Modeling consumer intentions toward probiotic-oral dissolving strips for diabetes prevention

Er Qjng Jin · Chai Nien Foo · Siok Koon Yeo

1 citations0/0 files storedJournal of Agriculture and Food Research

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Behavioral Health and Interventions Consumer Attitudes and Food Labeling Health, Technology, Consumer Behavior

Abstract

This study employed a combination of the Theory of Planned Behavior (TPB) and Health Belief Model (HBM) models to better understand consumer behavioral intention of probiotic-incorporated Oral Dissolving Strips (ODS) for diabetes prevention in Malaysia. One hundred and eighty of respondents were included in the analysis of Partial Least Squares Structural Equation Modelling (PLS-SEM) through Smart-PLS 4.0. The results revealed that the overall consumption of ODS with probiotics was 47.2%. Perceived benefits (β=0.335, p<0.001), subjective norms (β=0.303, p<0.001), perceived behavioral control (β=0.261, p<0.05) and perceived susceptibility (β=0.185, p<0.05) are the most significant factors influencing behavior intention. While attitudes (β=0.038, p=0.596) and perceived barriers (β=−0.005, p=0.941) and perceived severity (β=−0.113, p=0.149) do not significantly predict behavior intention in this model. These results suggest that targeted consumer education about the health benefits of these products could enhance adoption. This research provides valuable insights for health policymakers and industry stakeholders in promoting functional foods for diabetes prevention. • Oral dissolving strips (ODS) serve as a convenient and consumer-friendly carrier for probiotics. • Probiotic-incorporated ODS present a promising alternative for diabetes prevention. • Malaysian consumers show a moderate intention to consume probiotic-based ODS for antidiabetic purposes. • Perceived benefits significantly influence consumer purchase intentions toward probiotic ODS. • Marketing and health campaigns should focus on emphasizing the health benefits of probiotic ODS and leveraging social influence

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References

1981Evaluating Structural Equation Models with Unobservable Variables and Measurement Error 1991The theory of planned behavior 2014A new criterion for assessing discriminant validity in variance-based structural equation modeling 2018When to use and how to report the results of PLS-SEM 2021Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R 1988Social Learning Theory and the Health Belief Model 2019Assessing measurement model quality in PLS-SEM using confirmatory composite analysis 2013Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance

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