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| ID | Type | Description | Link |
|---|---|---|---|
| R01DK114735 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Heart, Lung, and Blood Institute (NHLBI) | NIH |
| National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) | NIH |
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This project tests a scalable and sustainable approach to weight gain prevention in a population of employees by using the worksite environment to deliver personalized feedback about worksite food purchases, daily calorie goals, social norms for healthy eating, and financial incentives for healthy food purchases. In the future, similar strategies could be adopted by other worksites, institutions, and food retailers and could contribute to the long-term environmental and social changes needed to reverse the obesity epidemic in the United States and worldwide.
The overall objective of ancillary studies added on to this project is to examine the psychological traits, cognitive skills, and genes that may influence the impact of the behavioral intervention to promote healthy diet and weight among employees at a large hospital worksite.
Adults in the United States gain an average of 1-2 pounds a year. Interventions to prevent weight gain at the population level are needed to reverse the rising prevalence of obesity. Although individual-level interventions can result in large weight changes among small groups of individuals, achieving changes in the population will require long-term strategies that create healthier food environments, establish new social norms, and improve motivation and skills for healthy lifestyle behaviors. The worksite is ideal for interventions to address weight and lifestyle behaviors because a majority of adults are employed, and provisions in the Affordable Care Act encourage worksite wellness. Our research team at Massachusetts General Hospital (MGH) has demonstrated that behavioral economics strategies, including traffic-light labels, choice architecture, social norms, and financial incentives, improve employees' healthy food choices. The proposed project will address the critical next phase of this research to determine if a worksite intervention delivered through the food environment can prevent weight gain and reduce cardiovascular risk of employees. This project builds on the established traffic-light labeling system at MGH and tests an intervention that aims to increase nutrition knowledge, motivate change in lifestyle behaviors, and promote socially normative behavior for healthier lifestyles among employees. The intervention will be integrated into the flow of the work day, thus lowering burden to employees and the employer. Study Design: In a randomized controlled trial, 600 MGH employees will be assigned to: 1) an intervention arm with automated, personalized feedback about (a) worksite food purchases and calorie and physical activity goals (weekly emails) and (b) social norm feedback plus small financial incentives for healthy food purchases (monthly letters) or 2) a control arm (standardized monthly letters). Study outcomes will be assessed at 1 year (end of intervention) and 2 year follow-up. The primary outcome is change in weight at 1 year. Secondary outcomes are cardiovascular risk factors, worksite food purchases, and dietary intake (as measured by the Healthy Eating Index). A novel exploratory outcome will be healthy food purchases of co-workers who are socially connected to study subjects. Aim 1 is to determine if employees assigned to the intervention have less weight gain and lower cardiovascular risk factors than the control group at 1 year and 2-year follow-up. Aim 2 is to determine if employees assigned to the intervention group make healthier food choices than the control group at 1 year and 2-year follow-up. Exploratory Aim 3 is to determine if employees socially connected to the intervention group make healthier worksite food choices over 1 year than employees connected to the control group. Implications: This innovative strategy utilizing personalized feedback, social norms, and financial incentives will provide a scalable and sustainable model that could be adopted in other worksite, institutional, and retail settings to prevent obesity at the population level.
