German Version of the Inventory of Motivations for Hospice Palliative Care Volunteerism: Are There Gender Differences?
Bibliographic record
Abstract
The present study examined gender differences in motivations for volunteering for hospice using a German version of the Inventory of Motivations for Hospice Palliative Care Volunteerism (IMHPCV). The IMHPCV was translated into German and back-translated into English following the World Health Organization's guidelines for the translation and adaptation of instruments. In an online survey, 599 female and 127 male hospice volunteers from hospice organizations throughout Germany completed the translated version of the IMHPCV, the Scales of the Attitude Structure of Volunteers as well as questions pertaining to their volunteer experience. Based on an exploratory structural equation modeling approach, adequate model fit was found for the expected factor structure of the German version of the IMHPCV. The IMHPCV showed adequate internal consistency and construct validity. Both female and male hospice volunteers found altruistic motives and humanitarian concerns most influential in their decision to volunteer for hospice. Personal gain was least influential. Men rated self-promotion, civic responsibility, and leisure as more important than women. Analyses provided support for the use of the IMHPCV as a measurement tool to assess motivations to volunteer for hospice. Implications for recruitment and retention of hospice volunteers, in particular males, are given.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".