Evaluation of two social norms nudge interventions to promote healthier food choices in a Canadian grocery store

doi:10.21203/rs.3.rs-1602470/v1

Download PDF

Research Article

Evaluation of two social norms nudge interventions to promote healthier food choices in a Canadian grocery store

https://doi.org/10.21203/rs.3.rs-1602470/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

The objective of this study was to determine the impact of two nudge interventions on customers’ produce purchases at a rural Canadian grocery store. A pre- and post-intervention observational study design was used. Sales data were gathered before and after the staggered implementation of two nudge-based interventions to encourage produce purchases: grocery cart dividers to encourage shoppers to fill one-third of their cart with produce and grocery cart plaques with information about how many fruits and vegetables were typically purchased in the store. The proportion of total sales accounted for by produce was compared between baseline and implementation of the first intervention (Phase 1), between implementation of the first intervention and the addition of the second intervention (Phase 2), and between baseline and post-implementation of both interventions together. There was a 5% relative increase (0.5% absolute increase) in produce spending between baseline and post-implementation of both interventions (10.3% to 10.8%, p<0.001, 95% CI 0.2%, 0.7%). Intervention phase-specific produce spending showed no significant change in the percentage of produce spending from baseline to Phase 1 of the intervention, and an 8% relative increase (0.8% absolute increase) in the percentage of produce spending from Phase 1 to Phase 2 of the intervention (10.3% to 11.1%, p<0.001, 95% CI 0.5, 1.1%). Simple, low-cost nudge interventions were effective at increasing the proportion of total grocery spend on produce. This study also demonstrated that partnerships with local businesses can promote healthier food choices in rural communities in Canada.

Nudge interventions

behaviour change

healthy eating

food choice

Fruit and vegetable consumption in children is an important contributor to reaching and maintaining a healthy body weight. A diet rich in fruits and vegetables is also protective against many chronic diseases such as cardiovascular disease, type 2 diabetes, and cancer (Afshin et al., 2019). Canada’s Food Guide (CFG) encourages individuals of all ages to include plenty of fruits and vegetables in meals and snacks (four to eight servings a day for children and seven to ten servings a day for adults (age and sex dependent)) (Health Canada, 2022). Despite this recommendation, just 20.7% of the Canadian population ages one and older met or exceeded CFG recommendations for daily fruit and vegetable consumption (Krueger et al., 2017). Youth -specific research has reported adherence to these recommendations to be as low as one in ten Canadian children (Minaker & Hammond, 2016).

Healthy eating is an individual behaviour but there are many internal and external factors – e.g., biological, psychological, cultural, and social factors, as well as community and policy settings – that influence food choices (Lobstein et al., 2015). Effective health promotion and childhood obesity prevention efforts must extend beyond a single sector and involve the whole-of-community so children and families see consistent messaging and are supported in making healthy choices where they live, learn, and play (Singh et al., 2010).

Sustainable Childhood Obesity Prevention through Community Engagement (SCOPE) is a community-based participatory research project in the province of British Columbia (BC), Canada. SCOPE developed Live 5-2-1-0, a multi-sectoral, multi-component childhood obesity prevention initiative centered on the evidence-based 5-2-1-0 message (i.e., five or more portions of vegetables and fruits, < two hours of recreational screen time, at least one hour of physical activity, and zero sugary drinks per day) (Amed et al., 2015, 2016). Using a collective impact approach, SCOPE partners with communities across BC to engage a range of community stakeholders (e.g., in local government, health, education, business) to share the Live 5-2-1-0 message and create healthier environments for children and families (Amed et al., 2015, 2016).

Businesses are an integral part of a community and play an influential role in the health behaviour choices that are available, as well as the healthy messaging that is relayed to local residents. Grocery stores are one private sector setting where health promotion initiatives aimed at increasing fruit and vegetable intake can be mutually beneficial to both the patron (improving customers’ food choices) and the business (potential profitability of increased produce sales, a high margin product category) (Chapman et al., 2019; Payne et al., 2014). However, to date, grocery store interventions aimed at promoting healthy food choices through education and environmental changes have had mixed outcomes and have been mildly successful at best (Escaron et al., 2013; Hartmann-Boyce et al., 2018).

