Autobiographical memory specificity and restrained eating: examining the influence of priming with images of healthy and unhealthy foods.

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Deborah Jane Wallis, Jessica Moss, Bethany Varnam, Barbara Dritschel, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2150713/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Jun, 2023 Read the published version in Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity → Version 1 posted 4 You are reading this latest preprint version Abstract Background : Dietary restraint has been linked to deficits in the ability to recall detailed memories of personally experienced events (referred to as autobiographical memory specificity). As priming with healthy foods increases the salience of restraint it would be expected to lead to greater deficits in memory specificity. Objective : To determine if priming word cues with images of healthy or unhealthy foods would influence the specificity of memory retrieval, and if deficits in memory specificity would be more evident in those reporting higher levels of dietary restraint, or currently dieting. Methods : Sixty female undergraduates self-reported if they were currently dieting and completed measures of mood, restraint, and disinhibition, and a modified version of the autobiographical memory task. Participants were presented with positive and negative words (unrelated to eating concerns) and asked to retrieve a specific memory in response to each cue. A food image was shown prior to each word cue; half of the participants were primed with images of healthy foods and half with images of unhealthy foods. Results : As expected, participants primed with healthy foods retrieved fewer specific memories than did those primed with unhealthy foods. However, neither restraint nor current dieting behaviour were associated with memory specificity. Conclusions : Differences in memory specificity between the priming conditions cannot be explained in terms of increased salience of restraint. However, it is plausible that unhealthy images led to an increase in positive affect, which in turn improved memory specificity. Level of evidence: Level I: Evidence obtained from: at least one properly designed experimental study dieting restraint memory-specificity positive affect priming 1. Introduction Autobiographical memory specificity (AMS) refers to the recollection of detailed memories of personally experienced events from one’s past and is intimately linked to the experience of the self [ 1 ]. Specific memories (e.g., ‘flying for the first time’ ) can come to mind spontaneously. However, everyday functioning often requires a voluntary search for memories, which makes demands on cognitive resources, particularly executive function [ 1 ]. A great deal of evidence relating to AMS has been generated using the autobiographical memory test (AMT;[ 2 ]). This task involves presenting participants with a series of cues (normally words) and inviting them to retrieve a specific memory from their past in response to each cue. Specific memories are defined as a memory of an event that occurred at a particular time and place, and that lasted less than one day. Studies using the AMT have revealed that certain groups have difficulties in accessing memories at the specific level. For example, participants with depression retrieve fewer specific memories ( 70% of trials) and instead retrieve categorical memories (e.g., “I always used to be happy”) [ 3 ]. This finding has been replicated numerous times (See [ 4 ] for a review) and has also been observed in individuals who have experienced significant trauma (see [ 5 ] for a review). Deficits in memory specificity have also been observed when images were used to cue memories in depressed and traumatised samples [ 6 , 7 ]. Poor AMS is associated with several negative consequences including poorer prognosis in participants with depression [ 8 ], greater risk of suicide [ 4 ], and impaired social problem solving [ 9 , 10 ]. Furthermore, poor AMS can predict depression in response to life stress, even in those without a history of depression [ 11 ] and moderate the impact of daily hassles on negative mood [ 12 ]. There is a growing body of evidence demonstrating impaired AMS in participants with clinical [ 13 – 17 ] and subclinical disordered eating [ 10 , 18 ]. One plausible explanation for poor AMS in participants with disordered eating relates to dietary restraint, which refers to the intentional restriction of food intake in order to reduce weight. Notably, restraint is associated with deficits in executive function, possibly due to individuals engaging in task irrelevant thoughts concerning food, weight, and body image [ 19 – 21 ]. Given the importance of executive function in voluntary retrieval of autobiographical memories [ 22 , 23 ], restraint would be expected to impair specificity by reducing the executive resources available to be utilised during the autobiographical memory search. Consistent with this line of reasoning, individuals who were currently dieting have been shown to retrieve fewer specific memories than non-dieters [ 24 ]. Similarly, scores on a measure of restraint, particularly concern with dieting , have been shown to negatively correlate with memory specificity [ 25 ]. There is also evidence that scores on the drive-for-thinness (DFT) subscale of the Eating Disorders Inventory (EDI, [ 26 ]), which correlates highly with measures of restrained eating [ 27 ], negatively predicts memory specificity [ 10 ]. Assuming that dietary restraint underlies the deficits in AMS observed in disordered eating, increasing the salience of this factor at the time of memory retrieval should worsen memory specificity. A robust method of making a concept salient is priming, which refers to the subconscious activation of mental representations (i.e., schema) that then bias the interpretation of incoming information, which in turn influences subsequent behaviour [ 28 ]. This is usually achieved by presenting one stimulus (the prime) for a brief period prior to the onset of the target stimulus [ 29 ]. In the context of eating, there is evidence that participants ate less after being primed with messages relating to healthy diet compared to a non-primed control group [ 30 ]. Similarly, in another study, females consumed fewer calories after being primed with words connoting healthy body image (e.g., slim) than neutral primes (e.g., room) [ 31 ]. Interestingly, priming participants with images of healthy snacks (compared to unhealthy) increased restraint in restrained eaters, but not unrestrained eaters [ 32 ]. A review of the priming literature confirmed the effectiveness of low-calorie foods in priming restraint [ 33 ]. Thus, images of healthy foods would seem the ideal method of priming restraint in the current study, with images of unhealthy foods being used in the control condition. The aim of the current study was to examine if using healthy and unhealthy food images to prime word cues on an autobiographical memory test would influence the proportion of specific memories retrieved on this task. Participants completed a modified version of the AMT whereby each memory cue (word) was preceded by an image of a food item. Half of the participants were primed with healthy images and half with unhealthy images. Participants reported if they were currently dieting and completed measures of mood (depression and anxiety), disinhibition and restraint. As healthy images were expected to make restraint salient [ 32 , 33 ] and as restraint has been linked to reduced memory specificity [ 10 , 26 ], it was predicted that, after controlling for depression, individuals primed with healthy images would retrieve significantly fewer specific memories on the AMT than would participants primed with unhealthy images. However, as priming of restraint should be more evident in those with high restraint scores [ 32 ] it was expected that individuals with higher restraint scores in the healthy prime condition would exhibit poorer memory specificity than would those with low restraint scores. In line with previous work [ 25 ], it was expected that self-reported dieters would retrieve fewer specific memories than would non-dieters. Assuming the finding in dieters is due to concurrent restraint, it would be expected that the deficit in memory specificity in dieters would be larger in the group primed with healthy images. 2. Methods 2.1. Design This study primarily used a 2 x 2 mixed factorial design, with priming condition (healthy vs unhealthy) as the between subjects’ factor and cue valence (positive vs negative) on the autobiographical memory test as the within subjects’ factor. A further 2x2 univariate design was used with dieting status and priming condition as the two between participant factors. The dependent variables were the time taken (in seconds) to retrieve specific memories and the proportion of specific memories retrieved. 