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Field
Trial Start Date
|
Before
October 06, 2025
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After
March 17, 2026
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|
Field
Trial End Date
|
Before
January 12, 2026
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After
June 06, 2026
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|
Field
Last Published
|
Before
April 02, 2026 05:37 PM
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After
June 26, 2026 04:38 PM
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|
Field
Study Withdrawn
|
Before
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After
No
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|
Field
Intervention Completion Date
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Before
|
After
June 04, 2026
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|
Field
Data Collection Complete
|
Before
|
After
Yes
|
|
Field
Final Sample Size: Number of Clusters (Unit of Randomization)
|
Before
|
After
no clusters
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|
Field
Was attrition correlated with treatment status?
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Before
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After
No
|
|
Field
Final Sample Size: Total Number of Observations
|
Before
|
After
149 participants analyzed for the primary outcome (84 control, 65 treatment). Up to 183 had an endline ASA24 recall (the outcome); 149 also had a matched baseline HEI.
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|
Field
Final Sample Size (or Number of Clusters) by Treatment Arms
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Before
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After
Randomized: 967 control / 945 treatment. Analyzed (primary outcome): 84 control / 65 treatment.
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|
Field
Is there a restricted access data set available on request?
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Before
|
After
Yes
|
|
Field
Restricted Data Contact
|
Before
|
After
[email protected]
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|
Field
Program Files
|
Before
|
After
No
|
|
Field
Data Collection Completion Date
|
Before
|
After
June 06, 2026
|
|
Field
Is data available for public use?
|
Before
|
After
No
|
|
Field
Intervention Start Date
|
Before
October 13, 2025
|
After
April 17, 2026
|
|
Field
Intervention End Date
|
Before
January 05, 2026
|
After
June 04, 2026
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|
Field
Experimental Design (Public)
|
Before
We will recruit 1,400 U.S. adults through the Forthright platform. After an eligibility screener (≥ 18 y, English-speaking, owns a smartphone, no diet restrictions), Forthright’s server-side block randomizer will assign participants 1: 1 to two parallel arms:
• Treatment arm – full AI-Nutrition app with real-time, personalized meal suggestions generated by AI and natural-language-processing algorithms.
• Control arm – only receives general dietary suggestions (e.g., USDA MyPlate tip sheets).
The study design is single blind from the participants’ side. Participants will be blind to allocation; they are told only that they will receive “nutrition guidance”. The control arm is not informed that another group uses an app. Forthright and our technology team will see and handle the randomization and allocations, while the data analysis team will be masked to the arm codes.
We will collect dietary intake along with several behavioral questions at the baseline (Week 0, before app access) and the post-intervention point (Week 12). The dietary intake will be collected with the ASA24 24-hour recall, and the behavioral questions will be given to study participants to assess their eating habits. The treatment arm participants will be instructed to use the app at least once per week and indicate whether they followed each personalized recommendation. App analytics (log-ins, screen views, session length) will be logged automatically for subsequent engagement analyses.
Data-collection schedule
Study week Assessment Mode Approx. time
0 (baseline) ASA24® 24-h recall; demographics; eating-behavior questionnaire Forthright survey link 20 min
1 – 12 App use (Treatment arm) + engagement logging In-app 5 min per use
12 (post) ASA24® 24-h recall; user-experience items Forthright survey link 20 min
|
After
We will screen approximately 1,900 U.S. adults through the Forthright Access platform. After an eligibility screener (≥ 18 years; basic English; regular smartphone and internet access; generally healthy adults for whom the Dietary Guidelines for Americans are appropriate — excluding those requiring medically supervised or restrictive diets, e.g., diabetes, celiac/gluten sensitivity, CKD requiring dietary restriction, prescribed or highly restrictive diets, or pregnancy), Forthright's server-side block randomizer will assign eligible participants 1:1 to two parallel arms. Accounting for ≈50% eligibility and ≈10% attrition, we anticipate an analytic sample of ≈780 (≈390 per arm).
Both arms use the same mobile/web application, which includes a Track Mode for all participants (log meals; view nutrient and diet-quality summaries) and a Personalized Recommendation Mode for the treatment arm only.
Treatment arm – the app with Track Mode plus the AI/NLP-driven Personalized Recommendation Mode (OpenAI engine constrained to USDA FPED, the Dietary Guidelines, and AMDR ranges; educational only).
Control arm – the same app shell in Track Mode only (tracking + general, non-personalized guidance); no AI-personalized recommendations.
Single-blind from the participant's side; participants are told only that they will receive "nutrition guidance"; the control arm is not informed another group receives AI recommendations. Forthright/the technology team handle randomization; the data-analysis team is masked to arm codes. Dietary intake and behavioral questions are collected at baseline (Week 0) and at the post-intervention endline [registered Week 12; implemented after ~7 weeks under the approved modification]. Intake is measured with ASA24; treatment participants are asked to use the app ≥ once/week and to indicate whether they followed each recommendation; app analytics are logged automatically for engagement/uptake analyses.
