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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation: A
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Brief Review and Meta-Analysis
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
Abstract
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Organic certification identifies food produced with more sustainable product methods.
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However, several studies have pointed out that it is also likely to generate a halo effect on the
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caloric estimation of food. As a result, unhealthy foods are perceived as containing fewer
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calories and may lead to increased consumption intentions. The aim of this paper is to
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quantify the magnitude of this organic halo effect and identify its possible moderators. We
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address the issue with a systematic review and a meta-analysis of the available literature
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specifically focused on the organic halo effect on food calorie estimation (i.e., 10 articles, 21
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studies). The results highlighted a strong "organic halo effect" on calorie estimation (r =
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0.40). Despite these findings, no stable moderator of the organic halo effect has been
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consistently identified across the literature. This meta-analysis provides a foundation for
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future research on the organic halo effect, offering a framework to guide upcoming studies on
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the phenomenon. The discussion outlines research avenues and advocates for a systematic
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investigation of specific moderators as well as an investigation of the conditions that promote
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the organic halo effect to facilitate and structured the exploration of the phenomenon.
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Keywords: Organic halo effect, Food labeling, Food Front-Packaging, Calories estimation,
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Food perceptions.
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
Introduction
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Overview of the Organic Halo Effect
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Health has emerged as a central concern for consumers in their food choices. This is reflected
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in a shift toward organically grown foods, which are often perceived as healthier and safer
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(Gundala et al., 2021; Kalra et al., 2021). This perception has contributed to a significant
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expansion of the organic food market in recent years (Food and Agriculture Organization of
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the United Nations, 2024; Willer et al., 2020). As defined and shared by numerous nations
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under international agreements (European Commission, 2022), the organic label ensures
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production that relies on natural substances and procedures. It preserves biodiversity and soil
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fertility while excluding synthetic fertilizers, pesticides, growth regulators, and feed additives
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(Browne et al., 2000; Sacchi et al., 2024). However, inconsistent findings have been reported
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regarding the nutritional differences between organic and non-organic foods (Gaylord et al.,
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2020; Kushi et al., 2012), and the association of the organic label with health benefits or low-
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calorie content is not consistently observed (Kst, 2019). Consumers often perceive organic
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foods as inherently healthier and more nutritious than conventionally produced alternatives,
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even though empirical evidence does not consistently support these beliefs (Giampieri et al.,
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2022). This gap between consumer beliefs and the reality of the organic label may lead
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individuals to underestimate the calories of certain products (Besson et al., 2019) and over
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consume them, especially in the case of unhealthy products (i.e., overly fatty or sweet
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products, Lee et al., 2018). According to some researchers, this phenomenon is associated
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with an increased risk of poor eating habits or the likelihood of skipping physical exercise,
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both of which are factors linked to overweight or obesity (Schuld & Schwarz, 2010, Schuldt
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et al., 2012). Overweight and obesity are associated with several health problems, including
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heart disease, diabetes, and hypertension (Chooi et al., 2019). Calorie awareness is critical to
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weight control and can influence individuals' dietary choices and overall health behaviors
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(Costa-Font & Mas, 2016; Shively et al., 2019). However, estimating the caloric content of
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foods remains a difficult and cognitively demanding task (Wansink & Chandon, 2006),
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leading to frequent underestimation by both lay and expert consumers, even when calorie
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information is available. For instance, Gustafson and Zeballos (2019) have conducted a study
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in which participants were asked to select ingredients for preparing a sandwich. Although
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participants were provided with the calorie count for each ingredient, they underestimated the
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total calorie content of the sandwich they were assembling by approximately 130 calories
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when the cumulative total was not explicitly displayed. These findings align with previous
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
research demonstrating that adults dining at fast-food restaurants tend to underestimate the
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calorie content of their meals by 175 calories (Block et al., 2013) and Taksler and Elbel
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(2014) showed that calorie labeling does not consistently improve consumers' estimates, while
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Cantor et al. (2015) found that awareness of calorie labeling declines over time. This
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underestimation in food content often results in overconsumption (Livingstone & Black,
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2003) and is considered a precursor to obesity (Lichtman et al., 1992; Young & Nestle, 2002).