There is growing evidence of the effectiveness of interventions that utilize ‘nudges’ – a nudge aims to alter an individual’s behaviour in a predictable way without restricting one’s options when making decisions (Chapman et al., 2019; Hanks et al., 2012; Olstad et al., 2015; Payne et al., 2015; Thorndike et al., 2014; Van Kleef et al., 2012; Veling et al., 2013; Wansink et al., 2012). Nudge interventions are based on dual-process models of behaviour which posit that behaviours result from the interaction of both an unconscious, automatic mode of processing (System I), and a conscious, slow, rational mode of processing (System II) (Strack & Deutsch, 2004). Nudge interventions utilize heuristics to influence the automatic/System I mode of processing and decision-making. Grocery store nudge interventions may also leverage the social aspects of grocery shopping such as shoppers’ perceptions of what foods are common, normal or appropriate to purchase (Payne et al., 2014). Examples of nudges in this setting include highlighting items using focused lighting, mounting shelf labels that advertise promoted items, and improving accessibility of products through product placement (Chapman et al., 2019; Cheung et al., 2019; Marteau et al., 2012).

One nudge-based intervention that has demonstrated effectiveness in increasing fruit and vegetable purchases in supermarkets is the installation of partitions in grocery carts to designate a section for ‘fruits and vegetables’, thereby emphasizing social appropriateness of purchasing fresh produce (Huitink et al., 2020; Payne et al., 2014; Wansink et al., 2017). Payne et al. divided grocery carts with a wide yellow line and included signage that indicated where shoppers should place nutritive items and where they should place “everything else,” (Payne et al., 2014). Preliminary evidence of the efficacy of this ‘half-cart’ intervention was promising as it showed a doubling of produce purchases (Payne et al., 2014). A Canadian study by Wansink et al. that implemented a similar ‘half-cart’ intervention, showed a significant increase in produce spending from $11.61 to $17.54 (Wansink et al., 2017). Payne et al. (2015) also trialed grocery cart placards with facts about the number of produce items normally purchased at that particular store and reported a significant increase in produce spending by 16%, without an increase in shopper total budgets. Similarly, Huitink et al. (2020) showed that an inlay in grocery carts with messages about the vegetable purchases of other customers, and an allocated grocery cart partition for vegetables, resulted in a statistically significant increase in grams of vegetables purchased (900 grams to 1120 grams on intervention days).

Canada’s geography plays a role in access to healthy foods, especially for rural and remote communities where maintaining food businesses is a challenge (Levy, 1984). Nudge interventions may represent a mutually beneficial activity for grocery stores to support a community driven, collective approach to health promotion while increasing produce sales. However, grocery nudge interventions have not been explored extensively within the context of remote, locally owned grocery stores in Canada. This represents a significant gap in the literature as available evidence suggests rural residence may be a risk factor for having a poorer diet due to limited availability and higher prices for fresh produce (Dean & Sharkey, 2011; Holston et al., 2020). Additionally, the most recent data from Canada on the impact of grocery store nudges that could be identified dates from 2007 (Wansink et al., 2017). The objective of this study was to address this knowledge gap by using up-to-date data to determine the impact of two evidence-based nudge interventions on customers’ purchasing patterns and produce sales at a grocery store located within a rural Canadian community.

Setting & Participants

The setting was a rural Live 5-2-1-0 partner community located in the Kootenay region of BC that has a population of approximately 7,400 (in 2016). The median age of the population is 48 years and the average household size is 2.2 persons (BC Centre for Disease Control, 2016). The community has two grocery stores; an independent grocery and a store that is part of a national supermarket chain. Both stores were approached by a local member of the research team and invited to participate. The independent grocery store agreed while the chain store declined due to the challenges in accessing data required to measure outcomes.

