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Record W6930619966 · doi:10.5281/zenodo.14832203

EFFECT OF PSYCHOLOGICAL CAPITAL EDUCATIONAL PROGRAM ON WORK ENGAGEMENT AMONG STAFF NURSES

2025· article· en· W6930619966 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCapital (architecture)Work engagementQuarter (Canadian coin)Employee engagementWork (physics)Construct (python library)Educational programSample (material)

Abstract

fetched live from OpenAlex

Abstract Background, Psychological Capital is seen as a core concept in the positive organizational behavior (POB) Psychological capital is considered an important composite construct that can help in addressing human capital issues in organizations. According to, Psy Cap places emphasis on the positive nature and strengths of an employee and the role that he or she has in stimulating levels of grow. Nurses need to educated psychological capital to improve work engagement levels which has a significant impact on patients and organization’ outcomes. This study aims to assessing the effect of educational program regarding psychological capital on work engagement. Design: A quasi-experimental study design was used. Setting: The study was conducted at5 critical care units. In Ain Shams specialized hospital that affiliated to Ain Shams University hospitals? The sample included 129 nurses out of 190who working in above mentioned setting Tools for data collection three tools were used for data collection, namely: Psychological capital Knowledge questionnaire, psychological capital questionnaire, Work engagement questionnaire. Results: more than two third (53.5%) of studied nurses were in the age group <40 years. slightly more than three quarter (88.4%) of studied nurses were female and slightly more than half (51.9%) had diploma. Additionally, slightly more than third (39.6%) were years of experience <20 years. slightly less than half (49.6%) of nurse’s knowledge about psychological capital. It marked improvement of nurse knowledge of psychological capital (76.7%) in post program phase. While minimal decreasing was occurred (71.3%) in follow up phase of program but still more than the preprogram phase. more than three quarter of nurses had satisfactory level of psychological capital (77.5%) before the program. which improved to (81.4%) at the post program phase. And to slightly decrease throughout the follow up phase to reach (79.8%). there was improvement of levels regarding psychological capital about nurses in post and follow up program than preprogram... three quarter of nurses had satisfactory level of work engagement (75.9%) before the program. which improved to (82.9%) at the post program phase. There was statistically significant relation throughout program phases, with p-value (p<0.05). Conclusion: the study results concluded that the staff nurses in the study settings have generally low level of psychological capital knowledge, while their work engagement is slightly high. The training program is effective in improving their psychological capital and consequently increasing their work engagement. Finally, there was a positive effect of psychological capital tanning program on enhancing work engagement among staff nurses. Recommendations: Create positive psychological capital dynamic which plays an active role in boosting nurses’ levels of work engagement. It is obvious that nurses with high self-efficiency, hopeful, resistant to adverse conditions and optimistic will contribute more to the organization engagement.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.382
Teacher spread0.345 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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