Xinjun Jiang

Background: Nutrition literacy is important for dietary self-management among patients receiving peritoneal dialysis (PD), yet the heterogeneity of nutrition literacy and its associations with dietary adherence and nutritional and metabolic indicators remain poorly understood. Aims: To identify latent nutrition literacy profiles among patients receiving PD, examine factors associated with profile membership, and explore differences in dietary adherence and nutritional and metabolic indicators across profiles. Methods: A multicenter cross-sectional study was conducted among 307 patients receiving PD from three tertiary hospitals in Hainan Province, China, between May and December 2025. Data were collected using a demographic questionnaire, the Nutrition Literacy Scale for Patients with End-Stage Kidney Disease Undergoing Dialysis, and the Renal Adherence Attitudes Questionnaire and the Renal Adherence Behaviour Questionnaire. Nutritional and metabolic indicators were extracted from electronic medical records. Latent profile analysis was performed using Mplus 8.3, and group comparisons and multinomial logistic regression analyses were conducted using SPSS 27.0. Results: The mean nutrition literacy score was 14.10 ± 5.01. Three nutrition literacy profiles representing relatively low (46.5%), moderate (30.0%), and high (23.5%) levels were identified. Compared with the low profile, female sex and higher monthly personal income were associated with the moderate profile, while female sex, younger age, higher educational attainment, higher income, and longer dialysis duration were associated with the high profile (all p < 0.05). Differences across profiles remained statistically significant after false discovery rate correction for dietary adherence behavior and attitude scores and for several nutritional and metabolic indicators, including hemoglobin, serum albumin, lipid profiles, body mass index, and electrolyte levels (all adjusted p < 0.05). Conclusion: Nutrition literacy among patients receiving PD was heterogeneous, with three profiles differing in sociodemographic and disease-related characteristics, dietary adherence scores, and several nutritional and metabolic indicators. These profiles may provide a descriptive framework for recognizing subgroups with different nutrition support needs; however, their clinical utility requires external and longitudinal validation.

Background: Digital interventions offer scalable alternatives to traditional face-to-face diabetes education, but often face challenges related to inconsistent clinical effectiveness, and declining user engagement. However, whether a digital structured education program integrated with behavioral nudge tools can improve metabolic, behavioral, and psychological outcomes in adults with type 2 diabetes remains unclear. Objective: This study aimed to evaluate the effectiveness of a digital structured education program integrated with behavioral nudge tools in improving metabolic, behavioral, and psychological outcomes among adults with type 2 diabetes. Methods: This multicenter randomized controlled trial was conducted in the endocrinology departments of 4 hospitals in China. Adults with type 2 diabetes were randomly assigned to an intervention group receiving a digital structured education program integrated with behavioral nudge tools (n=146) or a control group receiving standard digital diabetes education (n=147). Assessments were conducted at baseline and 12-week follow-up. The primary outcome was hemoglobin A _1c (HbA _1c ) at 12 weeks, adjusted for baseline HbA _1c , and study center. Secondary outcomes included fasting blood glucose (FBG), weight, BMI, waist circumference, blood pressure, lipid profiles, self-management behaviors, self-efficacy, and habit strength. Results: Among 293 participants (mean age 49.19, SD 10.02 y), 287 (97.9%) completed follow-up. At 12 weeks, the intervention group demonstrated significantly greater improvements than the control group in HbA _1c (adjusted mean difference −0.38%, 95% CI −0.68% to −0.09%; P= .01), FBG (adjusted mean difference −0.75, 95% CI −1.27 to −0.44 mmol/L; P <.001), weight (adjusted mean difference −0.84, 95% CI −1.61 to −0.07 kg; P= .03), BMI (adjusted mean difference −0.38, 95% CI −0.65 to −0.11 kg/m²; P= .01), systolic blood pressure (adjusted mean difference −2.71, 95% CI −4.62 to −0.79 mm Hg; P= .01), diastolic blood pressure (adjusted mean difference −2.92, 95% CI −4.47 to −1.37 mm Hg; P <.001), and total cholesterol (adjusted mean difference −0.27, 95% CI −0.48 to −0.05 mmol/L; P= .02). The intervention was also associated with significantly greater improvements in self-management behaviors, self-efficacy, and habit strength (all P <.05). Conclusions: Digital structured education integrated with behavioral nudge tools improved metabolic outcomes and strengthened psychological and behavioral determinants of self-management among adults with type 2 diabetes over a 12-week period. These findings suggest that a digital structured education program integrated with behavioral nudge tools may enhance diabetes self-management beyond standard digital diabetes education. Further studies with longer follow-up and real-world implementation are warranted to evaluate the sustainability, generalizability, and long-term clinical impact of this integrated intervention.

Background: While individual behavior is governed by both conscious control and unconscious automatic processes, the extent to which habit strength influences the relationship between self-efficacy and self-management behaviors in type 2 diabetes mellitus (T2DM) remains insufficiently quantified. Aims: To examine the associations among habit strength, self-efficacy, and diabetes self-management behaviors, and to explore whether habit strength may help explain the association between self-efficacy and diabetes self-management behaviors among patients with T2DM. Methods: This was a multicenter, cross-sectional study. A total of 292 patients with T2DM were recruited from four hospitals in Hainan Province, China. Self-efficacy, habit strength, and self-management behaviors were assessed using validated questionnaires. Associations among variables were examined using correlation. Path analysis was conducted using SPSS with the PROCESS macro to explore whether habit strength may explain the association between self-efficacy and self-management behaviors. Results: Patients demonstrated moderate levels of diabetes self-management behaviors (mean = 34.15 ± 13.51). Self-efficacy was positively associated with both habit strength and self-management behaviors, and habit strength was also positively associated with self-management behaviors. Path analysis suggested that habit strength may partially explain the association between self-efficacy and self-management behaviors, accounting for 18.6% of the total effect. Conclusion: Habit strength is associated with diabetes self-management behaviors and may partially explains the relationship between self-efficacy to behavioral performance in individuals with T2DM. Interventions that support habit formation may facilitate the application of patients’ self-efficacy to sustained self-management behaviors. Incorporating strategies that reduce cognitive burden and promote automatic behavioral engagement may enhance the effectiveness of diabetes self-management support.

