The prevalence of resilience in a group of professional nurses
Bibliographic record
Abstract
The literature and practice show that many professional nurses feel emotionally overloaded and are experiencing job dissatisfaction, which often results in them leaving the profession. Paradoxically, some nurses choose to remain in nursing and survive, cope and even thrive despite their unique workplace adversities. It is, however, not known what the prevalence of resilience amongst nurses is, and what influence working in private versus public contexts has on this resilience. The aims of this study were to determine the prevalence of resilience in a group of professional nurses, to determine whether private versus public contexts played a role in nurses’ resilience, and to obtain an indication of participants’ views of their profession and resilience therein. A cross-sectional survey design was used where professional nurses (N = 312) working in public and private hospitals in South Africa voluntarily completed measures of psycho-social well-being as indicators of their degree of resilience. They also answered three open-ended questions on their profession. Results showed moderate-tohigh correlations amongst scales, indicating conceptual coherence as indicators of resilience. Prevalence of resilience was determined by normalising the mean scores of the measuring instruments. The total value of the normalised mean scores was given as a fraction (0−1), representing a level of resilience manifested by the participants across all scales. This indicated three levels of resilience: 10% of participants manifested low resilience, 47% moderate resilience and 43% high resilience. Nurses in private health care had significantly (small practical effect) higher levels of resilience than nurses in public health care.OpsommingDie literatuur en praktyk dui daarop dat baie professionele verpleegkundiges emosioneel uitgeput is, werksontevredenheid ervaar en dikwels die beroep verlaat. Paradoksaal kies sommige verpleegkundiges om in die beroep te bly, en floreer selfs ten spyte van hul unieke en moeilike werksomstandighede. Dit is egter nie bekend wat die voorkoms van veerkragtigheid in verpleegkundiges is nie, of wat die invloed van werk in privaat versus die openbare omgewing op veerkragtigheid is nie. Die doelwitte van die studie was om die voorkoms van veerkragtigheid in ‘n groep professionele verpleegkundiges te bepaal, om die rol van privaat versus openbare omgewings in veerkragtigheid te bepaal, en om ‘n aanduiding van deelnemers se siening oor hul professie en veerkragtigheid daarin, te bekom. ‘n Dwarsdeursnit ontwerp was gebruik waarin professionele verpleegkundiges (N = 312) werksaam in openbare of privaat hospitale in Suid-Afrika vrywillig vraelyste oor psigososiale welstand as aanduiders van die vlak van veerkragtigheid, voltooi het. Hulle het ook drie oop-einde vrae oor hul beroep beantwoord. Bevindinge het op matige tot hoë korrelasies tussen skale gewys wat dui op konseptuele koherensie tussen die indikatore van veerkragtigheid. Veerkragtigheid is bereken deur normalisering van die gemiddelde tellings vir die meetinstrumente van al die skale. Die totale waarde van genormaliseerde gemiddeldes was as ‘n fraksie (0−1) uitgedruk. Drie vlakke van veerkragtigheid het gemanifesteer, 10% van die deelnemers het met lae veerkragtigheid gemanifesteer, 47% met matige veerkragtigheid en 43% met hoё veerkragtigheid. Verpleegkundiges in privaat gesondheidsorg het beduidende (klein praktiese waarde) hoёr vlakke van veerkragtigheid getoon as verpleegkundiges in openbare gesondheidsorg.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".