ArticleScientific reports2025
Protective factors against technostress in secondary school teachers.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Human-Machine Collaboration Depth and Teacher Burnout: A Dual-Path Moderated Mediation Model of Empowerment and Depletion.Behavioral sciences (Basel, Switzerland) · 2026Article
- Technostress, digital fatigue, and AI dependency as antecedents of burnout and SDG-4 achievement in EFL classrooms.Scientific reports · 2026Article
- Fear vs. temptation: a push-pull-mooring perspective on users' continuance intention toward AI face-swapping technology.Frontiers in psychology · 2026Article
- Digital literacy and creative teaching behavior among nursing educators: the chain mediating roles of self-efficacy and digital stress.Frontiers in psychology · 2026Article
- The ecological mechanism of digital technology integration: a comparative study of psychological and institutional support among university teachers in China and Kazakhstan.Frontiers in psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Reliance on innovative learning and teaching methodologies based on Information and Communication Technologies (ICTs) is continuously growing in educational institutions. However, using ICTs requires up-to-date knowledge, digital skills, and flexible adaptation to technological changes and challenges. These demands can lead teachers to experience technostress, undermining their ability to cope with emerging technologies and fully exploit their potential. This is particularly true for teachers who lack appropriate emotion regulation strategies and digital proficiency. In the present study, we investigated technostress creators among secondary school teachers, evaluating the predictive role of cognitive emotion regulation and the mediating role of self-efficacy in digital competencies. Notably, adaptive and maladaptive cognitive emotion regulation strategies were distinguished to clarify their distinct contributions to teachers' psychological experience of technostress creators. Mediation analyses highlighted a direct effect of maladaptive strategies on the experience of technostress creators, whereas adaptive strategies exerted an indirect effect through self-efficacy in digital competencies. Maladaptive emotion regulation was positively associated with higher levels of technostress creators, whereas adaptive emotion regulation was positively associated with self-efficacy in digital competencies. Self-efficacy in digital competencies, in turn, was negatively associated with the experience of technostress creators. These findings provide evidence for implementing not only emotion regulation-based but also digital self-efficacy-based interventions to mitigate teachers' technostress.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.