An Ontology-Based Serious Game Design for the Development of Nutrition and Food Literacy Skills

Are Nutrition Literacy and Sustainable Dietary Habits Associated with Cardiovascular Disease and Diabetes Developmental Risks?

OBJECTIVE

This study aimed to examine the association of nutritional literacy levels and sustainable nutritional behaviors with the risk of developing cardiovascular diseases and diabetes in the Turkish adult population.

METHODS

Sociodemographic information, disease history, nutritional habits, and physical activity levels of 3146 volunteer individuals (male = 1590, female = 1556) between the ages of 40-75 were collected using a questionnaire form and face-to-face interviews. The sustainable nutritional behaviors of the participants were evaluated using Turkish validated scales for Sustainable and Healthy Eating Behavior (SHE) and nutritional literacy levels with the Evaluation Instrument of Nutrition Literacy on Adults (EINLA). Cardiovascular disease risks of the participants were assessed with the Atherosclerotic Cardiovascular Disease (ASCVD) Risk Estimator program and the Heart Score (SCORE) scale and type-2 diabetes risk with the Finnish Diabetes Risk Score (FINDRISC). Each participant's 24-h food consumption record was obtained using the retrospective recall method.

RESULTS

It was determined that ASCVD and SCORE levels were significantly higher in males compared to females. It was observed that individuals with lower cardiovascular and diabetes risk scores had higher educational levels, and the risks increased significantly with age (p < 0.05). Anthropometric measurements such as body mass index, and waist hip circumference were significantly higher in those with higher cardiovascular and diabetes risk scores. Furthermore, in individuals with higher SCORE and FINDRISC levels, SHE and EINLA scores were significantly lower (p < 0.05). It was also observed that SCORE and diabetes risk scores increased with higher energy and macronutrient intakes.

CONCLUSION

The risk of developing cardiovascular disease and diabetes was associated with sustainable nutritional behaviors and nutritional literacy. It may be suggested that increasing nutritional literacy and encouraging sustainable nutritional behaviors may be effective strategies in the management and reduction of the prevalence of certain chronic diseases.KEY TEACHING POINTSCardiovascular diseases and diabetes are two major chronic conditions that can be managed and treated through proper nutrition.Increased nutritional literacy levels and sustainable dietary habits may result in reduced risk of cardiovascular diseases and diabetes.Nutritionists should assess the patients' nutrition literacy levels and implement sustainable, health-focused nutrition education programs to enhance their understanding of nutrition.

A Multimodal Approach for Real Time Recognition of Engagement towards Adaptive Serious Games for Health

In this article, an unobtrusive and affordable sensor-based multimodal approach for real time recognition of engagement in serious games (SGs) for health is presented. This approach aims to achieve individualization in SGs that promote self-health management. The feasibility of the proposed approach was investigated by designing and implementing an experimental process focusing on real time recognition of engagement. Twenty-six participants were recruited and engaged in sessions with a SG that promotes food and nutrition literacy. Data were collected during play from a heart rate sensor, a smart chair, and in-game metrics. Perceived engagement, as an approximation to the ground truth, was annotated continuously by participants. An additional group of six participants were recruited for smart chair calibration purposes. The analysis was conducted in two directions, firstly investigating associations between identified sitting postures and perceived engagement, and secondly evaluating the predictive capacity of features extracted from the multitude of sources towards the ground truth. The results demonstrate significant associations and predictive capacity from all investigated sources, with a multimodal feature combination displaying superiority over unimodal features. These results advocate for the feasibility of real time recognition of engagement in adaptive serious games for health by using the presented approach.

The ontology of fast food facts: conceptualization of nutritional fast food data for consumers and semantic web applications

Background

Fast food with its abundance and availability to consumers may have health consequences due to the high calorie intake which is a major contributor to life threatening diseases. Providing nutritional information has some impact on consumer decisions to self regulate and promote healthier diets, and thus, government regulations have mandated the publishing of nutritional content to assist consumers, including for fast food. However, fast food nutritional information is fragmented, and we realize a benefit to collate nutritional data to synthesize knowledge for individuals.

Methods

We developed the ontology of fast food facts as an opportunity to standardize knowledge of fast food and link nutritional data that could be analyzed and aggregated for the information needs of consumers and experts. The ontology is based on metadata from 21 fast food establishment nutritional resources and authored in OWL2 using Protégé.

Results

Three evaluators reviewed the logical structure of the ontology through natural language translation of the axioms. While there is majority agreement (76.1% pairwise agreement) of the veracity of the ontology, we identified 103 out of the 430 statements that were erroneous. We revised the ontology and publicably published the initial release of the ontology. The ontology has 413 classes, 21 object properties, 13 data properties, and 494 logical axioms.

Conclusion

With the initial release of the ontology of fast food facts we discuss some future visions with the continued evolution of this knowledge base, and the challenges we plan to address, like the management and publication of voluminous amount of semantically linked fast food nutritional data.

On How Chronic Conditions Affect the Patient-AI Interaction: A Literature Review

Background: Across the globe, managing chronic diseases has been recognized as a challenge for patients and healthcare providers. The state of the art in managing chronic conditions requires not only responding to the clinical needs of the patient, but also guaranteeing a comfortable state of wellbeing for them, despite living with the disease. This demands mutual effort between the patient and the physician in constantly collecting data, monitoring, and understanding the disease. The advent of artificial intelligence has made this process easier. However, studies have rarely attempted to analyze how the different artificial intelligence based health coaching systems are used to manage different types of chronic conditions. Objective: Throughout this grounded theory literature review, we aim to provide an overview for the features that characterize artificial intelligence based health coaching systems used by patients with chronic diseases. Methods: During our search and paper selection process process, we use three bibliographic libraries (PubMed, IEEE Xplore, and ACM Digital Library). Using the grounded theory, we extract overarching themes for the artificial intelligence based health coaching systems. These systems are then classified according to their role, platform, type of interaction with the patient, as well as targeted chronic conditions. Of 869 citations retrieved, 31 unique studies are included in this review. Results: The included studies assess 14 different chronic conditions. Common roles for AI-based health coaching systems are: developing adherence, informing, motivating, reminding, preventing, building a care network, and entertaining. Health coaching systems combine the aforementioned roles to cater to the needs of the patients. The combinations of these roles differ between multilateral, unilateral, opposing bilateral, complementing bilateral, one-role-missing, and the blurred role combinations. Conclusion: Clinical solutions and research related to artificial intelligence based health coaching systems are very limited. Clear guidelines to help develop artificial intelligence-based health coaching systems are still blurred. This grounded theory literature review attempted to shed the light on the research and development requirements for an effective health coaching system intended for patients with chronic conditions. Researchers are recommended to use this review to identify the most suitable role combination for an effective health coaching system development.