The relationship between psychological need satisfaction, job affective wellbeing and work uncertainty among the academic nursing educators
Bibliographic record
Abstract
Background : The growing recognition of the connection between employees' wellbeing, working conditions, satisfaction and productivity has increased the requirement for understanding the need for a culture of health, wellbeing and certainty in the workplace. Self-Determination Theory (SDT) posits innate universal psychological needs for autonomy, competence, and relatedness, which imply work climates allowing satisfaction of these needs facilitate work engagement and psychological wellbeing as well as promoting motivation and wellbeing in the work place. Purpose: This research study aims to continue this trend by investigating the relationship between psychological need satisfaction, job affective wellbeing and uncertainty at work among academic nursing educators at the Faculty of Nursing, Alexandria University. Methods : A descriptive correlational design was used. All academic nursing educators who were available and willing to participate at the time of data collection were included (N = 169). Basic Psychological Need Satisfaction at work, Job-Related Affective Wellbeing Scale (JAWS), Personal and Work environment uncertainty scales were used to measure the study variables. Results : The main finding of the study reveals perception of psychological need satisfaction among academic nursing educators is significantly related, and could lead to, higher feeling of job-related affective wellbeing, consequently increasing their tolerance of uncertainty at personal as well as work situations ( p < .05). Conclusions and recommendation : A positive and supportive work environment promoting employees’ sharing, learning, autonomy, competence, belonging or relatedness and staff interaction should be supported by organizations. Also, identifying organizational obstacles to embracing uncertainty through a training program focuses on building employee uncertainty management skills and, how to use their resources to improve their uncertainty management practices are essential.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".