Evidence map›Paper›PMID 34631995›Full record

ArticleInternational journal of nursing sciences2021

Second-order problem solving: Nurses' perspectives on learning from near misses.

Yi Yang, Huaping Liu, Gwen D Sherwood

Abstract read
In one paragraph

Article in International journal of nursing sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

3 authors.

Yi YangPeking Union Medical College, School of Nursing, China.
Huaping LiuPeking Union Medical College, School of Nursing, China.
Gwen D SherwoodThe University of North Carolina at Chapel Hill, School of Nursing, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesNear misses happen more frequently than actual errors, and highlight system vulnerabilities without causing any harm, thus provide a safe space for organizational learning. Second-order problem solving behavior offers a new perspective to better understand how nurses promote learning from near misses to improve organizational outcomes. This study aimed to explore frontline nurses' perspectives on using second-order problem solving behavior in learning from near misses to improve patient safety.

methodsA qualitative exploratory study design was employed. This study was conducted in three tertiary hospitals in east China from June to November 2015. Purposive sampling was used to recruit 19 frontline nurses. Semi-structured interviews and a qualitative directed content analysis was undertaken using Crossan's 4I Framework of Organizational Learning as a coding framework.

resultsSecond-order problem solving behavior, based on the 4I Framework of Organizational Learning, was referred to as being a leader in exposing near misses, pushing forward the cause analysis within limited capacity, balancing the active and passive role during improvement project, and promoting the continuous improvement with passion while feeling low-powered.

conclusions4I Framework of Organizational Learning can be an underlying guide to enrich frontline nurses' role in promoting organizations to learn from near misses. In this study, nurses displayed their pivotal role in organizational learning from near misses by using second-order problem solving. However, additional knowledge, skills, and support are needed to maximize the application of second-order problem solving behavior when near misses are recognized.

Indexed as

4I framework of organizational learningNear missesNursesNurse’s rolePatient safetyProblem solvingTertiary care centers

Identifiers

PMID34631995
PMCPMC8488812

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.