Intervention

The nudge interventions were based upon those developed by Payne and colleagues to subtly guide grocery shoppers to purchase more fruit and vegetables (Coldman et al., 2014; Payne et al., 2015). The interventions were introduced in two phases:

In Phase 1 (February 2016 to January 2017) grocery cart dividers were installed to encourage shoppers to fill one third of their cart with produce. The dividers were made of a thin plastic strip that had text reading “Fruit and Vegetables” and colourful graphics, in addition to arrows pointing towards the front of the cart (Fig.1). These flat strips were fastened to the bottom of the carts with zap straps at the junction of the middle and front thirds of the cart, creating a visual division in the cart. Dividers remained installed in all grocery carts for the duration of the study.
In Phase 2 (February 2017 to June 2018) plaques were installed inside all grocery carts with an informational message about how many fruits and vegetables were typically purchased in the store: “In this store the average shopper buys at least 4 fruits or vegetables” (Fig. 2). This information was based upon data collected in-store during the baseline time period (87 weeks).

Study Design & Data Collection

A pre- and post-intervention observational study design was used. The primary outcome was the proportion of total sales that was on produce post-intervention relative to the same measure at baseline. The categories representing produce spending, grocery spending, and the proportion of total sales were obtained from grocery store sales reports for 213 weeks during the baseline and intervention periods. The baseline period accounted for the first 87 weeks of data collection (June 2014 to January 2016), and the intervention periods spanned the subsequent 126 weeks (Phase 1, marked by the installation of the part-cart intervention, spanned 52 weeks from February 2016 to January 2017, and Phase 2, marked by the installation of the cart plaques, spanned 74 weeks from February 2017 to June 2018) (Fig. 3). Weekly sales data were averaged and grouped into baseline and intervention periods (including two phases of intervention). The percentage of produce spending to total spending was analyzed to determine the change from baseline to the intervention period. The differing durations of all three phases was due to challenges in coordinating intervention implementation schedules with the store. Grocery sales data were also analyzed every three months to ensure sales were not adversely affected by the implementation of the interventions during the study period.

Data analysis

Ethics approval for the study was obtained from the University of British Columbia Children’s and Women’s Health Centre of British Columbia Research Ethics Board (H15-01725). The proportion of produce sales compared to total sales was calculated each week at baseline from June 2014 to January 2016, and then each week during Phases 1 and 2, post-intervention. A two-sample t test was performed to assess whether there was a significant difference in the proportion of weekly produce to total sales at baseline compared to post-intervention. To assess whether there were any notable trends in seasonal produce purchasing, and to ensure that observed trends were consistent across baseline and intervention phases, monthly averages of the percentage of produce spending to total spending was calculated. Given the variable duration of the baseline and intervention periods, monthly averages were calculated and graphed for visual comparison across baseline and intervention.

A sensitivity analysis of matched months across all three time periods was also carried out to assess any effects of the variable length of each time period. The months of February to December in 2015 (baseline), 2016 (Phase 1), and 2017 (Phase 2) were compared using t tests.

There was a 5% relative increase (0.5% absolute increase) in the percentage of produce spending to total spending when comparing baseline to the time period post-implementation of both interventions (10.3–10.8%, 95% CI 0.2, 0.7% absolute increase, p < 0.001). Intervention phase-specific produce spending showed no significant change in the percentage of produce spending from baseline to Phase 1 of the intervention, and an 8% relative increase (0.8% absolute increase) in the percentage of produce spending from Phase 1 to Phase 2 of the intervention (10.3–11.1%, 95% CI 0.5, 1.1% absolute increase, p < 0.001) (Fig. 4).

Average monthly percent of produce sales to total sales were calculated and graphed for each month in the baseline and intervention periods. Seasonal produce purchasing patterns were observed across the baseline and intervention periods, whereby produce spending increased over the spring and summer months and decreased in the autumn and winter months (Fig. 5). Thus, trends in produce spending displayed during the intervention period were consistent with seasonal produce purchasing trends during the baseline period. In addition, Phase 2 saw a sustained monthly increase in the proportion of total sales in the produce category with the introduction of the grocery nudge interventions. Overall, total sales did not differ across the three time periods (baseline, phase 1 and phase 2).

