An educational programme for primary healthcare providers improved functional ability in older people living in the community
Bibliographic record
Abstract
Vass M, Avlund K, Lauridsen J, et al . Feasible model for prevention of functional decline in older people: municipality-randomized, controlled trial. J Am Geriatr Soc 2005;53:563–8.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Does an educational programme for healthcare providers in routine primary care improve functional ability and reduce nursing home admissions and mortality in older people? ### ![Graphic][5]</img>Design: randomised controlled trial. ### ![Graphic][6]</img>Allocation: {concealed}.* ### ![Graphic][7]</img>Blinding: unblinded. ### ![Graphic][8]</img>Follow up period: 3 years. ### ![Graphic][9]</img>Setting: 34 municipalities in Denmark. ### ![Graphic][10]</img>Participants: 4060 people 75 and 80 years of age who were living at home. 2876 were 75 years of age, and 1184 were 80 years of age. ### ![Graphic][11]</img>Intervention: 17 municipalities (2104 people) were allocated to the intervention, which comprised education for all municipality health professionals who conducted routine preventive home visits to people >75 years of age and an introduction for all local general practitioners (GPs) to a short geriatric assessment programme. Twice each year, 2 key persons from each municipality were asked to promote training in the use and interpretation of a standard assessment tool. Visiting professionals were … [1]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bthe%2BAmerican%2BGeriatrics%2BSociety%26rft.stitle%253DJ%2BAm%2BGeriatr%2BSoc%26rft.aulast%253DVass%26rft.auinit1%253DM.%26rft.volume%253D53%26rft.issue%253D4%26rft.spage%253D563%26rft.epage%253D568%26rft.atitle%253DFeasible%2Bmodel%2Bfor%2Bprevention%2Bof%2Bfunctional%2Bdecline%2Bin%2Bolder%2Bpeople%253A%2Bmunicipality-randomized%252C%2Bcontrolled%2Btrial.%26rft_id%253Dinfo%253Adoi%252F10.1111%252Fj.1532-5415.2005.53201.x%26rft_id%253Dinfo%253Apmid%252F15816999%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1111/j.1532-5415.2005.53201.x&link_type=DOI [3]: /lookup/external-ref?access_num=15816999&link_type=MED&atom=%2Febnurs%2F8%2F4%2F122.atom [4]: /lookup/external-ref?access_num=000227899200001&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.gif [11]: /embed/inline-graphic-7.gif
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".