Background/Objectives: Nurses are central to artificial intelligence (AI) implementation in healthcare, yet estimates of AI-related anxiety are difficult to compare because Artificial Intelligence Anxiety Scale (AIAS) versions have different total-score ranges. This review estimated AI anxiety using separate syntheses of range-compatible raw scores, with percent-of-maximum-possible (POMP) normalization as a secondary exploratory analysis. Methods: Following PRISMA 2020, PubMed, Scopus, CINAHL, and Google Scholar were searched from inception to 16 July 2026. Methodological quality was appraised using Joanna Briggs Institute checklists. Random-effects models used restricted maximum likelihood estimation with Hartung–Knapp inference; DerSimonian–Laird models were retained for sensitivity analysis. Prediction intervals, leave-one-out analyses, and influence diagnostics were examined. The protocol was retrospectively registered on OSF (DOI: 10.17605/OSF.IO/K3B56). Results: Twenty-five studies included 7271 nurses. The pooled mean was 45.85 (95% CI 44.45–47.26; 95% PI 41.75–49.96; I² = 80.0%) for the 16–80 AIAS (10 studies; N = 2545) and 69.28 (95% CI 62.03–76.53; 95% PI 50.58–87.97; I² = 94.4%) for the 21–147 AIAS (six studies; N = 2066). Pooled means were essentially unchanged under the alternative estimator. Extreme heterogeneity limited interpretation of the exploratory POMP synthesis. Conclusions: Mean AIAS scores were below theoretical midpoints. Raw AIAS totals from incompatible versions should not be pooled. Wide prediction intervals indicate substantial between-study variation, and the absence of validated severity cut-offs precludes clinical severity classification. Longitudinal, controlled, and psychometrically rigorous research is needed before specific anxiety-reduction interventions can be recommended.

Quality of life is shaped not only by disease, symptoms, and treatment but also by the social conditions in which adults live, work, age, and manage health. This chapter examines how social determinants of health influence quality of life through structural, material, psychosocial, behavioral, and healthcare-access pathways. It distinguishes broader social determinants from individual health-related social needs and uses a life-course perspective to explain how education, employment, housing, caregiving, financial security, social relationships, discrimination, functional ability, and access to services affect well-being from young adulthood to older age. Chronic conditions illustrate the reciprocal relationship between social disadvantage and disease, including financial toxicity, treatment burden, and disruption of family and occupational roles. The chapter also considers implications for respectful social assessment, interdisciplinary care, healthcare-system adaptation, community partnerships, and policy action. Improving quality of life across adulthood requires clinically effective care to be accompanied by sustained action on the unequal distribution of resources, opportunities, and social protection.

Objectives: To evaluate whether a multifaceted educational intervention was associated with changes in healthcare professionals’ knowledge, attitudes, self-reported practices, and catheter-associated urinary tract infection incidence in medical wards. Methods: This before-and-after intervention study was conducted in three internal medicine wards of a tertiary general hospital between September 2023 and December 2025, including a pre-intervention period (September 2023–April 2025), an intervention period (May–June 2025), and a post-intervention period (July–December 2025). The intervention included face-to-face education, interactive discussions, printed materials, posters, and ward-based reminders on evidence-based urinary catheter care. Healthcare professionals completed an anonymous structured questionnaire before and after the intervention, while catheter-associated urinary tract infection surveillance was conducted prospectively. Pre- and post-intervention questionnaire data were analyzed as independent groups. Results: We obtained questionnaire responses from 85 healthcare workers before the intervention and 78 after the intervention. The median total knowledge score increased significantly from 21 (interquartile range [IQR], 19–22) to 23 (IQR, 22–25; P < 0.001). Selected self-reported practices also improved significantly, whereas attitudes and perceptions were generally favorable at baseline and did not change significantly. The overall CAUTI rate decreased from 3.79 to 1.94 episodes per 1,000 catheter-days. After adjustment for ward, the post-intervention period was associated with a significantly lower CAUTI incidence (incidence rate ratio, 0.50; 95% confidence interval, 0.28–0.90; P = 0.020). Conclusion: The educational intervention was associated with improved knowledge, selected improvements in self-reported catheter-care practices, and lower catheter-associated urinary tract infection incidence.