MétaCan
Menu
Back to cohort
Record W4389742089 · doi:10.1111/jnu.12950

A longitudinal investigation of structural empowerment profiles among healthcare employees

2023· article· en· W4389742089 on OpenAlexaff
Baptiste Cougot, Nicolas Gillet, Alexandre J. S. Morin, Jules Gauvin, Florian Ollierou, L. Moret, Dominique Tripodi

Bibliographic record

VenueJournal of Nursing Scholarship · 2023
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsConcordia University
Fundersnot available
KeywordsEmpowermentHealth careAffect (linguistics)PsychologyNormativeNursingSocial psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

PURPOSE: Research on structural empowerment has typically adopted a variable-centered perspective, which is not ideal to study the combined effects of structural empowerment components. This person-centered investigation aims to enhance our knowledge about the configurations, or profiles, of healthcare employees' perceptions of the structural empowerment dimensions present in their workplace (opportunity, information, support, and resources). Furthermore, this study considers the replicability and stability of these profiles over a period of 2 years, and their outcomes (perceived quality of care, and positive and negative affect). DESIGN: Participants completed the same self-reported questionnaires twice, 2 years apart. METHODS: A sample of 633 healthcare employees (including a majority of nurses and nursing assistants) participated. Latent transition analyses were performed. RESULTS: Five profiles were identified: Low Empowerment, High Information, Normative, Moderately High Empowerment, and High Empowerment. Membership into the Normative and Moderately High Empowerment profiles demonstrated a high level of stability over time (79.1% to 83.2%). Membership in the other profiles was either moderately stable (43.5% for the High Empowerment profile) or relatively unstable (19.7% to 20.4% for the Low Empowerment and High Information profiles) over time. More desirable outcomes (i.e., higher positive affect and quality of care, and lower negative affect) were observed in the High Empowerment profile. CONCLUSIONS: These results highlight the benefits of high structural empowerment, in line with prior studies suggesting that structural empowerment can act as a strong organizational resource capable of enhancing the functioning of healthcare professionals. These findings additionally demonstrate that profiles characterized by the highest or lowest levels of structural empowerment were less stable over time than those characterized by more moderate levels. CLINICAL RELEVANCE: From an intervention perspective, organizations and managers should pay special attention to employees perceiving low levels of structural empowerment, as they experience the worst outcomes. In addition, they should try to maintain high levels of structural empowerment within the High Empowerment profile, as this profile is associated with the most desirable consequences. Such attention should be fruitful, considering the instability of the High Empowerment and Low Empowerment profiles over time. REGISTRATION: NCT04010773 on ClinicalTrials.gov (4 July, 2019).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.380
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing ScholarshipSame topicNursing education and managementFrench-language works237,207