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Record W3118410348 · doi:10.1080/13803395.2020.1863340

Slower information processing speed is associated with persistent burnout symptoms but not depression symptoms in nursing workers

2021· article· en· W3118410348 on OpenAlexaff
Guy G. Potter, Daniel Hatch, Hannah Hagy, Thea Radüntz, Patrick D. Gajewski, Michael Falkenstein, Gabriele Freude

Bibliographic record

VenueJournal of Clinical and Experimental Neuropsychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsInstitute of Aging
FundersNational Institute on AgingFoundation for the National Institutes of Health
KeywordsBurnoutDepression (economics)CognitionPsychologyDistressClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Burnout and depression both occur with chronic work-related stress, and cognitive deficits have been found when symptom severity results in work disability. Less is known about cognitive deficits associated with milder symptoms among active workers, and few studies have examined whether cognitive deficits predict persistent burnout and depression symptoms. The goal of this study was to examine the association of information processing speed and executive function performance to burnout and depression symptoms at baseline and 12-month follow-up in a sample of actively working individuals (N = 372).Method: The design was prospective with laboratory cognitive data at baseline, and burnout and depressive symptoms assessed at baseline and monthly follow-ups. Information processing speed and executive functions were assessed in a task-switching paradigm, including single-task reaction time (RT), switching costs, and mixing costs. Burnout was assessed with the Exhaustion subscale of the Oldenburg Burnout Inventory and depression with the Patient Health Questionnaire-9.Results: Slower RT was modestly associated with higher levels of burnout symptoms both cross-sectionally and prospectively, but switching costs and mixing costs were not associated with burnout symptoms. None of the cognitive measures were associated with depression symptoms cross-sectionally or prospectively.Conclusions: Despite statistically significant findings of slowed RT in acute exhaustion-related burnout, the proportion of variance accounted for in the models was small and did not predict clinically significant levels of distress. The absence of statistically significant findings for depression symptoms suggests the cognitive profile associated with the exhaustion dimension of burnout may be distinct from that of depression, which reflects a more heterogeneous symptomatology. Our data suggest the clinical impact of burnout symptoms on actively working individuals is marginal; nonetheless, it is important to screen and intervene on burnout and depression symptoms in the workplace because they can lead to other forms of work impairment.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.060
GPT teacher head0.465
Teacher spread0.405 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2021
Admission routes1
Has abstractyes

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