Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots
Abstract
:1. Introduction
2. Materials and Methods
Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Diet Quality Component | Grouping of Diet Quality Component | Scoring Criteria | Score |
---|---|---|---|
Variety—food groups | 5 food groups: meat/poultry/fish/egg, dairy/beans, grains, fruits, and vegetables | Each food group awarded 0 or 3 pts: 3 points awarded if at least 1 item from that group was consumed | 0–15 |
Variety—protein sources | 6 sources: meat, poultry, fish, dairy, beans, eggs | 3 or more sources consumed: 5 pts 2 sources consumed: 3 pts 1 source consumed: 1 pts 0 sources consumed: 0 pts | 0–5 |
Adequacy | 8 groups: vegetables, fruit, grain, fibre, protein, iron, calcium, vitamin C | Between 0 and 5 points awarded for each of the 8 adequacy groups, depending on percentage of Recommended Daily Allowance (RDA) met | 0–40 |
Moderation | 6 groups: total fat, saturated fat, cholesterol, sodium, empty calorie foods | Between 0 and 6 points awarded for each of the 5 moderation groups, depending on percentage of RDA met | 0–30 |
Balance | 2 groups: macronutrient ratio, fatty acid ratio, fatty acid ratio | Between 0 and 6 points awarded depending on ratio of macronutrients, and between 0 and 4 points awarded depending on ratio of fatty acids | 0–10 |
Chatbot | Variety—Food Groups | Variety—Protein Sources | Adequacy | Moderation | Balance | Total DQI-I Score |
---|---|---|---|---|---|---|
Gemini (n = 10) | 15.00 (±0.0) | 4.60 (±0.8) | 33.00 (±1.8) | 18.90 (±4.2) | 0.40 (±1.3) | 71.90 (±4.1) |
Microsoft Copilot (n = 10) | 15.00 (±0.0) | 5.00 (±0.0) | 34.50 (±2.1) | 17.40 (±2.4) | 0.40 (±0.8) | 72.30 (±4.1) |
ChatGPT 4.0 (n = 10) | 14.70 (±0.9) | 5.00 (±0.0) | 34.70 (±2.1) | 16.80 (±3.5) | 00.00 (±0.0) | 71.20 (±5.2) |
Overall (n = 30) | 14.90 (±0.5) | 4.87 (±0.5) | 34.07 (±2.1) | 17.70 (±3.5) | 0.27 (±0.9) | 71.80 (±4.3) |
Gender | Variety—Food Groups | Variety—Protein Sources | Adequacy | Moderation | Balance | Total DQI-I Score |
---|---|---|---|---|---|---|
Female (n = 15) | 15.00 (±0.0) | 5.00 (±0.0) | 34.27 (±1.9) | 17.20 (±3.8) | 0.27 (±1.3) | 71.73 (±3.9) |
Male (n = 15) | 14.80 (±0.7) | 4.73 (±0.7) | 33.87 (±2.3) | 18.20 (±3.1) | 0.27 (±0.7) | 71.87 (±4.9) |
p value * | 0.040 ** | 0.002 ** | 0.579 | 0.654 | 0.895 | 0.561 |
Chatbot | <5% | 5–9.99% | 10–14.99% | 15–19.99% | ≥20% |
---|---|---|---|---|---|
Gemini (n = 10) | n = 2 (20%) | n = 0 (0%) | n = 1 (10%) | n = 2 (20%) | n = 5 (50%) |
Microsoft Copilot (n = 10) | n = 3 (30%) | n = 2 (20%) | n = 2 (20%) | n = 2 (20%) | n = 1 (10%) |
ChatGPT 4.0 (n = 10) | n = 2 (20%) | n = 5 (50%) | n = 2 (20%) | n = 1 (10%) | n = 0 (0%) |
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Kaya Kaçar, H.; Kaçar, Ö.F.; Avery, A. Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots. Nutrients 2025, 17, 206. https://doi.org/10.3390/nu17020206
Kaya Kaçar H, Kaçar ÖF, Avery A. Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots. Nutrients. 2025; 17(2):206. https://doi.org/10.3390/nu17020206
Chicago/Turabian StyleKaya Kaçar, Hüsna, Ömer Furkan Kaçar, and Amanda Avery. 2025. "Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots" Nutrients 17, no. 2: 206. https://doi.org/10.3390/nu17020206
APA StyleKaya Kaçar, H., Kaçar, Ö. F., & Avery, A. (2025). Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots. Nutrients, 17(2), 206. https://doi.org/10.3390/nu17020206