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Record W2883492390 · doi:10.1186/s12889-018-5778-x

Longitudinal association between psychological demands and burnout for employees experiencing a high versus a low degree of job resources

2018· article· en· W2883492390 on OpenAlexaff
Anna-Carin Fagerlind Ståhl, Christian Ståhl, Peter Smith

Bibliographic record

VenueBMC Public Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsInstitute for Work & HealthPublic Health OntarioUniversity of Toronto
FundersVINNOVA
KeywordsBurnoutWorkloadMedicineEmotional exhaustionLongitudinal studyOccupational burnoutJob satisfactionSick leaveClinical psychologyPsychologySocial psychologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Exhaustion and burnout are common causes for sickness absence. This study examines the relationship between psychological demands and burnout over time, and if environmental support modifies the longitudinal relationship between psychological demands and burnout at baseline, with burnout measured 2 years subsequently. METHODS: A questionnaire was sent to employees in seven Swedish organizations in 2010-2012 with follow-up after 2 years, n = 1722 responded (64%). Linear regressions were used to examine the associations between burnout and psychological demands at baseline and burnout at follow-up. Stratified regression models examined if relationships between burnout and psychological demands at baseline on burnout at follow-up differed for employees in supportive versus unsupportive work environments. RESULTS: Burnout and psychological demands at baseline were associated with burnout at follow-up, after adjustment for study covariates. No significant differences were observed between estimates for psychological demands and burnout among respondents in supportive work environments versus those in unsupportive work environments. CONCLUSIONS: This study shows that high demands are associated with greater risk of burnout, regardless of level of other work supports. This has implications for prevention of sick leave due to burnout and for rehabilitation, where demands such as work pace, workload and conflicting demands at work may need to be reduced.

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)0.005
metaresearch head score (Gemma)0.003
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.234
GPT teacher head0.478
Teacher spread0.244 · 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

Citations53
Published2018
Admission routes1
Has abstractyes

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