The influence of success experience on self-efficacy when providing feedback through technology

Highlights

• We investigate tailoring in technology-supported physical activity interventions.

• Information is rarely tailored based on constructs from behavioral science.

• High self-efficacy is of major importance for optimal effectiveness.

• Experiencing success leads to increased self-efficacy.

• Mastery experience is a promising strategy for modern behavior change interventions.

Abstract

Background: as a high level of self-efficacy is associated with bigger behavioral changes as well as to higher levels of physical activity, the development and implementation of strategies that successfully improve self-efficacy are important to technological interventions. We performed an experiment to investigate whether self-efficacy regarding a specific task can be influenced by using feedback strategies that focus on success experience and are provided through technology. Method: subjects were asked to walk from A to B in exactly 14, 16 or 18 s, wearing scuba fins and a blindfold. The task guaranteed an equal level of task experience among all subjects at the start of the experiment and makes it difficult for subjects to estimate their performance accurately. This allowed us to manipulate feedback and success experience through technology-supported feedback. Results: subjects’ self-efficacy regarding the task decreases when experiencing little success and that self-efficacy regarding the task increases when experiencing success. This effect did not transfer to level of self-efficacy regarding physical activity in general. Graphical inspection of the data shows a trend towards a positive effect of success experience on task performance. Conclusion: experiencing success is a promising strategy to use in technology-supported interventions that aim at changing behavior, like mobile physical activity applications.

Introduction

More and more people live a sedentary lifestyle, resulting in a decrease in health and posing a risk for various diseases (e.g. Bankoski et al., 2011, Warren et al., 2010). On the other hand, a physically active lifestyle has significant positive effects on prevention of chronic diseases, such as cardiovascular disease, diabetes and cancer (Warburton, Nicol, & Bredin, 2006). Also, a sufficient level of physical activity has positive effects on mental health condition through reduced perceived stress and lower levels of burnout, depression and anxiety (Jonsdottir, Rödjer, Hadzibajramovic, Börjesson, & Ahlborg, 2010). Numerous interventions have already been developed to improve the level of physical activity in the general population (e.g. Dishman and Buckworth, 1996, Marcus et al., 1998). They are usually delivered through public media, flyers, e-mails, or consist of face to face (group) consultations, and show moderate effect sizes (Dishman & Buckworth, 1996).

A recent development regarding physical activity interventions is using mobile, technology-supported applications to achieve the desired effect. Examples include UbiFit Garden (Consolvo et al., 2008), BeWell+ (Lin et al., 2012) and Move2Play (Bielik et al., 2012). A study by Op den Akker, Jones, and Hermens (2014) concluded that many interventions apply tailoring, i.e. personalization of information or feedback, which increases the effect of the intervention (Hawkins, Kreuter, Resnicow, Fishbein, & Dijkstra, 2008). The most common technique is to provide previously obtained information about the individual and some also include a tailored goal and tailored inter-human interaction. Although the effectiveness of tailoring based on constructs from behavioral science – or adaptation (Hawkins et al., 2008) – has been proven, Op den Akker et al. (2014) show that none of the interventions used adaptation as a tailoring strategy. Such lack of adaptation in technology-supported physical activity interventions was also noticed by Achterkamp et al. (submitted for publication), who developed specific feedback strategies for these types of intervention. Four of the six feedback strategies include a focus on increasing self-efficacy, making it an important aspect when designing mobile activity coaches (Achterkamp et al., submitted for publication).

The concept op tailoring information or feedback enhances relevance for the individual and increases the impact of the message; guidelines for designing effective physical activity interventions strongly recommend tailoring feedback (Greaves et al., 2011). Traditional, non-technology-supported interventions that apply adaptation, e.g. by providing tailored information based on subjects’ attitudes, stage of change, social support or processes of change, show significantly larger effect sizes than interventions that do not tailor on these constructs (Noar, Benac, & Harris, 2007). Additionally, self-efficacy seems of major importance (Hawkins et al., 2008); a construct that is common in models and theories that explain behavior and behavioral change. High self-efficacy not only increases intention to perform the target behavior, it also leads to actual performance of the target behavior (Gist & Mitchell, 1992). Additionally, Achterkamp et al. (submitted for publication) showed that the level of self-efficacy is related to (1) level of activity at baseline: the higher the subjects’ level of self-efficacy, the higher their level of physical activity; and (2) the percentage of change as a result of a twelve week intervention: for subjects who are inactive at the start of the intervention, a higher level of self-efficacy is associated with a higher level of increase in physical activity. Bandura (1994) describes four sources of self-efficacy:

• Mastery experience: the subject successfully performs the target behavior.

• Vicarious experience: the subject observes a similar other perform the target behavior.

• Verbal (or social) persuasion: expressing faith in the subject’s capabilities.

• Physiological/affective states: correcting misinterpretations of bodily states.

A systematic review with meta-analysis (Ashford, Edmunds, & French, 2010) shows that the most successful strategy to increase self-efficacy for physical activity is using enactive mastery experience, including feedback about previous performance/successes, followed by vicarious experience and feedback about similar others’ performance.

So, traditional non-technology-supported interventions emphasize the importance of increasing self-efficacy to maximize the chance of positive results, but this knowledge is rarely applied in technology-supported interventions and it is not yet clear how this should be done. Therefore, the aim of the current study is to investigate whether experiencing success also leads to an increase in self-efficacy when using technology-supported feedback strategies. To our knowledge, no such experiment has been performed until now. Specifically, we aim to answer the following questions: what is the effect of a feedback strategy that focuses on success experience on (1) level of self-efficacy regarding a specific task, (2) level of self-efficacy regarding physical activity, and (3) task performance?