly in business and work-environments where they have led to employees feeling stressed, inadequate and worried about getting fired (Kim & Werbach, 2016). Thus, there is a need to
5 establish the effectiveness and drawbacks of gamification for various contexts.
Method
In order to answer the research questions, a between-subjects experimental study was conducted. An experimental group was compared to a control group, where both logged their PA during a week, while the experimental group was exposed to a leaderboard. This design was deemed appropriate to investigate and isolate the behavior change effects of leaderboards.
The independent variable was the leaderboard and the dependent variable was the participants’
change in PA. To investigate if self-evaluated competitiveness would moderate the effectiveness of leaderboards, a questionnaire was used.
Participants
A convenience sample was recruited through social media and personal connections.
This sample method was deemed the most appropriate due to the COVID-19 pandemic. There were 24 participants in the study (13 women, 9 men, 2 other/wishes not to answer, mode = 26- 35 years). They were required to be over 18 years old, fluent in Swedish, and have sufficient computer skills to answer online questionnaires and use a simple web application. Their average self-reported PA before the study was 310 minutes (SD=179). Nine participants were students, 12 worked in offices, and two had a job where they stood up or walked a lot.
Instruments and Materials Web application
A web application was created for the participants to report how many minutes of PA they engaged in during the day. We defined PA as anything from a brisk walk where one’s breath gets more strained, to a tough workout at the gym or practicing some sport. A database stored information about participants’ username, PA for every day, and total PA for the week.
Python, Structured Query Language and Common Gateway Interface were used for communication between the database and the interface.
Additionally, the database for the experimental group contained information about fictive users. These were made up usernames whose purpose was to keep each participant in the middle of the leaderboard. Their PA was calculated based on the participant’s PA for each day. For example, one fictive user was active 0.8 times the participant’s PA on Monday and 0.9 times the participant’s data on Tuesday. However, if the participant was active under 20 minutes per day or over 120 minutes per day, the fictive users’ PA for that day was set to a default value to make the leaderboard seem realistic. Thus, an exceedingly active participant could end up in the top of the leaderboard and an inactive participant could lose their place on the leaderboard. See Appendix A for all fictive users and their information.
The web application for the control group displayed an information box as well as a box where participants could enter username, day, and active minutes (see Figure 1). The experimental group had an additional leaderboard (see Figure 2), displaying the top six usernames with their corresponding total PA for the week so far. We selected six usernames because one compares oneself less to the group when there are 100 people compared to 10 people (Garcia et al., 2013). After a participant had reported their PA, their name was clearly highlighted on the leaderboard (see Figure 3).
6 Figure 1
Information box and box to enter data from the web application.
Figure 2
Leaderboard before entering today’s PA.
7 Figure 3
Leaderboard after entering today’s PA.
Revised Competitiveness Index
As a matter of assessing the degree of competitiveness of the participants, the Revised Competitiveness Index (RCI; Houston et al., 2002) was used. The RCI has 14 self-report questions with a 5-point scale (see Table B2 in Appendix B). An example item from the RCI is I like competition. In the RCI, competitiveness is seen as a stable trait (Harris & Houston, 2010). The RCI has a high internal consistency and test-retest reliability (Harris & Houston, 2010) and sufficient validity and reliability (Krägeloh et al., 2018; Krägeloh et al., 2019).
The RCI has two subscales: enjoyment of competition and contentiousness.
Contentious is defined as “likely to cause disagreement or argument” (Merriam-Webster, n.d.).
This study relies on the definition of competition as “a desire to win in interpersonal situations”
(Helmreich & Spence, 1978, as cited in Harris & Houston, 2010), and this does not necessitate a desire to create arguments. Additionally, the contentiousness subscale operates differently for New Zealand and US students (Krägeloh et al., 2019). Krägeloh et al. suggests that this subscale should only be used to look at group estimates of competitiveness. As no studies have tested the cross-cultural validity for the RCI in Sweden, and because we were hesitant about its place in a competitiveness scale, we chose to not include the contentiousness subscale in our statistical analysis.
For the purpose of this study, the RCI was translated into Swedish to avoid misunderstandings due to differing levels of English comprehension.
Questionnaires
A pre-questionnaire contained demographic questions, how many minutes the participants were active during a normal week, and the RCI (see Appendix B for all questions).
The demographic questions were asked to get a picture of the distribution of the participants regarding age, gender, and occupation. All participants answered this. At the end of the study, a post-questionnaire was answered. There was one post-questionnaire for the experimental group and one for the control group (see Appendix C for all questions). Both groups’
questionnaires included questions about if another reason than their participation in the study
8 had affected their PA, and their expected motivation for next week. The difference between the two questionnaires was that the experimental group answered questions regarding their opinions of the leaderboard, such as if they liked it or experienced stress due to it. All questionnaires were created in Google Forms.
Procedure
First, the participants gave informed consent where they were informed that they could end their participation at any time without explanation. This was especially important due to the concerns that one might find the leaderboard stressful or anxiety-inducing. They then answered the pre-questionnaire. Their competitiveness level was calculated and they were randomly assigned to a group. If necessary, the groups were adjusted to even the distribution of different levels of competitiveness in the two groups. During one week, the participants logged their daily PA every evening through the web application. A daily reminder (see Appendix D) was sent out to the participants between 20:00 and 20:30 via text message or email. After the week was done, they answered their group’s corresponding post-questionnaire.