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Several factors exacerbate this tendency, such as significantly underestimating larger portions
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(Bochard, 2018; Faulkner et al., 2014) and adding "healthy" foods like salads to a meal, which
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reduces the perceived calorie content of the entire dish (Chernev & Gal, 2010; Rozin &
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Holtermann, 2021). Food labels also influence consumer judgments (Schouteten et al., 2019),
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acting as contextual cues when direct information is inaccessible or difficult to interpret
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(Besson et al., 2019; Mussweiler, 2003). Labels can shape impressions of food products
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(Messer et al., 2017; Stoltze et al., 2021), as evidenced by studies showing that chocolate with
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a fair-trade label is perceived as having fewer calories (Schuldt et al., 2012), gluten-free
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products are considered healthier and lower in calories (Prada et al., 2019), and vegetarian-
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labeled hamburgers are seen as having fewer calories (Besson et al., 2020).
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Organic certification is one of the most extensively studied labels. Despite its intended
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purpose, it frequently results in lower calorie perceptions, higher fiber content estimations,
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and the belief that these foods can be consumed more often (Lee et al., 2013; Schuldt &
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Schwarz, 2010). These effects are more pronounced in environmentally conscious individuals
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(Prada et al., 2017; Schuldt & Schwarz, 2010). By reducing perceived calorie content, the
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organic label may inadvertently encourage overconsumption, particularly of fatty and sugary
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foods, posing significant health risks (Linder et al., 2010; Richetin et al., 2022; Schouteten et
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al., 2019; Schuldt & Schwarz, 2010). These labeling effects are attributed to the cognitive bias
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known as the halo effect (Berry & Romero, 2021; Besson et al., 2019; Chandon & Wansink,
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2007; Schuldt et al., 2012). First identified by Thorndike (1920) in the context of impression
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formation, this bias occurs when a favorable first impression leads to positive evaluations of
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other characteristics. The halo effect has been described as a transformation effect, where a
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"source characteristic" influences perceptions of a "target characteristic" (De Houwer et al.,
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2019). In the context of organic labeling, the "source characteristic" refers to the label itself,
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whereas the "target characteristic" pertains to the perceived calorie content. The organic halo
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effect – which involves consumers perceiving certain foods as healthier because of organic
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labeling or marketing (Schuldt & Schwarz, 2010) – has received considerable attention from
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
researchers over the last decade. They have shown that its implications for consumer behavior
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and health decisions could be significant. Yet, its reliability and effect size remain unclear.
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Rationale for the Meta-Analysis
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Despite the growing body of research documenting the impact of the organic label on calorie
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misestimation, no meta-analysis has yet been conducted to (i) estimate the magnitude of the
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effect, (ii) identify the degree of robustness of the effect across studies, and (iii) identify
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potential moderators. Hence, a systematic review and meta-analysis were conducted to
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examine its stability, reliability, and size. The primary objective was to identify relevant
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literature about the organic halo effect on calorie estimation, with the aim of providing a
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comprehensive overview of the available results and precisely determining its effect size.
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Methodology
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A comprehensive search of multiple databases was initially conducted (i.e., ScienceDirect,
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Scopus, Cochrane, Medline, PsycInfo, OpenGrey, PubMed, Trip Database, Sage Journals,
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HAL, AJPH) and on Google Scholar. The following search equation was used: ("Organic
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label" OR "Organic labeling" OR "Organic claim" OR "Eco-friendly label" OR "Eco-friendly
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labeling" OR "Eco-friendly claim") AND ("Calorie estimation" OR "Calorie evaluation" OR
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"Calorie judgments" OR "Kcal estimation" OR "Kcal evaluation" OR "Kcal judgments").
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This systematic review of the literature resulted in the identification of N = 151 documents.
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After the removal of duplicates and non-English documents, N = 95 documents remained.
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Each document was then assessed for relevance to the organic label and calorie estimation,
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with studies not focused on these topics being excluded. Further exclusions were made based
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on document type, retaining only original research articles and excluding critiques,
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commentaries, systematic reviews, memoirs, and excerpts. This process reduced the number
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of documents to N = 29. Additional exclusions were made by selecting only articles with a
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quantitative methodology, resulting in N = 10 documents being retained.
