Veidlapa Nr. M-3 (8)
Study Course Description
Digital Tools and Artificial Intelligence in Nutritionist Practice and Research
Course Code
REK_320
Branch of Science
Health sciences; Nutrition
ECTS
3.00
Target Audience
Rehabilitation
LQF
Level 6
Study Type And Form
Full-Time; Part-Time
Study Course Implementer
Course Supervisor
Lolita Vija Neimane
Structure Unit Manager
Liāna Deklava
Structural Unit
Department of Rehabilitation
Contacts
Riga, Anninmuizas Boulevard 26a, rk@rsu.lv, +371 20271291
About Study Course
Objective
The aim of the study course is to develop students’ understanding and practical competence in working with digital methods of measuring health and nutrition (eHealth, mobile health) in order to train students’ ability to choose and justify the most appropriate methods in clinical practice and research, critically evaluate data quality and limitations, as well as to develop, analyse, interpret and communicate nutrition and health related data. At the end of the course, students demonstrate what they have learned by developing a science conference poster and creating a protocol for a randomized controlled study.
Preliminary Knowledge
Basic knowledge of research methodology.
• basic nutrition assessment skills
• behavioural change theories
Learning Outcomes
Knowledge
1.After the course, the student: - explain the basic concepts of digital transformation, eHealth and mHealth, as well as the role, benefits and limitations of teleconsultation in the nutritionist’s practice; - describe and compare methods for measuring paper and digital dietary intake; - describe digital health measurement tools in the context of nutrition; - explain the basic principles for measuring body mass/composition and energy consumption; - explain the sources of nutritional data errors in nutritional studies; - describe the guiding principles of GDPR in the processing of health data, confidentiality requirements and the guiding principles of safe use of AI in dietary practices; - describes the possibilities and risks of using AI in research and understands the conditions for academic integrity and use of AI
Skills
1.- recommends and justifies the most appropriate method of measuring dietary intake for a specific purpose and situation; - interpret technology data in the context of nutrition by identifying potential adjacent factors and data quality risks and formulate conclusions understandable to the patient; - interpret the results of bioimpedence, DEXA and indirect calorimetry; - identify nutritional and digital measurement data errors, possible mixing factors and sources of heterogeneity; - use AI support to document nutritional advice; - develop a poster for a scientific conference on a categorised study and present it; - plan and develop a study protocol for a specific target group with an mHealth component in intervention, prepare and present a summary of the protocol.
Competences
1.- integrate digital data into the nutritionist’s work process - make informed decisions on the choice of method and interpretation of data - ensure data quality and formulate reasoned conclusions - respect ethics, GDPR and confidentiality in digital nutrition practices/research - safe and targeted use of AI in nutritional practices - working on an interdisciplinary team in the context of digital solutions - communicate scientific information in a professional format - plans a digital study
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Group work - randomised controlled study protocol |
60.00% from total grade
|
10 points
|
|
Develop a study protocol for a specific target group (e.g. young people, athletes, pregnant women, type 2 diabetes patients, seniors) with a mandatory mobile health (mHealth) component in the intervention group (e.g. mobile app + sensor + telecommunications). Protocol + 10 min presentation to be submitted. |
||
|
2.
Individual job - Conference Poster |
40.00% from total grade
|
10 points
|
|
Prepare a conference poster on a distributed study using digital nutrition/body composition/health measurement techniques. Downloadable digital poster + 5 min presentation. |
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Self-service presentations |
-
|
10 points
|
|
Group RCT Protocol + presentation - 60% - problem definition and objectives (5%) - population, inclusion/exclusion criteria, randomisation (5%) - description of intervention with mHealth component (10%) - outcomes (primary/secondary), measurement methods and data quality risks (10%) - data protection/ethical aspects + short data management plan (10%) - presentation (20%) individual poster + presentation - 40% - Summary of study and critical analysis (15%) - evaluation of digital measurement methods (accuracy, errors) (15%) - Poster design/structurality + clarity of presentation (10%) |
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Introduction. Course content.
The digital environment in the context of modern nutrition.
Digital transformation in health and nutrition; mHealth/eHealth core concepts; online consulting role; and
limitations.
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Methods for measuring dietary intake.
Comparison of paper size and digital methods (questionnaires, surveys, diaries, photo methods); suitability of methods in clinical practice and research.
