The emotional well-being of the nurse within the multi-skill setting
Bibliographic record
Abstract
The emotional well-being of nurses working in a multi-skill setting may be negatively influenced by their challenging work environment. A qualitative, explorative, descriptive and contextual study was conducted to investigate this phenomenon. The purpose of this study was to explore and describe the experience, as well as perceptions of coping mechanisms, of nurses working in the multi-skill setting, and to formulate recommendations to promote their emotional wellbeing. The population consisted of nurses working in a multi-skill setting (a Level-2 hospital)and included professional nurses, enrolled nurses and nurse assistants. An all-inclusive sample was used. Semi-structured interviews were conducted with three professional nurses,six enrolled nurses and one nurse assistant. These interviews were analysed according to the method described by Creswell (2003:192). The findings indicated that nurses have positive as well as negative experiences of the multi-skill setup. They cope by means of prioritising tasks, faith, self-motivation and mutual support. They also made suggestions for the promotion of their emotional well-being, on personal as well as managerial levels. Recommendations for further research, nurse education and practice were formulated. Recommendations for practice include ‘on-the-spot’ in-service training, appropriate task allocation, clearly defined scope of practice, time for rest and debriefing, strengthened relationships with management, promotion of strengths and creating a support system.OpsommingDie emosionele welstand van verpleegkundiges werksaam in ‘n multivaardigheidsopset kan moontlik negatief beïnvloed word deur die uitdagende werksomgewing. ‘n Kwalitatiewe, verkennende, beskrywende en kontekstuele studie is uitgevoer om hierdie verskynsel te ondersoek. Die doel van hierdie studie was om die ervaring van verpleegkundiges, asook hul persepsies van hanteringsmeganismes, in ‘n multi-vaardigheidsopset te verken en beskryf, sowel as om aanbevelings vir die bevordering van hulle emosionele welstand te formuleer. Die populasie het bestaan uit verpleegkundiges werksaam in ‘n multivaardigheidsopset (‘n Vlak-2 hospitaal) en het professionele verpleegkundiges, ingeskrewe verpleegkundiges en verpleegassistente ingesluit. ‘n Alles-insluitende steekproef is gebruik. Semi-gestruktureerde onderhoude is met drie professionele verpleegkundiges, ses ingeskrewe verpleegkundiges en een verpleegassistent gevoer. Hierdie onderhoude is volgens die metode deur Creswell(2003:192) beskryf, geanaliseer. Die bevindinge het getoon dat verpleegkundiges positiewe sowel as negatiewe ervaringe van die multivaardigheidsopset het. Hulle gebruik taakprioritisering, geloof, selfmotivering en wedersydse ondersteuning as hanteringsmeganismes. Hulle het ook voorstelle gemaak vir die bevordering van hul emosionele welstand, op persoonlike sowel as bestuursvlak. Aanbevelings vir verdere navorsing, verpleegonderwys en die praktyk is geformuleer. Aanbevelings vir die praktyk sluit in ‘in-die-oomblik’ indiensopleiding,toepaslike taaktoewysing, duidelikheid oor bestek van praktyk, tyd vir rus en ontlading, verbeterde verhoudings met bestuur, bevordering van sterk karaktereienskappe en die skep van ‘n ondersteuningsnetwerk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".