Dietary modification is central to chronic disease management, but conventional education-based approaches often require sustained self-regulation, which is challenging for populations with limited health literacy. Portion-control plates are an environmentally friendly tool that uses visual segmentation to guide portion selection. However, quantitative evidence on their metabolic benefits and whether these effects persist remains limited. This systematic review and meta-analysis aimed to evaluate the metabolic effects of portion-control plate interventions in adults with chronic diseases and to examine whether these effects vary across follow-up durations. PubMed, Web of Science, Scopus, Embase, Cochrane library, CKNI, VIP, Wanfang were searched from January 1999 to July 2025. Data were pooled to calculate mean differences and 95% confidence intervals using a random or fixed effect model. To assess temporal dynamics, analyses were stratified by follow-up duration (≤ 3 months, 3-6 months, and 6-12 months). Fourteen RCTs involving 1,762 participants were included. Body weight showed early reduction at 3 months (MD = -3.68 kg, 95% CI -7.78 to -0.42 ), attenuating by 6 months (MD = -1.77 kg, 95% CI - 4.46 to 0.92). Hemoglobin A1c remained relatively stable across time points (-1.08%, -0.72%, and -1.10% at 3, 6, and 12 months; overall MD = -0.82%). Fasting glucose improved progressively from 6 to 12 months (P = 0.02 for subgroup difference). Low-density lipoprotein reductions were sustained at 6 and 12 months, while diastolic blood pressure improved only at 12 months (MD = -2.72 mmHg). Evidence certainty was highest for 12-month HbA1c and lipid outcomes. Portion-control plate interventions produce modest metabolic improvements with distinct time-dependent patterns, including early weight reduction, sustained glycaemic and lipid benefits, and delayed vascular effects. As a low-burden environmental strategy that can be easily delivered by public health practitioners and primary care providers, visually guided portion control may represent a scalable dietary intervention for chronic disease management. The review was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD420251061435).

The utilization of digital health technologies (DHT) among nurses remains notably low, primarily due to limited digital health literacy (DHL). Enhancing DH

Aims: This study aims to develop and initially test an autonomous artificial intelligence (AI) agent to support nurse-led delirium screening and guideline-concordant prevention and management. Methods and results: We constructed a delirium-specific knowledge graph from publicly available clinical guidelines and implemented an autonomous AI agent that integrates retrieval-augmented generation with validated delirium assessment tools to simulate decision support in nursing workflows. In this proof-of-concept evaluation, the agent was benchmarked on 20 clinical patient cases to assess (i) tool selection accuracy, (ii) fidelity of clinical conclusions, and (iii) adherence to guideline-based delirium care recommendations. Human experts review rated coherence, relevance, and clinical interpretability of the outputs. The 20 cases were drawn from post-operative care (n = 6), cardiac intensive care unit care (n = 5), and cancer wards (n = 9), including 6 males (30%) and 14 females (70%), with a mean age of 56.5 years (SD 17.9; range 21–82). Two experienced registered nurses independently validated the agent’s outputs, benchmarked them against guideline-based recommendations. The agent achieved 100% accuracy in selecting appropriate tools and 90% overall accuracy in generating conclusions and care recommendations, compared with 45% for other large language model baselines. Recommendations were presented in a structured, actionable format and aligned with guideline-based delirium care. Conclusion: This proof-of-concept study suggests that an autonomous AI agent can deliver clinically interpretable, guideline-aligned delirium decision support and may help reduce missed or delayed recognition while standardizing nursing actions. Given the high delirium burden in cardiovascular pathways (e.g. cardiac intensive care units and post-operative care), prospective validation in cardiovascular settings is warranted to evaluate clinical impact, safety, and workflow integration.

This study investigated the association between heatwave exposure and the risk of new-onset diabetes among middle-aged and older adults, and further assess

Traditional interventions are largely offline, lack continuous support, and primarily focus on improving knowledge. This study aimed to explore the feasibility, acceptability, and preliminary effects of a phased online support program for patients with diabetes. A mixed-methods design with convenience sampling was adopted in this study. A total of 27 patients with diabetes were recruited from a tertiary hospital in Hainan Province. The patients underwent a phased online support program. Feasibility was assessed based on recruitment, participation, and retention rates. After the patients received the intervention at the 9-month follow-up, acceptability was assessed using one-on-one semi-structured interviews. The preliminary effects of the program were assessed by observing changes in clinical and psychosocial indicators. A designated researcher collected all the data from January 2022 to March 2023. The recruitment, participation, and retention rates were all over 80%. Participants perceived positive changes after participating in the program; they considered the program to be highly acceptable and expressed eagerness for ongoing support. Significant improvements were observed in HbA1c, fasting blood glucose, blood pressure, blood lipid profile, weight, body mass index, self-efficacy, diabetes distress, diabetes knowledge, self-management behavior, and chronic disease resource utilization at the 12-month follow-up. The phased online support program for patients with diabetes is feasible and acceptable, with promising preliminary results.The study was registered in the Chinese Clinical Trial Registry (ChiCTR2400082136, http//www.chictr.org.cn/, 21/3/2024).