EFFECTS OF ORGANIZATIONAL VALUES ON JOB SATISFACTION BY HOME HEALTH AIDES: MULTILEVEL MODELING STUDY
Bibliographic record
Abstract
Maintaining person-centred care and quality of life in long-term care (LTC) homes is difficult, posing challenges to residents and staff alike.Part of the reason for this situation is the chronic lack of staff to offer the needed level of personalized care and interaction.This pilot study implemented and evaluated a person-centred volunteer program within LTC homes where residents can access university student volunteer support and engage in more meaningful activities.Trained students are matched to residents with whom they volunteer twice a week for three hours at a time, over 18 months.Students document their experiences through weekly online journals.Students, residents, powers of attorney/caregivers, and staff are invited to participate in focus groups to evaluate the functioning of the program.Minimum Data Set data are gathered every three months to examine the impact on resident functioning.Preliminary focus group data show many strengths of the program, including the shared belief that students and residents are empowered by one another, that students have the time to engage in activities the staff may be unable to, and that student visits act as respite for caregivers.Journal entries highlight the wide variety of activities initiated by the volunteers, the impact of the program on increased outings and the importance of being paired with volunteers who speak the resident's preferred language.Student volunteers offer a positive addition to the LTC environment.Implications for the implementation of a formal volunteer program between University students and LTC residents including lessons learned will be discussed.
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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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".