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Meta-Analysis: Effects of Workload and Work Environment on Work Satisfaction in Health Personnel

2023· article· en· W4387816727 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Health Policy and Management · 2023
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsnot available
Fundersnot available
KeywordsWorkloadJob satisfactionWork (physics)MedicinePsychologyJob designNursingWork environmentEnvironmental healthApplied psychologyJob performanceSocial psychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Background: Job satisfaction is one of the important points to motivate and improve work efficiency, high job satisfaction can improve the performance of health workers and patient satisfaction. However, low job satisfaction results in fatigue and a tendency to increase the turnover of health workers which will exacerbate the condition of health facilities. The research objective was to analyze the effect of workload and work environment on job satisfaction in health workers. Subjects and Method: This study is a meta-analysis with PICO. Population: health workers. Intervention: high workload and safe work environment. Comparison: low workload and unsafe work environment. Outcome: job satisfaction. The articles used in this study were obtained from three databases namely Google Scholar, Science Direct and Pubmed. The keywords used to search for articles are “Workload” OR “Job Overload” AND “Safe Work Environment” AND “Job Satisfaction” AND “Health Workers” AND “Multivariate”. The articles used were full text in English from 2012 to 2022. Articles were selected using the PRISMA flowchart and analyzed using the RevMan 5.3 application. Results: A total of 17 cross-sectional study articles from Ethiopia, Switzerland, Israel, Belgium, China, Canada and Denmark. Based on the analysis, health workers with high workloads reduced job satisfaction 0.47 times compared to health workers with low workloads and this was statistically significant (aOR=0.47; 95% CI=0.24 to 0.92; p=0.030). Health workers with a safe work environment increased job satisfaction 2.75 times compared to health workers with an unsafe work environment and this was statistically significant (aOR=2.75; 95% CI=1.59 to 4.78; p=0.003). Conclusion: High workload reduces job satisfaction in health personnel and a safe work environment increases job satisfaction in health personnel. Keywords: workload, work environment, job satisfaction

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.

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)0.005
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.726
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.127
GPT teacher head0.443
Teacher spread0.315 · 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