2.2. Participants Sixty[1] female undergraduate students (mean age = 24.6, SD = 4.8), recruited using posters and social media adverts, took part in the study in exchange for course credit. Participants were assigned to one of two groups of 30. Ten individuals within each group reported that they were currently dieting. Characteristics of the two groups can be seen in Table 1. A power calculation using G*Power revealed that a sample size of 56 (28 per priming condition) would be required to detect a medium effect size (based on a predicted partial eta squared of .05) with a power of .8 and an alpha level of .05, thus the study was adequately powered. The study was approved by Research Ethics Committee of De Montfort University. 2.3. Materials and measures 2.3.1. Word cues: six positive words (calm, lively, happy, glorious, lucky, excited) and six negative words (sad, upset, tired, bored, bad, awful) matched for emotionality, imageability, and frequency of usage were drawn from a previous autobiographical memory study [34]. 2.3.2. Food images (primes): Twenty-four food images (12 high calorie, e.g., pizza, and 12 low calorie foods, e.g., salad) were drawn from a database of standardised food images (http://nutritionalneuroscience.eu/). The images had been rated for liking and perceived healthiness by adults and children [35]. The healthy (low-calorie) and unhealthy (high calorie) food depicted in the images used in the current study were equally liked, but high calorie foods were rated as significantly less healthy than low calorie foods. 2.3.3. Autobiographical Memory Test (AMT;[2]): Participants’ ability to retrieve specific memories of events from their past was assessed using a computerised variant of the AMT (presented using SuperLab version 5.1; Cedrus Corporation). Participants were presented with the word cues and invited to retrieve a specific memory in response to each cue word. A specific memory was defined as “a memory of an event that occurred at a particular time and place and that lasted less than a day”. Each word cue was primed with an image of a food item. Half of the participants were primed with images of healthy foods and half with images of unhealthy foods. Each trial began with a focus point (+) presented centrally (shown for 1 second), followed by a food prime (shown for 2 seconds[2]) and then a word cue (shown for 1 second) and participants asked to retrieve a specific memory in response to the cue word. Participants indicated they had retrieved a memory by pressing the space bar and were then asked to describe aloud the details of the memory, which were audio-recorded to allow for subsequent rating of specificity. If no memory was retrieved within 30 seconds (from the onset of the cue) then the next trial was initiated. Within each condition (healthy vs unhealthy) the order of the words and images was randomised for each participant. Prior to the main set of trials, participants completed two practice trials, where they received feedback relating to the specificity of their memory retrieval. Memories were coded as either specific (occurred at a specific time and place and lasted less than a day), categorical (summaries of repeated events), extended (events lasting longer than a day), or semantic associates (items, objects, places, or people associated with the cue). Decisions not to respond to a word, or failures to retrieve a memory within 30 seconds were coded as omissions. Memories were coded for specificity by the researcher who collected the data (either BV or JM) and subsequently by the first author (DW), who coded approximately 50% of the memories, to determine the reliability of the coding. There was a high degree of inter-rater reliability between the different coders ( K = 0.85). 2.3.4. Hospital Anxiety and Depression Scale (HADS [36]): The HADS is a 14-item questionnaire designed to measure anxiety and depression, with 7 items relating to each construct. Each item consists of four statements pertaining to a particular symptom and the participants is asked to choose the statement that best represents how they have been feeling during the last week. Each item is scored from 0-3 based on increasing severity of negative mood (maximum score of 21 on each subscale). Cronbach’s α indicated good reliability in the present study (anxiety = .83; depression = .84). 2.3.5. Three Factor Eating Questionnaire (TFEQ;[37]): The 21-item cognitive restraint subscale from the TFEQ was used to determine the degree to which participants were restrained eaters (i.e., making conscious efforts to restrict their food intake). Twelve items, e.g. “I consciously hold back at meals in order not to gain weight” require a true/false response. Eight items, e.g., “How likely are you to consciously eat less than you want?” require a response using a 4-point Likert-type scale to indicate likelihood of this behaviour, and the final item requires participants to rate their degree of restraint from zero (eat what I want, whenever I want) to 5 (highly restrained: constantly limiting food intake, never ‘giving in’). For each item, a response indicating restrained eating is scored with 1 point, thus the range of possible scores on this scale is 0-21, with higher scores equating to greater restraint. The 16-item disinhibition subscale from the TFEQ was used to assess the tendency of participants to overeat according to habit, situation, or under challenging conditions. This measure was included as there is evidence that disinhibition is linked to impaired episodic recall [38]. The disinhibition subscale consists of 16 items; thirteen items, e.g., “When I am blue, I often overeat” that require a true/false response and three items, e.g., “Do you eat sensibly in front of others and splurge alone?” that require a response on a 4-point Likert scale. Each response indicating a tendency to overeat is scored 1-point, thus the range of possible scores is 0-16 with higher scores equating to greater tendency towards disinhibited eating. In the present study both subscales showed good reliability, with Cronbach’s α of .74 (disinhibition) and .86 (cognitive restraint) respectively. 2.4. Procedure Having provided informed consent participants were randomly allocated to either the healthy or unhealthy priming conditions. They were then invited to complete the AMT followed by the demographic and questionnaire measures. Finally, height and weight were measured, in order to allow body mass index (BMI) to be calculated. 2.5. Data analysis Mean times (in seconds) to retrieve specific memories and the proportion of specific memories, adjusted for omissions, was calculated for each group and each type of word cue. For example, in response to positive cues if a participant retrieved four specific memories and made one omission then the proportion would be calculated using the following Eq. 4/(6 − 1)=, which would be .8 (80%). Retrieval times and proportion of specific memories were analysed using 2 prime (healthy vs unhealthy) x 2 cue valence (positive vs negative) mixed factorial ANCOVA, with HADS depression and restraint scores as covariates. To examine the influence of dieting status on memory performance (overall memory specificity) a 2 prime (healthy vs unhealthy) x dieting status (dieting vs not-dieting) univariate ANCOVA was conducted with depression entered as a covariate. Relationships between individual difference variables and memory performance were assessed using Pearson correlations (α adjusted for multiple tests). [1] An additional five participants took part but were excluded from the data analysis due to concerns about the quality of their memory data – extremely fast RTs and very high numbers (e.g., 10/12) of omissions [2] This timing was used to ensure supraliminal processing rather than subliminal 3. Results 3.1. Participant characteristics Analysis of the participant characteristics (see Table 1) of the two priming groups (healthy vs unhealthy) revealed no significant group differences in age, BMI, depression, anxiety restraint, or disinhibition (all tests p > .05). Dieters reported significantly higher restraint scores (mean = 13, SD = 3.6) than did non-dieters (M = 6.78, SD = 4.5); t(58) = 5.37, p .05). Table 1. Participant Characteristics (standard deviations are presented in parentheses). Healthy food primes (n=30) Unhealthy food primes (n=30) t-value P-Value Cohen’s d Age 24.33 (4.2) 24.9 (5.5) .45 >.05 .11 BMI 26.41 (5.5) 24.57 (6.0) 1.19 >.05 .32 Anxiety (HADS) 9.57 (4.0) 8.9 (4.5) .61 >.05 .16 Depression (HADS) 4.6 (3.7) 4.1 (3.4) .58 >.05 .15 Disinhibition (TFEQ) 6.53 (3.2) 7.3 (3.5) .92 >.05 .23 Restraint (TFEQ) 8.67 (4.6) 9.03 (5.7) .27 >.05 .08 Abbreviations: BMI= body mass index; HADS=Hospital Anxiety and Depression Scale; TFEQ = Three Factor Eating Questionnaire 3.2 Autobiographical memory performance Analysis of retrieval times for specific memories (presented in Table 2) revealed no main effects of valence, priming condition, restraint, or depression and no significant interactions, all tests p >.05. Analysis of the proportion of specific memories (see Table 2) revealed no main effects of valence; F(1, 54)=.23, p>.05, h 2 p =.004, restraint; F(1, 54)=.15, p>.05, h 2 p =.003, or depression; F(1, 54)=.44, p>.05, h 2 p =.008. There was, however, a significant main