Exclusion Criteria
The exclusion criteria for the statistical analysis were that the participant in the post- questionnaire answered that something other than the study affected their PA, in addition to that they had a change exceeding 50% of their initial self-reported PA. Another explanation for the change in PA would skew the results and we wanted to isolate the leaderboard’s behavior change effect. With a smaller difference, it was assumed that the participants were unaware of their change in PA and what affected this. For instance, one participant reported that they were less active than usual and that something else affected this, but they had close to zero change in PA. Four participants were excluded due to this. One participant dropped out and another was excluded due to failure to follow the instructions. This resulted in 18 participants to make statistical analyses on, eight in the control group and 10 in the experimental group.
Results
All statistical analyses were made using the software JASP. The significance level for the study was .05. Descriptive statistics, paired samples t-test, independent samples t-test, and Pearson’s correlation were done on the data.
The results from the questionnaires and reported daily PA during the experiment were analyzed. The main results were that no significant increase for the experimental group compared to the control group was found, and there was no correlation between competitiveness and change in PA.
Descriptive Statistics
Descriptive statistics for the two groups after the exclusions are shown in Table 1. Of the included participants, three reported being active less than 150 minutes per week in the pre- questionnaire, nine were within 150-300 minutes, and six were above 300 minutes. In the post- questionnaire, 83% thought that their original estimate of their weekly PA was correct. The control group’s PA before and during the study is displayed in Figure 4 and the experimental group’s PA is shown in Figure 5. Of all participants, 67% were already tracking their PA.
9 Table 1
Descriptive statistics for the control and experimental group after exclusions.
Competitiveness Score PA before PA during week Control Experiment Control Experiment Control Experiment
Sample size 8 10 8 10 8 10
Mean 3.3 3.4 283 358 307 452
Std. Deviation 1.1 1.0 199 175 202 223
Minimum 1.6 1.9 90 120 100 124
Maximum 4.6 4.9 600 600 680 785
Figure 4
All participants in the control group’s active minutes before and during the study.
10 Figure 5
All participants in the experimental group’s active minutes before and during the study.
Main Analyses
To investigate the effect of reporting one’s daily PA, a two-tailed paired t-test was done on both groups’ measures of PA before and during the study. The experimental group had a significant (p < 0.05) change in PA during the experiment week with a large effect size (Cohen’s d = 0.99). The control group did not have a significant change. The data is displayed in Table 2.
Table 2
Paired samples t-tests for both groups comparing the PA before the study to the PA during the study.
Measure 1 Measure 2 t df p Mean Difference SE Difference Cohen's d PA during C - PA before C 1.19 7 0.27 24.4 20.4 0.42 PA during E - PA before E 3.12 9 0.01 93.6 30.0 0.99
Note. Student's t-test.
11 To compare the two groups’ change in PA during the study, a two-tailed independent t-test was done. No significant difference (p = 0.09) was found (see Table 3).
Table 3
Independent samples t-test of the change in PA between the two groups.
95% CI for Mean Difference t df p Mean
Difference
SE Difference
Lower Upper Cohen's d Change -1.81 16 0.09 -69.2 38.3 -150.5 12.0 -0.86
Note. Student's t-test.
For the experimental group, Pearson's r correlation was done between several variables.
There was no correlation between the change in PA and self-reported competitiveness.
However, there was a significant correlation (r = 0.67, p < 0.05) between self-reported competitiveness and enjoyment of seeing the leaderboard. Moreover, a significant correlation was found between how stressed they were in relation to how motivated they felt to engage in PA next week (r = 0.78, p < 0.01). See Table 4.
Table 4
Pearson's correlations for competitiveness score and change in PA, competitiveness score and how much they enjoyed the leaderboard, and stress about the leaderboard compared to their motivation to exercise the week after the study.
Pearson's r p Lower 95%
CI
Upper 95%
CI Competitiveness
Score
- Change -0.02 0.95 -0.64 0.62
Competitiveness Score
- Enjoyment of leaderboard
0.67 * 0.04
0.06 0.91 Stress - Motivation 0.78 ** 0.008 0.29 0.95
* p < .05, ** p < .01, *** p < .001
In the final questionnaire for the experimental group, 60% of participants reported that they did not experience that the leaderboard affected their PA. The mean values for the experimental group’s motivation, comparison, enjoyment, and stress in regard to the leaderboard are displayed in Table 5. Exactly 50% had a specific goal, either being at the top or just not at the bottom.
12 Table 5
Descriptive statistics for the experienced motivation to be physically active next week, comparison to others on the leaderboard, enjoyment, and stress of the leaderboard.
Motivation Comparison Enjoyment Stress
Mean 3.5 3.7 3.9 1.5
Std.
Deviation
0.71 1.34 0.99 0.71
Minimum 3 1 2 1
Maximum 5 5 5 3
Note. A scale (1-5) was used; 1 is never or less than usual, 3 is neutral, and 5 indicates doing or feeling it more.
Sixty percent of the experimental group perceived that the leaderboard did not affect their PA, but two of these still had an increase of over 60% from their original self-reported PA. Examining both the control and experimental group, six participants that increased their PA with 30% or more reported a 3 (meaning no difference) when asked how active compared to a normal week they had been during the experiment.
