Evidence map›Paper›PMID 41422528›Full record

ArticleNursing open2025

Clinical Nurses' Perceptions of Digital Nursing Technology: A Qualitative Analysis Using the Theory of Planned Behaviour (TPB).

Young-Eun Jang, Hwa-Mi Yang

Abstract read
In one paragraph

Article in Nursing open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Young-Eun JangDepartment of Nursing, Sahmyook Health University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-5171-4906
Hwa-Mi YangDepartment of Nursing, Daejin University, Gyeonggi-do, Pocheon-si, Republic of Korea.ORCID https://orcid.org/0000-0002-8116-2188

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study explored factors influencing clinical nurses' adoption of digital nursing technologies (DNT) and examined their perceptions and behavioural intentions using the Theory of Planned Behaviour (TPB).

designA qualitative content analysis was conducted, guided by the TPB framework.

methodsIn depth interviews were conducted with 21 clinical nurses between March and April 2023. Data were analysed using qualitative content analysis to identify themes related to DNT perceptions and experiences.

resultsSeven main themes and 23 subthemes emerged. Nurses recognised benefits such as reduced workload, improved accuracy, enhanced efficiency, and expanded nursing services. Challenges included learning difficulties, limited perceived usefulness, data security concerns, and technical errors. Facilitators of adoption included supportive colleagues, role models, structured training, user-friendly technologies, adequate resources, positive prior experiences, and patient-centered design, while cultural resistance, lack of managerial support, and unclear regulatory guidance impeded use.

conclusionEffective adoption of DNT requires targeted educational programs to enhance nurses' digital competencies, user-friendly technology interfaces, and clear institutional policies. Addressing both individual and organisational factors is critical for safe and sustainable integration of digital technologies into nursing practice. REPORTING

methodThis study adhered to the consolidated criteria for reporting qualitative research (COREQ) guidelines. PATIENT OR PUBLIC CONTRIBUTION: No patient or public involvement.

Indexed as

Attitude of Health PersonnelDigital TechnologyNursesPerceptionAdultFemaleHumansInterviews as TopicMaleMiddle AgedQualitative Researchdigital technologynursing; perceptionqualitative research

Identifiers

PMID41422528
PMCPMC12718622

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.