effect of priming condition, such that participants primed with images of healthy foods retrieved significantly fewer specific memories (M=.63, SD=.35) than did participants primed with unhealthy images (M=.77, SD=.25); F(1, 54)= 4.45, p=.04, h 2 p =.08. There was no significant condition x restraint interaction; F(1, 54)=1.11, p>.05, h 2 p =.02 and no condition x restraint x valence interaction; F(1, 54)=1.49, p>.05, h 2 p =.03. Importantly, there was no condition x depression nor condition x depression x valence interactions, both tests F<1. Table 2. Mean retrieval times (in seconds) and proportion of specific memories as a function of priming condition and cue valence (standard deviations are presented in parentheses). Healthy primes (n=30) Unhealthy primes (n=30) Retrieval Time (seconds) Proportion of specific memories Retrieval Time (seconds) Proportion of specific memories Positive 11.81 (4.5) .62 (.35) 11.28 (5.8) .81 (.23) Negative 12.62 (6.6) .65 (.34) 11.32 (5.6) .73 (.26) Total 11.52 (5.17) .63 (.35) 11.91 (6.1) .77 (.25) 3.3 Influence of dieting status on memory specificity Analysis of the proportion of specific memories retrieved as a function of priming condition and dieting status revealed no main effect of dieting status, as dieters (M=.70, SE=.07) and non-dieters (M=.70, SE=.07) retrieved an equivalent proportion of specific memories; F.05, h 2 p =.002 and no significant interactions, all tests F<1. However, the main effect of condition in this analysis was trend significant; F(1, 55)=2.89, p=.09, h 2 p =.05. 3.4 Relationships between individual difference factors and memory specificity A series of Pearson tests (with adjusted a = .02) revealed that overall memory specificity was not related to anxiety, disinhibition, or BMI; all tests >.05. 4. Discussion The aim of the current study was to examine if using healthy and unhealthy food images to prime word cues on an autobiographical memory test would influence the proportion of specific memories retrieved on this task. As images of healthy foods were expected to make restraint salient [32, 33] and as restraint has been linked to reduced memory specificity [10, 26], it was predicted that, after controlling for depression, individuals primed with healthy images would retrieve significantly fewer specific memories than would participants primed with unhealthy images. This prediction was supported by the current findings. However, as priming of restraint should have been more evident in those with high restraint scores [32] it was expected that individuals with higher restraint scores in the healthy prime condition would exhibit poorer memory specificity than would those with low restraint scores. This prediction was not supported by the current data. The predictions that dieters would retrieve fewer specific memories than would non-dieters and that this difference would be larger in the group primed with healthy images were not supported by the current findings. The finding that participants primed with healthy images produced fewer specific memories than did participants primed with unhealthy images could be due to the healthy images making restraint more salient, which in turn would have reduced the available resources available for the memory search [19-21]. However, the current finding that restraint was not related to specificity does not support this explanation. Similarly, the current finding that dieters did not retrieve fewer specific memories than did non-dieters is also inconsistent with this explanation, particularly as dieters reported significantly higher restraint than did non-dieters. Thus, it would appear unlikely that the observed difference in memory specificity was due to the salience of restraint. One alternative explanation concerns the possible influence of the different food items on the content of the memories retrieved. For example, it might be easier to recall specific memories of eating unhealthy foods (as these tend to be eaten at special occasions like birthdays) than healthy foods. However, examination of the content of the memories retrieved in the current study (n»600) revealed that fewer than 10 memories referring to food were recalled, which does not support this explanation of group difference in specificity. Another plausible explanation concerns the affective response to the different food primes. Although the images were matched for liking [35], previous work has shown that images of unhealthy foods lead to greater increases in positive affect than do images of healthy foods [39] and are more rewarding than images of low-calorie foods [40]; thus, the current findings could be due to increases in positive affect in those primed with unhealthy images. Consistent with this proposal memory specificity has been linked to changes in positive affect [41]. The findings that restraint and dieting did not influence AMS are inconsistent with previous studies [25, 26]. It is possible that the variation in findings across the studies are due to differences in the type of memory cues utilised. In the current study we used positive and negative cue words (unrelated to eating), whereas Johannsen and Berntsen [25] used weight- and body-related words (e.g., food & clothes) and Ball et al. [26] utilised food-related (e.g., chocolate) and diet-related cues (e.g., exercise). It is, therefore, plausible that the cues used in the previous studies were more salient to dieters and restrained eaters and may therefore have been more likely to lead to impaired AMS [34]. This is important, as it shows that the relationship between restraint and memory specificity may be dependent on the salience of memory cues. Limitations It is notable that we did not take a measure of state hunger, which potentially could have influenced the level of memory specificity. However, if this was the key factor then it would have been expected that images of unhealthy rather than healthy foods would have resulted in lower specificity, as, in hungry participants, images of high calorie foods are more likely to attract attention [42, 43], and more likely to demand processing resources than healthy foods [44, 45]. Another limitation is that we did not compare primed with un-primed retrieval; this would have provided stronger evidence regarding if it was healthy images or unhealthy that led to changes in memory specificity. Another limitation is that we did not determine if the participants had a history of psychiatric diagnosis (e.g., depression or an eating disorder). However, in the adverts for the study, it was requested that individuals with a history of a mental health condition should not volunteer for the study. Furthermore, the presence of individuals with clinically relevant depression, anxiety, or disordered eating would have been evident from the scores on the TFEQ and HADS (see Table 1), which were all within the normal range for the healthy population. Finally, it would have been useful to try to quantify changes in restraint and mood in response to the images. Future work should aim to confirm the current findings whilst addressing these limitations. Conclusions As expected, priming autobiographical memory retrieval with images of healthy food led to lower memory specificity than did priming with unhealthy food primes. However, this cannot be explained in terms of increased salience of restraint, or current dieting behaviour, as neither of these factors was related to memory specificity. It would appear that the influence of restraint and dieting on memory specificity might be dependent upon cue salience. The most plausible explanation for the group difference in specificity is that unhealthy images might have led to an increase in positive affect relative to healthy images, which in turn led to greater memory specificity. The current findings suggest that priming might be a useful method of examining changes in memory retrieval that are related to eating behaviour. What Is Already Known On This Subject? Disordered eating is associated with reduced memory specificity, possibly due to reduced cognitive resources associated with restraint. Healthy food images have been shown to increase the salience of restraint. Therefore, priming word cues with healthy food images should lead to poorer memory specificity. What this study adds? We aimed to provide novel evidence of a causal relationship between restraint and autobiographical memory. We examined if priming dietary restraint reduced the number of specific memories recalled. Declarations Compliance with Ethical Standards The study was approved by Research Ethics Committee of De Montfort University and was conducted in accordance with the ethical standards laid down in the Declaration of Helsinki (1964 and later amendments). All participants gave their informed consent prior to inclusion in the study. Conflict of interests: All authors declare that they have no conflict of interests Role of funding source: The work was not supported by any funding bodies Data Availability The dataset generated and analysed for this study can be requested from the corresponding author on reasonable request. Contributors: DW and NR designed the study. NR programmed the experiment in Superlab. JM and BV collected and scored the data (including transcription and initial coding, with DW coding for the purpose of inter-rater reliability). NR and DW conducted the data analysis. NR, DW & BD wrote the initial version of the manuscript. All authors contributed to, and approved, the final version of the manuscript. References Conway MA, Pleydell-Pearce CW (2000) The construction of autobiographical memories in the self-memory system. Psychol Rev 107(2):261–288. https://doi.org/10.1037/0033-295X.107.2.261 Williams JMG, Broadbent K (1986) Autobiographical memory in suicide attempters. 