Evidence map›Paper›PMID 38022994›Full record

ArticleFrontiers in psychology2023

Mindfulness and technostress in the workplace: a qualitative approach.

Athina Ioannou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.3field-weighted citation impact, top 6% of its field
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

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

1 author at 1 institution in 1 country.

Athina IoannouSurrey Business School, University of Surrey, Guildford, United Kingdom.
University of Surrey · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Information Technology (IT) has been vastly characterized as a double-edged sword, offering significant benefits to individuals but at the same time bringing certain negative consequences, such as technostress. Technostress can severely affect individuals in the workplace, causing fatigue, loss of motivation, inability to concentrate, dissatisfaction at work and reduced productivity among others; thus significantly affecting individual well-being work as well as increasing costs for organisations. Recently, studies have shown the beneficial role of mindfulness in reducing technostress experiences of individuals; however, the evidence that exists until today is very limited, and mostly focused on evaluating the impact of mindfulness on technostress and its negative consequences. As the current research stands, at the moment it is relatively unknown how mindfulness affects the underlying mechanisms of technostress experiences of individuals. Through semi-structured interviews with 10 knowledge workers, the current study explores how mindfulness alleviates technostress within the workplace, by investigating the experiences of more mindful employees and learning from their practices. Findings offer a deeper insight into the relationship of mindfulness and technostress, revealing a toolkit of the underlying strategies that more mindful and IT mindful individuals deploy as well as their perceptions during technostress experiences at work thus shedding light on the path between mindfulness and technostress. The study contributes both to academia and practice, offering important implications to managers and practitioners that strive to improve employee well-being within organisations.

Indexed as

information technologymindfulnessorganisationtechnostressworkplace

Identifiers

PMID38022994
PMCPMC10679397
OpenAlexW4388623618

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.