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Record W4416284455 · doi:10.63329/av3nz12318

Occupational Stress in the Modern Workplace: A Systematic Review and Research Agenda (2010-2025)

2025· article· W4416284455 on OpenAlexaff
Haiqa Sharmeen, Moby Chaudhry

Bibliographic record

VenueScientific Societal & Behavioral Research Journal · 2025
Typearticle
Language
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsYorkville University
Fundersnot available
KeywordsOccupational stressAmbiguityStressorWorkloadPhenomenonAgile software developmentSystematic reviewRole conflict

Abstract

fetched live from OpenAlex

This study presents a systematic review of occupational stress literature from 2010 to 2025, analyzing 244 peer-reviewed articles to map the evolution of this critical field. The analysis reveals a significant paradigm shift: from conceptualizing stress as an individual-level psychological response to understanding it as a complex, multi-level phenomenon deeply embedded in organizational structures, leadership practices, and macroeconomic contexts. We identify the emergence of novel stressors linked to digitalization and global crises, while traditional drivers like workload and role ambiguity persist. Crucially, our findings delineate a cascading effect of occupational stress, establishing its robust connections to deteriorated mental well-being, impaired organizational commitment, suppressed innovative work behavior, and counterproductive knowledge dynamics. The review synthesizes evidence on the moderating role of leadership particularly ethical, authentic, and agile style as well as the mediating functions of psychological capital and team dynamics. We conclude by proposing an integrated framework and a detailed agenda for future research, emphasizing the need for cross-cultural, longitudinal, and intervention-focused studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0230.017
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.180
GPT teacher head0.460
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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