Addressing nurse well‐being through psychological resilience: A commentary on latent profile analysis and its implications DOI

Li‐Yen Chiu,

Lien‐Chung Wei

Research in Nursing & Health, Год журнала: 2024, Номер 47(4), С. 476 - 477

Опубликована: Июнь 23, 2024

Язык: Английский

The more resilient students are, the sooner they recover from examination stress: A daily diary study DOI
Xin Yu,

Jiaxu Zhao,

Ningzhe Zhu

и другие.

Applied Psychology Health and Well-Being, Год журнала: 2025, Номер 17(2)

Опубликована: Апрель 10, 2025

Abstract Resilience, particularly under stressful circumstances, is essential for well‐being. Prior research has shown the positive effects of resilience on overall self‐esteem and emotional balance, but dynamic nature these attributes consistently been overlooked. This study investigated how influences state balance during periods examination stress. To this end, we utilized a 13‐day daily diary design to collect data once day from 212 participants (160 females; Mage = 18.30; SDage 1.03). A multilevel linear model was constructed using Hierarchical Linear Modeling (HLM) examine situations. Our findings revealed that predicted higher levels both confirming previous studies. Notably, students with demonstrated quicker recovery in areas, underscoring resilience's role sustaining contributes expanding literature by highlighting its value maintaining stability.

Язык: Английский

Процитировано

0

Population Characteristics and Influencing Factors of Clinical Nurses’ Informatics Competency: A Latent Profile Analysis DOI

X Y Chen,

Li Zhu,

Shuping Gong

и другие.

Western Journal of Nursing Research, Год журнала: 2025, Номер unknown

Опубликована: Апрель 24, 2025

Background: Nursing informatics competency is crucial for reducing information system usage time and nursing errors, as well ensuring patient safety service quality. However, current research often overlooks individual differences, focusing on overall levels associations between different factors the sample. Objective: This study aimed to identify distinct latent profiles of clinical nurses’ analyze population characteristics influencing provide theoretical basis improving competency. Methods: used a general demographic questionnaire Informatics Competency Scale investigate 733 nurses from different-level hospitals in Chinese city. The were explored by profile analysis, univariate binary logistic regression analyses. Results: Nurses classified into 2 profiles: “high profile” (58.7%) “low (41.3%). Low predominantly technical secondary school nurses, working at primary hospitals, contract employment, with monthly income ≤¥3000 (approximately US$412). Salary satisfaction, career department, education level significantly influenced ( P < .05). Conclusions: highlights higher salary levels, department informatization more likely exhibit These findings foundation targeted interventions improve

Язык: Английский

Процитировано

0

Addressing nurse well‐being through psychological resilience: A commentary on latent profile analysis and its implications DOI

Li‐Yen Chiu,

Lien‐Chung Wei

Research in Nursing & Health, Год журнала: 2024, Номер 47(4), С. 476 - 477

Опубликована: Июнь 23, 2024

Язык: Английский

Процитировано

0