Identifying outcome domains to establish a core outcome set for progressive pulmonary fibrosis: a scoping review.

Introduction: People with idiopathic pulmonary fibrosis (IPF) and other forms of progressive pulmonary fibrosis (PPF) have a high symptom burden and a poor health-related quality of life (HRQoL). Despite efforts to offer specialised treatment, clinical care for these patients remains suboptimal and several nonmedical needs remain unaddressed. Developing a core outcome set (COS) can help to identify a minimum set of agreed-upon outcomes that should be measured and acted-upon in clinical care.

Increasing Generative Artificial Intelligence Competency among Students Enrolled in Doctoral Nursing Research Coursework.

Background:  Generative artificial intelligence (AI) tools may soon be integrated into health care practice and research. Nurses in leadership roles, many of whom are doctorally prepared, will need to determine whether and how to integrate them in a safe and useful way.

Objective:  This study aimed to develop and evaluate a brief intervention to increase PhD nursing students' knowledge of appropriate applications for using generative AI tools in health care.

Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice.

The electronic health record contains valuable patient data and offers opportunities to administer and analyze patients' individual needs longitudinally. However, most information in the electronic health record is currently stored in unstructured text notations. Natural Language Processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language, can be used to delve into unstructured text data to uncover valuable insights and knowledge.

A rapid review on current and potential uses of large language models in nursing.

Background: The application of large language models across commercial and consumer contexts has grown exponentially in recent years. However, a gap exists in the literature on how large language models can support nursing practice, education, and research. This study aimed to synthesize the existing literature on current and potential uses of large language models across the nursing profession.

The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research.

More clinicians and researchers are exploring uses for large language model chatbots, such as ChatGPT, for research, dissemination, and educational purposes. Therefore, it becomes increasingly relevant to consider the full potential of this tool, including the special features that are currently available through the application programming interface. One of these features is a variable called temperature, which changes the degree to which randomness is involved in the model's generated output.

Anxiety and Depression in Adults With Congenital Heart Disease.

Background: A comprehensive understanding of adult congenital heart disease outcomes must include psychological functioning. Our multisite study offered the opportunity to explore depression and anxiety symptoms within a global sample.

Objectives: In this substudy of the APPROACH-IS (Assessment of Patterns of Patient-Reported Outcomes in Adults With Congenital Heart Disease-International Study), the authors we investigated the prevalence of elevated depression and anxiety symptoms, explored associated sociodemographic and medical factors, and examined how quality of life (QOL) and health status (HS) differ according to the degree of psychological symptoms.

Using ChatGPT and Google Bard to improve the readability of written patient information: a proof of concept.

Patient information materials often tend to be written at a reading level that is too advanced for patients. In this proof-of-concept study, we used ChatGPT and Google Bard to reduce the reading level of three selected patient information sections from scientific journals. ChatGPT successfully improved readability.

Profiles of patients referred to specialized palliative care from the cardiology department at a university hospital: an 11-year longitudinal retrospective study.

Background: Although the majority of patients with cardiovascular diseases (CVD) have a significant symptom burden and progressive course towards the end of life, only a small proportion of patients currently receive palliative care. The current referral practices to palliative care from the cardiology department need to be scrutinized. The current study aimed to examine: 1) the clinical profile; 2) time between referral to palliative care and death; and 3) place of death for CVD patients who were referred to palliative care from a cardiology department.

What if your patient switches from Dr. Google to Dr. ChatGPT? A vignette-based survey of the trustworthiness, value, and danger of ChatGPT-generated responses to health questions.

ChatGPT is a new artificial intelligence system that revolutionizes the way how information can be sought and obtained. In this study, the trustworthiness, value, and danger of ChatGPT-generated responses on four vignettes that represented virtual patient questions were evaluated by 20 experts in the domain of congenital heart disease, atrial fibrillation, heart failure, or cholesterol. Experts generally considered ChatGPT-generated responses trustworthy and valuable, with few considering them dangerous.

Mental health in adult congenital heart disease.

Mental health issues are common in individuals with congenital heart disease (CHD), stemming from various factors such as traumatic experiences, existential questions, and genetic predisposition. This article provides an overview of the literature on mental disorders and mental health in adults with CHD (ACHD) and presents new data on mental health as a predictor of quality of life (QoL). Empirical data show that disorders such as depression, anxiety, bipolar disorder, psychosis, Attention Deficit Hyperactivity Disorder (ADHD), and autism spectrum disorders occur more often in people with CHD than in healthy counterparts (Graphical abstract).

Gothenburg Empowerment Scale (GES): psychometric properties and measurement invariance in adults with congenital heart disease from Belgium, Norway and South Korea.

Background: Patient empowerment is associated with improvements in different patient-reported and clinical outcomes. However, despite being widely researched, high quality and theoretically substantiated disease-generic measures of patient empowerment are lacking. The few good instruments that are available have not reported important psychometric properties, including measurement invariance.

Last year of life of adults with congenital heart diseases: causes of death and patterns of care.

Aims: Although life expectancy in adults with congenital heart diseases (CHD) has increased dramatically over the past five decades, still a substantial number of patients dies prematurely. To gain understanding in the trajectories of dying in adults with CHD, the last year of life warrants further investigation. Therefore, our study aimed to (i) define the causes of death and (ii) describe the patterns of healthcare utilization in the last year of life of adults with CHD.

Rationale, design and methodology of APPROACH-IS II: International study of patient-reported outcomes and frailty phenotyping in adults with congenital heart disease.

Background: In recent years, patient-reported outcomes (PROs) have received increasing prominence in cardiovascular research and clinical care. An understanding of the variability and global experience of PROs in adults with congenital heart disease (CHD), however, is still lacking. Moreover, information on epidemiological characteristics and the frailty phenotype of older adults with CHD is minimal.

Illness Identity in Inflammatory Bowel Disease.

Background: We examined the degree to which adults with inflammatory bowel disease (IBD) integrated their illness into their identity and linked illness identity to important patient-reported outcomes.

Methods: A total of 109 adults with IBD, aged 18 to 60 (M = 35.93; 77% women) completed questionnaires on the four illness identity dimensions (rejection, acceptance, engulfment, and enrichment), medication adherence, depressive symptoms, life satisfaction, health status, and health-related quality of life (HRQoL).