Unhealthy Diet

Background: Individual brief behavior change interventions often do not sufficiently address the common co-occurrence of multiple health risk behaviors among people. In addition, many interventions often fail to reach the majority of the target population and particularly those people who need them the most. To address these core challenges of individual prevention research, the "Proactive Automatised Lifestyle intervention (PAL)" was developed, a proactive screening and brief intervention driven by psychological health behavior change theory to motivate participants for behavior change. The trial ePAL aims to investigate the efficacy of the multi-behavior change intervention adressing tobacco smoking, alcohol use, diet and physical activity among general hospital patients over 2 years; and to investigate differential efficacy in different subgroups of patients. Methods: All patients admitted to non-intensive care wards on five medical departments within the University Medicine Hospital Greifswald (internal medicine A \& B, surgery, trauma surgery, ear-nose-throat) and aged 18 to 64 years are systematically approached by study assistants and asked to first participate in a survey and then in the randomizd controlled trial, irrespective of their reason of admission. A total of 788 participants is allocated to two study groups. The intervention group receives individualized feedback on all four health risk behaviors to enhance motivation to change identified health risk behaviors. The feedback is driven by psychological behavior change theory, tailored to the participants' current stages of change and delivered after baseline and at months 1 and 3. The control group receives routine care and minimal assessment only. Follow-ups are conducted at months 6, 12 and 24 after baseline; and more are planned for. Efficacy will be measured concerning self-reported change in health risk behaviors, health and motivation to change measures using latent growth curve modelling. Discussion: The trial will provide information on the efficacy of a population-based and individually tailored brief intervention to systematically provide individualized feedback to each patient for a healthy living. When found to be effective and implemented widely, such interventions may contribute to the prevention of widespread non-communicable diseases.

This study aims to evaluate the effectiveness of an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food consumption and improve dietary sustainability among adolescents and young adults. The intervention utilizes real-time behavioral data, including image-assisted dietary logging and contextual information, to identify high-risk consumption moments and deliver personalized, non-coercive nudges. The study will assess changes in ultra-processed food intake, contextual consumption patterns, and sustainability-related dietary indicators.

This study aims to evaluate the impact of public health interventions on changes in healthy lifestyle habits over time and their subsequent effects on health outcomes. The investigators hypothesize that exposing at-risk populations to structured physical activity programs, education on healthy nutrition, promotion of the Mediterranean diet, and workshops focused on strengthening psychological resilience will lead to improvements in anthropometric, oxidative, metabolic, and psychological parameters. Anthropometric and laboratory measures will be collected at multiple time points throughout the study. The longitudinal follow-up will span 12 months. It is anticipated that sustained adherence to healthy lifestyle behaviors will result in positive lifestyle changes and enhanced health-related quality of life.