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|
Field
Randomization Method
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Before
Forthright algorithm
|
After
Randomization was performed by the research team, using a computer-generated, stratified randomization procedure implemented in R with a fixed seed for reproducibility. Eligible participants who passed the electronic screener and provided e-consent were stratified by gender, age group (18–34, 35–49, 50+), and household income group (<$35k, $35k–$74k, $75k–$149k, ≥$150k); within each stratum (the cross-classification of gender × age × income), participants were allocated 1:1 to the treatment and control arms by random permutation of balanced assignment labels. Forthright provided panel recruitment and survey administration only; the study team generated and managed the allocation sequence and arm assignments. Participants were blind to allocation (single-blind from the participant side), and the data-analysis team was masked to the arm codes.
Original structure (as registered). Each completed survey earned $2.50 plus one loyalty point. Participants who completed both the baseline and endline surveys qualified for an app-engagement reward based on their app activity: the top 1% → $50, those ranked top 1–10% → $5, with ties split equally.
Modification at the (early) endline. End-survey incentives were augmented: the first 200 eligible participants who fully completed the end survey by Thursday, June 4, 2026 received $15 each, and all who completed it by that date were entered into a random drawing for one $150 gift card — in addition to the original app-engagement rewards (top 1% → $50; top 10% → $5).
|
|
Field
Randomization Unit
|
Before
Two arms are included: (1) Control – intake tracking app and general advice, and (2) Treatment – intake tracking app plus AI-generated dietary advice.
|
After
Two arms are included: Treatment arm — the app with Track Mode and the AI-driven Personalized Recommendation Mode: real-time personalized meal suggestions from an LLM/NLP engine (OpenAI) constrained to USDA FPED, the Dietary Guidelines, and AMDR ranges (educational only).
Control arm — the same app shell in Track Mode only (tracking features + general, non-personalized guidance); no AI-personalized recommendations.
|
|
Field
Planned Number of Clusters
|
Before
Primary design is individual-level randomization via Forthright. If operational constraints require batching or geographic assignment that induces clustering, we will amend the registry to specify the cluster unit and count and will use cluster-robust SEs accordingly.
|
After
Not applicable — individual-level randomization (no clustering). The unit of randomization is the individual participant; participants were stratified by gender × age × income and assigned 1:1 within strata.
|
|
Field
Intervention (Hidden)
|
Before
We will recruit 1,400 U.S. adults through the Forthright platform. After an eligibility screener (≥ 18 y, English-speaking, owns a smartphone, no diet restrictions), Forthright’s server-side block randomizer will assign participants 1: 1 to two parallel arms:
• Treatment arm – full AI-Nutrition app with real-time, personalized meal suggestions generated by AI and natural-language-processing algorithms.
• Control arm – only receives general dietary suggestions (e.g., USDA MyPlate tip sheets).
The study design is single blind from the participants’ side. Participants will be blind to allocation; they are told only that they will receive “nutrition guidance”. The control arm is not informed that another group uses an app. Forthright and our technology team will see and handle the randomization and allocations, while the data analysis team will be masked to the arm codes.
We will collect dietary intake along with several behavioral questions at the baseline (Week 0, before app access) and the post-intervention point (Week 12). The dietary intake will be collected with the ASA24 24-hour recall, and the behavioral questions will be given to study participants to assess their eating habits. The treatment arm participants will be instructed to use the app at least once per week and indicate whether they followed each personalized recommendation. App analytics (log-ins, screen views, session length) will be logged automatically for subsequent engagement analyses.
|
After
We will screen approximately 1,900 U.S. adults through the Forthright Access platform. After an eligibility screener (≥ 18 years; basic English; regular access to a smartphone and internet; generally healthy adults for whom the Dietary Guidelines for Americans are appropriate — excluding individuals requiring medically supervised or restrictive diets, e.g., diabetes, celiac disease/gluten sensitivity, chronic kidney disease requiring dietary restriction, prescribed/highly-restrictive diets, or pregnancy), Forthright's server-side block randomizer will assign eligible participants 1:1 to two parallel arms. We anticipate an analytic sample of approximately 780 (~390 per arm).
Both arms use the same mobile/web application. It has two components: a Track Mode for all participants (log meals, view nutrient and diet-quality summaries) and a Personalized Recommendation Mode for the treatment arm only.
Treatment arm — the app with Track Mode and the AI-driven Personalized Recommendation Mode: real-time personalized meal suggestions from an LLM/NLP engine (OpenAI) constrained to USDA FPED, the Dietary Guidelines, and AMDR ranges (educational only).
Control arm — the same app shell in Track Mode only (tracking features + general, non-personalized guidance); no AI-personalized recommendations.
Single-blind from the participant's side; the data-analysis team is masked to arm codes. Dietary intake and behavioral items are collected at baseline (Week 0) and at the post-intervention endline [registered Week 12; implemented after ~7 weeks under the approved modification]. Intake is measured with ASA24; treatment participants are asked to use the app ≥ once/week and indicate whether they followed each recommendation; app analytics are logged automatically. Emails are collected only for app registration and reminders.
|