Which messages about healthy and sustainable eating resonate best with consumers with low socio-economic status?

Consumers with low socioeconomic status (SES) eat less healthy and sustainable diets than consumers with higher status. This is attributed, at least in part, to inequalities in health communication. An online survey with 134 socioeconomically disadvantaged consumers in Italy was conducted to test the effectiveness of tailor-made communication material (infographics) about healthy and sustainable eating (HSE). Participants were recruited at two social supermarkets by a social service organisation as well as via a crowdsourcing platform. Participants found information about HSE delivered through infographics moderately effective in increasing motivation, capability, and opportunity for HSE, and moderately useful and likely to impact their behaviour. Certain messages were more effective than others for native consumers, while migrants showed more indifferent responses to the various messages and manifested lower motivation to shift towards HSE, limited access to and seeking of nutrition-related information, and lower trust in information sources. Selecting which messages to deliver strategically, while also considering differences between segments of the target audience and their preferred sources and channels for communication, is promising; yet, structural changes related to food's affordability and availability are also needed to facilitate an effective communication.

Changes in Food Consumption During the COVID-19 Pandemic: Analysis of Consumer Survey Data From the First Lockdown Period in Denmark, Germany, and Slovenia

This paper focuses on changes in food consumption that occurred during the COVID-19 pandemic. Its objective is to map changes at individual consumer level and identify the influence of different factors related to the COVID-19 pandemic on changes in individual food consumption. We conducted a cross-sectional online survey among 2,680 residents of Denmark (DK), Germany (DE), and Slovenia (SI) using quota sampling for gender, age and regional distribution. Data on consumption frequencies before and during the pandemic were collected with a food frequency questionnaire in the spring of 2020 (during the first lockdown period) for important types of fresh food and non-perishable food. Our results showed that, depending on the type of food, 15–42% of study participants changed their consumption frequency during the pandemic, compared to before. In all the study countries, the food categories with the highest rates of change were frozen food, canned food, and cake and biscuits; among the food categories with lower rates of change were bread, alcoholic drinks, and dairy products. People across all three countries shopped less frequently during lockdown and there was an overall reduction in the consumption of fresh foods, but an increase in the consumption of food with a longer shelf life in Denmark and Germany. Interestingly though, we observed diverging trends in all food categories analyzed, with some people decreasing and others increasing their consumption frequencies, demonstrating that the pandemic had different impacts on people's lifestyles and food consumption patterns. Using the method of multinomial regression analysis, we identified factors significantly (p < 0.01, p < 0.05, p < 0.1) related to increases and decrease in individuals' consumption frequencies in different food categories. The factors include restrictions put in place in response to the pandemic (i.e., closure of physical workplaces, canteens, cafés and restaurants, schools, and childcare institutions), changes in households' grocery shopping frequency, individuals' perceived risk of COVID-19, income losses due to the pandemic, and socio-demographic factors. Interesting differences between the countries were detected, allowing insights into the different food cultures. Conclusions include implications for policy-makers and actors in the food supply chain on the issues of healthy diets, food system resilience, and behavior change.

Effects of a diet based on inulin-rich vegetables on gut health and nutritional behavior in healthy humans

BACKGROUND

Inulin-type fructans (ITFs) are a type of fermentable dietary fiber that can confer beneficial health effects through changes in the gut microbiota. However, their effect on gut sensitivity and nutritional behavior is a matter of debate.

OBJECTIVE

We evaluated the impact of consuming ITF-rich vegetables daily on gut microbiota, gastro-intestinal symptoms, and food-related behavior in healthy individuals.

METHODS

A single group-design trial was conducted in 26 healthy individuals. During 2 wk, the participants were instructed to adhere to a controlled diet based on ITF-rich vegetables (providing a mean intake of 15 g ITF/d). Three test days were organized: before and after the nutritional intervention and 3 wk after returning to their usual diet. We assessed nutrient intake, food-related behavior, fecal microbiota composition, microbial fermentation, and gastrointestinal symptoms.

RESULTS

The major microbial modifications during the intervention were an increased proportion of the Bifidobacterium genus, a decreased level of unclassified Clostridiales, and a tendency to decrease Oxalobacteraceae. These changes were reversed 3 wk after the intervention. The volunteers showed greater satiety, a reduced desire to eat sweet, salty, and fatty food, and a trend to increase hedonic attitudes towards some inulin-rich vegetables. Only flatulence episodes were reported during the dietary intervention, whereas intestinal discomfort, inversely associated with Clostridium cluster IV and Ruminococcus callidus, was improved at the end of the intervention.

