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COVID-19 Pandemic and Work-Life Balance, Work-Family Conflict, Employee Burnout

2022· article· en· W4286623847 on OpenAlexaff
Afaf Khalid, Usman Raja, Muhammad Abdur Rahman Malik, Sadia Jahanzeb

Bibliographic record

VenueAcademy of Management Proceedings · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsBrock University
Fundersnot available
KeywordsBurnoutWork–life balanceWork–family conflictWork (physics)PandemicPsychologyBalance (ability)Personal lifeFamily lifeSocial psychologyCoronavirus disease 2019 (COVID-19)MedicineClinical psychologyPolitical scienceSociologySocioeconomics

Abstract

fetched live from OpenAlex

Despite the extent of working from home during the COVID pandemic, research exploring its positive or negative effects is exceptionally scarce. Unlike the traditional positive view of working from home, we hypothesize that working from home during the COVID pandemic has triggered work-life imbalance and work-family conflict for employees. Furthermore, we suggest that work-life imbalance and work-family conflict elicit burnout in employees. Using a time-lagged design, we collected data in three waves during the peak of the first wave of the COVID-19 pandemic to test our hypotheses. Overall, we found good support for the proposed hypotheses. Working from home had a significant positive relationship with burnout. Working from home was negatively related to work-life balance and positively related to work-family conflict. Both work-life balance and work-family conflict mediated the effects of working from home on burnout. These results significantly contribute to the research on working from home and burnout and present important implications for practice and future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.065
GPT teacher head0.325
Teacher spread0.260 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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