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Nov 22-23, 2018 | Paris, France

Joint Event

Nutrition and Health

International Conference on

Diabetes and Endocrinology

Journal of Insights in Nutrition and Metabolism | Volume 2

Development of Diabetes Affective Message System (DAMS)

Mohamed Ariffin Bin Mohamed Kawaja Kamaludin

Nanyang Technological University, Singapore

Diabetes mellitus or diabetes is a major cause of death

worldwide and ranks amongst cancer and cardiovascular

diseases. Among the non-clinical intervention programs,

scholarly articles suggest that emotion-based health

messages can be a powerful driver to promote health

preservation attitudes and behaviors. The objective of this

research is to develop a set of stimuli known as the Diabetes

Affective Message System (DAMS), which is relevant for

emotion-related studies in the diabetes health context. The

two emotions explored for this study is fear and enthusiasm.

All the patients recruited for Phase 1 and Phase 2 of the study

were diagnosed with type 2 diabetes and seek treatment in a

large public hospital in Singapore. In Phase 1 of the research,

eighty stimuli were curated. Four patients with diabetes

and eight healthcare providers took part in two separate

focus group discussions to determine the appropriateness

of the stimuli curated in diabetes related studies. After

replacing the stimuli based on the patients and healthcare

providers’ inputs, four patients were recruited for a one-to-

one interview regarding the appropriateness of the stimuli.

In Phase 2, 100 patients were recruited and were asked to

rank the stimuli according to three emotion metrics, namely

valence, arousal and dominance. The metrics were derived

from a standard known as Self-Assessment-Manikin (SAM).

A better understanding of emotional-based messages for

diabetes patients may have the potential to sway patients

towards prudent behaviors in managing their condition.

Speaker Biography

Mohamed Ariffin Bin Mohamed Kawaja Kamaludin is currently a PhD student in Nanyang

Technological University (NTU) in Singapore. His area of study is on emotion-based

messages as a behavioral intervention for diabetes patient in Singapore. Prior to his PhD,

he ran a startup which curates abstracts from the US Medical Library and categorize them

based on researchers’ profile using machine learning. He has 3 publications, a patent and a

technology disclosure filed under NTU