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The Effects of Food Priming on Restrained Eaters’ Food Consumption. Athens J Health 4:343–362. 10.30958/ajh.4-4-4 . https://pdfs.semanticscholar.org/e3ed/cccba174978dae7560e103c0fdd613175f09.pdf Buckland NJ, Er V, Redpath I, Beaulieu B (2018) Priming food intake with weight control cues: systematic review with a meta-analysis. Int J Behav Nutr Phys Activity 15(1):66. https://doi.org/10.1186/s12966-018-0698-9 Crane C, Barnhofer T, Williams JMG (2007) Cue self-relevance affects autobiographical memory specificity in individuals with a history major depression. Memory 15:312–327. https://doi.org/10.1080/09658210701256530 Charbonnier L, van Meer F, van der Laan LN, Viergever MA, Smeets PA (2016) Standardized food images: a photographing protocol and image database. Appetite 96:166–173. https://doi.org/10.1016/j.appet.2015.08.041 Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatrica Scandanavica 67(6):361–370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x Stunkard AJ, Messick S (1985) The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res 29(1):71–83 Martin AA, Davidson TL, McCrory MA (2018) Deficits in episodic memory are related to uncontrolled eating in a sample of healthy adults. Appetite 124(1):33–42. https://doi.org/10.1016/j.appet.2017.05.011 Privitera GJ, Antonetti DE, Creary HE (2013) The effect of food images on mood and arousal depends on dietary history and the fact and sugar content of the foods depicted. J Behav Brain Sci 3:1–6. http://dx.doi.org/10.4236/jbbs.2013.31001 Siep N, Roefs A, Roebroeck A, Havermansa,., Bonteb ML, Jansena A (2009) Hunger is the best spice: An fMRI study of the effects of attention, hunger and calorie content on food reward processing in the amygdala and orbitofrontal cortex. Behav Brain Res 198:149–158. https://doi.org/10.1016/j.bbr.2008.10.035 Yeung CA, Dalgleish T, Golden AM, Schartau P (2006) Reduced specificity of autobiographical memories following a negative mood induction. Behav Res Ther 44(10):1481–1490. https://doi.org/10.1016/j.brat.2005.10.011 di Pellegrino G, Magarelli S, Mengarelli F (2011) Food pleasantness affects visual selective attention. Q J Experimental Psychol 64:560–571. https://doi.org/10.1080/17470218.2010.504031 Piech RM, Pastorino MT, Zald DH (2010) All I saw was the cake. Hunger effects on attentional capture by visual food cues. Appetite 54:579–582. https://doi.org/10.1016/j.appet.2009.11.003 Harrar V, Toepel U, Murray M, Spence C (2011) Food’s visually-perceived fat content affects discrimination speed in an orthogonal spatial task. Exp Brain Res 214(3):351–356. https://doi.org/10.1007/s00221-011-2833-6 Toepel U, Knebel JF, Hudry J, le Coutre J, Murray MM (2009) The brain tracks the energetic value in food images. NeuroImage 44:967–974. https://doi.org/10.1016/j.neuroimage.2008.10.005 Cite Share Download PDF Status: Published Journal Publication published 21 Jun, 2023 Read the published version in Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity → Version 1 posted Reviewers agreed at journal 17 Oct, 2022 Editor assigned by journal 10 Oct, 2022 First submitted to journal 10 Oct, 2022 Editorial decision: Minor Revision 30 Mar, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2150713","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":144888810,"identity":"b341358c-9c3b-4fe1-bb8a-51f030eaf81d","order_by":0,"name":"Deborah Jane Wallis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDCCAzxgEoiZGw8kMNgkwCQMiNDC2ADUkkaqFgaGw4S18B3vPfi4ouYOg8Hxgw0HHvw5n8c/I4Hxww+Gw8a4tEieOZdseObYMwaDM4kNBxLbbhdL3EhgluxhOGyGS4vBjRwzyQa2wwxmB0BaGm4nbpBIYJAGutAGp5b7b4Ba/gG1nH8I9P6fcyAtzL/xarnBYybZ2AbUcgNoSwLbAZAWNpAtOB0meSYv2bCx7zCP/Y2HIL8kF0ucedhm2WOQjtP7fMfPHnzY8O2wnGR/8sGHP/7Y5fG3Jx++8aPC2rABlx4o4EFiMzbgi8hRMApGwSgYBUQAAOHPZcBS4tj3AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2216-1775","institution":"Birmingham City University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Deborah","middleName":"Jane","lastName":"Wallis","suffix":""},{"id":144888811,"identity":"a7f0f6ec-3d40-4df1-b973-57a70c87089f","order_by":1,"name":"Jessica Moss","email":"","orcid":"","institution":"De Montfort University Faculty of Health and Life Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jessica","middleName":"","lastName":"Moss","suffix":""},{"id":144888812,"identity":"aca10d62-4202-456c-bfb1-5556e8f3b4fd","order_by":2,"name":"Bethany Varnam","email":"","orcid":"","institution":"De Montfort University Faculty of Health and Life Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bethany","middleName":"","lastName":"Varnam","suffix":""},{"id":144888813,"identity":"5697874d-d315-4c78-a3ac-a0a0eed6b73e","order_by":3,"name":"Barbara Dritschel","email":"","orcid":"","institution":"Saint Andrews University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Dritschel","suffix":""},{"id":144888814,"identity":"a129e3ae-ea62-4c2c-83c7-56f621282c2b","order_by":4,"name":"Nathan Ridout","email":"","orcid":"https://orcid.org/0000-0002-7111-2996","institution":"Aston University School of Life and Health Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"Ridout","suffix":""}],"badges":[],"createdAt":"2022-10-10 11:28:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2150713/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2150713/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40519-023-01577-w","type":"published","date":"2023-06-21T21:19:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44731665,"identity":"7fdd5943-15b3-4e49-a324-ff168b6938e4","added_by":"auto","created_at":"2023-10-16 21:46:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":437255,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2150713/v1/00642db5-56dc-4deb-a5ca-eeb1b864c7bc.pdf"}],"financialInterests":"","formattedTitle":"Autobiographical memory specificity and restrained eating: examining the influence of priming with images of healthy and unhealthy foods.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAutobiographical memory specificity (AMS) refers to the recollection of detailed memories of personally experienced events from one\u0026rsquo;s past and is intimately linked to the experience of the self [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Specific memories (e.g., \u003cem\u003e\u0026lsquo;flying for the first time\u0026rsquo;\u003c/em\u003e) can come to mind spontaneously. However, everyday functioning often requires a voluntary search for memories, which makes demands on cognitive resources, particularly executive function [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A great deal of evidence relating to AMS has been generated using the autobiographical memory test (AMT;[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]). This task involves presenting participants with a series of cues (normally words) and inviting them to retrieve a specific memory from their past in response to each cue. Specific memories are defined as a memory of an event that occurred at a particular time and place, and that lasted less than one day. Studies using the AMT have revealed that certain groups have difficulties in accessing memories at the specific level. For example, participants with depression retrieve fewer specific memories (\u0026lt;\u0026thinsp;60% of trials) compared to controls (\u0026gt;\u0026thinsp;70% of trials) and instead retrieve categorical memories (e.g., \u0026ldquo;I always used to be happy\u0026rdquo;) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This finding has been replicated numerous times (See [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] for a review) and has also been observed in individuals who have experienced significant trauma (see [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] for a review). Deficits in memory specificity have also been observed when images were used to cue memories in depressed and traumatised samples [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Poor AMS is associated with several negative consequences including poorer prognosis in participants with depression [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], greater risk of suicide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and impaired social problem solving [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, poor AMS can predict depression in response to life stress, even in those without a history of depression [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and moderate the