Meaning creation and employee engagement in home health caregivers
Bibliographic record
Abstract
The purpose of this study is to contribute to an understanding on how home health caregivers experience engagement in their work, and specifically, how aspects of home healthcare work create meaning associated with employee engagement. Although much research on engagement has been conducted, little has addressed how individual differences such as worker orientation influence engagement, or how engagement is experienced within a caregiving context. The study is based on a qualitative study in two home homecare organisations in Denmark using a think-aloud data technique, interviews and observations. The analysis suggests caregivers experience meaning in three relatively distinct ways, depending on their work orientation. Specifically, the nature of engagement varies across caregivers oriented towards being ‘nurturers’, ‘professionals’, or ‘workers’, and the sources of engagement differ for each of these types of caregivers. The article contributes by (i) advancing our theoretical understanding of employee engagement by emphasising meaning creation and (ii) identifying factors that influence meaning creation and engagement of home health caregivers, which should consequently affect the quality of services provided home healthcare patients.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".