The overall objective of the ancillary studies added on to this project is to examine the psychological traits, cognitive skills, and genes that may influence the impact of a behaviorally-informed intervention on dietary choices, weight, and other objective health indicators. This research will expand on the randomized trial by examining psychological traits (impulsivity, self-control, social acceptance), cognitive skills (numeracy, health literacy), and genes (97 known BMI loci) that are associated with obesity and poor health and are specifically targeted by the intervention. We will use validated measures to assess traits and skills and well-established methods for genotyping and calculating genetic risk scores. Aim 1 will determine if psychological traits moderate the behavioral intervention effects on diet and weight. Aim 2 will determine if cognitive skills moderate the behavioral intervention effects on diet and weight. Aim 3 will determine if genetic risk for obesity moderates the intervention effect on weight. In secondary analyses, potential mediators of diet and weight outcomes, including dietary intent, self-efficacy, reward sensitivity, perceived norms, and perceived stress, will be assessed. Implications: Results of this research will l will inform the future design and implementation of more effective, tailored, and sustainable population approaches for obesity prevention.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Personalized feedback | Experimental | Emails and letters providing personalized nutrition feedback about food choices and health, social norms, and financial incentives for healthy food choices |
|
| Control | No Intervention | Monthly letters with general nutrition information |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Personalized nutrition feedback | Behavioral | Automated personalized nutrition feedback about cafeteria food purchases (weekly); social norms and small financial incentives to promote healthy purchases (monthly) |
| Measure | Description | Time Frame |
|---|---|---|
| Weight Change | Change in weight from baseline to 12 months | 12 months |
| Measure | Description | Time Frame |
|---|---|---|
| Weight Change | Change in weight from baseline to 24 months | 24 months |
| Change in Blood Pressure | Change from baseline in mean systolic and diastolic blood pressure (BP). |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Massachusetts General Hospital | Boston | Massachusetts | 02114 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37181927 | Derived | Dashti HS, Alimenti K, Levy DE, Hivert MF, McCurley JL, Saxena R, Thorndike AN. Chronotype Polygenic Score and the Timing and Quality of Workplace Cafeteria Purchases: Secondary Analysis of the ChooseWell 365 Randomized Controlled Trial. Curr Dev Nutr. 2023 Feb 18;7(3):100048. doi: 10.1016/j.cdnut.2023.100048. eCollection 2023 Mar. | |
| 36548448 | Derived | McCurley JL, Buckholtz JW, Roberto CA, Levy DE, Anderson EM, Chang Y, Thorndike AN. The association of impulsivity with effects of the ChooseWell 365 workplace nudge intervention on diet and weight. Transl Behav Med. 2023 May 13;13(5):281-288. doi: 10.1093/tbm/ibac103. |
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| ID | Title | Description |
|---|---|---|
| FG000 | Personalized Feedback | Emails and letters providing personalized nutrition feedback about food choices and health, social norms, and financial incentives for healthy food choices Personalized nutrition feedback: Automated personalized nutrition feedback about cafeteria food purchases (weekly); social norms and small financial incentives to promote healthy purchases (monthly) |
| FG001 | Control | Monthly letters with general nutrition information |
| Title | Milestones | Reasons Not Completed | |||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study- 12-month |
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| |||||||||||||||||||||
| Overall Study: 24-month Follow-up |
|
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| ID | Title | Description |
|---|---|---|
| BG000 | Personalized Feedback | Emails and letters providing personalized nutrition feedback about food choices and health, social norms, and financial incentives for healthy food choices Personalized nutrition feedback: Automated personalized nutrition feedback about cafeteria food purchases (weekly); social norms and small financial incentives to promote healthy purchases (monthly) |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Weight Change | Change in weight from baseline to 12 months | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | kg | 12 months |
|
24 months
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Personalized Feedback | Emails and letters providing personalized nutrition feedback about food choices and health, social norms, and financial incentives for healthy food choices Personalized nutrition feedback: Automated personalized nutrition feedback about cafeteria food purchases (weekly); social norms and small financial incentives to promote healthy purchases (monthly) |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Anne Thorndike, Prinicipal Investigator | Massachusetts General Hospital | 6177244608 | athorndike@mgh.harvard.edu |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Jun 17, 2019 | Aug 22, 2021 | Prot_SAP_000.pdf |
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| ID | Term |
|---|---|
| D001835 | Body Weight |
| ID | Term |
|---|---|
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| 12 and 24 months |
| Change in Total Cholesterol | Change from baseline in mean serum total cholesterol. | 12 and 24 months |