impact of daily hassles on negative mood [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is a growing body of evidence demonstrating impaired AMS in participants with clinical [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and subclinical disordered eating [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. One plausible explanation for poor AMS in participants with disordered eating relates to dietary restraint, which refers to the intentional restriction of food intake in order to reduce weight. Notably, restraint is associated with deficits in executive function, possibly due to individuals engaging in task irrelevant thoughts concerning food, weight, and body image [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Given the importance of executive function in voluntary retrieval of autobiographical memories [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], restraint would be expected to impair specificity by reducing the executive resources available to be utilised during the autobiographical memory search. Consistent with this line of reasoning, individuals who were currently dieting have been shown to retrieve fewer specific memories than non-dieters [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Similarly, scores on a measure of restraint, particularly \u003cem\u003econcern with dieting\u003c/em\u003e, have been shown to negatively correlate with memory specificity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. There is also evidence that scores on the \u003cem\u003edrive-for-thinness (DFT)\u003c/em\u003e subscale of the Eating Disorders Inventory (EDI, [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]), which correlates highly with measures of restrained eating [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], negatively predicts memory specificity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Assuming that dietary restraint underlies the deficits in AMS observed in disordered eating, increasing the salience of this factor at the time of memory retrieval should worsen memory specificity.\u003c/p\u003e \u003cp\u003eA robust method of making a concept salient is priming, which refers to the subconscious activation of mental representations (i.e., schema) that then bias the interpretation of incoming information, which in turn influences subsequent behaviour [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This is usually achieved by presenting one stimulus (the prime) for a brief period prior to the onset of the target stimulus [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In the context of eating, there is evidence that participants ate less after being primed with messages relating to healthy diet compared to a non-primed control group [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Similarly, in another study, females consumed fewer calories after being primed with words connoting healthy body image (e.g., slim) than neutral primes (e.g., room) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Interestingly, priming participants with images of healthy snacks (compared to unhealthy) increased restraint in restrained eaters, but not unrestrained eaters [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A review of the priming literature confirmed the effectiveness of low-calorie foods in priming restraint [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Thus, images of healthy foods would seem the ideal method of priming restraint in the current study, with images of unhealthy foods being used in the control condition.\u003c/p\u003e \u003cp\u003eThe aim of the current study was to examine if using healthy and unhealthy food images to prime word cues on an autobiographical memory test would influence the proportion of specific memories retrieved on this task. Participants completed a modified version of the AMT whereby each memory cue (word) was preceded by an image of a food item. Half of the participants were primed with healthy images and half with unhealthy images. Participants reported if they were currently dieting and completed measures of mood (depression and anxiety), disinhibition and restraint. As healthy images were expected to make restraint salient [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and as restraint has been linked to reduced memory specificity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], it was predicted that, after controlling for depression, individuals primed with healthy images would retrieve significantly fewer specific memories on the AMT than would participants primed with unhealthy images. However, as priming of restraint should be more evident in those with high restraint scores [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] it was expected that individuals with higher restraint scores in the healthy prime condition would exhibit poorer memory specificity than would those with low restraint scores. In line with previous work [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], it was expected that self-reported dieters would retrieve fewer specific memories than would non-dieters. Assuming the finding in dieters is due to concurrent restraint, it would be expected that the deficit in memory specificity in dieters would be larger in the group primed with healthy images.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003e2.1. Design\u003c/h2\u003e\n \u003cp\u003eThis study primarily used a 2 x 2 mixed factorial design, with priming condition (healthy vs unhealthy) as the between subjects\u0026rsquo; factor and cue valence (positive vs negative) on the autobiographical memory test as the within subjects\u0026rsquo; factor. A further 2x2 univariate design was used with dieting status and priming condition as the two between participant factors. The dependent variables were the time taken (in seconds) to retrieve specific memories and the proportion of specific memories retrieved.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003e2.2. Participants\u003c/h2\u003e\n \u003cp\u003eSixty[1] female undergraduate students (mean age\u0026thinsp;=\u0026thinsp;24.6, SD\u0026thinsp;=\u0026thinsp;4.8), recruited using posters and social media adverts, took part in the study in exchange for course credit. Participants were assigned to one of two groups of 30. Ten individuals within each group reported that they were currently dieting. Characteristics of the two groups can be seen in Table 1. A power calculation using G*Power revealed that a sample size of 56 (28 per priming condition) would be required to detect a medium effect size (based on a predicted partial eta squared of .05) with a power of .8 and an alpha level of .05, thus the study was adequately powered. The study was approved by Research Ethics Committee of De Montfort University.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003e2.3. Materials and measures\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003e2.3.1. Word cues:\u0026nbsp;\u003c/em\u003esix positive words (calm, lively, happy, glorious, lucky, excited) and six negative words (sad, upset, tired, bored, bad, awful) matched for emotionality, imageability, and frequency of usage were drawn from a previous autobiographical memory study [34].\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e2.3.2.\u0026nbsp;\u003c/em\u003e\u003cem\u003eFood images (primes):\u003c/em\u003e Twenty-four food images (12 high calorie, e.g., pizza, and 12 low calorie foods, e.g., salad) were drawn from a database of standardised food images (http://nutritionalneuroscience.eu/). The images had been rated for liking and perceived healthiness by adults and children [35]. The healthy (low-calorie) and unhealthy (high calorie) food depicted in the images used in the current study were equally liked, but high calorie foods were rated as significantly less healthy than low calorie foods.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e2.3.3.\u0026nbsp;\u003c/em\u003e\u003cem\u003eAutobiographical Memory Test (AMT;[2]):\u0026nbsp;\u003c/em\u003eParticipants\u0026rsquo; ability to retrieve specific memories of events from their past was assessed using a computerised variant of the AMT (presented using SuperLab version 5.1; Cedrus Corporation). Participants were presented with the word cues and invited to retrieve a specific memory in response to each cue word. A specific memory was defined as \u003cem\u003e\u0026ldquo;a memory of an event that occurred at a particular time and place and that lasted less than a day\u0026rdquo;.\u003c/em\u003e Each word cue was primed with an image of a food item. Half of the participants were primed with images of healthy foods and half with images of unhealthy foods.