Temporal Self-Regulation Theory: Why we keep trying (and failing) to go for that early morning run.

keep-the-dream-alive Last night in a burst of optimism I set my alarm for 5:30 AM. I thought I would sneak in an early morning run around the neighborhood before work. But as bells rang at that un-godly hour, I cracked an eye to a dark, cold room and groped for the snooze button. Ten minutes later, with a slight increase in clarity, I delayed once more “today, sleep is more important”…snooze again. As you might have guessed, I didn’t wake up in time to run.

We’ve all had a similar experience. Our preconceived intentions to engage in healthy behavior too often fail to come to fruition when it’s time to act. But we also intuit that our intentions are somehow linked to our behavior.

Most of the prevailing theoretical models of health behavior such as the Theory of Planned Behavior (Ajzen & Madden, 1986, request pdf), posit that intentions in combination with a number of other factors, such as behavioral beliefs, can predict likelihood of behavior. And these theories do predict behavior reasonably well (see Godin and Kok, 1996), but they fail to explain why large increases in intention only lead to small changes in behavior (see review by Webb and Sheeran, 2006). In this way these theories fail to fully explain health behavior.

Hall and Fong (2007), developed Temporal Self-Regulation Theory to help explain why, when it comes to health-related actions, the intention–behavior link may break down. They postulate that perhaps our intentions sometimes fail to lead to behavior because,

[many health behaviors are] associated with a characteristic set of contingencies whose valence changes dramatically depending on the temporal frame.

I’ve added emphasis to the quote to help break it down. In generally when psychologists talk about behavioral “contingencies” they are referring to if-then conditions that create potential for the occurrence of certain behavior and its consequences. Using the running example above, one behavioral contingency could be stated, “if I run in the morning, then I might be healthier when I’m older”. The “valence” of this contingency is positive—who doesn’t want to live a long and healthful life? “Temporal frame” refers to the very human capacity to think not only in the present moment or short-term, but also to weigh long-term consequences of our actions. Our example contingency has a long-term orientation. The authors contend that valence of the contingency changes with temporal frame, so let’s say I am thinking in the short-term, the behavioral contingency could then be stated, “if I run in the morning, then I might be tired for the rest of the day”. This is, of course, negative in valence. So the theory predicts that I will be more likely to create an intention to run in the morning if I’m focussed on the long-term as opposed to the short-term. This helps explain why it’s so hard to engage in health protective behaviors (such as running) and dis-engage in health risk behaviors (such as smoking). It is hard to delay gratification and most health risk behaviors are satisfying in the short-term and unsatisfying in the long-term, while most protective behaviors are predominately unsatisfying in the short-term and satisfying in the longer-term .

So, back to why my intention to run in the morning failed to lead to running after the alarm went off.

Last night when I set my alarm for 5:30 AM I was thinking about my long-term health, “I’ll look and feel so good in my summer swimsuit after working out” or “I’ll be less prone to disease when I’m older”.  Further the immediate costs of setting the alarm were low—I only had to click few buttons. In contrast, while reaching for the snooze, the costs of running were more immediate and the short-term consequence were salient, “I’m tired now, and I’ll be too sleepy to be productive today if I run”.

These tables and figures from Hall and Fong (2007) demonstrates how protective and risky health behavior have the opposite contingency valence with respect to time orientation. As depicted in the table 1, participants in this study estimated the point in time at which they would notice the benefit/cost of health protective behaviors (e.g. exercise and dieting), and health risk behaviors (e.g. smoking and drinking).

temporal proximity measure Hall and Fong (2007) Sticking with our morning run example, Figure 1 below demonstrates that people don’t notice the cost of running when thinking about rising at the crack of dawn for a run (question #1) or when deciding to run by setting the alarm an hour early (question #2). We start to feel the cost when the alarm goes off and we have to get out of bed and dress (questions #3). The perceived cost continues to grow as we run and after we’ve successfully run once (questions #4 and #5). We start to feel the cost less once we’ve made this morning run a regular routine for a week (question #6). As we continue to engage in our morning run routine the perceived cost continues to decrease, completely disappearing after a several years (question #9).

Now, what about the benefit of running early in the morning? Figure 1 indicates that we don’t feel the benefit of our run until we’ve done it regularly for a week (question #6), at which point the benefits grow exponentially for a year (question #8) and then decreases toward zero as we approach a decade (question #10).

These results provide evidence that the perceived benefit of running occurs well after the initial behavior occurs, while the perceived cost is felt just before, during  and a short while after the behavior initiates.

So when we are making the decision to set the alarm early for tomorrow’s run costs are low and abstract, so we are focusing on the long-term. When the alarm goes off and we are engaging in the behavior the costs are high and concrete, so we are focusing on the short-term. 

Before looking at Figure 1 below, notice that numbers 0 through 9 on the x-axis correspond to questions 1 through 10 in Table 1 pictured above. This is because academics like to make things more complicated than they need to be :). Screen Shot 2014-03-20 at 9.00.55 AM Figure 2 shows that the same trend holds for another health protective behavior (dieting). Screen Shot 2014-03-20 at 9.01.08 AMAs expected, the authors found the opposition result for health risk behavior—costs come after engaging in behavior and benefits occur before/during, see Figures 3 and 4 below. Screen Shot 2014-03-20 at 9.01.19 AM Screen Shot 2014-03-20 at 9.01.31 AM

So how does Temporal Self-Regulation Theory help me running in the morning? It suggests that on thing that might help is to try to minimize the short-term costs and maximize the short-term benefit. This can be hard, but may be as simple as rewarding yourself with a favorite breakfast if you complete the morning run.

Obviously, perceived temporal proximity with regard to behavior is only part of the picture. The authors introduce a working model (below) to illustrate Temporal Self-Regulation Theory more fully, which I’ve enhanced with definitions of each component. The model introduces two factors, behavioral prepotency and self-regulatory capacity that (1) influence (or moderate) the link between intentions and behavior; and (2) directly influence behavior in the absence of intentions. Health behaviors are complex and theories require continuous testing and refinement but Temporal Self-Regulation Theory adds an interesting new component to existing theories that is surely worth further consideration and testing.

Enhanced schematic representation of Temporal Self-Regulation Theory

References

Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22, 453-474.

Godin, G., & Kok, G. (1996). The theory of planned behavior: A review of its applications to health-related behaviors. American Journal of Health Promotion, 11, 87-98.

Hall, P. a., & Fong, G. T. (2007). Temporal self-regulation theory: A model for individual health behavior. Health Psychology Review, 1(1), 6–52. doi:10.1080/17437190701492437

Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132, 249-268. doi: 10.1037/0033-2909.132.2.249

 

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