ArticleJournal of the American Geriatrics Society2025
"We Didn't Ask to Be Sick:" Equipping Residents and Care Partners for Transitions From Long-Term Care to Hospital.
Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07153341 (A Pre-Post Trial Evaluating the Supporting Transitions and Empowering Preferences), which is not on this map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Pre-Post Trial Evaluating the Supporting Transitions and Empowering Preferences (STEP) Decision Support Intervention for Long-Term Care Residents Facing Hospital Transfer Decisions During Acute Health Crises
Who cites it
3 citing papers in PubMed.
- Nurses' perspectives on the effectiveness of mobile X-ray services in RACFs. a qualitative study.BMC nursing · 2026Article
- "We Didn't Ask to Be Sick:" Equipping Residents and Care Partners for Transitions From Long-Term Care to Hospital.Journal of the American Geriatrics Society · 2025Article
- Safe Enough to Thrive: A Dignity of Risk Framework for Older Adult Mental Health Care.Sage open agingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundPatient-centered care is fundamental to high-quality healthcare, emphasizing respect for individual needs and preferences. In long-term care (LTC), this approach, known as resident-centered care, necessitates accommodating diverse levels of resident autonomy, particularly for those with cognitive impairments. Transitioning from LTC to hospital settings presents significant challenges, as it can disrupt continuity of care and heighten stress for residents, care partners, and staff. To address these challenges, decision-making should be thoughtful and planned rather than rushed or based on emotions during crises.
methodsFollowing semi-structured needs assessment interviews with 28 participants from three LTC homes in Ontario, Canada, we organized focus groups with a subset of residents and care partners. These focus groups were conducted to gather insights and preferences for developing a decision-making tool tailored to LTC-to-hospital transitions. Using a framework designed to assess decisional needs and enhance decision outcomes, the focus groups explored participants' priorities and generated recommendations for the creation of a tool to test and evaluate in their LTC home.
resultsParticipants proposed three tools to improve LTC-to-hospital transitions: (1) a decision-aid flowchart to guide users through questions, record details, and provide care options and contact information; (2) a hospitalization chapter in the LTC home's admission handbook with guidance, checklists, and cost breakdowns; and (3) a lanyard with a dual-sided card and QR code linking to an electronic platform containing important resident information and contact details.
conclusionsThe study identified critical decisional needs and proposed tools that can address both preparation and decision-making aspects for hospital transitions from LTC. Co-designing these tools with residents and care partners ensures their alignment with user needs, enhancing resident-centered care during critical transitions. The implementation of these tools could significantly improve the transition experience, ensuring continuity of resident-centered care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.