Practical application to different situations
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital measuring tools and sensors in practice.
Continuous glucose monitor, accelerometer/step/intensity meter.
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Measurement of energy consumption and body composition in nutritional practice and research.
Bioimpedance, indirect calorimetry, DEXA, MR, USG
Description
Lecture - 1 hr 30 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Nutritional data cavity, errors, influencing factors.
Introduction to the written jobs.
Critical thinking when interpreting data; socially desirable responses; memory errors; why digital data isn’t always accurate; heterogeneity in research and conclusions.
Randomised controlled studies, conference presentations (posters).
Description
Lesson - 2 hr 15 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Data protection and artificial intelligence in nutritional practices.
Guiding principles of GDPR in digital nutrition practice/research; confidentiality; interdisciplinary cooperation with IT; AI
basic principles and safe use in practice.
AI in practice.
Practical stations: audio notes, summary of advice; verification of calculations; red flags in AI recommendations; data minimisation.
Description
Lesson – 2 h 15 min remotely or face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Artificial intelligence in research.
AI databases, scientific tools, academic integrity, literature summaries/structuring (e.g. nutrition guidelines).
Description
Lesson – 2 h 15 min remotely or face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Poster development.
Exploring research, creating a digital poster.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Development of a research protocol.
Group work – RCT with mHealth component. Development of a protocol. Creating a presentation.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Development of a research protocol.
Group work – RCT with mHealth component. Development of a protocol. Creating a presentation.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Final presentations - poster
Description
Lesson - 2 hr 15 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Final presentations - study protocol.
Description
Lesson - 2 hr 15 min face-to-face |
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
PART-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Introduction. Course content.
The digital environment in the context of modern nutrition.
Digital transformation in health and nutrition; mHealth/eHealth core concepts; online consulting role; and
limitations.
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Methods for measuring dietary intake.
Comparison of paper size and digital methods (questionnaires, surveys, diaries, photo methods); suitability of methods in clinical practice and research.
Practical application to different situations
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital measuring tools and sensors in practice.
Continuous glucose monitor, accelerometer/step/intensity meter.
Description
Lecture - 1 hr 30 min face-to-face |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Measurement of energy consumption and body composition in nutritional practice and research.
Bioimpedance, indirect calorimetry, DEXA, MR, USG
Description
Lecture - 1 hr 30 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Nutritional data cavity, errors, influencing factors.
Introduction to the written jobs.
Critical thinking when interpreting data; socially desirable responses; memory errors; why digital data isn’t always accurate; heterogeneity in research and conclusions.
Randomised controlled studies, conference presentations (posters).
Description
Lesson - 2 hr 15 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Data protection and artificial intelligence in nutritional practices.
Guiding principles of GDPR in digital nutrition practice/research; confidentiality; interdisciplinary cooperation with IT; AI
basic principles and safe use in practice.
AI in practice.
Practical stations: audio notes, summary of advice; verification of calculations; red flags in AI recommendations; data minimisation.
Description
Lesson – 2 h 15 min remotely or face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Artificial intelligence in research.
AI databases, scientific tools, academic integrity, literature summaries/structuring (e.g. nutrition guidelines).
Description
Lesson – 2 h 15 min remotely or face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Poster development.
Exploring research, creating a digital poster.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Development of a research protocol.
Group work – RCT with mHealth component. Development of a protocol. Creating a presentation.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Development of a research protocol.
Group work – RCT with mHealth component. Development of a protocol. Creating a presentation.
Description
Lesson - 2 hr 15 min remotely |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Final presentations - poster
Description
Lesson - 2 hr 15 min face-to-face |
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
3
|
Topics
|
Final presentations - study protocol.
Description
Lesson - 2 hr 15 min face-to-face |
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Diet, Anthropometry and Physical Activity (DAPA) Measurement Toolkit:
2.
NCP Terminology
3.
PICO. Cochrane Library
4.
Limketkai BN, Mauldin K, Manitius N, Jalilian L, Salonen BR. The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition. Curr Surg Rep. 2021;9(7):20
Additional Reading
1.
Wright, O. and Baruah, S. (2025). Integrating generative AI to strengthen counselling and communication in dietetic education. In R. Fitzgerald (Ed.), Inquiry in action: Using AI to reimagine learning and teaching. The University of Queensland.
2.
EFAD 2022 Supplementary document to the current International Code of Ethics