CONCLUSIONS

A higher consumption of ITF-rich vegetables allows a substantial increase in well-tolerated dietary fiber, which may in turn improve food-related behavior. Moreover, it leads to beneficial modifications of the gut microbiota composition and function. This trial is registered at clinicaltrial.gov as NCT03540550.

Does immersion or detachment facilitate healthy eating? Comparing the effects of sensory imagery and mindful decentering on attitudes and behavior towards healthy and unhealthy food

Many people would like to reduce indulging in unhealthy foods, but find it difficult to do so. Previous research shows that individuals eat smaller portions of unhealthy hedonic food if they first imagine the sensory properties of tempting food (sensory imagery; Cornil & Chandon, 2016). Similarly, they show less preference for such food if they think about food in a detached way (decentering; Papies, Barsalou, & Custers, 2012; Papies, Pronk, Keesman, & Barsalou, 2015). Given that these two mindsets are seemingly at odds with each other, we compared them across two studies to examine their effects on the preference for (Experiment 1) and consumption of (Experiment 2) hedonic healthy and unhealthy food. Although sensory imagery and decentering had largely different effects for preferences towards healthy and unhealthy foods, they had comparable effects on the consumption of both types of foods, serving to reduce the effects of consumption in participants affected by hunger and emotional eating. These results suggest that while sensory imagery and decentering are based on different mechanisms, they produce similar results when it comes to the consumption of hedonic food, regardless of how healthy the food is.

Which Factors Are Associated with Monitoring Goal Progress?

Three studies examined how people assess their progress on personal goals (e.g., whether they compare their progress to the past and/or to a desired target state), along with factors that might influence the nature of progress monitoring (e.g., whether the goal involves attaining a positive outcome or avoiding a negative outcome). Study 1 involved semi-structured interviews with 40 participants, in which we examined how participants monitored their progress and whether this was related to: (a) their level of self-efficacy, (b) whether the goal was prevention focused, and (c) whether goal progress was represented in quantifiable terms. Studies 2 (N = 492) and 3 (N = 481) were conducted online and additionally examined whether how participants monitored their progress differed as a function of the domain of the goal (i.e., whether it was related to physical development/health, finances, work/study, or social relationships). The findings suggest that participants: (i) were less likely to monitor their progress toward goals that were related to avoiding negative outcomes, (ii) were less likely to monitor their progress toward goals related to finances, work, or study with reference to the past, than progress toward other goals (e.g., those relating to physical development and health), (iii) found it easier to monitor their progress toward goals that they felt confident of attaining, but harder to monitor their progress toward goals related to work or study. Finally, the more participants thought about their goal in quantifiable terms, the more likely they were to monitor their progress, and the easier they found monitoring their progress to be. Taken together, these studies begin to describe the nature of progress monitoring and the factors that influence this important self-regulatory process.

Why Do People Act Like the Proverbial Ostrich? Investigating the Reasons That People Provide for Not Monitoring Their Goal Progress

Two studies examined peoples' reasons for not monitoring their progress toward their personal goals—a phenomenon that has been termed “the ostrich problem” (Webb et al., 2013). Study 1 used factor analysis to organize the reasons that people gave for not monitoring their goal progress, resulting in 10 factors. The most strongly endorsed reasons were: (a) that information on goal progress would demand a change in beliefs, or (b) undesired action; (c) that progress was poor, and (d) that thinking about and/or working on the goal was associated with negative emotions. Study 2 adopted a prospective design and investigated whether the reasons identified in Study 1 predicted: (a) the likelihood that participants would decline an opportunity to monitor their goal progress, and (b) the frequency with which participants monitored their goal progress. We found evidence that some of the most strongly endorsed reasons from Study 1 also predicted the avoidance of monitoring in Study 2; however, the belief that information about goal progress was likely to be inaccurate and not useful, and perceived control over goal attainment also reliably predicted the avoidance of monitoring in Study 2. Taken together, the findings explain why people do not monitor their goal progress and point to potential avenues for intervention.

What is the psychological impact of self-weighing? A meta-analysis

Many people self-weigh and many interventions addressing weight-related problems such as obesity promote self-weighing. However, while self-weighing has been associated with weight loss, there is mixed evidence regarding the psychological impact of this behaviour. The present review aimed to quantify the relationship between self-weighing and: (i) affect (e.g., anxiety, depression); (ii) psychological functioning (e.g., self-esteem); (iii) body-related attitudes and (iv) disordered eating. A computerized search of scientific databases in September 2014 and subsequent ancestry and citation searches identified 29 independent tests of the relationship between self-weighing on psychological outcomes. Meta-analysis was used to quantify the size of the association across the tests. Results indicated that there was no association between self-weighing and affect, body-related attitudes or disordered eating. There was, however, a small-sized negative association between self-weighing and psychological functioning. The age of participants, obesity status, the extent of weight loss, duration of self-weighing and study design (RCT versus correlational) were found to influence at least some of the psychological outcomes of self-weighing. The findings suggest that, for the most part, self-weighing is not associated with adverse psychological outcomes. However, in some cases the association between self-weighing and psychological outcomes may be more negative than in others.