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In order to be included in the meta-analysis, studies had to provide quantitative data on calorie
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estimation influenced by organic labels and report sufficient statistical data to calculate effect
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sizes.. After applying these criteria, N = 10 studies met all requirements and were included in
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the final meta-analysis. Specific exclusions included nine studies with insufficient statistical
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data, five studies focusing on non-relevant variables, and five studies lacking a direct
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comparison between organic and non-organic labels in terms of calorie estimation. The
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screening process was conducted by two independent reviewers who assessed articles at each
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
stage based on predefined inclusion and exclusion criteria. Titles and abstracts were first
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screened for relevance, followed by full-text reviews of eligible studies. In cases where there
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was disagreement about the inclusion of a particular study, the reviewers discussed the study
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qualitatively and reached consensus through deliberation. Disagreements were resolved
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through discussion to ensure that all included studies met the eligibility criteria. The authors
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who participated in the screening process were the first and second author, with the fourth and
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last author acting as referee in cases of disagreement. This rigorous process ensured that our
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meta-analysis included only the most relevant and robust studies
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Figure 1. Flow diagram of references found using keywords selected according to PRISMA
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guidelines
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Results
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In order to calculate the effect size of the different results obtained in various studies on the
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caloric estimation of organic-labeled foods compared to non-labeled foods, when it was not
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
reported in the articles, we first gathered the data necessary to calculate these effect sizes for
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each study. For studies that performed an ANOVA, we used the observed F-value, degrees of
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freedom, error of degrees of freedom, and sample size, and for studies that performed t-tests,
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we recorded the observed t-value, degrees of freedom, and sample size. These effect sizes
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(i.e., Pearson's r) as well as the within-study variances were calculated using R (4.3.1). The
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effect sizes reported in the articles were previously converted to Pearson's r.
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Main Organic Halo Effect
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We conducted the meta-analysis with the “metafor” package through the JASP software, with
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a Paule-Mandel random-effects model. The heterogeneity test of the results is significant at a
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rate of 0.04, Q = 172335.442, p <.001 (see Appendix 2 and Figure 2), the value of the Q
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statistic indicates variation between effect size in the included studies, which may be
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associated with methodological differences. This variation in effect size is estimated at T2 =
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0.044 and the proportion of this variation due to heterogeneity is strong as I2 = 99.972
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indicates an extremely large proportion of variability (see Appendix 4). Thus, the results of
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the different studies are highly heterogeneous and studies in this meta-analysis cannot be
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considered as having similar population samples. The overall effect is statistically significant,
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r = 0.40 [0.31; 0.48], p < .001 (see Figure 2). In Figure 2, the study Prada et al. (2016)c
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appears furthest from the vertical line representing the null effect, suggesting that this
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intervention had the largest effect on the population compared to the other studies included in
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the analysis. Conversely, the study from Sörqvist et al., (2015)c is positioned closest to the
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vertical line, indicating that the intervention had the smallest effect on its population.
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Additionally, the confidence interval for this latter study intersects the vertical line, signifying
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that the intervention effect was not statistically significant.
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Figure 2. Forest plot showing effect sizes (Pearson's r) of included studies on calorie
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estimation. Each study is labeled according to its citation format (e.g., “Schuldt et Schwarz,
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2010”) for consistency with the text. The vertical line represents the overall estimated effect
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size (r = 0.40).
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
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Note. In some studies, multiple analyses were incorporated, reflecting various tests of the organic halo effect on
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calorie estimation conducted within a single research program. For Besson et al. (2019), a refers to the
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estimation of the organic halo effect in Study 1, and b refers to the estimation in Study 2. For Lee et al. (2013),
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the letters correspond to the product type tested in their single study: a = cookie, b = chips, c = yogurt. For Prada
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et al. (2017), a refers to the general test (general category) of the organic halo effect in Study 1, b to the general
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test in Study 2, c to the effect of a specific type of organic product (processed vs whole food) on calorie
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estimation in Study 1, and d to the effect of a specific type of organic product (processed vs whole food) in
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Study 2. For Prada et al. (2016)a, a refers to the organic halo effect in Study 1 (halo effect on calorie estimation
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for a dish). For Prada et al. (2016)b, b corresponds to the organic halo effect in Study 2 (halo effect on calorie
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estimation for a dish), while Prada et al. (2016)c refers to Study 2 (general beliefs associated with organic vs.
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conventional products).For McCrickerd et al. (2020)a, a refers to the organic halo effect on the product type
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soymilk, while for McCrickerd et al. (2020)b, b refers to the organic halo effect on the product type instant
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noodle. For Sörqvist et al. (2015)a, a refers to the test of the halo effect in Experiment 3. For Sörqvist et al.
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(2015)b, b corresponds to the test of the halo effect associated with the raisins product in Experiment 2, while
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Sörqvist et al. (2015)c, c refers to the test of the halo effect associated with the grape product in Experiment 2.
