Bridging Experience and Practice: A Grounded Theory Study of Nurses' Hospitalisation Experiences as Patients or Family Members.

Aims: This study aimed to develop a grounded theory that explains how nurses' experiences as patients or family members influence their provision of patient-centred care.

Design: A grounded theory approach.

Methods: Twenty clinical nurses in South Korea participated; nine had experiences as patients and 11 as family members during hospitalisation.

Exploring Social-Ecological Pathways From Sexual Identity to Sleep Among Chinese Women: Structural Equation Modeling Analysis.

Background: Women and sexual minority individuals have been found to be at higher risk for experiencing poor sleep health compared to their counterparts. However, research on the sleep health of sexual minority women (SMW) is lacking in China.

Objective: This study aimed to examine sleep quality and social support for Chinese women with varied sexual identities, and then investigate the in-depth relationships between sexual identity and sleep.

Prediction of reduced left ventricular ejection fraction using atrial fibrillation or flutter electrocardiograms: A machine-learning study.

Objective: Although the evaluation of left ventricular ejection fraction (LVEF) in patients with atrial fibrillation (AF) or atrial flutter (AFL) is crucial for appropriate medical management, the prediction of reduced LVEF (<50%) with AF/AFL electrocardiograms (ECGs) lacks evidence. This study aimed to investigate deep-learning approaches to predict reduced LVEF (<50%) in patients with AF/AFL ECGs and easily obtainable clinical information.

Methods: Patients with 12-lead ECGs of AF/AFL and echocardiography were divided into those with LVEF <50% and ≥50%.

Predicting branch retinal vein occlusion development using multimodal deep learning and pre-onset fundus hemisection images.

Branch retinal vein occlusion (BRVO) is a leading cause of visual impairment in working-age individuals, though predicting its occurrence from retinal vascular features alone remains challenging. We developed a deep learning model to predict BRVO based on pre-onset, metadata-matched fundus hemisection images. This retrospective cohort study included patients diagnosed with unilateral BRVO from two Korean tertiary centers (2005-2023), using hemisection fundus images from 27 BRVO-affected eyes paired with 81 unaffected hemisections (27 counter and 54 contralateral) for training.

Pace of Life Is Faster for a Bored Person: Exploring the Relationship Between Trait Boredom and Fast Life History Strategy.

Life history theory suggests that in harsh, unpredictable environments, individuals may benefit from adopting a fast life history strategy. This may involve experiencing boredom more frequently and intensely as an adaptive mechanism to seek novel stimuli, potentially increasing the number of sexual partners and offspring. This study explored the relationship between trait boredom-a chronic characteristic of feeling bored-and fast life history strategies.