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https://ptsldigital.ukm.my/jspui/handle/123456789/519928Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Nik Shanita Safii, Assoc. Prof. Dr. | - |
| dc.contributor.author | Norashikin Mustafa (P95560) | - |
| dc.date.accessioned | 2023-10-17T09:31:01Z | - |
| dc.date.available | 2023-10-17T09:31:01Z | - |
| dc.date.issued | 2022-03-08 | - |
| dc.identifier.other | ukmvital:130299 | - |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/519928 | - |
| dc.description | Poor adherence to nutrition recommendation may compromise athlete's and active individual's health and sports performance. Individualised meal planning is a comprehensive approach to achieve nutrition needs. However, sports dietitians or nutritionists (SD/N) are facing time constraints to provide a meal plan for athletes using conventional counselling methods. The existing technology such as sports nutrition mobile apps have limited resources of the Malaysian food database, which frequently provides inappropriate nutrition recommendations, making it difficult for athletes and active individuals to apply them. Thus, this study proposed a meal planner expert system using an inference engine approach to recommend meal plans for Malaysian athletes and active individuals which tally with their sports nutrition requirement and food preferences. The expert system aims to mimic the way SD/N develop a meal plan to achieve dietary requirements. The design and development research (DDR) approach was applied, comprising of four phases. In phase I, the need assessment using validated questionnaire indicated that most SD/N (n= 24) perceived digital health technology usage is important in sports nutrition services. Next, in phase II(A), based on the sevenday dietary history among athletes (n=187 adult and n=174 adolescent athletes) and active individuals (n=77), 1189 food items that regularly consumed by them were identified and added into the food database. The food data model specified each food items based on its characteristics which include their nutrient values, portion size or household measurements, food groups, food exchange groups, and mealtime. The knowledge acquisition through in-dept interview in phase II (B) model the workflow of meal planning activities by SD/N(n=5). The food database and workflow were used as a reference in designing the architecture of the iDietScoreTM system which is comprises of three components. Phase III involved the development of one of the components, the web-based application that usable to compile the meal plan database from SD/N. Meanwhile phase IV comprised the development of the following components: (1) an inference engine in the expert system that recommends a meal plan that is compatible with the user's energy requirements, training schedule, and dietary preferences, as well as inferring a different food option if the user was dissatisfied with a specific food item in the provided meal plan; and (2) the mobile application for user interface interaction. All SD/N experts agreed on the relevance of the rules used in the inference engine (n=8, CVI= 1.00, k= 0.871-1.00). The formative usability evaluation by target users (n=15) and experts (n=8) generated essential information to iteratively refine the content, functionality, food database, and user interface of the mobile app. As a result, the summative evaluation of the iDietScoreTM mobile app demonstrated a good total usability score (5.3/7.0) using M-MAUQ, suggesting that the participants (n=121) somewhat agreed that the features and functions were easy to use (5.5/7.0), satisfied (5.6/7.0), and useful (5.7/7.0). Seventy-two percent of participants approved the meal plans recommended by the expert system. Overall, the newly developed iDietScoreTM is a valid and usable system to recommend Malaysian athletes and active individuals with personalised meal plan tailored to their sports nutrition needs and food preferences. Hence, the iDietScoreTM system is a potential tool to guide users in meeting their dietary requirements through individualised meal planning. Future research should identify the effectiveness of the iDietScoreTM meal planner expert system in achieving optimal sports nutrition requirements,Ijazah Doktor Falsafah | - |
| dc.language.iso | eng | - |
| dc.publisher | UKM, Kuala Lumpur | - |
| dc.relation | Faculty of Health Sciences / Fakulti Sains Kesihatan | - |
| dc.rights | UKM | - |
| dc.subject | Athletes | - |
| dc.subject | Feeding Behavior | - |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations | - |
| dc.subject | Dissertations, Academic -- Malaysia | - |
| dc.title | iDietScoreTM: development, validation and evaluation of meal planner expert system for Malaysian athletes and active individuals | - |
| dc.type | Theses | - |
| dc.description.notes | e-thesis | - |
| dc.format.pages | 418 | - |
| Appears in Collections: | Faculty of Health Sciences / Fakulti Sains Kesihatan | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_130299+Source01+Source010.PDF Restricted Access | 7.34 MB | Adobe PDF |  View/Open |
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