One participant identified that the other users on the leaderboard were fake.
Discussion
The present study was designed to investigate the behavior change effectiveness of leaderboards and if competitiveness moderated that effect.
The first research question was: How effective are leaderboards for increasing physical activity in adults? This study examined this by comparing an experimental group to a control group. The results of the paired samples t-test showed that the experimental group had a significant increase in PA when comparing their estimated activity before the intervention to their activity during the study. This indicates that leaderboards can affect PA positively. The control group, however, did not have a significant change in PA during the study. Moreover, the independent samples t-test did not show a significant difference between the control and experimental group, meaning that we cannot say that leaderboards are more effective than simply logging one’s PA. So the answer to the first research question is that leaderboards are effective for increasing PA in adults, but not significantly more effective than only logging one’s PA.
The second research question was: Does competitiveness level impact a leaderboard’s effectiveness? The results showed that there was no correlation between self-reported competitiveness and change in PA.
However, there was a correlation between self-reported competitiveness and enjoyment of the leaderboard. This is in line with the findings of Höllig et al. (2020) where the intention to use a system was only indirectly associated with competitiveness through enjoyment when one imagines oneself working in a consultation company.
13 The lack of significant results for the second research question might result from problems with the RCI. Newby and Klein (2014) criticized the RCI based on that it measures enjoyment of competition and agreeableness instead of a desire to be superior, as they claim the original authors’ purpose with the scale was. Furthermore, there has been criticism towards self-evaluations to measure competitiveness, insisting that researchers should instead look at behaviors that show competitiveness (Amo et al., 2020). Using another scale for measuring competitiveness or looking at objective measures could have yielded another result.
Overall, the participants were moderately positive to the leaderboard and they experienced little stress caused by it. This contradicts the ethical concerns that leaderboards would cause stress, anxiety, and put pressure on the participants posed by Orji et al. (2019).
Thus, the results from this study did not show that leaderboards are better than not seeing a leaderboard, but the leaderboard does not do any harm. Furthermore, there are indications that users who are more competitive enjoy leaderboards more which could lead to them being more motivated.
A Cognitive Science Perspective on the Findings
The prospective explanations of leaderboards’ behavior change effectiveness that were addressed in the introduction will now be discussed in relation to this study’s findings.
Partial support for social comparison was found since the participants reported an average of 3.7 (where 1 is never and 5 is very often) in comparing themselves to others on the leaderboard. However, it might not have had a considerable behavior change effect given the results. The participants in the study were told to use usernames unrelated to their real name.
This in combination with the made-up names on the leaderboard could mean that they did not feel a connection to the others. We did not ask whether they felt a connection or relation to the fake users. Garcia et al (2013) predicts that knowing the people on the leaderboard would make you more engaged. As they did not know who the others on the leaderboard were they could not know how similar they were, one of the things that Garcia et al. (2013) says gives effect.
Another factor that invokes competition is relevance of the subject (Garcia et al., 2013). In this case, the participants had not chosen directly what to compete in, which could make it feel less relevant. However, relevance may have been simulated by personally recruiting participants as they might have felt motivated to participate as a way of helping us.
Additionally, no evidence was found that goal setting was at work. In the present study, half of the participants reported having a specific goal of placement on the leaderboard.
However, one could theorize that the others could have had unconscious goals. For instance, some participants were not aware that they had a change in PA, meaning that they could have engaged in other unconscious processes. Namely, two participants who thought the leaderboard did not affect them increased their original PA with more than 60%. Additionally, overall six participants that increased their PA with 30% or more thought there had been no difference in their PA compared to a normal week. Zuckerman and Gal-Oz (2014) also found that participants’ subjective reports of their change in PA did not match the objective accounts. This implies that other processes, such as goal setting, could be unconscious as well.
No harmful effects on intrinsic motivation were found. No questions were asked regarding participants’ sense of autonomy, competence or relatedness, which need to be satisfied according to Ryan and Deci (2017) for there to be intrinsic motivation. However, the participants in our study did not feel stressed by the leaderboard. Furthermore, there were no reports of people anticipating being less motivated to be active the following week. If their intrinsic motivation was thwarted, the opposite would be expected. On the other hand, no evidence was found regarding a positive change in intrinsic motivation either.
14 Limitations
The findings might be limited by a number of methodological concerns. Firstly, the sample size is very small. A larger sample may have shown more clear and reliable results.
Furthermore, there is a risk that the participants’ self-reported PA before the study could be inaccurate. An attempt to control this was made by a question in the post-questionnaire regarding whether they thought their initial estimate was correct, where 83% answered “yes”.
Prince et al. (2008) investigated the accuracy of self-reported PA compared to direct measurements (e.g. accelerometers and pedometers) and found discrepancies between them.
Overall they found problems with both measurements.
The aim was to make the leaderboard as realistic as possible while still having fictive users. Therefore we set the restrictions that if a participant was active for less than 20 minutes or more than 120 minutes, a default value was set for each fictive user. We were successful since only one participant figured out that the other usernames did not belong to real people.
