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Record W4413781122 · doi:10.1371/journal.pone.0330594

Unraveling the after-hours dilemma: Consequences of overworking among teleworkers—A scoping review protocol

2025· article· en· W4413781122 on OpenAlexaff
Bao-Zhu Stephanie Long, Kishana Balakrishnar, Luke Anthony Fiorini, Aaron Howe, Ali Bani‐Fatemi, Basem Gohar, Behdin Nowrouzi‐Kia

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCentre for Addiction and Mental HealthUniversity Health NetworkUniversity of GuelphLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsDilemmaProtocol (science)MedicineMathematicsAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Telework, also referred to as telecommuting, remote work, flexible work, and virtual work, involves working from a location different from the traditional office and often uses online communication technologies. Despite the numerous advantages associated with teleworking, it also raises concerns about work-life balance and health implications due to working after hours (WAH). OBJECTIVE: This proposed study aims to understand the health consequences of teleworkers working beyond their scheduled hours. METHODS: This review will search seven online databases (APA PsycINFO, Medline, Embase, Scopus, Business Source Premier, CINAHL, and Sociological Abstracts) to gather relevant articles. The inclusion criteria will encompass peer-reviewed studies published from 2010 onwards, focusing on WAH among teleworkers and reporting mental and physical health consequences. The exclusion criteria will include non-peer-reviewed articles, grey literature, and studies involving patients with pre-existing conditions. DISCUSSION: This review will provide valuable insights into the mental and physical health consequences of WAH among teleworkers, underscoring the urgent need for strategies to mitigate these risks and promote overall well-being. Future efforts, including collaborations between researchers, industry leaders, and policymakers, can guide the development of targeted interventions and evidence-based policies that improve telework environments and support long-term worker health and productivity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.341
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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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