The sensitivity analysis using matched months from all three phases showed similar results to the main analysis. There was a significant increase in produce sales between Phase 1 and Phase 2 (10.3–10.9%, 95% CI 0.31 to 1.05, p < 0.001). However, there was no significant increase in produce sales from baseline when Phase 1 and Phase 2 data for the specified months were combined.

Our study sought to evaluate the effectiveness of nudge interventions in a rural Canadian grocery store to encourage consumers to purchase more fruits and vegetables. Our findings show that installing a grocery cart divider to create a designated space for produce in combination with a cart plaque with an informational message about typical fruit and vegetable purchasing practices in the store was associated with a statistically significant increase in the proportion of total sales that were for produce. Given the increase in produce sales with the addition of the plaque, it is possible that the impact on produce sales was primarily due to the plaque rather than the cart divider. Our results add to the existing evidence that nudges can be an effective strategy for increasing the purchase of fruits and vegetables in grocery stores.

Our results are similar to those of previously published studies that were used to form the basis of this study (Payne et al., 2014, 2015; Wansink et al., 2017). While their outcome measures varied, these studies suggested that some combination of nudge interventions including grocery cart dividers and informational social norm messages pertaining to fruit and vegetable purchasing patterns had the potential to increase produce sales (Huitink et al., 2020; Payne et al., 2015; Wansink et al., 2017). Additionally, our finding of a potential benefit to implementing several grocery store nudge interventions at once is consistent with a previous study by Chapman et al. that suggested multiple concurrent nudges may be needed to influence purchasing behaviour (Chapman et al., 2019). However, further research to examine the effect of the informational plaque alone would be needed to clarify its impact on produce sales relative to its impact when combined with the cart divider.

Installing the grocery cart divider on its own was associated with no significant increase in produce sales compared to baseline and there were intermittent periods during Phase 1 when the proportion of produce sales to total other sales dropped below baseline levels of this same measure (Fig. 5). This differs from findings reported by Wansink and colleagues that grocery cart dividers resulted in increased spending on produce (Wansink et al., 2017). However, that study also involved participants being handed flyers promoting fruit and vegetable consumption and direct interaction with researchers during their visit to the store. It is therefore possible that social desirability factors could have increased produce spending in Wansink and colleagues’ study. The results of our study suggest that in a real-world setting, a grocery cart divider on its own may not be sufficient to nudge shoppers to buy more produce. However, the presence of both nudges in Phase 2 demonstrated a consistent and sustained increase in produce sales relative to total sales over the course of the study. As mentioned, future research could build on our work by examining the impact of the informational plaque alone to determine the precise effect of each intervention.

The present study has several strengths including a relatively low study cost, simple and feasible ‘real-world’ implementation, and secondary use of existing objective sales data that minimizes workload on grocery store owners. Additionally, each nudge was assessed at different time points but over a long time period that included all calendar months, allowing us to understand the impact of a single partitioned cart nudge versus a combination of the partitioned cart and the placard nudges. During the study time period, the Consumer Price Index (CPI) for fruit and vegetables and food in general was examined to identify any possible impact of changes in this on study results. Between June 2014 and June 2018, the CPI increased by 11.6 for fresh fruit and vegetables and by 10 for food in general (Statistics Canada, n.d.). The similarity in these increases make it unlikely that changing food prices impacted our results.