However, this becomes a confounding variable as not all participants were at the same spot on the leaderboard. Some participants experienced being at the number one place, while some dropped out of the leaderboard for a while. Nonetheless, everyone got to see their name on the leaderboard some time during the week and no one was at the top spot for the entire week. One alternative to this could have been to have the participants compete against each other, but this would mean they would have been very far apart from each other on the leaderboard as they engaged in varying amounts of PA. Thus, if we had designed the experiment like this, the participants would have been in even more diverse positions on the leaderboard and the top user would have been at the top of the leaderboard for the entire week, instead of now ending up at the second place. Now, all participants that were exceedingly active got a challenge in their competition against our star fictive user Äpple. As one especially active participant stated in the post-questionnaire: “[I] got stoked when Äpple pulled ahead the last few days and threw in an extra workout the last day to get the time up a bit.”
Another limitation is that the participants could not see a “live” leaderboard. They only saw the updated leaderboard after they had logged their daily PA. This was so that the algorithm that calculated all fictive users’ PA would work. If they could have seen a live leaderboard, they could perhaps have exercised more the same day if they were close to an opponent. But this would deplete our purpose of keeping the participants from being at the top of the leaderboard, as the time and resources for this project did not allow for a more advanced algorithm. Additionally, as the web application used self-report, if the participants saw a live leaderboard they might feel more inclined to round up their PA if they noticed that they were close to climbing some positions.
Furthermore, the leaderboard could be altered by incorporating more of the ideas of Garcia et al. (2013) of social comparison by letting users keep their real names or include links to pages where there could be information about each user so that they could know more when comparing themselves.
Moreover, the decision to translate the RCI into Swedish was made because the participants were Swedish and we did not want differing English skills to affect the results.
Nonetheless, the translation could have made the RCI lose some of its reliability as this has not been tested.
When changing behavior, the goal is for it to be sustained long term (Michie et al., 2009). As the duration of this study was only a week, the long-term effects are unknown. In the post-questionnaire, most people answered that they thought they would be equally or somewhat more motivated (M = 3.5, where 3 is no change) than normally to engage in PA the week after the study. But we do not know if their behavior actually changed.
15 The majority of the participants were already quite active (control group M = 285 minutes, experimental group M = 358 minutes) and 67% already used a way to track their PA.
Only three out of 18 reported in the pre-questionnaire a number below the recommended 150 minutes of PA per week. As previous studies have shown that fitness apps mainly work for people who are already motivated to be physically active (Jarrahi, et al., 2018), this limits if we can say that our results are applicable to inactive people as well.
Future Works
Future studies should aim for more participants to make more sound statistical analyses on. Future studies could also control for the inaccuracy of self-report by having the participants wear a tracker that can measure their objective PA before and during the study.
Moreover, it would be interesting to investigate if any benefits of the leaderboard persist over time when one has stopped using it. Additionally, it would be interesting with a similar study design during a longer period of time, where one could investigate the leaderboard’s long-term effects.
There is still a need to investigate more gamification strategies individually. Studies could be done not only on leaderboards, but also strategies such as badges, levels, etc.
Additionally, other traits that might impact the effect of gamification strategies could be considered. Liu et al. (2017) proposed that individual characteristics (e.g. goal orientation, computer anxieties, and need for achievement) could influence if someone will use a system.
Thus, one could investigate these traits in relation to gamification strategies.
Implications of Findings
The findings of this study contribute to the cognitive science field with knowledge about leaderboards and more specifically, leaderboards in relation to competitiveness. The results were not as optimistic as other studies have shown. However, some of these earlier studies have not been made in a PA setting (e.g. Call et al., 2021; Landers et al., 2017). If individual gamification strategies only are behavior change effective in certain settings, that also poses a need for more research of individual gamification strategies in various contexts.
The results can help designers of fitness applications decide whether to include leaderboards or not. The leaderboard was not significantly behavior change effective, meaning that designers should be hesitant to use it on its own.
However, since the results show that competitive people enjoy a leaderboard more, this supports the view that personalization of applications based on personality traits is valuable. In this case though, competitiveness level did not correlate with change in PA or motivation. Thus, designers must make a choice regarding if enjoyment is enough to include a leaderboard, or if they need it to be behavior change effective as well.
Conclusions
This study’s goal was to investigate whether leaderboards are behavior change effective in increasing PA and if self-reported competitiveness affects this. This was done through an experiment where two groups reported their daily PA while one group saw a leaderboard.
The leaderboard was not significantly better than logging one’s PA. Moreover, no relation between change in PA and self-reported competitiveness was found. The participants overall liked the leaderboard and did not experience stress because of it. This means that the leaderboard did not do any harm and thus it does not hurt to include a leaderboard in PA applications. But it might not be as magically behavior change effective as some try to claim.
16 While traits might affect how useful leaderboards can be for individuals, this study showed no support for competitiveness.
The results were not as positive as in earlier studies on leaderboards, done mostly in educational environments. We assumed that leaderboards should be behavior change effective in PA applications because leaderboards are present in sport competitions and there are theories within psychology that explain their potential efficiency. The lack of correlation between competitiveness and change in PA could be explained by the participants in this study not having chosen exactly what to compete in. If they had chosen the competition setting themselves, competitiveness level could have had a greater significance. Additionally, the results could be distorted due to the study design or the small sample size. Or, leaderboards might need to be combined with one or several other gamification strategies in order to be behavior change effective.
