Hope, self‐efficacy, spiritual well‐being and job satisfaction
Bibliographic record
Abstract
TITLE: Hope, self-efficacy, spiritual well-being and job satisfaction. AIM: This paper is a report of a study of the relations of spiritual well-being, global job satisfaction, and general self-efficacy to hope in Continuing Care Assistants. BACKGROUND: Healthcare providers have described their hope as an important part of their work and a form of work motivation. Hope may be an important factor in preventing burnout and improving job satisfaction. METHODS: A concurrent triangulation mixed method design was used. Sixty-four Continuing Care Assistants (personal care aides) who registered for a 'Living with Hope' Conference completed a demographic form, Herth Hope Index, Global Job Satisfaction Questionnaire, Spiritual Well-Being Scale, General Self-Efficacy Scale, and a hope questionnaire. Data were collected in 2007. The response rate was 58%. RESULTS: Using linear regression, 29.9% of the variance in Herth Hope Index score was accounted for by scores from the General Self-Efficacy Scale and Spiritual Well-Being Scale. General Self-efficacy scores (positive relationship) and Spiritual Well-Being scores (negative relationship) accounted for a significant part of the variance. Qualitative data supported all findings, with the exception of the negative relationship between hope and spiritual well-being; participants wrote that faith, relationships, helping others and positive thinking helped them to have hope. They also wrote that hope had a positive influence on their job satisfaction and performance. CONCLUSION: Hope is an important concept in the work life of Continuing Care Assistants. Supportive relationships, adequate resources, encouragement by others, and improving perceptions of self-efficacy (ability to achieve goals in their workplace) may foster their hope.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".