| Change in LDL Cholesterol | Change from baseline in mean serum LDL. | 12 and 24 months |
| Change in Triglycerides | Change in mean serum triglycerides. | 12 and 24 months |
| Change in HDL Cholesterol | Change in mean serum HDL. | 12 and 24 months |
| Change in Hemoglobin A1C | Change in mean serum hemoglobin A1c. | 12 and 24 months |
| Change in Green-labeled (Healthy) Food Purchases | Change in cafeteria food purchases labeled green. | 12 and 24 months |
| Change in Red-labeled (Unhealthy) Food Purchases | Change in cafeteria food purchases labeled red. | 12 and 24 months |
| Change in Healthy Purchasing Score | Change in overall score of the healthfulness of foods purchased, weighting the proportion of red, yellow, and green foods. To calculate the score, red foods are weighted 0, yellow are weighted 0.5, and green foods are weighted 1.0. Weighted scores are multiplied x 100, and the range is from 0 (least healthy cafeteria purchases, i.e. all red) to 100 (healthiest cafeteria purchases, i.e. all green). | 12 and 24 months |
| Change in Healthy Eating Index Score-15 | Change in Healthy Eating Index (HEI) scores. Healthy Eating Index Score is a measure of overall dietary quality that was calculated from two 24-hour dietary recalls. The range is from 0 (lowest diet quality) to 100 (highest diet quality) points. | 12 and 24 months |
| 34097048 | Derived | Thorndike AN, McCurley JL, Gelsomin ED, Anderson E, Chang Y, Porneala B, Johnson C, Rimm EB, Levy DE. Automated Behavioral Workplace Intervention to Prevent Weight Gain and Improve Diet: The ChooseWell 365 Randomized Clinical Trial. JAMA Netw Open. 2021 Jun 1;4(6):e2112528. doi: 10.1001/jamanetworkopen.2021.12528. |
| 32692747 | Derived | Dashti HS, Hivert MF, Levy DE, McCurley JL, Saxena R, Thorndike AN. Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial. PLoS Med. 2020 Jul 21;17(7):e1003219. doi: 10.1371/journal.pmed.1003219. eCollection 2020 Jul. |
| 31775714 | Derived | Feig EH, Levy DE, McCurley JL, Rimm EB, Anderson EM, Gelsomin ED, Thorndike AN. Association of work-related and leisure-time physical activity with workplace food purchases, dietary quality, and health of hospital employees. BMC Public Health. 2019 Nov 27;19(1):1583. doi: 10.1186/s12889-019-7944-1. |
| 30414448 | Derived | Levy DE, Gelsomin ED, Rimm EB, Pachucki M, Sanford J, Anderson E, Johnson C, Schutzberg R, Thorndike AN. Design of ChooseWell 365: Randomized controlled trial of an automated, personalized worksite intervention to promote healthy food choices and prevent weight gain. Contemp Clin Trials. 2018 Dec;75:78-86. doi: 10.1016/j.cct.2018.11.004. Epub 2018 Nov 7. |
| Missed 12-month follow-up visit |
|
| Became ineligible: new job in cafeteria |
|
| NOT COMPLETED |
|
|
| BG001 | Control | Monthly letters with general nutrition information |
| BG002 | Total | Total of all reporting groups |
| years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Ethnicity (NIH/OMB) | Count of Participants | Participants |
|
| Race/Ethnicity, Customized | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| Education | Count of Participants | Participants |
|
| Job category | Count of Participants | Participants |
|
| Weight | Mean | Standard Deviation | kg |
|
| Weight category | Count of Participants | Participants |
|
| Body Mass Index (BMI) | Mean | Standard Deviation | kg/m^2 |
|
| Systolic blood pressure | Mean | Standard Deviation | mmHg |
|
| Diastolic blood pressure | Mean | Standard Deviation | mmHg |
|
| Total cholesterol | Mean | Standard Deviation | mg/dL |
|
| LDL cholesterol | Mean | Standard Deviation | mg/dL |
|
| HDL cholesterol | Mean | Standard Deviation | mg/dL |
|
| Triglycerides | Mean | Standard Deviation | mg/dL |
|
| Hemoglobin A1C | Mean | Standard Deviation | percent |
|
| Percentage green-labeled (healthy) food purchased | Green-labeled food is the healthiest food in the cafeteria and has a main ingredient of either fruit, vegetable, low-fat dairy, or lean protein AND is low in calories and unhealthy fats. | Mean | Standard Deviation | percent |
|
| Percentage yellow-labeled food purchased | Yellow-labeled food is considered "less healthy" than green-labeled food but healthier than red-labeled food. | Mean | Standard Deviation | percent |
|
| Percentage red-labeled food purchased | Red-labeled food is the least healthy food in the cafeteria and is high in calories, unhealthy fats (saturated), or both. | Mean | Standard Deviation | percent |
|
| Healthy purchasing score | Overall score of the healthfulness of foods purchased, weighting the proportion of red, yellow, and green foods. To calculate the score, red foods are weighted 0, yellow are weighted 0.5, and green foods are weighted 1.0. Weighted scores are multiplied x 100, and the range is from 0 (least healthy cafeteria purchases, i.e. all red) to 100 (healthiest cafeteria purchases, i.e. all green). | Mean | Standard Deviation | units on a scale from 0-100 |
