Bibliographic record
Abstract
PURPOSE: The concept behind constant observation is not new. Whilst traditionally performed by nursing staff, it is now commonly performed by sitters. Details surrounding the usage, job description, training, clinical and cost effectiveness of sitters are not known; hence the reason for this review. METHODS: A literature search was performed in MEDLINE, Cochrane Database of Systematic Reviews, and PubMed from the years 1960 to October 2011. The definition for sitter used in the articles was accepted for this review. RESULTS: From this review, it is evident that sitters are being employed in a variety of settings. The question of which type of person would provide the most benefit in the sitter role is still not clear; whilst sitters have typically included family and volunteers, it may be trained volunteers who may offer the most cost-effective solution. The paucity of information available regarding the training and assessments of sitters and the lack of formal guidelines regulating sitters' use results in a lack of information available regarding these sitters, and current available evidence is conflicting regarding the benefits in terms of cost and clinical outcome. The only strong evidence relating to clinical benefit comes from the use of fully-trained sitters as part of a multi-interventional program (i.e., HELP) CONCLUSIONS: Current evidence supports a role for the sitter as part of the management of patients with delirium. The most cost-effective sitter role appears to be trained volunteers. Further research is needed to determine the specific type of training required for the sitter role. The creation of a national set of regulations or guidelines would provide safeguards in the industry to ensure safe and effective patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".