Evidence map›Paper›PMID 36767021›Full record

ReviewHealthcare (Basel, Switzerland)2023

Positioning Technostress in the JD-R Model Perspective: A Systematic Literature Review.

Martina Pansini, Ilaria Buonomo, Clara De Vincenzi, Bruna Ferrara, Paula Benevene

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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

5 authors.

Martina PansiniDepartment of Human Sciences, LUMSA University, 00193 Rome, Italy.ORCID 0000-0001-8207-7754
Ilaria BuonomoDepartment of Human Sciences, LUMSA University, 00193 Rome, Italy.ORCID 0000-0001-8212-6798
Clara De VincenziDepartment of Human Sciences, LUMSA University, 00193 Rome, Italy.ORCID 0000-0001-6854-5750
Bruna FerraraDepartment of Human Sciences, LUMSA University, 00193 Rome, Italy.
Paula BeneveneDepartment of Human Sciences, LUMSA University, 00193 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to describe the effects of Technostress on employees' well-being and productivity. We adopted the Job Demands Resources Model as a theoretical framework to analyze the "Technostress" phenomenon in order to clarify whether and how technology can be considered a job demand, a job resource, or part of the effects of personal resources in the workplace. The sources search and selection process was conducted according to the PRISMA guidelines and regarded papers published from 2010 to 2022. Overall, the findings show that most selected papers consider ICT a job demand negatively affecting human behavior, thoughts, and attitudes. In contrast, some report that ICT acts as a job resource, thus reducing the impact of job demands and their physiological and psychological costs. Finally, a third category of studies does not consider the effects of ICT itself but gives more space to the interaction among ICT, the organizational context in which it is used, and the personal characteristics of ICT users. More specifically, the findings show how individual features and organizational procedures can shape the interpretations employees make about their ICT-related experiences at work and, consequently, their performance or well-being. Findings suggest that when ICT tools are strategically planned and used within organizations, they can enrich the employee experience at work, positively affecting the individual and the organizational level.

Indexed as

ICT usejob demandstechnostresswell-being promotion strategiesworkplace healthwork-related stress

Identifiers

PMID36767021
PMCPMC9914396

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.