The article by McKee et al. [1] offers fascinating new insights into the antecedents and consequences of dietary lapses in dieters. It is part of a growing innovative new movement of researchers applying ecological momentary assessment (EMA) methods to capture the causes of overeating in chronic dieters (restrained eaters) and of eating disorders such as bulimia nervosa [2–5]. In a nutshell, the goal of this movement is to go beyond mainstream cross-sectional research by getting as close as possible to “where the action takes place.” On the one hand, such efforts can add to our theoretical insights into the causes and consequences of eating problems. On the other, if we have a thorough understanding of what is driving eating problems in people’s natural environments, we can also devise more targeted interventions to help people cope with these problem behaviors in the here and now.

The work by McKee et al. stands out as a very comprehensive attempt to bring together a wide range of variables within one analysis and in pointing out promising avenues for intervention. The article may thus serve as a common ground and a call for future basic research delving more deeply into the underlying processes of some effects. For instance, why exactly does the presence of other people lead to overeating—is it due to activated social norms, licensing effects due to motivated social comparison, or other mechanisms? Do we see patterns of depletion if we rely on more indirect operationalizations of control efforts over time [6] rather than self-reported depletion at the time of measurement? Likewise, the article should stimulate applied interventions testing the effectiveness of various self-control (and coping) strategies to prevent (deal with) lapses in the most efficient way. McKee et al.’s intriguing supplementary analyses suggest that maladaptive patterns of “snowballing” (e.g., what-the-hell dynamics) may be more prevalent among overweight dieters, highlighting the need to find effective tools for relapse prevention.

What we are less certain about is whether the event-contingent approach used by McKee et al. is the best approach to also accurately gauge the base-rate of lapse occurrence. Specifically, event-contingent scheduling may lead to an overestimation of temptation enactment because actions may be more salient and more clearly defined than nonactions and strong temptations may be more likely to be reported than weak ones. The diary adherence analyses in McKee et al. suggests that participants may even be aware of their own reporting biases. Signal-contingent approaches, whereby the participant is prompted to report on current experience at random times, may be better suited to offset possible base-rate distortions (but may suffer from a lower number of critical observations instead).

For further criterion validation purposes, future field research should routinely include long-term follow-up measures of weight change as a “gold standard.” In our own basic research comparing dieters and nondieters, for instance, we linked EMA data with self-reported weight change over a 4-month period. We found that one factor that strongly discriminated successful from unsuccessful dieters was their performance on a laboratory measure of inhibitory control [4]. From a broader perspective of self-control [7], these and other studies in eating research and related areas suggest that dietary success may best be promoted by a combination of approaches, including those aimed at (a) reducing temptation strength [8, 9], (b) improving self-monitoring [10]—often a byproduct of the intervention itself, [c] boosting motivation such as via goal highlighting and precommittment [11], (d) training important cognitive ability factors such as inhibitory control and working memory capacity [12, 13], as well as (e) increasing the use of proactive strategies such as situation and stimulus selection that reduce the likelihood of temptation exposure. With the rapid advancements in technology, we predict that we will soon see a range of intelligent (i.e., flexible), smartphone-administered interventions building on these accumulated insights. Whether smarter phones can help dieters to effectively deal with evolutionarily inflicted motivational dilemmas of food intake in temptation-laden, “obesogenic” environments [14] remains to be seen.