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
In this meta-analysis, a funnel plot (see Figure 3) was used to detect potential publication bias
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among the different studies. The black dots, which represent each of the studies, indicate the
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precision of the studies. As most of the studies are located at the top of the graph, the overall
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precision of the studies is good. The study closest to the common effect (i.e., vertical line) is
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the most precise, namely Sörqvist et al. (2015)b. The other studies, which are less precise, are
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more affected by chance. Furthermore, a regression test for funnel plot asymmetry was
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conducted to detect potential publication bias. Egger's test indicated a significant asymmetry
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(z = -2.92, p = .004) suggesting the presence of a potential publication bias.
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Figure 3. Funnel plot illustrating the distribution of effect sizes across studies relative to the
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standard error.
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In Figure 3, the funnel plot illustrates the distribution of effect sizes across studies, with the
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vertical line representing the overall estimated effect size (r = 0.40) derived from the meta-
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analysis. The horizontal axis labeled “GEN” refers to the generalization metric used to
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measure the distribution of effect sizes. The area within the funnel indicates the expected
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range of effect sizes given the standard error, while points outside the funnel indicate
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potential outliers or publication bias. Studies plotted inside the funnel are within the expected
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range of variation based on standard error, while those outside the funnel may indicate
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outliers or potential publication bias.
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Discussion and Future directions
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
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In order to gain a comprehensive understanding of the organic halo effect across different
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settings, our meta-analysis included both laboratory and real-world studies. Studies from four
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of the analyzed articles were conducted in controlled laboratory environments (Demartini et
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al., 2018; Kiss et al., 2015; McCrickerd et al., 2019; Schuldt & Schwarz, 2010), three were
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conducted online (Amos et al., 2019; Besson et al., 2019; Prada et al., 2016), two took place
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in real-world settings, such as a mall (Lee et al., 2013) and a university campus (Sörqvist et
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al., 2015), while one article employed both online and laboratory designs (Prada et al., 2017).
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The combination of experimental, online, and naturalistic settings allows for the examination
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of the robustness and applicability of the organic halo effect in various contexts. This broader
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perspective on the translation of these findings into real-world consumer behaviors is crucial
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for advancing knowledge in this field.
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Reliability of the Organic Halo effect
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The results of this meta-analysis provide robust evidence for the existence of the organic halo
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effect, whereby the presence of an organic label influences calorie estimates. This effect
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highlights the important role of cognitive biases in shaping consumer perceptions of organic
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foods. The findings underscore the importance of considering the impact of labeling on
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dietary decisions and public health interventions aimed at promoting accurate calorie
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awareness. According to Gignac & Szodorai (2016), the magnitude of this effect is strong (r =
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.40). The confidence intervals observed for the individual studies and for their aggregate
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effect are narrow, reflecting low uncertainty around these effects. Furthermore, most of the
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studies included in the meta-analysis also report small confidence intervals. This consistency
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increases confidence in the reported effect sizes of the individual studies. These narrow
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intervals suggest accurate estimates of effect sizes within each study, which strengthens the
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overall credibility of the organic halo effect. Specifically, the results suggest that the presence
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of an organic claim or ingredient may influence consumers' perceptions of the calories and
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overall healthiness of a product, potentially leading them to consume more than they would of
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a similar product without the claim.
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This first meta-analysis contributes to the existing body of knowledge by providing an initial
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state of the art on the reliability and magnitude of the organic halo effect on calorie
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estimation, particularly regarding the consistent impact of organic labeling on consumers’
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perception of calorie content. This finding underscores the influence of the organic halo effect
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on dietary choices and potential overconsumption. Our meta-analysis underscores the need for
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
further research on potential moderators, as we observed significant heterogeneity. It suggests
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that unexamined factors may influence the relationship between organic labeling and calorie
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estimation. Thus, our meta-analysis underscores the need for further research on potential
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moderators. The variability in the organic halo effect likely depends on contextual and
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methodological factors, including study settings (e.g., naturalistic versus laboratory
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conditions), participant characteristics (e.g., environmental attitudes), and the types of food
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characteristics (e.g., calorie content) examined. The limited number of studies included in this
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meta-analysis, combined with the non-systematic examination of potential moderators,
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highlights the importance of expanding research on this phenomenon. Establishing a
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consistent framework for investigating moderators is crucial to better understanding the
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conditions under which the organic halo effect emerges and its strength across different
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contexts. One key moderator that warrants further investigation is the study setting. Prior
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research suggests that eating behaviors, such as the portion size effect, differ significantly
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between laboratory and real-world contexts (Gough et al., 2021). Similarly, the organic halo
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effect may be more pronounced in naturalistic environments that reflect real-world purchasing
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or consumption behaviors. While our analysis did not include a formal moderation analysis
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due to inconsistent reporting across studies, future research should systematically explore the
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role of study setting to clarify its influence on consumer judgments of organically labeled
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foods. Such investigations would not only address a critical gap but also enhance the
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understanding of contextual factors shaping the organic halo effect.
