Dietary fiber (DF) is one type of carbohydrate that cannot be digested by the gastrointestinal tract. It is widely recognized as an essential ingredient for health due to its remarkable prebiotic properties. Studies have shown that DF is important in the management of metabolic diseases, such as obesity and diabetes, by regulating the balance of gut microbiota and slowing down the absorption of glucose. It is worth noting that patients with metabolic diseases might suffer from intestinal dysfunction (such as constipation), which is triggered by factors such as the disease itself or medication. This increases the complexity of chronic disease treatment. Although medications are the most common treatment for chronic disease, long-term use might increase the financial and psychological burden. DF as a prebiotic has received significant attention not only in the therapy for constipation but also as an adjunctive treatment in metabolic disease. This review focuses on the application of DF in modulating metabolic diseases with special attention on the effect of DF on intestinal dysfunction. Furthermore, the molecular mechanisms through which DF alleviates intestinal disorders are discussed, including modulating the secretion of gastrointestinal neurotransmitters and hormones, the expression of aquaporins, and the production of short-chain fatty acids.

This study aimed to explore the influence of self-control and learning engagement on the positive employment cognitive appraisal and employment anxiety of college students. A questionnaire survey was conducted among a random sample of 1910 college students using the Positive Employment Cognitive Appraisal Scale for College Students, the Diagnostic Scale for Employment Anxiety of College Graduates, the Learning Engagement Scale, and the Self-Control Scale. (1) Positive cognitive appraisal of employment was found to have a significant positive correlation with both self-control and learning engagement, while demonstrating a negative correlation with employment anxiety. Similarly, self-control exhibited a positive correlation with learning engagement and a negative correlation with employment anxiety. Furthermore, learning engagement was also negatively correlated with employment anxiety. (2) Positive employment cognitive appraisal had a significant negative predictive effect on employment anxiety; self-control and learning engagement were found to play a chain mediating role in the relationship between positive employment appraisal and employment anxiety. (3) There was a masking effect on the relevant paths of learning engagement. This study highlights the importance of enhancing both self-control and continuous learning commitment to boost employment confidence. However, it is important to recognize the limitations of single-pathway explanations, and to incorporate a broader array of environmental and systemic factors in comprehensive interventions. To address employment anxiety, it is essential to start with cognitive restructuring, while concurrently enhancing self-management and learning engagement capabilities. Additionally, attention should be paid to potential environmental variables to avoid one-sidedness in mechanism explanations.

Background/Objectives: Dietary microstructure affects energy intake. Traditional Universal Eating Monitors (UEMs) offer accuracy but are limited for monitoring diverse diets. We developed the ‘Feeding Table’, a novel UEM that simultaneously tracks intake of up to 12 foods, enabling high-resolution monitoring of eating microstructure for multiple foods simultaneously. Methods: Forty-nine healthy volunteers participated: 15 (10 male, 8 female) in a location preference experiment and 31 (15 male, 16 female) in a standard meal test. The location preference study involved four weekly sessions. Participants received a standardized breakfast based on individual energy needs; lunch intake was measured 3 h later with food items in pseudo-randomized positions. The standard meal test occurred over two consecutive days to assess the Feeding Table’s performance in monitoring eating behavior under standardized conditions. Results: In two consecutive days of standard meal tests, the Feeding Table showed reasonable day-to-day repeatability for energy and macronutrient intake (energy: r = 0.82; fat: r = 0.86; carbohydrate: r = 0.86; protein: r = 0.58). Among the four repeated intake measurements, the results demonstrated high intra-class correlation coefficients (ICCs: energy 0.94, protein 0.90, fat 0.90, and carbohydrate 0.93). No significant positional bias was observed (energy: p = 0.07; macronutrients: p = 0.70). Conclusions: The Feeding Table maintains UEM accuracy while enabling multi-food, real-time monitoring of dietary microstructure and food choice, offering enhanced precision for studying eating behaviors.