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Determinants of nurse manager job satisfaction: A systematic review

2021· review· en· W3131054037 on OpenAlexaff
Tatiana Penconek, Kaitlyn Tate, Andréa Bernardes, Sarah Lee, Simone P.M. Micaroni, Alexandre Pazetto Balsanelli, André Almeida de Moura, Greta G. Cummings

Bibliographic record

VenueInternational Journal of Nursing Studies · 2021
Typereview
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCINAHLJob satisfactionNursingAutonomyPsychologyJob designJob attitudePersonnel psychologyMEDLINEJob performanceMedicineApplied psychologyPsychological interventionSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Front-line nurse managers provide direct oversight of healthcare delivery to ensure organizational expectations are implemented to achieve optimal patient and staff outcomes. Ensuring the job satisfaction of front-line nurse managers is key to retaining these individuals in their roles. Understanding factors influencing job satisfaction of nurse managers can support the development and implementation of strategies to enhance job satisfaction and sustain retention. OBJECTIVES: We aimed to systematically review the empirical literature measuring determinants of job satisfaction among nurse managers. DESIGN: We conducted a systematic review using 11 electronic databases. DATA SOURCES: Electronic databases included ABI Inform, Academic Search Premier, CINAHL, EMBASE, ERIC, Health Source Nursing, Medline, ProQuest Dissertations and Theses, PsychINFO, and LILACS. REVIEW METHODS: We included research articles that examined the determinants of job satisfaction for front-line nurse managers. Two research team members independently reviewed and determined inclusion of each study. Each study was appraised independently for quality by two team members. Data extraction was completed for included studies. Content analysis was used to categorize factors associated with job satisfaction of nurse managers. RESULTS: A total of 5608 articles were screened for inclusion or exclusion. Thirty-eight studies were included. One hundred and one factors influencing nurse manager job satisfaction were reported in the included studies. Factors were grouped into three main categories: job characteristics, organizational characteristics, and personal characteristics. Most factors were examined in single studies or their relationship with job satisfaction was equivocal. However, across these categories, findings included significant positive relationships between autonomy, power, social support among team members and job satisfaction of front-line nurse managers. A significant negative relationship between job stress and nurse manager job satisfaction was indicated in the findings. CONCLUSIONS: Promoting autonomy, power to make decisions for change, social support, team cohesion, and strategies to reduce job stress may improve job satisfaction of front-line nurse managers. Innovative solutions such as co-management and targeted administrative and electronic resources warrant further investigation. Promoting prosocial group behaviours, team building, coaching and the implementation of wellness programs may improve social support, team cohesion, and wellbeing. Examining factors of nurse managers job satisfaction beyond the acute care setting could provide further insights into the role that the practice environment plays in nurse manager job satisfaction. TWEETABLE ABSTRACT: Promoting autonomy, power to effect decisions for change, social support, team cohesion, and strategies to reduce job stress are important drivers of job satisfaction of front-line managers.

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)0.008
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0070.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.101
GPT teacher head0.483
Teacher spread0.382 · 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 designSystematic review
Domainnot available
GenreReview

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".

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Citations177
Published2021
Admission routes1
Has abstractno

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