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Without addressing this issue, conclusions about the consistency of the organic halo effect
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across contexts should be interpreted with caution, acknowledging the need for further
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research. Examining whether naturalistic or laboratory settings amplify or diminish the effect
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would provide a more nuanced perspective, contributing to a broader understanding of the
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variables that shape consumer perceptions of organic products.
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By identifying these gaps, this study lays a foundation for further research into the cognitive
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and environmental factors that drive the organic halo effect, providing clear guidance for
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future studies and practical applications in consumer behavior and health decision-making.
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However, a limitation of the literature on the organic halo effect is the potential for
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publication bias, as indicated by the asymmetry in the funnel plot. This provides a more
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nuanced interpretation of our conclusions, as it suggests that studies with non-significant
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findings may be underrepresented in the literature. Further research is needed to develop a
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clearer and more comprehensive understanding of this phenomenon.
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
Based on our findings, several areas require further investigation. Future works should
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investigate how the organic label influences calorie estimates across product types and
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contexts, and how consumers' perceptions of healthiness and sustainability interact to shape
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their judgments. Additionally, more studies are required on individual differences in
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environmental attitudes, health awareness, and how frequently people read nutritional labels.
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These insights will help clarify how the organic halo effect varies across consumer groups and
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product types. Moreover, future studies should employ a combination of laboratory and real-
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world settings to assess the impact of the organic halo effect on actual consumer behaviors,
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including purchasing decisions and consumption patterns.
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Perspectives on the product properties
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Consistent with previous findings by Lee et al. (2018), the effects of the organic label are
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largely observed when the labeled product is a "vice" food (unhealthy due to its high content
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of calories, fats, sugars, or salts, see Lunardo et al., 2022). McKrickerd et al. (2019) observed
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that instant noodles labeled as 'organic' were estimated to contain significantly fewer calories
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than control noodles, whereas the same effect was not observed for soy milk. The weakest
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effect of the organic label was found in the study by Sörqvist et al. (2015)c for grapes.
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Conversely, the strongest effect of the organic label on calorie estimates was noted in the
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second study by Prada et al. (2016)c, where unhealthy organic food (i.e., lasagna) was
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perceived as having fewer calories than its conventional counterpart. Thus, the type of food
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seems to be a strong moderator of misperception, which should be explored in future research.
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If unhealthy items are more consistently undervalued in terms of calorie content, the impact
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on overall health could be more significant. The type of food or its perceived 'healthiness'
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may act as a moderator of the organic halo effect, as consumer perceptions are often
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influenced by the specific characteristics of a product. For example, organic labels may have a
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stronger effect on indulgent or processed foods than on those already associated with health
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(e.g., fruits and vegetables). However, this meta-analysis did not include a formal
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examination of these moderators due to inconsistent reporting across studies. Many studies
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did not provide sufficient detail about the type of food studied or participants' prior
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perceptions of healthiness, which limited our ability to conduct a robust moderation analysis.
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Future research should prioritize the collection of detailed and consistent data on food types,
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perceived healthiness, and other product attributes to facilitate a deeper examination of these
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potential moderators. Such efforts would improve our understanding of how and when the
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organic halo effect manifests across contexts.
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
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Individual differences moderating the organic halo effect
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Based on the results of this meta-analytic approach, future research could focus on the role of
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environmental attitudes and behaviors, as well as the frequency of reading nutritional
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information. These factors were the only moderators of calorie estimation observed in the
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different studies selected in this work (Lee et al., 2013; Schuldt & Schwarz, 2010). With
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contrasting results, environmental attitudes tested in three studies (Amos et al., 2019; Schuldt
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& Schwarz, 2010; Sörqvist et al., 2015) increased the organic halo effect on individuals'
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caloric estimation only in Schuldt & Schwarz (2010). This effect seems worth investigating to
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verify its stability, as pro-environmental values tend to increase in the population (especially
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among young people) as a result of the climate emergency (Wallis & Loy, 2021). In terms of
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pro-environmental behavior, a contrary finding is highlighted by Lee et al. (2013). A weaker
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halo effect on calorie estimation is observed among individuals who more frequently engage
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in pro-environmental activities, when compared to those who do not, but only for chips.
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When it comes to reading nutritional information, regularly doing so reduces the effect of the
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organic halo on calorie estimation (Lee et al., 2013). This finding suggests that the halo effect
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is likely due to a lack of information, which encourages impression formation based on
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heuristics.
