Publications by authors named "K J Kayser"

Objectives: Patients with advanced lung cancer (LC) face significant physical, psychological, and functional challenges, increasing their reliance on caregivers for practical and emotional support. This study evaluates the efficacy of CareSTEPS (Self-Care, Stress management, Symptom management, Effective communication, Problem-solving, and Social support), a 6-week telephone-delivered intervention designed to improve psychological functioning (depression and anxiety symptoms) and reduce caregiver burden among family caregivers of patients with advanced LC.

Methods: In this multisite, open-label, parallel-group randomized controlled trial, 174 caregivers (74.

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Background: We developed a high-intensity parenting intervention (HIP) to help parents support the academic success of childhood cancer survivors (CCSs), who often face post-treatment challenges affecting their school-related functioning. This randomized controlled trial (NCT03178617) evaluated HIP's efficacy compared to lower-intensity, single-session, treatment-as-usual services (LIP) in Latino families. Primary outcomes were parenting efficacy and CCSs' school functioning; secondary outcomes included parenting knowledge and measures of CCSs' academic performance, attention, and functioning outside of school.

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Unlabelled: The purpose of this project is to assess, for practicing pediatric nurses in the U.S., what is the impact of the Stewards of Children Child Sexual Abuse (CSA) program on their attitudes about reporting suspected CSA.

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Rural women face an increased risk of cervical cancer diagnosis in comparison to women living in metropolitan areas. This review synthesized and critically evaluated cervical cancer screening interventions that target women living in rural communities in the USA. EBSCO, JSTOR, Medline, PsychINFO, Psychology and Behavioral Sciences Collection, PubMed, and Cochrane Library were searched using keywords related to cervical cancer screening, rural communities, and prevention interventions.

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Background: Missingness in health care data poses significant challenges in the development and implementation of artificial intelligence (AI) and machine learning solutions. Identifying and addressing these challenges is critical to ensuring the continued growth and accuracy of these models as well as their equitable and effective use in health care settings.

Objective: This study aims to explore the challenges, opportunities, and potential solutions related to missingness in health care data for AI applications through the conduct of a digital conference and thematic analysis of conference proceedings.

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