Evidence map›Paper›PMID 40890794›Full record

ArticleBMC nursing2025

Austrian nurses' positive opinions on geriatric care and their ideas for tackling challenges in caring for the ageing population- a modified focus group study in long-term care.

Lena Maria Lampersberger, Eva Pichler, Christa Lohrmann, Franziska Großschädl

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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Lena Maria LampersbergerInstitute of Nursing Science, Medical University of Graz, Graz, Austria. l.lampersberger@medunigraz.at.
Eva PichlerInstitute of Nursing Science, Medical University of Graz, Graz, Austria.
Christa LohrmannInstitute of Nursing Science, Medical University of Graz, Graz, Austria.
Franziska GroßschädlInstitute of Nursing Science, Medical University of Graz, Graz, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs the demand for long-term care increases due to an ageing population, ensuring continuous and high-quality geriatric nursing is crucial. However, geriatric nursing faces challenges such as workforce shortages, high workload, and high emotional demand, which can impact quality of care, job satisfaction, and career change. Little is known about nurses’ opinions on geriatric nursing and their ideas for addressing challenges in caring for the ageing population. This study aims to explore what nurses in Austria value about working in geriatric nursing and their ideas about addressing challenges in geriatric nursing.

methodsA descriptive qualitative study was conducted using a modified focus group approach that included freelisting interviews and the nominal group technique. The two used sampling methods (i.e., convenience and snowball sampling) generated a convenience sample of 12 participants. Two focus group workshops were held in 2025 with nurses working in long-term care in Austria. The freelisting data were analysed using salience analysis. The ranked ideas generated in the nominal group technique were analysed using Van Breda’s method of ranking.

resultsNurses valued the appreciation they received from colleagues and older persons they care for, the opportunity to work with the family and relatives of older persons, and their ability to provide individualised and person-centred care. A skilled geriatric nurse was described as possessing empathy, sensitivity, and broad expertise in health care. The three highest-ranked ideas for strengthening geriatric nursing were (1) Promoting/strengthening older persons’ self-care abilities (e.g., providing holistic, individualised care), (2) Coordinating care between services for the older persons, and (3) Promoting/strengthening the team.

conclusionsThese explorative findings suggest that strengthening geriatric nursing requires structural attention to improvements such as reducing bureaucracy, enhanced collaboration across healthcare sectors with the assistance of community nurses, and recognition of nurses’ competencies using a skill- and grade-mix. Implementing a supportive work environment (e.g., adequate equipment/staff/time), optimising skill- and grade-mix approaches, and listening to nurses’ expert insights may contribute to sustainable and high-quality long-term care for the ageing population. Future research should consider a co-research design to plan and introduce target group-specific interventions in geriatric nursing based on nurses’ suggestions. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Ageing populationFreelisting interviewsGeriatric nursingLong-term careNominal group technique

Identifiers

PMID40890794
PMCPMC12400631

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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.