حواس پرتی، میل به غذا خوردن و مصرف مواد غذایی. به سمت یک مدل توسعه یافته از غذا خوردن بدون فکر

Abstract This study compared the impact of different forms of distraction on eating behaviour with a focus on the mechanisms behind this association and the link between the amount consumed and changes in the desire to eat. Participants (n = 81) were randomly allocated to four conditions: driving, television viewing, social interaction or being alone in which they took part in a taste test. Measures of the desire to eat (i.e. Hunger, fullness, motivation to eat) were assessed before and after the intervention. The results showed that those watching television consumed more than the social or driving conditions. Food intake was associated with a decreased desire to eat for those eating alone, but was unrelated to changes in the desire to eat for those driving. Watching television also created a decrease in the desire to eat commensurate with food intake whereas social eating resulted in the reverse relationship. The results are discussed in terms an expanded model of mindless eating and it is argued that eating more requires not only distraction away from the symptom of hunger but also sufficient cognitive capacity left to attend to the process of eating.

Introduction Although the literature indicates a role for biological factors in the regulation of food intake (e.g. Mercer and Speakman, 2001 and Pinel, 2011) much research highlights that the desire to eat and eating behaviour are influenced by a multitude of psychological factors (see Conner, 2006 and Ogden, 2010 for reviews). One area that has received much attention over the past few years is the impact of distraction and the ways in which factors such as television viewing, aspects of the food environment and social interaction influence how much food is consumed. These will now be considered. In terms of the impact of television viewing, several studies indicate that food intake in the current meal is increased when distracted by watching television (Bellissimo et al., 2007 and Temple et al., 2007). Similarly, Higgs and Woodward (2009) showed an impact of television viewing on subsequent meals and reported that participants who ate lunch whilst watching television had less vivid memories of their lunch and consumed more in a subsequent snack tasting session compared to a control group. Furthermore, Blass et al. (2006) found that although those watching television ate significantly more food than a control group the two groups had comparable ratings of appetite. Moray, Fu, Brill, and Mayoral (2007) also concluded that estimates of food intake were less accurate if participants were watching television whilst eating. In a similar vein research indicates that many other factors may distract from eating including listening to a story (Bellisle and Dalix, 2001 and Long et al., 2011), listening to music (Stroebele & de Castro, 2006), playing a computer game (Oldham-Cooper, Hardman, Nicoll, Rogers, & Brunstrom, 2011) and engaging in a word counting task (Boon, Stroebe, Schut, & Ijntema, 2002). Research has also explored the ways in which aspects of the food environment can distract an individual making it easier to overeat and harder to monitor how much is being consumed (Fisher et al., 2003, Rozin et al., 1998 and Wansink, 2004). For example, a multitude of studies indicate that over eating can be triggered by factors such as the ambience of the room, container size, plate size, variety of food and perceived time of day (Stroebele and de Castro, 2006, Wansink et al., 2006, Wansink et al., 2006 and Wansink and Park, 2001). In particular, research indicates that the environment distracts the individual and that not only do people make automatic decisions to eat without any conscious processing, they also deny that the environment has an impact of their food intake (Wansink, 2004, Wansink, 2004, Wansink, 2009, Wansink, 2004, Wansink, 2009, Wansink and Kim, 2005, Wansink, 2004, Wansink and Sobal, 2007, Wansink, 2009 and Wansink and Kim, 2005). This process has been termed ‘mindless eating’ and can be contrasted with ‘mindful’ eating when people are encouraged to self monitor and process what they eat (Wansink and Sobal, 2007). Research has also addressed the impact of social influence on eating behaviour and several studies indicate that that people tend to eat more food in the presence of others or in groups rather than when eating alone (Berry et al., 1985, De Castro, 1991, De Castro and Brewer, 1992, Hirsch and Kramer, 1993, Patel and Schlundt, 2001 and Redd and de Castro, 1992). In line with research on television viewing it has been argued that social influence is also a type of distraction, as attention is generally diverted away from the meal to concentrate on actions such as talking and interpreting information (Hetherington, Anderson, Norton, & Newson, 2006). In contrast, however, it has been suggested that social influence functions via the expectations of the experience itself. For example Klesges, Bartsch, Norwood, Kautzrnan, and Haugrud (1984) argued that eating with others is regarded as a pleasant event, whereas eating alone is considered a response to overcoming hunger (Herman, Roth, & Polivy, 2003). Accordingly, such expectations change food intake. Similarly, Feunekes, de Graaf, and van Staveren (1995) suggested that people predict that they will overeat in the presence of others which in turn becomes a self fulfilling prophecy. This could be as a result of expecting to be eating for a longer period of time when in the presence of others as shown in de Castro’s time-extension hypothesis (1990), theorising that the more people present during a meal; the longer