\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eEach trial began with a focus point (+) presented centrally (shown for 1 second), followed by a food prime (shown for 2 seconds[2]) and then a word cue (shown for 1 second) and participants asked to retrieve a specific memory in response to the cue word. \u0026nbsp;Participants indicated they had retrieved a memory by pressing the space bar and were then asked to describe aloud the details of the memory, which were audio-recorded to allow for subsequent rating of specificity. If no memory was retrieved within 30 seconds (from the onset of the cue) then the next trial was initiated. \u0026nbsp; Within each condition (healthy vs unhealthy) the order of the words and images was randomised for each participant. Prior to the main set of trials, participants completed two practice trials, where they received feedback relating to the specificity of their memory retrieval. Memories were coded as either specific (occurred at a specific time and place and lasted less than a day), categorical (summaries of repeated events), extended (events lasting longer than a day), or semantic associates (items, objects, places, or people associated with the cue). Decisions not to respond to a word, or failures to retrieve a memory within 30 seconds were coded as omissions. Memories were coded for specificity by the researcher who collected the data (either BV or JM) and subsequently by the first author (DW), who coded approximately 50% of the memories, to determine the reliability of the coding. There was a high degree of inter-rater reliability between the different coders (\u003cem\u003eK\u003c/em\u003e = 0.85).\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e2.3.4.\u0026nbsp;\u003c/em\u003e\u003cem\u003eHospital Anxiety and Depression Scale (HADS [36]):\u0026nbsp;\u003c/em\u003eThe HADS is a 14-item questionnaire designed to measure anxiety and depression, with 7 items relating to each construct. Each item consists of four statements pertaining to a particular symptom and the participants is asked to choose the statement that best represents how they have been feeling during the last week. Each item is scored from 0-3 based on increasing severity of negative mood (maximum score of 21 on each subscale). Cronbach\u0026rsquo;s \u0026alpha; indicated good reliability in the present study (anxiety = .83; depression = .84).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e2.3.5.\u0026nbsp;\u003c/em\u003e\u003cem\u003eThree Factor Eating Questionnaire (TFEQ;[37]):\u0026nbsp;\u003c/em\u003eThe 21-item cognitive restraint subscale from the TFEQ was used to determine the degree to which participants were restrained eaters (i.e., making conscious efforts to restrict their food intake). Twelve items, e.g. \u0026ldquo;I consciously hold back at meals in order not to gain weight\u0026rdquo; require a true/false response. Eight items, e.g., \u0026ldquo;How likely are you to consciously eat less than you want?\u0026rdquo; require a response using a 4-point Likert-type scale to indicate likelihood of this behaviour, and the final item requires participants to rate their degree of restraint from zero (eat what I want, whenever I want) to 5 (highly restrained: constantly limiting food intake, never \u0026lsquo;giving in\u0026rsquo;). For each item, a response indicating restrained eating is scored with 1 point, thus the range of possible scores on this scale is 0-21, with higher scores equating to greater restraint. The 16-item disinhibition subscale from the TFEQ was used to assess the tendency of participants to overeat according to habit, situation, or under challenging conditions. This measure was included as there is evidence that disinhibition is linked to impaired episodic recall [38]. The disinhibition subscale consists of 16 items; thirteen items, e.g., \u0026ldquo;When I am blue, I often overeat\u0026rdquo; that require a true/false response and three items, e.g., \u0026ldquo;Do you eat sensibly in front of others and splurge alone?\u0026rdquo; that require a response on a 4-point Likert scale. Each response indicating a tendency to overeat is scored 1-point, thus the range of possible scores is 0-16 with higher scores equating to greater tendency towards disinhibited eating. In the present study both subscales showed good reliability, with Cronbach\u0026rsquo;s \u0026alpha; of .74 (disinhibition) and .86 (cognitive restraint) respectively.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003e2.4. Procedure\u003c/h2\u003e\n \u003cp\u003eHaving provided informed consent participants were randomly allocated to either the healthy or unhealthy priming conditions. They were then invited to complete the AMT followed by the demographic and questionnaire measures. Finally, height and weight were measured, in order to allow body mass index (BMI) to be calculated.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e2.5. Data analysis\u003c/h2\u003e\n \u003cp\u003eMean times (in seconds) to retrieve specific memories and the proportion of specific memories, adjusted for omissions, was calculated for each group and each type of word cue. For example, in response to positive cues if a participant retrieved four specific memories and made one omission then the proportion would be calculated using the following Eq. 4/(6\u0026thinsp;\u0026minus;\u0026thinsp;1)=, which would be .8 (80%). Retrieval times and proportion of specific memories were analysed using 2 prime (healthy vs unhealthy) x 2 cue valence (positive vs negative) mixed factorial ANCOVA, with HADS depression and restraint scores as covariates. To examine the influence of dieting status on memory performance (overall memory specificity) a 2 prime (healthy vs unhealthy) x dieting status (dieting vs not-dieting) univariate ANCOVA was conducted with depression entered as a covariate. Relationships between individual difference variables and memory performance were assessed using Pearson correlations (\u0026alpha; adjusted for multiple tests).\u003c/p\u003e\n \u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e[1] An additional five participants took part but were excluded from the data analysis due to concerns about the quality of their memory data \u0026ndash; extremely fast RTs and very high numbers (e.g., 10/12) of omissions\u0026nbsp;\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv\u003e\n \u003cp\u003e[2] This timing was used to ensure supraliminal processing rather than subliminal\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e3.1. Participant characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAnalysis of the participant characteristics (see Table 1) of the two priming groups (healthy vs unhealthy) revealed no significant group differences in age, BMI, depression, anxiety restraint, or disinhibition (all tests \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05). Dieters reported significantly higher restraint scores (mean\u0026thinsp;=\u0026thinsp;13, SD\u0026thinsp;=\u0026thinsp;3.6) than did non-dieters (M\u0026thinsp;=\u0026thinsp;6.78, SD\u0026thinsp;=\u0026thinsp;4.5); t(58)\u0026thinsp;=\u0026thinsp;5.37, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;1.47). However, they did not differ from non-dieters in age, BMI, depression, anxiety, or disinhibition (all tests p\u0026thinsp;\u0026gt;\u0026thinsp;.05).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1. Participant Characteristics (standard deviations are presented in parentheses).\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"579\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy food primes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnhealthy food primes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e\u003cstrong\u003et-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCohen\u0026rsquo;s d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e24.33 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e24.9 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e26.41 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e24.57 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety (HADS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e9.57 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e8.9 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression (HADS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e4.6 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e4.1 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisinhibition (TFEQ)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e6.53 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e7.3 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"23.1433506044905%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRestraint (TFEQ)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.962003454231432%\"\u003e\n \u003cp\u003e8.67 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.243523316062177%\"\u003e\n \u003cp\u003e9.03 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.398963730569948%\"\u003e\n \u003cp\u003e\u0026gt;.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.12607944732297%\"\u003e\n \u003cp\u003e.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eAbbreviations: BMI= body mass index; HADS=Hospital Anxiety and Depression Scale; TFEQ = Three Factor Eating Questionnaire\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u003cstrong\u003e3.2\u0026nbsp;\u003c/strong\u003eAutobiographical memory performance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAnalysis of retrieval times for specific memories (presented in Table 2) revealed no main effects of valence, priming condition, restraint, or depression and no significant interactions, all tests \u003cem\u003ep\u003c/em\u003e\u0026gt;.05.