Does monitoring goal progress promote goal attainment? A meta-analysis of the experimental evidence

Control theory and other frameworks for understanding self-regulation suggest that monitoring goal progress is a crucial process that intervenes between setting and attaining a goal, and helps to ensure that goals are translated into action. However, the impact of progress monitoring interventions on rates of behavioral performance and goal attainment has yet to be quantified. A systematic literature search identified 138 studies (N = 19,951) that randomly allocated participants to an intervention designed to promote monitoring of goal progress versus a control condition. All studies reported the effects of the treatment on (a) the frequency of progress monitoring and (b) subsequent goal attainment. A random effects model revealed that, on average, interventions were successful at increasing the frequency of monitoring goal progress (d+ = 1.98, 95% CI [1.71, 2.24]) and promoted goal attainment (d+ = 0.40, 95% CI [0.32, 0.48]). Furthermore, changes in the frequency of progress monitoring mediated the effect of the interventions on goal attainment. Moderation tests revealed that progress monitoring had larger effects on goal attainment when the outcomes were reported or made public, and when the information was physically recorded. Taken together, the findings suggest that monitoring goal progress is an effective self-regulation strategy, and that interventions that increase the frequency of progress monitoring are likely to promote behavior change.

What information do consumers consider, and how do they look for it, when shopping for groceries online?

Previous research investigating what information shoppers seek when purchasing groceries has used either lab-experiments or observed shoppers in supermarkets. The present research investigates this question in a relatively naturalistic online-grocery environment. Forty participants completed their weekly shopping online while their eye-movements were recorded. Ten of the participants were subsequently interviewed to gain insight into their information seeking behaviour. We found that, when looking for products, 95% of participants navigated through the 'virtual departments', 80% used the 'search' facility, and 68% browsed the special offer pages. Once on the product pages, participants tended to look at the pictures of products, rather than examine detailed product information. To explain these findings, we suggest that online grocery sites simulate familiar supermarket environments, which may explain why consumers prefer to browse categories of products rather than use search terms. We also suggest that additional strategies are needed if consumers are to be encouraged to view detailed product information.

The neural basis of monitoring goal progress

The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC) as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent functional magnetic resonance imagining (fMRI) while playing a game that involved monitoring progress toward either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory (WM) in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress toward a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring.

Discriminating between the Effects of Valence and Salience in the Implicit Association Test

The Implicit Association Test (IAT) is the most widely used indirect measure of attitudes in social psychology. It has been suggested that artefacts such as salience asymmetries and familiarity can influence performance on the IAT. Chang and Mitchell (2009) proposed that the ease with which IAT stimuli are classified (classification fluency) is the common mechanism underlying both of these factors. In the current study, we investigated the effect of classification fluency on the IAT and trialled a measure—the split IAT—for dissociating between the effects of valence and salience in the IAT. Across six experiments, we examined the relationship between target classification fluency and salience asymmetries in the IAT. In the standard IAT, the more fluently classified target category was, all else being equal, compatible with pleasant attributes over unpleasant attributes. Furthermore, the more fluently classified target category was more easily classified with the more salient attribute category in the split IAT, independent of evaluative associations. This suggests that the more fluently classified category is also the more salient target category.

Processing fluency as a predictor of salience asymmetries in the Implicit Association Test

The Implicit Association Test (IAT) is the most popular indirect measure of attitudes in social psychology. Rothermund and Wentura (2001, 2004) suggested that artifacts such as salience asymmetries are a source of compatibility effects in the IAT, and, therefore, the IAT does not necessarily measure attitude. They claim that salience asymmetries correspond with visual search asymmetries, such that the stimulus categories that are more quickly detected in a visual search task are also compatible in the IAT. We propose that processing fluency is a more reliable indicator of salience asymmetries in the IAT than are visual search asymmetries. To test this hypothesis, we set processing fluency in opposition to visual search asymmetry to see which variable better predicted IAT effects. In one pair of categories, the category that was more quickly detected in visual search was also more fluently processed in a binary classification task. In a second pair of categories, the category that was more quickly detected in visual search was the less fluently processed category. Across four experiments, we demonstrated that compatibility effects in the IAT corresponded with differences in processing fluency between categories, rather than with visual search asymmetries.