Europe's older adult population stands at 106 million, making up 21% of all residents. This number will grow to 150 million or 30% in the next 30 years . The launch of this plant-based supplement analysis tool comes at a crucial moment as digital nutrition resources don't deal very well with quality issues. Research reveals a concerning trend - out of 998 nutrition apps examined, only 16 qualified for evaluation. These apps scored poorly on credibility with just 2.09 out of 5 .
Plant-based supplements need special evaluation methods. Health authorities in the Netherlands suggest that vegetarian and vegan diets should include 20% to 30% more protein to make up for lower protein quality . The new VEGANScreener tackles this challenge with 29 specific questions. The tool uses 17 questions to examine beneficial foods and nutrients, while 12 questions look at areas that need limits . Five scientific partners from different European countries worked together to create this detailed plant-based supplement evaluation tool . Recent studies show that plant-based protein supplements help improve athletic performance in healthy people more effectively than consuming little or no protein . This finding proves how important proper analysis of plant-based supplements is for people of all backgrounds.
Researchers develop plant-based supplement analysis tool
A new plant-based supplement analysis tool helps older adults who choose plant-based diets meet their unique nutritional needs. This solution comes at a time when plant-based eating grows in popularity and creates a demand for specialized nutrition guidance.
Why older adults need better plant-based nutrition tracking
Older adults switching to plant-based diets face serious nutritional risks. Plant-based foods have lower quantities of essential amino acids than animal-based proteins. This makes them prone to protein deficiencies [1]. These deficiencies can reduce muscle mass, bone health and cognitive abilities [1]. The aging process brings additional challenges like reduced appetite. Studies show older adults feel 37% greater fullness after fasting compared to younger people [2].
Appetite reduction (anorexia of aging) affects between 15% and 30% of older adults living in communities. The number rises to 31% for seniors in hospitals and care facilities [2]. Increasing portion sizes - a common suggestion - doesn't work well for many older adults.
How the tool addresses protein quality and sustainability
The digital tool uses innovative Meal Protein Quality Scores (MPQS) to assess essential amino acid profiles [1]. Its algorithms provide three ways to improve diet:
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Gram-by-gram substitution
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Proportional adjustments
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Adding missing nutritional components
This science-based approach helps users optimize protein intake without eating more food. Health authorities recommend 20-30% more protein for vegetarian and vegan diets [2]. The tool balances nutritional needs with environmental goals to make sustainable eating both available and nutritionally complete.
Who worked on the tool's development
Researchers from Denmark and the Netherlands worked together on this tool. They conducted focus groups with dietitians and older adults [1]. This accessible design approach identified key needs through three phases: needs assessment, solution conceptualization, and usability testing [1].
Nutrition scientists and food informatics experts built databases with essential amino acid content information. These databases help the tool find the best food combinations [2]. The original research identified dietitians as the core team of users. They recognized older adults would need basic education about protein quality before wider adoption [2].
Focus groups shape tool features and usability
The development team ran extensive focus groups to identify key features needed for the plant-based supplement analysis tool. They gathered vital input from dietitians and older adults in Denmark and the Netherlands.
What dietitians and older adults wanted in the tool
Both user groups showed strong interest in features that provided feedback on protein quality, sustainability, and micronutrients [2]. The users' main priority was personalization, and participants noted that "one size does not fit all" [3]. Users wanted to enter their personal information such as age, sex, protein requirements, allergies, and food priorities [2].
Dietitians preferred to enter simple ingredients during consultations for dietary assessment. Older adults liked working with food pictures better [2]. Both groups made ease of use their priority. They asked for features like remembered input history, flexible portion size options, and quick meal-focused assessments instead of full-day tracking [2].
Users wanted evaluations for each meal and daily summaries. An interesting finding showed dietitians preferred clear, direct feedback while older adults liked more positive framing [2]. Dietitians asked for 3-5 options for alternative suggestions, while older adults wanted 3-10 alternatives [2].
How the Walt Disney and brainwriting methods were used
The research team used innovative collaboration techniques during the conceptualization phase. The Walt Disney method split participants into three distinct roles—dreamers, realists, and critics—to look at challenges from different viewpoints [4]. This well-laid-out approach helped create balanced solutions by looking at creative possibilities and practical limits [2].
Dreamers focused on unconstrained brainstorming, realists checked implementation feasibility, and critics spotted potential flaws and risks [4]. The team also used brainwriting techniques. This allowed participants to create ideas on their own before group discussion, which stopped dominant voices from controlling the conversation [2].
Which features were considered deal-breakers
Participants identified several non-negotiable requirements during the focus groups. Both user groups listed slow performance, too much time investment, unsuitable alternative suggestions, and overall tool complexity as deal-breakers [2].
Missing products in the database would stop dietitians from adopting the tool [2]. Older adults pointed to tool pricing as their specific deal-breaker [2]. Users also mentioned that poor experience elements like small fonts, bad contrast, and complex navigation would make them stop using the tool [3].
Developers test tool with real users
Researchers conducted thorough usability testing with dietitians and older adults to refine the original plant-based supplement analysis tool interface after developing the prototypes.
What screenshots revealed about usability issues
The usability tests with screenshots showed four interfaces that were hard to use. Screenshot 4A (consultation session) received the lowest usability score from dietitians at just 42% [2], mainly because they rated their understanding at only 3% [2]. The dietitians also gave screenshot 3A (add food intake) a low score of 46% [2]. Older adults gave better ratings to these same interfaces, with screenshot 3A scoring 60% [2].
Users found several problems in all screenshots. They were confused by symbols like the magnifying glass function and triangles that showed more information. The filter usage wasn't clear, and the color coding system puzzled them. Both groups had trouble figuring out how to enter drinks and snacks that weren't standard meal items.