|
| Healthy Eating Index Score | Healthy Eating Index Score is a measure of overall dietary quality that was calculated from 2 24-hour dietary recalls. The range is from 0 (lowest diet quality) to 100 (highest diet quality). | Mean | Standard Deviation | units on a scale from 0-100 |
|
| Hypertension | Count of Participants | Participants |
|
| Hyperlipidemia | Count of Participants | Participants |
|
| Prediabetes or diabetes | Count of Participants | Participants |
|
| Weight goal | Count of Participants | Participants |
|
| Current smoker | Count of Participants | Participants |
|
|
|
|
| Secondary | Weight Change | Change in weight from baseline to 24 months | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | kg | 24 months |
|
|
|
|
| Secondary | Change in Blood Pressure | Change from baseline in mean systolic and diastolic blood pressure (BP). | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | mm Hg | 12 and 24 months |
|
|
|
|
| Secondary | Change in Total Cholesterol | Change from baseline in mean serum total cholesterol. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | mg/dL | 12 and 24 months |
|
|
|
|
| Secondary | Change in LDL Cholesterol | Change from baseline in mean serum LDL. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | mg/dL | 12 and 24 months |
|
|
|
|
| Secondary | Change in Triglycerides | Change in mean serum triglycerides. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | mg/dL | 12 and 24 months |
|
|
|
|
| Secondary | Change in HDL Cholesterol | Change in mean serum HDL. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | mg/dL | 12 and 24 months |
|
|
|
|
| Secondary | Change in Hemoglobin A1C | Change in mean serum hemoglobin A1c. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | Percentage | 12 and 24 months |
|
|
|
|
| Secondary | Change in Green-labeled (Healthy) Food Purchases | Change in cafeteria food purchases labeled green. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | percentage of purchases labeled green | 12 and 24 months |
|
|
|
|
| Secondary | Change in Red-labeled (Unhealthy) Food Purchases | Change in cafeteria food purchases labeled red. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | percentage of purchases labeled red | 12 and 24 months |
|
|
|
|
| Secondary | Change in Healthy Purchasing Score | Change in overall score of the healthfulness of foods purchased, weighting the proportion of red, yellow, and green foods. To calculate the score, red foods are weighted 0, yellow are weighted 0.5, and green foods are weighted 1.0. Weighted scores are multiplied x 100, and the range is from 0 (least healthy cafeteria purchases, i.e. all red) to 100 (healthiest cafeteria purchases, i.e. all green). | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | score on a scale (range 0-100) | 12 and 24 months |
|
|
|
|
| Secondary | Change in Healthy Eating Index Score-15 | Change in Healthy Eating Index (HEI) scores. Healthy Eating Index Score is a measure of overall dietary quality that was calculated from two 24-hour dietary recalls. The range is from 0 (lowest diet quality) to 100 (highest diet quality) points. | We conducted an intent-to-treat analysis with all missing data imputed for 12 and 24-month outcomes. | Posted | Mean | 95% Confidence Interval | score on a scale (range 0-100) | 12 and 24 months |
|
|
|
|
| 0 |
| 299 |
| 0 |
| 299 |
| 0 |
| 299 |
| EG001 | Control | Monthly letters with general nutrition information | 0 | 303 | 0 | 303 | 0 | 303 |
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| Change in diastolic BP from baseline to 12 months |
|
| Change in diastolic BP from baseline to 24 months |
|
| 0.19 |
| Mean Difference (Net) |
| 1.5 |
| 2-Sided |
| 95 |
| -0.7 |
| 3.7 |
| Superiority |
| Change in diastolic BP at 12 months | Mixed Models Analysis | 0.07 | Mean Difference (Net) | -1.6 | 2-Sided | 95 | -3.2 | 0.1 | Superiority |
| Change in diastolic BP at 24 months | Mixed Models Analysis | 0.94 | Mean Difference (Net) | 0.1 | 2-Sided | 95 | -1.5 | 1.6 | Superiority |
| 0.53 |
| Mean Difference (Net) |
| 1.6 |
| 2-Sided |
| 95 |
| -3.5 |
| 6.7 |
| Superiority |
| 0.60 |
| Mean Difference (Net) |
| 1.2 |
| 2-Sided |
| 95 |
| -3.4 |
| 5.7 |
| Superiority |
| 0.29 |
| Mean Difference (Net) |
| 4.0 |
| 2-Sided |
| 95 |
| -3.4 |
| 11.5 |
| Superiority |
| 0.72 |
| Mean Difference (Net) |
| -0.3 |
| 2-Sided |
| 95 |
| -1.9 |
| 1.3 |
| Superiority |
| 0.40 |
| Mean Difference (Net) |
| 0.0 |
| 2-Sided |
| 95 |
| 0.0 |
| 0.1 |
| Superiority |
| Mixed Models Analysis |
| <0.001 |
| Mean Difference (Net) |
| 4.8 |
| 2-Sided |
| 95 |
| 2.9 |
| 6.8 |
| Superiority |
| Mixed Models Analysis |
| <0.001 |
| Mean Difference (Net) |
| -3.1 |
| 2-Sided |
| 95 |
| -4.3 |
| -2.0 |
| Superiority |
| Mixed Models Analysis |
| <0.001 |
| Mean Difference (Net) |
| 4.0 |
| 2-Sided |
| 95 |
| 2.6 |
| 5.3 |
| Superiority |
| Mean Difference (Net) |
| 1.6 |
| 2-Sided |
| 95 |
| -0.7 |
| 3.8 |
| Superiority |