Background: The implantable cardioverter-defibrillator (ICD) is the established treatment for patients with a history of or at risk for sudden cardiac arrest. Patients receiving an ICD are diverse, and little is known regarding their preferences for support and education postimplantation. The purpose of this study was to examine race, gender, and age preferences for receiving support and education (e.g., written, verbal).

Methods: Participants (N = 108, 75% Caucasian, 74% male, age 65 +/- 11 years) completed a research team-designed survey at a regularly scheduled clinic visit with the cardiac electrophysiologist at an academic medical center or offsite clinic. Descriptive statistics, Pearson chi(2), and independent t-tests were conducted.

Results: The study demonstrates important associations between race, gender, and age with patient preferences for support and education with regard to ICD care. African Americans preferred written materials (P = 0.006) and a phone call with the cardiologist (P =0.036). Women preferred an ICD support group (P = 0.023), a phone call with the device nurse (P = 0.027), and a professional counselor (P = 0.049). Women's choice to receive education from their cardiologist approached significance (P = 0.055). Patients < or =67 years of age preferred to receive support via an Internet chat room with other ICD patients (P =0.036), and to receive education via an Internet Web site (P = 0.022).

Conclusions: Findings suggest methods of providing better care to ICD patients by offering them support and educational materials in their preferred modality. These data can aid in optimizing clinical care. Incorporating assessments of individual preferences into future clinical trial design is desirable.

Download full-text PDF

Source
http://dx.doi.org/10.1111/j.1540-8159.2008.02248.xDOI Listing

Publication Analysis

Top Keywords

support education
16
preferences receiving
8
receiving support
8
preferences support
8
race gender
8
gender age
8
phone call
8
receive education
8
icd patients
8
support
7

Similar Publications

The feasibility of using machine learning to predict COVID-19 cases.

Int J Med Inform

January 2025

School of Geography and the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY, United Kingdom. Electronic address:

Background: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported epidemic data, particularly in underdeveloped regions with limited access to COVID-19 test kits and healthcare infrastructure. In the post-COVID era, this issue remains crucial.

View Article and Find Full Text PDF

Clinical Relevance: Interprofessional education and collaborative working are known to improve patient outcomes. The evidence to support this approach in optometry is lacking.

Background: There is no published evidence into the effectiveness of interprofessional education for pharmacy and optometry students.

View Article and Find Full Text PDF

Background And Objectives: Chronic kidney disease (CKD) is a major public health concern that uniquely impacts older Black Americans, a population also likely to have family members also diagnosed with CKD. This study aimed to (1) describe how participants viewed their decision preferences considering the experiences of family, and friends previously diagnosed with CKD, and (2) to understand how these social complexities informed their own decisions for future CKD care.

Research Design And Methods: Utilizing a phenomenologically-informed approach, this study explored participants' perceptions of how patients and their family members' experiences with CKD influenced treatment-related decision-making.

View Article and Find Full Text PDF

Comparing answers of ChatGPT and Google Gemini to common questions on benign anal conditions.

Tech Coloproctol

January 2025

Ellen Leifer Shulman and Steven Shulman Digestive Disease Center, Cleveland Clinic Florida, 2950 Cleveland Clinic Blvd, Weston, FL, USA.

Introduction: Chatbots have been increasingly used as a source of patient education. This study aimed to compare the answers of ChatGPT-4 and Google Gemini to common questions on benign anal conditions in terms of appropriateness, comprehensiveness, and language level.

Methods: Each chatbot was asked a set of 30 questions on hemorrhoidal disease, anal fissures, and anal fistulas.

View Article and Find Full Text PDF

Adaptive immune resistance in cancer describes the various mechanisms by which tumors adapt to evade anti-tumor immune responses. IFN-γ induction of programmed death-ligand 1 (PD-L1) was the first defined and validated adaptive immune resistance mechanism. The endoplasmic reticulum (ER) is central to adaptive immune resistance as immune modulatory secreted and integral membrane proteins are dependent on ER.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!