Relationship Between Clinical Nurse Specialist Role Implementation, Satisfaction, and Intent to Stay
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: There is a lack of research examining the relationship between role satisfaction and intent to remain in one's professional role from the perspective of nurses in advanced practice roles. The purpose of this study is to examine the strength of the relationship between clinical nurse specialist (CNS) role implementation, role satisfaction, and intent to remain in a CNS role. DESIGN: We conducted a secondary analysis of data from a cross-sectional survey. SETTING: The setting of this study was Canada. SAMPLE: We included 423 of 471 (90%) questionnaires of graduate-prepared CNSs. METHODS: We surveyed all CNSs in Canada from April to August 2011. Cronbach's α (.79-.96) was used to assess the reliability of the portion of the questionnaire that measured CNS role dimensions. Using logistic regression analysis, we examined the relationship between CNS role implementation, role satisfaction, and intent to stay. RESULTS: Clinical, research, scholarly and professional development, and consultation activities were significantly associated with improved CNS role satisfaction, and role satisfaction positively influenced intent to stay. However, CNS roles heavily focused on consultation activities negatively influenced CNS intent to stay. Only scholarly and professional development activities both improved role satisfaction and indirectly influenced intent to stay in the role. CONCLUSION/IMPLICATIONS: There is a small positive association between some CNS role dimensions and role satisfaction, and role satisfaction positively influences intent to stay. However, too many consultation activities decreased CNS intent to remain in the role. Given the multidimensional role of the CNS and unique patient needs, CNSs will want to work closely with their managers to design a role that meets patient needs and optimizes CNS satisfaction and intent to stay in the role. Further research is needed to understand if CNS role implementation influences CNS departures and the relationship between intending to leave and actual departures from a CNS role.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".