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Record W4399122909 · doi:10.1186/s12889-024-18677-6

Work & life stress experienced by professional workers during the pandemic: a gender-based analysis

2024· article· en· W4399122909 on OpenAlexafffundabout
Melissa Corrente, Jungwee Park, Henrietta Akuamoah-Boateng, Jelena Atanackovic, Ivy Lynn Bourgeault

Bibliographic record

VenueBMC Public Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsStatistics CanadaWilfrid Laurier UniversityUniversity of Ottawa
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsStressorMental healthMedicineBiostatisticsPandemicPublic healthPromotion (chess)Work (physics)GerontologyOccupational stressEnvironmental healthNursingPsychiatryCoronavirus disease 2019 (COVID-19)Clinical psychologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The COVID-19 pandemic impacted work and home life exacerbating pre-existing stressors and introducing new ones. These impacts were notably gendered. In this paper, we explore the different work and home life related stressors of professional workers specifically as a result of the COVID-19 pandemic through the gender-based analysis of two pan Canadian surveys: The Canadian Community Health Survey (2019, 2020, 2021) and the Healthy Professional Worker Survey (2021). Analyses revealed high rates of work stress among professional workers compared to other workers and this was particularly notable for women. Work overload emerged as the most frequently selected source of work stress, followed by digital stress, poor work relations, and uncertainty. Similar trends were noted in life stress among professional workers, particularly women. Time pressure consistently stood out as the primary source of non-work stress, caring for children and physical and mental health conditions. These findings can help to develop more targeted and appropriate workplace mental health promotion initiatives that are applicable to professional workers taking gender more fully into consideration.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.108
GPT teacher head0.391
Teacher spread0.283 · 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.

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

Citations19
Published2024
Admission routes3
Has abstractyes

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