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This raises broader questions about how individuals process information to arrive at a caloric
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assessment. Previous research has already highlighted the difficulty individuals face in
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accurately estimating the caloric content of a dish, even when precise caloric information is
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provided (e.g., Gustafson & Zeballos, 2019). This underscores the ambiguity surrounding
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what a calorie represents for most individuals. To reduce this caloric ambiguity, individuals
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may rely on heuristic cues, such as the organic label, to inform their judgments. This idea is
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further supported by the work of Perkovic et al. (2018), who demonstrated that individuals
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learn to perceive organic foods as healthier through implicit statistical learning grounded in
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empirical patterns—specifically, that products from healthful food categories are more likely
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to be organic. They then apply this acquired knowledge when making dietary decisions. In
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that case, the label would serve as a cue to disambiguate the situation. Otherwise, the multiple
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sources of caloric information available on food may be weighted differently by individuals.
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Consequently, an organic label might be given greater consideration than a nutritional facts
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panel when forming caloric estimates (see Gawronski & Corneille, 2024 for the same
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reasoning on attitudes).
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New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
Additionally, personality traits are associated with positive attitudes toward organic food,
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suggesting that openness to experience may be linked to a greater influence from organic
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labels (Sogari et al., 2019). Moreover, the extent of objective knowledge about food and
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calories, such as that possessed by nutritionists compared to the general population, may
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affect caloric estimates of organic foods (Ellison et al., 2016). An examination of the
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literature from social psychology and consumer behavior may offer novel perspectives on
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potential moderators, thereby enhancing the understanding of the organic halo effect, as
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proposed by Cialdini (2001) and Chandon and Wansink (2007). To better understand the
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implications of the organic halo effect based on individual interactions, further exploration is
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needed into the role of peer influence on food behaviors involving organic labels. Research
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indicates that peers exert considerable influence on food preferences and dietary behaviors,
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particularly among children and adolescents, as evidenced by Birch's findings (1999) and
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subsequent studies by Salvy and colleagues (2011). This influence could potentially amplify
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the organic halo effect if peers endorse or consume "healthy" foods. Cialdini (2001) posits
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that such endorsement may reinforce the perceived healthiness of these foods. The interaction
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between the organic halo and peer influence is complex and moderated by factors such as
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self-esteem and social conformity (Chandon & Wansink, 2007). Investigating this interplay
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can reveal underlying mechanisms and inform interventions to mitigate misleading health
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claims.
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Beyond these attitudinal and behavioral differences, more macro-level differences such as
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cultural or socioeconomic status differences could have an impact. Cultural factors
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significantly impact food perception, with the halo effect being stronger in cultures that highly
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value organic food (Prada et al., 2019). Another potential moderator is socioeconomic status
415
(SES). Individuals with higher SES may perceive organic foods differently, influencing their
416
susceptibility to the halo effect (Willer et al., 2020).
417
418
Future directions on environmental influence and marketing strategies
419
Despite the growing body of literature on the organic halo effect, there is still much to be
420
explored in terms of environmental and marketing factors that may influence this
421
phenomenon. In addition, it would be valuable to examine how the context in which products
422
are consumed may moderate the effect of the organic halo effect on labeling or consumption
423
behavior. One promising avenue of research is to investigate the potential impact of
424
contextual cues and environmental factors on the organic halo effect. For example, studies
425
could examine whether the presence of other healthy options on a menu or in a store might
426
New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
influence the impact of organic halo labeling on consumption behavior. Especially
427
considering that the majority of published articles in this meta-analysis focus on unhealthy
428
foods (60%). Several studies have also found that consumers are more likely to perceive a
429
product as healthier when it is displayed in a health food store compared to a convenience
430
store (Vermeer & Sevincer, 2019). Similarly, the presence of health-related imagery or
431
language on packaging may contribute to the organic halo effect (Bialkova & Grunert, 2014).
432
Therefore, future research could examine how contextual factors, such as the retail
433
environment or packaging design, influence consumers' perceptions of the healthiness of
434
products, which could have important implications for public policy and industry practices
435
related to food labeling.
436
437
Furthermore, given the prevalence of health claims on food packaging and in advertising, it is
438
important to understand how marketing strategies may contribute to the organic halo effect.