Future works should investigate more gamification strategies individually, in different settings, and in combination with various personality traits. By looking at various traits, future behavior change applications can be adjusted with the most appropriate gamification techniques for each individual user. Going forward there are further theories within cognitive science and psychology that can help explain and give inspiration to gamification and behavior change applications.
17 References
Amo, L., Liao, R., Kishore, R., & Rao, H. R. (2020). Effects of structural and trait
competitiveness stimulated by points and leaderboards on user engagement and performance growth: A natural experiment with gamification in an informal learning environment. European journal of information systems, 29(6), 704-730.
https://doi.org/10.1080/0960085X.2020.1808540
Arigo, D., Brown, M. M., Pasko, K., & Suls, J. (2020). Social comparison features in
physical activity promotion apps: scoping meta-review. Journal of medical Internet research ,22(3), e15642. https://doi.org/10.2196/15642
Baretta, D., Perski, O., & Steca, P. (2019). Exploring users’ experiences of the uptake and adoption of physical activity apps: longitudinal qualitative study. JMIR mHealth and uHealth, 7(2), e11636. https://doi.org/10.2196/11636
Call, T., Fox, E., & Sprint, G. (2021). Gamifying Software Engineering Tools to Motivate Computer Science Students to Start and Finish Programming Assignments Earlier.
IEEE Transactions on Education, 1–9. https://doi.org/10.1109/TE.2021.3069945 Chapman, G., Colby, H., Convery, K., & Coups, E. J. (2016). Goals and Social Comparisons
Promote Walking Behavior. Medical Decision Making., 36(4), 472–478.
https://doi.org/10.1177/0272989X15592156
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From Game Design Elements to Gamefulness: Defining “Gamification”. Proceedings of the 15th International Academic MindTrek Conference, 9–15. https://doi.org/10.1145/2181037.2181040 Elliot, A. J., Jury, M., & Murayama, K. (2018). Trait and perceived environmental
competitiveness in achievement situations. Journal of personality, 86(3), 353-367.
https://doi.org/10.1111/jopy.12320
Folkhälsomyndigheten. (25 november 2020). Fysisk aktivitet – rekommendationer.
https://www.folkhalsomyndigheten.se/livsvillkor-levnadsvanor/fysisk-aktivitet-och- matvanor/fysisk-aktivitet--rekommendationer/
Folkhälsomyndigheten (2021). Folkhälsans utveckling - årsrapport 2021 (Artikelnummer:
21014).
https://www.folkhalsomyndigheten.se/contentassets/39ef6af33177445bb6d2ad88829c c5ce/folkhalsans-utveckling-arsrapport-2021.pdf
Garcia, S. M., Tor, A., & Schiff, T. M. (2013). The Psychology of Competition: A Social Comparison Perspective. Perspectives on psychological science, 8(6), 634-650.
https://doi.org/10.1177/1745691613504114
Hanus, M., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers and Education, 80, 152–161.
https://doi.org/10.1016/j.compedu.2014.08.019
Harris, P. B., & Houston, J. M. (2010). A Reliability Analysis of the Revised Competitiveness Index. Psychological reports, 106(3), 870-874. https://doi.org/10.2466/pr0.106.3.870- 874
Houston, J., Harris, P., McIntire, S., & Francis, D. (2002). Revising the competitiveness index using factor analysis. Psychological Reports, 90(1), 31–34.
https://doi.org/10.2466/PR0.90.1.31-34
Huang, R., Ritzhaupt, A., Sommer, M., Zhu, J., Stephen, A., Valle, N., Hampton, J., & Li, J.
(2020). The impact of gamification in educational settings on student learning outcomes: a meta-analysis. Educational Technology Research and Development, 68(4), 1875–1901. https://doi.org/10.1007/s11423-020-09807-z
18 Höllig, C. E, Tumasjan, A., & Welpe, I.M. (2020). Individualizing gamified systems: The role of trait competitiveness and leaderboard design. Journal of business research, 106, 288- 303. https://doi.org/10.1016/j.jbusres.2018.10.046
Jarrahi, M., Gafinowitz, N., & Shin, G. (2018). Activity trackers, prior motivation, and perceived informational and motivational affordances. Personal and Ubiquitous Computing, 22(2), 433–448. https://doi.org/10.1007/s00779-017-1099-9
Johnson, D., Deterding, S., Kuhn, K., Staneva, A., Stoyanov, S., & Hides, L. (2016).
Gamification for health and wellbeing: A systematic review of the literature. Internet Interventions, 6, 89-106. https://doi.org/10.1016/j.invent.2016.10.002
Kappen, D. L., Mirza-Babaei, P., & Nacke, L. E. (2020). Technology Facilitates Physical Activity Through Gamification: A Thematic Analysis of an 8-Week Study. Frontiers in Computer Science, 2. https://doi.org/10.3389/fcomp.2020.530309
Kim, T., & Werbach, K. (2016). More than just a game: ethical issues in gamification. Ethics and Information Technology, 18(2), 157–173. https://doi.org/10.1007/s10676-016- 9401-5
Klein, W. M. P., & Rice, E. L. (2019). Health Cognitions, Decision-Making, and Behavior. In J.M. Suls, R. L. Collins, & L. Wheeler (Eds.), Social comparison, judgment, and behavior. Oxford University Press.