How feedback led to interface improvements
The testing showed that screens needed more visual consistency. Research findings indicated that standardization was needed for colors, symbols, and text elements like save buttons [2]. Users weren't sure what to do next on several screens, so the team focused on fixing these navigation issues.
Why dietitians were chosen as the primary user group
The research team chose dietitians as the main users even though they tested with both groups. Three key factors drove this decision. Dietitians already knew the nutrition basics needed to use the tool well [2]. Their direct feedback helped avoid confusion among older adults [2]. The team also found that dietitians could effectively explain complex nutritional data about plant-based supplements to older adults [2].
Tool integrates data science and nutrition algorithms
Image Source: ACS Publications - American Chemical Society
The plant-based supplement analysis tool combines advanced nutritional science with powerful data processing capabilities.
How the Meal Protein Quality Score (MPQS) works
The MPQS looks at both protein quantity and quality in meals. It combines digestibility-adjusted essential amino acid (EAA) intake with total protein consumed. This detailed metric creates a score from 0 to 100 that shows how well a meal meets EAA requirements [5]. Hospital meal data analysis showed that meals with more plant protein had lower protein quality scores [6].
What databases and algorithms power the tool
The tool uses the enhanced NEVO food database with amino acid profiles for foods containing more than 1% protein [5]. The digestibility data comes mainly from ileal measurements, then fecal values. Human studies take priority over animal research [5]. Artificial neural network (ANN) machine learning algorithms boost the tool's analysis capabilities [7].
How the tool suggests alternatives to improve meals
The tool offers three different algorithms for personalized recommendations:
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Gram-by-gram alternatives swap specific items with similar foods
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Missing-piece alternatives find single items that push MPQS to 100
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Proportion-adjustment uses linear programming to make existing meal components better [2]
Why amino acid tracking is critical for plant-based supplements
Plant proteins have lower essential amino acid levels (21-23%) compared to animal proteins (32-43%) [8]. Methionine and lysine pose particular challenges. These amino acids appear in much lower amounts in plant sources (1.0% and 3.6%) versus animal proteins (2.5% and 7.0%) [8]. Smart combinations of complementary plant proteins help fix these shortages without making portions bigger [5].
Conclusion
Plant-based supplement analysis tools mark a major step forward in nutritional technology. These tools help older adults who want to switch to plant-based diets. Without doubt, this innovative solution helps seniors with specific dietary needs. The tool's Meal Protein Quality Scores system stands out. It reviews amino acid profiles without needing larger portions - vital since older adults often eat less.
Researchers from Denmark and the Netherlands worked together and got amazing results with their intuitive design approach. Focus groups showed what dietitians and older adults needed most: custom options, meal-based reviews, and proper feedback systems. The team used Walt Disney and brainwriting methods that made the tool's design better by looking at different views.
Tests showed some interface issues needed work, especially with navigation, clear symbols, and consistent visuals. While both groups tested the tool, dietitians became the main users because they knew nutrition better and could explain complex data to older adults.
The tool's technology base deserves a closer look. It uses food databases with amino acid profiles, machine learning algorithms, and three different recommendation systems to create a strong analytical engine. This smart approach solves the basic problem - plant proteins have fewer essential amino acids than animal proteins.
This plant-based supplement analysis tool fills a big gap in nutrition tech. Europe's older population keeps growing, and more people want plant-based diets. These specialized tools will become more valuable. The careful development process, scientific method, and intuitive design show how technology can tackle complex nutrition challenges while supporting eco-friendly food choices.
FAQs
Q1. How does the plant-based supplement analysis tool work? The tool uses a Meal Protein Quality Score (MPQS) to evaluate both the quantity and quality of protein in meals. It analyzes essential amino acid profiles and total protein consumed, generating a score from 0 to 100 to indicate how well a meal meets nutritional requirements.
Q2. Why is this tool particularly important for older adults? Older adults on plant-based diets face unique nutritional challenges, including potential protein deficiencies. The tool helps address these issues by providing tailored recommendations without increasing portion sizes, which is crucial as aging often reduces appetite.
Q3. What features does the tool offer for personalization? The tool allows users to enter personal information such as age, sex, protein requirements, allergies, and food preferences. It also provides per-meal evaluations, daily summaries, and suggests alternative food options to improve nutritional intake.
Q4. How does the tool suggest alternatives to improve meals? The tool uses three distinct algorithms to generate personalized recommendations: gram-by-gram alternatives, missing-piece alternatives, and proportion-adjustment. These help users optimize their meals for better nutritional quality without necessarily increasing portion sizes.
Q5. Who are the primary users of this tool? While the tool was developed with input from both dietitians and older adults, dietitians were ultimately chosen as the primary users. This is because they already possess the nutritional knowledge required to operate the tool effectively and can interpret complex nutritional data for older adults using plant-based supplements.
References
[1] - https://www.news-medical.net/news/20250101/Plant-based-diets-made-easier-for-seniors-with-innovative-tech.aspx
[2] - https://pmc.ncbi.nlm.nih.gov/articles/PMC11695958/
[3] - https://onlinelibrary.wiley.com/doi/10.1111/hex.13923
[4] - https://akisconnect.eu/iss-tools-and-methods/tool-details?id=47&name=Walt+Disney+method
[5] - https://www.medrxiv.org/content/10.1101/2024.06.04.24308419v1.full-text
[6] - https://pubmed.ncbi.nlm.nih.gov/39290315/
[7] - https://www.researchgate.net/publication/381626537_Artificial_Neural_Network_Algorithm_in_Nutritional_Assessment_Implication_for_Machine_Learning_Prediction_in_Nutritional_Assessments_in_Strict_Veganism
[8] - https://pmc.ncbi.nlm.nih.gov/articles/PMC6245118/