This study has several limitations. The pre- and post-intervention observational study design limits the ability to make causal inferences about the findings. It is possible that there were other events occurring simultaneously that led to the observed effects on produce sales. Furthermore, data were collected sequentially from baseline to intervention phases. Thus, there are no time-matched grocery store sales data for comparison and it is possible that the observed results were a result of general changes in produce sales over time. However, as mentioned previously, the baseline and intervention phases spanned several seasons thus mitigating the likelihood of the observed effects being a result of seasonal changes in purchasing behaviours. Another limitation to this study is the use of total produce sales with no data on individual customer-level purchasing to determine the primary outcome measure. Use of aggregate sales data makes it unclear whether customers purchased a greater number of fruits and vegetables, or whether they purchased more expensive fruits and vegetables. Thus, future studies should investigate the effect of grocery cart dividers and social norm message nudges in a rural, Canadian context using customer-level produce sales data (such as grams of produce sales per customer) and using a randomized control trial study design. Lastly, our study did not collect data on produce consumption and therefore cannot ascertain whether an increase in produce purchasing translated into healthier eating at an individual level.

Grocery stores are one example of a private sector setting that can have a positive role in creating a healthier environment for local residents. Our study demonstrates that nudge interventions can be a feasible, relatively low-cost strategy to promote fruit and vegetable purchases, without negatively impacting total sales in a locally owned food business. Given the importance of fruit and vegetable consumption in promoting health and preventing chronic disease, the implementation of grocery store nudge interventions has the potential to positively influence the health of communities. Future research is needed to better understand whether an increase in produce purchases translates to an increase in the consumption of fruits and vegetables.

Ethics approval and consent to participate

Ethics approval for the study was obtained from the University of British Columbia Children’s and Women’s Health Centre of British Columbia Research Ethics Board (H15-01725). All procedures were in accordance with the ethical standards of these Research Ethics Boards. As all data were aggregated and anonymized, there were no human participants directly involved in the study and therefor informed consent was not a requirement of this study. No individual human data or clinical data were gathered or used.

Consent for publication

Not applicable

Availability of data and materials

The data that support the findings of this study are available from the participating grocery store but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the participating grocery store. The owners of the grocery store gave permission for use of their commercially sensitive data for this study only.

Competing interests

The authors declare that they have no competing interests

Funding

The study described in this manuscript received no specific funding.

Authors' contributions

SS performed data collection, preliminary data analysis, and contributed to early drafts of the manuscript. MSM completed data analysis, prepared figures, and drafted the manuscript. SP contributed to study design and intervention planning and implementation, and provided feedback on drafts of the manuscript. KC contributed to intervention planning and implementation and provided feedback on drafts of the manuscript. KB performed data collection, preliminary data analysis, and contributed to early drafts of the manuscript

IH contributed to study design, intervention planning and implementation and data collection. SA provided guidance on study design and feedback to manuscript drafts. All authors contributed to and reviewed the final manuscript.

Acknowledgments

The authors would like to acknowledge the invaluable support of Vaughn Jarrett in the facilitation of this research project.

