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Record W2566803454 · doi:10.1037/ocp0000063

Promoting personal resources and reducing exhaustion through positive work reflection among caregivers.

2016· article· en· W2566803454 on OpenAlexaff
Elisa Clauß, Annekatrin Hoppe, Deirdre O’Shea, Marangelie Morales, Anna Steidle, Alexandra Michel

Bibliographic record

VenueJournal of Occupational Health Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOptimismIntervention (counseling)PsycINFOPsychologyEmotional exhaustionWell-beingClinical psychologyBurnoutMEDLINEPsychiatrySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

The aim of this study was to test the effects of a daily positive work reflection intervention on fostering personal resources (i.e., hope and optimism) and decreasing exhaustion (i.e., emotional exhaustion and fatigue) among caregivers for the elderly and caregivers who provide services at patients' homes. Using an intervention/waitlist control group design, 46 caregivers in an intervention group were compared with 44 caregivers in a control group at 3 points of measurement: pre-intervention, post-intervention, and at a 2-week follow-up. The results show that emotional exhaustion and fatigue were reduced for the intervention group. Primarily, caregivers with a high need for recovery at baseline benefited from the intervention. The results reveal no intervention effects for personal resources; however, they reveal a trend that the intervention led to an increase in hope and optimism among caregivers with a high need for recovery. Overall, the findings show that caregivers benefit from a daily positive work reflection intervention, particularly when their baseline levels of resources and well-being are low. (PsycINFO Database Record

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)0.002
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 score0.313
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.110
GPT teacher head0.484
Teacher spread0.374 · 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

Citations74
Published2016
Admission routes1
Has abstractyes

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