Krägeloh, C. U., Wang, G. Y., Zhao, Q., Medvedev, O. N., Wu, Y., & Henning, M. A. (2018).
Revised Competitiveness Index for use in China: Translation and Rasch analysis.
International journal of educational research, 90, 78-86.
https://doi.org/10.1016/j.ijer.2018.05.008
Krägeloh, C. U., Medvedev, O. N., Hill, E.M., Webster, C. S., Booth, R. J., & Henning, M. A.
(2019). Improving Measurement of Trait Competitiveness: A Rasch Analysis of the Revised Competitiveness Index With Samples From New Zealand and US University
Students. Psychological reports, 122(2), 689-708.
https://doi.org/10.1177/0033294118762548
Landers, R. N., Bauer, K. N., & Callan, R. C. (2017). Gamification of task performance with leaderboards: A goal setting experiment. Computers in human behavior, 71, 508-515.
https://doi.org/10.1016/j.chb.2015.08.008
Liu, D., Santhanam, R., & Webster, J. (2017). Toward Meaningful Engagement: A Framework for Design and Research of Gamified Information Systems. MIS quarterly, 41(4), 1011- 1034. https://doi.org/10.25300/MISQ/2017/41.4.01
Maher, C., Ferguson, M., Vandelanotte, C., Plotnikoff, R., De Bourdeaudhuij, I., Thomas, S., Nelson-Field, K., & Olds, T. (2015). A Web-Based, Social Networking Physical Activity Intervention for Insufficiently Active Adults Delivered via Facebook App:
Randomized Controlled Trial. Journal of medical Internet research, 17(7), e174.
https://doi.org/10.2196/jmir.4086
Merriam-Webster. (n.d.). Contentious. In Merriam-Webster.com. Retrieved 20 May, 2021, from https://www.merriam-webster.com/dictionary/contentious
Michie, S., Abraham, C., Whittington, C., McAteer, J., & Gupta, S. (2009). Effective Techniques in Healthy Eating and Physical Activity Interventions: A Meta-Regression.
Health Psychology, 28(6), 690–701. https://doi.org/10.1037/a0016136
Mitchell, R., Schuster, L., & Hyun Seung, J. (2020). Gamification and the impact of extrinsic motivation on needs satisfaction: Making work fun? Journal of business research, 106, 323-330. https://doi.org/10.1016/j.jbusres.2018.11.022
Newby, J. L., & Klein, R. G. (2014). Competitiveness Reconceptualized: Psychometric
19 Development of the Competitiveness Orientation Measure as a Unified Measure of Trait Competitiveness. The Psychological record, 64(4), 879-895.
https://doi.org/10.1007/s40732-014-0083-2
Orji, R., Oyibo, K., Lomotey, R., & Orji, F. (2019). Socially-driven persuasive health intervention design: Competition, social comparison, and cooperation. Health Informatics Journal, 25(4), 1451–1484. https://doi.org/10.1177/1460458218766570 Ortiz‐Rojas, M., Chiluiza, K., & Valcke, M. (2019). Gamification through leaderboards: An
empirical study in engineering education. Computer Applications in Engineering Education, 27(4), 777–788. https://doi.org/10.1002/cae.12116
Prince, S., Adamo, K., Hamel, M., Hardt, J., Connor Gorber, S., & Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. The International Journal of Behavioral Nutrition and Physical Activity, 5(1), 56–56. https://doi.org/10.1186/1479-5868-5-56
Ryan, R., & Deci, E. (2017). Self-determination theory: basic psychological needs in motivation, development, and wellness. The Guilford Press.
World Health Organisation (2018). Global action plan on physical activity 2018-2030 - more
active people for a healthier world.
https://apps.who.int/iris/bitstream/handle/10665/272722/9789241514187- eng.pdf?sequence=1&isAllowed=y
World Health Organisation (2020). WHO guidelines on physical activity and sedentary behaviour. https://www.who.int/publications/i/item/9789240015128
Zuckerman, O., & Gal-Oz, A. (2014). Deconstructing gamification: evaluating the
effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity. Personal and Ubiquitous Computing, 18(7), 1705–1719.
https://doi-org.proxy.ub.umu.se/10.1007/s00779-014-0783-2
20 Appendix A
Fictive Users Table A1
Fictive users, their scores for each day, and default value.
Fictive username
Monday Tuesday Wednesday Thursday Friday Saturday Sunday Default
kv1337 0.5 0.6 0.4 0.3 0.5 0.6 0.2 20
umeälven 1.1 1.2 1.1 0.9 0.8 1.1 1.2 60
användare 0.8 0.9 1.2 1.1 0.9 1.2 0.8 40
Yeet#1 0.7 0.4 0.8 0.3 0.4 0.5 0.4 25
Äpple 1.8 1.7 1.9 1.5 1.9 1.6 1.5 100
bert 1.3 0.5 1.2 0.6 1.7 0.3 1.3 45
Kattälskare 1.4 0.5 0.7 0.9 0.6 0.8 0.8 50
21 Appendix B
Pre-Questionnaire
Table B1
Demographic information questions. The questionnaire was written in Swedish so the questions and answers are displayed in their original form.
Fråga Svarsalternativ
Det här är en studie som utförs som en del av ett examensarbete på kandidatnivå i Kognitionsvetenskap vid Umeå Universitet. Syftet är att undersöka människors fysiska aktivitet när de får rapportera in den i relation till hur tävlingsinriktade de är. För att delta måste du vara över 18 år.
