The Rise of Anti-Intellectualism, Snapshot of Nursing in Gaza, Video Monitoring to Reduce Falls: December Issue Recommended Reading

The December issue of AJN is now live.

Some articles in this issue will be open access or free to access for a set period; others will require log-in or subscription. Below are some articles of note we’d like to draw your attention to.

This issue has two original research articles. The first is of these is an observational cohort study looking at implementation of a continuous video monitoring program to decrease falls in a long-term acute care hospital setting. This article is open access.

The second original research article in our December issue is “Investigating the Relationships Among Nurses’ Stress, Sleep Quality, and Mental Health, and the Mediating Role of Coping Strategies and Social Support: A Cross-Sectional Study.” According to the authors, “This study highlights strong associations between stress, sleep quality, anxiety, and depressive symptoms, with coping strategies and social support as potential mediators.”

An integrative review (currently free to read) looks at what we currently know (and don’t know but need to study) about best practices for implementing hospital-based virtual nursing.

Our editorial by editor-in-chief Carl Kirton indulges a little word play in its title, “The Rise of AI.” But […]

2025-11-20T11:34:48-05:00November 20th, 2025|digital health, Nursing, nursing research, Public health, Technology|0 Comments
Read More

Deep Research: Understanding the Limitations of the Latest Powerful AI Tool for Scholarly Authors

In February 2024, I wrote an AJN Off the Charts blog post titled “Leveraging AI and Technology for Comprehensive Research: Tips for Researchers and Students.” Since then, the field of AI has undergone rapid evolution. It is evident to all of us watching the field develop that companies hosting and developing large language models (LLMs) would eventually target scientific research. In my previous post, I explained that there is no single software solution for conducting research or literature reviews using AI. However, the deployment of new features in AI software platforms, such as deep research capabilities, may mislead us into thinking otherwise. The purpose of this blog post is to introduce the idea of deep research tools, while also providing tips for users who wish to explore these evolving tools.

What is deep research?

Image: Marcus Winkler/Unsplash

Deep research is a term used by LLM software platforms that allow users to enter a prompt to initiate an in-depth process that involves finding, analyzing, and synthesizing “hundreds of online sources to create a comprehensive report at the level of a research analysis” (OpenAI, 2025). There is also a consideration for time using this tool, as the responses are not instantaneous and result time can vary based […]

2025-11-18T09:05:01-05:00November 18th, 2025|artificial intelligence (AI), Nursing, nursing research, Technology|0 Comments
Read More

Continuous Glucose Monitoring and Time in Range: Improving Data for Diabetes Management

Nursing roles in diabetes management.

A continuous glucose monitor reader (or a smartphone app) scans the sensor attached to the patient’s body for interstitial fluid glucose level and can provide data such as average blood glucose level or percentage of time spent in a target range over a given period of time.

Knowledge is power. When a person with diabetes knows their blood glucose levels, they can better self-manage lifestyle choices and medications and be an active participant in preventing complications. Glucose information can be obtained through a variety of methods. The majority of people with known diabetes receive reports on their glucose from the health care provider who is able to do lab work to obtain fasting or random blood glucose level, hemoglobin A1c (HbA1c, or just A1c) level, and urine glucose.

Nurses play an integral role to partner with the patient about their diabetes and provide education on the meaning of glucose measurement. In the outpatient setting, nurses can help the patient adjust insulin dosages and work on glucose monitoring skills and interpretation. Inpatient, nurses oversee and utilize glucose results and help with self-management skills in anticipation of care at […]

2024-06-19T10:57:17-04:00June 19th, 2024|Diabetes, digital health, Nursing, patient engagement, Technology|1 Comment
Read More

Leveraging AI and Technology for Comprehensive Research: Tips for Researchers and Students

The research-to-practice gap.

Today’s rapidly changing health care settings require medical and nursing professionals and students to remain up to date on trending research, topics, and evidence for guiding practice. While this may sound fundamental for nurses, multiple barriers make this incredibly challenging. Factors such as limited time, large volumes of new research to sift through, and experience with reading and analyzing research contribute to what is known as the research-to-practice gap. This blog post will explore how to harness AI and technology to gain a high-level and comprehensive overview of a research topic of interest.

Define the topic.

Before leveraging AI tools, it’s critical to develop the focus of the topic of interest. It is helpful to frame or organize your topic or area of interest to ensure the search is thorough. For example, you could use the PICO format (patient/population, intervention, comparison, and outcomes) to phrase your question or area of interest.

Let’s say you want to learn more about skin damage related to external urinary devices for adult females. A good PICO question might be: Among adult females in acute care settings, what type of skin damage occurs when using external urinary devices compared to those who do not use these devices?

Search the literature.

Searching academic databases can be […]

2024-02-02T09:40:10-05:00February 1st, 2024|artificial intelligence (AI), Nursing, nursing research, Technology|0 Comments
Read More

AI and Nursing: Are We Ready?

Three considerations about nursing and AI.

Lisiane Pruinelli

In my role as a nursing professor under the University of Florida Artificial Intelligence Initiative (ai.ufhealth.org) and in leading several national and international efforts, I apply what I’ve learned in years of clinical and educational experience to articulate the implications of AI for the nursing profession.

Doing so, I see three broad considerations that will affect the profession’s future. 1) The need to take into account the history of the nursing profession and the fact we are the most trusted profession in the US, 2) The question of how we can best incorporate new technologies and/or ideas into the care we deliver every day, and 3) The issue of how we can build the new generation of nurses while also training current nurses in order that they can play a role at the forefront of the AI/health care revolution while continuing to be strong advocates for safe and ethical care.

These three considerations are elaborated below:

2024-01-25T10:10:18-05:00January 16th, 2024|artificial intelligence (AI), Nursing, Technology|1 Comment
Read More

Comment ground rules

1. Please be respectful.
2. We moderate all comments.

Content disclaimer

Views expressed on the blog are solely those of the authors or persons quoted. They do not necessarily reflect AJN’s views or those of Wolters Kluwer Health/Lippincott Williams and Wilkins.
Go to Top