Afshin, A., Sur, P. J., Fay, K. A., Cornaby, L., Ferrara, G., Salama, J. S., Mullany, E. C., Abate, K. H., Abbafati, C., Abebe, Z., Afarideh, M., Aggarwal, A., Agrawal, S., Akinyemiju, T., Alahdab, F., Bacha, U., Bachman, V. F., Badali, H., Badawi, A., … Murray, C. J. L. (2019). Health effects of dietary risks in 195 countries, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 393(10184), 1958–1972. https://doi.org/10.1016/S0140-6736(19)30041-8
Amed, S., Naylor, P. J., Pinkney, S., Shea, S., Mâsse, L. C., Berg, S., Collet, J. P., & Wharf Higgins, J. (2015). Creating a collective impact on childhood obesity: Lessons from the SCOPE initiative. Canadian Journal of Public Health, 106(6), e426–e433. https://doi.org/10.17269/CJPH.106.5114
Amed, S., Shea, S., Pinkney, S., Higgins, J. W., & Naylor, P. J. (2016). Wayfinding the live 5-2-1-0 initiative—At the intersection between systems thinking and community-based childhood obesity prevention. International Journal of Environmental Research and Public Health, 13(6), 1–16. https://doi.org/10.3390/ijerph13060614
BC Centre for Disease Control. (2016). BC Community Health Data. http://communityhealth.phsa.ca/CHSAHealthProfiles/CHSAHealthReportDemographics/Kimberley
Chapman, L. E., Sadeghzadeh, C., Koutlas, M., Zimmer, C., & De Marco, M. (2019). Evaluation of three behavioural economics “nudges” on grocery and convenience store sales of promoted nutritious foods. Public Health Nutrition, 22(17), 3250–3260. https://doi.org/10.1017/S1368980019001794
Cheung, T. T. L., Gillebaart, M., Kroese, F. M., Marchiori, D., Fennis, B. M., & De Ridder, D. T. D. (2019). Cueing healthier alternatives for take-away: A field experiment on the effects of (disclosing) three nudges on food choices. BMC Public Health, 19(1), 1–10. https://doi.org/10.1186/s12889-019-7323-y
Coldman, A., Phillips, N., Wilson, C., Decker, K., Chiarelli, A. M., Brisson, J., Zhang, B., Payne, J., Doyle, G., & Ahmad, R. (2014). Pan-Canadian study of mammography screening and mortality from breast cancer. Journal of the National Cancer Institute, 106(11), dju261-. https://doi.org/10.1093/jnci/dju261
Dean, W. R., & Sharkey, J. R. (2011). Rural and Urban Differences in the Associations between Characteristics of the Community Food Environment and Fruit and Vegetable Intake. Journal of Nutrition Education and Behavior, 43(6), 426–433. https://doi.org/10.1016/j.jneb.2010.07.001
Escaron, A. L., Meinen, A. M., Nitzke, S. A., & Martinez-Donate, A. P. (2013). Supermarket and grocery store-based interventions to promote healthful food choices and eating practices: A systematic review. Preventing Chronic Disease, 10(4), 1–20. https://doi.org/10.5888/pcd10.120156
Hanks, A. S., Just, D. R., Smith, L. E., & Wansink, B. (2012). Healthy convenience: Nudging students toward healthier choices in the lunchroom. Journal of Public Health (United Kingdom), 34(3), 370–376. https://doi.org/10.1093/pubmed/fds003
Hartmann-Boyce, J., Bianchi, F., Piernas, C., Riches, S. P., Frie, K., Nourse, R., & Jebb, S. A. (2018). Grocery store interventions to change food purchasing behaviors: A systematic review of randomized controlled trials. American Journal of Clinical Nutrition, 107(6), 1004–1016. https://doi.org/10.1093/ajcn/nqy045
Health Canada. (2022). Canada’s Food Guide Health Canada, Government of Canada,. https://food-guide.canada.ca/en/
Holston, D., Stroope, J., Greene, M., & Houghtaling, B. (2020). Perceptions of the Food Environment and Access among Predominantly Black Low-Income Residents of Rural Louisiana Communities. International Journal of Environmental Research and Public Health, 17(15), 5340. https://doi.org/10.3390/ijerph17155340
Huitink, M., Poelman, M. P., van den Eynde, E., Seidell, J. C., & Dijkstra, S. C. (2020). Social norm nudges in shopping trolleys to promote vegetable purchases: A quasi-experimental study in a supermarket in a deprived urban area in the Netherlands. Appetite, 151(April), 104655. https://doi.org/10.1016/j.appet.2020.104655