Först kommer du fylla i detta formulär, sedan under en veckas tid rapportera in din dagliga fysiska aktivitet. I slutet av veckan kommer du få fylla i ett till formulär. Det första formuläret tar ca 15 minuter att fylla i, det sista formuläret tar ca 5 minuter att fylla i.
Rapporteringen sker via en webbsida och tar ca 2 minuter per dag att utföra. Du kommer få ett meddelande varje kväll som påminner dig att rapportera in. Det går inte att rapportera in allt på en och samma gång utan måste göras på den dagen det handlar om. Om du glömmer att rapportera kommer det räknas som att du inte varit fysiskt aktiv den dagen.
Det är helt frivilligt att delta och du kan när som helst avsluta ditt deltagande utan att berätta varför. Du kan när som helst be om att få din data raderad.
Data som samlas in kommer vara anonymiserad och inte presenteras på sådant sätt att den kan ledas tillbaka till någon individ. Telefonnummer/mailadresser som samlas in kommer raderas efter att studien avslutats.
Om du känner någon annan som är med i studien vill vi be dig att inte diskutera studien med dem förens ni båda är klara med veckans inrapportering samt enkäten efter studien.
Om du har några frågor kan du maila Fanny på fada0025@student.umu.se eller Elin på kv18efn@cs.umu.se
Tack för ditt deltagande!
Fanny och Elin
Jag förstår ovanstående och godkänner att jag är med i studien. Ja
Ålder 18-25; 26-35; 36-45;
46-55; 56-65; 66+
Kön Kvinna; Man;
Annat/vill inte ange
Huvudsaklig sysselsättning Studerande; Jobbar
med kontorsjobb eller annat stillasittande;
Jobbar med arbete där jag står/går mycket;
22
Annat Ungefär hur många minuter brukar du ägna dig åt fysisk aktivitet en normal
vecka? Med fysisk aktivitet menar vi allt från att gå en rask promenad där din andning blir lite mer ansträngd, till ett hårt gympass eller att utöva någon sport.
Det räknas inte om du går runt i ditt hem eller strosar lugnt på stan.
Kort svarstext
Hitta på ett unikt användarnamn. Det ska gärna inte vara kopplat till ditt riktiga namn. Det kommer användas för att koppla ihop dina svar från enkäter och inrapportering med varandra. Det viktiga är att du kommer ihåg användarnamnet då du kommer använda det vid inrapportering av din fysiska aktivitet.
Kort svarstext
Vi kommer skicka ut en länk till sidan där du ska rapportera in din fysiska aktivitet under veckan. Vi kommer också under studiens gång skicka ut
påminnelser via sms eller mail varje kväll. Du kan välja mellan att ange din mail eller ditt telefonnummer.
Kort svarstext
Table B2
The RCI and the corresponding Swedish translation used for each item.
Original Item Swedish Translation
Enjoyment of Competition
I like competition. Jag tycker om konkurrens.
I am a competitive individual. Jag är en tävlingsinriktad individ.
I enjoy competing against other people. Jag tycker om att tävla mot motståndare.
I don’t like competing against other people.* Jag tycker inte om att tävla mot andra.*
I get satisfaction from competing with others. Jag njuter av att tävla mot andra.
I find competitive situations unpleasant.* Jag finner tävlingsinriktade situationer obehagliga.*
I dread competing against other people.* Jag oroar mig för att tävla mot andra.*
I try to avoid competing with others.* Jag försöker undvika att tävla mot andra.*
I often try to outperform others. Jag försöker ofta prestera bättre än andra.
Contentiousness
I try to avoid arguments.* Jag försöker undvika gräl.*
I will do almost anything to avoid an argument.* Jag gör nästan vad som helst för att undvika gräl.*
I often remain quiet rather than risk hurting another person.*
Jag är oftast hellre tyst än att riskera att såra någon annan.*
I don’t enjoy challenging others even when I think they are wrong.*
Jag tycker inte om att ifrågasätta andra även om jag tycker att de har fel.*
In general, I will go along with the group rather than create conflict.*
Generellt håller jag med gruppen istället för att skapa konflikt.*
*Items are reverse coded
23 Appendix C
Post-Questionnaires
Table C1
The control group’s post questionnaire questions. The questionnaire was written in Swedish so the questions and answers are displayed in their original form.
Fråga Svarsalternativ
Avsnitt 1
Tack så mycket för att du har deltagit i vår studie! Vi har bara några sista frågor att ställa som tar ca 5 minuter att svara på.
Användarnamn Kort svarstext
Hur aktiv jämfört med en vanligt vecka upplever du att du har varit under studien?
Skala 1-5, där 1 = Mycket mindre; 5 = Mycket mer
Om du har haft en förändring i fysisk aktivitet jämfört med en normal vecka, finns det någon annan anledning än ditt deltagande i studien?
Ja; Nej
Tycker du att uppskattningen du gjorde i första enkäten av hur fysisk aktiv du brukar vara en normal vecka (när du inte är med i studien) var korrekt?
Kort svarstext
Missade du att fylla i din aktivitet någon dag? Om ja, varför?
Kort svarstext
Var det någon dag som du gick ut och promenerade eller tränade efter och på grund av att du fått påminnelsen?
