Development of a Personalized Dietetic Behavior Change Framework for Chronic Disease Management

Thesis Abstract

Chronic non-communicable diseases driven by inadequate dietary management pose persistent challenges for effective long-term care, with existing one-size-fits-all dietary interventions yielding limited adherence and suboptimal health outcomes. This study develops and empirically evaluates a Personalized Dietetic Behavior Change Framework (P-DCBF) designed to enhance dietary adherence and clinical outcomes for adults with at least one chronic disease (type 2 diabetes, cardiovascular disease, or obesity-related conditions). The specific objectives are (1) to synthesize nutrition behavior theories into an integrated framework that accommodates individual dietary preferences, health literacy, cultural context, and psychosocial determinants; (2) to identify baseline predictors of diet adherence and intermediate health markers across diverse patient subgroups; (3) to design a digital decision-support tool and dietetic protocol that operationalize personalized goals, feedback, and motivational strategies grounded in Self-Determination Theory and the Health Belief Model; (4) to pilot and validate the framework in clinical nutrition settings and (5) to assess feasibility, acceptability, and potential impact on clinical outcomes. A mixed-methods, multi-site study employs a sequential explanatory design. In the quantitative phase, a prospective cohort of 420 adults with chronic disease across three urban healthcare centers is followed for 12 months. Adherence to prescribed dietary plans is measured via a validated Food Adherence Scale, 24-hour dietary recalls, and objective biomarkers (HbA1c for diabetes, LDL-C, and blood pressure) at baseline, 6 months, and 12 months. Predictors include demographic variables, health literacy (Newest Vital Sign), motivation (Treatment Self-Regulation Questionnaire), perceived barriers (the Illness Perception Questionnaire), and personality traits (Big Five Inventory). Data are analyzed using hierarchical multiple regression to determine incremental variance explained by psychosocial factors beyond sociodemographic covariates, and growth curve modeling to examine trajectories of adherence and biomarkers. In parallel, qualitative interviews (n=40) with a purposive subsample explore experiences with the P-DCBF, perceived facilitators and barriers, and cultural adaptions, analyzed thematically via reflexive thematic analysis to extract core dimensions of personalization and acceptability. The qualitative phase informs refinement of the framework and the digital tool. The methodological framework integrates Self-Determination Theory to emphasize autonomy, competence, and relatedness, and the Health Belief Model to address perceived severity, susceptibility, benefits, and barriers, culminating in a holistic P-DCBF model. The analytic plan includes regression-based mediation analyses to test whether motivation mediates the relationship between perceived barriers and adherence, and whether biomarker changes are mediated by adherence. The study also assesses the reliability and validity of the digital decision-support tool through usability testing (System Usability Scale) and content validity indices, with an initial Cronbach’s alpha target of ?0.80 for multi-item scales. Ethical considerations include informed consent, data anonymization, and adherence to data protection regulations, with ethical approvals obtained from institutional review boards at all participating centers. Expected findings indicate that personalization amplifies dietary adherence and yields clinically meaningful improvements in HbA1c, LDL-C, and systolic blood pressure, particularly among subgroups with higher health literacy and intrinsic motivation. It is anticipated that the integrated framework will outperform standard care in predicting adherence and that the digital tool will demonstrate high usability and acceptability among patients and clinicians. The study contributes to knowledge by offering a theoretically grounded, empirically validated model for personalized dietetic behavior change in chronic disease management, bridging nutrition science with behavioral psychology and health informatics. It provides practical implications for dietitians through a scalable protocol and a decision-support platform that tailor dietary recommendations to individual preferences, psychosocial contexts, and cultural backgrounds, thereby enhancing adherence and health outcomes. The final conclusion posits that a personalized, theory-driven framework substantially improves dietary behavior change and clinical indicators compared with conventional approaches. Recommendations include integrating the P-DCBF into routine nutrition care, investing in clinician training on personalized counseling and digital tools, and conducting a multi-country randomized trial to evaluate generalizability across diverse populations.