In surveying the literature support for attention biases tow

In surveying the literature, support for attention biases towards appetitive cues appears in the substance abuse and obesity literatures. For example, attention bias towards drug-related cues has been found among alcohol (Field et al., 2004), tobacco (Bradley et al., 2003; Mogg et al., 2005), caffeine (Yeomans et al., 2005), and opioid (Garland et al., 2013; Lubman et al., 2000) users. As an example, Garland et al. (2013) found that semagacestat opioid-dependent chronic pain patients exhibited an attentional bias towards opioid cues (e.g., pictures of Oxycontin and Vicodin pills or bottles), whereas non-dependent opioid users did not. Moreover, among opioid-dependent individuals, the magnitude of the attentional bias was associated with the self-reported relief obtained from pain treatments (Garland et al., 2013). Similarly, heavy alcohol drinkers showed an attentional bias towards alcohol cues in comparison to light social drinkers, and self-reported alcohol craving was correlated with the magnitude of the attentional bias (Field et al., 2004). In addition, studies are beginning to explore the effects of training the attentional bias away from substance-relevant cues. For instance, in an attention bias modification paradigm similar to that used with anxiety disorders, training attentional bias away from alcohol cues significantly reduced the level of drinking compared to the control condition (McGeary et al., 2014). In line with our model, attention bias to alcohol-related cues is positively related to alcohol use during early adolescence (van Hemel-Ruiter et al., 2015) and alcohol bias predicts alcohol use in the following year (Janssen et al., 2015). Moreover, as predicted by our model, the relation between attention bias to alcohol cues and alcohol use seems to be moderated by effortful control – such that alcohol bias is related to alcohol use only for adolescents with low effortful control (van Hemel-Ruiter et al., 2015). A similar pattern of findings is present in the obesity literature, in which higher attentional bias towards food cues is present in obese and overweight adults compared to individuals with a healthy weight (e.g., Castellanos et al., 2009; Werthmann et al., 2011). Indeed, higher attention bias towards food cues has been related to higher craving and hunger in healthy weight and obese individuals (Kemps and Tiggemann, 2009; Werthmann et al., 2011). When required to fast, individuals (healthy or obese) displayed a bias towards food (Castellanos et al., 2009). However, only obese individuals were more likely to orient and maintain attention to food cues after eating. Moreover, across the entire sample, self-reported hunger and stimuli depicting higher calorie foods were positively related to increased likelihood of orienting towards food cues. Recent work training participants to attend towards or away from food-related cues in an anti-saccade task increased and reduced chocolate intake, accordingly (Werthmann et al., 2014). In support for our developmental model, the relation between attention bias towards food cues and obesity appears to be present during childhood – such that overweight 8- to 10-year-old children displayed a larger attention bias to food cues compared to normal weight children (Folkvord et al., 2015). Moreover, attentional bias to food cues seems to have developmental implications as producers predicted weight gain six months later in a group of obese children (Werthmann et al., 2015). However, the role of executive attention in this domain is still unclear. One study found that effortful control moderated the relation between approach bias, another type of cognitive bias related to the behavioral tendency to move towards food, such that individuals with high approach bias and low effortful control consumed higher amounts of unhealthy food than individuals with high effortful control (Kakoschke et al., 2015). Although there was a similar pattern with attention bias to food cues, in which individuals with high attention bias to food and low effortful control consumed the most food, the interaction was not significant (Kakoschke et al., 2015). Overall, the data suggest that attentional bias, as a general mechanism, is related to the motivational state of the individual (e.g., hunger). However, for some individuals, these rewarding cues remain salient across states, leading them to unhealthy outcomes (Castellanos et al., 2009).