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Record W2774184543 · doi:10.12735/ier.v5n1p13

Examining the Factors Impacting Academics’ Psychological Well-Being: A Review of Research

2017· review· en· W2774184543 on OpenAlexvenueno aff
Raheleh Salimzadeh, Alenoush Saroyan, Nathan C. Hall

Bibliographic record

VenueInternational Education Research · 2017
Typereview
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsWell-beingPsychologyPsychological well-beingApplied psychologySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Existing research suggests that academics are subjected to high levels of job-related stress. Numerous aspects of an academic career such as time constraint, work overload, work-life conflict, and emotional demands are stressful and trigger negative emotional responses. There is further evidence to suggest that job-related stress compromises physical and psychological well-being, and impairs productivity among academics. The purpose of the present paper was to review the empirical research on how work-related stress and experiences impact academics’ psychological well-being. Accordingly, a thorough review of the literature was conducted and 46 studies attending to aspects of psychological well-being were identified and analyzed. The literature was found to be fragmented. The review concludes that job-related stress and specific types of experiences adversely impact academics’ psychological well-being by making them vulnerable to psychological distress, negative emotions, depression, and burnout. Implications for improving psychological well-being among academics are addressed and directions for future research are proposed.

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)0.033
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0040.001

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 head0.828
GPT teacher head0.757
Teacher spread0.071 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations52
Published2017
Admission routes1
Has abstractyes

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