Perceived Effectiveness of Added Sugar Labels
Study Details
Study Description
Brief Summary
This study aims to develop a restaurant menu label to indicate foods and beverage items on restaurant menus that contain high amounts of added sugars and to test its perceived effectiveness.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
Objectives and hypotheses:
The goal of this study is to examine how added sugar restaurant menu labels influence U.S. adults' perceptions and reactions. Predictions:
In a between-subjects experiment with 3 arms (control label, icon-only added sugars label, and icon plus text added sugars label):
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Added sugar labels will be perceived as more effective than the control label.
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The text plus icon label will be perceived as more effective than the icon-only label.
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A larger proportion of participants who see the added sugar labels will report learning something new than those who see the control label.
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Added sugar labels will lead participants to more accurately identify restaurant menu items high in added sugars compared to the control label, and the text plus icon label will outperform the icon-only label on this outcome.
Additionally, using a within-subjects design:
The study will examine which label (control, icon, text plus icon) most discourages wanting to consume menu items high in added sugars.
Analyses will compare various icon and text options for the added sugars label to determine which icon and which text variations are perceived as most discouraging for wanting to consume items high in added sugars. The is no hypothesis about which will be perceived as more discouraging.
Planned analyses:
For predictions 1-2: linear regression model (OLS) regressing PME on indicator variables for experimental condition. The margins command in STATA will be used to conduct pairwise comparisons between each condition (i.e., icon-only vs. icon plus text label). Also, PME will be regressed on an indicator variable combining the added sugar label groups.
For predictions 3-4, Poisson regression with robust standard errors will be used to estimate relative probability, regressing each dichotomous outcome on indicator variables for experimental condition. The margins command in STATA will be used to conduct pairwise comparisons between each condition. The outcomes will be regressed on an indicator variable combining the added sugar label groups. If the Poisson regressions do not converge, logistic regression will be used.
For the within-subjects comparisons, mixed effects linear models will be used to assess the relationship between condition and rating of label discouragement for consuming items high in added sugars.
A critical alpha 0.05 will be used, and statistical tests will be two-tailed. Because this is an initial, exploratory study to help identify the best performing label to use in a larger trial, alpha level will not be adjusted to control for multiple comparisons.
If there is evidence of deviations from modeling assumptions required for the parametric tests above, non-parametric sensitivity analyses will be conducted.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Control label Participant will see a QR code and footnote saying, "Scan the QR code for more menu information." The label will be applied to all menu items displayed. |
Other: Menu label
Participants will be shown a sample of items from a restaurant menu, displayed with labels
|
| Experimental: Icon plus text added sugars label Participant will see a label containing an icon plus text label with an explanatory footnote. The label will be applied to items high in added sugars (exceeding half the daily value). Participants will randomly view one of 18 variations of icons and text in this arm. |
Other: Menu label
Participants will be shown a sample of items from a restaurant menu, displayed with labels
|
| Experimental: Icon only added sugars label Participant will see a label containing an icon only with an explanatory footnote. The label will be applied to items high in added sugars (exceeding half the daily value). Participants will randomly view one of 6 variations of icons in this arm. |
Other: Menu label
Participants will be shown a sample of items from a restaurant menu, displayed with labels
|
Outcome Measures
Primary Outcome Measures
- Perceived message effectiveness (PME) [Up to approximately 5 minutes]
Measured using 3 items adapted from Baig et al. (2018): scale 1-5, "This label makes me concerned about the health effects of consuming menu items high in added sugars", "This label makes consuming menu items high in added sugars seem unpleasant", "This label discourages me from wanting to consume menu items high in added sugars." This outcome is for the between-subjects experiment.
- Perception of how discouraging the label is for wanting to consume items high in added sugars [Up to approximately 7 minutes]
Based on a single item adapted from Baig et al. (2018): "This label discourages me from wanting to consume menu items high in added sugar" (scale 1-5). This outcome is the within-subjects objectives.
- Perception of knowledge gain [Up to approximately 1 minute]
Dichotomous response (yes/no) to the question, "Did you learn something new from this label?" This outcome is for the between-subjects experiment.
- Correct identification of items high in added sugars [Up to approximately 2 minutes]
"Now please look at the menu items below, and select all the ones you think have more than half the daily value for added sugars" with 8 possible responses. A dichotomous outcome variable based on the distribution of correct answers in the sample will be created. This outcome is for the between-subjects experiment.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Equal or greater than 18 years of age
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Less than 100 years of age
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English-speaking
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U.S. residents
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Had to have purchased food from a restaurant at least once per month prior to the COVID-19 pandemic
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Participants will reflect the U.S. Census Bureau's 2018 American Community Survey 5-year estimates for gender, race/ethnicity, educational attainment, and age
Exclusion criteria:
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Failing the attention check question
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Completing the survey in less than 30% of the median completion time
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Straightlining
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Providing nonsensical responses to open-ended questions
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | University of California, Davis | Davis | California | United States | 95616 |
Sponsors and Collaborators
- University of California, Davis
- Center for Science in the Public Interest (CSPI)
Investigators
- Principal Investigator: Jennifer Falbe, ScD, MPH, University of California, Davis
Study Documents (Full-Text)
None provided.More Information
Publications
- 1641776