\u003c/p\u003e\n \u003cp\u003eAnalysis of the proportion of specific memories (see Table 2) revealed no main effects of valence; F(1, 54)=.23, p\u0026gt;.05,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.004, restraint; F(1, 54)=.15, p\u0026gt;.05,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.003, or depression; F(1, 54)=.44, p\u0026gt;.05,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.008. There was, however, a significant main effect of priming condition, such that participants primed with images of healthy foods retrieved significantly fewer specific memories (M=.63, SD=.35) than did participants primed with unhealthy images (M=.77, SD=.25); F(1, 54)= 4.45, p=.04,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.08. There was no significant condition x restraint interaction; F(1, 54)=1.11, p\u0026gt;.05,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.02 \u0026nbsp;and no condition x restraint x valence interaction; F(1, 54)=1.49, p\u0026gt;.05, h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.03. Importantly, there was no condition x depression nor condition x depression x valence interactions, both tests F\u0026lt;1.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. Mean retrieval times (in seconds) and proportion of specific memories as a function of priming condition and cue valence (standard deviations are presented in parentheses).\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.479201331114808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"44.09317803660566%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy primes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"43.427620632279535%\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnhealthy primes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=30)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.479201331114808%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.465890183028286%\"\u003e\n \u003cp\u003eRetrieval Time (seconds)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.62728785357737%\"\u003e\n \u003cp\u003eProportion of specific memories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.80199667221298%\"\u003e\n \u003cp\u003eRetrieval Time (seconds)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.625623960066555%\"\u003e\n \u003cp\u003eProportion of specific memories\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.479201331114808%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.465890183028286%\"\u003e\n \u003cp\u003e11.81 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.62728785357737%\"\u003e\n \u003cp\u003e.62 (.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.80199667221298%\"\u003e\n \u003cp\u003e11.28 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.625623960066555%\"\u003e\n \u003cp\u003e.81 (.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.479201331114808%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.465890183028286%\"\u003e\n \u003cp\u003e12.62 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.62728785357737%\"\u003e\n \u003cp\u003e.65 (.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.80199667221298%\"\u003e\n \u003cp\u003e11.32 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.625623960066555%\"\u003e\n \u003cp\u003e.73 (.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"12.479201331114808%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.465890183028286%\"\u003e\n \u003cp\u003e11.52 (5.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.62728785357737%\"\u003e\n \u003cp\u003e.63 (.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.80199667221298%\"\u003e\n \u003cp\u003e11.91 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.625623960066555%\"\u003e\n \u003cp\u003e.77 (.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e3.3\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;Influence of dieting status on memory specificity\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAnalysis of the proportion of specific memories retrieved as a function of priming condition and dieting status revealed no main effect of dieting status, as dieters (M=.70, SE=.07) and non-dieters (M=.70, SE=.07) retrieved an equivalent proportion of specific memories; F\u0026lt;1. There was also no main effect of depression; F(1, 55)=.11, p\u0026gt;.05,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.002\u0026nbsp;and no significant interactions, all tests F\u0026lt;1. However, the main effect of condition in this analysis was trend significant; F(1, 55)=2.89, p=.09,\u0026nbsp;h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e=.05.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cstrong\u003e3.4\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;Relationships between individual difference factors and memory specificity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eA series of Pearson tests (with adjusted a = .02) revealed that overall memory specificity was not related to anxiety, disinhibition, or BMI; all tests \u0026gt;.05.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe aim of the current study was to examine if using healthy and unhealthy food images to prime word cues on an autobiographical memory test would influence the proportion of specific memories retrieved on this task. As images of healthy foods were expected to make restraint salient [32, 33] and as restraint has been linked to reduced memory specificity [10, 26], it was predicted that, after controlling for depression, individuals primed with healthy images would retrieve significantly fewer specific memories than would participants primed with unhealthy images. This prediction was supported by the current findings. However, as priming of restraint should have been more evident in those with high restraint scores [32] it was expected that individuals with higher restraint scores in the healthy prime condition would exhibit poorer memory specificity than would those with low restraint scores. This prediction was not supported by the current data. The predictions that dieters would retrieve fewer specific memories than would non-dieters and that this difference would be larger in the group primed with healthy images were not supported by the current findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe finding that participants primed with healthy images produced fewer specific memories than did participants primed with unhealthy images could be due to the healthy images making restraint more salient, which in turn would have reduced the available resources available for the memory search [19-21]. \u0026nbsp;However, the current finding that restraint was not related to specificity does not support this explanation. Similarly, the current finding that dieters did not retrieve fewer specific memories than did non-dieters is also inconsistent with this explanation, particularly as dieters reported significantly higher restraint than did non-dieters. Thus, it would appear unlikely that the observed difference in memory specificity was due to the salience of restraint. One alternative explanation concerns the possible influence of the different food items on the content of the memories retrieved. For example, it might be easier to recall specific memories of eating unhealthy foods (as these tend to be eaten at special occasions like birthdays) than healthy foods. \u0026nbsp;However, examination of the content of the memories retrieved in the current study (n\u0026raquo;600) revealed that fewer than 10 memories referring to food were recalled, which does not support this explanation of group difference in specificity. Another plausible explanation concerns the affective response to the different food primes. Although the images were matched for liking [35], previous work has shown that images of unhealthy foods lead to greater increases in positive affect than do images of healthy foods [39] and are more rewarding than images of low-calorie foods [40]; thus, the current findings could be due to increases in positive affect in those primed with unhealthy images. Consistent with this proposal memory specificity has been linked to changes in positive affect [41]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe findings that restraint and dieting did not influence AMS are inconsistent with previous studies [25, 26]. It is possible that the variation in findings across the studies are due to differences in the type of memory cues utilised. In the current study we used positive and negative cue words (unrelated to eating), whereas Johannsen and Berntsen [25] used weight- and body-related words (e.g., food \u0026amp; clothes) and Ball et al. [26] utilised food-related (e.g., chocolate) and diet-related cues (e.g., exercise). It is, therefore, plausible that the cues used in the previous studies were more salient to dieters and restrained eaters and may therefore have been more likely to lead to impaired AMS [34]. This is important, as it shows that the relationship between restraint