439
For example, the use of health claims and symbols, such as the "heart healthy" symbol, may
440
create an impression of overall healthiness, leading consumers to underestimate the calorie or
441
fat content of the product (Wansink & Chandon, 2006). It is also possible that certain
442
marketing techniques, such as product positioning or endorsement by a celebrity or athlete,
443
may contribute to the organic halo effect (Cohen & Babey, 2012). Therefore, future research
444
should examine the interaction between organic labels and marketing strategies, as well as the
445
potential moderating role of individual differences in susceptibility to marketing tactics.
446
447
Overall, more research is needed to better understand the mechanisms underlying the organic
448
halo effect and the potential impact of environmental and marketing factors on this
449
phenomenon. By gaining a deeper understanding of these processes, it may be possible to
450
develop interventions to mitigate the organic halo effect and promote healthier food choices.
451
452
Does the Organic Halo effect translate into real behaviors?
453
Another direction for research is to promote the use of measures that accurately reflect actual
454
behavior. The organic halo effect could have an impact at different levels. At the purchasing
455
level, we could expect that organic products are more likely to be chosen than their
456
conventional counterparts and more likely to be included in unplanned purchases. At the
457
consumption level, we can hypothesize that people tend to eat organic food more often
458
compared to non-organic food. Future research should aim to use more objective measures of
459
consumption, such as actual purchases or observed consumption in laboratory or field
460
New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
settings. One possible approach to measuring actual consumption behavior is to conduct
461
studies in real-world settings, such as physical and online supermarkets or restaurants. For
462
example, studies could focus on comparing the purchasing behavior of people exposed to
463
products with an organic label to those who are not and examine whether the organic label
464
leads to increased purchases of less healthy options.
465
Previous studies on the Nutri-Score label, a front-of-package label that informs consumers
466
about the overall healthfulness of a product, have demonstrated in both laboratory and field
467
settings that it can effectively modify consumer behavior (Dubois et al., 2020; Egnell et al.,
468
2021). These results suggest that similar methodologies could be applied to test the influence
469
of the organic label on real behaviors. Moreover, the use of cutting-edge technologies, such as
470
virtual reality, to simulate diverse environments could provide further insights into the
471
influence of these labels on consumer behavior
472
473
Applied Recommendations for Marketing and Public Policies
474
This meta-analysis enhances the theoretical understanding of cognitive biases in food labeling
475
and consumer behavior, highlighting the need for further exploration of the underlying
476
cognitive processes and potential moderators of this effect. The results have important
477
implications for marketers and food producers. The organic halo effect can lead to the
478
underestimation of the calorie content in products certified as organic, potentially misleading
479
consumers into thinking these products contain fewer calories than they actually do. It is
480
therefore crucial that businesses develop transparent and ethical marketing strategies.
481
Marketers must consider the ethical implications of using organic labels and ensure that
482
health claims are not misleading, helping to avoid contributing to unhealthy consumption
483
behaviors. From a public policy perspective, it is evident that there is a pressing need for
484
stricter food labeling regulations. Current organic labeling regulations, such as the USDA
485
Organic label in the U.S. and the EU Organic logo, focus on production methods such as
486
sustainable agriculture and the absence of synthetic pesticides. However, these standards do
487
not address common consumer misconceptions about the healthfulness or caloric content of
488
organic products. To mitigate such misconceptions, we propose the systematic association of
489
the organic label with the Nutri-Score to mitigate the organic halo effect, ensuring that
490
consumers receive a more balanced and accurate evaluation of a product's nutritional quality.
491
To ensure broader applicability, we recommend pairing the organic label with a standardized
492
nutritional grading system, such as a traffic light system, star ratings, or other regionally
493
appropriate indicators, to provide consumers with balanced information on both nutritional
494
New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
quality and sustainability attributes. Also, we recommend future research to investigate
495
whether disclaimers explicitly clarifying that organic certification pertains to farming
496
practices rather than nutritional properties can effectively mitigate the organic halo effect. In
497
addition, stricter enforcement and greater transparency in the certification process, such as
498
random audits and public databases of certified producers, could increase trust and
499
understanding of the organic labeling system. Such regulations will help prevent consumers
500
from being misled about the health benefits of organic products. Public health campaigns
501
should aim to educate consumers about the organic halo effect, thereby promoting more
502
informed and healthier food choices.