the duration of the meal and the greater the food intake (e.g. Bellisle et al., 1999, de Castro et al., 1997 and de Castro et al., 1990). Not all research, however, shows an increase in food intake in social situations and studies indicate that this effect is influenced by the relationships with the other people eating. For example, when the other person(s) present is a stranger, the social facilitation of eating tends to be weaker or even absent (Clendenen et al., 1994, De Castro, 1994, Hetherington et al., 2006 and Salvy et al., 2007). This may be a result of impression management and the desire to be seen in a positive light in front of strangers (Leary and Kowalski, 1990 and Tice et al., 1995). Mori, Chaiken, and Pliner (1987), however, argued that impression management is just as likely to take place between familiar companions of the opposite sex, especially if they find each other desirable. SimilarIy, Wansink and Park (2000) reported that whereas women decrease their food intake as an attempt to appear more feminine, men consider overeating to be a sign of masculinity and power. Research has also highlighted possible mechanisms for the impact of distraction on food intake with a particular focus on memory. For example, it has been argued that distraction divides an individual’s selective attention away from the encoding of the meal and interrupts episodic memory formation (Boon et al., 2002, Brunstrom and Mitchell, 2006, Chun and Turk-Browne, 2007, Stroebele and de Castro, 2006, Ward and Mann, 2000, Long et al., 2011 and Moray et al., 2007). In line with this, Herman and Polivy expanded their boundary model of eating to include a role for memory and reported that when the amount consumed by participants was made salient by leaving the wrappers of the sweets nearby, participants were more aware of how much they had eaten and consequently ate less than those who couldn’t see any wrappers (Polivy, Herman, Hackett, & Kuleshnyk, 1986). In a similar vein, research indicates that reminding participants of recent meals makes the memories of these meals more apparent which in turn suppresses subsequent food intake (Higgs, 2002, Higgs, 2005, Higgs, 2008 and Higgs et al., 2008a). Research also shows that lacking a memory of meals or having impaired memory such as amnesia can increase food intake (Higgs et al., 2008b and Rozin et al., 1998). Research has therefore explored the impact of distraction on food intake with a focus television viewing, the food environment and social interaction. Such studies, however, have tended to explore the impact of individual forms of cognitive distraction compared to a control condition of no distraction, rather than making comparisons across different manipulations of cognitive capacity. In line with this, the present experimental study aimed to compare across three different forms of distraction which varied in the extent to which they utilised an individual’s cognitive capacity and to assess their relative impact on eating behaviour. In particular, the study focused on two common distractions, namely, television viewing and social interaction and compared them with the impact of driving as although research indicates that eating whilst driving increases the risk of a crash due to a decrease in eye contact, attention to the road and taking the participants’ hand off the wheel (Stutts et al., 2005 and Young et al., 2008), little is known about the reverse affect of driving on eating. Therefore these three forms of distraction were compared to a control condition of eating alone. Some previous studies have also attempted to address the mechanisms behind the link between distraction and eating with a focus on memory. Although, providing some insights into the ways in which distraction may influence food intake the emphasis to date has been on distraction as a trigger to the onset of eating behaviour and food choice rather than eating as an ongoing behaviour. At its simplest, eating behaviour is a classic example of a negative feedback system as it is driven by factors such as hunger and a desire to eat which are in turn modified and reduced once food has been consumed causing a sense of fullness or satiety (Blundell, 1979 and Blundell and Burley, 1987). From this perspective, it is therefore hypothesised that not only does distraction trigger the onset of eating it distracts from the consequences of this eating, thus making changes in hunger and/or fullness harder to detect. The present study therefore explored the impact of distraction on the relationship between food intake and subsequent changes in hunger and the desire to eat. This finds reflection in the suggestion that as well as inhibiting memory, distraction may also inhibit our attention to signals of satiety which remains untested (Wansink, 2009). It is also parallel to the notion of hunger as a symptom which is perceived and modified through processes such as mood, attention and social influence (Ogden, 2007 and Roberts and Pennebaker, 1995; 2010). Accordingly, it was predicted that distraction would result in increased eating behaviour and that different forms of distraction would have differing effects on the amount consumed. In addition, it was also predicted that distraction would disrupt the relationship between food intake and a reduction in the desire to eat as participants would be less able to monitor the impact of any food consumed on their perceptions of hunger. No specific predictions were made as to which condition would be the most distracting or whether the mechanisms linking distraction with changes in food intake would be consistent or different across the different forms of distraction being manipulated.