Krueger, H., Koot, J., & Andres, E. (2017). The economic benefits of fruit and vegetable consumption in Canada. Canadian Journal of Public Health, 108(2), e152–e161. https://doi.org/10.17269/CJPH.108.5721
Levy, A. (1984). In Canada. In Adoption & Fostering (Vol. 8, Issue 1). https://doi.org/10.1177/030857598400800119
Lobstein, T., Jackson-Leach, R., Moodie, M. L., Hall, K. D., Gortmaker, S. L., Swinburn, B. A., James, W. P. T., Wang, Y., & McPherson, K. (2015). Child and adolescent obesity: Part of a bigger picture. The Lancet, 385(9986), 2510–2520. https://doi.org/10.1016/S0140-6736(14)61746-3
Marteau, T. M., Hollands, G. J., & Fletcher, P. C. (2012). Changing human behavior to prevent disease: The importance of targeting automatic processes. Science, 337(6101), 1492–1495. https://doi.org/10.1126/science.1226918
Minaker, L., & Hammond, D. (2016). Low Frequency of Fruit and Vegetable Consumption Among Canadian Youth: Findings From the 2012/2013 Youth Smoking Survey. Journal of School Health, 86(2), 135–142. https://doi.org/10.1111/josh.12359
Olstad, D. L., Vermeer, J., McCargar, L. J., Prowse, R. J. L., & Raine, K. D. (2015). Using traffic light labels to improve food selection in recreation and sport facility eating environments. Appetite, 91, 329–335. https://doi.org/10.1016/j.appet.2015.04.057
Payne, C. R., Niculescu, M., Just, D. R., & Kelly, M. P. (2014). Shopper marketing nutrition interventions. Physiology and Behavior, 136, 111–120. https://doi.org/10.1016/j.physbeh.2014.03.029
Payne, C. R., Niculescu, M., Just, D. R., & Kelly, M. P. (2015). Shopper marketing nutrition interventions: Social norms on grocery carts increase produce spending without increasing shopper budgets. Preventive Medicine Reports, 2, 287–291. https://doi.org/10.1016/j.pmedr.2015.04.007
Singh, G. K., Siahpush, M., & Kogan, M. D. (2010). Neighborhood socioeconomic conditions, built environments, and childhood obesity. Health Affairs, 29(3), 503–512. https://doi.org/10.1377/hlthaff.2009.0730
Statistics Canada. (n.d.). Table 18-10-0004-01 Consumer Price Index, monthly, not seasonally adjusted. https://doi.org/10.25318/1810000401-eng
Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8(3), 220–247. https://doi.org/10.1207/s15327957pspr0803_1
Thorndike, A. N., Riis, J., Sonnenberg, L. M., & Levy, D. E. (2014). Traffic-light labels and choice architecture: Promoting healthy food choices. American Journal of Preventive Medicine, 46(2), 143–149. https://doi.org/10.1016/j.amepre.2013.10.002
Van Kleef, E., Otten, K., & Van Trijp, H. C. M. (2012). Healthy snacks at the checkout counter: A lab and field study on the impact of shelf arrangement and assortment structure on consumer choices. BMC Public Health, 12(1), 1. https://doi.org/10.1186/1471-2458-12-1072
Veling, H., Aarts, H., & Stroebe, W. (2013). Using stop signals to reduce impulsive choices for palatable unhealthy foods. British Journal of Health Psychology, 18(2), 354–368. https://doi.org/10.1111/j.2044-8287.2012.02092.x
Wansink, B., Shimizu, M., & Camps, G. (2012). What would Batman eat?: Priming children to make healthier fast food choices. Pediatric Obesity, 7(2), 121–123. https://doi.org/10.1111/j.2047-6310.2011.00003.x
Wansink, B., Soman, D., & Herbst, K. C. (2017). Larger partitions lead to larger sales: Divided grocery carts alter purchase norms and increase sales. Journal of Business Research, 75, 202–209. https://doi.org/10.1016/j.jbusres.2016.06.023

No competing interests reported.

Download PDF

Editorial decision: Major revision
20 Jun, 2022
Reviews received at journal
29 May, 2022
Reviewers agreed at journal
19 May, 2022
Reviewers invited by journal
18 May, 2022
Editor assigned by journal
18 May, 2022
Editor invited by journal
06 May, 2022
Submission checks completed at journal
06 May, 2022
First submitted to journal
27 Apr, 2022

You are reading this latest preprint version

Evaluation of two social norms nudge interventions to promote healthier food choices in a Canadian grocery store

Status:

Version 1

Abstract

Figures

Introduction

Methods

Results

Discussion

Declarations

References

Additional Declarations

Status:

Version 1