503
504
Finally, we also recommend that legislators systematically implement Nutri-Score. Nutri-
505
Score is a front-of-pack nutrition label featuring a graded color-coding system. It is designed
506
to clearly and simply convey the overall nutritional value of foods, helping consumers make
507
healthier purchasing decisions and motivating manufacturers to enhance the nutritional
508
quality of their products. The label uses a five-color scale (ranging from dark green to dark
509
orange) with letters from A to E to ensure it is easily accessible and understandable for
510
consumers. Nutri-Score has demonstrated beneficial effects on both the nutritional quality of
511
shopping baskets and the quantity of low-nutritional-quality foods consumed (see Hercberg et
512
al., 2022 for a review). This system could help consumers better understand that the organic
513
label does not impact nutritional value or the total caloric content of foods. By addressing
514
these issues, policymakers can help mitigate the risk of overconsumption and its associated
515
health problems, ultimately contributing to better public health outcomes.
516
517
Limitations
518
Notwithstanding the promising findings, there are some limitations to this metanalysis that
519
should be acknowledged. First, although we included studies from different countries and
520
settings, most studies were conducted in Western countries, which may limit the
521
generalizability of our findings to other cultures. Second, the potential influence of study
522
settings on effect sizes is an important consideration in interpreting the results of this meta-
523
analysis. Previous research, such as that by Gough et al. (2021), has shown that eating
524
behavior effects, such as the influence of portion size on food intake, can differ significantly
525
between controlled laboratory conditions and real-world settings. This suggests that
526
naturalistic settings may provide a stronger or more ecologically valid context for studying
527
the organic halo effect. While our analysis did not account for study setting as a moderator
528
New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
due to limited and inconsistent reporting, future studies should explicitly examine how these
529
contextual factors influence calorie estimation and related judgments.
530
Third, we were only able to include studies that measured organic halo effects using self-
531
report measures of food intake, which may not fully capture the complexity of organic halo
532
effects on food choices and eating behaviors. Future research should include more objective
533
measures of food choice and eating behavior, such as behavioral or physiological measures.
534
For example, stress or physiological arousal may affect heart rate variability and blood
535
pressure, which in turn may affect food choices. Other measures, such as pupil size, may
536
reflect arousal and interest in food. Individual metabolic responses, such as blood glucose
537
levels, can also influence food choices. People may crave certain foods when their blood
538
glucose levels are low (Page et al., 2011).
539
As mentioned above, another limitation of this meta-analysis is that relatively few studies
540
measured potential moderating processes. This makes it difficult to draw definitive
541
conclusions about the mechanisms underlying the halo effect in the context of health claims.
542
Furthermore, the studies included in this meta-analysis have largely focused on food products,
543
leaving open the question of whether the halo effect operates in a similar way in other areas,
544
such as dietary supplements or beauty supplements, where health claims are also common
545
(Kapoor et al., 2022).
546
Also, the current meta-analysis focused primarily on studies using terms such as "calorie" and
547
"kcal" which are common in the food labeling and calorie estimation literature. However, this
548
search strategy may have inadvertently excluded research from regions or disciplines where
549
alternative terms such as “energy” or ”kilojoule” are used to quantify the energy content of
550
foods. For example, studies conducted in countries such as Australia and New Zealand, where
551
”kilojoule” is a standard metric, may not have been captured in this analysis.
552
Finally, we recommend that future research not only investigates the mechanisms underlying
553
the organic halo effect but also expands the range of studies to ensure that the reported effects
554
are robust and free from potential publication bias.
555
556
Conclusion
557
Overall, the results of this meta-analysis confirm the existence and importance of the organic
558
halo effect in food evaluation.These findings will serve as a foundation for future research and
559
inform the design and interpretation of subsequent studies related to the halo effect.
560
Moreover, they will shed light on its relevance and implications for both individuals and
561
broader public health initiatives. More specifically, the perspectives offered by our findings
562
New Challenges and Perspectives on the Organic Halo Effect on Calories Estimation
highlight the need for a comprehensive understanding of diet and health, emphasizing the
563
significance of considering various cognitive, environmental, and social factors that influence
564
food choices. This meta-analytic review provides important insights into the specific factors
565
contributing to the organic halo effect, including the influence of health claims and
566
ingredients. It additionally suggests several research avenues aimed at better understanding its
567
functioning. Finally, It is also recommended that food manufacturers and marketers consider
568
the potential impact of health claims and other extrinsic cues on how consumers perceive their
569
products. This includes being transparent about the true health benefits of a product and
570
avoiding the use of misleading or inaccurate health claims.
571
572
Declarations
573
574
Competing interests
575
The authors declare that the research was conducted in the absence of any commercial or
576
financial relationships that could be construed as a potential conflict of interest.
577
578
Availability of data and materials
579
All the data and materials in this article are available on the OSF platform:
580
https://osf.io/znxpu
581
582
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