Results Participants’ demographics Participants’ demographics by condition are shown in Table 1. The results showed that the majority of participants were full time students, white, with a mean age of 22 years. The four conditions were matched in terms of age, ethnicity, occupation, BMI, restrained eating and body dissatisfaction indicating that the randomisation procedure was effective. Table 1. Participant demographics by condition (means/SDs/%/n). Driving (n = 21) Television (n = 20) Social (n = 19) Alone (n = 21) F/X2 Age 22.38 22.9 21.95 21.9 F = 0.16 SD = 4.93 SD = 5.45 SD = 5.57 SD = 5.14 P = 0.95 Ethnic. W = 16 (76.2%) W = 18 (90%) W = 17 (89.5%) W = 20 (95.2%) X2 = 13.45 B = 0 (0%) B = 0 (0%) B = 0(0%) B = 1 (4.8%) P = 0.14 A = 5 (23.8%) A = 1 (5%) A = 1 (5.3%) A = 0 (0%) O = 0 (0%) O = 1 (5%) O = 1 (5.3%) O = 0 (0%) Occup. FT stud 19 (90.5%) 10 (50%) 14 (73.7%) 16 (76.2%) X2 = 10.53 Work 1 (4.8%) 9 (45%) 4 (21.1%) 5 (23.8%) P = 0.1 PT stud 1 (4.8%) 1 (5%) 1 (5.3%) 0 (0%) BMI 21.26 22.69 22.24 22.56 F = 0.46 SD = 2.39 SD = 5.16 SD = 5.19 SD = 4.25 P = 0.7 Rest. eating 2.67 2.43 2.45 2.45 F = 0.32 SD = 1.0 SD = 0.94 SD = 0.99 SD = 0.78 P = 0.8 Body diss. 2.22 2.65 2.47 2.48 F = 0.65 SD = 0.95 SD = 0.99 SD = 1.13 SD = 0.84 P = 0.6 Table options The impact of condition on changes in desire to eat and food intake The impact of condition on changes in desire to eat and food intake are shown in Table 2. Table 2. Impact of condition on the desire to eat and mass consumed (mean/SD). Driving (n = 21) Television (n = 20) Social (n = 19) Alone (n = 21) ME time (F/p) ME cond (F/p) Tx cond (F/p) T1 T2 T1 T2 T1 T2 T1 T2 Hung 2.98 2.74 3.51 2.8 3.4 2.8 3.2 2.8 23.6 0.5 1.1 −0.8 −1.1 −0.9 −0.9 −1.1 −1.3 −0.8 −0.8 0.0001 0.7 0.4 Full 2.4 2.7 2.2 2.8 2.2 2.7 2.4 3 32 0.5 0.6 −0.9 −1.2 −0.9 −0.8 −1 −1.2 −0.8 −0.7 0.0001 0.7 0.6 Mot 2.9 2.7 3.5 2.8 3.3 2.9 3.1 2.5 19.2 0.9 0.6 −0.8 −1.1 −0.9 −0.9 −1.1 −1.9 −0.9 −0.8 0.0001 0.4 0.6 Mass Cons (g) 14.02 28.61 14.16 18.21 ME cond −10.34 −24.44 −12.33 −20.9 F = 2.91 p = 0.04 Table options The results showed a significant main effect of time for hunger, fullness and motivation to eat indicating that regardless of condition participants reported a lower desire to eat after the intervention. The results showed no main effects of condition or time by condition interactions for any measures of the desire to eat. A main effect of condition was found for food intake. Post hoc tests showed that those in the television condition consumed more than those in the social (p < 0.01) and driving (p < 0.05) conditions. Differences between the television and alone condition were not significant (p = 0.06). Associations between food intake and baseline desire to eat The results for correlations between baseline hunger, fullness and motivation to eat and subsequent food intake are shown in Table 3. Table 3. Associations between baseline desire to eat and mass eaten across conditions. Driving (n = 21) Television (n = 20) Social (n = 19) Alone (n = 21) Hunger r = 0.27 r = 0.32 r = 0.37 r = 0.17 p = 0.23 p = 0.17 p = 0.12 r = 0.46 Fullness r = 0.04 r = −0.19 r = −0.37 r = −0.36 p = 0.87 p = 0.41 p = 0.12 p = 0.11 Motivation to eat r = 0.28 r = 0.34 r = 0.26 r = 0.21 p = 0.22 p = 0.14 p = 0.28 p = 0.37 Table options The results showed no significant correlations for any of the four conditions indicating that the amount consumed during the intervention was not related to participants’ baseline levels of their desire to eat. Associations between food intake and changes in desire to eat within and between conditions Changes in ratings of desire to eat were computed (T2–T1) so that more negative scores reflected a decrease in ratings of hunger, fullness and the motivation to eat. Associations between food intake and changes in the desire to eat within each condition were then analysed using Pearson’s correlation coefficients. Comparisons between conditions were then compared using the unstandardised beta coefficients and standard error scores to compute Z-scores (see Table 4). Table 4. Associations between mass consumed and changes in the desire to eat within and between conditions. Driving (n = 21) Television (n = 20) Social (n = 19) Alone (n = 21) Z scores Change in hunger r = 0.37 r = −0.51 ⁎ r = 0.33 r = −0.16 D−T = 1.56 ß = −3.8 ß = −11.87 ß = 4.56 ß = −5.25 D−S = 2.16⁎ SE = 2.2 SE = 4.7 SE = 3.17 SE = 7.6 D−A = −0.18 T−S = 2.89⁎ T−A = 0.74 S−A = −1.19 Change in fullness r = 0.11 r = 0.36 r = −0.09 r = 0.47 ⁎ D−T = −1.21 ß = 1.41 ß = 8.91 ß = −1.6 ß = 16.7 D−S = 0.56 SE = 2.99 SE = 5.4 SE = 4.5 SE = 7.07 D−A = −1.99⁎ T−S = −1.49 T−A = 0.88 S−A = −2.18⁎ Change in motivation to eat r = −0.26 r = −0.47 ⁎ r = 0.3 r = −0.47 ⁎ D−T = −1.67 ß = −2.6 ß = −12.5 ß = 3.99 ß = −9.3 D−S = −1.75 SE = 2.2 SE = 5.5 SE = 3.06 SE = 4.85 D−A = 1.26 T−S = −2.62⁎ T−A = −0.44 S−A = 2.32⁎ ⁎ p < 0.05. Table options In terms of associations within condition the results showed no associations between changes in the desire to eat and the mass consumed for either the driving or social conditions indicating that the amount eaten was unrelated to a change in either hunger, fullness or the motivation to eat. For the television condition, however, greater intake of food was associated with a greater decrease in both hunger and the motivation to eat and for those in the alone condition a greater intake of food was associated with a greater increase in fullness and a greater decrease in the motivation to eat. It is important to note that whilst the correlations between changes in hunger, motivation to eat and food intake were negative for the driving, television and alone conditions they were positive for the social condition. Further, whilst the correlations for fullness and food intake were positive for the driving, television and alone conditions they were negative for the social condition. This indicates that whilst increased food intake was related to a decrease in the desire to eat in the driving, television and alone conditions, it was associated with an increased desire to eat in the social condition. The data were then analysed to assess differences in the associations between food intake and the desire to eat between conditions. For changes in hunger, the results showed significant differences between the social condition and both the driving (p < 0.05) and the television condition (p < 0.05). For changes in fullness, differences were found between the alone condition and both the driving (p < 0.05) and the social condition (p < 0.05). Finally, in terms of the motivation to eat, differences were found between social condition and both the television (p < 0.05) and alone (p < 0.05) conditions. This indicates that the positive association between the amount eaten and several of the ratings of the change in the desire to eat found in both the alone and television conditions was significant greater than several of the ratings of the desire to eat in the social and driving conditions. Accordingly, when alone or watching television eating more was associated with a decrease in the desire to eat and this association was greater than when either driving or being sociable. Further, in the social condition, eating more was associated with an increase in the desire to eat.