Evidence map›Paper›PMID 35574293›Full record

ArticleJournal of multidisciplinary healthcare2022

Novel Approach to the Actions for Causes Elimination of Staff Resistance to Innovative Change.

Rolandas Drejeris, Egle Drejeriene

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

2 authors.

Rolandas DrejerisFaculty of Bioeconomy Development, Vytautas Magnus University, Kaunas, Lithuania.ORCID 0000-0002-8104-363X
Egle DrejerieneMedicine Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Commonly, employees' resistance to innovation is one of the main barriers to innovative change and one of the negative stimuli of employment relationships in the health-care institutions. Identifying the reasons of resistance is a topical issue for every organization, as the speed of change always affect their competitiveness. Aim of the study is to develop a methodology, which would facilitate the choice of an appropriate strategy necessary to enable the health-care organizations to eliminate or at least to reduce resistance to often essential innovative changes. Methods: The model was formed on the basis of the empirical research as a result of voluntary survey. The new approach manifests itself in original solutions by applying the method of quantitative modeling. This method is designed to calculate the strength of the resistance impact to innovation. A total of 217 employees were interviewed in two of the most innovative public Lithuanian primary health-care clinics (Vilnius and Kaunas university clinics). Results: Using a mathematical approach, the causes of change resistance were ranked and the suggested respective strategies were represented graphically and expressed in the form of a model. Its use will enhance the innovation capacity of the organization by avoiding or mitigating staff resistance. Conclusion: Based on aggregate information from numerous sources, the article pinpoints the causes and briefly reviews possible ways to eliminate resistance to innovation. Suggested methodology is based on quantitative modeling method. Such use of modeling methodology can help the administrators of health-care institutions to eliminate causes of staff resistance for change, and such circumstances will accelerate innovation development. The article reviews the strategies for resistance elimination and assigns them to each specific cause.

Indexed as

employment relationshipinnovationorganizational climateresistancestaff behaviorstrategy

Identifiers

PMID35574293
PMCPMC9091473

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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.