and memory specificity may be dependent on the salience of memory cues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIt is notable that we did not take a measure of state hunger, which potentially could have influenced the level of memory specificity. However, if this was the key factor then it would have been expected that images of unhealthy rather than healthy foods would have resulted in lower specificity, as, in hungry participants, images of high calorie foods are more likely to attract attention [42, 43], and more likely to demand processing resources than healthy foods [44, 45]. Another limitation is that we did not compare primed with un-primed retrieval; this would have provided stronger evidence regarding if it was healthy images or unhealthy that led to changes in memory specificity. Another limitation is that we did not determine if the \u0026nbsp; participants had a history of psychiatric diagnosis (e.g., depression or an eating disorder). However, in the adverts for the study, it was requested that individuals with a history of a mental health condition should not volunteer for the study. Furthermore, the presence of individuals with clinically relevant depression, anxiety, or disordered eating would have been evident from the scores on the TFEQ and HADS (see Table 1), which were all within the normal range for the healthy population. \u0026nbsp;Finally, it would have been useful to try to quantify changes in restraint and mood in response to the images. Future work should aim to confirm the current findings whilst addressing these limitations.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAs expected, priming autobiographical memory retrieval with images of healthy food led to lower memory specificity than did priming with unhealthy food primes. However, this cannot be explained in terms of increased salience of restraint, or current dieting behaviour, as neither of these factors was related to memory specificity. It would appear that the influence of restraint and dieting on memory specificity might be dependent upon cue salience. The most plausible explanation for the group difference in specificity is that unhealthy images might have led to an increase in positive affect relative to healthy images, which in turn led to greater memory specificity. The current findings suggest that priming might be a useful method of examining changes in memory retrieval that are related to eating behaviour.\u0026nbsp;\u003c/p\u003e"},{"header":"What Is Already Known On This Subject?","content":"\u003cp\u003eDisordered eating is associated with reduced memory specificity, possibly due to reduced cognitive resources associated with restraint. Healthy food images have been shown to increase the salience of restraint. Therefore, priming word cues with healthy food images should lead to poorer memory specificity. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe aimed to provide novel evidence of a causal relationship between restraint and autobiographical memory. We examined if priming dietary restraint reduced the number of specific memories recalled.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by Research Ethics Committee of De Montfort University and was conducted in accordance with the ethical standards laid down in the Declaration of Helsinki (1964 and later amendments). All participants gave their informed consent prior to inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflict of interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of funding source:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was not supported by any funding bodies\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset generated and analysed for this study can be requested from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDW and NR designed the study. NR programmed the experiment in Superlab. JM and BV collected and scored the data (including transcription and initial coding, with DW coding for the purpose of inter-rater reliability). NR and DW conducted the data analysis. NR, DW \u0026amp; BD wrote the initial version of the manuscript. All authors contributed to, and approved, the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eConway MA, Pleydell-Pearce CW (2000) The construction of autobiographical memories in the self-memory system. Psychol Rev 107(2):261\u0026ndash;288. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-295X.107.2.261\u003c/span\u003e\u003cspan address=\"10.1037/0033-295X.107.2.261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams JMG, Broadbent K (1986) Autobiographical memory in suicide attempters. 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NeuroImage 44:967\u0026ndash;974. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuroimage.2008.10.005\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2008.10.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eawd","sideBox":"Learn more about [Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity](https://www.springer.com/journal/40519)","snPcode":"40519","submissionUrl":"https://submission.nature.com/new-submission/40519/3","title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"dieting, restraint, memory-specificity, positive affect, priming","lastPublishedDoi":"10.21203/rs.3.rs-2150713/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2150713/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eDietary restraint has been linked to deficits in the ability to recall detailed memories of personally experienced events (referred to as autobiographical memory specificity). As priming with healthy foods increases the salience of restraint it would be expected to lead to greater deficits in memory specificity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eTo determine if priming word cues with images of healthy or unhealthy foods would influence the specificity of memory retrieval, and if deficits in memory specificity would be more evident in those reporting higher levels of dietary restraint, or currently dieting.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eSixty female undergraduates self-reported if they were currently dieting and completed measures of mood, restraint, and disinhibition, and a modified version of the autobiographical memory task. Participants were presented with positive and negative words (unrelated to eating concerns) and asked to retrieve a specific memory in response to each cue. A food image was shown prior to each word cue; half of the participants were primed with images of healthy foods and half with images of unhealthy foods.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eAs expected, participants primed with healthy foods retrieved fewer specific memories than did those primed with unhealthy foods. However, neither restraint nor current dieting behaviour were associated with memory specificity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: \u003c/em\u003eDifferences in memory specificity between the priming conditions cannot be explained in terms of increased salience of restraint. However, it is plausible that unhealthy images led to an increase in positive affect, which in turn improved memory specificity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLevel of evidence:\u003c/strong\u003e Level I: Evidence obtained from: at least one properly designed experimental study\u003c/p\u003e","manuscriptTitle":"Autobiographical memory specificity and restrained eating: examining the influence of priming with images of healthy and unhealthy foods.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-10-19 16:42:41","doi":"10.21203/rs.3.rs-2150713/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2022-10-17T15:33:18+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2022-10-10T13:31:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","date":"2022-10-10T07:26:49+00:00","index":"","fulltext":""},{"type":"decision","content":"Minor Revision","date":"2020-03-30T13:10:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"eawd","sideBox":"Learn more about [Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity](https://www.springer.com/journal/40519)","snPcode":"40519","submissionUrl":"https://submission.nature.com/new-submission/40519/3","title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"fc4a4bd0-9df0-412a-8491-b7e37a3bde2a","owner":[],"postedDate":"October 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T21:29:53+00:00","versionOfRecord":{"articleIdentity":"rs-2150713","link":"https://doi.org/10.1007/s40519-023-01577-w","journal":{"identity":"eating-and-weight-disorders-studies-on-anorexia-bulimia-and-obesity","isVorOnly":false,"title":"Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity"},"publishedOn":"2023-06-21 21:19:12","publishedOnDateReadable":"June 21st, 2023"},"versionCreatedAt":"2022-10-19 16:42:41","video":"","vorDoi":"10.1007/s40519-023-01577-w","vorDoiUrl":"https://doi.org/10.1007/s40519-023-01577-w","workflowStages":[]},"version":"v1","identity":"rs-2150713","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2150713","identity":"rs-2150713","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}