Ja; Nej
Brukar du vanligtvis logga din fysiska aktivitet?
T.ex. genom en smartklocka, app, fysisk träningsdagbok.
Ja; Nej
Hur motiverad att vara fysisk aktiv tror du att du kommer vara nästa vecka?
Skala 1-5, där 1 = Mindre än vanligt; 5 = Mer än vanligt
Avsnitt 2
Den här studien har undersökt hur effektiva topplistor är för att öka fysisk aktivitet, samt om det finns något samband mellan hur tävlingsinriktade personer är och hur effektiva topplistor är.
Du har varit med i kontrollgruppen och har därför inte sett någon topplista. Det är för att vi vill
kontrollera för effekten av att enbart rapportera in sin fysiska aktivitet.
24
Vill du ha information om resultatet av studien när data har analyserats? I så fall fyll i din mailadress
Kort svarstext
Table C2
The experimental group’s post questionnaire questions. The questionnaire was written in Swedish so the questions and answers are displayed in their original form.
Fråga Svarsalternativ
Avsnitt 1
Tack så mycket för att du har deltagit i vår studie! Vi har bara några sista frågor att ställa som tar ca 5 minuter att svara på.
Användarnamn Kort svarstext
Hur aktiv jämfört med en vanligt vecka upplever du att du har varit under studien?
Skala 1-5, där 1 = Mycket mindre; 5 = Mycket mer
Om du har haft en förändring i fysisk aktivitet jämfört med en normal vecka, finns det någon annan anledning än ditt deltagande i studien?
Ja; Nej
Tycker du att uppskattningen du gjorde i första enkäten av hur fysisk aktiv du brukar vara en normal vecka (när du inte är med i studien) var korrekt?
Kort svarstext
Missade du att fylla i din aktivitet någon dag? Om ja, varför?
Kort svarstext
Var det någon dag som du gick ut och promenerade eller tränade efter och på grund av att du fått påminnelsen?
Ja; Nej
När du rapporterat in dina aktiva minuter för en dag kunde du se en topplista med din placering. La du märke till den?
Ja; Nej
Upplevde du att topplistan påverkade din fysiska aktivitet?
Ja, den har gjort mig mer aktiv; Ja, den har gjort mig mindre aktiv; Nej, den har inte påverkat mig Jämförde du dig med de andra användarna på
topplistan?
Skala 1-5, där 1 = Aldrig; 5 = Mycket ofta
Satte du något mål för var du ville placera dig på topplistan?
Ja, jag ville vara allra högst upp på listan; Ja, jag ville klättra en eller ett par placeringar; Ja, jag ville bara inte vara sist; Nej; Annat...
Tyckte du om att kunna se topplistan? Skala 1-5, där 1 = Nej, inte alls; 5 = Ja, mycket Hur stressad blev du av topplistan? Skala 1-5, där 1 = Inte alls; 5 = Väldigt Brukar du vanligtvis logga din fysiska aktivitet?
T.ex. genom en smartklocka, app, fysisk
Ja; Nej
25
träningsdagbok.
Hur motiverad att vara fysisk aktiv tror du att du kommer vara nästa vecka?
Skala 1-5, där 1 = Mindre än vanligt; 5 = Mer än vanligt
Avsnitt 2
Den här studien har undersökt hur effektiva topplistor är för att öka fysisk aktivitet, samt om det finns något samband mellan hur tävlingsinriktade personer är och hur effektiva topplistor är.
Du har under studien varit med i experimentgruppen.
Du har därför under veckan sett en topplista. De andra namnen på topplistan har varit fiktiva deltagare vars aktiva minuter beräknades beroende på dina aktiva minuter. Det betyder att ingen annan deltagare i studien har kunnat se dina inrapporterade minuter och du har inte kunnat se de andra deltagarnas aktivitet.
Förstod du att de andra namnen på topplistan var fiktiva personer?
Ja; Nej
Om ja, hur förstod du det? Lång svarstext
Vill du ha information om resultatet av studien när data har analyserats? I så fall fyll i din mailadress
Kort svarstext
26 Appendix D
Daily Reminders
SMS or e-mail notifications sent out to the participants during the week. All reminders were sent out in Swedish.
First Message
Message with link to the correct website, sent out on the first day. The italicized words were switched out to the correct link and username for each specific participant.
Tack igen för ditt deltagande i vår studie! Idag är första dagen att logga aktiva minuter. Här kommer länken till rapporteringssidan: länk
Användarnamnet som du ska skriva in är användarnamn.
Kom ihåg att om du känner någon annan som är med i studien ber vi er att inte diskutera den förrän ni är klara med veckan. Mer information finns på sidan och tveka inte att höra av dig till oss om du skulle ha några funderingar!
Reminder message
Sent out every evening days 2-6 sometime between 20:00 and 20:30:
Hej! Det här är en påminnelse att rapportera in tiden du varit fysiskt aktiv idag. Länken finns i ett tidigare sms/mail.
Final message
Sent out on the seventh day, with a link to the correct post-questionnaire:
Idag är sista dagen att rapportera in dina aktiva minuter! Efter att du har gjort det får du besvara en kort enkät som tar 5 minuter att svara på. Stort tack för ditt deltagande! Här är länken till enkäten: länk
