Use of home care services by older Veterans and dependants in Melbourne, Australia, 2007-2016
Bibliographic record
Abstract
Introduction: Military life may have a lasting effect on Veterans and their dependants, resulting in a different aging experience than among the general population. This study investigated the home care utilization of older community-living individuals supported by the Australian Department of Veterans' Affairs (DVA). Methods: This was a retrospective cohort study covering 10 years of data (Jan. 1, 2007-Dec. 31, 2016) on episodes of care provided by a home care organization. Veterans and dependants were compared with age- and gender-matched non-DVA-supported clients. Descriptive statistics and generalized linear mixed-effects modelling were used to characterize home care requirements. Results: Of 26,093 episodes, 45.3% involved Veterans (91.7% male) and 54.7% involved dependants (99.6% female). The median hours of care per episode for Veterans and dependants were 60% and 62% more, respectively, than for non-DVA-supported individuals. Veterans and dependants were 3.3 and 3.8 times more likely, respectively, to utilize assistance with personal care. After adjusting for confounding, Veterans and dependants were associated with 16% and 14% more hours of home care per episode, respectively. Cognitive dysfunction and complex care requirements increased the hours of care by, on average, 17% and 52%, respectively. Compared with episodes involving non-DVA-supported clients, episodes with Veterans and dependants were 35% more likely to result in a transfer to hospital. Discussion: Veterans and dependants used more home care assistance to live in the community than their non-DVA-supported compatriots. Appropriate and adequate health and welfare services need to be developed for this unique group to support well-being into later life.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".