Factors Influencing Preventive Health Behaviors in Middle-Aged Adults with Prediabetes: A Cross-Sectional Study

Jaruayporn Jaisit; Thanee Kaewthummanukul; Chiraporn Tachaudomdach; Nattaya Suwankruhasn

doi:10.60099/prijnr.2026.281763

Authors

Jaruayporn Jaisit PhD (Candidate), Faculty of Nursing, Chiang Mai University, Chiang Mai, Thailand. https://orcid.org/0009-0003-2650-2885
Thanee Kaewthummanukul Faculty of Nursing, Chiang Mai University, Chiang Mai, Thailand. https://orcid.org/0009-0007-9256-2359
Chiraporn Tachaudomdach aculty of Nursing, Chiang Mai University, Chiang Mai, Thailand. https://orcid.org/0000-0002-1294-280X
Nattaya Suwankruhasn Faculty of Nursing, Chiang Mai University, Chiang Mai Thailand. https://orcid.org/0009-0007-6800-9254

DOI:

https://doi.org/10.60099/prijnr.2026.281763

Keywords:

Information–Motivation–Behavioral Skills Model, Knowledge, Middle-aged adults, Prediabetes, Preventive health behaviors, Risk perception, Self-eff icacy, Subjective norms

Abstract

Prediabetes among middle-aged adults represents a significant public health concern, and engagement in preventive health behaviors is essential to reduce disease progression. However, evidence on the factors influencing preventive health behaviors among adults with prediabetes in Thailand remains limited. This descriptive, cross-sectional study aimed to test a hypothesized Causal Model of Preventive Health Behaviors in Thai Middle-Aged Adults with Prediabetes grounded in the Information-Motivation-Behavioral Skill model. A total of 325 Thai participants were recruited using a multistage sampling from nine health-promoting hospitals in one health region in Northern Thailand. Data were collected using structured questionnaires; Demographic Characteristics, Knowledge, Attitudes, Risk Perception, Subjective Norms, Preventive Behavioral Skills, Self-Efficacy, and Preventive Health Behaviors. Descriptive statistical methods and structural equation modeling were employed to analyze the data.

The findings demonstrated that the proposed model explained 40.8% of the variance in preventive health behaviors. Information, preventive behavioral skills, and self-efficacy had positive direct effects on preventive health behaviors, with preventive behavioral skills emerging as the strongest predictor. However, the unusually high coefficient should be interpreted with caution due to potential conceptual overlap between constructs. Attitude towards preventive health behaviors demonstrated a positive indirect effect on preventive health behaviors through preventive behavioral skills. Nurses can use these findings to develop innovative interventions that emphasize increasing knowledge, enhancing positive attitudes, and developing behavioral skills and self-efficacy, integrated with technology. However, such interventions should be tested before being widely used in practice.

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