Notable psychological theories stress that decision-making depends on an individual’s cognitive frames or mental representations of the decision problem (Birnberg et al., 2007). The design of incentive systems has an important effect on cognitive frames that influence individuals’ perception of fairness, their levels of aspiration, and whether they see outcomes as gains or losses. Two leading psychology theories − organizational justice theory (Adams, 1963, 1966) and prospect/ framing theory (Kahneman and Tversky, 1979; Kahneman, 2003) − propose that cognitive frames arise by comparing an outcome to a reference point. In organizational justice theory, the reference point represents a comparison with a relevant other, whereas in prospect theory the reference point is basically the status quo (Kahneman, 2003) and may be invoked by a variety of characteristics of the incentive system. An idea common to both theories is that reference points shape cognitive frames and that a deviation from them causes internal conflicts that individuals try to avoid (Birnberg et al., 2007). In more complex decision situations, individuals face several cognitive frames at the same time, and the question arises on which one plays a central role in decision-making and how they interact. Although the two theories share a profoundly related concept, it is interesting that they remain discrete: whereas the organizational justice theory applies reference values to decisions about motivation to exert effort without explicit consideration of the outcome risk, prospect theory uses them to predict risk-taking behavior (pure monetary payoffs in the absence of any effort). Yet, in practice, decisions about risk and effort are often simultaneous: in many settings individuals face an option that requires a lot of effort, which potentially brings a high payoff, but the probability of obtaining that payoff depends on the success in completing the task. The alternative is to choose an easy option that requires little effort and has a high probability of success but results in a low payoff. Examples of these options are choosing between a more difficult or an easier field of study that leads to different future salary levels; between a demanding or a less demanding job with the corresponding pay levels and chances of success; between writing a scientific paper for a high impact journal or a low impact journal with the corresponding effort, probabilities of success, and impact factors; choosing between highly uncertain but high-yielding projects in which a lot of effort and new knowledge has to be invested or certain low-yielding projects that require an average amount of work and acquired knowledge. The aim of this paper is to use both theories to establish which cognitive frames dominate in simultaneous decisions on risk and effort. The literatures on neuroscience, psychology (Hughes et al., 2015; Salamone et al., 1994; Treadway et al., 2015; Walton et al., 2006; Wardle et al., 2012), and animal behavior (Cocker et al., 2012; Hosking et al., 2014a,b) jointly examine the relation between risk and effort (reviewed in Salamone et al., 2012; Miller et al., 2013). This body of work reinforces the conjecture that decisions about risk and effort are related because the neural networks activated in both types of decisions tend to overlap.